[SPARK-16556][SPARK-16559][SQL] Fix Two Bugs in Bucket Specification

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

**Issue 1: Silent Ignorance of Bucket Specification When Creating Table Using Schema Inference**

When creating a data source table without explicit specification of schema or SELECT clause, we silently ignore the bucket specification (CLUSTERED BY... SORTED BY...) in [the code](https://github.com/apache/spark/blob/ce3b98bae28af72299722f56e4e4ef831f471ec0/sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala#L339-L354).

For example,
```SQL
CREATE TABLE jsonTable
USING org.apache.spark.sql.json
OPTIONS (
  path '${tempDir.getCanonicalPath}'
)
CLUSTERED BY (inexistentColumnA) SORTED BY (inexistentColumnB) INTO 2 BUCKETS
```

This PR captures it and issues an error message.

**Issue 2: Got a run-time `java.lang.ArithmeticException` when num of buckets is set to zero.**

For example,
```SQL
CREATE TABLE t USING PARQUET
OPTIONS (PATH '${path.toString}')
CLUSTERED BY (a) SORTED BY (b) INTO 0 BUCKETS
AS SELECT 1 AS a, 2 AS b
```
The exception we got is
```
ERROR org.apache.spark.executor.Executor: Exception in task 0.0 in stage 1.0 (TID 2)
java.lang.ArithmeticException: / by zero
```

This PR captures the misuse and issues an appropriate error message.

### How was this patch tested?
Added a test case in DDLSuite

Author: gatorsmile <gatorsmile@gmail.com>

Closes #14210 from gatorsmile/createTableWithoutSchema.

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