├── .github
├── .gitignore
└── workflows
│ └── R-CMD-check.yaml
├── res_readme.fst
├── man
├── figures
│ ├── fst.png
│ ├── README-speed-bench-1.png
│ └── README-multi-threading-1.png
├── decompress_fst.Rd
├── hash_fst.Rd
├── compress_fst.Rd
├── metadata_fst.Rd
├── fst-package.Rd
├── fst.Rd
├── threads_fst.Rd
└── write_fst.Rd
├── inst
└── WORDLIST
├── tests
├── testthat
│ ├── keyedTable.rds
│ ├── datasets
│ │ ├── legacy.fst
│ │ ├── legacy.rds
│ │ ├── test-set.rds
│ │ ├── 0.9.8-0.9.18.fst
│ │ └── utf8.csv
│ ├── helper_fstwrite.R
│ ├── test_legacy.R
│ ├── test_bigvector.R
│ ├── test_nanotime.R
│ ├── test_rbind.R
│ ├── test_access.R
│ ├── test_interface.R
│ ├── test_keys.R
│ ├── test_special_tables.R
│ ├── test_lintr.R
│ ├── test_date.R
│ ├── test_integer64.R
│ ├── test_omp.R
│ ├── test_time.R
│ ├── test_encoding.R
│ ├── test_roundtrip.R
│ ├── test_factor.R
│ ├── test_compress.R
│ ├── test_meta.R
│ ├── test_fst_table.R
│ └── test_fst.R
└── testthat.R
├── _pkgdown.yml
├── .gitignore
├── .Rbuildignore
├── fst.Rproj
├── NAMESPACE
├── DESCRIPTION
├── R
├── RcppExports.R
├── onAttach.R
├── hash.R
├── package.R
├── type_dependencies.R
├── compress.R
├── openmp.R
├── fst.R
└── fst_table.R
├── src
├── openmp.cpp
├── fst_compress.cpp
├── flex_store.cpp
└── RcppExports.cpp
├── cran-comments.md
├── cran-checklist.md
├── CONTRIBUTING.md
├── CONDUCT.md
├── README.md
├── README.Rmd
├── NEWS.md
└── LICENSE
/.github/.gitignore:
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1 | *.html
2 |
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/res_readme.fst:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/res_readme.fst
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/man/figures/fst.png:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/man/figures/fst.png
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/inst/WORDLIST:
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1 | Collet
2 | fstlib
3 | Fstlib
4 | LZ
5 | multithreaded
6 | Yann
7 | ZSTD
8 |
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/tests/testthat/keyedTable.rds:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/tests/testthat/keyedTable.rds
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/_pkgdown.yml:
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1 | url: http://www.fstpackage.org
2 |
3 | template:
4 | params:
5 | bootswatch: cerulean
6 |
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/tests/testthat/datasets/legacy.fst:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/tests/testthat/datasets/legacy.fst
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/tests/testthat/datasets/legacy.rds:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/tests/testthat/datasets/legacy.rds
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/man/figures/README-speed-bench-1.png:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/man/figures/README-speed-bench-1.png
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/tests/testthat/datasets/test-set.rds:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/tests/testthat/datasets/test-set.rds
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/tests/testthat.R:
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1 |
2 | # required packages
3 | library(testthat)
4 | library(fst)
5 |
6 | # run tests
7 | test_check("fst")
8 |
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/man/figures/README-multi-threading-1.png:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/man/figures/README-multi-threading-1.png
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/tests/testthat/datasets/0.9.8-0.9.18.fst:
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https://raw.githubusercontent.com/fstpackage/fst/HEAD/tests/testthat/datasets/0.9.8-0.9.18.fst
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/.gitignore:
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1 | *.a
2 | *.dll
3 | *.dll
4 | *.fea
5 | *.fst
6 | *.gcov
7 | *.gz
8 | *.html
9 | *.o
10 | *.orig
11 | *.pdf
12 | *.rds
13 | *.Rhistory
14 | *.Rproj
15 | *.so
16 | *.txt
17 | *.zip
18 | .Rproj.user
19 | *.TMP
20 | /revdep/*
21 | /docs/*
22 | /src-i386/
23 |
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/.Rbuildignore:
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1 | ^\.github$
2 | ^.*\.Rproj$
3 | ^\.Rproj\.user$
4 | \.o$
5 | ^_pkgdown\.yml$
6 | ^CONDUCT\.md$
7 | \.dll$
8 | ^docs$
9 | \.a$
10 | \.Rmd$
11 | LZ4/LICENSE$
12 | \.md$
13 | ^docs$
14 | \.TMP$
15 | \.png$
16 | \.yml$
17 | ^dataset\.fst$
18 | ^res_readme\.fst$
19 | ^_pkgdown\.yml$
20 | ^CRAN-RELEASE$
21 | ^revdep$
22 | ^\.github$
23 | ^CRAN-SUBMISSION$
24 |
--------------------------------------------------------------------------------
/man/decompress_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/compress.R
3 | \name{decompress_fst}
4 | \alias{decompress_fst}
5 | \title{Decompress a raw vector with compressed data.}
6 | \usage{
7 | decompress_fst(x)
8 | }
9 | \arguments{
10 | \item{x}{raw vector with data previously compressed with \code{compress_fst}.}
11 | }
12 | \value{
13 | a raw vector with previously compressed data.
14 | }
15 | \description{
16 | Decompress a raw vector with compressed data.
17 | }
18 |
--------------------------------------------------------------------------------
/fst.Rproj:
--------------------------------------------------------------------------------
1 | Version: 1.0
2 |
3 | RestoreWorkspace: Default
4 | SaveWorkspace: Default
5 | AlwaysSaveHistory: Default
6 |
7 | EnableCodeIndexing: Yes
8 | UseSpacesForTab: Yes
9 | NumSpacesForTab: 2
10 | Encoding: ISO8859-1
11 |
12 | RnwWeave: knitr
13 | LaTeX: pdfLaTeX
14 |
15 | AutoAppendNewline: Yes
16 | StripTrailingWhitespace: Yes
17 |
18 | BuildType: Package
19 | PackageUseDevtools: Yes
20 | PackageInstallArgs: --no-multiarch --with-keep.source
21 | PackageCheckArgs: --use-valgrind --as-cran
22 | PackageRoxygenize: rd,collate,namespace
23 |
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/tests/testthat/helper_fstwrite.R:
--------------------------------------------------------------------------------
1 |
2 | # Convenience method to tests on different versions of the package
3 | # Not used in the CRAN release
4 | fstwriteproxy <- function(x, path, compress = 0, uniform_encoding = TRUE) {
5 | write_fst(x, path, compress, uniform_encoding) # use current version of fst package
6 | }
7 |
8 |
9 | fstreadproxy <- function(path, columns = NULL, from = 1, to = NULL, as_data_table = FALSE) {
10 | read_fst(path, columns, from, to, as_data_table)
11 | }
12 |
13 |
14 | fstmetaproxy <- function(path) {
15 | metadata_fst(path)
16 | }
17 |
--------------------------------------------------------------------------------
/tests/testthat/test_legacy.R:
--------------------------------------------------------------------------------
1 |
2 | context("legacy format")
3 |
4 |
5 | test_that("Read legacy format", {
6 | expect_error(
7 | dt <- read_fst("datasets/legacy.fst", old_format = TRUE),
8 | "Parameter old_format is depricated"
9 | )
10 |
11 | expect_error(
12 | metadata_fst("datasets/legacy.fst"),
13 | "File header information does not contain the fst format marker"
14 | )
15 | })
16 |
17 |
18 | test_that("0.9.8-0.9.18.fst", {
19 |
20 | # BigEndian systems will fail this test
21 | skip_on_cran()
22 | skip_on_ci()
23 |
24 | expect_equal(
25 | readRDS("datasets/test-set.rds"),
26 | read_fst("datasets/0.9.8-0.9.18.fst")
27 | )
28 | })
29 |
--------------------------------------------------------------------------------
/tests/testthat/test_bigvector.R:
--------------------------------------------------------------------------------
1 |
2 | context("big vectors")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 | # nolint start
13 | # # Sample data
14 | # x <- list(X = rep(1.1, 500000000))
15 | # setDT(x)
16 | # gc()
17 | #
18 | # require(microbenchmark)
19 | #
20 | # test_that("Read meta of sorted file",
21 | # {
22 | # microbenchmark(
23 | # write.fst(x, "testdata/big.fst"), times = 1)
24 | #
25 | # rm(x)
26 | # gc()
27 | #
28 | # microbenchmark(
29 | # y <- read.fst("testdata/big.fst", as.data.table = TRUE),
30 | # times = 1)
31 | #
32 | # rm(y)
33 | # gc()
34 | # })
35 | # nolint end
36 |
--------------------------------------------------------------------------------
/man/hash_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/hash.R
3 | \name{hash_fst}
4 | \alias{hash_fst}
5 | \title{Parallel calculation of the hash of a raw vector}
6 | \usage{
7 | hash_fst(x, seed = NULL, block_hash = TRUE)
8 | }
9 | \arguments{
10 | \item{x}{raw vector that you want to hash}
11 |
12 | \item{seed}{The seed value for the hashing algorithm. If NULL, a default seed will be used.}
13 |
14 | \item{block_hash}{If TRUE, a multi-threaded implementation of the 64-bit xxHash algorithm will
15 | be used. Note that block_hash = TRUE or block_hash = FALSE will result in different hash values.}
16 | }
17 | \value{
18 | hash value
19 | }
20 | \description{
21 | Parallel calculation of the hash of a raw vector
22 | }
23 |
--------------------------------------------------------------------------------
/tests/testthat/test_nanotime.R:
--------------------------------------------------------------------------------
1 |
2 | context("nanotime column")
3 |
4 |
5 | library(data.table)
6 |
7 |
8 | # Clean testdata directory
9 | if (!file.exists("testdata")) {
10 | dir.create("testdata")
11 | } else {
12 | file.remove(list.files("testdata", full.names = TRUE))
13 | }
14 |
15 |
16 | test_that("Cycle return the nanotime type", {
17 | skip_if_not(requireNamespace("nanotime", quietly = TRUE))
18 |
19 | # Prepare example
20 | dt_nanotime <- data.frame(
21 | Nano = nanotime::nanotime(Sys.Date() + 1:100)
22 | )
23 |
24 | expect_true(inherits(dt_nanotime$Nano, "nanotime"))
25 |
26 | # Write to fst
27 | fstwriteproxy(dt_nanotime, "testdata/dt_nanotime.fst")
28 | dt_nanotime_read <- fstreadproxy("testdata/dt_nanotime.fst")
29 |
30 | # nanotime type preserved:
31 | expect_true(inherits(dt_nanotime_read$Nano, "nanotime"))
32 |
33 | expect_identical(dt_nanotime, dt_nanotime_read)
34 | })
35 |
--------------------------------------------------------------------------------
/tests/testthat/datasets/utf8.csv:
--------------------------------------------------------------------------------
1 | Language;ICanEatGlass
2 | Old Irish (Ogham);᚛᚛ᚉᚑᚅᚔᚉᚉᚔᚋ ᚔᚈᚔ ᚍᚂᚐᚅᚑ ᚅᚔᚋᚌᚓᚅᚐ᚜
3 | Old Norse (Runes);ᛖᚴ ᚷᛖᛏ ᛖᛏᛁ ᚧ ᚷᛚᛖᚱ ᛘᚾ ᚦᛖᛋᛋ ᚨᚧ ᚡᛖ ᚱᚧᚨ ᛋᚨᚱ
4 | Georgian;მინას ვჭამ და არა მტკივა.
5 | Armenian;Կրնամ ապակի ուտել և ինծի անհանգիստ չըներ։
6 | Bangla / Bengali;আমি কাঁচ খেতে পারি, তাতে আমার কোনো ক্ষতি হয় না।
7 | Marathi;मी काच खाऊ शकतो, मला ते दुखत नाही.
8 | Kannada;ನನಗೆ ಹಾನಿ ಆಗದೆ, ನಾನು ಗಜನ್ನು ತಿನಬಹುದು
9 | Hindi;मैं काँच खा सकता हूँ और मुझे उससे कोई चोट नहीं पहुंचती.
10 | Malayalam;എനിക്ക് ഗ്ലാസ് തിന്നാം. അതെന്നെ വേദനിപ്പിക്കില്ല.
11 | Telugu;నేను గాజు తినగలను మరియు అలా చేసినా నాకు ఏమి ఇబ్బంది లేదు
12 | Sinhalese;මට වීදුරු කෑමට හැකියි. එයින් මට කිසි හානියක් සිදු නොවේ.
13 | Urdu(3);چ کھا سکتا ہوں اور مجھے تکلیف نہیں ہوتی ۔
14 | Pashto(3);زه شيشه خوړلې شم، هغه ما نه خوږوي
15 | Farsi / Persian(3;من می توانم بدونِ احساس درد شيشه بخورم
16 | Chinese (Traditional);我能吞下玻璃而不傷身體。
17 | Japanese;私はガラスを食べられます。それは私を傷つけません。
18 |
--------------------------------------------------------------------------------
/NAMESPACE:
--------------------------------------------------------------------------------
1 | # Generated by roxygen2: do not edit by hand
2 |
3 | S3method("$",fst_table)
4 | S3method("[",fst_table)
5 | S3method("[[",fst_table)
6 | S3method(as.data.frame,fst_table)
7 | S3method(as.list,fst_table)
8 | S3method(dim,fst_table)
9 | S3method(dimnames,fst_table)
10 | S3method(names,fst_table)
11 | S3method(print,fst_table)
12 | S3method(print,fstmetadata)
13 | S3method(row.names,fst_table)
14 | S3method(str,fst_table)
15 | export(compress_fst)
16 | export(decompress_fst)
17 | export(fst)
18 | export(fst.metadata)
19 | export(hash_fst)
20 | export(metadata_fst)
21 | export(read.fst)
22 | export(read_fst)
23 | export(threads_fst)
24 | export(write.fst)
25 | export(write_fst)
26 | import(Rcpp)
27 | importFrom(fstcore,threads_fstlib)
28 | importFrom(parallel,detectCores)
29 | importFrom(utils,capture.output)
30 | importFrom(utils,packageVersion)
31 | importFrom(utils,str)
32 | importFrom(utils,tail)
33 | useDynLib(fst, .registration = TRUE)
34 |
--------------------------------------------------------------------------------
/tests/testthat/test_rbind.R:
--------------------------------------------------------------------------------
1 |
2 | context("row binding")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testoutput")) {
7 | dir.create("testoutput")
8 | } else {
9 | file.remove(list.files("testoutput", full.names = TRUE))
10 | }
11 |
12 |
13 | char_vec <- function(nr_of_rows) {
14 | sapply(
15 | 1:nr_of_rows,
16 | function(x) {
17 | paste(sample(LETTERS, sample(1:4, 1)), collapse = "")
18 | }
19 | )
20 | }
21 |
22 | # Sample data
23 | nr_of_rows <- 10000L
24 | nr_of_levels <- 8
25 |
26 | char_na <- char_vec(nr_of_rows)
27 | char_na[sample(1:nr_of_rows, 10)] <- NA
28 | datatable <- data.frame(
29 | Xint = 1:nr_of_rows,
30 | Ylog = sample(c(TRUE, FALSE, NA), nr_of_rows, replace = TRUE),
31 | Zdoub = rnorm(nr_of_rows),
32 | Qchar = char_vec(nr_of_rows),
33 | WFact = factor(sample(char_vec(nr_of_levels), nr_of_rows, replace = TRUE)),
34 | char_na = char_na,
35 | stringsAsFactors = FALSE
36 | )
37 |
--------------------------------------------------------------------------------
/DESCRIPTION:
--------------------------------------------------------------------------------
1 | Package: fst
2 | Type: Package
3 | Title: Lightning Fast Serialization of Data Frames
4 | Description: Multithreaded serialization of compressed data frames using the 'fst' format. The
5 | 'fst' format allows for full random access of stored data and a wide range of compression
6 | settings using the LZ4 and ZSTD compressors.
7 | Version: 0.9.9
8 | Date: 2022-02-08
9 | Authors@R:
10 | person("Mark", "Klik", email = "markklik@gmail.com", role = c("aut", "cre", "cph"))
11 | Depends:
12 | R (>= 3.0.0)
13 | Imports:
14 | fstcore,
15 | Rcpp
16 | LinkingTo:
17 | Rcpp,
18 | fstcore
19 | SystemRequirements: little-endian platform
20 | RoxygenNote: 7.3.2
21 | Suggests:
22 | testthat,
23 | bit64,
24 | data.table,
25 | lintr,
26 | nanotime,
27 | crayon
28 | License: AGPL-3 | file LICENSE
29 | Encoding: UTF-8
30 | URL: http://www.fstpackage.org
31 | BugReports: https://github.com/fstpackage/fst/issues
32 |
--------------------------------------------------------------------------------
/man/compress_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/compress.R
3 | \name{compress_fst}
4 | \alias{compress_fst}
5 | \title{Compress a raw vector using the LZ4 or ZSTD compressor.}
6 | \usage{
7 | compress_fst(x, compressor = "ZSTD", compression = 0, hash = FALSE)
8 | }
9 | \arguments{
10 | \item{x}{raw vector.}
11 |
12 | \item{compressor}{compressor to use for compressing \code{x}. Valid options are "LZ4" and "ZSTD" (default).}
13 |
14 | \item{compression}{compression factor used. Must be in the range 0 (lowest compression) to 100 (maximum compression).}
15 |
16 | \item{hash}{Compute hash of compressed data. This hash is stored in the resulting raw vector and
17 | can be used during decompression to check the validity of the compressed vector. Hash
18 | computation is done with the very fast xxHash algorithm and implemented as a parallel operation,
19 | so the performance hit will be very small.}
20 | }
21 | \description{
22 | Compress a raw vector using the LZ4 or ZSTD compressor.
23 | }
24 |
--------------------------------------------------------------------------------
/man/metadata_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/fst.R
3 | \name{metadata_fst}
4 | \alias{metadata_fst}
5 | \alias{fst.metadata}
6 | \title{Read metadata from a fst file}
7 | \usage{
8 | metadata_fst(path, old_format = FALSE)
9 |
10 | fst.metadata(path, old_format = FALSE)
11 | }
12 | \arguments{
13 | \item{path}{path to fst file}
14 |
15 | \item{old_format}{must be FALSE, the old fst file format is deprecated and can only be read and
16 | converted with fst package versions 0.8.0 to 0.8.10.}
17 | }
18 | \value{
19 | Returns a list with meta information on the stored dataset in \code{path}.
20 | Has class \code{fstmetadata}.
21 | }
22 | \description{
23 | Method for checking basic properties of the dataset stored in \code{path}.
24 | }
25 | \examples{
26 | # Sample dataset
27 | x <- data.frame(
28 | First = 1:10,
29 | Second = sample(c(TRUE, FALSE, NA), 10, replace = TRUE),
30 | Last = sample(LETTERS, 10)
31 | )
32 |
33 | # Write to fst file
34 | fst_file <- tempfile(fileext = ".fst")
35 | write_fst(x, fst_file)
36 |
37 | # Display meta information
38 | metadata_fst(fst_file)
39 | }
40 |
--------------------------------------------------------------------------------
/tests/testthat/test_access.R:
--------------------------------------------------------------------------------
1 |
2 | context("access")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 | test_that("Reading non-existent file gives an error", {
13 | expect_error(fstreadproxy("AccessStore/non-existent.fst"))
14 | })
15 |
16 |
17 | test_that("Writing to incorrect path gives an error", {
18 | expect_error(fstwriteproxy(data.frame(A = 1:10), "AccessStore/A/non-existent.fst"))
19 | })
20 |
21 |
22 | test_that("Columns need to be of type character", {
23 | fstwriteproxy(data.frame(A = 1:10), "testdata/bla.fst")
24 | expect_error(fstreadproxy("testdata/bla.fst", 2), "Parameter 'columns' should be a character vector of column names")
25 | })
26 |
27 |
28 | test_that("Columns need to be of type character", {
29 | expect_error(fstreadproxy("testdata/bla.fst", to = c(1, 2)), "Parameter 'to' should have a numerical value")
30 | })
31 |
32 |
33 | test_that("Old read and write interface still functional", {
34 | x <- fstreadproxy("testdata/bla.fst")
35 | y <- read.fst("testdata/bla.fst")
36 | write.fst(y, "testdata/bla.fst")
37 |
38 | expect_identical(x, y)
39 | })
40 |
--------------------------------------------------------------------------------
/R/RcppExports.R:
--------------------------------------------------------------------------------
1 | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
2 | # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
3 |
4 | fststore <- function(fileName, table, compression, uniformEncoding) {
5 | .Call(`_fst_fststore`, fileName, table, compression, uniformEncoding)
6 | }
7 |
8 | fstmetadata <- function(fileName) {
9 | .Call(`_fst_fstmetadata`, fileName)
10 | }
11 |
12 | fstretrieve <- function(fileName, columnSelection, startRow, endRow) {
13 | .Call(`_fst_fstretrieve`, fileName, columnSelection, startRow, endRow)
14 | }
15 |
16 | fsthasher <- function(rawVec, seed, blockHash) {
17 | .Call(`_fst_fsthasher`, rawVec, seed, blockHash)
18 | }
19 |
20 | fstcomp <- function(rawVec, compressor, compression, hash) {
21 | .Call(`_fst_fstcomp`, rawVec, compressor, compression, hash)
22 | }
23 |
24 | fstdecomp <- function(rawVec) {
25 | .Call(`_fst_fstdecomp`, rawVec)
26 | }
27 |
28 | getnrofthreads <- function() {
29 | .Call(`_fst_getnrofthreads`)
30 | }
31 |
32 | setnrofthreads <- function(nrOfThreads) {
33 | .Call(`_fst_setnrofthreads`, nrOfThreads)
34 | }
35 |
36 | restore_after_fork <- function(restore) {
37 | invisible(.Call(`_fst_restore_after_fork`, restore))
38 | }
39 |
40 | hasopenmp <- function() {
41 | .Call(`_fst_hasopenmp`)
42 | }
43 |
44 |
--------------------------------------------------------------------------------
/tests/testthat/test_interface.R:
--------------------------------------------------------------------------------
1 |
2 | context("package interface")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | x <- data.table(A = 1:10, B = sample(c(TRUE, FALSE, NA), 10, replace = TRUE))
14 |
15 | test_that("From unkeyed data.table to data.table", {
16 | fstwriteproxy(x, "testdata/nokey.fst")
17 |
18 | y <- fstreadproxy("testdata/nokey.fst")
19 | expect_false(is.data.table(y))
20 |
21 | y <- fstreadproxy("testdata/nokey.fst", as_data_table = TRUE)
22 | expect_null(key(y))
23 | expect_true(is.data.table(y))
24 |
25 | z <- fstmetaproxy("testdata/nokey.fst") # expect no error
26 | })
27 |
28 |
29 | xkey <- readRDS("keyedTable.rds") # import keyed table to avoid memory leaks in data.table (LeakSanitizer)
30 |
31 | test_that("From keyed data.table to data.table", {
32 | fstwriteproxy(xkey, "testdata/key.fst")
33 |
34 | y <- fstreadproxy("testdata/key.fst")
35 | expect_false(is.data.table(y))
36 |
37 | y <- fstreadproxy("testdata/key.fst", as_data_table = TRUE)
38 | expect_true(is.data.table(y))
39 | expect_equal(key(y), "B")
40 | expect_equal(xkey, y)
41 |
42 | z <- fstmetaproxy("testdata/key.fst") # expect no error
43 | })
44 |
--------------------------------------------------------------------------------
/tests/testthat/test_keys.R:
--------------------------------------------------------------------------------
1 |
2 | context("keys")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | x <- data.table(A = 1:10, B = 10:1, C = 100:109, D = 20:29, E = 1:10)
14 | setkey(x, A, B, D)
15 |
16 |
17 | test_that("Fully keyed table", {
18 | fstwriteproxy(x, "testdata/keys.fst")
19 | y <- fstreadproxy("testdata/keys.fst", as_data_table = TRUE)
20 | expect_equal(key(y), key(x))
21 | })
22 |
23 |
24 | test_that("Missing last key", {
25 | fstwriteproxy(x, "testdata/keys.fst")
26 | y <- fstreadproxy("testdata/keys.fst", columns = c("A", "B", "C", "E"), as_data_table = TRUE)
27 | expect_equal(key(y), c("A", "B"))
28 | })
29 |
30 |
31 | test_that("Missing middle key", {
32 | fstwriteproxy(x, "testdata/keys.fst")
33 | y <- fstreadproxy("testdata/keys.fst", columns = c("A", "C", "D", "E"), as_data_table = TRUE)
34 | expect_equal(key(y), c("A"))
35 | })
36 |
37 |
38 | test_that("Missing first key", {
39 | fstwriteproxy(x, "testdata/keys.fst")
40 | res <- fst:::fstretrieve("testdata/keys.fst", c("B", "C", "D", "E"), 1L, NULL)
41 | y <- fstreadproxy("testdata/keys.fst", columns = c("B", "C", "D", "E"), as_data_table = TRUE)
42 | expect_null(key(y))
43 | })
44 |
--------------------------------------------------------------------------------
/man/fst-package.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/package.R
3 | \docType{package}
4 | \name{fst-package}
5 | \alias{fst-package}
6 | \title{Lightning Fast Serialization of Data Frames for R.}
7 | \description{
8 | Multithreaded serialization of compressed data frames using the 'fst' format.
9 | The 'fst' format allows for random access of stored data which can be compressed with the
10 | LZ4 and ZSTD compressors.
11 | }
12 | \details{
13 | The fst package is based on three C++ libraries:
14 | \itemize{
15 | \item \strong{fstlib}: library containing code to write, read and compute on files stored in the \emph{fst} format.
16 | Written and owned by Mark Klik.
17 | \item \strong{LZ4}: library containing code to compress data with the LZ4 compressor. Written and owned
18 | by Yann Collet.
