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

    https://github.com/apache/spark/pull/22467#discussion_r218835682
  
    --- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/ParquetPartitioningTest.scala 
---
    @@ -0,0 +1,253 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.sql.hive
    +
    +import java.io.File
    +
    +import org.apache.spark.sql._
    +import org.apache.spark.sql.hive.test.TestHiveSingleton
    +import org.apache.spark.sql.test.SQLTestUtils
    +import org.apache.spark.util.Utils
    +
    +// The data where the partitioning key exists only in the directory 
structure.
    +case class ParquetData(intField: Int, stringField: String)
    +// The data that also includes the partitioning key
    +case class ParquetDataWithKey(p: Int, intField: Int, stringField: String)
    +
    +case class StructContainer(intStructField: Int, stringStructField: String)
    +
    +case class ParquetDataWithComplexTypes(
    +    intField: Int,
    +    stringField: String,
    +    structField: StructContainer,
    +    arrayField: Seq[Int])
    +
    +case class ParquetDataWithKeyAndComplexTypes(
    +    p: Int,
    +    intField: Int,
    +    stringField: String,
    +    structField: StructContainer,
    +    arrayField: Seq[Int])
    +
    +/**
    + * A collection of tests for parquet data with various forms of 
partitioning.
    + */
    +abstract class ParquetPartitioningTest extends QueryTest with SQLTestUtils 
with TestHiveSingleton {
    +  import testImplicits._
    +
    +  var partitionedTableDir: File = null
    +  var normalTableDir: File = null
    +  var partitionedTableDirWithKey: File = null
    +  var partitionedTableDirWithComplexTypes: File = null
    +  var partitionedTableDirWithKeyAndComplexTypes: File = null
    +
    +  override def beforeAll(): Unit = {
    +    super.beforeAll()
    +    partitionedTableDir = Utils.createTempDir()
    +    normalTableDir = Utils.createTempDir()
    +
    +    (1 to 10).foreach { p =>
    +      val partDir = new File(partitionedTableDir, s"p=$p")
    +      sparkContext.makeRDD(1 to 10)
    +        .map(i => ParquetData(i, s"part-$p"))
    +        .toDF()
    +        .write.parquet(partDir.getCanonicalPath)
    +    }
    +
    +    sparkContext
    +      .makeRDD(1 to 10)
    +      .map(i => ParquetData(i, s"part-1"))
    +      .toDF()
    +      .write.parquet(new File(normalTableDir, "normal").getCanonicalPath)
    +
    +    partitionedTableDirWithKey = Utils.createTempDir()
    +
    +    (1 to 10).foreach { p =>
    +      val partDir = new File(partitionedTableDirWithKey, s"p=$p")
    +      sparkContext.makeRDD(1 to 10)
    +        .map(i => ParquetDataWithKey(p, i, s"part-$p"))
    +        .toDF()
    +        .write.parquet(partDir.getCanonicalPath)
    +    }
    +
    +    partitionedTableDirWithKeyAndComplexTypes = Utils.createTempDir()
    +
    +    (1 to 10).foreach { p =>
    +      val partDir = new File(partitionedTableDirWithKeyAndComplexTypes, 
s"p=$p")
    +      sparkContext.makeRDD(1 to 10).map { i =>
    +        ParquetDataWithKeyAndComplexTypes(
    +          p, i, s"part-$p", StructContainer(i, f"${i}_string"), 1 to i)
    +      }.toDF().write.parquet(partDir.getCanonicalPath)
    +    }
    +
    +    partitionedTableDirWithComplexTypes = Utils.createTempDir()
    +
    +    (1 to 10).foreach { p =>
    +      val partDir = new File(partitionedTableDirWithComplexTypes, s"p=$p")
    +      sparkContext.makeRDD(1 to 10).map { i =>
    +        ParquetDataWithComplexTypes(i, s"part-$p", StructContainer(i, 
f"${i}_string"), 1 to i)
    +      }.toDF().write.parquet(partDir.getCanonicalPath)
    +    }
    +  }
    +
    +  override protected def afterAll(): Unit = {
