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| <p>This page tracks external software projects that supplement Apache Spark and add to its ecosystem.</p> |
| |
| <h2 id="popular-libraries-with-pyspark-integrations">Popular libraries with PySpark integrations</h2> |
| |
| <ul> |
| <li><a href="https://github.com/great-expectations/great_expectations">great-expectations</a> - Always know what to expect from your data</li> |
| <li><a href="https://github.com/apache/airflow">Apache Airflow</a> - A platform to programmatically author, schedule, and monitor workflows</li> |
| <li><a href="https://github.com/dmlc/xgboost">xgboost</a> - Scalable, portable and distributed gradient boosting</li> |
| <li><a href="https://github.com/shap/shap">shap</a> - A game theoretic approach to explain the output of any machine learning model</li> |
| <li><a href="https://github.com/awslabs/python-deequ">python-deequ</a> - Measures data quality in large datasets</li> |
| <li><a href="https://github.com/datahub-project/datahub">datahub</a> - Metadata platform for the modern data stack</li> |
| <li><a href="https://github.com/dbt-labs/dbt-spark">dbt-spark</a> - Enables dbt to work with Apache Spark</li> |
| <li><a href="https://github.com/DAGWorks-Inc/hamilton">Hamilton</a> - Enables one to declaratively describe PySpark transformations that helps keep code testable, modular, and logically visualizable.</li> |
| </ul> |
| |
| <h2 id="connectors">Connectors</h2> |
| |
| <ul> |
| <li><a href="https://github.com/spark-redshift-community/spark-redshift">spark-redshift</a> - Performant Redshift data source for Apache Spark</li> |
| <li><a href="https://github.com/microsoft/sql-spark-connector">spark-sql-connector</a> - Apache Spark Connector for SQL Server and Azure SQL</li> |
| <li><a href="https://github.com/Azure/azure-cosmosdb-spark">azure-cosmos-spark</a> - Apache Spark Connector for Azure Cosmos DB</li> |
| <li><a href="https://github.com/Azure/azure-event-hubs-spark">azure-event-hubs-spark</a> - Enables continuous data processing with Apache Spark and Azure Event Hubs</li> |
| <li><a href="https://github.com/Azure/azure-kusto-spark">azure-kusto-spark</a> - Apache Spark connector for Azure Kusto</li> |
| <li><a href="https://github.com/mongodb/mongo-spark">mongo-spark</a> - The MongoDB Spark connector</li> |
| <li><a href="https://github.com/couchbase/couchbase-spark-connector">couchbase-spark-connector</a> - The Official Couchbase Spark connector</li> |
| <li><a href="https://github.com/datastax/spark-cassandra-connector">spark-cassandra-connector</a> - DataStax connector for Apache Spark to Apache Cassandra</li> |
| <li><a href="https://github.com/elastic/elasticsearch-hadoop">elasticsearch-hadoop</a> - Elasticsearch real-time search and analytics natively integrated with Spark</li> |
| <li><a href="https://github.com/neo4j-contrib/neo4j-spark-connector">neo4j-spark-connector</a> - Neo4j Connector for Apache Spark</li> |
| <li><a href="https://github.com/StarRocks/starrocks-connector-for-apache-spark">starrocks-connector-for-apache-spark</a> - StarRocks Apache Spark connector</li> |
| <li><a href="https://github.com/pingcap/tispark">tispark</a> - TiSpark is built for running Apache Spark on top of TiDB/TiKV</li> |
| </ul> |
| |
| <h2 id="open-table-formats">Open table formats</h2> |
| |
| <ul> |
| <li><a href="https://delta.io">Delta Lake</a> - Storage layer that provides ACID transactions and scalable metadata handling for Apache Spark workloads</li> |
| <li><a href="https://github.com/apache/hudi">Hudi</a>: Upserts, Deletes And Incremental Processing on Big Data</li> |
| <li><a href="https://github.com/apache/iceberg">Iceberg</a> - Open table format for analytic datasets</li> |
| </ul> |
| |
| <h2>Infrastructure projects</h2> |
| |
| <ul> |
| <li><a href="https://github.com/apache/kyuubi">Kyuubi</a> - Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses</li> |
| <li><a href="https://github.com/spark-jobserver/spark-jobserver">REST Job Server for Apache Spark</a> - REST interface for managing and submitting Spark jobs on the same cluster.</li> |
| <li><a href="https://mesos.apache.org/">Apache Mesos</a> - Cluster management system that supports |
| running Spark</li> |
| <li><a href="https://www.alluxio.org/">Alluxio</a> (née Tachyon) - Memory speed virtual distributed |
| storage system that supports running Spark</li> |
| <li><a href="https://github.com/filodb/FiloDB">FiloDB</a> - a Spark integrated analytical/columnar |
| database, with in-memory option capable of sub-second concurrent queries</li> |
