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apache / calcite / af5444ffdfd9e836b052ee58abec9430d55d4139
commitaf5444ffdfd9e836b052ee58abec9430d55d4139[log] [tgz]
authorJulian Hyde <jhyde@apache.org>Mon May 24 18:35:53 2021 -0700
committerJulian Hyde <jhyde@apache.org>Fri May 28 11:20:21 2021 -0700
treecb053e7f28d0b7c80da91dd289e705fb481206ff
parent6a9832c14e7c7c02a0176920b87d15dab474300a [diff]
[CALCITE-4620] Join on CASE causes AssertionError in RelToSqlConverter

The fix is to remove the logic that generates ON conditions
and instead use the logic that is used for all other
expressions. This logic is more widely used, and therefore
already handles cases such as CASE. (Previous bugs such as
[CALCITE-3207] LIKE, [CALCITE-4610] Sarg, and
[CALCITE-1422] IS NULL have been caused by this unnecessary
split.)

We have retained the logic that reverses 't1.id = t0.id' to
't0.id = t1.id' if 't0' is from the left side of the join.

We have reverted one test case, which was accidentally
seeing 'mandatoryColumn IS NULL' simplified to 'FALSE',
because the simplification was not the point of the test.
3 files changed
tree: cb053e7f28d0b7c80da91dd289e705fb481206ff
  1. .github/
  2. .idea/
  3. babel/
  4. bom/
  5. buildSrc/
  6. cassandra/
  7. core/
  8. druid/
  9. elasticsearch/
  10. example/
  11. file/
  12. geode/
  13. gradle/
  14. innodb/
  15. kafka/
  16. linq4j/
  17. mongodb/
  18. pig/
  19. piglet/
  20. plus/
  21. redis/
  22. release/
  23. server/
  24. site/
  25. spark/
  26. splunk/
  27. src/
  28. ubenchmark/
  29. .asf.yaml
  30. .editorconfig
  31. .gitattributes
  32. .gitignore
  33. .ratignore
  34. .travis.yml
  35. appveyor.yml
  36. build.gradle.kts
  37. gradle.properties
  38. gradlew
  39. gradlew.bat
  40. LICENSE
  41. NOTICE
  42. README
  43. README.md
  44. settings.gradle.kts
  45. sqlline
  46. sqlline.bat
  47. sqlsh
  48. sqlsh.bat
README.md

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Apache Calcite

Apache Calcite is a dynamic data management framework.

It contains many of the pieces that comprise a typical database management system but omits the storage primitives. It provides an industry standard SQL parser and validator, a customisable optimizer with pluggable rules and cost functions, logical and physical algebraic operators, various transformation algorithms from SQL to algebra (and the opposite), and many adapters for executing SQL queries over Cassandra, Druid, Elasticsearch, MongoDB, Kafka, and others, with minimal configuration.

For more details, see the home page.