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yi.wu d8b001fa87 [SPARK-31620][SQL] Fix reference binding failure in case of an final agg contains subquery 
### What changes were proposed in this pull request?

Instead of using `child.output` directly, we should use `inputAggBufferAttributes` from the current agg expression  for `Final` and `PartialMerge` aggregates to bind references for their `mergeExpression`.

### Why are the changes needed?

When planning aggregates, the partial aggregate uses agg fucs' `inputAggBufferAttributes` as its output, see https://github.com/apache/spark/blob/v3.0.0-rc1/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala#L105

For final `HashAggregateExec`, we need to bind the `DeclarativeAggregate.mergeExpressions` with the output of the partial aggregate operator, see https://github.com/apache/spark/blob/v3.0.0-rc1/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala#L348

This is usually fine. However, if we copy the agg func somehow after agg planning, like `PlanSubqueries`, the `DeclarativeAggregate` will be replaced by a new instance with new `inputAggBufferAttributes` and `mergeExpressions`. Then we can't bind the `mergeExpressions` with the output of the partial aggregate operator, as it uses the `inputAggBufferAttributes` of the original `DeclarativeAggregate` before copy.

Note that, `ImperativeAggregate` doesn't have this problem, as we don't need to bind its `mergeExpressions`. It has a different mechanism to access buffer values, via `mutableAggBufferOffset` and `inputAggBufferOffset`.

### Does this PR introduce _any_ user-facing change?

Yes, user hit error previously but run query successfully after this change.

### How was this patch tested?

Added a regression test.

Closes #28496 from Ngone51/spark-31620.

Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-05-15 15:36:28 +00:00
..
catalyst [SPARK-31712][SQL][TESTS] Check casting timestamps before the epoch to Byte/Short/Int/Long types 2020-05-15 04:24:58 +00:00
core [SPARK-31620][SQL] Fix reference binding failure in case of an final agg contains subquery 2020-05-15 15:36:28 +00:00
hive [SPARK-31716][SQL] Use fallback versions in HiveExternalCatalogVersionsSuite 2020-05-15 00:30:25 -07:00
hive-thriftserver [SPARK-31715][SQL][TEST] Fix flaky SparkSQLEnvSuite that sometimes varies single derby instance standard 2020-05-15 06:36:34 +00:00
create-docs.sh [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-api-docs.py [SPARK-31474][SQL][FOLLOWUP] Replace _FUNC_ placeholder with functionname in the note field of expression info 2020-04-23 13:33:04 +09:00
gen-sql-config-docs.py [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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.