spark-instrumented-optimizer/sql
hyukjinkwon bfe60fcdb4 [SPARK-24934][SQL] Explicitly whitelist supported types in upper/lower bounds for in-memory partition pruning
## What changes were proposed in this pull request?

Looks we intentionally set `null` for upper/lower bounds for complex types and don't use it. However, these look used in in-memory partition pruning, which ends up with incorrect results.

This PR proposes to explicitly whitelist the supported types.

```scala
val df = Seq(Array("a", "b"), Array("c", "d")).toDF("arrayCol")
df.cache().filter("arrayCol > array('a', 'b')").show()
```

```scala
val df = sql("select cast('a' as binary) as a")
df.cache().filter("a == cast('a' as binary)").show()
```

**Before:**

```
+--------+
|arrayCol|
+--------+
+--------+
```

```
+---+
|  a|
+---+
+---+
```

**After:**

```
+--------+
|arrayCol|
+--------+
|  [c, d]|
+--------+
```

```
+----+
|   a|
+----+
|[61]|
+----+
```

## How was this patch tested?

Unit tests were added and manually tested.

Author: hyukjinkwon <gurwls223@apache.org>

Closes #21882 from HyukjinKwon/stats-filter.
2018-07-30 13:20:03 +08:00
..
catalyst [SPARK-21274][SQL] Implement INTERSECT ALL clause 2018-07-29 22:11:01 -07:00
core [SPARK-24934][SQL] Explicitly whitelist supported types in upper/lower bounds for in-memory partition pruning 2018-07-30 13:20:03 +08:00
hive [SPARK-24865] Remove AnalysisBarrier 2018-07-27 14:29:05 +08:00
hive-thriftserver [SPARK-24829][STS] In Spark Thrift Server, CAST AS FLOAT inconsistent with spark-shell or spark-sql 2018-07-27 13:27:17 +08:00
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.