19 | \item \strong{ZSTD}: library containing code to compress data with the ZSTD compressor. Written by
20 | Yann Collet and owned by Facebook, Inc.
21 | }
22 |
23 | As of version 0.9.8, these libraries are included in the fstcore package, on which fst depends.
24 | The copyright notices of the above libraries can be found in the fstcore package.
25 | }
26 | \seealso{
27 | Useful links:
28 | \itemize{
29 | \item \url{http://www.fstpackage.org}
30 | \item Report bugs at \url{https://github.com/fstpackage/fst/issues}
31 | }
32 |
33 | }
34 | \author{
35 | \strong{Maintainer}: Mark Klik \email{markklik@gmail.com} [copyright holder]
36 |
37 | }
38 |
--------------------------------------------------------------------------------
/src/openmp.cpp:
--------------------------------------------------------------------------------
1 | /*
2 | fst - R package for ultra fast storage and retrieval of datasets
3 |
4 | Copyright (C) 2017-present, Mark AJ Klik
5 |
6 | This file is part of the fst R package.
7 |
8 | The fst R package is free software: you can redistribute it and/or modify it
9 | under the terms of the GNU Affero General Public License version 3 as
10 | published by the Free Software Foundation.
11 |
12 | The fst R package is distributed in the hope that it will be useful, but
13 | WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
14 | FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
15 | for more details.
16 |
17 | You should have received a copy of the GNU Affero General Public License along
18 | with the fst R package. If not, see .
19 |
20 | You can contact the author at:
21 | - fst R package source repository : https://github.com/fstpackage/fst
22 | */
23 |
24 |
25 | #include
26 |
27 | #include
28 |
29 |
30 | // [[Rcpp::export]]
31 | SEXP getnrofthreads()
32 | {
33 | return fstcore::getnrofthreads();
34 | }
35 |
36 |
37 | // [[Rcpp::export]]
38 | int setnrofthreads(SEXP nrOfThreads)
39 | {
40 | return fstcore::setnrofthreads(nrOfThreads);
41 | }
42 |
43 |
44 | // [[Rcpp::export]]
45 | void restore_after_fork(bool restore)
46 | {
47 | fstcore::restore_after_fork(restore);
48 | }
49 |
50 |
51 | // [[Rcpp::export]]
52 | SEXP hasopenmp()
53 | {
54 | return fstcore::hasopenmp();
55 | }
56 |
57 |
--------------------------------------------------------------------------------
/src/fst_compress.cpp:
--------------------------------------------------------------------------------
1 | /*
2 | fst - R package for ultra fast storage and retrieval of datasets
3 |
4 | Copyright (C) 2017-present, Mark AJ Klik
5 |
6 | This file is part of the fst R package.
7 |
8 | The fst R package is free software: you can redistribute it and/or modify it
9 | under the terms of the GNU Affero General Public License version 3 as
10 | published by the Free Software Foundation.
11 |
12 | The fst R package is distributed in the hope that it will be useful, but
13 | WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
14 | FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
15 | for more details.
16 |
17 | You should have received a copy of the GNU Affero General Public License along
18 | with the fst R package. If not, see .
19 |
20 | You can contact the author at:
21 | - fst R package source repository : https://github.com/fstpackage/fst
22 | */
23 |
24 |
25 | #include
26 |
27 | #include
28 |
29 |
30 | // [[Rcpp::export]]
31 | SEXP fsthasher(SEXP rawVec, SEXP seed, SEXP blockHash)
32 | {
33 | return fstcore::fsthasher(rawVec, seed, blockHash);
34 | }
35 |
36 |
37 | // [[Rcpp::export]]
38 | SEXP fstcomp(SEXP rawVec, SEXP compressor, SEXP compression, SEXP hash)
39 | {
40 | return fstcore::fstcomp(rawVec, compressor, compression, hash);
41 | }
42 |
43 |
44 | // [[Rcpp::export]]
45 | SEXP fstdecomp(SEXP rawVec)
46 | {
47 | return fstcore::fstdecomp(rawVec);
48 | }
49 |
50 |
--------------------------------------------------------------------------------
/tests/testthat/test_special_tables.R:
--------------------------------------------------------------------------------
1 |
2 | context("special tables")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | difftime_mode <- function(mode = "double") {
14 | vec <- (Sys.time() + 1) - Sys.time()
15 | mode(vec) <- mode
16 | vec[0]
17 | }
18 |
19 |
20 | datatable <- data.frame(
21 | Xint = integer(0),
22 | Ylog = logical(0),
23 | Zdoub = double(0),
24 | Qchar = character(0),
25 | Ordered = ordered(sample(LETTERS, 26, replace = TRUE))[0],
26 | Date = as.Date("2019-01-01")[0],
27 | Raw = as.raw(255)[0],
28 | Difftime = difftime_mode(),
29 | DiffTime_int = difftime_mode("integer"),
30 | WFact = factor(sample(LETTERS, 26, replace = TRUE))[0],
31 | WFactNA = factor(NA)[0],
32 | stringsAsFactors = FALSE
33 | )
34 |
35 |
36 | test_that("zero row multi-column table", {
37 |
38 | # read-write cycle
39 | write_fst(datatable, "testdata/zero_row.fst")
40 |
41 | x <- fst("testdata/zero_row.fst")
42 | expect_equal(nrow(x), 0)
43 |
44 | y <- read_fst("testdata/zero_row.fst")
45 | expect_equal(datatable, y)
46 | })
47 |
48 |
49 | test_that("zero-column table", {
50 |
51 | # read-write cycle
52 | write_fst(data.frame(), "testdata/zero_column.fst")
53 |
54 | x <- fst("testdata/zero_column.fst")
55 | expect_equal(ncol(x), 0)
56 | expect_equal(nrow(x), 0)
57 |
58 | y <- read_fst("testdata/zero_column.fst")
59 | expect_equal(data.frame(), y)
60 | })
61 |
--------------------------------------------------------------------------------
/man/fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/fst_table.R
3 | \name{fst}
4 | \alias{fst}
5 | \title{Access a fst file like a regular data frame}
6 | \usage{
7 | fst(path, old_format = FALSE)
8 | }
9 | \arguments{
10 | \item{path}{path to fst file}
11 |
12 | \item{old_format}{must be FALSE, the old fst file format is deprecated and can only be read and
13 | converted with fst package versions 0.8.0 to 0.8.10.}
14 | }
15 | \value{
16 | An object of class \code{fst_table}
17 | }
18 | \description{
19 | Create a fst_table object that can be accessed like a regular data frame. This object
20 | is just a reference to the actual data and requires only a small amount of memory.
21 | When data is accessed, only a subset is read from file, depending on the minimum and
22 | maximum requested row number. This is possible because the fst file format allows full
23 | random access (in columns and rows) to the stored dataset.
24 | }
25 | \examples{
26 | \dontrun{
27 | # generate a sample fst file
28 | path <- paste0(tempfile(), ".fst")
29 | write_fst(iris, path)
30 |
31 | # create a fst_table object that can be used as a data frame
32 | ft <- fst(path)
33 |
34 | # print head and tail
35 | print(ft)
36 |
37 | # select columns and rows
38 | x <- ft[10:14, c("Petal.Width", "Species")]
39 |
40 | # use the common list interface
41 | ft[TRUE]
42 | ft[c(TRUE, FALSE)]
43 | ft[["Sepal.Length"]]
44 | ft$Petal.Length
45 |
46 | # use data frame generics
47 | nrow(ft)
48 | ncol(ft)
49 | dim(ft)
50 | dimnames(ft)
51 | colnames(ft)
52 | rownames(ft)
53 | names(ft)
54 | }
55 | }
56 |
--------------------------------------------------------------------------------
/src/flex_store.cpp:
--------------------------------------------------------------------------------
1 | /*
2 | fst - R package for ultra fast storage and retrieval of datasets
3 |
4 | Copyright (C) 2017-present, Mark AJ Klik
5 |
6 | This file is part of the fst R package.
7 |
8 | The fst R package is free software: you can redistribute it and/or modify it
9 | under the terms of the GNU Affero General Public License version 3 as
10 | published by the Free Software Foundation.
11 |
12 | The fst R package is distributed in the hope that it will be useful, but
13 | WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
14 | FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
15 | for more details.
16 |
17 | You should have received a copy of the GNU Affero General Public License along
18 | with the fst R package. If not, see .
19 |
20 | You can contact the author at:
21 | - fst R package source repository : https://github.com/fstpackage/fst
22 | */
23 |
24 | #include
25 |
26 | #include
27 |
28 |
29 | // [[Rcpp::export]]
30 | SEXP fststore(Rcpp::String fileName, SEXP table, SEXP compression, SEXP uniformEncoding)
31 | {
32 | return fstcore::fststore(fileName, table, compression, uniformEncoding);
33 | }
34 |
35 |
36 | // [[Rcpp::export]]
37 | SEXP fstmetadata(Rcpp::String fileName)
38 | {
39 | return fstcore::fstmetadata(fileName);
40 | }
41 |
42 |
43 | // [[Rcpp::export]]
44 | SEXP fstretrieve(Rcpp::String fileName, SEXP columnSelection, SEXP startRow, SEXP endRow)
45 | {
46 | return fstcore::fstretrieve(fileName, columnSelection, startRow, endRow);
47 | }
48 |
--------------------------------------------------------------------------------
/.github/workflows/R-CMD-check.yaml:
--------------------------------------------------------------------------------
1 | # Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
2 |
3 | name: R-CMD-check
4 |
5 | on:
6 | push:
7 | pull_request:
8 |
9 | jobs:
10 | R-CMD-check:
11 | runs-on: ${{ matrix.config.os }}
12 |
13 | name: ${{ matrix.config.os }} (${{ matrix.config.r }})
14 |
15 | strategy:
16 | fail-fast: false
17 | matrix:
18 | config:
19 | - {os: macOS-latest, r: 'release'}
20 | - {os: windows-2022, r: 'devel'}
21 | - {os: windows-latest, r: '4.1'}
22 | - {os: windows-latest, r: '3.6'}
23 | - {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'}
24 | - {os: ubuntu-latest, r: 'release'}
25 | - {os: ubuntu-20.04, r: 'release'}
26 | - {os: ubuntu-20.04, r: 'oldrel-4'}
27 | - {os: ubuntu-latest, r: 'oldrel-4'}
28 |
29 | env:
30 | GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
31 | R_KEEP_PKG_SOURCE: yes
32 |
33 | steps:
34 | - uses: actions/checkout@v4
35 |
36 | - uses: r-lib/actions/setup-pandoc@v2
37 |
38 | - uses: r-lib/actions/setup-r@v2
39 | with:
40 | r-version: ${{ matrix.config.r }}
41 | http-user-agent: ${{ matrix.config.http-user-agent }}
42 | use-public-rspm: true
43 |
44 | - uses: r-lib/actions/setup-r-dependencies@v2
45 | with:
46 | extra-packages: any::rcmdcheck
47 | needs: check
48 |
49 | - uses: r-lib/actions/check-r-package@v2
50 | with:
51 | args: 'c("--no-manual", "--as-cran")'
52 |
--------------------------------------------------------------------------------
/tests/testthat/test_lintr.R:
--------------------------------------------------------------------------------
1 |
2 | context("code quality")
3 |
4 |
5 | test_that("Package Style", {
6 | # lintr throws a lot of valgrind warnings, so skip on CRAN for now
7 | skip_on_cran()
8 |
9 | skip_on_ci()
10 |
11 | # lintr has many new and updated lints from version 2 onwards
12 | skip_if_not_installed("lintr", "2.0.0")
13 |
14 | lints <- lintr::linters_with_defaults(
15 | line_length_linter = lintr::line_length_linter(120),
16 | cyclocomp_linter = lintr::cyclocomp_linter(37)
17 | )
18 |
19 | code_files <- list.files(
20 | c("../../R", "../../tests"), "R$",
21 | full.names = TRUE, recursive = TRUE
22 | )
23 |
24 | # manualy remove RcppExports file and few generated files (e.g. by codecov())
25 | code_files <- code_files[!(code_files %in% c("../../R/RcppExports.R"))]
26 |
27 | # Calculate lintr results for all code files
28 | lint_results <- lintr:::flatten_lints(lapply(code_files, function(file) {
29 | if (interactive()) {
30 | message(".", appendLF = FALSE)
31 | }
32 | lintr::lint(file, linters = lints, parse_settings = FALSE)
33 | }))
34 |
35 | # newline
36 | if (interactive()) {
37 | message()
38 | }
39 |
40 | lint_output <- NULL
41 |
42 | if (length(lint_results) > 0) {
43 | lint_results <- sapply(
44 | lint_results,
45 | function(lint_res) {
46 | paste(lint_res$filename, " (", lint_res$line_number, "): ", lint_res$message)
47 | }
48 | )
49 |
50 | print(lint_results)
51 | }
52 |
53 | expect_true(length(lint_results) == 0, paste(lint_results, sep = "\n", collapse = "\n"))
54 | })
55 |
--------------------------------------------------------------------------------
/cran-comments.md:
--------------------------------------------------------------------------------
1 |
2 | ## Submission
3 |
4 | With this release of fst (v0.9.8), the fstlib library is no longer inluded in the fst package, but
5 | imported from package `fstcore`. This allows for better separation of updates to the fstlib C++ library and the fst
6 | wrapper package and avoids duplicate code in fst and fstcore. Packages can also directly use the interface
7 | exported from the fstcore package from C/C++ code.
8 |
9 | With this new setup the linker problem on macOS systems is also resolved.
10 |
11 | ## Test environments
12 |
13 | * macOS 11.6.2 20G314 using R 4.1.2 on github build infrastructure
14 | * Ubuntu 20.04.3 LTS using R version 4.0.5 on github build infrastructure
15 | * Ubuntu 20.04.3 LTS using R 4.1.2 on github build infrastructure
16 | * Ubuntu 20.04.3 LTS using R dev (2022-01-30 r81596) on github build infrastructure
17 | * Microsoft Windows Server 2019 10.0.17763 Datacenter using R 4.1.2 on github build infrastructure
18 | * Ubuntu 18.04 locally using clang-10.0
19 | * Docker with the rocker/r-devel-ubsan-clang instrumented image
20 | * Local Ubuntu with instrumented image using clang-10
21 | * Windows 11 local R 3.6.3
22 | * Windows 11 local R 4.1.2
23 | * Singularity-container package for running rchk on Ubuntu 18.04
24 | * Valgrind on Ubuntu 18.04
25 | * Rhub (all available systems)
26 |
27 | ## R CMD check results
28 |
29 | There are no errors or warnings.
30 |
31 | ## revdepcheck results
32 |
33 | We checked 29 reverse dependencies (26 from CRAN + 3 from Bioconductor), comparing R CMD check results across CRAN and dev versions of this package.
34 |
35 | * We saw 0 new problems
36 | * We failed to check 0 packages
37 |
--------------------------------------------------------------------------------
/cran-checklist.md:
--------------------------------------------------------------------------------
1 |
2 | # Checks before releasing to CRAN
3 |
4 | * Build and test package on:
5 | - Clang 6.0.0 (on latest Ubuntu)
6 | - R-hub infrastructure (all available platforms)
7 | - docker with the rocker/r-devel-ubsan-clang instrumented image
8 | - docker with the rocker/r-devel-san instrumented image
9 | - Travis Linux and OSX
10 | - AppVeyor (Windows Server)
11 | - latest R dev version on Windows
12 | * Test packages with dependencies on fst using revdepcheck::revdep_check()
13 | * Merge develop branch into release branch
14 | * Bump version to even value in DESCRIPTION and check package startup message
15 | * Update README.Rmd and verify generated README.md on Github (release)
16 | * Update cran_comments.md
17 | * Build docs folder using pkgdown::build_site()
18 | * Update NEWS.md and make sure to remove '(in development)' in the version title and update version number
19 | * Credit all GitHub contributions in NEWS.md
20 | * Submit to CRAN
21 |
22 | # After releasing to CRAN
23 |
24 | * Update NEWS.md with the release date
25 | * Build docs folder using pkgdown::build_site(). Check that the package date is correct.
26 | * Merge branch release into master
27 | * Tag the release on Github
28 | * Commit latest docs to the fstpackage.github.io and fstpackage.github.io/fst repository
29 | * Go to the repository release page and create a new release with tag version vx.y.z.
30 | Copy and paste the contents of the relevant NEWS.md section into the release notes.
31 | * Merge branch master into release
32 | * Add '(in development)' to version title in NEWS.md and update to odd version number
33 | * Check package startup message
34 | * Merge release branch into develop
35 |
--------------------------------------------------------------------------------
/tests/testthat/test_date.R:
--------------------------------------------------------------------------------
1 |
2 | context("date column")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | test_that("Type double Date issue #22 and #33", {
14 | u1 <- data.frame(DT = Sys.Date() - 1:10, variable = rep(c("A", "B"), 5), value = 1:10)
15 | fstwriteproxy(u1, "testdata/u1.fst")
16 | expect_equal(typeof(u1$DT), "double") # double type date (expensive)
17 |
18 | u2 <- fstreadproxy("testdata/u1.fst")
19 | expect_equal(u1, u2)
20 | expect_equal(typeof(u2$DT), "double") # remains double (no conversion to integer like in feather)
21 | })
22 |
23 |
24 | test_that("Include NA dates", {
25 | u1 <- data.frame(DT = as.Date("2010-01-01") + c(0L, 365L, NA))
26 | fstwriteproxy(u1, "testdata/u1.fst")
27 | expect_equal(typeof(u1$DT), "double") # double type date (expensive)
28 |
29 | u2 <- fstreadproxy("testdata/u1.fst")
30 | expect_equal(u1, u2)
31 | expect_equal(typeof(u2$DT), "double") # converted to integer type date
32 | })
33 |
34 |
35 | test_that("Include NA dates on integer Date vector", {
36 | u1 <- data.frame(DT = as.Date("2010-01-01") + c(0L, 365L, NA))
37 | u1[, "DT"] <- as.integer(u1$DT)
38 | class(u1$DT) <- "Date"
39 |
40 | fstwriteproxy(u1, "testdata/u1.fst")
41 | expect_equal(typeof(u1$DT), "integer") # integer type date
42 |
43 | u2 <- fstreadproxy("testdata/u1.fst")
44 | expect_equal(typeof(u2$DT), "integer") # still integer type date
45 | expect_equal(as.integer(u1$DT), as.integer(u2$DT)) # integer values identical
46 |
47 | expect_equal(class(u2$DT), c("IDate", "Date")) # integer values identical
48 | })
49 |
--------------------------------------------------------------------------------
/R/onAttach.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | .onAttach <- function(libname, pkgname) { # nolint
24 | # Runs when attached to search() path such as by library() or require()
25 | if (interactive()) {
26 | v <- packageVersion("fst")
27 | d <- read.dcf(system.file("DESCRIPTION", package = "fst"), fields = c("Packaged", "Built"))
28 |
29 | if (is.na(d[1])) {
30 | if (is.na(d[2])) {
31 | return() # neither field exists
32 | } else {
33 | d <- unlist(strsplit(d[2], split = "; "))[3]
34 | }
35 | } else {
36 | d <- d[1]
37 | }
38 |
39 | # version number odd => dev
40 | dev <- as.integer(v[1, 3]) %% 2 == 1
41 |
42 | packageStartupMessage("fst package v", v, if (dev) paste0(" IN DEVELOPMENT built ", d))
43 |
44 | # check for old version
45 | if (dev && (Sys.Date() - as.Date(d)) > 28)
46 | packageStartupMessage("\n!!! This development version of the package is rather old, please update !!!")
47 | }
48 | }
49 |
--------------------------------------------------------------------------------
/tests/testthat/test_integer64.R:
--------------------------------------------------------------------------------
1 |
2 | context("integer64 column")
3 |
4 |
5 | library(data.table)
6 |
7 |
8 | # Clean testdata directory
9 | if (!file.exists("testdata")) {
10 | dir.create("testdata")
11 | } else {
12 | file.remove(list.files("testdata", full.names = TRUE))
13 | }
14 |
15 | # Prepare example
16 | if (requireNamespace("bit64", quietly = TRUE)) {
17 | dtint64 <- data.frame(
18 | Int64 = bit64::as.integer64(sample(c(2345612345679, 1234567890, 8714567890), 100, replace = TRUE))
19 | )
20 | }
21 |
22 |
23 | test_that("Type integer64 issue #28", {
24 |
25 | skip_if_not(requireNamespace("bit64", quietly = TRUE))
26 |
27 | expect_equal(class(dtint64$Int64), "integer64")
28 |
29 | # Write to fst
30 | fstwriteproxy(dtint64, "testdata/dt_int64.fst")
31 |
32 | # bit64 integer64 type preserved:
33 | dtint64_read <- fstreadproxy("testdata/dt_int64.fst")
34 |
35 | # bit64::integer64 type preserved:
36 | expect_equal(class(dtint64_read$Int64), "integer64")
37 | expect_identical(dtint64, dtint64_read)
38 | })
39 |
40 |
41 | test_that("Type integer64 with compression", {
42 |
43 | skip_if_not(requireNamespace("bit64", quietly = TRUE))
44 |
45 | # Write to fst
46 | fstwriteproxy(dtint64, "testdata/dt_int64.fst", 95)
47 |
48 | dtint64_read <- fstreadproxy("testdata/dt_int64.fst")
49 |
50 | # bit64::integer64 type preserved:
51 | expect_equal(class(dtint64_read$Int64), "integer64")
52 | expect_identical(dtint64, dtint64_read)
53 | })
54 |
55 |
56 | test_that("Type integer64 with compression as data.table", {
57 |
58 | skip_if_not(requireNamespace("bit64", quietly = TRUE))
59 |
60 | setDT(dtint64)
61 | fstwriteproxy(dtint64, "testdata/dt_int64.fst", 95) # Write to fst
62 |
63 | dtint64_read <- fstreadproxy("testdata/dt_int64.fst", as_data_table = TRUE)
64 |
65 | # bit64::integer64 type preserved:
66 | expect_equal(class(dtint64_read$Int64), "integer64")
67 | expect_identical(dtint64, dtint64_read)
68 | })
69 |
--------------------------------------------------------------------------------
/R/hash.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' Parallel calculation of the hash of a raw vector
24 | #'
25 | #' @param x raw vector that you want to hash
26 | #' @param seed The seed value for the hashing algorithm. If NULL, a default seed will be used.
27 | #' @param block_hash If TRUE, a multi-threaded implementation of the 64-bit xxHash algorithm will
28 | #' be used. Note that block_hash = TRUE or block_hash = FALSE will result in different hash values.
29 | #'
30 | #' @return hash value
31 | #'
32 | #' @export
33 | hash_fst <- function(x, seed = NULL, block_hash = TRUE) {
34 | if (!is.null(seed)) {
35 | if (((!is.numeric(seed)) || (length(seed) != 1))) { # nolint
36 | stop("Please specify an integer value for the hash seed")
37 | }
38 |
39 | seed <- as.integer(seed)
40 | }
41 |
42 | if (!is.logical(block_hash) || length(block_hash) != 1) {
43 | stop("Please specify a logical value for parameter block_hash")
44 | }
45 |
46 | if (!is.raw(x)) {
47 | stop("Please specify a raw vector as input parameter x")
48 | }
49 |
50 | fsthasher(x, seed, block_hash)
51 | }
52 |
--------------------------------------------------------------------------------
/tests/testthat/test_omp.R:
--------------------------------------------------------------------------------
1 |
2 | context("OpenMP")
3 |
4 |
5 | # Clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | test_that("Get number of threads", {
14 | nr_of_threads <- threads_fst()
15 | expect_gte(nr_of_threads, 1) # expect at least a single thread
16 | prev_threads <- threads_fst(2) # Set number of OpenMP threads
17 | expect_equal(nr_of_threads, prev_threads)
18 | nr_of_threads <- threads_fst()
19 |
20 | # Systems with OpenMP activated should have more than a single thread
21 | if (fst:::hasopenmp()) {
22 | expect_equal(nr_of_threads, 2)
23 | } else {
24 | expect_equal(nr_of_threads, 1)
25 | }
26 | })
27 |
28 |
29 | test_that("threads_fst(0) use all logical cores", {
30 | threads_fst(0)
31 | nr_of_threads <- threads_fst()
32 | logical_cores <- parallel::detectCores(logical = TRUE)
33 |
34 | # Systems with OpenMP activated should have more than a single thread
35 | if (fst:::hasopenmp()) {
36 | expect_gt(nr_of_threads, 1)
37 | } else {
38 | expect_equal(nr_of_threads, 1)
39 | }
40 | })
41 |
42 |
43 | test_that("Loading fst works with options", {
44 |
45 | # Note that neither of the tests in this block will be informative when run
46 | # on a machine without openmp. They'll pass even if the thing they're testing
47 | # is broken.
48 |
49 | orig_op <- getOption("fst_threads")
50 | options(fst_threads = 1)
51 |
52 | # First test that .onload, which happens when the namespace is loaded by ::,
53 | # reads from the fst.threads option.
54 | fstcore:::.onLoad()
55 | nr_of_threads <- threads_fst()
56 | expect_equal(nr_of_threads, 1)
57 |
58 | # Next, test that subsequently attaching the package doesn't change
59 | # the number of threads.
60 | fstcore:::.onAttach()
61 | nr_of_threads <- threads_fst()
62 | expect_equal(nr_of_threads, 1)
63 | options(fst.threads = orig_op) # reset option
64 | })
65 |
66 |
67 | test_that("Set reset_after_fork", {
68 |
69 | expect_error(threads_fst(reset_after_fork = 3), "Parameter reset_after_fork should be set")
70 |
71 | })
72 |
--------------------------------------------------------------------------------
/man/threads_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/openmp.R
3 | \name{threads_fst}
4 | \alias{threads_fst}
5 | \title{Get or set the number of threads used in parallel operations}
6 | \usage{
7 | threads_fst(nr_of_threads = NULL, reset_after_fork = NULL)
8 | }
9 | \arguments{
10 | \item{nr_of_threads}{number of threads to use or \code{NULL} to get the current number of threads used in
11 | multithreaded operations.}
12 |
13 | \item{reset_after_fork}{when \code{fst} is running in a forked process, the usage of OpenMP can
14 | create problems. To prevent these, \code{fst} switches back to single core usage when it detects a fork.
