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Takuya UESHIN 3dda58af2b [SPARK-26370][SQL] Fix resolution of higher-order function for the same identifier. 
## What changes were proposed in this pull request?

When using a higher-order function with the same variable name as the existing columns in `Filter` or something which uses `Analyzer.resolveExpressionBottomUp` during the resolution, e.g.,:

```scala
val df = Seq(
  (Seq(1, 9, 8, 7), 1, 2),
  (Seq(5, 9, 7), 2, 2),
  (Seq.empty, 3, 2),
  (null, 4, 2)
).toDF("i", "x", "d")

checkAnswer(df.filter("exists(i, x -> x % d == 0)"),
  Seq(Row(Seq(1, 9, 8, 7), 1, 2)))
checkAnswer(df.select("x").filter("exists(i, x -> x % d == 0)"),
  Seq(Row(1)))
```

the following exception happens:

```
java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.BoundReference cannot be cast to org.apache.spark.sql.catalyst.expressions.NamedExpression
  at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:237)
  at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
  at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
  at scala.collection.TraversableLike.map(TraversableLike.scala:237)
  at scala.collection.TraversableLike.map$(TraversableLike.scala:230)
  at scala.collection.AbstractTraversable.map(Traversable.scala:108)
  at org.apache.spark.sql.catalyst.expressions.HigherOrderFunction.$anonfun$functionsForEval$1(higherOrderFunctions.scala:147)
  at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:237)
  at scala.collection.immutable.List.foreach(List.scala:392)
  at scala.collection.TraversableLike.map(TraversableLike.scala:237)
  at scala.collection.TraversableLike.map$(TraversableLike.scala:230)
  at scala.collection.immutable.List.map(List.scala:298)
  at org.apache.spark.sql.catalyst.expressions.HigherOrderFunction.functionsForEval(higherOrderFunctions.scala:145)
  at org.apache.spark.sql.catalyst.expressions.HigherOrderFunction.functionsForEval$(higherOrderFunctions.scala:145)
  at org.apache.spark.sql.catalyst.expressions.ArrayExists.functionsForEval$lzycompute(higherOrderFunctions.scala:369)
  at org.apache.spark.sql.catalyst.expressions.ArrayExists.functionsForEval(higherOrderFunctions.scala:369)
  at org.apache.spark.sql.catalyst.expressions.SimpleHigherOrderFunction.functionForEval(higherOrderFunctions.scala:176)
  at org.apache.spark.sql.catalyst.expressions.SimpleHigherOrderFunction.functionForEval$(higherOrderFunctions.scala:176)
  at org.apache.spark.sql.catalyst.expressions.ArrayExists.functionForEval(higherOrderFunctions.scala:369)
  at org.apache.spark.sql.catalyst.expressions.ArrayExists.nullSafeEval(higherOrderFunctions.scala:387)
  at org.apache.spark.sql.catalyst.expressions.SimpleHigherOrderFunction.eval(higherOrderFunctions.scala:190)
  at org.apache.spark.sql.catalyst.expressions.SimpleHigherOrderFunction.eval$(higherOrderFunctions.scala:185)
  at org.apache.spark.sql.catalyst.expressions.ArrayExists.eval(higherOrderFunctions.scala:369)
  at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificPredicate.eval(Unknown Source)
  at org.apache.spark.sql.execution.FilterExec.$anonfun$doExecute$3(basicPhysicalOperators.scala:216)
  at org.apache.spark.sql.execution.FilterExec.$anonfun$doExecute$3$adapted(basicPhysicalOperators.scala:215)

...
```

because the `UnresolvedAttribute`s in `LambdaFunction` are unexpectedly resolved by the rule.

This pr modified to use a placeholder `UnresolvedNamedLambdaVariable` to prevent unexpected resolution.

## How was this patch tested?

Added a test and modified some tests.

Closes #23320 from ueshin/issues/SPARK-26370/hof_resolution.

Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2018-12-15 00:23:28 +08:00
..
catalyst [SPARK-26370][SQL] Fix resolution of higher-order function for the same identifier. 2018-12-15 00:23:28 +08:00
core [SPARK-26370][SQL] Fix resolution of higher-order function for the same identifier. 2018-12-15 00:23:28 +08:00
hive [SPARK-26319][SQL][TEST] Add appendReadColumns Unit Test for HiveShimSuite 2018-12-10 22:26:28 +08:00
hive-thriftserver [SPARK-26090][CORE][SQL][ML] Resolve most miscellaneous deprecation and build warnings for Spark 3 2018-11-19 09:16:42 -06:00
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

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.