├── CODE_OF_CONDUCT.md ├── CONTRIBUTING.md ├── LICENSE └── README.md /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | ## Code of Conduct 2 | This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct). 3 | For more information see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact 4 | opensource-codeofconduct@amazon.com with any additional questions or comments. 5 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # Contributing Guidelines 2 | 3 | Thank you for your interest in contributing to our project. Whether it's a bug report, new feature, correction, or additional 4 | documentation, we greatly value feedback and contributions from our community. 5 | 6 | Please read through this document before submitting any issues or pull requests to ensure we have all the necessary 7 | information to effectively respond to your bug report or contribution. 8 | 9 | 10 | ## Reporting Bugs/Feature Requests 11 | 12 | We welcome you to use the GitHub issue tracker to report bugs or suggest features. 13 | 14 | When filing an issue, please check existing open, or recently closed, issues to make sure somebody else hasn't already 15 | reported the issue. Please try to include as much information as you can. Details like these are incredibly useful: 16 | 17 | * A reproducible test case or series of steps 18 | * The version of our code being used 19 | * Any modifications you've made relevant to the bug 20 | * Anything unusual about your environment or deployment 21 | 22 | 23 | ## Contributing via Pull Requests 24 | Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that: 25 | 26 | 1. You are working against the latest source on the *main* branch. 27 | 2. You check existing open, and recently merged, pull requests to make sure someone else hasn't addressed the problem already. 28 | 3. You open an issue to discuss any significant work - we would hate for your time to be wasted. 29 | 30 | To send us a pull request, please: 31 | 32 | 1. Fork the repository. 33 | 2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change. 34 | 3. Ensure local tests pass. 35 | 4. Commit to your fork using clear commit messages. 36 | 5. Send us a pull request, answering any default questions in the pull request interface. 37 | 6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation. 38 | 39 | GitHub provides additional document on [forking a repository](https://help.github.com/articles/fork-a-repo/) and 40 | [creating a pull request](https://help.github.com/articles/creating-a-pull-request/). 41 | 42 | 43 | ## Finding contributions to work on 44 | Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any 'help wanted' issues is a great place to start. 45 | 46 | 47 | ## Code of Conduct 48 | This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct). 49 | For more information see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact 50 | opensource-codeofconduct@amazon.com with any additional questions or comments. 51 | 52 | 53 | ## Security issue notifications 54 | If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our [vulnerability reporting page](http://aws.amazon.com/security/vulnerability-reporting/). Please do **not** create a public github issue. 55 | 56 | 57 | ## Licensing 58 | 59 | See the [LICENSE](LICENSE) file for our project's licensing. 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For 404 | the avoidance of doubt, this paragraph does not form part of the 405 | public licenses. 406 | 407 | Creative Commons may be contacted at creativecommons.org. 408 | 409 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Redset 2 | Redset is a dataset containing three months worth of user query metadata that 3 | ran on a selected sample of instances in the Amazon Redshift fleet. We provide 4 | query metadata for 200 provisioned and serverless instances each. 5 | 6 | As stated in the [paper](https://assets.amazon.science/24/3b/04b31ef64c83acf98fe3fdca9107/why-tpc-is-not-enough-an-analysis-of-the-amazon-redshift-fleet.pdf), Redset is not intended to be representative of Redshift as a whole. Instead, Redset provides biased sample data to support the development of new benchmarks for these specific workloads. For fleet analysis and sampling methodology please take a look at the paper. 7 | 8 | ## Security 9 | See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information. 10 | 11 | ## License 12 | Redset © 2024 by Amazon is licensed under Creative Commons 13 | Attribution-NonCommercial 4.0 International. 14 | 15 | ## FAQ 16 | **Does the Paper study Redset?** No. The paper studies metadata generated by the entire Amazon Redshift fleet. Redset is a non-representative biased random sample of this metadata. The dataset is released as a standalone contribution from the paper with the express purpose of aiding the development or augmentation of future benchmarks, as well as enabling exploration of ML based techniques, e.g., for workload forecasting. 17 | 18 | **Is Redset a representative sample?