15 | After the fork, the number of threads is reset to it's initial setting. However, on some compilers
16 | (e.g. Intel), switching back to multi-threaded mode can lead to issues. When \code{reset_after_fork}
17 | is set to \code{FALSE}, \code{fst} is left in single-threaded mode after the fork ends. After the fork,
18 | multithreading can be activated again manually by calling \code{threads_fst} with an appropriate value
19 | for \code{nr_of_threads}. The default (\code{reset_after_fork = NULL}) leaves the fork behavior unchanged.}
20 | }
21 | \value{
22 | the number of threads (previously) used
23 | }
24 | \description{
25 | For parallel operations, the performance is determined to a great extend by the number of threads
26 | used. More threads will allow the CPU to perform more computational intensive tasks simultaneously,
27 | speeding up the operation. Using more threads also introduces some overhead that will scale with the
28 | number of threads used. Therefore, using the maximum number of available threads is not always the
29 | fastest solution. With \code{threads_fst} the number of threads can be adjusted to the users
30 | specific requirements. As a default, \code{fst} uses a number of threads equal to the number of
31 | logical cores in the system.
32 | }
33 | \details{
34 | The number of threads can also be set with \code{options(fst_threads = N)}.
35 | NOTE: This option is only read when the package's namespace is first loaded, with commands like
36 | \code{library}, \code{require}, or \code{::}. If you have already used one of these, you
37 | must use \code{threads_fst} to set the number of threads.
38 | }
39 |
--------------------------------------------------------------------------------
/R/package.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' @useDynLib fst, .registration = TRUE
24 | #' @import Rcpp
25 | #' @importFrom fstcore threads_fstlib
26 | #' @importFrom utils packageVersion
27 | #' @importFrom utils capture.output
28 | #' @importFrom utils tail
29 | #' @importFrom utils str
30 | #' @importFrom parallel detectCores
31 | NULL
32 |
33 |
34 | #' Lightning Fast Serialization of Data Frames for R.
35 | #'
36 | #' Multithreaded serialization of compressed data frames using the 'fst' format.
37 | #' The 'fst' format allows for random access of stored data which can be compressed with the
38 | #' LZ4 and ZSTD compressors.
39 | #'
40 | #' The fst package is based on three C++ libraries:
41 | #'
42 | #' * **fstlib**: library containing code to write, read and compute on files stored in the _fst_ format.
43 | #' Written and owned by Mark Klik.
44 | #' * **LZ4**: library containing code to compress data with the LZ4 compressor. Written and owned
45 | #' by Yann Collet.
46 | #' * **ZSTD**: library containing code to compress data with the ZSTD compressor. Written by
47 | #' Yann Collet and owned by Facebook, Inc.
48 | #'
49 | #' As of version 0.9.8, these libraries are included in the fstcore package, on which fst depends.
50 | #' The copyright notices of the above libraries can be found in the fstcore package.
51 | #'
52 | #' @md
53 | #' @name fst-package
54 | #' @aliases fst-package
55 | "_PACKAGE"
56 |
--------------------------------------------------------------------------------
/CONTRIBUTING.md:
--------------------------------------------------------------------------------
1 |
2 | # Contributions
3 |
4 | Contributions to `fst` are welcome from anyone and are best sent as pull requests on [the GitHub repository](https://github.com/fstpackage/fst/). This page provides some instructions to potential contributors about how to add to the package.
5 |
6 | 1. Contributions can be submitted as [a pull request](https://help.github.com/articles/creating-a-pull-request/) on GitHub by forking or cloning the [fst repository](https://github.com/fstpackage/fst/), making changes and submitting the pull request.
7 |
8 | 2. Pull requests should involve only one commit per substantive change. This means if you change multiple files (e.g., code and documentation), these changes should be committed together. If you don't know how to do this (e.g., you are making changes in the GitHub web interface) just submit anyway and the maintainer will clean things up.
9 |
10 | 3. Pull requests that involve code in the 3rd party libraries `LZ4`, `ZSTD` or `fstlib` (located under `src/fstcore`) will not be accepted. These libraries are used _as-is_ and any issues can be reported at their respective GitHub repositories.
11 |
12 | 4. All contributions must be submitted consistent with the package license ([AGPL-3](https://www.gnu.org/licenses/agpl-3.0.en.html)).
13 |
14 | 5. Contributions in the code (not documentation) that consist of more than 1000 characters (excluding spaces)
15 | need to be noted in the `Authors@R` field in the [`DESCRIPTION`](https://github.com/fstpackage/fst/blob/master/DESCRIPTION) file. Just follow the format of the existing entries to add your name (and, optionally, email address).
16 |
17 | 6. This package uses `royxgen` code and documentation markup, so changes should be made to `roxygen` comments in the source code `.R` files. If changes are made, `roxygen` needs to be run. The easiest way to do this is a command line call to: `Rscript -e devtools::document()`. Please resolve any `roxygen` errors before submitting a pull request.
18 |
19 | 7. Please run `R CMD BUILD fst` and `R CMD CHECK fst_VERSION.tar.gz` before submitting the pull request to check for any errors.
20 |
21 | 8. Changes requiring a new package dependency should be discussed on the GitHub issues page before submitting a pull request.
22 |
23 | Any questions you have can be opened as GitHub issues or directed to markklik (at) gmail.com.
24 |
--------------------------------------------------------------------------------
/tests/testthat/test_time.R:
--------------------------------------------------------------------------------
1 |
2 | context("time")
3 |
4 |
5 | # some helper functions
6 | source("helper_fstwrite.R")
7 |
8 |
9 | roundtrip_vector <- function(x) {
10 | df <- data.frame(x = x, stringsAsFactors = FALSE)
11 | roundtrip(df)$x
12 | }
13 |
14 |
15 | roundtrip <- function(df) {
16 | temp <- tempfile()
17 | fstwriteproxy(df, temp)
18 | on.exit(unlink(temp))
19 |
20 | fstreadproxy(temp)
21 | }
22 |
23 |
24 | # POSIXct
25 | test_that("preserves times", {
26 | x1 <- ISOdate(2001, 10, 10, tz = "US/Pacific") + c(0, NA)
27 | x2 <- roundtrip_vector(x1)
28 |
29 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
30 | expect_identical(attr(x1, "class"), attr(x1, "class"))
31 | expect_identical(unclass(x1), unclass(x2))
32 |
33 | mode(x1) <- "integer"
34 | x2 <- roundtrip_vector(x1)
35 |
36 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
37 | expect_identical(attr(x1, "class"), attr(x1, "class"))
38 | expect_identical(unclass(x1), unclass(x2))
39 | })
40 |
41 |
42 | test_that("throws error on POSIXlt", {
43 | df <- data.frame(x = Sys.time())
44 | df$x <- as.POSIXlt(df$x)
45 |
46 | expect_error(roundtrip(df), "Unknown type found in column")
47 | })
48 |
49 |
50 | test_that("empty timezone attribute", {
51 | x1 <- Sys.time()
52 |
53 | # set to empty time zone
54 | attributes(x1)$tzone <- ""
55 |
56 | x2 <- roundtrip_vector(x1)
57 |
58 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
59 | expect_identical(x1, x2)
60 |
61 | mode(x1) <- "integer"
62 |
63 | x2 <- roundtrip_vector(x1)
64 |
65 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
66 | expect_identical(x1, x2)
67 | })
68 |
69 |
70 | test_that("doesn't lose undue precision", {
71 | base <- ISOdate(2001, 10, 10)
72 | x1 <- base + 1e-6 * (0:3)
73 | x2 <- roundtrip_vector(x1)
74 |
75 | expect_identical(x1, x2)
76 | })
77 |
78 |
79 | test_that("NULL tzone attribute is retained", {
80 | x1 <- Sys.time()
81 | attributes(x1)$tzone <- NULL # no tzone set
82 |
83 | expect_equal(typeof(x1), "double")
84 |
85 | # write / read cycle
86 | x2 <- roundtrip_vector(x1)
87 |
88 | expect_equal(typeof(x2), "double")
89 | expect_null(attributes(x2)$tzone)
90 |
91 | mode(x1) <- "integer"
92 | expect_equal(typeof(x1), "integer")
93 |
94 | # write / read cycle
95 | x2 <- roundtrip_vector(x1)
96 | expect_equal(typeof(x2), "integer")
97 | expect_null(attributes(x2)$tzone)
98 | })
99 |
--------------------------------------------------------------------------------
/R/type_dependencies.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | # load bit64 namespace when integer64 type column is read from file
24 | require_bit64 <- function() {
25 | if (!requireNamespace("bit64", quietly = TRUE)) {
26 | warning(
27 | "Some columns are type 'integer64' but package bit64 is not installed. ",
28 | "Those columns will print as strange looking floating point data. ",
29 | "There is no need to reload the data. Simply install.packages('bit64') to obtain ",
30 | "the integer64 print method and print the data again."
31 | )
32 | }
33 | }
34 |
35 |
36 | # load data.table namespace when ITime type column is read from file
37 | require_data_table <- function() {
38 | if (!requireNamespace("data.table", quietly = TRUE)) {
39 | warning(
40 | "Some columns are type 'ITime' but package data.table is not installed. ",
41 | "Those columns will print incorrectly. There is no need to ",
42 | "reload the data. Simply install.packages('data.table') to obtain the data.table print ",
43 | "method and print the data again."
44 | )
45 | }
46 | }
47 |
48 |
49 | require_nanotime <- function() {
50 | # called in print when they see nanotime columns are present
51 | if (!requireNamespace("nanotime", quietly = TRUE)) {
52 | warning(
53 | "Some columns are type 'nanotime' but package nanotime is not installed. ",
54 | "Those columns will print as strange looking floating point data. There is no need to ",
55 | "reload the data. Simply install.packages('nanotime') to obtain the nanotime print ",
56 | "method and print the data again."
57 | )
58 | }
59 | }
60 |
--------------------------------------------------------------------------------
/R/compress.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' Compress a raw vector using the LZ4 or ZSTD compressor.
24 | #'
25 | #' @param x raw vector.
26 | #' @param compressor compressor to use for compressing \code{x}. Valid options are "LZ4" and "ZSTD" (default).
27 | #' @param compression compression factor used. Must be in the range 0 (lowest compression) to 100 (maximum compression).
28 | #' @param hash Compute hash of compressed data. This hash is stored in the resulting raw vector and
29 | #' can be used during decompression to check the validity of the compressed vector. Hash
30 | #' computation is done with the very fast xxHash algorithm and implemented as a parallel operation,
31 | #' so the performance hit will be very small.
32 | #'
33 | #' @export
34 | compress_fst <- function(x, compressor = "ZSTD", compression = 0, hash = FALSE) {
35 | if (!is.numeric(compression)) {
36 | stop("Parameter compression should be a numeric value in the range 0 to 100")
37 | }
38 |
39 | if (!is.character(compressor)) {
40 | stop("Parameter compressor should be set to 'LZ4' or 'ZSTD'.")
41 | }
42 |
43 | if (!is.raw(x)) {
44 | stop("Parameter x is not set to a raw vector.")
45 | }
46 |
47 | compressed_vec <- fstcomp(x, compressor, as.integer(compression), hash)
48 |
49 | if (inherits(compressed_vec, "fst_error")) {
50 | stop(compressed_vec)
51 | }
52 |
53 | compressed_vec
54 | }
55 |
56 |
57 | #' Decompress a raw vector with compressed data.
58 | #'
59 | #' @param x raw vector with data previously compressed with \code{compress_fst}.
60 | #'
61 | #' @return a raw vector with previously compressed data.
62 | #' @export
63 | decompress_fst <- function(x) {
64 |
65 | if (!is.raw(x)) {
66 | stop("Parameter x should be a raw vector with compressed data.")
67 | }
68 |
69 | decompressed_vec <- fstdecomp(x)
70 |
71 | if (inherits(decompressed_vec, "fst_error")) {
72 | stop(decompressed_vec)
73 | }
74 |
75 | decompressed_vec
76 | }
77 |
--------------------------------------------------------------------------------
/tests/testthat/test_encoding.R:
--------------------------------------------------------------------------------
1 |
2 | context("encoding")
3 |
4 |
5 | # some helper functions
6 | source("helper_fstwrite.R")
7 |
8 |
9 | # Clean testdata directory
10 | if (!file.exists("testdata")) {
11 | dir.create("testdata")
12 | } else {
13 | file.remove(list.files("testdata", full.names = TRUE))
14 | }
15 |
16 |
17 | testwriteread <- function(x, encoding, uniform_encoding = TRUE) {
18 | fstwriteproxy(x, "testdata/encoding.fst", uniform_encoding)
19 | y <- fstreadproxy("testdata/encoding.fst")
20 |
21 | for (col in seq_len(ncol(x))) {
22 | if (typeof(x[[col]]) == "character") {
23 | expect_equal(Encoding(y[[col]]), rep(encoding[col], nrow(x)))
24 | }
25 | }
26 |
27 | expect_equal(x, y)
28 | }
29 |
30 |
31 | test_that("utf8, native and latin1 encodings", {
32 | native <- data.frame(x = rep("Arende", 5), stringsAsFactors = FALSE)
33 | latin1 <- data.frame(x = rep("Ärende", 5), stringsAsFactors = FALSE)
34 | Encoding(latin1$x) <- "latin1"
35 | utf8 <- data.frame(x = enc2utf8(rep("Ärende", 5)), stringsAsFactors = FALSE)
36 |
37 | # test encodings
38 | testwriteread(native, c("unknown"))
39 | testwriteread(latin1, c("latin1"))
40 | testwriteread(utf8, "UTF-8")
41 | })
42 |
43 |
44 | test_that("I can eat glass in various languages", {
45 | x <- read.csv2("datasets/utf8.csv", encoding = "UTF-8", stringsAsFactors = FALSE)
46 |
47 | testwriteread(x, c("unknown", "UTF-8"))
48 | })
49 |
50 |
51 | test_that("Mixed encodings", {
52 | x <- data.frame(Mixed = c("Ärende", enc2native("native"), enc2utf8("Ärende")), stringsAsFactors = FALSE)
53 | Encoding(x$Mixed[1]) <- "latin1" # be sure
54 |
55 | fstwriteproxy(x, "testdata/mixed.fst")
56 | y <- fstreadproxy("testdata/mixed.fst")
57 |
58 | expect_equal(Encoding(y$Mixed), c("latin1", "unknown", "latin1")) # recoded to latin1
59 |
60 | expect_failure(expect_equal(x, y)) # mix of unknown, latin1 and UTF-8
61 |
62 | expect_error(
63 | fstwriteproxy(x, "testdata/mixed.fst", uniform_encoding = FALSE),
64 | "Character vectors with mixed encodings are currently not supported"
65 | )
66 |
67 | Encoding(x$Mixed[1]) <- "UTF-8" # mix of unknown and UTF-8
68 | expect_error(
69 | fstwriteproxy(x, "testdata/mixed.fst", uniform_encoding = FALSE),
70 | "Character vectors with mixed encodings are currently not supported"
71 | )
72 |
73 | fstwriteproxy(x, "testdata/mixed.fst")
74 | y <- fstreadproxy("testdata/mixed.fst")
75 |
76 | expect_equal(Encoding(y$Mixed), c("UTF-8", "unknown", "UTF-8")) # recoded to UTF-8
77 | })
78 |
79 |
80 | test_that("Column name encoding", {
81 | x <- read.csv2("datasets/utf8.csv", encoding = "UTF-8", stringsAsFactors = FALSE)[2, 2]
82 |
83 | df <- data.frame(X = 1:10)
84 | colnames(df) <- x
85 |
86 | fstwriteproxy(df, "testdata/enc_cols.fst")
87 | y <- fstreadproxy("testdata/enc_cols.fst")
88 |
89 | expect_equal(Encoding(colnames(y)), "UTF-8")
90 | })
91 |
--------------------------------------------------------------------------------
/R/openmp.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' Get or set the number of threads used in parallel operations
24 | #'
25 | #' For parallel operations, the performance is determined to a great extend by the number of threads
26 | #' used. More threads will allow the CPU to perform more computational intensive tasks simultaneously,
27 | #' speeding up the operation. Using more threads also introduces some overhead that will scale with the
28 | #' number of threads used. Therefore, using the maximum number of available threads is not always the
29 | #' fastest solution. With \code{threads_fst} the number of threads can be adjusted to the users
30 | #' specific requirements. As a default, \code{fst} uses a number of threads equal to the number of
31 | #' logical cores in the system.
32 | #'
33 | #' The number of threads can also be set with \code{options(fst_threads = N)}.
34 | #' NOTE: This option is only read when the package's namespace is first loaded, with commands like
35 | #' \code{library}, \code{require}, or \code{::}. If you have already used one of these, you
36 | #' must use \code{threads_fst} to set the number of threads.
37 | #'
38 | #' @param nr_of_threads number of threads to use or \code{NULL} to get the current number of threads used in
39 | #' multithreaded operations.
40 | #' @param reset_after_fork when \code{fst} is running in a forked process, the usage of OpenMP can
41 | #' create problems. To prevent these, \code{fst} switches back to single core usage when it detects a fork.
42 | #' After the fork, the number of threads is reset to it's initial setting. However, on some compilers
43 | #' (e.g. Intel), switching back to multi-threaded mode can lead to issues. When \code{reset_after_fork}
44 | #' is set to \code{FALSE}, \code{fst} is left in single-threaded mode after the fork ends. After the fork,
45 | #' multithreading can be activated again manually by calling \code{threads_fst} with an appropriate value
46 | #' for \code{nr_of_threads}. The default (\code{reset_after_fork = NULL}) leaves the fork behavior unchanged.
47 | #'
48 | #' @return the number of threads (previously) used
49 | #' @export
50 | threads_fst <- function(nr_of_threads = NULL, reset_after_fork = NULL) {
51 | fstcore::threads_fstlib(nr_of_threads, reset_after_fork)
52 | }
53 |
--------------------------------------------------------------------------------
/man/write_fst.Rd:
--------------------------------------------------------------------------------
1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/fst.R
3 | \name{write_fst}
4 | \alias{write_fst}
5 | \alias{write.fst}
6 | \alias{read_fst}
7 | \alias{read.fst}
8 | \title{Read and write fst files.}
9 | \usage{
10 | write_fst(x, path, compress = 50, uniform_encoding = TRUE)
11 |
12 | write.fst(x, path, compress = 50, uniform_encoding = TRUE)
13 |
14 | read_fst(
15 | path,
16 | columns = NULL,
17 | from = 1,
18 | to = NULL,
19 | as.data.table = FALSE,
20 | old_format = FALSE
21 | )
22 |
23 | read.fst(
24 | path,
25 | columns = NULL,
26 | from = 1,
27 | to = NULL,
28 | as.data.table = FALSE,
29 | old_format = FALSE
30 | )
31 | }
32 | \arguments{
33 | \item{x}{a data frame to write to disk}
34 |
35 | \item{path}{path to fst file}
36 |
37 | \item{compress}{value in the range 0 to 100, indicating the amount of compression to use.
38 | Lower values mean larger file sizes. The default compression is set to 50.}
39 |
40 | \item{uniform_encoding}{If `TRUE`, all character vectors will be assumed to have elements with equal encoding.
41 | The encoding (latin1, UTF8 or native) of the first non-NA element will used as encoding for the whole column.
42 | This will be a correct assumption for most use cases.
43 | If `uniform.encoding` is set to `FALSE`, no such assumption will be made and all elements will be converted
44 | to the same encoding. The latter is a relatively expensive operation and will reduce write performance for
45 | character columns.}
46 |
47 | \item{columns}{Column names to read. The default is to read all columns.}
48 |
49 | \item{from}{Read data starting from this row number.}
50 |
51 | \item{to}{Read data up until this row number. The default is to read to the last row of the stored dataset.}
52 |
53 | \item{as.data.table}{If TRUE, the result will be returned as a \code{data.table} object. Any keys set on
54 | dataset \code{x} before writing will be retained. This allows for storage of sorted datasets. This option
55 | requires \code{data.table} package to be installed.}
56 |
57 | \item{old_format}{must be FALSE, the old fst file format is deprecated and can only be read and
58 | converted with fst package versions 0.8.0 to 0.8.10.}
59 | }
60 | \value{
61 | `read_fst` returns a data frame with the selected columns and rows. `write_fst`
62 | writes `x` to a `fst` file and invisibly returns `x` (so you can use this function in a pipeline).
63 | }
64 | \description{
65 | Read and write data frames from and to a fast-storage (`fst`) file.
66 | Allows for compression and (file level) random access of stored data, even for compressed datasets.
67 | Multiple threads are used to obtain high (de-)serialization speeds but all background threads are
68 | re-joined before `write_fst` and `read_fst` return (reads and writes are stable).
69 | When using a `data.table` object for `x`, the key (if any) is preserved,
70 | allowing storage of sorted data.
71 | Methods `read_fst` and `write_fst` are equivalent to `read.fst` and `write.fst` (but the
72 | former syntax is preferred).
73 | }
74 | \examples{
75 | # Sample dataset
76 | x <- data.frame(A = 1:10000, B = sample(c(TRUE, FALSE, NA), 10000, replace = TRUE))
77 |
78 | # Default compression
79 | fst_file <- tempfile(fileext = ".fst")
80 | write_fst(x, fst_file) # filesize: 17 KB
81 | y <- read_fst(fst_file) # read fst file
82 | # Maximum compression
83 | write_fst(x, fst_file, 100) # fileSize: 4 KB
84 | y <- read_fst(fst_file) # read fst file
85 |
86 | # Random access
87 | y <- read_fst(fst_file, "B") # read selection of columns
88 | y <- read_fst(fst_file, "A", 100, 200) # read selection of columns and rows
89 | }
90 |
--------------------------------------------------------------------------------
/tests/testthat/test_roundtrip.R:
--------------------------------------------------------------------------------
1 |
2 | context("roundtrip-vector")
3 |
4 |
5 | # some helper functions
6 | source("helper_fstwrite.R")
7 |
8 |
9 | roundtrip_vector <- function(x) {
10 | df <- data.frame(x = x, stringsAsFactors = FALSE)
11 | roundtrip(df)$x
12 | }
13 |
14 |
15 | roundtrip_vector_dt <- function(x) {
16 | dt <- data.table(x = x, stringsAsFactors = FALSE)
17 | roundtrip(dt)$x
18 | }
19 |
20 |
21 | roundtrip <- function(df) {
22 | temp <- tempfile()
23 | fstwriteproxy(df, temp)
24 | on.exit(unlink(temp))
25 |
26 | fstreadproxy(temp)
27 | }
28 |
29 |
30 | # Logical
31 | test_that("preserves three logical values", {
32 | x <- c(FALSE, TRUE, NA)
33 | expect_identical(roundtrip_vector(x), x)
34 | })
35 |
36 |
37 | # Integer
38 | test_that("preserves integer values", {
39 | x <- 1:10
40 | x[sample(1:10, 3)] <- NA
41 | expect_identical(roundtrip_vector(x), x)
42 | })
43 |
44 |
45 | # Double
46 | test_that("preserves special floating point values", {
47 | x <- c(Inf, -Inf, NaN, NA)
48 | expect_identical(roundtrip_vector(x), x)
49 | })
50 |
51 |
52 | test_that("doesn't lose precision", {
53 | x <- c(1 / 3, sqrt(2), pi)
54 | expect_identical(roundtrip_vector(x), x)
55 | })
56 |
57 |
58 | # Character
59 | test_that("preserves character values", {
60 | x <- c("this is a string", "", NA, "another string")
61 | expect_identical(roundtrip_vector(x), x)
62 | })
63 |
64 |
65 | test_that("can have NA on end of string", {
66 | x <- c("this is a string", NA)
67 | expect_identical(roundtrip_vector(x), x)
68 | })
69 |
70 |
71 | # Factor
72 | test_that("preserves simple factor", {
73 | x <- factor(c("abc", "def"))
74 | expect_identical(roundtrip_vector(x), x)
75 | })
76 |
77 |
78 | test_that("preserves NA in factor and levels", {
79 | x1 <- factor(c("abc", "def", NA))
80 | x2 <- addNA(x1)
81 |
82 | expect_identical(roundtrip_vector(x1), x1)
83 | expect_identical(roundtrip_vector(x2), x2)
84 | })
85 |
86 |
87 | # Date
88 | test_that("preserves dates", {
89 | x <- as.Date("2010-01-01") + c(0L, 365L, NA)
90 | mode(x) <- "integer"
91 | res <- roundtrip_vector(x)
92 | class(res) <- c("IDate", "Date") # gains class IDate from data.table
93 | expect_identical(as.integer(res), as.integer(x))
94 | })
95 |
96 |
97 | # ITime
98 | test_that("preserves time of day", {
99 | x <- as.ITime(c(1:10, NA), origin = "1970-01-01")
100 | res <- roundtrip_vector_dt(x)
101 | expect_identical(res, x)
102 |
103 | mode(x) <- "double"
104 | res <- roundtrip_vector_dt(x)
105 | expect_identical(res, x)
106 | })
107 |
108 |
109 | # POSIXct
110 | test_that("preserves times", {
111 | x1 <- ISOdate(2001, 10, 10, tz = "US/Pacific") + c(0, NA)
112 | x2 <- roundtrip_vector(x1)
113 |
114 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
115 | expect_identical(attr(x1, "class"), attr(x1, "class"))
116 | expect_identical(unclass(x1), unclass(x2))
117 |
118 | mode(x1) <- "integer"
119 | x2 <- roundtrip_vector(x1)
120 |
121 | expect_identical(attr(x1, "tzone"), attr(x2, "tzone"))
122 | expect_identical(attr(x1, "class"), attr(x1, "class"))
123 | expect_identical(unclass(x1), unclass(x2))
124 |
125 | })
126 |
127 |
128 | test_that("throws error on POSIXlt", {
129 | df <- data.frame(x = Sys.time())
130 | df$x <- as.POSIXlt(df$x)
131 |
132 | expect_error(roundtrip(df), "Unknown type found in column")
133 | })
134 |
135 |
136 | # nolint start
137 | # Time --------------------------------------------------------------------
138 | #
139 | # test_that("preserves hms", {
140 | # x <- hms::hms(1:100)
141 | # expect_identical(roundtrip_vector(x), x)
142 | # })
143 | #
144 | # test_that("converts time to hms", {
145 | # x1 <- structure(1:100, class = "time")
146 | # x2 <- roundtrip_vector(x1)
147 | #
148 | # expect_s3_class(x2, "hms")
149 | # })
150 | #
151 | #
152 | #
153 | #
154 | # test_that("doesn't lose undue precision", {
155 | # base <- ISOdate(2001, 10, 10)
156 | # x1 <- base + 1e-6 * (0:3)
157 | # x2 <- roundtrip_vector(x1)
158 | #
159 | # expect_identical(x1, x2)
160 | # })
161 | # nolint end
162 |
--------------------------------------------------------------------------------
/tests/testthat/test_factor.R:
--------------------------------------------------------------------------------
1 |
2 | context("factor column")
3 |
4 |
5 | # some helper functions
6 | source("helper_fstwrite.R")
7 |
8 |
9 | # Clean testdata directory
10 | if (!file.exists("FactorStore")) {
11 | dir.create("FactorStore")
12 | } else {
13 | file.remove(list.files("FactorStore", full.names = TRUE))
14 | }
15 |
16 |
17 | char_vec <- function(nrofrows) {
18 | sapply(1:nrofrows, function(x) {
19 | paste(sample(LETTERS, sample(1:4, 1)), collapse = "")
20 | }
21 | )
22 | }
23 |
24 |
25 | factor_vec <- function(nrofrows, nroflevels) {
26 | levels <- NULL
27 | while (length(levels) < nroflevels) {
28 | levels <- unique(c(levels, char_vec(nroflevels)))
29 | }
30 |
31 | levels <- levels[1:nroflevels]
32 |
33 | factor(sample(levels, nrofrows, replace = TRUE), levels = levels)
34 | }
35 |
36 |
37 | sample_data <- function(nrofrows, nroflevels) {
38 | data.frame(WFact1 = factor_vec(nrofrows, nroflevels), WFact2 = factor_vec(nrofrows, nroflevels))
39 | }
40 |
41 |
42 | to_frame <- function(x) {
43 | data.frame(x, row.names = NULL, stringsAsFactors = FALSE)
44 | }
45 |
46 |
47 | test_write_read <- function(dt, offset = 3, cap = 3) {
48 | fstwriteproxy(dt, "FactorStore/data1.fst")
49 |
50 | # Read full dataset
51 | data <- fstreadproxy("FactorStore/data1.fst")
52 | expect_equal(dt, data)
53 |
54 | # Read with small offset
55 | data <- fstreadproxy("FactorStore/data1.fst", from = offset)
56 | expect_equal(to_frame(dt[offset:nrow(dt), , drop = FALSE]), data)
57 |
58 | # Read with medium offset
59 | data <- fstreadproxy("FactorStore/data1.fst", from = nrow(dt) - cap)
60 | expect_equal(to_frame(dt[(nrow(dt) - cap):nrow(dt), , drop = FALSE]), data)
61 |
62 | # Read less rows
63 | data <- fstreadproxy("FactorStore/data1.fst", to = cap)
64 | expect_equal(to_frame(dt[1:cap, , drop = FALSE]), data)
65 |
66 | # Read less rows
67 | data <- fstreadproxy("FactorStore/data1.fst", to = nrow(dt) - cap)
68 | expect_equal(to_frame(dt[1:(nrow(dt) - cap), , drop = FALSE]), data)
69 |
70 | # Read less rows with offset
71 | data <- fstreadproxy("FactorStore/data1.fst", from = offset, to = nrow(dt) - cap)
72 | expect_equal(to_frame(dt[offset:(nrow(dt) - cap), , drop = FALSE]), data)
73 | }
74 |
75 |
76 | test_that("Multiple sizes of 1-byte factor columns are stored correctly", {
77 | dt <- sample_data(30, 10)
78 | test_write_read(dt)
79 | test_write_read(dt[1:8, ])
80 | test_write_read(dt[1:7, ])
81 | # test large size here ?