| <li><a href="http://zeppelin-project.org/">Zeppelin</a> - Multi-purpose notebook which supports 20+ language backends, including Apache Spark</li> |
| <li><a href="https://github.com/kubeflow/spark-operator">Kubeflow Spark Operator</a> - Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.</li> |
| <li><a href="https://developer.ibm.com/storage/products/ibm-spectrum-conductor-spark/">IBM Spectrum Conductor</a> - Cluster management software that integrates with Spark and modern computing frameworks.</li> |
| <li><a href="https://mlflow.org">MLflow</a> - Open source platform to manage the machine learning lifecycle, including deploying models from diverse machine learning libraries on Apache Spark.</li> |
| <li><a href="https://datafu.apache.org/docs/spark/getting-started.html">Apache DataFu</a> - A collection of utils and user-defined-functions for working with large scale data in Apache Spark, as well as making Scala-Python interoperability easier.</li> |
| </ul> |
| |
| <h2>Applications using Spark</h2> |
| |
| <ul> |
| <li><a href="https://mahout.apache.org/">Apache Mahout</a> - Previously on Hadoop MapReduce, |
| Mahout has switched to using Spark as the backend</li> |
| <li><a href="https://github.com/bigdatagenomics/adam">ADAM</a> - A framework and CLI for loading, |
| transforming, and analyzing genomic data using Apache Spark</li> |
| <li><a href="https://github.com/salesforce/TransmogrifAI">TransmogrifAI</a> - AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning</li> |
| <li><a href="https://github.com/JohnSnowLabs/spark-nlp">Natural Language Processing for Apache Spark</a> - A library to provide simple, performant, and accurate NLP annotations for machine learning pipelines</li> |
| <li><a href="http://rumbledb.org">Rumble for Apache Spark</a> - A JSONiq engine to query, with a functional language, large, nested, and heterogeneous JSON datasets that do not fit in dataframes.</li> |
| </ul> |
| |
| <h2>Performance, monitoring, and debugging tools for Spark</h2> |
| |
| <ul> |
| <li><a href="https://www.datamechanics.co/delight">Data Mechanics Delight</a> - Delight is a free, hosted, cross-platform Spark UI alternative backed by an open-source Spark agent. It features new metrics and visualizations to simplify Spark monitoring and performance tuning.</li> |
| <li><a href="https://github.com/dataflint/spark">DataFlint</a> - DataFlint is A Spark UI replacement installed via an open-source library, which updates in real-time and alerts on performance issues</li> |
| </ul> |
| |
| <h2>Additional language bindings</h2> |
| |
| <h3>C# / .NET</h3> |
| |
| <ul> |
| <li><a href="https://github.com/Microsoft/Mobius">Mobius</a>: C# and F# language binding and extensions to Apache Spark</li> |
| </ul> |
| |
| <h3>Clojure</h3> |
| |
| <ul> |
| <li><a href="https://github.com/zero-one-group/geni">Geni</a> - A Clojure dataframe library that runs on Apache Spark with a focus on optimizing the REPL experience.</li> |
| </ul> |
| |
| <h3>Julia</h3> |
| |
| <ul> |
| <li><a href="https://github.com/dfdx/Spark.jl">Spark.jl</a></li> |
| </ul> |
| |
| <h3>Kotlin</h3> |
| |
| <ul> |
| <li><a href="https://github.com/JetBrains/kotlin-spark-api">Kotlin for Apache Spark</a></li> |
| </ul> |
| |
| <h2 id="adding-new-projects">Adding new projects</h2> |
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| <p>To add a project, open a pull request against the <a href="https://github.com/apache/spark-website">spark-website</a> repository. Add an entry to <a href="https://github.com/apache/spark-website/blob/asf-site/third-party-projects.md">this markdown file</a>, then run <code class="language-plaintext highlighter-rouge">jekyll build</code> to generate the HTML too. Include both in your pull request. See the README in this repo for more information.</p> |
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| <h5>Latest News</h5> |
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| <li><a href="/news/spark-3-5-2-released.html">Spark 3.5.2 released</a> |
| <span class="small">(Aug 10, 2024)</span></li> |
| |
| <li><a href="/news/spark-4.0.0-preview1.html">Preview release of Spark 4.0</a> |
| <span class="small">(Jun 03, 2024)</span></li> |
| |
| <li><a href="/news/spark-3-4-3-released.html">Spark 3.4.3 released</a> |
| <span class="small">(Apr 18, 2024)</span></li> |
| |
| <li><a href="/news/spark-3-5-1-released.html">Spark 3.5.1 released</a> |
| <span class="small">(Feb 23, 2024)</span></li> |
| |
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| <p class="small" style="text-align: right;"><a href="/news/index.html">Archive</a></p> |
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