5c4d8f9538
### What changes were proposed in this pull request? SPARK-23596 added `CodegenInterpretedPlanTest` at Apache Spark 2.4.0 in a wrong way because `withSQLConf` depends on the execution time `SQLConf.get` instead of `test` function declaration time. So, the following code executes the test twice without controlling the `CodegenObjectFactoryMode`. This PR aims to fix it correct and introduce a new function `testFallback`. ```scala trait CodegenInterpretedPlanTest extends PlanTest { override protected def test( testName: String, testTags: Tag*)(testFun: => Any)(implicit pos: source.Position): Unit = { val codegenMode = CodegenObjectFactoryMode.CODEGEN_ONLY.toString val interpretedMode = CodegenObjectFactoryMode.NO_CODEGEN.toString withSQLConf(SQLConf.CODEGEN_FACTORY_MODE.key -> codegenMode) { super.test(testName + " (codegen path)", testTags: _*)(testFun)(pos) } withSQLConf(SQLConf.CODEGEN_FACTORY_MODE.key -> interpretedMode) { super.test(testName + " (interpreted path)", testTags: _*)(testFun)(pos) } } } ``` ### Why are the changes needed? 1. We need to use like the following. ```scala super.test(testName + " (codegen path)", testTags: _*)( withSQLConf(SQLConf.CODEGEN_FACTORY_MODE.key -> codegenMode) { testFun })(pos) super.test(testName + " (interpreted path)", testTags: _*)( withSQLConf(SQLConf.CODEGEN_FACTORY_MODE.key -> interpretedMode) { testFun })(pos) ``` 2. After we fix this behavior with the above code, several test cases including SPARK-34596 and SPARK-34607 fail because they didn't work at both `CODEGEN` and `INTERPRETED` mode. Those test cases only work at `FALLBACK` mode. So, inevitably, we need to introduce `testFallback`. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Pass the CIs. Closes #31766 from dongjoon-hyun/SPARK-34596-SPARK-34607. Lead-authored-by: Dongjoon Hyun <dhyun@apple.com> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dhyun@apple.com> |
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.. | ||
catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-api-docs.py | ||
gen-sql-config-docs.py | ||
gen-sql-functions-docs.py | ||
mkdocs.yml | ||
README.md |
Spark SQL
This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.
Running ./sql/create-docs.sh
generates SQL documentation for built-in functions under sql/site
, and SQL configuration documentation that gets included as part of configuration.md
in the main docs
directory.