82 | })
83 |
84 |
85 | test_that("Multiple sizes of 2-byte factor columns are stored correctly", {
86 | dt <- sample_data(30, 257)
87 | test_write_read(dt)
88 | test_write_read(dt[1:4, ], 2, 2)
89 | test_write_read(dt[1:3, ], 1, 1)
90 | # test large size here ?
91 | })
92 |
93 |
94 | # with thanks to @martinblostein for tracking the corresponding bug
95 | # see: https://github.com/fstpackage/fst/issues/128
96 | test_that("length 1 factor column with 2 byte level vector is stored correctly", {
97 | df <- data.frame(a = factor("X1", levels = paste0("X", 1:128)))
98 | write_fst(df, "FactorStore/one_row.fst")
99 | x <- read_fst("FactorStore/one_row.fst")
100 |
101 | expect_equal(df, x)
102 | })
103 |
104 |
105 | test_that("Multiple sizes of 4-byte factor columns are stored correctly", {
106 | dt <- sample_data(30, 70000)
107 | test_write_read(dt)
108 | test_write_read(dt[1:8, ])
109 | test_write_read(dt[1:7, ])
110 | # test large size here ?
111 | })
112 |
113 |
114 | test_that("Small factor with a single NA level", {
115 | dt <- data.frame(A = 1:3, B = as.factor(rep(NA, 3)))
116 | fstwriteproxy(dt, "FactorStore/data1.fst")
117 | expect_equal(fstreadproxy("FactorStore/data1.fst"), dt)
118 | })
119 |
120 |
121 | test_that("Single block one-column factor with a single NA level", {
122 | dt <- data.frame(B = as.factor(rep(NA, 10)))
123 | test_write_read(dt)
124 | })
125 |
126 |
127 | test_that("Single block factor with a single NA level", {
128 | dt <- data.frame(A = 1:1000, B = as.factor(rep(NA, 10)))
129 | test_write_read(dt)
130 | })
131 |
132 |
133 | test_that("Medium factor with a single NA level", {
134 | dt <- data.frame(A = 1:10000, B = as.factor(rep(NA, 10000)))
135 | test_write_read(dt)
136 | })
137 |
--------------------------------------------------------------------------------
/CONDUCT.md:
--------------------------------------------------------------------------------
1 |
2 | # Contributor Covenant Code of Conduct
3 |
4 | ## Our Pledge
5 |
6 | We as members, contributors, and leaders pledge to make participation in our
7 | community a harassment-free experience for everyone, regardless of age, body
8 | size, visible or invisible disability, ethnicity, sex characteristics, gender
9 | identity and expression, level of experience, education, socio-economic status,
10 | nationality, personal appearance, race, religion, or sexual identity
11 | and orientation.
12 |
13 | We pledge to act and interact in ways that contribute to an open, welcoming,
14 | diverse, inclusive, and healthy community.
15 |
16 | ## Our Standards
17 |
18 | Examples of behavior that contributes to a positive environment for our
19 | community include:
20 |
21 | * Demonstrating empathy and kindness toward other people
22 | * Being respectful of differing opinions, viewpoints, and experiences
23 | * Giving and gracefully accepting constructive feedback
24 | * Accepting responsibility and apologizing to those affected by our mistakes,
25 | and learning from the experience
26 | * Focusing on what is best not just for us as individuals, but for the
27 | overall community
28 |
29 | Examples of unacceptable behavior include:
30 |
31 | * The use of sexualized language or imagery, and sexual attention or
32 | advances of any kind
33 | * Trolling, insulting or derogatory comments, and personal or political attacks
34 | * Public or private harassment
35 | * Publishing others' private information, such as a physical or email
36 | address, without their explicit permission
37 | * Other conduct which could reasonably be considered inappropriate in a
38 | professional setting
39 |
40 | ## Enforcement Responsibilities
41 |
42 | Community leaders are responsible for clarifying and enforcing our standards of
43 | acceptable behavior and will take appropriate and fair corrective action in
44 | response to any behavior that they deem inappropriate, threatening, offensive,
45 | or harmful.
46 |
47 | Community leaders have the right and responsibility to remove, edit, or reject
48 | comments, commits, code, wiki edits, issues, and other contributions that are
49 | not aligned to this Code of Conduct, and will communicate reasons for moderation
50 | decisions when appropriate.
51 |
52 | ## Scope
53 |
54 | This Code of Conduct applies within all community spaces, and also applies when
55 | an individual is officially representing the community in public spaces.
56 | Examples of representing our community include using an official e-mail address,
57 | posting via an official social media account, or acting as an appointed
58 | representative at an online or offline event.
59 |
60 | ## Enforcement
61 |
62 | Instances of abusive, harassing, or otherwise unacceptable behavior may be
63 | reported to the community leaders responsible for enforcement at
64 | [INSERT CONTACT METHOD].
65 | All complaints will be reviewed and investigated promptly and fairly.
66 |
67 | All community leaders are obligated to respect the privacy and security of the
68 | reporter of any incident.
69 |
70 | ## Enforcement Guidelines
71 |
72 | Community leaders will follow these Community Impact Guidelines in determining
73 | the consequences for any action they deem in violation of this Code of Conduct:
74 |
75 | ### 1. Correction
76 |
77 | **Community Impact**: Use of inappropriate language or other behavior deemed
78 | unprofessional or unwelcome in the community.
79 |
80 | **Consequence**: A private, written warning from community leaders, providing
81 | clarity around the nature of the violation and an explanation of why the
82 | behavior was inappropriate. A public apology may be requested.
83 |
84 | ### 2. Warning
85 |
86 | **Community Impact**: A violation through a single incident or series
87 | of actions.
88 |
89 | **Consequence**: A warning with consequences for continued behavior. No
90 | interaction with the people involved, including unsolicited interaction with
91 | those enforcing the Code of Conduct, for a specified period of time. This
92 | includes avoiding interactions in community spaces as well as external channels
93 | like social media. Violating these terms may lead to a temporary or
94 | permanent ban.
95 |
96 | ### 3. Temporary Ban
97 |
98 | **Community Impact**: A serious violation of community standards, including
99 | sustained inappropriate behavior.
100 |
101 | **Consequence**: A temporary ban from any sort of interaction or public
102 | communication with the community for a specified period of time. No public or
103 | private interaction with the people involved, including unsolicited interaction
104 | with those enforcing the Code of Conduct, is allowed during this period.
105 | Violating these terms may lead to a permanent ban.
106 |
107 | ### 4. Permanent Ban
108 |
109 | **Community Impact**: Demonstrating a pattern of violation of community
110 | standards, including sustained inappropriate behavior, harassment of an
111 | individual, or aggression toward or disparagement of classes of individuals.
112 |
113 | **Consequence**: A permanent ban from any sort of public interaction within
114 | the community.
115 |
116 | ## Attribution
117 |
118 | This Code of Conduct is adapted from the [Contributor Covenant][homepage],
119 | version 2.0, available at
120 | https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
121 |
122 | Community Impact Guidelines were inspired by [Mozilla's code of conduct
123 | enforcement ladder](https://github.com/mozilla/diversity).
124 |
125 | [homepage]: https://www.contributor-covenant.org
126 |
127 | For answers to common questions about this code of conduct, see the FAQ at
128 | https://www.contributor-covenant.org/faq. Translations are available at
129 | https://www.contributor-covenant.org/translations.
130 |
--------------------------------------------------------------------------------
/src/RcppExports.cpp:
--------------------------------------------------------------------------------
1 | // Generated by using Rcpp::compileAttributes() -> do not edit by hand
2 | // Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
3 |
4 | #include
5 |
6 | using namespace Rcpp;
7 |
8 | #ifdef RCPP_USE_GLOBAL_ROSTREAM
9 | Rcpp::Rostream& Rcpp::Rcout = Rcpp::Rcpp_cout_get();
10 | Rcpp::Rostream& Rcpp::Rcerr = Rcpp::Rcpp_cerr_get();
11 | #endif
12 |
13 | // fststore
14 | SEXP fststore(Rcpp::String fileName, SEXP table, SEXP compression, SEXP uniformEncoding);
15 | RcppExport SEXP _fst_fststore(SEXP fileNameSEXP, SEXP tableSEXP, SEXP compressionSEXP, SEXP uniformEncodingSEXP) {
16 | BEGIN_RCPP
17 | Rcpp::RObject rcpp_result_gen;
18 | Rcpp::RNGScope rcpp_rngScope_gen;
19 | Rcpp::traits::input_parameter< Rcpp::String >::type fileName(fileNameSEXP);
20 | Rcpp::traits::input_parameter< SEXP >::type table(tableSEXP);
21 | Rcpp::traits::input_parameter< SEXP >::type compression(compressionSEXP);
22 | Rcpp::traits::input_parameter< SEXP >::type uniformEncoding(uniformEncodingSEXP);
23 | rcpp_result_gen = Rcpp::wrap(fststore(fileName, table, compression, uniformEncoding));
24 | return rcpp_result_gen;
25 | END_RCPP
26 | }
27 | // fstmetadata
28 | SEXP fstmetadata(Rcpp::String fileName);
29 | RcppExport SEXP _fst_fstmetadata(SEXP fileNameSEXP) {
30 | BEGIN_RCPP
31 | Rcpp::RObject rcpp_result_gen;
32 | Rcpp::RNGScope rcpp_rngScope_gen;
33 | Rcpp::traits::input_parameter< Rcpp::String >::type fileName(fileNameSEXP);
34 | rcpp_result_gen = Rcpp::wrap(fstmetadata(fileName));
35 | return rcpp_result_gen;
36 | END_RCPP
37 | }
38 | // fstretrieve
39 | SEXP fstretrieve(Rcpp::String fileName, SEXP columnSelection, SEXP startRow, SEXP endRow);
40 | RcppExport SEXP _fst_fstretrieve(SEXP fileNameSEXP, SEXP columnSelectionSEXP, SEXP startRowSEXP, SEXP endRowSEXP) {
41 | BEGIN_RCPP
42 | Rcpp::RObject rcpp_result_gen;
43 | Rcpp::RNGScope rcpp_rngScope_gen;
44 | Rcpp::traits::input_parameter< Rcpp::String >::type fileName(fileNameSEXP);
45 | Rcpp::traits::input_parameter< SEXP >::type columnSelection(columnSelectionSEXP);
46 | Rcpp::traits::input_parameter< SEXP >::type startRow(startRowSEXP);
47 | Rcpp::traits::input_parameter< SEXP >::type endRow(endRowSEXP);
48 | rcpp_result_gen = Rcpp::wrap(fstretrieve(fileName, columnSelection, startRow, endRow));
49 | return rcpp_result_gen;
50 | END_RCPP
51 | }
52 | // fsthasher
53 | SEXP fsthasher(SEXP rawVec, SEXP seed, SEXP blockHash);
54 | RcppExport SEXP _fst_fsthasher(SEXP rawVecSEXP, SEXP seedSEXP, SEXP blockHashSEXP) {
55 | BEGIN_RCPP
56 | Rcpp::RObject rcpp_result_gen;
57 | Rcpp::RNGScope rcpp_rngScope_gen;
58 | Rcpp::traits::input_parameter< SEXP >::type rawVec(rawVecSEXP);
59 | Rcpp::traits::input_parameter< SEXP >::type seed(seedSEXP);
60 | Rcpp::traits::input_parameter< SEXP >::type blockHash(blockHashSEXP);
61 | rcpp_result_gen = Rcpp::wrap(fsthasher(rawVec, seed, blockHash));
62 | return rcpp_result_gen;
63 | END_RCPP
64 | }
65 | // fstcomp
66 | SEXP fstcomp(SEXP rawVec, SEXP compressor, SEXP compression, SEXP hash);
67 | RcppExport SEXP _fst_fstcomp(SEXP rawVecSEXP, SEXP compressorSEXP, SEXP compressionSEXP, SEXP hashSEXP) {
68 | BEGIN_RCPP
69 | Rcpp::RObject rcpp_result_gen;
70 | Rcpp::RNGScope rcpp_rngScope_gen;
71 | Rcpp::traits::input_parameter< SEXP >::type rawVec(rawVecSEXP);
72 | Rcpp::traits::input_parameter< SEXP >::type compressor(compressorSEXP);
73 | Rcpp::traits::input_parameter< SEXP >::type compression(compressionSEXP);
74 | Rcpp::traits::input_parameter< SEXP >::type hash(hashSEXP);
75 | rcpp_result_gen = Rcpp::wrap(fstcomp(rawVec, compressor, compression, hash));
76 | return rcpp_result_gen;
77 | END_RCPP
78 | }
79 | // fstdecomp
80 | SEXP fstdecomp(SEXP rawVec);
81 | RcppExport SEXP _fst_fstdecomp(SEXP rawVecSEXP) {
82 | BEGIN_RCPP
83 | Rcpp::RObject rcpp_result_gen;
84 | Rcpp::RNGScope rcpp_rngScope_gen;
85 | Rcpp::traits::input_parameter< SEXP >::type rawVec(rawVecSEXP);
86 | rcpp_result_gen = Rcpp::wrap(fstdecomp(rawVec));
87 | return rcpp_result_gen;
88 | END_RCPP
89 | }
90 | // getnrofthreads
91 | SEXP getnrofthreads();
92 | RcppExport SEXP _fst_getnrofthreads() {
93 | BEGIN_RCPP
94 | Rcpp::RObject rcpp_result_gen;
95 | Rcpp::RNGScope rcpp_rngScope_gen;
96 | rcpp_result_gen = Rcpp::wrap(getnrofthreads());
97 | return rcpp_result_gen;
98 | END_RCPP
99 | }
100 | // setnrofthreads
101 | int setnrofthreads(SEXP nrOfThreads);
102 | RcppExport SEXP _fst_setnrofthreads(SEXP nrOfThreadsSEXP) {
103 | BEGIN_RCPP
104 | Rcpp::RObject rcpp_result_gen;
105 | Rcpp::RNGScope rcpp_rngScope_gen;
106 | Rcpp::traits::input_parameter< SEXP >::type nrOfThreads(nrOfThreadsSEXP);
107 | rcpp_result_gen = Rcpp::wrap(setnrofthreads(nrOfThreads));
108 | return rcpp_result_gen;
109 | END_RCPP
110 | }
111 | // restore_after_fork
112 | void restore_after_fork(bool restore);
113 | RcppExport SEXP _fst_restore_after_fork(SEXP restoreSEXP) {
114 | BEGIN_RCPP
115 | Rcpp::RNGScope rcpp_rngScope_gen;
116 | Rcpp::traits::input_parameter< bool >::type restore(restoreSEXP);
117 | restore_after_fork(restore);
118 | return R_NilValue;
119 | END_RCPP
120 | }
121 | // hasopenmp
122 | SEXP hasopenmp();
123 | RcppExport SEXP _fst_hasopenmp() {
124 | BEGIN_RCPP
125 | Rcpp::RObject rcpp_result_gen;
126 | Rcpp::RNGScope rcpp_rngScope_gen;
127 | rcpp_result_gen = Rcpp::wrap(hasopenmp());
128 | return rcpp_result_gen;
129 | END_RCPP
130 | }
131 |
132 | static const R_CallMethodDef CallEntries[] = {
133 | {"_fst_fststore", (DL_FUNC) &_fst_fststore, 4},
134 | {"_fst_fstmetadata", (DL_FUNC) &_fst_fstmetadata, 1},
135 | {"_fst_fstretrieve", (DL_FUNC) &_fst_fstretrieve, 4},
136 | {"_fst_fsthasher", (DL_FUNC) &_fst_fsthasher, 3},
137 | {"_fst_fstcomp", (DL_FUNC) &_fst_fstcomp, 4},
138 | {"_fst_fstdecomp", (DL_FUNC) &_fst_fstdecomp, 1},
139 | {"_fst_getnrofthreads", (DL_FUNC) &_fst_getnrofthreads, 0},
140 | {"_fst_setnrofthreads", (DL_FUNC) &_fst_setnrofthreads, 1},
141 | {"_fst_restore_after_fork", (DL_FUNC) &_fst_restore_after_fork, 1},
142 | {"_fst_hasopenmp", (DL_FUNC) &_fst_hasopenmp, 0},
143 | {NULL, NULL, 0}
144 | };
145 |
146 | RcppExport void R_init_fst(DllInfo *dll) {
147 | R_registerRoutines(dll, NULL, CallEntries, NULL, NULL);
148 | R_useDynamicSymbols(dll, FALSE);
149 | }
150 |
--------------------------------------------------------------------------------
/tests/testthat/test_compress.R:
--------------------------------------------------------------------------------
1 |
2 | context("in-memory compression")
3 |
4 |
5 | # Sample raw vector
6 | raw_vector <- function(length) {
7 | as.raw(sample(1:10, length, replace = TRUE))
8 | }
9 |
10 | raw_vec <- raw_vector(100) # vector size less than single block
11 |
12 |
13 | test_that("interface for compressing raw vectors", {
14 | y <- compress_fst(raw_vec)
15 | expect_equal(typeof(y), "raw")
16 |
17 | expect_error(compress_fst(5), "Parameter x is not set to a raw vector")
18 |
19 | expect_error(compress_fst(raw_vec, 4), "Parameter compressor should be set")
20 |
21 | expect_error(compress_fst(raw_vec, compression = TRUE), "Parameter compression should be a numeric value")
22 |
23 | expect_error(compress_fst(raw_vec[0], compressor = "LZ4", compression = 0), "Source contains no data")
24 | })
25 |
26 |
27 | # rest write / read cycle for single vector and compression settings
28 | test_round_cycle <- function(vec, compressor, compression) {
29 | y <- compress_fst(raw_vec, compressor, compression)
30 | z <- decompress_fst(y)
31 |
32 | expect_equal(raw_vec, z, info = paste("compressor:", compressor, "compression:", compression)) # return type
33 |
34 | y
35 | }
36 |
37 |
38 | # rest write / read cycle for multiple compression settings
39 | test_vec <- function(raw_vec) {
40 | y1 <- test_round_cycle(raw_vec, "LZ4", 0)
41 | y2 <- test_round_cycle(raw_vec, "LZ4", 100)
42 | y3 <- test_round_cycle(raw_vec, "ZSTD", 0)
43 | y4 <- test_round_cycle(raw_vec, "ZSTD", 100)
44 |
45 | list(y1, y2, y3, y4)
46 | }
47 |
48 |
49 | test_that("compress round cycle small vector", {
50 | # single core
51 | threads_fst(1)
52 | comp_result1 <- test_vec(raw_vec)
53 |
54 | # dual core (max on CRAN)
55 | threads_fst(2)
56 | comp_result2 <- test_vec(raw_vec)
57 |
58 | # result independent of the number of blocks used
59 | expect_equal(comp_result1, comp_result2)
60 | })
61 |
62 |
63 | test_that("compress round cycle single block", {
64 | # compress_fst prefers 48 block of at least 16384 bytes (16 kB)
65 | raw_vec <- raw_vector(16384) # exactly single block
66 |
67 | # single core single block
68 | threads_fst(1)
69 | comp_result1 <- test_vec(raw_vec)
70 |
71 | # only 1 core will be active on a single block
72 | threads_fst(2)
73 | comp_result2 <- test_vec(raw_vec)
74 |
75 | # result independent of the number of blocks used
76 | expect_equal(comp_result1, comp_result2)
77 | })
78 |
79 |
80 | test_that("compress round cycle around single block", {
81 | # compress_fst prefers 48 block of at least 16384 bytes (16 kB)
82 | raw_vec <- raw_vector(16383) # exactly single block minus 1
83 |
84 | # single core single block
85 | threads_fst(1)
86 | comp_result1 <- test_vec(raw_vec)
87 |
88 | # only 1 core will be active on a single block
89 | threads_fst(2)
90 | comp_result2 <- test_vec(raw_vec)
91 |
92 | # result independent of the number of blocks used
93 | expect_equal(comp_result1, comp_result2)
94 |
95 | raw_vec <- raw_vector(16385) # exactly single block plus 1
96 |
97 | # single core single block
98 | threads_fst(1)
99 | comp_result1 <- test_vec(raw_vec)
100 |
101 | # 2 cores will be active on two blocks
102 | threads_fst(2)
103 | comp_result2 <- test_vec(raw_vec)
104 |
105 | # result independent of the number of blocks used
106 | expect_equal(comp_result1, comp_result2)
107 | })
108 |
109 |
110 | test_that("compress round cycle multiple blocks per thread", {
111 | raw_vec <- raw_vector(100000)
112 |
113 | threads_fst(1)
114 | comp_result1 <- test_vec(raw_vec)
115 |
116 | threads_fst(2)
117 | comp_result2 <- test_vec(raw_vec)
118 |
119 | # result independent of the number of blocks used
120 | expect_equal(comp_result1, comp_result2)
121 | })
122 |
123 |
124 | test_that("compress round cycle blocksize larger than 16kB", {
125 | raw_vec <- raw_vector(1000000)
126 |
127 | threads_fst(1)
128 | comp_result1 <- test_vec(raw_vec)
129 |
130 | threads_fst(2)
131 | comp_result2 <- test_vec(raw_vec)
132 |
133 | # result independent of the number of blocks used
134 | expect_equal(comp_result1, comp_result2)
135 | })
136 |
137 |
138 | raw_vec <- raw_vector(50000) # 4 blocks
139 |
140 |
141 | test_that("erroneous compressed data", {
142 | # Test LZ4 compressor
143 | z <- compress_fst(raw_vec, compressor = "LZ4", compression = 100) # note: very bad compression ratio
144 |
145 | y <- z
146 | y[41:48] <- as.raw(0L) # mess up second block offset
147 | expect_error(decompress_fst(y), "Incorrect header information found")
148 |
149 | y <- z
150 | y[17:24] <- as.raw(0L) # set vector length to zero
151 | expect_error(decompress_fst(y), "Incorrect header information found")
152 |
153 | y <- decompress_fst(z)
154 | expect_equal(raw_vec, y) # return type
155 |
156 | # Test ZSTD compressor
157 | y <- compress_fst(raw_vec, compressor = "ZSTD", compression = 0)
158 | z <- decompress_fst(y)
159 | expect_equal(raw_vec, z) # return type
160 |
161 | y <- compress_fst(raw_vec, compressor = "ZSTD", compression = 100) # maximum compression
162 | z <- decompress_fst(y)
163 | expect_equal(raw_vec, z) # return type
164 |
165 | # Mess up compressed data block
166 | # Header has length 76, so data of first block starts at byte 77
167 |
168 | # This error is catched by ZSTD
169 | y[77] <- as.raw(0L) # set vector length to zero
170 | expect_error(decompress_fst(y), "An error was detected in the compressed data stream")
171 |
172 | # If using block hashes, erro is catched by fst
173 | y <- compress_fst(raw_vec, compressor = "ZSTD", compression = 100, hash = TRUE) # hash data blocks
174 | y[77] <- as.raw(0L) # set vector length to zero
175 | expect_error(decompress_fst(y), "Incorrect input vector")
176 | })
177 |
178 |
179 | test_that("hash can use custom seed", {
180 | hash1 <- hash_fst(raw_vec)
181 | hash2 <- hash_fst(raw_vec, 345345)
182 |
183 | # alter vector in two places
184 | raw_vec[100] <- as.raw((as.integer(raw_vec[100]) + 2) %% 256) ## nolint
185 | raw_vec[200] <- as.raw((as.integer(raw_vec[200]) + 2) %% 256) ## nolint
186 | hash3 <- hash_fst(raw_vec)
187 |
188 | expect_true(sum(hash1 != hash2) == 2)
189 | expect_true(sum(hash1 != hash3) == 2)
190 | })
191 |
192 |
193 | test_that("block_hash can be set", {
194 | hash1 <- hash_fst(raw_vec)
195 |
196 | # larger than 1 block raw vectors give different results
197 | hash4 <- hash_fst(raw_vec, block_hash = FALSE) # single threaded hash
198 | expect_true(sum(hash1 != hash4) == 2)
199 |
200 | small_raw_vec <- as.raw(rep(0, 10))
201 | hash1 <- hash_fst(small_raw_vec)
202 |
203 | # smaller than 1 block raw vectors give identical results
204 | hash4 <- hash_fst(small_raw_vec, block_hash = FALSE) # single threaded hash
205 | expect_true(sum(hash1 != hash4) == 0)
206 | })
207 |
208 |
209 |
210 | test_that("argument error", {
211 | expect_error(compress_fst(1), "Parameter x is not set to a raw vector")
212 |
213 | expect_error(hash_fst(as.raw(1), "no integer"), "Please specify an integer value for the hash seed")
214 |
215 | expect_error(hash_fst(1), "Please specify a raw vector as input parameter x")
216 |
217 | expect_error(hash_fst(as.raw(1), block_hash = 1), "Please specify a logical value for parameter block_hash")
218 |
219 | })
220 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 |
2 |
3 |
4 |
5 |
6 | [](https://github.com/fstpackage/fst/actions/workflows/R-CMD-check.yaml)
8 | [](https://www.gnu.org/licenses/agpl-3.0)
10 | [](https://cran.r-project.org/package=fst)
11 | [](https://fastverse.r-universe.dev/ui#package:fastverse)
13 | [](https://app.codecov.io/gh/fstpackage/fst)
14 | [](http://cran.rstudio.com/web/packages/fst/index.html)
15 | [](http://cran.rstudio.com/web/packages/fst/index.html)
16 |
17 | ## Overview
18 |
19 | The [*fst* package](https://github.com/fstpackage/fst) for R provides a
20 | fast, easy and flexible way to serialize data frames. With access speeds
21 | of multiple GB/s, *fst* is specifically designed to unlock the potential
22 | of high speed solid state disks that can be found in most modern
23 | computers. Data frames stored in the *fst* format have full random
24 | access, both in column and rows.
