[SPARK-18538][SQL][BACKPORT-2.1] Fix Concurrent Table Fetching Using DataFrameReader JDBC APIs

### What changes were proposed in this pull request?

#### This PR is to backport https://github.com/apache/spark/pull/15975 to Branch 2.1

---

The following two `DataFrameReader` JDBC APIs ignore the user-specified parameters of parallelism degree.

```Scala
  def jdbc(
      url: String,
      table: String,
      columnName: String,
      lowerBound: Long,
      upperBound: Long,
      numPartitions: Int,
      connectionProperties: Properties): DataFrame
```

```Scala
  def jdbc(
      url: String,
      table: String,
      predicates: Array[String],
      connectionProperties: Properties): DataFrame
```

This PR is to fix the issues. To verify the behavior correctness, we improve the plan output of `EXPLAIN` command by adding `numPartitions` in the `JDBCRelation` node.

Before the fix,
```
== Physical Plan ==
*Scan JDBCRelation(TEST.PEOPLE) [NAME#1896,THEID#1897] ReadSchema: struct<NAME:string,THEID:int>
```

After the fix,
```
== Physical Plan ==
*Scan JDBCRelation(TEST.PEOPLE) [numPartitions=3] [NAME#1896,THEID#1897] ReadSchema: struct<NAME:string,THEID:int>
```
### How was this patch tested?
Added the verification logics on all the test cases for JDBC concurrent fetching.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16111 from gatorsmile/jdbcFix2.1.