Github user liancheng commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16156#discussion_r90968974
  
    --- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
 ---
    @@ -578,4 +578,66 @@ class ParquetFilterSuite extends QueryTest with 
ParquetTest with SharedSQLContex
           // scalastyle:on nonascii
         }
       }
    +
    +  test("SPARK-18539 - filtered by non-existing parquet column") {
    +    Seq("parquet").foreach { format =>
    +      withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true") {
    +        withTempPath { path =>
    +          import testImplicits._
    +          Seq((1, "abc"), (2, "hello")).toDF("a", 
"b").write.format(format).save(path.toString)
    +
    +          // user-specified schema contains nonexistent columns
    +          val schema = StructType(
    +            Seq(StructField("a", IntegerType),
    +              StructField("b", StringType),
    +              StructField("c", IntegerType)))
    +          val readDf1 = 
spark.read.schema(schema).format(format).load(path.toString)
    +
    +          // Read the table without any filter
    +          checkAnswer(readDf1, Row(1, "abc", null) :: Row(2, "hello", 
null) :: Nil)
    +          // Read the table with a filter on existing columns
    +          checkAnswer(readDf1.filter("a < 2"), Row(1, "abc", null) :: Nil)
    +
    +          // Read the table with a filter on nonexistent columns
    +          checkAnswer(readDf1.filter("c < 2"), Nil)
    +          checkAnswer(readDf1.filter("c is not null"), Nil)
    +
    +          checkAnswer(readDf1.filter("c is null"),
    +            Row(1, "abc", null) :: Row(2, "hello", null) :: Nil)
    +
    +          checkAnswer(readDf1.filter("c is null and a < 2"),
    +            Row(1, "abc", null) :: Nil)
    +
    +          // With another parquet file that contains the column "c"
    +          Seq((2, "abc", 3), (3, "hello", 4)).toDF("a", "b", "c")
    +            .write.format(format).mode(SaveMode.Append).save(path.toString)
    +
    +          // Right now, there are 2 parquet files. one with the column "c",
    +          // the other does not have it.
    +          val readDf2 = 
spark.read.schema(schema).format(format).load(path.toString)
    --- End diff --
    
    By default, we don't enable Parquet schema merging. Could you please 
reorganize this test case into something like this to have both code paths 
tested?
    
    ```scala
    Seq(true, false).foreach { merge =>
      test("SPARK-18539 - filtered by non-existing parquet column - schema 
merging enabled: $merge") {
        // ...
        val readDf2 = spark.read
          .option("mergeSchema", merge.toString)
          .schema(schema)
          .format(format)
          .load(path.toString)
        // ...
      }
    }
    ```



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