25 |
26 | The figure below compares the read and write performance of the *fst*
27 | package to various alternatives.
28 |
29 | | Method | Format | Time (ms) | Size (MB) | Speed (MB/s) | N |
30 | |:--------------|:--------|:----------|:----------|:-------------|:--------|
31 | | readRDS | bin | 1577 | 1000 | 633 | 112 |
32 | | saveRDS | bin | 2042 | 1000 | 489 | 112 |
33 | | fread | csv | 2925 | 1038 | 410 | 232 |
34 | | fwrite | csv | 2790 | 1038 | 358 | 241 |
35 | | read_feather | bin | 3950 | 813 | 253 | 112 |
36 | | write_feather | bin | 1820 | 813 | 549 | 112 |
37 | | **read_fst** | **bin** | **457** | **303** | **2184** | **282** |
38 | | **write_fst** | **bin** | **314** | **303** | **3180** | **291** |
39 |
40 | These benchmarks were performed on a laptop (i7 4710HQ @2.5 GHz) with a
41 | reasonably fast SSD (M.2 Samsung SM951) using the dataset defined below.
42 | Parameter *Speed* was calculated by dividing the in-memory size of the
43 | data frame by the measured time. These results are also visualized in
44 | the following graph:
45 |
46 | 
47 |
48 | As can be seen from the figure, the measured speeds for the *fst*
49 | package are very high and even top the maximum drive speed of the SSD
50 | used. The package accomplishes this by an effective combination of
51 | multi-threading and compression. The on-disk file sizes of *fst* files
52 | are also much smaller than that of the other formats tested. This is an
53 | added benefit of *fst*’s use of type-specific compressors on each stored
54 | column.
55 |
56 | In addition to methods for data frame serialization, *fst* also provides
57 | methods for multi-threaded in-memory compression with the popular LZ4
58 | and ZSTD compressors and an extremely fast multi-threaded hasher.
59 |
60 | ## Multi-threading
61 |
62 | The *fst* package relies heavily on multi-threading to boost the read-
63 | and write speed of data frames. To maximize throughput, *fst* compresses
64 | and decompresses data *in the background* and tries to keep the disk
65 | busy writing and reading data at the same time.
66 |
67 | ## Installation
68 |
69 | The easiest way to install the package is from CRAN:
70 |
71 | ``` r
72 | install.packages("fst")
73 | ```
74 |
75 | You can also use the development version from GitHub:
76 |
77 | ``` r
78 | # install.packages("devtools")
79 | devtools::install_github("fstpackage/fst", ref = "develop")
80 | ```
81 |
82 | ## Basic usage
83 |
84 | Using *fst* is simple. Data can be stored and retrieved using methods
85 | *write_fst* and *read_fst*:
86 |
87 | ``` r
88 | # Generate some random data frame with 10 million rows and various column types
89 | nr_of_rows <- 1e7
90 |
91 | df <- data.frame(
92 | Logical = sample(c(TRUE, FALSE, NA), prob = c(0.85, 0.1, 0.05), nr_of_rows, replace = TRUE),
93 | Integer = sample(1L:100L, nr_of_rows, replace = TRUE),
94 | Real = sample(sample(1:10000, 20) / 100, nr_of_rows, replace = TRUE),
95 | Factor = as.factor(sample(labels(UScitiesD), nr_of_rows, replace = TRUE))
96 | )
97 |
98 | # Store the data frame to disk
99 | write_fst(df, "dataset.fst")
100 |
101 | # Retrieve the data frame again
102 | df <- read_fst("dataset.fst")
103 | ```
104 |
105 | *Note: the dataset defined in this example code was also used to obtain
106 | the benchmark results shown in the introduction.*
107 |
108 | ## Random access
109 |
110 | The *fst* file format provides full random access to stored datasets.
111 | You can retrieve a selection of columns and rows with:
112 |
113 | ``` r
114 | df_subset <- read_fst("dataset.fst", c("Logical", "Factor"), from = 2000, to = 5000)
115 | ```
116 |
117 | This reads rows 2000 to 5000 from columns *Logical* and *Factor* without
118 | actually touching any other data in the stored file. That means that a
119 | subset can be read from file **without reading the complete file
120 | first**. This is different from, say, *readRDS* or *read_feather* where
121 | you have to read the complete file or column before you can make a
122 | subset.
123 |
124 | ## Compression
125 |
126 | For compression the excellent and speedy
127 | [LZ4](https://github.com/lz4/lz4) and
128 | [ZSTD](https://github.com/facebook/zstd) compression algorithms are
129 | used. These compressors (in combination with type-specific bit filters),
130 | enable *fst* to achieve high compression speeds at reasonable
131 | compression factors. The compression factor can be tuned from 0
132 | (minimum) to 100 (maximum):
133 |
134 | ``` r
135 | write_fst(df, "dataset.fst", 100) # use maximum compression
136 | ```
137 |
138 | Compression reduces the size of the *fst* file that holds your data. But
139 | because the (de-)compression is done *on background threads*, it can
140 | increase the total read- and write speed as well. The graph below shows
141 | how the use of multiple threads enhances the read and write speed of our
142 | sample dataset.
143 |
144 | 
145 |
146 | The *csv* format used by the *fread* and *fwrite* methods of package
147 | *data.table* is actually a human-readable text format and not a binary
148 | format. Normally, binary formats would be much faster than the *csv*
149 | format, because *csv* takes more space on disk, is row based,
150 | uncompressed and needs to be parsed into a computer-native format to
151 | have any meaning. So any serializer that’s working on *csv* has an
152 | enormous disadvantage as compared to binary formats. Yet, the results
153 | show that *data.table* is on par with binary formats and when more
154 | threads are used, it can even be faster. Because of this impressive
155 | performance, it was included in the graph for comparison.
156 |
157 | ## Bindings in other languages
158 |
159 | **Julia**:
160 | [**`FstFileFormat.jl`**](https://github.com/xiaodaigh/FstFileFormat.jl)
161 | A naive Julia binding using RCall.jl
162 |
163 | > **Note to users**: From CRAN release v0.8.0, the *fst* format is
164 | > stable and backwards compatible. That means that all *fst* files
165 | > generated with package v0.8.0 or later can be read by future versions
166 | > of the package.
167 |
--------------------------------------------------------------------------------
/tests/testthat/test_meta.R:
--------------------------------------------------------------------------------
1 |
2 | context("metadata")
3 |
4 |
5 | library(data.table)
6 |
7 |
8 | require_extensions <- function() {
9 | requireNamespace("nanotime", quietly = TRUE) && requireNamespace("bit64", quietly = TRUE)
10 | }
11 |
12 | # Clean testdata directory
13 | if (!file.exists("testdata")) {
14 | dir.create("testdata")
15 | } else {
16 | file.remove(list.files("testdata", full.names = TRUE))
17 | }
18 |
19 |
20 | posix_i <- as.integer(as.POSIXct("2001-02-03")) + 1L:5L
21 | class(posix_i) <- c("POSIXct", "POSIXt")
22 |
23 | date_i <- as.integer(Sys.Date() + 1:10)
24 | class(date_i) <- "Date"
25 |
26 | difftime <- (Sys.time() + 1:10) - Sys.time()
27 | difftime_int <- difftime
28 | mode(difftime_int) <- "integer"
29 |
30 |
31 | # Sample data
32 | x <- data.table(
33 | A = 1:10,
34 | B = sample(c(TRUE, FALSE, NA), 10, replace = TRUE),
35 | C = sample(1:100, 10) / 100,
36 | D = Sys.Date() + 1:10,
37 | E = sample(LETTERS, 10),
38 | F = factor(sample(LETTERS, 10)),
39 | G = as.POSIXct("2001-02-03") + 1:10,
40 | H = posix_i,
41 | I = date_i,
42 | J = as.raw(sample(0:255, 10)),
43 | K = ordered(sample(LETTERS, 10)),
44 | L = difftime,
45 | M = difftime_int,
46 | N = as.ITime(Sys.time() + 1:10)
47 | )
48 |
49 |
50 | if (require_extensions()) {
51 | x$O <- bit64::as.integer64(101:110) # nolint
52 | x$P <- nanotime::nanotime(2:11) # nolint
53 | }
54 |
55 |
56 | test_that("v0.7.2 interface still works", {
57 | fstwriteproxy(x, "testdata/meta.fst")
58 |
59 | x <- fst.metadata("testdata/meta.fst")
60 |
61 | expect_true(!is.null(x))
62 | })
63 |
64 |
65 | test_that("format contains fst magic value", {
66 | zz <- file("testdata/meta.fst", "rb") # open file in binary mode
67 | header_hash <- readBin(zz, integer(), 12)
68 | close(zz)
69 |
70 | expect_equal(header_hash[3], 1) # fst format version (even numbers are dev versions)
71 | expect_equal(header_hash[12], 1346453840) # fst magic number
72 | expect_equal(header_hash[5], 0) # free bytes
73 | expect_equal(header_hash[6], 0) # free bytes
74 | })
75 |
76 |
77 | test_that("Read meta of uncompressed file", {
78 | fstwriteproxy(x, "testdata/meta.fst")
79 | y <- fstmetaproxy("testdata/meta.fst")
80 |
81 | expect_equal(basename(y$path), basename("meta.fst"))
82 | expect_equal(y$nrOfRows, 10)
83 | expect_equal(y$keys, NULL)
84 | expect_equal(y$columnNames, LETTERS[1:16][seq_len(ncol(x))])
85 | expect_equal(y$columnBaseTypes, c(4, 6, 5, 5, 2, 3, 5, 4, 4, 8, 3, 5, 4, 4, 7, 7)[seq_len(ncol(x))])
86 | expect_equal(y$columnTypes, c(5, 15, 10, 11, 2, 3, 12, 6, 8, 18, 4, 13, 7, 9, 16, 17)[seq_len(ncol(x))])
87 | })
88 |
89 |
90 | test_that("Read meta of compressed file", {
91 | fstwriteproxy(x, "testdata/meta.fst", compress = 100)
92 | y <- fstmetaproxy("testdata/meta.fst")
93 |
94 | expect_equal(basename(y$path), "meta.fst")
95 | expect_equal(y$nrOfRows, 10)
96 | expect_equal(y$keys, NULL)
97 | expect_equal(y$columnNames, LETTERS[1:16][seq_len(ncol(x))])
98 | expect_equal(y$columnBaseTypes, c(4, 6, 5, 5, 2, 3, 5, 4, 4, 8, 3, 5, 4, 4, 7, 7)[seq_len(ncol(x))])
99 | expect_equal(y$columnTypes, c(5, 15, 10, 11, 2, 3, 12, 6, 8, 18, 4, 13, 7, 9, 16, 17)[seq_len(ncol(x))])
100 | })
101 |
102 |
103 | test_that("Print meta data without keys", {
104 | fstwriteproxy(x, "testdata/meta.fst", compress = 100)
105 | y <- fstmetaproxy("testdata/meta.fst")
106 | res <- capture_output(print(fstmetaproxy("testdata/meta.fst")))
107 |
108 | if (require_extensions()) {
109 | expect_equal(res, paste(
110 | "\n10 rows, 16 columns (meta.fst)\n",
111 | "* 'A': integer",
112 | "* 'B': logical",
113 | "* 'C': double",
114 | "* 'D': Date",
115 | "* 'E': character",
116 | "* 'F': factor",
117 | "* 'G': POSIXct",
118 | "* 'H': POSIXct",
119 | "* 'I': IDate",
120 | "* 'J': raw",
121 | "* 'K': ordered factor",
122 | "* 'L': difftime",
123 | "* 'M': difftime",
124 | "* 'N': ITime",
125 | "* 'O': integer64",
126 | "* 'P': nanotime",
127 | sep = "\n"
128 | ))
129 | } else {
130 | expect_equal(res, paste(
131 | "\n10 rows, 14 columns (meta.fst)\n",
132 | "* 'A': integer",
133 | "* 'B': logical",
134 | "* 'C': double",
135 | "* 'D': Date",
136 | "* 'E': character",
137 | "* 'F': factor",
138 | "* 'G': POSIXct",
139 | "* 'H': POSIXct",
140 | "* 'I': IDate",
141 | "* 'J': raw",
142 | "* 'K': ordered factor",
143 | "* 'L': difftime",
144 | "* 'M': difftime",
145 | "* 'N': ITime",
146 | sep = "\n"
147 | ))
148 | }
149 | })
150 |
151 |
152 | # raw sorting not supported
153 | x$J <- NULL # nolint
154 |
155 |
156 | test_that("Read meta of sorted file", {
157 | z <- copy(x)
158 | setkey(z, B, C)
159 | fstwriteproxy(z, "testdata/meta.fst")
160 | y <- fstmetaproxy("testdata/meta.fst")
161 |
162 | expect_equal(basename(y$path), "meta.fst")
163 | expect_equal(y$nrOfRows, 10)
164 | expect_equal(y$keys, c("B", "C"))
165 | expect_equal(y$columnNames, LETTERS[c(1:9, 11:16)][seq_len(ncol(x))])
166 | expect_equal(y$columnBaseTypes, c(4, 6, 5, 5, 2, 3, 5, 4, 4, 3, 5, 4, 4, 7, 7)[seq_len(ncol(x))])
167 | expect_equal(y$columnTypes, c(5, 15, 10, 11, 2, 3, 12, 6, 8, 4, 13, 7, 9, 16, 17)[seq_len(ncol(x))])
168 | })
169 |
170 |
171 | test_that("Print meta data with keys", {
172 | z <- copy(x)
173 | setkey(z, D, K, B)
174 | fstwriteproxy(z, "testdata/meta.fst", compress = 100)
175 | y <- fstmetaproxy("testdata/meta.fst")
176 | res <- capture_output(print(fstmetaproxy("testdata/meta.fst")))
177 |
178 | if (require_extensions()) {
179 | expect_equal(res, paste(
180 | "\n10 rows, 15 columns (meta.fst)\n",
181 | "* 'D': Date (key 1)",
182 | "* 'K': ordered factor (key 2)",
183 | "* 'B': logical (key 3)",
184 | "* 'A': integer",
185 | "* 'C': double",
186 | "* 'E': character",
187 | "* 'F': factor",
188 | "* 'G': POSIXct",
189 | "* 'H': POSIXct",
190 | "* 'I': IDate",
191 | "* 'L': difftime",
192 | "* 'M': difftime",
193 | "* 'N': ITime",
194 | "* 'O': integer64",
195 | "* 'P': nanotime",
196 | sep = "\n"
197 | ))
198 | } else {
199 | expect_equal(res, paste(
200 | "\n10 rows, 13 columns (meta.fst)\n",
201 | "* 'D': Date (key 1)",
202 | "* 'K': ordered factor (key 2)",
203 | "* 'B': logical (key 3)",
204 | "* 'A': integer",
205 | "* 'C': double",
206 | "* 'E': character",
207 | "* 'F': factor",
208 | "* 'G': POSIXct",
209 | "* 'H': POSIXct",
210 | "* 'I': IDate",
211 | "* 'L': difftime",
212 | "* 'M': difftime",
213 | "* 'N': ITime",
214 | sep = "\n"
215 | ))
216 | }
217 | })
218 |
219 |
220 | test_that("Print meta data with keys and unordered columns", {
221 | skip_if_not(require_extensions())
222 |
223 | colnames(x) <- LETTERS[seq.int(ncol(x), 1)]
224 |
225 | setkey(x, L, F, N) # nolint
226 | fstwriteproxy(x, "testdata/meta.fst", compress = 100)
227 | y <- fstmetaproxy("testdata/meta.fst")
228 | res <- capture_output(print(fstmetaproxy("testdata/meta.fst")))
229 |
230 | # note that columns are printed in original order (except keys)
231 | expect_equal(res, paste(
232 | "\n10 rows, 15 columns (meta.fst)\n",
233 | "* 'L': Date (key 1)",
234 | "* 'F': ordered factor (key 2)",
235 | "* 'N': logical (key 3)",
236 | "* 'O': integer",
237 | "* 'M': double",
238 | "* 'K': character",
239 | "* 'J': factor",
240 | "* 'I': POSIXct",
241 | "* 'H': POSIXct",
242 | "* 'G': IDate",
243 | "* 'E': difftime",
244 | "* 'D': difftime",
245 | "* 'C': ITime",
246 | "* 'B': integer64",
247 | "* 'A': nanotime",
248 | sep = "\n"
249 | ))
250 | })
251 |
--------------------------------------------------------------------------------
/tests/testthat/test_fst_table.R:
--------------------------------------------------------------------------------
1 |
2 | context("fst_table")
3 |
4 |
5 | # clean testdata directory
6 | if (!file.exists("testdata")) {
7 | dir.create("testdata")
8 | } else {
9 | file.remove(list.files("testdata", full.names = TRUE))
10 | }
11 |
12 |
13 | # generate sample data and store
14 | df <- data.frame(X = 1:26, Y = LETTERS, Z = runif(26, 4, 7), stringsAsFactors = FALSE)
15 | test_file <- "testdata/fst_table.fst"
16 | write_fst(df, test_file)
17 | x <- fst(test_file)
18 |
19 | # single column table
20 | df2 <- df["X"]
21 | test_file2 <- "testdata/fst_table2.fst"
22 | write_fst(df2, test_file2)
23 | y <- fst(test_file2)
24 |
25 |
26 | # see issues #175 and #136
27 | test_that("fst_table does throw normalizePath error on non-existing file", {
28 | expect_error(fst("testdata/non_existing.fst"), "Error opening fst file for reading")
29 | })
30 |
31 |
32 | test_that("fst_table returns a fst_table class object", {
33 | expect_equal(class(x), "fst_table")
34 |
35 | str_object <- unclass(x)
36 | expect_equal(names(str_object), c("meta", "col_selection", "row_selection", "old_format"))
37 | })
38 |
39 |
40 | test_that("fst_table has basic data.frame interface", {
41 | expect_equal(as.data.frame(x), as.data.frame(df))
42 |
43 | expect_equal(x[2], df[2])
44 |
45 | expect_equal(x[2.6], df[2.6])
46 |
47 | expect_equal(x[TRUE], df[TRUE])
48 |
49 | expect_equal(x[c(1.1, 2)], df[c(1.1, 2)])
50 |
51 | expect_equal(x[c(TRUE, FALSE)], df[c(TRUE, FALSE)])
52 |
53 | expect_equal(x[c(TRUE, FALSE, TRUE)], df[c(TRUE, FALSE, TRUE)])
54 |
55 | expect_equal(as.data.frame(x, row.names = LETTERS), as.data.frame(df, row.names = LETTERS))
56 |
57 | expect_equal(as.list(x), as.list(df))
58 |
59 | expect_equal(x[["Y"]], df[["Y"]])
60 |
61 | expect_equal(x[["S"]], df[["S"]])
62 |
63 | expect_equal(x$X, df$X)
64 |
65 | expect_equal(x$S, df$S)
66 |
67 | expect_equal(nrow(x), nrow(df))
68 |
69 | expect_equal(ncol(x), ncol(df))
70 |
71 | expect_equal(dim(x), dim(df))
72 |
73 | expect_equal(dimnames(x), dimnames(df))
74 |
75 | expect_equal(colnames(x), colnames(df))
76 |
77 | expect_equal(rownames(x), rownames(df))
78 |
79 | expect_equal(names(x), names(df))
80 |
81 | expect_equal(x[[1:2]], df[[1:2]])
82 |
83 | expect_equal(x[[c(2, 4)]], df[[c(2, 4)]])
84 |
85 | expect_equal(x[["G"]], df[["G"]])
86 | })
87 |
88 |
89 | test_that("fst_table [ generic", {
90 | # '[' generic with 2 arguments
91 |
92 | expect_equal(x[], df[])
93 |
94 | expect_equal(x[2], df[2])
95 |
96 | expect_equal(x[i = 2], df[2])
97 |
98 | expect_equal(x[j = 2], df[2])
99 |
100 | expect_equal(x[drop = FALSE], df[, ])
101 |
102 | # '[' generic with 3 arguments
103 |
104 | expect_equal(x[, ], df[, ])
105 |
106 | expect_equal(x[, 2:3], df[, 2:3])
107 |
108 | expect_equal(as.list(x[2, ]), as.list(df[2, ]))
109 |
110 | expect_equal(as.list(x[2:10, ]), as.list(df[2:10, ]))
111 |
112 | expect_equal(x[2, drop = FALSE], df[2])
113 |
114 | expect_equal(as.list(x[2, 1:3]), as.list(df[2, 1:3]))
115 |
116 | # '[' generic with 4 arguments
117 |
118 | expect_equal(x[, , drop = FALSE], df[])
119 |
120 | expect_equal(x[, , ], df[])
121 |
122 | expect_equal(x[j = 2, drop = FALSE], df[2])
123 | })
124 |
125 |
126 | test_that("fst_table allows for drop argument", {
127 | # fst drops dimensions in same cases as data.frame. Less warnings are given.
