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Takeshi Yamamuro 47d84e4d0e [SPARK-22814][SQL] Support Date/Timestamp in a JDBC partition column 
## What changes were proposed in this pull request?
This pr supported Date/Timestamp in a JDBC partition column (a numeric column is only supported in the master). This pr also modified code to verify a partition column type;
```
val jdbcTable = spark.read
 .option("partitionColumn", "text")
 .option("lowerBound", "aaa")
 .option("upperBound", "zzz")
 .option("numPartitions", 2)
 .jdbc("jdbc:postgresql:postgres", "t", options)

// with this pr
org.apache.spark.sql.AnalysisException: Partition column type should be numeric, date, or timestamp, but string found.;
  at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.verifyAndGetNormalizedPartitionColumn(JDBCRelation.scala:165)
  at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.columnPartition(JDBCRelation.scala:85)
  at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:36)
  at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:317)

// without this pr
java.lang.NumberFormatException: For input string: "aaa"
  at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
  at java.lang.Long.parseLong(Long.java:589)
  at java.lang.Long.parseLong(Long.java:631)
  at scala.collection.immutable.StringLike$class.toLong(StringLike.scala:277)
```

Closes #19999

## How was this patch tested?
Added tests in `JDBCSuite`.

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #21834 from maropu/SPARK-22814.
2018-07-30 07:42:00 -07:00
..
catalyst [SPARK-22814][SQL] Support Date/Timestamp in a JDBC partition column 2018-07-30 07:42:00 -07:00
core [SPARK-22814][SQL] Support Date/Timestamp in a JDBC partition column 2018-07-30 07:42:00 -07:00
hive [SPARK-24957][SQL] Average with decimal followed by aggregation returns wrong result 2018-07-30 20:53:45 +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

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.