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apache / calcite / 48126d3d3834e28e84ae3fc4c65b86831b5d6aef
commit48126d3d3834e28e84ae3fc4c65b86831b5d6aef[log] [tgz]
authorStamatis Zampetakis <zabetak@gmail.com>Thu Jul 29 14:16:20 2021 +0300
committerStamatis Zampetakis <zabetak@gmail.com>Tue Aug 10 12:47:35 2021 +0300
tree98debacef707f7470319e413b174759cdd0da928
parent8346167252bcb90cd64ced9e3a5c893de28f88ed [diff]
[CALCITE-4706] JDBC adapter generates casts exceeding Redshift's data types bounds

1. Add Redshift type system ensuring precision/scale bounds are
satisfied when casting.
2. Consider max precision for DECIMAL and CHAR data types in
SqlDialect#getCastSpec.
3. Consider max scale for DECIMAL data types in SqlDialect#getCastSpec.
4. Extend RelToSqlConverterTest.Sql with custom type system to allow
writting tests with non-default type system (e.g., simulate systems with
large numeric precision).
5. Set typesystem explicitly in SqlDialectFactoryImpl since it cannot
be derived from the metadata and the default is not appropriate.
6. Add unit tests casting to DECIMAL, CHAR, VARCHAR, with
precision/scale exceeding Redshift's bounds.

Close apache/calcite#2470
6 files changed
tree: 98debacef707f7470319e413b174759cdd0da928
  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.