This module implements integration tests for Influx API
This module implements integration tests for Influx API
This module implements integration tests for InfluxDB. As such, they record in 31 | code the assumptions made with regards to the HTTP API. Given that these tests 32 | pass, the unit tests are sufficient to guarantee correct behaviour.
This module makes sure that using vibe corresponds in using the HTTP API 33 | correctly.
Delete this DB
A result of a query
InfluxDB(https://www.influxdata.com/products/) is an open source time-series database. 31 | It supports high write loads, large data set storage, and conserves space through downsampling, automatically expiring and deleting 32 | unwanted data as well as backup and restore. InfluxDB also makes it easy to analyze data by providing an easy-to-use SQL-like query language.
This library implements a convenience wrapper API for influx.
InfluxDB(https://www.influxdata.com/products/) is an open source time-series database. 31 | It supports high write loads, large data set storage, and conserves space through downsampling, automatically expiring and deleting 32 | unwanted data as well as backup and restore. InfluxDB also makes it easy to analyze data by providing an easy-to-use SQL-like query language.
This library implements a convenience wrapper API for influx.
An InfluxDB measurement
Sends management commands to the DB (CREATE, DROP). 31 | The parameter must be the full command (e.g. "DROP DATABASE mydb")
Conversion utilities that help to work with Mir Series and ndslice.
To use this module mir-algorithm package should be included into users dub.json file.
Converts MeasurementSeries.Rows to Mir Series.
mir.timeserires
BSD 3-clause
Kaleidic Associates Advisory Limited
Converts a DateTime to a string suitable for use in queries 31 | e.g. SELECT * FROM foo WHERE time >=
Converts a SysTime to a string suitable for use in queries 31 | e.g. SELECT * FROM foo WHERE time >=
The two lines must be equivalent under InfluxDB's line protocol 31 | Since the tags and fields aren't ordered, a straight comparison 32 | might yield false errors. 33 | The timestamp is also taken care of by comparing it to the current timestamp 34 | and making sure not too much time has passed since then
Insert data into the DB.
Insert data into the DB.
This module implements a convenience wrapper API for influx.
Converts a DateTime to a string suitable for use in queries 31 | e.g. SELECT * FROM foo WHERE time >=
Converts a SysTime to a string suitable for use in queries 32 | e.g. SELECT * FROM foo WHERE time >=
Holds information about the database name and URL, forwards 33 | it to the implemetation functions for managing, querying and 34 | writing to the DB
An InfluxDB measurement
Data for one measurement
A query response
A result of a query
This module implements integration tests for Influx API
1 enum jsonString = ` 31 | 2 { 32 | 3 "results": [{ 33 | 4 "series": [{ 34 | 5 "columns": ["time", "othervalue", "tag1", "tag2", "value"], 35 | 6 "name": "myname", 36 | 7 "values": [ 37 | 8 ["2015-06-11T20:46:02Z", 4, "toto", "titi", 2], 38 | 9 ["2017-03-14T23:15:01.06282785Z", 3, "letag", "othertag", 1] 39 | 10 ] 40 | 11 }], 41 | 12 "statement_id": 42 42 | 13 }] 43 | 14 } 44 | 15 `; 45 | 16 46 | 17 jsonString.deserialize!Response.shouldEqual( 47 | 18 Response( 48 | 19 [ 49 | 20 Result( 50 | 21 [ 51 | 22 MeasurementSeries( 52 | 23 "myname", //name 53 | 24 ["time", "othervalue", "tag1", "tag2", "value"], //columns 54 | 25 //values 55 | 26 [ 56 | 27 ["2015-06-11T20:46:02Z", "4", "toto", "titi", "2"], 57 | 28 ["2017-03-14T23:15:01.06282785Z", "3", "letag", "othertag", "1"], 58 | 29 ] 59 | 30 ), 60 | 31 ], 61 | 32 62 | 33 42, // statement_id 63 | 34 ) 64 | 35 ] 65 | 36 ) 66 | 37 ); 67 |
This module makes sure that using vibe corresponds in using the HTTP API 31 | correctly.
