230f144197
## What changes were proposed in this pull request? ### Fixes `ClassCastException` in the `array_position` function - [SPARK-24350](https://issues.apache.org/jira/browse/SPARK-24350) When calling `array_position` function with a wrong type of the 1st argument an `AnalysisException` should be thrown instead of `ClassCastException` Example: ```sql select array_position('foo', 'bar') ``` ``` java.lang.ClassCastException: org.apache.spark.sql.types.StringType$ cannot be cast to org.apache.spark.sql.types.ArrayType at org.apache.spark.sql.catalyst.expressions.ArrayPosition.inputTypes(collectionOperations.scala:1398) at org.apache.spark.sql.catalyst.expressions.ExpectsInputTypes$class.checkInputDataTypes(ExpectsInputTypes.scala:44) at org.apache.spark.sql.catalyst.expressions.ArrayPosition.checkInputDataTypes(collectionOperations.scala:1401) at org.apache.spark.sql.catalyst.expressions.Expression.resolved$lzycompute(Expression.scala:168) at org.apache.spark.sql.catalyst.expressions.Expression.resolved(Expression.scala:168) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAliases$$anonfun$org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveAliases$$assignAliases$1$$anonfun$apply$3.applyOrElse(Analyzer.scala:256) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAliases$$anonfun$org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveAliases$$assignAliases$1$$anonfun$apply$3.applyOrElse(Analyzer.scala:252) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288) ``` ## How was this patch tested? unit test Author: Vayda, Oleksandr: IT (PRG) <Oleksandr.Vayda@barclayscapital.com> Closes #21401 from wajda/SPARK-24350-array_position-error-fix. |
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catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-markdown.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 an extension of SQLContext called HiveContext that allows 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
.