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author | Cheng Lian <lian@databricks.com> | 2016-04-27 13:55:07 -0700 |
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committer | Yin Huai <yhuai@databricks.com> | 2016-04-27 13:55:13 -0700 |
commit | 24bea000476cdd0b43be5160a76bc5b170ef0b42 (patch) | |
tree | 5336028911f2db913d333bbfbf17b54e1b843f5c /sql/core/src | |
parent | f405de87c878c49b17acb2c874be1084465384e9 (diff) | |
download | spark-24bea000476cdd0b43be5160a76bc5b170ef0b42.tar.gz spark-24bea000476cdd0b43be5160a76bc5b170ef0b42.tar.bz2 spark-24bea000476cdd0b43be5160a76bc5b170ef0b42.zip |
[SPARK-14954] [SQL] Add PARTITION BY and BUCKET BY clause for data source CTAS syntax
Currently, we can only create persisted partitioned and/or bucketed data source tables using the Dataset API but not using SQL DDL. This PR implements the following syntax to add partitioning and bucketing support to the SQL DDL:
```
CREATE TABLE <table-name>
USING <provider> [OPTIONS (<key1> <value1>, <key2> <value2>, ...)]
[PARTITIONED BY (col1, col2, ...)]
[CLUSTERED BY (col1, col2, ...) [SORTED BY (col1, col2, ...)] INTO <n> BUCKETS]
AS SELECT ...
```
Test cases are added in `MetastoreDataSourcesSuite` to check the newly added syntax.
Author: Cheng Lian <lian@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes #12734 from liancheng/spark-14954.
Diffstat (limited to 'sql/core/src')
-rw-r--r-- | sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlParser.scala | 12 |
1 files changed, 10 insertions, 2 deletions
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlParser.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlParser.scala index 79fdf9fb22..e4c837a7ab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlParser.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlParser.scala @@ -289,6 +289,7 @@ class SparkSqlAstBuilder(conf: SQLConf) extends AstBuilder { } val options = Option(ctx.tablePropertyList).map(visitTablePropertyList).getOrElse(Map.empty) val provider = ctx.tableProvider.qualifiedName.getText + val bucketSpec = Option(ctx.bucketSpec()).map(visitBucketSpec) if (ctx.query != null) { // Get the backing query. @@ -302,9 +303,16 @@ class SparkSqlAstBuilder(conf: SQLConf) extends AstBuilder { } else { SaveMode.ErrorIfExists } - CreateTableUsingAsSelect(table, provider, temp, Array.empty, None, mode, options, query) + + val partitionColumnNames = + Option(ctx.partitionColumnNames) + .map(visitIdentifierList(_).toArray) + .getOrElse(Array.empty[String]) + + CreateTableUsingAsSelect( + table, provider, temp, partitionColumnNames, bucketSpec, mode, options, query) } else { - val struct = Option(ctx.colTypeList).map(createStructType) + val struct = Option(ctx.colTypeList()).map(createStructType) CreateTableUsing(table, struct, provider, temp, options, ifNotExists, managedIfNoPath = false) } } |