1 manage(influxURL, "DROP DATABASE test_vibe_db"); 32 | 2 wait; 33 | 3 manage(influxURL, "CREATE DATABASE test_vibe_db"); 34 | 4 wait; 35 | 5 manage(influxURL, "DROP DATABASE test_vibe_db"); 36 | 6 wait; 37 |
1 manage(influxURL, "DROP DATABASE test_vibe_db"); 38 | 2 wait; 39 | 3 manage(influxURL, "CREATE DATABASE test_vibe_db"); 40 | 4 wait; 41 | 5 scope(exit) { 42 | 6 manage(influxURL, "DROP DATABASE test_vibe_db"); 43 | 7 wait; 44 | 8 } 45 | 9 46 | 10 const json = query(influxURL, "test_vibe_db", "SELECT * from foo").parseJSON; 47 | 11 JSONValue expected; 48 | 12 JSONValue result; 49 | 13 result["statement_id"] = JSONValue(0); 50 | 14 expected["results"] = [result]; 51 | 15 json.shouldEqual(expected); 52 |
Example of a response (prettified): 53 | { 54 | "results": [{ 55 | "series": [{ 56 | "columns": ["time", "othervalue", "tag1", "tag2", "value"], 57 | "name": "foo", 58 | "values": [ 59 | ["2015-06-11T20:46:02Z", 4, "toto", "titi", 2], 60 | ["2017-03-14T23:15:01.06282785Z", 3, "letag", "othertag", 1] 61 | ] 62 | }], 63 | "statement_id": 0 64 | }] 65 | } 66 | */ 67 | //
1 import std.algorithm: map; 68 | 2 69 | 3 manage(influxURL, "DROP DATABASE test_vibe_db"); 70 | 4 wait; 71 | 5 manage(influxURL, "CREATE DATABASE test_vibe_db"); 72 | 6 wait; 73 | 7 scope(exit) { 74 | 8 manage(influxURL, "DROP DATABASE test_vibe_db"); 75 | 9 wait; 76 | 10 } 77 | 11 78 | 12 write(influxURL, "test_vibe_db", "foo,tag1=letag,tag2=othertag value=1,othervalue=3"); 79 | 13 write(influxURL, "test_vibe_db", "foo,tag1=toto,tag2=titi value=2,othervalue=4 1434055562000000000"); 80 | 14 wait; 81 | 15 82 | 16 { 83 | 17 const json = query(influxURL, "test_vibe_db", "SELECT * from foo").parseJSON; 84 | 18 const result = json.object["results"].array[0].object; 85 | 19 const table = result["series"].array[0].object; 86 | 20 table["columns"].array.map!(a => a.str).shouldBeSameSetAs( 87 | 21 ["time", "othervalue", "tag1", "tag2", "value"]); 88 | 22 table["name"].str.shouldEqual("foo"); 89 | 23 table["values"].array.length.shouldEqual(2); 90 | 24 } 91 |
Insert Mir times-series with single column into the DB. 31 | Supported time types are SysTime, DateTime, Date, and long.
See also the example in the mir-integration folder.
measurement name
column name
1D time-series
list of tags to add to each measurement (optional)
Insert Mir times-series with multiple columns into the DB. 31 | Supported time types are SysTime, DateTime, Date, and long.
See also the example in the mir-integration folder.
measurement name
array of column names
2D time-series
list of tags to add to each measurement (optional)
Converts MeasurementSeries.Rows to Mir Series.
Time type. Default time type is DateTime. Supported types are SysTime, DateTime, and Date.
Data type. Default data type is double.
MeasurementSeries rows
List of columns (optional). The "time" colummn is ignored.
2D Mir Series.