128 |
129 | # 3 arguments:
130 |
131 | expect_equal(df[, "X"], x[, "X"])
132 | expect_equal(df[2, "X"], x[2, "X"])
133 | expect_equal(df[2:4, "X"], x[2:4, "X"])
134 |
135 | # 4 arguments:
136 |
137 | expect_equal(df[, "X", drop = TRUE], x[, "X", drop = TRUE])
138 | expect_equal(df[, "X", ], x[, "X", ])
139 | expect_equal(df[2, "X", drop = TRUE], x[2, "X", drop = TRUE])
140 | expect_equal(df[2, "X", ], x[2, "X", ])
141 | expect_equal(df[2:4, "X", drop = TRUE], x[2:4, "X", drop = TRUE])
142 | expect_equal(df[2:4, "X", ], x[2:4, "X", ])
143 | expect_equal(df[2:4, 2, drop = TRUE], x[2:4, 2, drop = TRUE])
144 | expect_equal(df[2:4, 2, ], x[2:4, 2, ])
145 | })
146 |
147 |
148 | test_that("fst_table throws errors on incorrect use of interface", {
149 | expect_error(x[[c("X", 3)]], "Subscript out of bounds")
150 |
151 | expect_error(x[[c("X", 3)]], "Subscript out of bounds")
152 |
153 | expect_error(x[4], "Subscript out of bounds")
154 |
155 | expect_error(x[5.3], "Subscript out of bounds")
156 |
157 | expect_error(x[c(1, NA, 2)], "Subscript out of bounds")
158 |
159 | expect_error(x[c(1.1, NA, 2)], "Subscript out of bounds")
160 |
161 | expect_error(x[c(TRUE, NA)], "Subscript out of bounds")
162 |
163 | expect_error(x[[as.integer(NULL)]], "Please use a length one integer or")
164 |
165 | expect_error(x[[c(2, 0)]], "Second index out of bounds")
166 |
167 | expect_error(x[[c(3, 100)]], "Second index out of bounds")
168 |
169 | expect_error(x[[5]], "Invalid column index 5")
170 |
171 | expect_error(x[[-3]], "Invalid column index -3")
172 | })
173 |
174 |
175 | test_that("fst_table has correct printing for small single column table", {
176 | df <- data.frame(X = 1)
177 | write_fst(df, test_file)
178 | x <- fst(test_file)
179 |
180 | res <- capture_output(print(x))
181 | res <- crayon::strip_style(res)
182 |
183 | expect_equal(res, paste(
184 | "",
185 | "1 rows, 1 columns (fst_table.fst)\n",
186 | " X",
187 | " ",
188 | "1 1",
189 | sep = "\n"
190 | ))
191 | })
192 |
193 |
194 | test_that("fst_table has correct printing for big single column table", {
195 | df <- data.frame(X = 1:100)
196 | write_fst(df, test_file)
197 | x <- fst(test_file)
198 |
199 | res <- capture_output(print(x))
200 | res <- crayon::strip_style(res)
201 |
202 | expect_equal(res, paste(
203 | "",
204 | "100 rows, 1 columns (fst_table.fst)\n",
205 | " X",
206 | " ",
207 | "1 1",
208 | "2 2",
209 | "3 3",
210 | "4 4",
211 | "5 5",
212 | "-- --",
213 | "96 96",
214 | "97 97",
215 | "98 98",
216 | "99 99",
217 | "100 100",
218 | sep = "\n"
219 | ))
220 | })
221 |
222 |
223 | test_that("fst_table has correct printing for big multi column table", {
224 | df <- data.frame(X = 1:104, Y = c(LETTERS, LETTERS, LETTERS, LETTERS), stringsAsFactors = TRUE)
225 | write_fst(df, test_file)
226 | x <- fst(test_file)
227 |
228 | res <- capture_output(print(x))
229 | res <- crayon::strip_style(res)
230 |
231 | expect_equal(res, paste(
232 | "",
233 | "104 rows, 2 columns (fst_table.fst)\n",
234 | " X Y",
235 | " ",
236 | "1 1 A",
237 | "2 2 B",
238 | "3 3 C",
239 | "4 4 D",
240 | "5 5 E",
241 | "-- -- --",
242 | "100 100 V",
243 | "101 101 W",
244 | "102 102 X",
245 | "103 103 Y",
246 | "104 104 Z",
247 | sep = "\n"
248 | ))
249 | })
250 |
251 |
252 | test_that("fst_table has correct printing for small multi column table", {
253 | df <- data.frame(X = 1:9, Y = LETTERS[10:18], stringsAsFactors = TRUE)
254 | write_fst(df, test_file)
255 | x <- fst(test_file)
256 |
257 | res <- capture_output(print(x))
258 | res <- crayon::strip_style(res)
259 |
260 | expect_equal(res, paste(
261 | "",
262 | "9 rows, 2 columns (fst_table.fst)\n",
263 | " X Y",
264 | " ",
265 | "1 1 J",
266 | "2 2 K",
267 | "3 3 L",
268 | "4 4 M",
269 | "5 5 N",
270 | "6 6 O",
271 | "7 7 P",
272 | "8 8 Q",
273 | "9 9 R",
274 | sep = "\n"
275 | ))
276 | })
277 |
--------------------------------------------------------------------------------
/tests/testthat/test_fst.R:
--------------------------------------------------------------------------------
1 |
2 | context("subsetting and compression")
3 |
4 |
5 | # some helper functions
6 | source("helper_fstwrite.R")
7 |
8 |
9 | # Clean testdata directory
10 | if (!file.exists("FactorStore")) {
11 | dir.create("FactorStore")
12 | } else {
13 | file.remove(list.files("FactorStore", full.names = TRUE))
14 | }
15 |
16 | # Create a pool of strings
17 | nroflevels <- 8
18 |
19 | char_vec <- function(nr_of_rows) {
20 | sapply(1:nr_of_rows, function(x) {
21 | paste(sample(LETTERS, sample(1:4, 1)), collapse = "")
22 | })
23 | }
24 |
25 |
26 | char_veclong <- function(nr_of_rows) {
27 | sapply(
28 | 1:nr_of_rows,
29 | function(x) {
30 | paste(sample(LETTERS, sample(20:25, 1)), collapse = "")
31 | }
32 | )
33 | }
34 |
35 |
36 | date_vec <- function(nr_of_rows) {
37 | date_vec <- sample(1:nr_of_rows, replace = TRUE)
38 | class(date_vec) <- c("IDate", "Date")
39 | date_vec
40 | }
41 |
42 |
43 | difftime_vec <- function(nr_of_rows, mode = "double") {
44 | vec <- (Sys.time() + 1:nr_of_rows) - Sys.time()
45 | mode(vec) <- mode
46 | vec
47 | }
48 |
49 |
50 | # Sample data
51 | nr_of_rows <- 10000L
52 | char_na <- char_vec(nr_of_rows)
53 | char_na[sample(1:nr_of_rows, 10)] <- NA
54 | datatable <- data.frame(
55 | Xint = 1:nr_of_rows,
56 | Ylog = sample(c(TRUE, FALSE, NA), nr_of_rows, replace = TRUE),
57 | Zdoub = rnorm(nr_of_rows),
58 | Qchar = char_vec(nr_of_rows),
59 | WFact = factor(sample(char_vec(nroflevels), nr_of_rows, replace = TRUE)),
60 | Ordered = ordered(sample(char_vec(nroflevels), nr_of_rows, replace = TRUE)),
61 | char_na = char_na,
62 | CharLong = char_veclong(nr_of_rows),
63 | Date = date_vec(nr_of_rows),
64 | DateDouble = as.Date("2015-01-01") + 1:nr_of_rows,
65 | Raw = as.raw(sample(0:255, nr_of_rows, replace = TRUE)),
66 | Difftime = difftime_vec(nr_of_rows),
67 | DiffTime_int = difftime_vec(nr_of_rows, "integer"),
68 | stringsAsFactors = FALSE
69 | )
70 |
71 |
72 | # A write / read cylce for a range of columns and rows
73 | test_write_read <- function(
74 | col, from = 1L, to = nr_of_rows, sel_columns = NULL, compress = 0L,
75 | tot_length = nr_of_rows) {
76 | dt <- datatable[1:tot_length, col, drop = FALSE]
77 |
78 | fstwriteproxy(dt, "FactorStore/data1.fst", compress) # use compression
79 |
80 | # Read full dataset
81 | to <- min(to, nr_of_rows)
82 | data <- fstreadproxy("FactorStore/data1.fst", columns = sel_columns, from = from, to = to)
83 |
84 | if (is.null(sel_columns)) {
85 | sub_dt <- dt[from:to, , drop = FALSE]
86 | } else {
87 | sub_dt <- dt[from:to, sel_columns, drop = FALSE]
88 | }
89 |
90 | row.names(sub_dt) <- NULL
91 |
92 | uneq <- sub_dt[, 1] != data[, 1]
93 | difftable <- sub_dt
94 | difftable[, "Row"] <- seq_len(nrow(difftable))
95 | difftable[, "Other"] <- data[, 1]
96 |
97 | message <- paste(
98 | "args: col:", col, "| from:", from, "| to:", to, "| setColumns:", sel_columns,
99 | "| compress:", compress, "| tot_length", tot_length, " cols sub_dt:", ncol(sub_dt), ", rows sub_dt:",
100 | nrow(sub_dt), "cols data:", ncol(data), ", rows data:", nrow(data),
101 | "head sub_dt:", paste(sub_dt[1:10, 1], collapse = ","),
102 | "head data:", paste(data[1:10, 1], collapse = ","),
103 | "unequals:", sum(uneq),
104 | "uneq rows sub_dt1", paste(difftable[uneq, ][1:min(25, sum(uneq, na.rm = TRUE)), 1], collapse = ","),
105 | "uneq rows sub_dt2", paste(difftable[uneq, ][1:min(25, sum(uneq, na.rm = TRUE)), 2], collapse = ","),
106 | "uneq rows sub_dt3", paste(difftable[uneq, ][1:min(25, sum(uneq, na.rm = TRUE)), 3], collapse = ",")
107 | )
108 |
109 | expect_equal(sub_dt, data, info = message)
110 | }
111 |
112 | col_names <- colnames(datatable)
113 |
114 |
115 | test_that("Single uncompressed vectors", {
116 | sapply(
117 | col_names,
118 | function(x) {
119 | test_write_read(x)
120 | }
121 | )
122 | })
123 |
124 |
125 | test_that("Small uncompressed vectors", {
126 | sapply(col_names, function(x) {
127 | test_write_read(x, to = 30L, tot_length = 30L)
128 | })
129 | })
130 |
131 |
132 | test_that("Single weakly compressed vectors", {
133 | sapply(
134 | col_names,
135 | function(x) {
136 | test_write_read(x, compress = 30L)
137 | }
138 | )
139 | })
140 |
141 |
142 | test_that("Single small weakly compressed vectors", {
143 | sapply(
144 | col_names,
145 | function(x) {
146 | test_write_read(x, to = 30L, tot_length = 30L, compress = 30L)
147 | }
148 | )
149 | })
150 |
151 |
152 | test_that("Single medium sized weakly compressed vectors", {
153 | sapply(
154 | col_names,
155 | function(x) {
156 | test_write_read(x, to = 8193L, tot_length = 8193L, compress = 30L)
157 | }
158 | )
159 | })
160 |
161 |
162 | test_that("Single moderate compressed vectors", {
163 | sapply(
164 | col_names,
165 | function(x) {
166 | test_write_read(x, compress = 60L)
167 | }
168 | )
169 | })
170 |
171 |
172 | test_that("Single small moderate compressed vectors", {
173 | sapply(
174 | col_names,
175 | function(x) {
176 | test_write_read(x, to = 30L, tot_length = 30L, compress = 60L)
177 | }
178 | )
179 | })
180 |
181 |
182 | # Various boundary conditions
183 |
184 | blocktests <- function(col, block_start, block_end, compression) {
185 | last_row <- min(block_end * block_size + block_size - 1L, nr_of_rows)
186 | test_write_read(col, 1L + block_start * block_size, last_row, NULL, compression) # full
187 | test_write_read(col, 1L + block_start * block_size + 4L, last_row, NULL, compression) # offset
188 | test_write_read(col, 1L + block_start * block_size, last_row - 10L, NULL, compression) # remainder
189 | }
190 |
191 |
192 | blocktestsingletype <- function(type) {
193 | # Single first block
194 | blocktests(type, 0, 0, 0L) # uncompressed
195 | blocktests(type, 0, 0, 40L) # algorithm 1
196 | blocktests(type, 0, 0, 80L) # algorithm 2
197 |
198 | # Single middle block
199 | blocktests(type, 1, 1, 0L) # uncompressed
200 | blocktests(type, 1, 1, 40L) # algorithm 1
201 | blocktests(type, 1, 1, 80L) # algorithm 2
202 |
203 | last_block <- as.integer((nr_of_rows - 1) / block_size) ## nolint
204 |
205 | # Single last block
206 | blocktests(type, last_block, last_block, 0L) # uncompressed
207 | blocktests(type, last_block, last_block, 40L) # algorithm 1
208 | blocktests(type, last_block, last_block, 80L) # algorithm 2
209 |
210 | # Multiple blocks
211 | blocktests(type, 0, 1, 0L) # uncompressed
212 | blocktests(type, last_block - 1, last_block, 0L) # uncompressed
213 | blocktests(type, 0, last_block, 0L) # uncompressed
214 |
215 | blocktests(type, 0, 1, 40L) # algorithm 1
216 | blocktests(type, last_block - 1, last_block, 40L) # algorithm 1
217 | blocktests(type, 0, last_block, 40L) # algorithm 1
218 |
219 | blocktests(type, 0, 1, 80L) # algorithm 2
220 | blocktests(type, last_block - 1, last_block, 80L) # algorithm 2
221 | blocktests(type, 0, last_block, 80L) # algorithm 2
222 | }
223 |
224 |
225 | block_size <- 4096
226 |
227 | # Test blocks
228 | test_that("Integer column block tests", {
229 | blocktestsingletype("Xint")
230 | })
231 |
232 |
233 | test_that("Logical column block tests", {
234 | blocktestsingletype("Ylog")
235 | })
236 |
237 |
238 | test_that("Date column block tests", {
239 | blocktestsingletype("Date")
240 | })
241 |
242 | block_size <- 2048
243 |
244 |
245 | # Test blocks
246 | test_that("Real column block tests", {
247 | blocktestsingletype("Zdoub")
248 | })
249 |
250 |
251 | block_size <- 2047
252 |
253 | test_that("Character column block tests", {
254 | blocktestsingletype("Qchar")
255 | })
256 |
257 |
258 | test_that("Factor column block tests", {
259 | blocktestsingletype("WFact")
260 | })
261 |
262 |
263 | test_that("Character column block tests with NA's", {
264 | blocktestsingletype("char_na")
265 | })
266 |
267 |
268 | test_that("Mixed columns are stored correctly", {
269 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"))
270 | })
271 |
272 |
273 | test_that("From and to row can be set", {
274 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"), from = 10)
275 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"), to = 8)
276 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"), from = 4, to = 13)
277 | })
278 |
279 |
280 | test_that("Select columns", {
281 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"),
282 | sel_columns = "Zdoub"
283 | )
284 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"),
285 | sel_columns = c("Ylog", "WFact")
286 | )
287 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"),
288 | sel_columns = c("WFact", "Ylog")
289 | )
290 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact", "char_na", "Date"),
291 | from = 7, to = 13, sel_columns = c("Ylog", "Qchar")
292 | )
293 | })
294 |
295 |
296 | test_that("Select unknown column", {
297 | expect_error(data <- fstreadproxy("FactorStore/data1.fds", columns = "bla"))
298 | expect_error(data <- fstreadproxy("FactorStore/data1.fds", columns = c("WFact", "bla")))
299 | })
300 |
301 |
302 | test_that("Select out of range row number", {
303 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact"), from = 4, to = 7000)
304 | test_write_read(c("Xint", "Ylog", "Zdoub", "Qchar", "WFact"), from = 4, to = NULL)
305 | expect_error(
306 | fstreadproxy("FactorStore/data1.fst", from = 12000, to = NULL),
307 | "Row selection is out of range"
308 | )
309 | expect_error(fstreadproxy("FactorStore/data1.fst", from = 0, to = NULL), "Parameter 'from' should have")
310 | })
311 |
--------------------------------------------------------------------------------
/README.Rmd:
--------------------------------------------------------------------------------
1 | ---
2 | output:
3 | github_document
4 | ---
5 |
6 |
7 |
8 | ```{r, echo = FALSE}
9 | knitr::opts_chunk$set(
10 | collapse = TRUE,
11 | comment = "#>",
12 | fig.path = "man/figures/README-"
13 | )
14 | ```
15 |
16 |
17 |
18 | [](https://github.com/fstpackage/fst/actions/workflows/R-CMD-check.yaml)
19 | [](https://www.gnu.org/licenses/agpl-3.0)
20 | [](https://cran.r-project.org/package=fst)
21 | [](https://fastverse.r-universe.dev/ui#package:fastverse)
22 | [](https://app.codecov.io/gh/fstpackage/fst)
23 | [](http://cran.rstudio.com/web/packages/fst/index.html)
24 | [](http://cran.rstudio.com/web/packages/fst/index.html)
25 |
26 | ## Overview
27 |
28 | The [_fst_ package][fstRepo] for R provides a fast, easy and flexible way to serialize data frames. With access speeds of multiple GB/s, _fst_ is specifically designed to unlock the potential of high speed solid state disks that can be found in most modern computers. Data frames stored in the _fst_ format have full random access, both in column and rows.
29 |
30 | The figure below compares the read and write performance of the _fst_ package to various alternatives.
31 |
32 | ```{r speedTable, results = 'asis', message = FALSE, echo = FALSE}
33 | require(ggplot2)
34 | require(data.table)
35 | require(fst)
36 | require(knitr)
37 |
38 | speed_results <- read_fst("res_readme.fst", as.data.table = TRUE)
39 |
40 | speeds <- speed_results[NrOfRows == 5e7, list(
41 | `Time (ms)` = as.integer(median(Time)),
42 | `Size (MB)` = format(median(FileSize), digits = 2),
43 | `Speed (MB/s)` = as.integer(median(Speed)),
44 | N = .N),
45 | by = "Package,Mode"]
46 |
47 | speeds[Package == "data.table" & Mode == "Write", Method := "fwrite"]
48 | speeds[Package == "data.table" & Mode == "Read", Method := "fread"]
49 | speeds[Package == "fst" & Mode == "Write", Method := "write_fst"]
50 | speeds[Package == "fst" & Mode == "Read", Method := "read_fst"]
51 | speeds[Package == "baseR" & Mode == "Write", Method := "saveRDS"]
52 | speeds[Package == "baseR" & Mode == "Read", Method := "readRDS"]
53 | speeds[Package == "feather" & Mode == "Write", Method := "write_feather"]
54 | speeds[Package == "feather" & Mode == "Read", Method := "read_feather"]
55 | speeds[, Format := "bin"]
56 | speeds[Package == "data.table", Format := "csv"]
57 | setkey(speeds, Package, Mode)
58 |
59 | display_speeds <- copy(speeds)
60 | for (col in colnames(display_speeds)[2:ncol(display_speeds)]) {
61 | setnames(display_speeds, col, "CurCol")
62 | display_speeds[, CurCol := as.character(CurCol)]
63 | display_speeds[Package == "fst", CurCol := paste0("**", CurCol, "**")]
64 | setnames(display_speeds, "CurCol", col)
65 | }
66 |
67 | kable(display_speeds[, c(7, 8, 3, 4, 5, 6)])
68 | ```
69 |
70 | These benchmarks were performed on a laptop (i7 4710HQ @2.5 GHz) with a reasonably fast SSD (M.2 Samsung SM951) using the dataset defined below. Parameter *Speed* was calculated by dividing the in-memory size of the data frame by the measured time. These results are also visualized in the following graph:
71 |
72 | ```{r speed-bench, echo = FALSE, message = FALSE, results = 'hide', fig.width = 8.5, fig.height = 6}
73 | ggplot(speed_results[NrOfRows == 5e7, .(Speed = median(Speed)), by = "Package,Mode"]) +
74 | geom_bar(aes(Mode, Speed, fill = Mode), colour = "darkgrey", stat = "identity") +
75 | facet_wrap(~ Package, 1) +
76 | ylim(0, NA) +
77 | ylab("Read or Write speed (MB/s)") +
78 | xlab("") +
79 | theme(legend.position="none")
80 | ```
81 |
82 | As can be seen from the figure, the measured speeds for the _fst_ package are very high and even top the maximum drive speed of the SSD used. The package accomplishes this by an effective combination of multi-threading and compression. The on-disk file sizes of _fst_ files are also much smaller than that of the other formats tested. This is an added benefit of _fst_'s use of type-specific compressors on each stored column.
83 |
84 | In addition to methods for data frame serialization, _fst_ also provides methods for multi-threaded in-memory compression with the popular LZ4 and ZSTD compressors and an extremely fast multi-threaded hasher.
85 |
86 | ## Multi-threading
87 |
88 | The _fst_ package relies heavily on multi-threading to boost the read- and write speed of data frames. To maximize throughput, _fst_ compresses and decompresses data _in the background_ and tries to keep the disk busy writing and reading data at the same time.
89 |
90 | ## Installation
91 |
92 | The easiest way to install the package is from CRAN:
93 |
94 | ```{r, eval = FALSE}
95 | install.packages("fst")
96 | ```
97 |
98 | You can also use the development version from GitHub:
99 |
100 | ```{r, eval = FALSE}
101 | # install.packages("devtools")
102 | devtools::install_github("fstpackage/fst", ref = "develop")
103 | ```
104 |
105 | ## Basic usage
106 |
107 | ```{r, results = 'hide', echo = FALSE, message = FALSE}
108 | require(fst)
109 | ```
110 |
111 | Using _fst_ is simple. Data can be stored and retrieved using methods _write\_fst_ and _read\_fst_:
112 |
113 | ```{r}
114 | # Generate some random data frame with 10 million rows and various column types
115 | nr_of_rows <- 1e7
116 |
117 | df <- data.frame(
118 | Logical = sample(c(TRUE, FALSE, NA), prob = c(0.85, 0.1, 0.05), nr_of_rows, replace = TRUE),
119 | Integer = sample(1L:100L, nr_of_rows, replace = TRUE),
120 | Real = sample(sample(1:10000, 20) / 100, nr_of_rows, replace = TRUE),
121 | Factor = as.factor(sample(labels(UScitiesD), nr_of_rows, replace = TRUE))
122 | )
123 |
124 | # Store the data frame to disk
125 | write_fst(df, "dataset.fst")
126 |
127 | # Retrieve the data frame again
128 | df <- read_fst("dataset.fst")
129 | ```
130 |
131 | _Note: the dataset defined in this example code was also used to obtain the benchmark results shown in the introduction._
132 |
133 | ## Random access
134 |
135 | The _fst_ file format provides full random access to stored datasets. You can retrieve a selection of columns and rows with:
136 |
137 | ```{r, results = 'hide'}
138 | df_subset <- read_fst("dataset.fst", c("Logical", "Factor"), from = 2000, to = 5000)
139 | ```
140 |
141 | This reads rows 2000 to 5000 from columns _Logical_ and _Factor_ without actually touching any other data in the stored file. That means that a subset can be read from file **without reading the complete file first**. This is different from, say, _readRDS_ or _read\_feather_ where you have to read the complete file or column before you can make a subset.
142 |
143 | ## Compression
144 |
145 | For compression the excellent and speedy [LZ4][lz4Repo] and [ZSTD][zstdRepo] compression algorithms are used. These compressors (in combination with type-specific bit filters), enable _fst_ to achieve high compression speeds at reasonable compression factors. The compression factor can be tuned from 0 (minimum) to 100 (maximum):
146 |
147 | ```{r, results = 'hide'}
148 | write_fst(df, "dataset.fst", 100) # use maximum compression
149 | ```
150 |
151 | Compression reduces the size of the _fst_ file that holds your data. But because the (de-)compression is done _on background threads_, it can increase the total read- and write speed as well. The graph below shows how the use of multiple threads enhances the read and write speed of our sample dataset.
152 |
153 | ```{r multi-threading, fig.width = 10, fig.height = 8, echo = FALSE}
154 | speed_results[Package %in% c("baseR", "feather"), Threads := 1]
155 | speed_results[, Threads := as.factor(Threads)]
156 | speed_results[, Speed := 0.001 * Speed]
157 | speed_results[, NrOfRows := ifelse(NrOfRows == 1e7, "1 million rows", "10 million rows")]
158 |
159 |
160 | fig_results <- speed_results[, .(Speed = median(Speed)), by = "Package,Mode,NrOfRows,Threads"]
161 |
162 | ggplot(fig_results) +
163 | geom_bar(aes(Package, Speed, fill = Threads),
164 | stat = "identity", position = "dodge", width = 0.8) +
165 | facet_grid(Mode ~ NrOfRows, scales = "free_y") +
166 | scale_fill_manual(values = colorRampPalette(c("#FBE3A5", "#433B54"))(10)[10:3]) +
167 | ylab("Read or write speed in GB/s") +
168 | theme_minimal()
169 | ```
170 |
171 | The _csv_ format used by the _fread_ and _fwrite_ methods of package _data.table_ is actually a human-readable text format and not a binary format. Normally, binary formats would be much faster than the _csv_ format, because _csv_ takes more space on disk, is row based, uncompressed and needs to be parsed into a computer-native format to have any meaning. So any serializer that's working on _csv_ has an enormous disadvantage as compared to binary formats. Yet, the results show that _data.table_ is on par with binary formats and when more threads are used, it can even be faster. Because of this impressive performance, it was included in the graph for comparison.
172 |
173 | ## Bindings in other languages
174 |
175 | **Julia**: [**`FstFileFormat.jl`**][fstformatRepo] A naive Julia binding using RCall.jl
176 |
177 | > **Note to users**: From CRAN release v0.8.0, the _fst_ format is stable and backwards compatible. That means that all _fst_ files generated with package v0.8.0 or later can be read by future versions of the package.
178 |
179 | ```{r, echo = FALSE, results = 'hide'}
180 | # cleanup
181 | file.remove("dataset.fst")
182 | ```
183 |
184 | [fstRepo]: https://github.com/fstpackage/fst
185 | [lz4Repo]: https://github.com/lz4/lz4
186 | [zstdRepo]: https://github.com/facebook/zstd
187 | [fstformatRepo]: https://github.com/xiaodaigh/FstFileFormat.jl
188 |
--------------------------------------------------------------------------------
/R/fst.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' Read and write fst files.
