[SPARK-12660][SPARK-14967][SQL] Implement Except Distinct by Left Anti Join

#### What changes were proposed in this pull request?
Replaces a logical `Except` operator with a `Left-anti Join` operator. This way, we can take advantage of all the benefits of join implementations (e.g. managed memory, code generation, broadcast joins).
```SQL
  SELECT a1, a2 FROM Tab1 EXCEPT SELECT b1, b2 FROM Tab2
  ==>  SELECT DISTINCT a1, a2 FROM Tab1 LEFT ANTI JOIN Tab2 ON a1<=>b1 AND a2<=>b2
```
 Note:
 1. This rule is only applicable to EXCEPT DISTINCT. Do not use it for EXCEPT ALL.
 2. This rule has to be done after de-duplicating the attributes; otherwise, the enerated
    join conditions will be incorrect.

This PR also corrects the existing behavior in Spark. Before this PR, the behavior is like
```SQL
  test("except") {
    val df_left = Seq(1, 2, 2, 3, 3, 4).toDF("id")
    val df_right = Seq(1, 3).toDF("id")

    checkAnswer(
      df_left.except(df_right),
      Row(2) :: Row(2) :: Row(4) :: Nil
    )
  }
```
After this PR, the result is corrected. We strictly follow the SQL compliance of `Except Distinct`.

#### How was this patch tested?
Modified and added a few test cases to verify the optimization rule and the results of operators.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #12736 from gatorsmile/exceptByAntiJoin.

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