1 import mir.series; 31 | 2 import std.datetime: DateTime; 32 | 3 33 | 4 auto influxSeries = MeasurementSeries("coolness", 34 | 5 ["time", "foo", "bar"], 35 | 6 [ 36 | 7 ["2015-06-11T20:46:02Z", "1.0", "2.0"], 37 | 8 ["2013-02-09T12:34:56Z", "3.0", "4.0"], 38 | 9 ]); 39 | 10 40 | 11 auto series = influxSeries.rows.toMirSeries; 41 | 12 42 | 13 // sort data if required 43 | 14 { 44 | 15 import mir.ndslice.algorithm: all; 45 | 16 import mir.ndslice.allocation: uninitSlice; 46 | 17 import mir.ndslice.topology: pairwise; 47 | 18 48 | 19 if (!series.time.pairwise!"a <= b".all) 49 | 20 { 50 | 21 series.sort( 51 | 22 uninitSlice!size_t(series.length), // index buffer 52 | 23 uninitSlice!double(series.length)); // data buffer 53 | 24 } 54 | 25 } 55 | 26 56 | 27 assert(series.time == [ 57 | 28 DateTime(2013, 2, 9, 12, 34, 56), 58 | 29 DateTime(2015, 6, 11, 20, 46, 2)]); 59 | 30 60 | 31 assert(series.data == [ 61 | 32 [3.0, 4.0], 62 | 33 [1.0, 2.0]]); 63 |
This module implements integration tests for Influx API
1 31 | 2 import influxdb.api: Database, Measurement; 32 | 3 33 | 4 const database = Database(influxURL, "myspecialDB"); 34 | 5 scope(exit) database.drop; 35 | 6 36 | 7 database.insert(Measurement("cpu", ["tag1": "foo"], ["temperature": "42"])); 37 | 8 database.insert(Measurement("cpu", ["tag1": "foo"], ["temperature": "68"])); 38 | 9 39 | 10 { 40 | 11 const response = database.query("SELECT * from cpu"); 41 | 12 const result = response.results[0]; 42 | 13 const series = result.series[0]; 43 | 14 series.rows.length.shouldEqual(2); 44 | 15 } 45 | 16 46 | 17 { 47 | 18 const response = database.query("SELECT * from cpu WHERE temperature > 50"); 48 | 19 const result = response.results[0]; 49 | 20 const series = result.series[0]; 50 | 21 series.rows.length.shouldEqual(1); 51 | 22 } 52 |
1 53 | 2 import influxdb.api: Database, Measurement; 54 | 3 55 | 4 const database = Database(influxURL, "myspecialDB"); 56 | 5 scope(exit) database.drop; 57 | 6 58 | 7 database.insert(Measurement("cpu", ["tag1": "foo"], ["temperature": "42"]), 59 | 8 Measurement("cpu", ["tag1": "bar"], ["temperature": "68"]), 60 | 9 Measurement("cpu", ["tag1": "baz"], ["temperature": "54"])); 61 | 10 62 | 11 const response = database.query("SELECT * from cpu WHERE temperature > 50"); 63 | 12 const result = response.results[0]; 64 | 13 const series = result.series[0]; 65 | 14 series.rows.length.shouldEqual(2); 66 |
1 67 | 2 import influxdb.api: Database, Measurement; 68 | 3 import std.datetime; 69 | 4 70 | 5 const database = Database(influxURL, "myspecialDB"); 71 | 6 scope(exit) database.drop; 72 | 7 73 | 8 database.insert(Measurement("cpu", ["tag1": "foo"], ["temperature": "42"], SysTime(DateTime(2017, 1, 1)))); 74 | 9 database.insert(Measurement("cpu", ["tag1": "foo"], ["temperature": "68"], SysTime(DateTime(2015, 1, 1)))); 75 | 10 76 | 11 { 77 | 12 const response = database.query("SELECT * from cpu"); 78 | 13 const result = response.results[0]; 79 | 14 const series = result.series[0]; 80 | 15 series.rows.length.shouldEqual(2); 81 | 16 } 82 | 17 83 | 18 { 84 | 19 const response = database.query("SELECT * from cpu WHERE time >= '2016-01-01 00:00:00'"); 85 | 20 const result = response.results[0]; 86 | 21 const series = result.series[0]; 87 | 22 series.rows.length.shouldEqual(1); 88 | 23 } 89 |
