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* [SPARK-17298][SQL] Require explicit CROSS join for cartesian productsSrinath Shankar2016-09-031-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Require the use of CROSS join syntax in SQL (and a new crossJoin DataFrame API) to specify explicit cartesian products between relations. By cartesian product we mean a join between relations R and S where there is no join condition involving columns from both R and S. If a cartesian product is detected in the absence of an explicit CROSS join, an error must be thrown. Turning on the "spark.sql.crossJoin.enabled" configuration flag will disable this check and allow cartesian products without an explicit CROSS join. The new crossJoin DataFrame API must be used to specify explicit cross joins. The existing join(DataFrame) method will produce a INNER join that will require a subsequent join condition. That is df1.join(df2) is equivalent to select * from df1, df2. ## How was this patch tested? Added cross-join.sql to the SQLQueryTestSuite to test the check for cartesian products. Added a couple of tests to the DataFrameJoinSuite to test the crossJoin API. Modified various other test suites to explicitly specify a cross join where an INNER join or a comma-separated list was previously used. Author: Srinath Shankar <srinath@databricks.com> Closes #14866 from srinathshankar/crossjoin.
* [SPARK-16771][SQL] WITH clause should not fall into infinite loop.Dongjoon Hyun2016-08-121-0/+57
## What changes were proposed in this pull request? This PR changes the CTE resolving rule to use only **forward-declared** tables in order to prevent infinite loops. More specifically, new logic is like the following. * Resolve CTEs in `WITH` clauses first before replacing the main SQL body. * When resolving CTEs, only forward-declared CTEs or base tables are referenced. - Self-referencing is not allowed any more. - Cross-referencing is not allowed any more. **Reported Error Scenarios** ```scala scala> sql("WITH t AS (SELECT 1 FROM t) SELECT * FROM t") java.lang.StackOverflowError ... scala> sql("WITH t1 AS (SELECT * FROM t2), t2 AS (SELECT 2 FROM t1) SELECT * FROM t1, t2") java.lang.StackOverflowError ... ``` Note that `t`, `t1`, and `t2` are not declared in database. Spark falls into infinite loops before resolving table names. ## How was this patch tested? Pass the Jenkins tests with new two testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14397 from dongjoon-hyun/SPARK-16771-TREENODE.