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Jungtaek Lim (HeartSaVioR) f24a46011c [SPARK-30993][SQL] Use its sql type for UDT when checking the type of length (fixed/var) or mutable 
### What changes were proposed in this pull request?

This patch fixes the bug of UnsafeRow which misses to handle the UDT specifically, in `isFixedLength` and `isMutable`. These methods don't check its SQL type for UDT, always treating UDT as variable-length, and non-mutable.

It doesn't bring any issue if UDT is used to represent complicated type, but when UDT is used to represent some type which is matched with fixed length of SQL type, it exposes the chance of correctness issues, as these informations sometimes decide how the value should be handled.

We got report from user mailing list which suspected as mapGroupsWithState looks like handling UDT incorrectly, but after some investigation it was from GenerateUnsafeRowJoiner in shuffle phase.

0e2ca11d80/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateUnsafeRowJoiner.scala (L32-L43)

Here updating position should not happen on fixed-length column, but due to this bug, the value of UDT having fixed-length as sql type would be modified, which actually corrupts the value.

### Why are the changes needed?

Misclassifying of the type of length for UDT can corrupt the value when the row is presented to the input of GenerateUnsafeRowJoiner, which brings correctness issue.

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

No.

### How was this patch tested?

New UT added.

Closes #27747 from HeartSaVioR/SPARK-30993.

Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-03-02 22:33:11 +08:00
..
catalyst [SPARK-30993][SQL] Use its sql type for UDT when checking the type of length (fixed/var) or mutable 2020-03-02 22:33:11 +08:00
core [SPARK-30993][SQL] Use its sql type for UDT when checking the type of length (fixed/var) or mutable 2020-03-02 22:33:11 +08:00
hive [SPARK-30972][SQL] PruneHiveTablePartitions should be executed as earlyScanPushDownRules 2020-02-28 11:50:20 +08:00
hive-thriftserver [SPARK-30950][BUILD] Setting version to 3.1.0-SNAPSHOT 2020-02-25 19:44:31 -08:00
create-docs.sh [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-api-docs.py [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-config-docs.py [SPARK-30840][CORE][SQL] Add version property for ConfigEntry and ConfigBuilder 2020-02-22 09:46:42 +09:00
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.