Data for one measurement
1 31 | 2 import std.datetime: SysTime, DateTime, UTC; 32 | 3 import std.array: array; 33 | 4 34 | 5 auto series = MeasurementSeries("coolness", 35 | 6 ["time", "foo", "bar"], 36 | 7 [ 37 | 8 ["2015-06-11T20:46:02Z", "red", "blue"], 38 | 9 ["2013-02-09T12:34:56Z", "green", "yellow"], 39 | 10 ]); 40 | 11 41 | 12 series.rows[0]["foo"].shouldEqual("red"); 42 | 13 series.rows[0]["time"].shouldEqual("2015-06-11T20:46:02Z"); 43 | 14 series.rows[0].time.shouldEqual(SysTime(DateTime(2015, 06, 11, 20, 46, 2), UTC())); 44 | 15 45 | 16 series.rows[1]["bar"].shouldEqual("yellow"); 46 | 17 series.rows[1]["time"].shouldEqual("2013-02-09T12:34:56Z"); 47 | 18 series.rows[1].time.shouldEqual(SysTime(DateTime(2013, 2, 9, 12, 34, 56), UTC())); 48 | 19 49 | 20 series.rows["time"][0].shouldEqual("2015-06-11T20:46:02Z"); 50 | 21 series.rows["bar"][1].shouldEqual("yellow"); 51 | 22 52 | 23 series.rows.array.shouldEqual( 53 | 24 [ 54 | 25 MeasurementSeries.Rows.Row(["time", "foo", "bar"], 55 | 26 ["2015-06-11T20:46:02Z", "red", "blue"], 56 | 27 ), 57 | 28 MeasurementSeries.Rows.Row(["time", "foo", "bar"], 58 | 29 ["2013-02-09T12:34:56Z", "green", "yellow"], 59 | 30 ), 60 | 31 ] 61 | 32 ); 62 |
1 auto series = MeasurementSeries("coolness", 63 | 2 ["time", "foo", "bar"], 64 | 3 [["2015-06-11T20:46:02Z", "red", "blue"]]); 65 | 4 series.rows[0].get("foo", "oops").shouldEqual("red"); 66 | 5 series.rows[0].get("quux", "oops").shouldEqual("oops"); 67 |
1 import std.conv: to; 68 | 2 auto series = MeasurementSeries("coolness", 69 | 3 ["time", "foo", "bar"], 70 | 4 [["2015-06-11T20:46:02Z", "red", "blue"]]); 71 | 5 series.rows[0].to!string.shouldEqual("Row(time: 2015-06-11T20:46:02Z, foo: red, bar: blue)"); 72 |
1 73 | 2 import std.datetime: SysTime, DateTime, UTC, usecs; 74 | 3 import std.array: array; 75 | 4 76 | 5 auto series = MeasurementSeries("coolness", 77 | 6 ["time", "foo", "bar"], 78 | 7 [ 79 | 8 ["2017-05-10T14:47:38.82524801Z", "red", "blue"], 80 | 9 ]); 81 | 10 82 | 11 series.rows[0].time.shouldEqual(SysTime(DateTime(2017, 05, 10, 14, 47, 38), 825248.usecs, UTC())); 83 |
This module implements integration tests for InfluxDB. As such, they record in 31 | code the assumptions made with regards to the HTTP API. Given that these tests 32 | pass, the unit tests are sufficient to guarantee correct behaviour.
These tests can be run with dub run -c integration and require a running 33 | instance of InfluxDB on localhost:8086. On systems with systemd, install 34 | InfluxDB (as appropriate for the Linux distribution) and start it with 35 | systemctl start influxdb.
If these tests fail, nothing else in this repository will work.
