[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 where-clause:
```
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

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Sean Zhong <seanzhong@databricks.com>

Closes #13743 from clockfly/SPARK-15916.