site/third-party-projects.html - spark-website - Git at Google

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       <p>This page tracks external software projects that supplement Apache Spark and add to its ecosystem.</p>

 <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>

 <p>Note that all project and product names should follow <a href="/trademarks.html">trademark guidelines</a>.</p>

 <h2>spark-packages.org</h2>

 <p><a href="https://spark-packages.org/">spark-packages.org</a> is an external,
 community-managed list of third-party libraries, add-ons, and applications that work with
 Apache Spark. You can add a package as long as you have a GitHub repository.</p>

 <h2>Infrastructure projects</h2>

 <ul>
   <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="http://mlbase.org/">MLbase</a> - Machine Learning research project on top of Spark</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/EclairJS/eclairjs-node">EclairJS</a> - enables Node.js developers to code
 against Spark, and data scientists to use Javascript in Jupyter notebooks.</li>
   <li><a href="https://github.com/Hydrospheredata/mist">Mist</a> - Serverless proxy for Spark cluster (spark middleware)</li>
   <li><a href="https://github.com/GoogleCloudPlatform/spark-on-k8s-operator">K8S Operator for Apache Spark</a> - Kubernetes operator for specifying and 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://delta.io">Delta Lake</a> - Storage layer that provides ACID transactions and scalable metadata handling for Apache Spark workloads.</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://github.com/databricks/koalas">Koalas</a> - Data frame API on Apache Spark that more closely follows Python&#8217;s pandas.</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://wiki.apache.org/mrql/">Apache MRQL</a> - A query processing and optimization
 system for large-scale, distributed data analysis, built on top of Apache Hadoop, Hama, and Spark</li>
   <li><a href="https://github.com/sameeragarwal/blinkdb">BlinkDB</a> - a massively parallel, approximate query engine built
 on top of Shark and Spark</li>
   <li><a href="https://github.com/adobe-research/spindle">Spindle</a> - Spark/Parquet-based web
 analytics query engine</li>
   <li><a href="https://github.com/thunderain-project/thunderain">Thunderain</a> - a framework
 for combining stream processing with historical data, think Lambda architecture</li>
   <li><a href="https://github.com/OryxProject/oryx">Oryx</a> -  Lambda architecture on Apache Spark,
 Apache Kafka for real-time large scale machine learning</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://github.com/g1thubhub/phil_stopwatch">Performance and debugging library</a> - A library to analyze Spark and PySpark applications for improving performance and finding the cause of failures</li>
   <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>
 </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/TheClimateCorporation/clj-spark">clj-spark</a></li>
   <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>Groovy</h3>

 <ul>
   <li><a href="https://github.com/bunions1/groovy-spark-example">groovy-spark-example</a></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>

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             <span class="small">(May 13, 2022)</span></li>

           <li><a href="/news/3-1-3-released.html">Spark 3.1.3 released</a>
             <span class="small">(Feb 18, 2022)</span></li>

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	<p>This page tracks external software projects that supplement Apache Spark and add to its ecosystem.</p>

	<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>

	<p>Note that all project and product names should follow <a href="/trademarks.html">trademark guidelines</a>.</p>

	<h2>spark-packages.org</h2>

	<p><a href="https://spark-packages.org/">spark-packages.org</a> is an external,
	community-managed list of third-party libraries, add-ons, and applications that work with
	Apache Spark. You can add a package as long as you have a GitHub repository.</p>

	<h2>Infrastructure projects</h2>

	<ul>
	<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="http://mlbase.org/">MLbase</a> - Machine Learning research project on top of Spark</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/EclairJS/eclairjs-node">EclairJS</a> - enables Node.js developers to code
	against Spark, and data scientists to use Javascript in Jupyter notebooks.</li>
	<li><a href="https://github.com/Hydrospheredata/mist">Mist</a> - Serverless proxy for Spark cluster (spark middleware)</li>
	<li><a href="https://github.com/GoogleCloudPlatform/spark-on-k8s-operator">K8S Operator for Apache Spark</a> - Kubernetes operator for specifying and 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://delta.io">Delta Lake</a> - Storage layer that provides ACID transactions and scalable metadata handling for Apache Spark workloads.</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://github.com/databricks/koalas">Koalas</a> - Data frame API on Apache Spark that more closely follows Python’s pandas.</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://wiki.apache.org/mrql/">Apache MRQL</a> - A query processing and optimization
	system for large-scale, distributed data analysis, built on top of Apache Hadoop, Hama, and Spark</li>
	<li><a href="https://github.com/sameeragarwal/blinkdb">BlinkDB</a> - a massively parallel, approximate query engine built
	on top of Shark and Spark</li>
	<li><a href="https://github.com/adobe-research/spindle">Spindle</a> - Spark/Parquet-based web
	analytics query engine</li>
	<li><a href="https://github.com/thunderain-project/thunderain">Thunderain</a> - a framework
	for combining stream processing with historical data, think Lambda architecture</li>
	<li><a href="https://github.com/OryxProject/oryx">Oryx</a> - Lambda architecture on Apache Spark,
	Apache Kafka for real-time large scale machine learning</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://github.com/g1thubhub/phil_stopwatch">Performance and debugging library</a> - A library to analyze Spark and PySpark applications for improving performance and finding the cause of failures</li>
	<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>
	</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/TheClimateCorporation/clj-spark">clj-spark</a></li>
	<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>Groovy</h3>

	<ul>
	<li><a href="https://github.com/bunions1/groovy-spark-example">groovy-spark-example</a></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>

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