1 curlPostQuery("CREATE DATABASE testdb").shouldSucceed; 36 | 2 curlPostQuery("DROP DATABASE testdb").shouldSucceed; 37 |
1 curlPostQuery("FOO DATABASE testdb").shouldFail; 38 |
1 import std.string: join; 39 | 2 import std.json: parseJSON; 40 | 3 import std.algorithm: find; 41 | 4 42 | 5 // in case there's still data there, delete the DB 43 | 6 curlPostQuery("DROP DATABASE testdb").shouldSucceed; 44 | 7 curlPostQuery("CREATE DATABASE testdb").shouldSucceed; 45 | 8 scope(exit) curlPostQuery("DROP DATABASE testdb").shouldSucceed; 46 | 9 47 | 10 const lines = curlGet("SELECT * from foo").shouldSucceed; 48 | 11 const json = lines.join(" ").find("{").parseJSON; 49 | 12 json.toString.shouldEqual(`{"results":[{"statement_id":0}]}`); 50 |
1 import std.string: join; 51 | 2 import std.json: parseJSON; 52 | 3 import std.algorithm: find, map; 53 | 4 54 | 5 // in case there's still data there, delete the DB 55 | 6 curlPostQuery("DROP DATABASE testdb").shouldSucceed; 56 | 7 curlPostQuery("CREATE DATABASE testdb").shouldSucceed; 57 | 8 scope(exit) curlPostQuery("DROP DATABASE testdb").shouldSucceed; 58 | 9 59 | 10 curlPostWrite("foo,tag1=letag,tag2=othertag value=1,othervalue=3").shouldSucceed; 60 | 11 curlPostWrite("foo,tag1=toto,tag2=titi value=2,othervalue=4 1434055562000000000").shouldSucceed; 61 | 12 62 | 13 /* 63 | 14 Example of a response (prettified): 64 | 15 { 65 | 16 "results": [{ 66 | 17 "series": [{ 67 | 18 "columns": ["time", "othervalue", "tag1", "tag2", "value"], 68 | 19 "name": "foo", 69 | 20 "values": [ 70 | 21 ["2015-06-11T20:46:02Z", 4, "toto", "titi", 2], 71 | 22 ["2017-03-14T23:15:01.06282785Z", 3, "letag", "othertag", 1] 72 | 23 ] 73 | 24 }], 74 | 25 "statement_id": 0 75 | 26 }] 76 | 27 } 77 | 28 */ 78 | 29 79 | 30 { 80 | 31 const lines = curlGet("SELECT * from foo").shouldSucceed; 81 | 32 const json = lines.join(" ").find("{").parseJSON; 82 | 33 const result = json.object["results"].array[0].object; 83 | 34 const table = result["series"].array[0].object; 84 | 35 table["columns"].array.map!(a => a.str).shouldBeSameSetAs( 85 | 36 ["time", "othervalue", "tag1", "tag2", "value"]); 86 | 37 table["name"].str.shouldEqual("foo"); 87 | 38 table["values"].array.length.shouldEqual(2); 88 | 39 } 89 | 40 90 | 41 { 91 | 42 const lines = curlGet("SELECT value from foo WHERE value > 1").shouldSucceed; 92 | 43 const json = lines.join(" ").find("{").parseJSON; 93 | 44 const result = json.object["results"].array[0].object; 94 | 45 const table = result["series"].array[0].object; 95 | 46 table["values"].array.length.shouldEqual(1); 96 | 47 } 97 | 48 98 | 49 { 99 | 50 const lines = curlGet("SELECT othervalue from foo WHERE othervalue > 42").shouldSucceed; 100 | 51 const json = lines.join(" ").find("{").parseJSON; 101 | 52 const result = json.object["results"].array[0]; 102 | 53 // no result in this case, no data with othervalue > 42 103 | 54 json.object["results"].array[0].toString.shouldEqual(`{"statement_id":0}`); 104 | 55 } 105 |