24 | #'
25 | #' Read and write data frames from and to a fast-storage (`fst`) file.
26 | #' Allows for compression and (file level) random access of stored data, even for compressed datasets.
27 | #' Multiple threads are used to obtain high (de-)serialization speeds but all background threads are
28 | #' re-joined before `write_fst` and `read_fst` return (reads and writes are stable).
29 | #' When using a `data.table` object for `x`, the key (if any) is preserved,
30 | #' allowing storage of sorted data.
31 | #' Methods `read_fst` and `write_fst` are equivalent to `read.fst` and `write.fst` (but the
32 | #' former syntax is preferred).
33 | #'
34 | #' @param x a data frame to write to disk
35 | #' @param path path to fst file
36 | #' @param compress value in the range 0 to 100, indicating the amount of compression to use.
37 | #' Lower values mean larger file sizes. The default compression is set to 50.
38 | #' @param uniform_encoding If `TRUE`, all character vectors will be assumed to have elements with equal encoding.
39 | #' The encoding (latin1, UTF8 or native) of the first non-NA element will used as encoding for the whole column.
40 | #' This will be a correct assumption for most use cases.
41 | #' If `uniform.encoding` is set to `FALSE`, no such assumption will be made and all elements will be converted
42 | #' to the same encoding. The latter is a relatively expensive operation and will reduce write performance for
43 | #' character columns.
44 | #' @return `read_fst` returns a data frame with the selected columns and rows. `write_fst`
45 | #' writes `x` to a `fst` file and invisibly returns `x` (so you can use this function in a pipeline).
46 | #' @examples
47 | #' # Sample dataset
48 | #' x <- data.frame(A = 1:10000, B = sample(c(TRUE, FALSE, NA), 10000, replace = TRUE))
49 | #'
50 | #' # Default compression
51 | #' fst_file <- tempfile(fileext = ".fst")
52 | #' write_fst(x, fst_file) # filesize: 17 KB
53 | #' y <- read_fst(fst_file) # read fst file
54 |
55 | #' # Maximum compression
56 | #' write_fst(x, fst_file, 100) # fileSize: 4 KB
57 | #' y <- read_fst(fst_file) # read fst file
58 | #'
59 | #' # Random access
60 | #' y <- read_fst(fst_file, "B") # read selection of columns
61 | #' y <- read_fst(fst_file, "A", 100, 200) # read selection of columns and rows
62 | #' @export
63 | write_fst <- function(x, path, compress = 50, uniform_encoding = TRUE) {
64 | if (!is.character(path)) stop("Please specify a correct path.")
65 |
66 | if (!is.data.frame(x)) stop("Please make sure 'x' is a data frame.")
67 |
68 | dt <- fststore(normalizePath(path, mustWork = FALSE), x, as.integer(compress), uniform_encoding)
69 |
70 | if (inherits(dt, "fst_error")) {
71 | stop(dt)
72 | }
73 |
74 | return(invisible(x))
75 | }
76 |
77 |
78 | #' Read metadata from a fst file
79 | #'
80 | #' Method for checking basic properties of the dataset stored in \code{path}.
81 | #'
82 | #' @param path path to fst file
83 | #' @param old_format must be FALSE, the old fst file format is deprecated and can only be read and
84 | #' converted with fst package versions 0.8.0 to 0.8.10.
85 | #' @return Returns a list with meta information on the stored dataset in \code{path}.
86 | #' Has class \code{fstmetadata}.
87 | #' @examples
88 | #' # Sample dataset
89 | #' x <- data.frame(
90 | #' First = 1:10,
91 | #' Second = sample(c(TRUE, FALSE, NA), 10, replace = TRUE),
92 | #' Last = sample(LETTERS, 10)
93 | #' )
94 | #'
95 | #' # Write to fst file
96 | #' fst_file <- tempfile(fileext = ".fst")
97 | #' write_fst(x, fst_file)
98 | #'
99 | #' # Display meta information
100 | #' metadata_fst(fst_file)
101 | #' @export
102 | metadata_fst <- function(path, old_format = FALSE) {
103 | if (old_format != FALSE) {
104 | stop(
105 | "Parameter old_format is depricated, fst files written with fst package version",
106 | " lower than 0.8.0 should be read (and rewritten) using fst package versions <= 0.8.10."
107 | )
108 | }
109 |
110 | full_path <- normalizePath(path, mustWork = FALSE)
111 |
112 | metadata <- fstmetadata(full_path)
113 |
114 | if (inherits(metadata, "fst_error")) {
115 | stop(metadata)
116 | }
117 |
118 | col_info <- list(
119 | path = full_path, nrOfRows = metadata$nrOfRows,
120 | keys = metadata$keyNames, columnNames = metadata$colNames,
121 | columnBaseTypes = metadata$colBaseType, keyColIndex = metadata$keyColIndex,
122 | columnTypes = metadata$colType
123 | )
124 | class(col_info) <- "fstmetadata"
125 |
126 | col_info
127 | }
128 |
129 |
130 | #' @export
131 | print.fstmetadata <- function(x, ...) {
132 | cat("\n")
133 | cat(x$nrOfRows, " rows, ", length(x$columnNames), " columns (", basename(x$path),
134 | ")\n\n",
135 | sep = ""
136 | )
137 |
138 | types <- c(
139 | "unknown", "character", "factor", "ordered factor", "integer", "POSIXct", "difftime",
140 | "IDate", "ITime", "double", "Date", "POSIXct", "difftime", "ITime", "logical", "integer64",
141 | "nanotime", "raw"
142 | )
143 |
144 | # table has no key columns
145 | if (is.null(x$keys)) {
146 | column_names <- format(encodeString(x$columnNames, quote = "'"))
147 | cat(paste0("* ", column_names, ": ", types[x$columnTypes], "\n"), sep = "")
148 | return(invisible(NULL))
149 | }
150 |
151 | # table has key columns
152 | keys <- data.frame(
153 | k = x$keys,
154 | count = seq_along(x$keys),
155 | stringsAsFactors = FALSE
156 | )
157 |
158 | col_info <- data.frame(
159 | k = x$columnNames,
160 | o = seq_along(x$columnNames),
161 | t = types[x$columnTypes],
162 | stringsAsFactors = FALSE
163 | )
164 |
165 | # merge keys to correct column
166 | col_info <- merge(col_info, keys, "k", all.x = TRUE, sort = FALSE)
167 |
168 | col_info$k <- format(encodeString(col_info$k, quote = "'"))
169 | col_info$l <- paste0(" (key ", col_info$count, ")")
170 | col_info[is.na(col_info$count), "l"] <- ""
171 |
172 | col_info <- col_info[order(col_info$count, col_info$o), ] # key columns at the top
173 |
174 | cat(paste0("* ", col_info$k, ": ", col_info$t, col_info$l, "\n"), sep = "")
175 | }
176 |
177 |
178 | #' @rdname write_fst
179 | #' @export
180 | write.fst <- function(x, path, compress = 50, uniform_encoding = TRUE) { # nolint
181 | write_fst(x, path, compress, uniform_encoding)
182 | }
183 |
184 |
185 | #' @rdname write_fst
186 | #'
187 | #' @param columns Column names to read. The default is to read all columns.
188 | #' @param from Read data starting from this row number.
189 | #' @param to Read data up until this row number. The default is to read to the last row of the stored dataset.
190 | #' @param as.data.table If TRUE, the result will be returned as a \code{data.table} object. Any keys set on
191 | #' dataset \code{x} before writing will be retained. This allows for storage of sorted datasets. This option
192 | #' requires \code{data.table} package to be installed.
193 | #' @param old_format must be FALSE, the old fst file format is deprecated and can only be read and
194 | #' converted with fst package versions 0.8.0 to 0.8.10.
195 | #'
196 | #' @export
197 | read_fst <- function(path, columns = NULL, from = 1, to = NULL, as.data.table = FALSE, old_format = FALSE) { # nolint
198 | file_name <- normalizePath(path, mustWork = FALSE)
199 |
200 | if (!is.null(columns)) {
201 | if (!is.character(columns)) {
202 | stop("Parameter 'columns' should be a character vector of column names.")
203 | }
204 | }
205 |
206 | if (!is.numeric(from) || from < 1 || length(from) != 1) {
207 | stop("Parameter 'from' should have a numerical value equal or larger than 1.")
208 | }
209 |
210 | from <- as.integer(from)
211 |
212 | if (!is.null(to)) {
213 | if (!is.numeric(to) || length(to) != 1) {
214 | stop("Parameter 'to' should have a numerical value larger than 1 (or NULL).")
215 | }
216 |
217 | to <- as.integer(to)
218 | }
219 |
220 | if (old_format != FALSE) {
221 | stop(
222 | "Parameter old_format is depricated, fst files written with fst package version",
223 | " lower than 0.8.0 should be read (and rewritten) using fst package versions <= 0.8.10."
224 | )
225 | }
226 |
227 | res <- fstretrieve(file_name, columns, from, to)
228 |
229 | if (inherits(res, "fst_error")) {
230 | stop(res)
231 | }
232 |
233 | nr_of_rows <- 0
234 | if (length(res$resTable) > 0) { # check for NULL tables's
235 | nr_of_rows <- length(res$resTable[[1]])
236 | }
237 |
238 | # long vectors are not supported yet with data.table, tibble's or data.frame,
239 | # so return a list instead
240 | if (nr_of_rows >= 2^31) {
241 | return(res$resTable)
242 | }
243 |
244 | if (as.data.table) {
245 | if (!requireNamespace("data.table", quietly = TRUE)) {
246 | stop("Please install package data.table when using as.data.table = TRUE")
247 | }
248 |
249 | key_names <- res$keyNames
250 | res <- data.table::setDT(res$resTable) # nolint
251 | if (length(key_names) > 0) data.table::setattr(res, "sorted", key_names)
252 | return(res)
253 | }
254 |
255 | res_table <- res$resTable
256 |
257 | # use setters from data.table to improve performance
258 | if (requireNamespace("data.table", quietly = TRUE)) {
259 | data.table::setattr(res_table, "class", "data.frame")
260 | data.table::setattr(res_table, "row.names", base::.set_row_names(nr_of_rows))
261 | } else {
262 | class(res_table) <- "data.frame"
263 | attr(res_table, "row.names") <- base::.set_row_names(nr_of_rows) # nolint
264 | }
265 |
266 | res_table
267 | }
268 |
269 |
270 | #' @rdname write_fst
271 | #' @export
272 | read.fst <- function(path, columns = NULL, from = 1, to = NULL, as.data.table = FALSE, old_format = FALSE) { # nolint
273 | read_fst(path, columns, from, to, as.data.table, old_format)
274 | }
275 |
276 |
277 | #' @rdname metadata_fst
278 | #' @export
279 | fst.metadata <- function(path, old_format = FALSE) { # nolint
280 | metadata_fst(path, old_format)
281 | }
282 |
--------------------------------------------------------------------------------
/NEWS.md:
--------------------------------------------------------------------------------
1 |
2 | # fst 0.9.9 (in development)
3 |
4 | ## Enhancements
5 |
6 | ## Bugs solved
7 |
8 | ## Library updates
9 |
10 |
11 | # fst 0.9.8
12 |
13 | With this release of `fst`, the `fstlib` library is no longer build with the `fst` package, but
14 | imported from package `fstcore`. This allows for better separation of updates of the C++ code underlying the `fst`
15 | format and the R wrapper package. Also, with this setup, other packages can directly use the C++ interface exported
16 | from the fstcore package.
17 |
18 | ## Bugs solved
19 |
20 | * The package had linking problems on ARM macOS systems, preventing a correct build. These problems originated from
21 | minor differences between the xxHash implementations in the LZ4 and ZSTD libraries and incorrect linker parameters.
22 |
23 | ## Library updates
24 |
25 | * Library LZ4 updated to version 1.9.3
26 | * library ZSTD updated to version 1.5.2
27 |
28 |
29 | # fst 0.9.6
30 |
31 | Version 0.9.6 is a minor update to 'hotfix' an issue with the use of `sample.int()`. All calls to `sample.int()` now
32 | explicitly reference a length one size object.
33 |
34 | # fst 0.9.4
35 |
36 | Version 0.9.4 is a minor update to 'hotfix' an issue with suggested packages as reported by CRAN.
37 |
38 | ## Bugs solved
39 |
40 | * Packages `nanotime`, `bit64` and `lintr` are now used conditionally as is required for packages suggested in DESCRIPTION, see 'Writing R Extensions' 1.1.3.1 (thanks @CRAN for reporting)
41 |
42 |
43 | # fst 0.9.2
44 |
45 | Version 0.9.2 of the `fst` package brings support for zero-row table serialization and compression for long vectors. In addition, `fst` was prepared for the change in the default settings for the stringsAsFactors argument (data.frame) in R 4.0.0.
46 |
47 | ## Library updates
48 |
49 | * Library `fstlib` updated to version 0.1.6
50 | * Library LZ4 updated to version 1.9.2
51 | * library ZSTD updated to version 1.4.4
52 |
53 | ## Enhancements
54 |
55 | * Incorrect column selection gets a more informative error message (issue #138, thanks Jean-Luc and @Moohan for reporting).
56 | * Long raw vectors can be hashed with hash_fst (issue #202)
57 | * Empty tables are serialized correctly using `write_fst()` (issue #99)
58 |
59 | ## Bugs solved
60 |
61 | * Ellipsis is forwarded in method `str.fst_table()` (issue #219, thanks @nbenn for reporting).
62 | * Coloring is turned off for terminals that don't support it or when package `crayon` is not installed (issue #198, thanks @muschellij2 for reporting and the code fix).
63 | * Method `metadata_fst()` correctly displays the key of the data table if column names are not in alphabetical order (issue #199, thanks @renkun-ken for the pull request).
64 | * stringsAsFactors argument defaults to FALSE for upcoming R 4.0.0 (issue #234, thanks @CRAN for reporting)
65 |
66 |
67 | # fst 0.9.0
68 |
69 | Version 0.9.0 of the `fst` package addresses the request from CRAN maintainers to fix issues identified by rchk. These issues result from PROTECT / UNPROTECT pairs called in the constructor / destructor pairs of C++ classes. rchk (rightfully) warns about those because it can't determine from the code if pairs are properly matched. With this submission the relevant SEXP classes are protected by containing them in SEXP classes that are already PROTECTED, which allows for removal of the PROTECT / UNPROTECT pairs in question.
70 |
71 | As of `fst` version 0.9.0, support for fst files generated with `fst` package versions lower than 0.8.0 has been deprecated. This significantly reduces the (C++) code base and prepares `fst` for future code changes.
72 |
73 | ## Library updates
74 |
75 | * Library `fstlib` updated to version 0.1.1
76 |
77 | ## Enhancements
78 |
79 | * Method `setnrofthreads` returns invisible result to avoid printing unwanted output (thanks @renkun-ken for the pull request)
80 |
81 | ## Bugs solved
82 |
83 | * Empty subsets can be selected using `fst::fst` (thanks @renkun-ken for reporting)
84 |
85 | ## Documentation
86 |
87 | Various documentation issues have been fixed (thanks @ginberg and @renkun-ken for the pull requests).
88 |
89 |
90 | # fst 0.8.10
91 |
92 | Version 0.8.10 of the `fst` package is an intermediate release designed to update the incorporated C++ libraries
93 | to their latest versions and to fix reported issues. Also, per request of CRAN maintainers, the OpenMP build option was moved to the correct flag in the Makevars file, resolving a warning in the package check.
94 |
95 | ## Library updates
96 |
97 | * Library `fstlib` updated to version 0.1.0
98 |
99 | * Library `ZSTD` updated to version 1.3.7
100 |
101 | * Library `LZ4` updated to version 1.8.3
102 |
103 | ## Bugs solved
104 |
105 | * Method `compress_fst()` can handle vectors with sizes larger than 4 GB (issue #176, thanks @bwlewis for reporting)
106 |
107 | * A _fst_ file is correctly read from a subfolder on a network drive where the user does not have access to the top-level folder (issues #136 and #175, thanks @xiaodaigh for reporting).
108 |
109 | * The suggested data.table dependency is now properly escaped (issue #181, thanks @jangorecki for the pull request)
110 |
111 | ## Documentation
112 |
113 | * Documentation updates (issue #158, thanks @HughParsonage for submitting)
114 |
115 |
116 | # fst 0.8.8
117 |
118 | Version 0.8.8 of the `fst` package is an intermediate release designed to fix valgrind warnings reported on CRAN builds (per request of CRAN maintainers). These warnings were due to `fst` writing uninitialized data buffers to file, which was done to maximize speed. To fix these warnings (and for safety), all memory blocks are now initialized to zero before being written to disk.
119 |
120 |
121 | # fst 0.8.6
122 |
123 | Version 0.8.6 of the `fst` package brings clearer printing of `fst_table` objects. It also includes optimizations for controlling the number of threads used by the package during reads and writes and after a fork has ended. The `LZ4` and `ZSTD` compression libraries are updated to their latest (and fastest) releases. UTF-8 encoded column names are now correctly stored in the `fst` format.
124 |
125 | ## New features
126 |
127 | * More advanced printing generic of the `fst_table` reference object, showing column types, (possible) keys, and the table header and footer data (issue #131, thanks @renkun-ken for reporting and discussions).
128 |
129 | * User has more control over the number of threads used by fst. Option 'fst_threads' can now be used to initialize the number of threads when the package is first loaded (issue #132, thanks to @karldw for the pull request).
130 |
131 | * Option 'fst_restore_after_fork' can be used to select the threading behavior after a fork has ended. Like the `data.table` package, `fst` switches back to a single thread when a fork is detected (using OpenMP in a fork can lead to problems). Unlike `data.table`, the `fst` package restores the number of threads to it's previous setting when the fork ends. If this leads to unexpected problems, the user can set the 'fst_restore_after_fork' option to FALSE to disable that.
132 |
133 | ## Bugs solved
134 |
135 | * Character encoding of column names correctly stored in the `fst` format (issue #144, thanks @shrektan for reporting and discussions).
136 |
137 | ## Documentation
138 |
139 | * Improved accuracy of fst_table documentation regarding random row access (issue #143, thanks @martinblostein for pointed out the unclarity)
140 |
141 | * Improved documentation on background threads during `write_fst()` and `read_fst()` (issue #121, thanks @krlmlr for suggestions and discussion)
142 |
143 |
144 | # fst 0.8.4
145 |
146 | The v0.8.4 release brings a `data.frame` interface to the `fst` package. Column and row selection can now be done directly from the `[` operator. In addition, it fixes some issues and prepares the package for the next build toolchain of CRAN.
147 |
148 | ## New features
149 |
150 | * A `data.frame` interface was added to the package. The user can create a reference object to a `fst` file with method `fst`. That reference can be used like a `data.frame` and will automatically make column- and row- selections in the referenced `fst` file.
151 |
152 | ## Bugs solved
153 |
154 | * Build issues with the dev build of R have been fixed. In particular, `fst` now builds correctly with the Clang 6.0 toolchain which will be released by CRAN shortly (thanks @kevinushey for reporting the problem and CRAN maintainers for the advance warning.
155 |
156 | * An error was fixed where compressing a short factor column with 128 to 32767 levels but only a single value, returned incorrect results (issue #128, thanks @martinblostein for reporting and help fixing the problem).
157 |
158 | * An error was fixed where columns f type 'ITime' were incorrectly serialized (issue #126, thanks @Giqles for reporting the problem).
159 |
160 | * An error was fixed where using `fst` as a dependency in another package and building that package in RStudio, crashed RStudio. The problem was that RStudio uses a fork to build or document a package. That fork made `fst` use OpenMP library methods, which leads to crashes on macOS. After the fix, no calls to any OpenMP library method are now made from `fst` when it's run from a forked process (issue #100 and issue #109, thanks to @eipi10, @PeteHaitch, @kevinushey, @thierrygosselin, @xiaodaigh and @jzzcutler for reporting the problem and help fix it).
161 |
162 | ## Documentation
163 |
164 | * Documentation for method `write_fst` was improved (issue #123, thanks @krlmlr for reporting and submitting a pull request).
165 |
166 |
167 | # fst 0.8.2
168 |
169 | ## New features
170 |
171 | * Package `fst` has support for multi-threading using OpenMP. Compression, decompression and disk IO have been largely parallelized for (much) improved performance.
172 |
173 | * Many new column types are now supported by the `fst` format (where appropriate, both the `double` and `integer` variants are supported):
174 |
175 | * `raw`
176 | * `DateTime`
177 | * `integer64`
178 | * `nanotime`
179 | * `POSIXct`
180 | * `ordered factors`
181 | * `difftime`
182 |
183 | _Thanks @arunsrinivasan, @derekholmes, @phillc73, @HughParsonage, @statquant, @eddelbuettel, @eipi10, and @verajosemanuel for feature requests and helpful discussions._
184 |
185 | * Multi-threaded `LZ4` and `ZSTD` compression using methods `compress_fst` and `decompress_fst`. These methods provide a direct API to the `LZ4` and `ZSTD` compressors at speeds of multiple GB/s. A specific block format is used to facilitate parallel processing. For additional stability, hashes can be calculated if required.
186 |
187 | * Method `hash_fst` provides an extremely fast multi-threaded 64-bit hashing algorithm based on `xxHash`. Speeds up to the memory bandwidth can be achieved.
188 |
189 | * Faster conversion to `data.table` in `read_fst`. _Thanks @dselivanov_
190 |
191 | * Package `data.table` is now an optional dependency. _Thanks @jimhester_. Note that in the near future, a dependency on `data.table` will probably be introduced again, as `fst` will get a `data.table`-like interface.
192 |
193 | * The `fst` format has a _magic number_ to be able to identify a `fst` file without actually opening the file or requiring the `fstlib` library. _Thanks @davidanthoff._
194 |
195 | * For development versions, the build number is now shown when fst is loaded. _Thanks @skanskan._
196 |
197 | * Character encodings are preserved for character and factor columns. _Thanks @carioca67 and @adrianadermon_
198 |
199 | * Naming of fst methods is now consistent. _Thanks @jimhester and @brinkhuis._
200 |
201 | * The core C++ code with the API to read and write `fst` files, and use compression and hashing now lives in a separate library called [`fstlib`](https://github.com/fstpackage/fstlib). Although not visible to the user, this is a major development allowing `fst` to be implemented for other languages than `R` (with comparable performance).
202 |
203 | ## Bugs solved
204 |
205 | * Tilde-expansion in `write_fst` not correctly processed. _Thanks @HughParsonage, @PoGibas._
206 |
207 | * Writing more than INT_MAX rows crashes `fst`. _Thanks @wei-wu-nyc_
208 |
209 | * Incorrect fst file is created when an empty data.table is saved. _Thanks @wei-wu-nyc._
210 |
211 | * Error/crash when saving factor column with 0 factor levels. _Thanks @martinblostein._
212 |
213 | * No warning was given when disk runs out of space during a `fstwrite` operation.
214 |
215 | * A data.table warning message was given on modification of columns of a sorted table. _Thanks @martinblostein._
216 |
217 | * Stack imbalance warnings under certain conditions. _Thanks @ryankennedyio_
218 |
219 | ## Benchmarks
220 |
221 | Thanks to @mattdowle, @st-pasha, @phillc73 for valuable discussions on `fst` benchmarks and how to accurately perform (and present) them.
222 |
223 | ## Additional credits
224 |
225 | * Special thanks to @arunsrinivasan for a lot of valuable discussions on the future direction of the `fst` package, I hope `fst` may continue to benefit from your experience!
226 |
227 | * Thanks for reporting and discussing various bugs, inconsistencies, instabilities or installation problems to @treysp, @wei-wu-nyc, @khsu15, @PMassicotte, @xiaodaigh, @renkun-ken, @statquant, @tgolden23, @carioca67, @jzzcutler, @MehranMoghtadai.
228 |
229 | * And thanks to @mperone, @kendonB, @xiaodaigh, @derekholmes, @pmakai, @1beb, @BenoitLondon, @skanskan, @petermuller71, @nextpagesoft, @cawthm, @jeroenjanssens, @dselivanov, @Fpadt and @kbroman for helpful (online) discussions and (feature) requests. All the community feedback is much appreciated and tremendously helps to to improve the stability and usability of `fst`! (if I missed anyone, I apologize in advance, please let me know and I will fix this document ASAP)
230 |
--------------------------------------------------------------------------------
/R/fst_table.R:
--------------------------------------------------------------------------------
1 | # fst - R package for ultra fast storage and retrieval of datasets
2 | #
3 | # Copyright (C) 2017-present, Mark AJ Klik
4 | #
5 | # This file is part of the fst R package.
6 | #
7 | # The fst R package is free software: you can redistribute it and/or modify it
8 | # under the terms of the GNU Affero General Public License version 3 as
9 | # published by the Free Software Foundation.
10 | #
11 | # The fst R package is distributed in the hope that it will be useful, but
12 | # WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 | # FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License
14 | # for more details.
15 | #
16 | # You should have received a copy of the GNU Affero General Public License along
17 | # with the fst R package. If not, see .
18 | #
19 | # You can contact the author at:
20 | # - fst R package source repository : https://github.com/fstpackage/fst
21 |
22 |
23 | #' Access a fst file like a regular data frame
24 | #'
25 | #' Create a fst_table object that can be accessed like a regular data frame. This object
26 | #' is just a reference to the actual data and requires only a small amount of memory.
27 | #' When data is accessed, only a subset is read from file, depending on the minimum and
28 | #' maximum requested row number. This is possible because the fst file format allows full
29 | #' random access (in columns and rows) to the stored dataset.
