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</style><table class="infobox vevent"><tbody><tr><th colspan="2" class="infobox-above summary">Apache SystemDS</th></tr><tr><td colspan="2" class="infobox-image logo"><span typeof="mw:File"></span></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Programmer" title="Programmer">Developer(s)</a></th><td class="infobox-data"><a href="Apache_Software_Foundation" class="mw-redirect" title="Apache Software Foundation">Apache Software Foundation</a>, <a href="IBM" title="IBM">IBM</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Initial release</th><td class="infobox-data">November 2, 2015<span style="display:none"> (<span class="bday dtstart published updated">2015-11-02</span>)</span></td></tr><tr style="display: none;"><td colspan="2" class="infobox-full-data"></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_release_life_cycle" title="Software release life cycle">Stable release</a></th><td class="infobox-data"><div style="margin:0px;">3.0.0

/ July 5, 2022<span style="display:none"> (<span class="bday dtstart published updated">2022-07-05</span>)</span></div></td></tr><tr style="display:none"><td colspan="2">

</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Repository_(version_control)" title="Repository (version control)">Repository</a></th><td class="infobox-data"><span class="url"><a rel="nofollow" class="external text" href="https://github.com/apache/systemds">SystemDS Repository</a></span></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Written in</th><td class="infobox-data"><a href="Java_(programming_language)" title="Java (programming language)">Java</a>, <a href="Python_(programming_language)" title="Python (programming language)">Python</a>, DML, <a href="C_(programming_language)" title="C (programming language)">C</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Operating_system" title="Operating system">Operating system</a></th><td class="infobox-data"><a href="Linux" title="Linux">Linux</a>, <a href="MacOS" title="MacOS">macOS</a>, <a href="Windows" class="mw-redirect" title="Windows">Windows</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_categories#Categorization_approaches" title="Software categories">Type</a></th><td class="infobox-data"><a href="Machine_Learning" class="mw-redirect" title="Machine Learning">Machine Learning</a>, <a href="Deep_Learning" class="mw-redirect" title="Deep Learning">Deep Learning</a>, <a href="Data_Science" class="mw-redirect" title="Data Science">Data Science</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_license" title="Software license">License</a></th><td class="infobox-data"><a href="Apache_License_2.0" class="mw-redirect" title="Apache License 2.0">Apache License 2.0</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Website</th><td class="infobox-data"><span class="url"><a rel="nofollow" class="external text" href="https://systemds.apache.org/">systemds<wbr>.apache<wbr>.org</a></span></td></tr></tbody></table>

<p><b>Apache SystemDS</b> (Previously, Apache SystemML) is an open source ML system for the end-to-end data science lifecycle.

</p><p>SystemDS's distinguishing characteristics are:

</p>

<ol><li>Algorithm customizability via R-like and Python-like languages.</li>

<li>Multiple execution modes, including Standalone, <a href="Apache_Spark" title="Apache Spark">Spark</a> Batch, <a href="Apache_Spark" title="Apache Spark">Spark</a> MLContext, <a href="Apache_Hadoop" title="Apache Hadoop">Hadoop</a> Batch, and JMLC.</li>

<li>Automatic optimization based on data and cluster characteristics to ensure both efficiency and scalability.</li></ol>

<div class="mw-heading mw-heading2"><h2 id="History">History</h2></div>

<p>SystemML was created in 2010 by researchers at the <a href="IBM_Almaden_Research_Center" class="mw-redirect" title="IBM Almaden Research Center">IBM Almaden Research Center</a> led by IBM Fellow Shivakumar Vaithyanathan. It was observed that data scientists would write machine learning algorithms in languages such as <a href="R_(programming_language)" title="R (programming language)">R</a> and <a href="Python_(programming_language)" title="Python (programming language)">Python</a> for small data. When it came time to scale to big data, a systems programmer would be needed to scale the algorithm in a language such as <a href="Scala_(programming_language)" title="Scala (programming language)">Scala</a>. This process typically involved days or weeks per iteration, and errors would occur translating the algorithms to operate on big data. SystemML seeks to simplify this process. A primary goal of SystemML is to automatically scale an algorithm written in an R-like or Python-like language to operate on big data, generating the same answer without the error-prone, multi-iterative translation approach.

