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apache / mnemonic / ff7ff72f8660ce80faf46aa37ffba1ac2dd9df7c
commitff7ff72f8660ce80faf46aa37ffba1ac2dd9df7c[log] [tgz]
authordependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>Tue Jan 24 18:13:19 2023 +0000
committerYanhui Zhao <wildyz.yky@gmail.com>Thu Feb 09 07:43:39 2023 -0800
treec0767d4d72758d8c541d75b264eaf2c2e1bb74cd
parent0f9a74b79d188797e13c1f8f66410f6b6577f2a6 [diff]
Bump testng from 6.8.17 to 7.7.0

Bumps [testng](https://github.com/cbeust/testng) from 6.8.17 to 7.7.0.
- [Release notes](https://github.com/cbeust/testng/releases)
- [Changelog](https://github.com/cbeust/testng/blob/master/CHANGES.txt)
- [Commits](https://github.com/cbeust/testng/compare/testng-6.8.17...7.7.0)

---
updated-dependencies:
- dependency-name: org.testng:testng
  dependency-type: direct:development
...

Signed-off-by: dependabot[bot] <support@github.com>
1 file changed
tree: c0767d4d72758d8c541d75b264eaf2c2e1bb74cd
  1. .devcontainer/
  2. .github/
  3. .vscode/
  4. docker/
  5. gradle/
  6. mnemonic-benches/
  7. mnemonic-collections/
  8. mnemonic-common/
  9. mnemonic-computing-services/
  10. mnemonic-core/
  11. mnemonic-examples/
  12. mnemonic-hadoop/
  13. mnemonic-memory-services/
  14. mnemonic-sessions/
  15. mnemonic-spark/
  16. tools/
  17. .asf.yaml
  18. .gitattributes
  19. .gitignore
  20. build.gradle
  21. gradlew
  22. gradlew.bat
  23. KEYS
  24. LICENSE
  25. NOTICE
  26. pom.xml
  27. README.md
  28. settings.gradle
README.md

================================

Mnemonic Official Website

CI

Apache Mnemonic is a non-volatile hybrid memory storage oriented library, it proposed a non-volatile/durable Java object model and durable computing service that bring several advantages to significantly improve the performance of massive real-time data processing/analytics. developers are able to use this library to design their cache-less and SerDe-less high performance applications.

Features:

  • In-place data storage on local non-volatile memory
  • Durable Object Model (DOM)
  • Durable Native Computing Model (DNCM)
  • Object graphs lazy loading & sharing
  • Auto-reclaim memory resources and Mnemonic objects
  • Hierarchical cache pool for massive data caching
  • Extensible memory services for new device adoption and allocation optimization
  • Durable data structure collection(WIP)
  • Durable computing service
  • Minimize memory footprint of on-heap
  • Reduce GC Overheads as the following chart shown (collected from Apache Spark experiments)
  • Drop-in Hadoop MapReduce support
  • Drop-in Hadoop Spark support