** No. As stated in section 6 in [the paper](https://www.amazon.science/publications/why-tpc-is-not-enough-an-analysis-of-the-amazon-redshift-fleet), the Redset workloads is a biased sample based on a “busy-ness“ score (see the paper for the exact definition). This ensures a diverse set of example workloads that can be studied individually. However, aggregating over the workloads in the dataset will not yield a representative view of the overall Amazon Redshift fleet. 19 | 20 | **Does each Redset cluster equal one Customer?** No. A customer/organization often has several clusters of various sizes and purposes. Redset does not disclose whom a cluster belongs to. It is therefore impossible to draw conclusions about the number of customers in Redset and, for the same reason, impossible to make statements like “X% of customers do/have Y”. 21 | 22 | **Can I use scanned bytes to approximate table sizes?** No. There a various factors in the execution engine and Amazon Redshift’s overall design that simply make it impossible to derive or even approximate table sizes from scanned bytes. To give two examples: 1) Redshift uses a columnar storage and thus accesses only data that is actually queried 2) Redshift implements block skipping (and other execution techniques) to tremendously limit the amount of data it needs to process. 23 | 24 | 25 | ## Download 26 | Folder structure: 27 | * s3://redshift-downloads/redset 28 | * README 29 | * LICENSE 30 | * provisioned/ 31 | * full.parquet 32 | * sample_0.01.parquet (1% uniform random data sample) 33 | * sample_0.001.parquet (0.1% uniform random data sample) 34 | * parts/ 35 | * One individual `.parquet` file per cluster 36 | * serverless/ 37 | * full.parquet 38 | * sample_0.01.parquet (1% uniform random sample) 39 | * sample_0.001.parquet (0.1% uniform random data sample) 40 | * parts/ 41 | * One individual `.parquet` file per cluster 42 | 43 | You can either download files using their http link, e.g., 44 | https://s3.amazonaws.com/redshift-downloads/redset/LICENSE 45 | Or interact with the s3 bucket using the [AWS CLI](https://aws.amazon.com/cli/). 46 | For example, to download the full serverless dataset you can run: 47 | ``` 48 | aws s3 cp --no-sign-request s3://redshift-downloads/redset/serverless/full.parquet . 49 | ``` 50 | 51 | ## Schema 52 | | Column | Name Description | 53 | | ------ | ---------------- | 54 | | instance_id | Uniquely identifies a redshift cluster | 55 | | cluster_size | Size of the cluster (only available for provisioned) | 56 | | user_id | Identifies the user that issued the query | 57 | | database_id | Identifies the database that was queried | 58 | | query_id | Unique per instance | 59 | | arrival_timestamp | Timestamp when the query arrived on the system | 60 | | compile_duration_ms | Time the query spent compiling in milliseconds | 61 | | queue_duration_ms | Time the query spent queueing in milliseconds | 62 | | execution_duration_ms | Time the query spent executing in milliseconds | 63 | | feature_fingerprint | Hash value of the query fingerprint. A proxy for query-likeness, though not based on text. Will overestimate repetition. | 64 | | was_aborted | Whether the query was aborted during its lifetime | 65 | | was_cached | Whether the query was answered from result cache | 66 | | cache_source_query_id | If query was answered from result cache, this is the query id for the query which populated the cache | 67 | | query_type | Type of query, e.g.., `select`, `copy`, ... | 68 | | num_permanent_tables_accessed | Number of permanent table accesses by the query (regular database table) | 69 | | num_external_tables_accessed | Number of [external tables](https://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_EXTERNAL_TABLE.html) accessed by the query | 70 | | num_system_tables_accessed | Number of [system tables](https://docs.aws.amazon.com/redshift/latest/dg/cm_chap_system-tables.html) accessed by the query | 71 | | read_table_ids | Comma separated list of unique permanent table ids read by the query | 72 | | write_table_ids | Comma separated list of unique table ids written to by the query | 73 | | mbytes_scanned | Total number of megabytes scanned by the query | 74 | | mbytes_spilled | Total number of megabytes spilled by the query | 75 | | num_joins | Number of joins in the query plan | 76 | | num_scans | Number of scans in the query plan | 77 | | num_aggregations | Number of aggregations in the query plan | 78 | 79 | ## Citation 80 | You may find the paper [here](https://assets.amazon.science/24/3b/04b31ef64c83acf98fe3fdca9107/why-tpc-is-not-enough-an-analysis-of-the-amazon-redshift-fleet.pdf). 81 | ``` 82 | @Inproceedings{Renen2024, 83 | author = {Alexander van Renen and Dominik Horn and Pascal Pfeil and Kapil Eknath Vaidya and Wenjian Dong and Murali Narayanaswamy and Zhengchun Liu and Gaurav Saxena and Andreas Kipf and Tim Kraska}, 84 | title = {Why TPC is not enough: An analysis of the Amazon Redshift fleet}, 85 | year = {2024}, 86 | url = {https://www.amazon.science/publications/why-tpc-is-not-enough-an-analysis-of-the-amazon-redshift-fleet}, 87 | booktitle = {VLDB 2024}, 88 | } 89 | ``` 90 | --------------------------------------------------------------------------------