</p><p>On June 15, 2015, at the Spark Summit in San Francisco, Beth Smith, General Manager of IBM Analytics, announced that IBM was open-sourcing SystemML as part of IBM's major commitment to <a href="Apache_Spark" title="Apache Spark">Apache Spark</a> and Spark-related projects. SystemML became publicly available on <a href="GitHub" title="GitHub">GitHub</a> on August 27, 2015 and became an Apache Incubator project on November 2, 2015. On May 17, 2017, the Apache Software Foundation Board approved the graduation of Apache SystemML as an Apache Top Level Project.

</p>

<div class="mw-heading mw-heading2"><h2 id="Key_technologies">Key technologies</h2></div>

<p>The following are some of the technologies built into the SystemDS engine.

</p>

<ul><li><a rel="nofollow" class="external text" href="https://cacm.acm.org/magazines/2019/5/236413-compressed-linear-algebra-for-declarative-large-scale-machine-learning/fulltext">Compressed Linear Algebra for Large Scale Machine Learning</a></li>

<li><a rel="nofollow" class="external text" href="https://arxiv.org/pdf/1605.05826">Declarative Machine Learning Language</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="Examples">Examples</h2></div>

<div class="mw-heading mw-heading3"><h3 id="Principal_Component_Analysis">Principal Component Analysis</h3></div><p>

The following code snippet<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> does the <a href="Principal_component_analysis" title="Principal component analysis">Principal component analysis</a> of input matrix <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle A}">

</mstyle>

</mrow>

<annotation encoding="application/x-tex">{\displaystyle A}</annotation>

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</math></span><img src="./7daff47fa58cdfd29dc333def748ff5fa4c923e3.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.743ex; height:2.176ex;" alt="{\displaystyle A}" loading="lazy"></span> , which returns the <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle eigenvectors}">

</mstyle>

</mrow>

<annotation encoding="application/x-tex">{\displaystyle eigenvectors}</annotation>

</semantics>

</math></span><img src="./cdc82a6e89c2e65cce15c46a55f50d9a2415af10.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:12.804ex; height:2.509ex;" alt="{\displaystyle eigenvectors}" loading="lazy"></span> and the <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\textstyle eigenvalues}">

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</mrow>

<annotation encoding="application/x-tex">{\textstyle eigenvalues}</annotation>

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</math></span><img src="./34b8e3fe894e2d80cf6f264cc36166cf64c52317.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:12.034ex; height:2.509ex;" alt="{\textstyle eigenvalues}" loading="lazy"></span>.</p><div class="mw-highlight mw-highlight-lang-r mw-content-ltr mw-highlight-lines" dir="ltr"><pre><span class="c1"># PCA.dml</span>

<span class="c1"># Refer: https://github.com/apache/systemds/blob/master/scripts/algorithms/PCA.dml#L61</span>

<span class="c1"># perform z-scoring (centering and scaling)</span>

<span class="n">A</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">scale</span><span class="p">(</span><span class="n">A</span><span class="p">,</span><span class="w"> </span><span class="n">center</span><span class="o">==</span><span class="m">1</span><span class="p">,</span><span class="w"> </span><span class="n">scale</span><span class="o">==</span><span class="m">1</span><span class="p">);</span>

<span class="c1"># co-variance matrix </span>

<span class="n">mu</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">colSums</span><span class="p">(</span><span class="n">A</span><span class="p">)</span><span class="o">/</span><span class="n">N</span><span class="p">;</span>

<span class="c1"># compute eigen vectors and values</span>

<span class="p">[</span><span class="n">evalues</span><span class="p">,</span><span class="w"> </span><span class="n">evectors</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">eigen</span><span class="p">(</span><span class="n">C</span><span class="p">);</span>

</pre></div>

<div class="mw-heading mw-heading3"><h3 id="Invocation_script">Invocation script</h3></div>

<div class="mw-highlight mw-highlight-lang-shell-session mw-content-ltr" dir="ltr"><pre><span class="go">spark-submit SystemDS.jar -f PCA.dml -nvargs INPUT=INPUT_DIR/pca-1000x1000 \</span>

<span class="go"> OUTPUT=OUTPUT_DIR/pca-1000x1000-model PROJDATA=1 CENTER=1 SCALE=1</span>

</pre></div>

<div class="mw-heading mw-heading3"><h3 id="Database_functions">Database functions</h3></div>