30 | #'
31 | #' @inheritParams metadata_fst
32 | #' @return An object of class \code{fst_table}
33 | #' @export
34 | #' @examples
35 | #' \dontrun{
36 | #' # generate a sample fst file
37 | #' path <- paste0(tempfile(), ".fst")
38 | #' write_fst(iris, path)
39 | #'
40 | #' # create a fst_table object that can be used as a data frame
41 | #' ft <- fst(path)
42 | #'
43 | #' # print head and tail
44 | #' print(ft)
45 | #'
46 | #' # select columns and rows
47 | #' x <- ft[10:14, c("Petal.Width", "Species")]
48 | #'
49 | #' # use the common list interface
50 | #' ft[TRUE]
51 | #' ft[c(TRUE, FALSE)]
52 | #' ft[["Sepal.Length"]]
53 | #' ft$Petal.Length
54 | #'
55 | #' # use data frame generics
56 | #' nrow(ft)
57 | #' ncol(ft)
58 | #' dim(ft)
59 | #' dimnames(ft)
60 | #' colnames(ft)
61 | #' rownames(ft)
62 | #' names(ft)
63 | #' }
64 | fst <- function(path, old_format = FALSE) {
65 | # old format is deprecated as of v0.9.0
66 | if (old_format != FALSE) {
67 | stop(
68 | "Parameter old_format is depricated, fst files written with fst package version",
69 | " lower than 0.8.0 should be read (and rewritten) using fst package versions <= 0.8.10."
70 | )
71 | }
72 |
73 | # wrap in a list so that additional elements can be added if required
74 | ft <- list(
75 | meta = metadata_fst(path, old_format),
76 | col_selection = NULL,
77 | row_selection = NULL,
78 | old_format = old_format
79 | )
80 |
81 | # class attribute
82 | class(ft) <- "fst_table"
83 |
84 | ft
85 | }
86 |
87 |
88 | #' @export
89 | row.names.fst_table <- function(x) {
90 | as.character(seq_len(length(.subset2(x, "meta")$columnBaseTypes)))
91 | }
92 |
93 |
94 | #' @export
95 | dim.fst_table <- function(x) {
96 | c(.subset2(x, "meta")$nrOfRows, length(.subset2(x, "meta")$columnBaseTypes))
97 | }
98 |
99 |
100 | #' @export
101 | dimnames.fst_table <- function(x) {
102 | list(
103 | as.character(seq_len(.subset2(x, "meta")$nrOfRows)),
104 | .subset2(x, "meta")$columnNames
105 | )
106 | }
107 |
108 |
109 | #' @export
110 | names.fst_table <- function(x) {
111 | .subset2(x, "meta")$columnNames
112 | }
113 |
114 |
115 | #' @export
116 | `[[.fst_table` <- function(x, j, exact = TRUE) {
117 | if (!exact) {
118 | warning("exact ignored", call. = FALSE)
119 | }
120 |
121 | meta_info <- .subset2(x, "meta")
122 |
123 | if (length(j) != 1) {
124 | # select at least one column number
125 | if (length(j) == 0) {
126 | stop("Please use a length one integer or character vector to specify the column", call. = FALSE)
127 | }
128 |
129 | # recursive indexing (up to level 1)
130 |
131 | if (length(j) != 2) {
132 | stop("Recursive indexing is currently only supported up to level 1.", call. = FALSE)
133 | }
134 |
135 | if (is.character(j)) {
136 | stop("Subscript out of bounds.", call. = FALSE)
137 | }
138 |
139 | # check row number
140 |
141 | if (j[2] < 1 || j[2] > meta_info$nrOfRows) {
142 | stop("Second index out of bounds.", call. = FALSE)
143 | }
144 |
145 | col_name <- meta_info$columnNames[as.integer(j[1])]
146 |
147 | return(
148 | read_fst(
149 | meta_info$path,
150 | col_name,
151 | from = j[2],
152 | to = j[2],
153 | old_format = .subset2(x, "old_format")
154 | )[[1]]
155 | )
156 | }
157 |
158 | if (!(is.numeric(j) || is.character(j))) {
159 | stop("Please use a length 1 integer of character vector to specify the column", call. = FALSE)
160 | }
161 |
162 | # length one integer column selection
163 | if (is.numeric(j)) {
164 | if (j < 1 || j > length(meta_info$columnNames)) {
165 | stop("Invalid column index ", j, call. = FALSE)
166 | }
167 |
168 | j <- meta_info$columnNames[as.integer(j)]
169 | } else {
170 | if (!(j %in% meta_info$columnNames)) {
171 | return(NULL)
172 | }
173 | }
174 |
175 | # determine row selection here from metadata
176 |
177 | read_fst(meta_info$path, j, old_format = .subset2(x, "old_format"))[[1]]
178 | }
179 |
180 |
181 | # override needed to avoid the [[ operator messing up the str output
182 |
183 | #' @export
184 | str.fst_table <- function(object, ...) {
185 | str(unclass(object), ...)
186 | }
187 |
188 |
189 | #' @export
190 | `$.fst_table` <- function(x, j) {
191 | x[[j]]
192 | }
193 |
194 |
195 | #' @export
196 | print.fst_table <- function(x, number_of_rows = 50, ...) {
197 | meta_info <- .subset2(x, "meta")
198 |
199 | cat("\n")
200 | cat(meta_info$nrOfRows, " rows, ", length(meta_info$columnNames),
201 | " columns (", basename(meta_info$path), ")\n\n",
202 | sep = ""
203 | )
204 |
205 | if (!is.numeric(number_of_rows)) number_of_rows <- 100L
206 | if (!is.infinite(number_of_rows)) number_of_rows <- as.integer(number_of_rows)
207 | if (number_of_rows <= 0L) {
208 | return(invisible())
209 | } # ability to turn off printing
210 |
211 | table_splitted <- (meta_info$nrOfRows > number_of_rows) && (meta_info$nrOfRows > 10)
212 |
213 | if (table_splitted) {
214 | sample_data_head <- read_fst(meta_info$path, from = 1, to = 5, old_format = .subset2(x, "old_format"))
215 | sample_data_tail <- read_fst(meta_info$path,
216 | from = meta_info$nrOfRows - 4, to = meta_info$nrOfRows,
217 | old_format = .subset2(x, "old_format")
218 | )
219 |
220 | sample_data <- rbind.data.frame(sample_data_head, sample_data_tail)
221 | } else {
222 | sample_data <- read_fst(meta_info$path, old_format = .subset2(x, "old_format"))
223 | }
224 |
225 | # use bit64 package if available for correct printing
226 | if ((!"bit64" %in% loadedNamespaces()) && any(sapply(sample_data, inherits, "integer64"))) require_bit64() # nolint
227 | if ((!"nanotime" %in% loadedNamespaces()) && any(sapply(sample_data, inherits, "nanotime"))) require_nanotime() # nolint
228 | if ((!"data.table" %in% loadedNamespaces()) && any(sapply(sample_data, inherits, "ITime"))) require_data_table() # nolint
229 |
230 | types <- c(
231 | "unknown", "character", "factor", "ordered factor", "integer", "POSIXct", "difftime",
232 | "IDate", "ITime", "double", "Date", "POSIXct", "difftime", "ITime", "logical", "integer64",
233 | "nanotime", "raw"
234 | )
235 |
236 | # turn off colored output at default
237 | color_on <- FALSE
238 |
239 | if (requireNamespace("crayon", quietly = TRUE)) {
240 | color_on <- crayon::has_color() # terminal has color
241 | }
242 |
243 | type_row <- matrix(paste("<", types[meta_info$columnTypes], ">", sep = ""), nrow = 1)
244 | colnames(type_row) <- meta_info$columnNames
245 |
246 | # convert to aligned character columns
247 | sample_data_print <- format(sample_data)
248 |
249 | if (table_splitted) {
250 | dot_row <- matrix(rep("--", length(meta_info$columnNames)), nrow = 1)
251 | colnames(dot_row) <- meta_info$columnNames
252 |
253 | sample_data_print <- rbind(
254 | type_row,
255 | sample_data_print[1:5, , drop = FALSE],
256 | dot_row,
257 | sample_data_print[6:10, , drop = FALSE]
258 | )
259 |
260 | rownames(sample_data_print) <- c(" ", 1:5, "--", (meta_info$nrOfRows - 4):meta_info$nrOfRows)
261 |
262 | y <- capture.output(print(sample_data_print))
263 |
264 | # the length of y must be a multiple of 13 and color must be permitted
265 | # if not, take defensive action; skip coloring and solve later
266 | if (!color_on || (length(y) %% 13 != 0)) {
267 | print(sample_data_print)
268 | return(invisible(x))
269 | }
270 |
271 | type_rows <- seq(2, length(y), 13)
272 | gray_rows <- seq(8, length(y), 13)
273 |
274 | y[gray_rows] <- paste0("\033[38;5;248m", y[gray_rows], "\033[39m")
275 |
276 | gray_rows <- c(type_rows, gray_rows)
277 | } else {
278 | # table is not splitted along the row axis
279 | sample_data_print <- rbind(
280 | type_row,
281 | sample_data_print
282 | )
283 |
284 | rownames(sample_data_print) <- c(" ", seq_len(meta_info$nrOfRows))
285 |
286 | # no color terminal available
287 | if (!color_on) {
288 | print(sample_data_print)
289 | return(invisible(x))
290 | }
291 |
292 | y <- capture.output(print(sample_data_print))
293 |
294 | gray_rows <- type_rows <- seq(2, length(y), 2 + meta_info$nrOfRows)
295 | }
296 |
297 | # type rows are set to italic light grey
298 | y[type_rows] <- paste0("\033[3m\033[38;5;248m", y[type_rows], "\033[39m\033[23m")
299 |
300 | # use light grey color up to width of row name column
301 | row_text_size <- regexpr("^[0-9-]*", tail(y, 1))
302 | row_text_size <- attr(row_text_size, "match.length")
303 |
304 | y[-gray_rows] <- paste0(
305 | "\033[38;5;248m", substr(y[-gray_rows], 1, row_text_size),
306 | "\033[39m", substr(y[-gray_rows], row_text_size + 1, nchar(y[-gray_rows]))
307 | )
308 |
309 | cat(y, sep = "\n")
310 | return(invisible(x))
311 | }
312 |
313 |
314 | #' @export
315 | as.data.frame.fst_table <- function(x, row.names = NULL, optional = FALSE, ...) { # nolint
316 | meta_info <- .subset2(x, "meta")
317 | as.data.frame(read_fst(meta_info$path, old_format = .subset2(x, "old_format")), row.names, optional, ...)
318 | }
319 |
320 | #' @export
321 | as.list.fst_table <- function(x, ...) {
322 | as.list(as.data.frame(x))
323 | }
324 |
325 |
326 | .column_indexes_fst <- function(meta_info, j) {
327 | # test correct column names
328 | if (is.character(j)) {
329 | wrong <- !(j %in% meta_info$columnNames)
330 |
331 | if (any(wrong)) {
332 | names <- j[wrong]
333 | stop(sprintf("Undefined columns: %s", paste(names, collapse = ", ")))
334 | }
335 | } else if (is.logical(j)) {
336 | if (any(is.na(j))) {
337 | stop("Subscript out of bounds.", call. = FALSE)
338 | }
339 |
340 | j <- meta_info$columnNames[j]
341 | } else if (is.numeric(j)) {
342 | if (any(is.na(j))) {
343 | stop("Subscript out of bounds.", call. = FALSE)
344 | }
345 |
346 | if (any(j <= 0)) {
347 | stop("Only positive column indexes supported.", call. = FALSE)
348 | }
349 |
350 | if (any(j > length(meta_info$columnBaseTypes))) {
351 | stop("Subscript out of bounds.", call. = FALSE)
352 | }
353 |
354 | j <- meta_info$columnNames[j]
355 | }
356 |
357 | j
358 | }
359 |
360 |
361 | # drop to lower dimension when drop = TRUE
362 | return_drop <- function(x, drop) {
363 | if (!drop || ncol(x) > 1) {
364 | return(x)
365 | }
366 |
367 | x[[1]]
368 | }
369 |
370 |
371 | #' @export
372 | `[.fst_table` <- function(x, i, j, drop) {
373 | # check for old_format in case an 'old' fst_table object was deserialized
374 | if (.subset2(x, "old_format") != FALSE) {
375 | stop(
376 | "fst files written with fst package version",
377 | " lower than 0.8.0 should be read (and rewritten) using fst package versions <= 0.8.10."
378 | )
379 | }
380 |
381 | meta_info <- .subset2(x, "meta")
382 |
383 | # no additional arguments provided
384 |
385 | if (missing(i) && missing(j)) {
386 | # never drop as with data.frame
387 | return(read_fst(meta_info$path))
388 | }
389 |
390 |
391 | if (nargs() <= 2) {
392 | # result is never dropped with 2 arguments
393 |
394 | if (missing(i)) {
395 | # we have a named argument j
396 | j <- .column_indexes_fst(meta_info, j)
397 | return(read_fst(meta_info$path, j))
398 | }
399 |
400 | # i is interpreted as j
401 | j <- .column_indexes_fst(meta_info, i)
402 | return(read_fst(meta_info$path, j))
403 | }
404 |
405 | # drop dimension if single column selected and drop != FALSE
406 | drop_dim <- FALSE
407 |
408 | if (!missing(j) && length(j) == 1) {
409 | if (!(!missing(drop) && drop == FALSE)) {
410 | drop_dim <- TRUE
411 | }
412 | }
413 |
414 | # special case where i is interpreted as j: select all rows, never drop
415 |
416 | if (nargs() == 3 && !missing(drop) && !missing(i)) {
417 | j <- .column_indexes_fst(meta_info, i)
418 | return(read_fst(meta_info$path, j))
419 | }
420 |
421 | # i and j not reversed
422 |
423 | # full columns
424 | if (missing(i)) {
425 | j <- .column_indexes_fst(meta_info, j)
426 | x <- read_fst(meta_info$path, j)
427 |
428 | if (!drop_dim) {
429 | return(x)
430 | }
431 | return(x[[1]])
432 | }
433 |
434 |
435 | # determine integer vector from i
436 | if (!(is.numeric(i) || is.logical(i))) {
437 | stop("Row selection should be done using a numeric or logical vector", call. = FALSE)
438 | }
439 |
440 | if (is.logical(i)) {
441 | i <- which(i)
442 | }
443 |
444 | # cast to integer and determine row range
445 | i <- as.integer(i)
446 |
447 | # empty row selection
448 | if (length(i) == 0) {
449 | min_row <- 1
450 | max_row <- 1
451 | } else {
452 | min_row <- min(i)
453 | max_row <- max(i)
454 |
455 | # boundary check
456 | if (min_row < 0) {
457 | stop("Row selection out of range")
458 | }
459 |
460 | if (max_row > meta_info$nrOfRows) {
461 | stop("Row selection out of range")
462 | }
463 | }
464 |
465 | # column subset
466 |
467 | # select all columns
468 | if (missing(j)) {
469 | fst_data <- read_fst(meta_info$path, from = min_row, to = max_row)
470 | x <- fst_data[1 + i - min_row, ] # row selection, no dropping
471 | } else {
472 | j <- .column_indexes_fst(meta_info, j)
473 | fst_data <- read_fst(meta_info$path, j, from = min_row, to = max_row)
474 | x <- fst_data[1 + i - min_row, , drop = FALSE] # row selection, no dropping
475 | }
476 |
477 | if (!drop_dim) {
478 | return(x)
479 | }
480 | return(x[[1]])
481 | }
482 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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406 | finally terminates your license, and (b) permanently, if the copyright
407 | holder fails to notify you of the violation by some reasonable means
408 | prior to 60 days after the cessation.
409 |
410 | Moreover, your license from a particular copyright holder is
411 | reinstated permanently if the copyright holder notifies you of the
412 | violation by some reasonable means, this is the first time you have
413 | received notice of violation of this License (for any work) from that
414 | copyright holder, and you cure the violation prior to 30 days after
415 | your receipt of the notice.
416 |
417 | Termination of your rights under this section does not terminate the
418 | licenses of parties who have received copies or rights from you under
419 | this License. If your rights have been terminated and not permanently
420 | reinstated, you do not qualify to receive new licenses for the same
421 | material under section 10.
422 |
423 | 9. Acceptance Not Required for Having Copies.
424 |
425 | You are not required to accept this License in order to receive or
426 | run a copy of the Program. Ancillary propagation of a covered work
427 | occurring solely as a consequence of using peer-to-peer transmission
428 | to receive a copy likewise does not require acceptance. However,
429 | nothing other than this License grants you permission to propagate or
430 | modify any covered work. These actions infringe copyright if you do
431 | not accept this License. Therefore, by modifying or propagating a
432 | covered work, you indicate your acceptance of this License to do so.
433 |
434 | 10. Automatic Licensing of Downstream Recipients.
435 |
436 | Each time you convey a covered work, the recipient automatically
437 | receives a license from the original licensors, to run, modify and
438 | propagate that work, subject to this License. You are not responsible
439 | for enforcing compliance by third parties with this License.
440 |
441 | An "entity transaction" is a transaction transferring control of an
442 | organization, or substantially all assets of one, or subdividing an
443 | organization, or merging organizations. If propagation of a covered
444 | work results from an entity transaction, each party to that
445 | transaction who receives a copy of the work also receives whatever
446 | licenses to the work the party's predecessor in interest had or could
447 | give under the previous paragraph, plus a right to possession of the
448 | Corresponding Source of the work from the predecessor in interest, if
449 | the predecessor has it or can get it with reasonable efforts.
450 |
451 | You may not impose any further restrictions on the exercise of the
452 | rights granted or affirmed under this License. For example, you may
453 | not impose a license fee, royalty, or other charge for exercise of
454 | rights granted under this License, and you may not initiate litigation
455 | (including a cross-claim or counterclaim in a lawsuit) alleging that
456 | any patent claim is infringed by making, using, selling, offering for
457 | sale, or importing the Program or any portion of it.
458 |
459 | 11. Patents.
460 |
461 | A "contributor" is a copyright holder who authorizes use under this
462 | License of the Program or a work on which the Program is based. The
463 | work thus licensed is called the contributor's "contributor version".
464 |
465 | A contributor's "essential patent claims" are all patent claims
466 | owned or controlled by the contributor, whether already acquired or
467 | hereafter acquired, that would be infringed by some manner, permitted
468 | by this License, of making, using, or selling its contributor version,
469 | but do not include claims that would be infringed only as a
470 | consequence of further modification of the contributor version. For
471 | purposes of this definition, "control" includes the right to grant
472 | patent sublicenses in a manner consistent with the requirements of
473 | this License.
474 |
475 | Each contributor grants you a non-exclusive, worldwide, royalty-free
476 | patent license under the contributor's essential patent claims, to
477 | make, use, sell, offer for sale, import and otherwise run, modify and
478 | propagate the contents of its contributor version.
479 |
480 | In the following three paragraphs, a "patent license" is any express
481 | agreement or commitment, however denominated, not to enforce a patent
482 | (such as an express permission to practice a patent or covenant not to
483 | sue for patent infringement). To "grant" such a patent license to a
484 | party means to make such an agreement or commitment not to enforce a
485 | patent against the party.
486 |
487 | If you convey a covered work, knowingly relying on a patent license,
488 | and the Corresponding Source of the work is not available for anyone
489 | to copy, free of charge and under the terms of this License, through a
490 | publicly available network server or other readily accessible means,
491 | then you must either (1) cause the Corresponding Source to be so
492 | available, or (2) arrange to deprive yourself of the benefit of the
493 | patent license for this particular work, or (3) arrange, in a manner
494 | consistent with the requirements of this License, to extend the patent
495 | license to downstream recipients. "Knowingly relying" means you have
496 | actual knowledge that, but for the patent license, your conveying the
497 | covered work in a country, or your recipient's use of the covered work
498 | in a country, would infringe one or more identifiable patents in that
499 | country that you have reason to believe are valid.
500 |
501 | If, pursuant to or in connection with a single transaction or
502 | arrangement, you convey, or propagate by procuring conveyance of, a
503 | covered work, and grant a patent license to some of the parties
504 | receiving the covered work authorizing them to use, propagate, modify
505 | or convey a specific copy of the covered work, then the patent license
506 | you grant is automatically extended to all recipients of the covered
507 | work and works based on it.
508 |
509 | A patent license is "discriminatory" if it does not include within
510 | the scope of its coverage, prohibits the exercise of, or is
511 | conditioned on the non-exercise of one or more of the rights that are
512 | specifically granted under this License. You may not convey a covered
513 | work if you are a party to an arrangement with a third party that is
514 | in the business of distributing software, under which you make payment
515 | to the third party based on the extent of your activity of conveying
516 | the work, and under which the third party grants, to any of the
517 | parties who would receive the covered work from you, a discriminatory
518 | patent license (a) in connection with copies of the covered work
519 | conveyed by you (or copies made from those copies), or (b) primarily
520 | for and in connection with specific products or compilations that
521 | contain the covered work, unless you entered into that arrangement,
522 | or that patent license was granted, prior to 28 March 2007.
523 |
524 | Nothing in this License shall be construed as excluding or limiting
525 | any implied license or other defenses to infringement that may
526 | otherwise be available to you under applicable patent law.
527 |
528 | 12. No Surrender of Others' Freedom.
529 |
530 | If conditions are imposed on you (whether by court order, agreement or
531 | otherwise) that contradict the conditions of this License, they do not
532 | excuse you from the conditions of this License. If you cannot convey a
533 | covered work so as to satisfy simultaneously your obligations under this
534 | License and any other pertinent obligations, then as a consequence you may
535 | not convey it at all. For example, if you agree to terms that obligate you
536 | to collect a royalty for further conveying from those to whom you convey
537 | the Program, the only way you could satisfy both those terms and this
538 | License would be to refrain entirely from conveying the Program.
539 |
540 | 13. Remote Network Interaction; Use with the GNU General Public License.
541 |
542 | Notwithstanding any other provision of this License, if you modify the
543 | Program, your modified version must prominently offer all users
544 | interacting with it remotely through a computer network (if your version
545 | supports such interaction) an opportunity to receive the Corresponding
546 | Source of your version by providing access to the Corresponding Source
547 | from a network server at no charge, through some standard or customary
548 | means of facilitating copying of software. This Corresponding Source
549 | shall include the Corresponding Source for any work covered by version 3
550 | of the GNU General Public License that is incorporated pursuant to the
551 | following paragraph.
552 |
553 | Notwithstanding any other provision of this License, you have
554 | permission to link or combine any covered work with a work licensed
555 | under version 3 of the GNU General Public License into a single
556 | combined work, and to convey the resulting work. The terms of this
557 | License will continue to apply to the part which is the covered work,
558 | but the work with which it is combined will remain governed by version
559 | 3 of the GNU General Public License.
560 |
561 | 14. Revised Versions of this License.
562 |
563 | The Free Software Foundation may publish revised and/or new versions of
564 | the GNU Affero General Public License from time to time. Such new versions
565 | will be similar in spirit to the present version, but may differ in detail to
566 | address new problems or concerns.
567 |
568 | Each version is given a distinguishing version number. If the
569 | Program specifies that a certain numbered version of the GNU Affero General
570 | Public License "or any later version" applies to it, you have the
571 | option of following the terms and conditions either of that numbered
572 | version or of any later version published by the Free Software
573 | Foundation. If the Program does not specify a version number of the
574 | GNU Affero General Public License, you may choose any version ever published
575 | by the Free Software Foundation.
576 |
577 | If the Program specifies that a proxy can decide which future
578 | versions of the GNU Affero General Public License can be used, that proxy's
579 | public statement of acceptance of a version permanently authorizes you
580 | to choose that version for the Program.
581 |
582 | Later license versions may give you additional or different
583 | permissions. However, no additional obligations are imposed on any
584 | author or copyright holder as a result of your choosing to follow a
585 | later version.
586 |
587 | 15. Disclaimer of Warranty.
588 |
589 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
590 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
591 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
592 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
593 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
594 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
595 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
596 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
597 |
598 | 16. Limitation of Liability.
599 |
600 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
601 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
602 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
603 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
604 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
605 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
606 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
607 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
608 | SUCH DAMAGES.
609 |
610 | 17. Interpretation of Sections 15 and 16.
611 |
612 | If the disclaimer of warranty and limitation of liability provided
613 | above cannot be given local legal effect according to their terms,
614 | reviewing courts shall apply local law that most closely approximates
615 | an absolute waiver of all civil liability in connection with the
616 | Program, unless a warranty or assumption of liability accompanies a
617 | copy of the Program in return for a fee.
618 |
619 | END OF TERMS AND CONDITIONS
620 |
621 | How to Apply These Terms to Your New Programs
622 |
623 | If you develop a new program, and you want it to be of the greatest
624 | possible use to the public, the best way to achieve this is to make it
625 | free software which everyone can redistribute and change under these terms.
626 |
627 | To do so, attach the following notices to the program. It is safest
628 | to attach them to the start of each source file to most effectively
629 | state the exclusion of warranty; and each file should have at least
630 | the "copyright" line and a pointer to where the full notice is found.
631 |
632 |
633 | Copyright (C)
634 |
635 | This program is free software: you can redistribute it and/or modify
636 | it under the terms of the GNU Affero General Public License as published by
637 | the Free Software Foundation, either version 3 of the License, or
638 | (at your option) any later version.
639 |
640 | This program is distributed in the hope that it will be useful,
641 | but WITHOUT ANY WARRANTY; without even the implied warranty of
642 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
643 | GNU Affero General Public License for more details.
644 |
645 | You should have received a copy of the GNU Affero General Public License
646 | along with this program. If not, see .
647 |
648 | Also add information on how to contact you by electronic and paper mail.
649 |
650 | If your software can interact with users remotely through a computer
651 | network, you should also make sure that it provides a way for users to
652 | get its source. For example, if your program is a web application, its
653 | interface could display a "Source" link that leads users to an archive
654 | of the code. There are many ways you could offer source, and different
655 | solutions will be better for different programs; see section 13 for the
656 | specific requirements.
657 |
658 | You should also get your employer (if you work as a programmer) or school,
659 | if any, to sign a "copyright disclaimer" for the program, if necessary.
660 | For more information on this, and how to apply and follow the GNU AGPL, see
661 | .
662 |
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