GitHub user clockfly opened a pull request:
https://github.com/apache/spark/pull/13743
[SPARK-15916][SQL] JDBC filter push down should respect operator precedence
## What changes were proposed in this pull request?
This PR fixes the problem that the precedence order is messed when pushing
where-clause expression to JDBC layer.
**Case 1:**
For sql `select * from table where (a or b) and c`, the where-clause is
wrongly converted to JDBC where-clause `a or (b and c)` after filter push down.
The consequence is that JDBC may returns less or more rows than expected.
**Case 2:**
For sql `select * from table where always_false_condition`, the result
table may not be empty if the JDBC RDD is partitioned using:
```
spark.read.jdbc(url, table, predicates = Array("partition 1 where clause",
"partition 2 where clause"...)
```
## How was this patch tested?
Unit test.
This PR also close #13640
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/clockfly/spark SPARK-15916
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/13743.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #13743
----
commit bcfef466ec4cc74c4fd6b6180a9008600c6ca07b
Author: hyukjinkwon <gurwls...@gmail.com>
Date: 2016-06-13T10:32:16Z
Consider top level and/or precedence for parenthesis
commit 2f1ada38d6a50916b3f5c9a681e01d8f13c0ac4b
Author: Sean Zhong <seanzh...@databricks.com>
Date: 2016-06-17T21:10:34Z
fix partition where clause pushdown
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