<p><a href="DBSCAN" title="DBSCAN">DBSCAN</a> clustering algorithm with <a href="Euclidean_distance" title="Euclidean distance">Euclidean distance</a>.</p><div class="mw-highlight mw-highlight-lang-r mw-content-ltr mw-highlight-lines" dir="ltr"><pre><span class="n">X</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">rand</span><span class="p">(</span><span class="n">rows</span><span class="o">=</span><span class="m">1780</span><span class="p">,</span><span class="w"> </span><span class="n">cols</span><span class="o">=</span><span class="m">180</span><span class="p">,</span><span class="w"> </span><span class="n">min</span><span class="o">=</span><span class="m">1</span><span class="p">,</span><span class="w"> </span><span class="n">max</span><span class="o">=</span><span class="m">20</span><span class="p">)</span><span class="w"> </span>

<span class="p">[</span><span class="n">indices</span><span class="p">,</span><span class="w"> </span><span class="n">model</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">dbscan</span><span class="p">(</span><span class="n">X</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">X</span><span class="p">,</span><span class="w"> </span><span class="n">eps</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="m">2.5</span><span class="p">,</span><span class="w"> </span><span class="n">minPts</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="m">360</span><span class="p">)</span>

</pre></div>

<div class="mw-heading mw-heading2"><h2 id="Improvements">Improvements</h2></div>

<p>SystemDS 2.0.0 is the first major release under the new name. This release contains a major refactoring, a few major features, a large number of improvements and fixes, and some experimental features to better support the end-to-end data science lifecycle. In addition to that, this release also removes several features that are not up date and outdated.

</p>

<ul><li>New mechanism for DML-bodied (script-level) <code>builtin</code> functions, and a wealth of new built-in functions for data preprocessing including data cleaning, augmentation and feature engineering techniques, new ML algorithms, and model debugging.</li>

<li>Several methods for data cleaning have been implemented including multiple imputations with multivariate imputation by chained equations (MICE) and other techniques, SMOTE, an oversampling technique for class imbalance, forward and backward NA filling, cleaning using schema and length information, support for outlier detection using standard deviation and inter-quartile range, and functional dependency discovery.</li>

<li>A complete framework for lineage tracing and reuse including support for loop deduplication, full and partial reuse, compiler assisted reuse, several new rewrites to facilitate reuse.</li>

<li>New federated runtime backend including support for federated matrices and frames, federated <code>builtin</code>s (<code>transform-encode</code>, <code>decode</code> etc.).</li>

<li>Refactor compression package and add functionalities including quantization for lossy compression, binary cell operations, left matrix multiplication. [experimental]</li>

<li>New python bindings with supports for several <code>builtin</code>s, matrix operations, federated tensors and lineage traces.</li>

<li>Cuda implementation of cumulative aggregate operators (<code>cumsum</code>, <code>cumprod</code> etc.)</li>

<li>New model debugging technique with slice finder.</li>

<li>New tensor data model (basic tensors of different value types, data tensors with schema) [experimental]</li>

<li>Cloud deployment scripts for AWS and scripts to set up and start federated operations.</li>

<li>Performance improvements with <code>parallel sort</code>, <code>gpu cum agg</code>, <code>append cbind</code> etc.</li>

<li>Various compiler and runtime improvements including new and improved rewrites, reduced Spark context creation, new <code>eval</code> framework, list operations, updated native kernel libraries to name a few.</li>

<li>New data reader/writer for <code>json</code> frames and support for <code>sql</code> as a data source.</li>

<li>Miscellaneous improvements: improved documentation, better testing, run/release scripts, improved packaging, Docker container for systemds, support for lambda expressions, bug fixes.</li>

<li>Removed MapReduce compiler and runtime backend, <code>pydml</code> parser, Java-UDF framework, script-level debugger.</li>

<li>Deprecated <code>./scripts/algorithms</code>, as those algorithms gradually will be part of SystemDS <code>builtin</code>s.</li></ul>

</p>

<div class="mw-heading mw-heading2"><h2 id="Contributions">Contributions</h2></div>

<p>Apache SystemDS welcomes contributions in code, question and answer, community building, or spreading the word. The contributor guide is available at <a rel="nofollow" class="external free" href="https://github.com/apache/systemds/blob/main/CONTRIBUTING.md">https://github.com/apache/systemds/blob/main/CONTRIBUTING.md</a>

</p>

<ul><li><a href="Comparison_of_deep_learning_software" title="Comparison of deep learning software">Comparison of deep learning software</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

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</style><cite class="citation cs2"><a rel="nofollow" class="external text" href="https://github.com/apache/systemds"><i>Apache SystemDS</i></a>, The Apache Software Foundation, 2022-02-24<span class="reference-accessdate">, retrieved <span class="nowrap">2022-03-06</span></span></cite></span>

