[SPARK-16400][SQL] Remove InSet filter pushdown from Parquet

## What changes were proposed in this pull request?
This patch removes InSet filter pushdown from Parquet data source, since row-based pushdown is not beneficial to Spark and brings extra complexity to the code base.

## How was this patch tested?
N/A

Author: Reynold Xin <rxin@databricks.com>

Closes #14076 from rxin/SPARK-16400.

1 files changed, 0 insertions, 30 deletions

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
index 84fdcfea3c..f59d474d00 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
@@ -514,36 +514,6 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
     }
   }
 
-  test("SPARK-11164: test the parquet filter in") {
-    import testImplicits._
-    withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true") {
-      withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "false") {
-        withTempPath { dir =>
-          val path = s"${dir.getCanonicalPath}/table1"
-          (1 to 5).map(i => (i.toFloat, i%3)).toDF("a", "b").write.parquet(path)
-
-          // When a filter is pushed to Parquet, Parquet can apply it to every row.
-          // So, we can check the number of rows returned from the Parquet
-          // to make sure our filter pushdown work.
-          val df = spark.read.parquet(path).where("b in (0,2)")
-          assert(stripSparkFilter(df).count == 3)
-
-          val df1 = spark.read.parquet(path).where("not (b in (1))")
-          assert(stripSparkFilter(df1).count == 3)
-
-          val df2 = spark.read.parquet(path).where("not (b in (1,3) or a <= 2)")
-          assert(stripSparkFilter(df2).count == 2)
-
-          val df3 = spark.read.parquet(path).where("not (b in (1,3) and a <= 2)")
-          assert(stripSparkFilter(df3).count == 4)
-
-          val df4 = spark.read.parquet(path).where("not (a <= 2)")
-          assert(stripSparkFilter(df4).count == 3)
-        }
-      }
-    }
-  }
-
   test("SPARK-16371 Do not push down filters when inner name and outer name are the same") {
     withParquetDataFrame((1 to 4).map(i => Tuple1(Tuple1(i)))) { implicit df =>
       // Here the schema becomes as below: