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apache / tez / refs/heads/dependabot/npm_and_yarn/tez-ui/src/main/webapp/express-4.19.2
commit0464ef0518086460d24978ffa5ab032c10ba17dd[log] [tgz]
authordependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>Mon Mar 25 21:05:44 2024 +0000
committerGitHub <noreply@github.com>Mon Mar 25 21:05:44 2024 +0000
treee60471b5d69dd1d800878ec981515929a4f478b9
parent34bb628e3a25edf5e36e3ca1bf73f06752a43118 [diff]
Bump express from 4.15.2 to 4.19.2 in /tez-ui/src/main/webapp

Bumps [express](https://github.com/expressjs/express) from 4.15.2 to 4.19.2.
- [Release notes](https://github.com/expressjs/express/releases)
- [Changelog](https://github.com/expressjs/express/blob/master/History.md)
- [Commits](https://github.com/expressjs/express/compare/4.15.2...4.19.2)

---
updated-dependencies:
- dependency-name: express
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
1 file changed
tree: e60471b5d69dd1d800878ec981515929a4f478b9
  1. .github/
  2. build-tools/
  3. docs/
  4. hadoop-shim/
  5. hadoop-shim-impls/
  6. tez-api/
  7. tez-build-tools/
  8. tez-common/
  9. tez-dag/
  10. tez-dist/
  11. tez-examples/
  12. tez-ext-service-tests/
  13. tez-mapreduce/
  14. tez-plugins/
  15. tez-runtime-internals/
  16. tez-runtime-library/
  17. tez-tests/
  18. tez-tools/
  19. tez-ui/
  20. INSTALL.md ⇨ docs/src/site/markdown/install.md
  21. .asf.yaml
  22. .gitignore
  23. BUILDING.txt
  24. Jenkinsfile
  25. LICENSE
  26. NOTICE
  27. pom.xml
  28. README.md
  29. 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.