spark-instrumented-optimizer/sql
Marek Novotny 74a8d6308b [SPARK-24165][SQL] Fixing conditional expressions to handle nullability of nested types
## What changes were proposed in this pull request?
This PR is proposing a fix for the output data type of ```If``` and ```CaseWhen``` expression. Upon till now, the implementation of exprassions has ignored nullability of nested types from different execution branches and returned the type of the first branch.

This could lead to an unwanted ```NullPointerException``` from other expressions depending on a ```If```/```CaseWhen``` expression.

Example:
```
val rows = new util.ArrayList[Row]()
rows.add(Row(true, ("a", 1)))
rows.add(Row(false, (null, 2)))
val schema = StructType(Seq(
  StructField("cond", BooleanType, false),
  StructField("s", StructType(Seq(
    StructField("val1", StringType, true),
    StructField("val2", IntegerType, false)
  )), false)
))

val df = spark.createDataFrame(rows, schema)

df
  .select(when('cond, struct(lit("x").as("val1"), lit(10).as("val2"))).otherwise('s) as "res")
  .select('res.getField("val1"))
  .show()
```
Exception:
```
Exception in thread "main" java.lang.NullPointerException
	at org.apache.spark.sql.catalyst.expressions.codegen.UnsafeWriter.write(UnsafeWriter.java:109)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
	at org.apache.spark.sql.execution.LocalTableScanExec$$anonfun$unsafeRows$1.apply(LocalTableScanExec.scala:44)
	at org.apache.spark.sql.execution.LocalTableScanExec$$anonfun$unsafeRows$1.apply(LocalTableScanExec.scala:44)
...
```
Output schema:
```
root
 |-- res.val1: string (nullable = false)
```

## How was this patch tested?
New test cases added into
- DataFrameSuite.scala
- conditionalExpressions.scala

Author: Marek Novotny <mn.mikke@gmail.com>

Closes #21687 from mn-mikke/SPARK-24165.
2018-07-11 12:21:03 +08:00
..
catalyst [SPARK-24165][SQL] Fixing conditional expressions to handle nullability of nested types 2018-07-11 12:21:03 +08:00
core [SPARK-24165][SQL] Fixing conditional expressions to handle nullability of nested types 2018-07-11 12:21:03 +08:00
hive Revert "[SPARK-24268][SQL] Use datatype.simpleString in error messages" 2018-07-09 14:24:23 -07:00
hive-thriftserver [SPARK-24553][WEB-UI] http 302 fixes for href redirect 2018-06-27 15:36:59 -07:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 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.