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| author | Daoyuan Wang <daoyuan.wang@intel.com> | 2016-03-16 22:52:10 -0700 |
|---|---|---|
| committer | Reynold Xin <rxin@databricks.com> | 2016-03-16 22:52:10 -0700 |
| commit | d1c193a2f1a5e2b98f5df1b86d7a7ec0ced13668 (patch) | |
| tree | 94aef4269107c7dbb650980116c9bd2ca72566ba /docs/sql-programming-guide.md | |
| parent | c890c359b1dfb64274d1d0067b1e16d834035f11 (diff) | |
| download | spark-d1c193a2f1a5e2b98f5df1b86d7a7ec0ced13668.tar.gz spark-d1c193a2f1a5e2b98f5df1b86d7a7ec0ced13668.tar.bz2 spark-d1c193a2f1a5e2b98f5df1b86d7a7ec0ced13668.zip | |
[SPARK-12855][MINOR][SQL][DOC][TEST] remove spark.sql.dialect from doc and test
## What changes were proposed in this pull request?
Since developer API of plug-able parser has been removed in #10801 , docs should be updated accordingly.
## How was this patch tested?
This patch will not affect the real code path.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #11758 from adrian-wang/spark12855.
Diffstat (limited to 'docs/sql-programming-guide.md')
| -rw-r--r-- | docs/sql-programming-guide.md | 7 |
1 files changed, 0 insertions, 7 deletions
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 3138fd5fb4..2fdc97f8a0 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -122,13 +122,6 @@ Spark build. If these dependencies are not a problem for your application then u is recommended for the 1.3 release of Spark. Future releases will focus on bringing `SQLContext` up to feature parity with a `HiveContext`. -The specific variant of SQL that is used to parse queries can also be selected using the -`spark.sql.dialect` option. This parameter can be changed using either the `setConf` method on -a `SQLContext` or by using a `SET key=value` command in SQL. For a `SQLContext`, the only dialect -available is "sql" which uses a simple SQL parser provided by Spark SQL. In a `HiveContext`, the -default is "hiveql", though "sql" is also available. Since the HiveQL parser is much more complete, -this is recommended for most use cases. - ## Creating DataFrames |