spark-instrumented-optimizer/sql
hyukjinkwon 4b2011ec9d [SPARK-17989][SQL] Check ascendingOrder type in sort_array function rather than throwing ClassCastException
## What changes were proposed in this pull request?

This PR proposes to check the second argument, `ascendingOrder`  rather than throwing `ClassCastException` exception message.

```sql
select sort_array(array('b', 'd'), '1');
```

**Before**

```
16/10/19 13:16:08 ERROR SparkSQLDriver: Failed in [select sort_array(array('b', 'd'), '1')]
java.lang.ClassCastException: org.apache.spark.unsafe.types.UTF8String cannot be cast to java.lang.Boolean
	at scala.runtime.BoxesRunTime.unboxToBoolean(BoxesRunTime.java:85)
	at org.apache.spark.sql.catalyst.expressions.SortArray.nullSafeEval(collectionOperations.scala:185)
	at org.apache.spark.sql.catalyst.expressions.BinaryExpression.eval(Expression.scala:416)
	at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1$$anonfun$applyOrElse$1.applyOrElse(expressions.scala:50)
	at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1$$anonfun$applyOrElse$1.applyOrElse(expressions.scala:43)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:292)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:292)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:74)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:291)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:297)
```

**After**

```
Error in query: cannot resolve 'sort_array(array('b', 'd'), '1')' due to data type mismatch: Sort order in second argument requires a boolean literal.; line 1 pos 7;
```

## How was this patch tested?

Unit test in `DataFrameFunctionsSuite`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15532 from HyukjinKwon/SPARK-17989.
2016-10-19 19:36:21 -07:00
..
catalyst [SPARK-17989][SQL] Check ascendingOrder type in sort_array function rather than throwing ClassCastException 2016-10-19 19:36:21 -07:00
core [SPARK-17989][SQL] Check ascendingOrder type in sort_array function rather than throwing ClassCastException 2016-10-19 19:36:21 -07:00
hive [SPARK-17980][SQL] Fix refreshByPath for converted Hive tables 2016-10-19 10:20:12 +08:00
hive-thriftserver [SPARK-17819][SQL] Support default database in connection URIs for Spark Thrift Server 2016-10-16 20:15:32 -07:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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 allows 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.