</li>

<li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text"><cite id="CITEREFSystemDS" class="citation web cs1">SystemDS, Apache. <a rel="nofollow" class="external text" href="https://systemds.apache.org/">"SystemML 1.2.0 Release Notes"</a>. <i>systemds.apache.org</i><span class="reference-accessdate">. Retrieved <span class="nowrap">2021-02-26</span></span>.</cite></span>

</li>

</ol></div></div>

<div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2></div>

<ul><li><a rel="nofollow" class="external text" href="https://systemds.apache.org/">Apache SystemML website</a></li>

<li><a rel="nofollow" class="external text" href="http://researcher.watson.ibm.com/researcher/view_group.php?id=3174">IBM Research - SystemML</a></li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20180321002223/http://www.spark.tc/q-a-with-shiv-vaithyanathan-creator-of-systemml-and-ibm-fellow/">Q & A with Shiv Vaithyanathan, Creator of SystemML and IBM Fellow</a></li>

<li><a rel="nofollow" class="external text" href="http://www.spark.tc/a-universal-translator-for-big-data-and-machine-learning/">A Universal Translator for Big Data and Machine Learning</a></li>

<li><a rel="nofollow" class="external text" href="https://www.youtube.com/watch?v=WkYqjWL1xzk">SystemML: Declarative Machine Learning at Scale presentation by Fred Reiss</a></li>

<li><a rel="nofollow" class="external text" href="http://researcher.watson.ibm.com/researcher/files/us-ytian/systemML.pdf">SystemML: Declarative Machine Learning on MapReduce</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20160310150949/http://researcher.watson.ibm.com/researcher/files/us-ytian/systemML.pdf">Archived</a> 2016-03-10 at the <a href="Wayback_Machine" title="Wayback Machine">Wayback Machine</a></li>

<li><a rel="nofollow" class="external text" href="http://www.vldb.org/pvldb/vol7/p553-boehm.pdf">Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML</a></li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20150218102423/http://sites.computer.org/debull/A14sept/p52.pdf">SystemML's Optimizer: Plan Generation for Large-Scale Machine Learning Programs</a></li>

<li><a rel="nofollow" class="external text" href="https://www.zdnet.com/article/ibms-systemml-machine-learning-system-becomes-apache-incubator-project/">IBM's SystemML machine learning system becomes Apache Incubator project</a></li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20150617032644/http://www.theinquirer.net/inquirer/news/2413132/ibm-donates-machine-learning-tech-to-apache-spark-open-source-community">IBM donates machine learning tech to Apache Spark open source community</a></li>

<li><a rel="nofollow" class="external text" href="http://www.eweek.com/developer/ibms-systemml-moves-forward-as-apache-incubator-project.html">IBM's SystemML Moves Forward as Apache Incubator Project</a></li></ul>

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</style><div id="The_Apache_Software_Foundation253" style="font-size:114%;margin:0 4em"><a href="The_Apache_Software_Foundation" title="The Apache Software Foundation">The Apache Software Foundation</a></div></th></tr><tr><th scope="row" class="navbox-group" style="width:1%">Top-level<br>projects</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Apache_Accumulo" title="Apache Accumulo">Accumulo</a></li>

<li><a href="Apache_ActiveMQ" title="Apache ActiveMQ">ActiveMQ</a></li>

<li><a href="Apache_Airavata" title="Apache Airavata">Airavata</a></li>

<li><a href="Apache_Airflow" title="Apache Airflow">Airflow</a></li>

<li><a href="Apache_Allura" title="Apache Allura">Allura</a></li>

<li><a href="Apache_Ambari" class="mw-redirect" title="Apache Ambari">Ambari</a></li>

<li><a href="Apache_Aries" title="Apache Aries">Aries</a></li>

<li><a href="Apache_Arrow" title="Apache Arrow">Arrow</a></li>

<li><a href="Apache_HTTP_Server" title="Apache HTTP Server">Apache HTTP Server</a></li>

<li><a href="Apache_Bloodhound" class="mw-redirect" title="Apache Bloodhound">Bloodhound</a></li>

