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apache / tez / master
commit1fc00352ccae70d265649621aca22a5904ba771f[log] [tgz]
authorRaghav Aggarwal <raghavaggarwal03.ra@gmail.com>Mon Jan 26 15:06:15 2026 +0530
committerGitHub <noreply@github.com>Mon Jan 26 10:36:15 2026 +0100
tree30cedc7eb20f74ba745a84b2ad9dd66b0246b4c0
parentffd346b93ae325ace48e6c5c6697d5ca5a686dcf [diff]
TEZ-4654: Migrate from commons-lang2.x to commons-lang3.x (#441) (Raghav Aggarwal reviewed by Laszlo Bodor)

- Upgrade to commons-lang-3.19.0
- org.apache.commons.lang.ArrayUtils => org.apache.commons.lang3.ArrayUtils
- org.apache.commons.lang.RandomStringUtils => org.apache.commons.lang3.RandomStringUtils
- org.apache.commons.lang.StringEscapeUtils => org.apache.commons.lang3.StringEscapeUtils
- org.apache.commons.lang.StringUtils => org.apache.commons.lang3.StringUtils
- org.apache.commons.lang.SystemUtils => org.apache.commons.lang3.SystemUtils
- org.apache.commons.lang.exception.ExceptionUtils => org.apache.commons.lang3.exception.ExceptionUtils
- org.apache.commons.lang.mutable.MutableInt => org.apache.commons.lang3.mutable.MutableInt
- org.apache.commons.lang.NotImplementedException => org.apache.commons.lang3.NotImplementedException
47 files changed
tree: 30cedc7eb20f74ba745a84b2ad9dd66b0246b4c0
  1. .github/
  2. build-tools/
  3. dev-support/
  4. docs/
  5. hadoop-shim/
  6. hadoop-shim-impls/
  7. tez-api/
  8. tez-build-tools/
  9. tez-common/
  10. tez-dag/
  11. tez-dist/
  12. tez-examples/
  13. tez-ext-service-tests/
  14. tez-mapreduce/
  15. tez-plugins/
  16. tez-runtime-internals/
  17. tez-runtime-library/
  18. tez-tests/
  19. tez-tools/
  20. tez-ui/
  21. INSTALL.md ⇨ docs/src/site/markdown/install.md
  22. .asf.yaml
  23. .gitignore
  24. BUILDING.txt
  25. Jenkinsfile
  26. LICENSE
  27. NOTICE
  28. pom.xml
  29. README.md
  30. Tez_DOAP.rdf
README.md

Apache Tez

Apache Tez is a generic data-processing pipeline engine envisioned as a low-level engine for higher abstractions such as Apache Hadoop Map-Reduce, Apache Pig, Apache Hive etc.

At its heart, tez is very simple and has just two components:

  • The data-processing pipeline engine where-in one can plug-in input, processing and output implementations to perform arbitrary data-processing. Every ‘task’ in tez has the following:
  • Input to consume key/value pairs from.
  • Processor to process them.
  • Output to collect the processed key/value pairs.
  • A master for the data-processing application, where-by one can put together arbitrary data-processing ‘tasks’ described above into a task-DAG to process data as desired. The generic master is implemented as a Apache Hadoop YARN ApplicationMaster.