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Erik Erlandson 1cb5bfc47a [SPARK-32159][SQL] Fix integration between Aggregator[Array[_], _, _] and UnresolvedMapObjects 
Context: The fix for SPARK-27296 introduced by #25024 allows `Aggregator` objects to appear in queries. This works fine for aggregators with atomic input types, e.g. `Aggregator[Double, _, _]`.

However it can cause a null pointer exception if the input type is `Array[_]`.  This was historically considered an ignorable case for serialization of `UnresolvedMapObjects`, but the new ScalaAggregator class causes these expressions to be serialized over to executors because the resolve-and-bind is being deferred.

### What changes were proposed in this pull request?
A new rule `ResolveEncodersInScalaAgg` that performs the resolution of the expressions contained in the encoders so that properly resolved expressions are serialized over to executors.

### Why are the changes needed?
Applying an aggregator of the form `Aggregator[Array[_], _, _]` using `functions.udaf()` currently causes a null pointer error in Catalyst.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
A unit test has been added that does aggregation with array types for input, buffer, and output. I have done additional testing with my own custom aggregators in the spark REPL.

Closes #28983 from erikerlandson/fix-spark-32159.

Authored-by: Erik Erlandson <eerlands@redhat.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-07-09 08:42:20 +00:00
..
catalyst [SPARK-32159][SQL] Fix integration between Aggregator[Array[_], _, _] and UnresolvedMapObjects 2020-07-09 08:42:20 +00:00
core [SPARK-32159][SQL] Fix integration between Aggregator[Array[_], _, _] and UnresolvedMapObjects 2020-07-09 08:42:20 +00:00
hive [SPARK-32159][SQL] Fix integration between Aggregator[Array[_], _, _] and UnresolvedMapObjects 2020-07-09 08:42:20 +00:00
hive-thriftserver [SPARK-32057][SQL][TEST-HIVE1.2][TEST-HADOOP2.7] ExecuteStatement: cancel and close should not transiently ERROR 2020-07-08 09:28:16 +09:00
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.