<li><a href="Apache_Brooklyn" title="Apache Brooklyn">Brooklyn</a></li>

<li><a href="Apache_Calcite" title="Apache Calcite">Calcite</a></li>

<li><a href="Apache_Camel" title="Apache Camel">Camel</a></li>

<li><a href="Apache_CarbonData" title="Apache CarbonData">CarbonData</a></li>

<li><a href="Apache_Cassandra" title="Apache Cassandra">Cassandra</a></li>

<li><a href="Apache_Cayenne" title="Apache Cayenne">Cayenne</a></li>

<li><a href="Apache_CloudStack" title="Apache CloudStack">CloudStack</a></li>

<li><a href="Apache_Cocoon" title="Apache Cocoon">Cocoon</a></li>

<li><a href="Apache_Cordova" title="Apache Cordova">Cordova</a></li>

<li><a href="Apache_CouchDB" title="Apache CouchDB">CouchDB</a></li>

<li><a href="Apache_cTAKES" title="Apache cTAKES">cTAKES</a></li>

<li><a href="Apache_Derby" title="Apache Derby">Derby</a></li>

<li><a href="Apache_Directory" title="Apache Directory">Directory</a></li>

<li><a href="Apache_Drill" title="Apache Drill">Drill</a></li>

<li><a href="Apache_Druid" title="Apache Druid">Druid</a></li>

<li><a href="Apache_Empire-db" title="Apache Empire-db">Empire-db</a></li>

<li><a href="Apache_Felix" title="Apache Felix">Felix</a></li>

<li><a href="Apache_Flink" title="Apache Flink">Flink</a></li>

<li><a href="Apache_Flume" class="mw-redirect" title="Apache Flume">Flume</a></li>

<li><a href="FreeMarker" title="FreeMarker">FreeMarker</a></li>

<li><a href="Apache_Geronimo" title="Apache Geronimo">Geronimo</a></li>

<li><a href="Apache_Groovy" title="Apache Groovy">Groovy</a></li>

<li><a href="Apache_Guacamole" title="Apache Guacamole">Guacamole</a></li>

<li><a href="Apache_Hadoop" title="Apache Hadoop">Hadoop</a></li>

<li><a href="Apache_HBase" title="Apache HBase">HBase</a></li>

<li><a href="Apache_Helix" title="Apache Helix">Helix</a></li>

<li><a href="Apache_Iceberg" title="Apache Iceberg">Iceberg</a></li>

<li><a href="Apache_Ignite" title="Apache Ignite">Ignite</a></li>

<li><a href="Apache_Impala" title="Apache Impala">Impala</a></li>

<li><a href="Apache_Jackrabbit" title="Apache Jackrabbit">Jackrabbit</a></li>

<li><a href="Apache_James" title="Apache James">James</a></li>

<li><a href="Apache_JMeter" title="Apache JMeter">JMeter</a></li>

<li><a href="Apache_Kafka" title="Apache Kafka">Kafka</a></li>

<li><a href="Apache_Kylin" title="Apache Kylin">Kylin</a></li>

<li><a href="Apache_Lucene" title="Apache Lucene">Lucene</a></li>

<li><a href="Apache_Mahout" title="Apache Mahout">Mahout</a></li>

<li><a href="Apache_Maven" title="Apache Maven">Maven</a></li>

<li><a href="Apache_MyFaces" title="Apache MyFaces">MyFaces</a></li>

<li><a href="Apache_Mynewt" title="Apache Mynewt">Mynewt</a></li>

<li><a href="NetBeans" title="NetBeans">NetBeans</a></li>

<li><a href="Apache_Nutch" title="Apache Nutch">Nutch</a></li>

<li><a href="NuttX" title="NuttX">NuttX</a></li>

<li><a href="Apache_OFBiz" title="Apache OFBiz">OFBiz</a></li>

<li><a href="Apache_Oozie" title="Apache Oozie">Oozie</a></li>

<li><a href="Apache_OpenEJB" title="Apache OpenEJB">OpenEJB</a></li>

<li><a href="Apache_OpenJPA" title="Apache OpenJPA">OpenJPA</a></li>

<li><a href="Apache_OpenNLP" title="Apache OpenNLP">OpenNLP</a></li>

<li><a href="Apache_OpenOffice" title="Apache OpenOffice">OрenOffice</a></li>

<li><a href="Apache_PDFBox" title="Apache PDFBox">PDFBox</a></li>

<li><a href="Apache_Parquet" title="Apache Parquet">Parquet</a></li>

<li><a href="Apache_Phoenix" title="Apache Phoenix">Phoenix</a></li>

<li><a href="Apache_Pinot" title="Apache Pinot">Pinot</a></li>

<li><a href="Apache_Pivot" title="Apache Pivot">Pivot</a></li>

<li><a href="Apache_Roller" title="Apache Roller">Roller</a></li>

<li><a href="Apache_RocketMQ" title="Apache RocketMQ">RocketMQ</a></li>

<li><a href="Apache_Samza" title="Apache Samza">Samza</a></li>

<li><a href="Apache_Shiro" title="Apache Shiro">Shiro</a></li>

<li><a href="Apache_SINGA" title="Apache SINGA">SINGA</a></li>

<li><a href="Apache_Sling" title="Apache Sling">Sling</a></li>

<li><a href="Apache_Spark" title="Apache Spark">Spark</a></li>

<li><a href="Apache_Storm" title="Apache Storm">Storm</a></li>

<li><a href="Apache_SpamAssassin" title="Apache SpamAssassin">SpamAssassin</a></li>

