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If you're wondering what Big Data things are in Fedora, or are interested in working on packaging or reviews to help out the Big Data SIG, this is the page to look at!

If you know of a big-data-related package that is already in Fedora, or have one that you'd like to get into Fedora, be sure to list it here, or link to the page describing what needs to be done, or link to the bugzilla that needs help.


Packages available in Fedora

Package Description Packaged
Sources Who Notes
Apache Hadoop Batch processing system and core of the Hadoop ecosystem 2.4.1 2.7.1 hadoop.git Hadoop packaging
Apache HBase The Apache Hadoop NoSQL Database 0.98.3 hbase.git HBase packaging
Apache Hive SQL-on-Hadoop query framework, a data warehouse for Hadoop 0.12.2 1.2.1 hive.git
Apache Pig Language for expression data analysis programs run on MapReduce 0.13.10 0.15.0 pig.git Pig packaging
Apache Zookeeper A service for highly reliable distributed coordination 3.4.6 3.4.6 zookeeper.git
Apache Oozie Workflow scheduler system to manage Apache Hadoop jobs 4.0.1 4.2.0 oozie.git rsquared Oozie packaging
Apache Ambari Hadoop cluster manager 1.5.1 2.1.0 ambari.git
Apache Accumulo A software platform for processing vast amounts of data 1.6.1 1.7.0 accumulo.git
Apache Mesos Cluster manager for sharing distributed application frameworks 0.22.1 0.23.9 mesos.git Mesos packaging
Apache Solr Ultra-fast Lucene-based Search Server 5.3.1 5.3.1 solr.git
Apache Spark Lightning-fast cluster computing 0.9.1 1.4.1 spark.git Spark packaging
Scala packaging
AMPLab Tachyon A memory resident, fault tolerant distributed file system 0.99 0.7.0 tachyon.git Tachyon packaging

Packages we're working on

Package Description Packaged
Sources Who Notes
Apache Flume Data ingestion tool for large amounts of log data 1.6.0 1.6.0 flume-rpm.git gil Flume packaging RHBZ#1279201
Cloudera Kite SDK Kite SDK to simplify the development of data-related systems 1.0.0 1.1.0 kite.spec
Apache Crunch Java library provides a framework for MapReduce pipelines. 0.11.0 0.12.0 crunch-rpm.git gil
Apache Tez Generalizes the MapReduce paradigm to a more powerful framework 0.5.3 0.7.0 tez-rpm.git gil
Apache Kafka Publish-subscribe messaging broker for large scale 0.8.0 kafka-rpm.git jromanes Kafka packaging
Apache Storm Distributed real-time computation system 0.9.3 0.9.5 storm-rpm.git jromanes Storm packaging
Apache Tajo Low-latency and scalable SQL-on-Hadoop framework 0.10.0 0.10.1 tajo.spec gil
Apache Jena Java framework for building Semantic Web and Linked Data applications 3.0.0 3.0.0 jena.spec donpellegrino
Cascading Data processing workflows on a Hadoop using any JVM-based language 2.6.3 2.7.1 cascading.spec gil
Apache Sqoop2 Bulk data transfer between Hadoop and structured datastores 1.99.3 1.99.6 sqoop.spec pmackinn RHBZ #1089675
Neo4j Java Graph Database 2.2.3 2.2.6 neo4j.spec gil
Apache Cassandra A highly scalable key-value store N.A. 3.0.0-beta2 (some) Apache Cassandra dependencies gil

Packages we'd like to include

Becoming a packager

Not yet a packager? Check out the Package Maintainers, or the Join the package collection maintainers page to get more information. You could also ask on the Big Data SIG mailing list for assistance and see if you can find a willing helper or sponsor. For bundling Java packages read the Java packaging guidelines first.

Typical workflow (relies on github)

  • Clone original repo, if modifications are required.
  • Patch where necessary. (Use github tickets where possible if working as a group).
    • Try to organize your patch set into meaningful units, and create tickets to push upstream where possible.
    • For patches that require carrying, they should be applied to the raw-sources where possible.
  • Create a package-rpm repo with specs and system integration files (systemd, custom-conf, etc).
  • Use rpmbuild | hack fedpkg to enable prototype package building
    • spectool -g package.spec (will download sources)
    • md5sum package-sources.tar.gz > sources
    • fedpkg local
  • Once you feel you have a package ready for review run the following prior to submit:
    • Setup Fedora Review
    • rpmlint package.spec
    • mock --clean --init -r fedora-rawhide-x86_64 && fedora-review -m fedora-rawhide-x86_64 -n package.srpm

Packaging Notes

  • Fedora java rpms can not bundle dependent jars. Every jar file not created by the build must come from an rpm in the Fedora repository.
  • All jars must be built from source
  • Fedora build tools: xmvn-resolve, mvn-local, mvn-rpmbuild, mvn-build no longer available in rawhide, considered private implementation
  • Fedora rpm macros: %pom_*, %mvn_build, %mvn_install, %mvn_file
  • xmvn-subst for dependency jars when packaging
  • Fedora Java Packaging guidelines: JNI handling: System.load replaces System.loadLibrary, jar file in %{_jnidir} Jar files in %{_javadir}
  • Fedora build systems have no internet access, avoid DNS if possible.
  • Breaking apart or subsuming subelements
    • Depending on the popularity of a sub-element as a stand-alone package it sometimes makes more sense to break it out as a sub-package which can stand alone, but doesn't have to live in a separate repository. This is a choice which will have to be made by the upstream group and will depend heavily on their ideal workflow, but from a maintenance perspective it's far easier to maintain as a sub-package. E.g. one project produces multiple libs/jars.
  • Fedora is OpenJDK7 or higher. You cannot mix-and-match usage of the Fedora versions of maven and ant with Java 6, since they are themselves compiled with source="1.7".