<li><a href="Apache_Struts" title="Apache Struts">Struts</a>

<li><a href="Apache_Subversion" title="Apache Subversion">Subversion</a></li>

<li><a href="Apache_Superset" title="Apache Superset">Superset</a></li>

<li><a href="Apache_Tapestry" title="Apache Tapestry">Tapestry</a></li>

<li><a href="Apache_Thrift" title="Apache Thrift">Thrift</a></li>

<li><a href="Apache_TinkerPop" class="mw-redirect" title="Apache TinkerPop">TinkerPop</a></li>

<li><a href="Apache_Tomcat" title="Apache Tomcat">Tomcat</a></li>

<li><a href="Apache_Trafodion" class="mw-redirect" title="Apache Trafodion">Trafodion</a></li>

<li><a href="Apache_Traffic_Server" title="Apache Traffic Server">Traffic Server</a></li>

<li><a href="Apache_Velocity" title="Apache Velocity">Velocity</a></li>

<li><a href="Apache_Wicket" title="Apache Wicket">Wicket</a></li>

<li><a href="Apache_Xalan" title="Apache Xalan">Xalan</a></li>

<li><a href="Apache_Xerces" title="Apache Xerces">Xerces</a></li>

<li><a href="Apache_XMLBeans" title="Apache XMLBeans">XMLBeans</a></li>

<li>Yetus</li>

<li><a href="Apache_ZooKeeper" title="Apache ZooKeeper">ZooKeeper</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="Apache_Commons" title="Apache Commons">Commons</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<li><a href="Commons_Daemon" title="Commons Daemon">Daemon</a></li>

<li><a href="Apache_Jelly" title="Apache Jelly">Jelly</a></li>

<li><a href="Apache_Commons_Logging" title="Apache Commons Logging">Logging</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Incubator</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Apache_Taverna" title="Apache Taverna">Taverna</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other projects</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Apache_Batik" title="Apache Batik">Batik</a></li>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Attic</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<li><a href="AxKit" title="AxKit">AxKit</a></li>

<li><a href="Apache_Beehive" title="Apache Beehive">Beehive</a></li>

<li><a href="Apache_iBATIS" title="Apache iBATIS">iBATIS</a></li>

<li><a href="Apache_Click" title="Apache Click">Click</a></li>

<li><a href="Apache_Continuum" title="Apache Continuum">Continuum</a></li>

<li><a href="Deltacloud" title="Deltacloud">Deltacloud</a></li>

<li><a href="Apache_Giraph" title="Apache Giraph">Giraph</a></li>

<li><a href="Apache_Harmony" title="Apache Harmony">Harmony</a></li>

<li><a href="Jakarta_Project" title="Jakarta Project">Jakarta</a></li>

<li><a href="Apache_Marmotta" title="Apache Marmotta">Marmotta</a></li>

<li><a href="Apache_MXNet" title="Apache MXNet">MXNet</a></li>

<li><a href="Jini" title="Jini">River</a></li>

<li><a href="Apache_Shale" title="Apache Shale">Shale</a></li>

<li><a href="Jakarta_Slide" class="mw-redirect" title="Jakarta Slide">Slide</a></li>

<li><a href="Sqoop" title="Sqoop">Sqoop</a></li>

<li><a href="Apache_Stanbol" title="Apache Stanbol">Stanbol</a></li>

<li><a href="Apache_Tuscany" class="mw-redirect" title="Apache Tuscany">Tuscany</a></li>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Licenses</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Apache_License" title="Apache License">Apache License</a></li></ul>

</div></td></tr><tr><td class="navbox-abovebelow" colspan="2"><div>

<ul><li><span class="noviewer" typeof="mw:File"><span title="Category"></span></span> <b>Category</b></li></ul>

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This article is issued from <a class="external text" title="Last edited on 2024-07-05" href="https://en.wikipedia.org/wiki/?title=Apache_SystemDS&oldid=1232781565">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.

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