    +    try {
    +      partitionedTableDir.delete()
    +      normalTableDir.delete()
    +      partitionedTableDirWithKey.delete()
    +      partitionedTableDirWithComplexTypes.delete()
    +      partitionedTableDirWithKeyAndComplexTypes.delete()
    +    } finally {
    +      super.afterAll()
    +    }
    +  }
    +
    +  /**
    +   * Drop named tables if they exist
    + *
    +   * @param tableNames tables to drop
    +   */
    +  def dropTables(tableNames: String*): Unit = {
    +    tableNames.foreach { name =>
    +      sql(s"DROP TABLE IF EXISTS $name")
    +    }
    +  }
    +
    +  Seq(
    +    "partitioned_parquet",
    +    "partitioned_parquet_with_key",
    +    "partitioned_parquet_with_complextypes",
    +    "partitioned_parquet_with_key_and_complextypes").foreach { table =>
    +
    +    test(s"ordering of the partitioning columns $table") {
    +      checkAnswer(
    +        sql(s"SELECT p, stringField FROM $table WHERE p = 1"),
    +        Seq.fill(10)(Row(1, "part-1"))
    +      )
    +
    +      checkAnswer(
    +        sql(s"SELECT stringField, p FROM $table WHERE p = 1"),
    +        Seq.fill(10)(Row("part-1", 1))
    +      )
    +    }
    +
    +    test(s"project the partitioning column $table") {
    +      checkAnswer(
    +        sql(s"SELECT p, count(*) FROM $table group by p"),
    +        Row(1, 10) ::
    +          Row(2, 10) ::
    +          Row(3, 10) ::
    +          Row(4, 10) ::
    +          Row(5, 10) ::
    +          Row(6, 10) ::
    +          Row(7, 10) ::
    +          Row(8, 10) ::
    +          Row(9, 10) ::
    +          Row(10, 10) :: Nil
    +      )
    +    }
    +
    +    test(s"project partitioning and non-partitioning columns $table") {
    +      checkAnswer(
    +        sql(s"SELECT stringField, p, count(intField) FROM $table GROUP BY 
p, stringField"),
    +        Row("part-1", 1, 10) ::
    +          Row("part-2", 2, 10) ::
    +          Row("part-3", 3, 10) ::
    +          Row("part-4", 4, 10) ::
    +          Row("part-5", 5, 10) ::
    +          Row("part-6", 6, 10) ::
    +          Row("part-7", 7, 10) ::
    +          Row("part-8", 8, 10) ::
    +          Row("part-9", 9, 10) ::
    +          Row("part-10", 10, 10) :: Nil
    +      )
    +    }
    +
    +    test(s"simple count $table") {
    +      checkAnswer(
    +        sql(s"SELECT COUNT(*) FROM $table"),
    +        Row(100))
    +    }
    +
    +    test(s"pruned count $table") {
    +      checkAnswer(
    +        sql(s"SELECT COUNT(*) FROM $table WHERE p = 1"),
    +        Row(10))
    +    }
    +
    +    test(s"non-existent partition $table") {
    +      checkAnswer(
    +        sql(s"SELECT COUNT(*) FROM $table WHERE p = 1000"),
    +        Row(0))
    +    }
    +
    +    test(s"multi-partition pruned count $table") {
    +      checkAnswer(
    +        sql(s"SELECT COUNT(*) FROM $table WHERE p IN (1,2,3)"),
    +        Row(30))
    +    }
    +
    +    test(s"non-partition predicates $table") {
    +      checkAnswer(
    +        sql(s"SELECT COUNT(*) FROM $table WHERE intField IN (1,2,3)"),
    +        Row(30))
    +    }
    +
    +    test(s"sum $table") {
    +      checkAnswer(
    +        sql(s"SELECT SUM(intField) FROM $table WHERE intField IN (1,2,3) 
AND p = 1"),
    +        Row(1 + 2 + 3))
    +    }
    +
    +    test(s"hive udfs $table") {
    +      checkAnswer(
    +        sql(s"SELECT concat(stringField, stringField) FROM $table"),
    +        sql(s"SELECT stringField FROM $table").rdd.map {
    +          case Row(s: String) => Row(s + s)
    +        }.collect().toSeq)
    +    }
    +  }
    +
    +  Seq(
    +    "partitioned_parquet_with_key_and_complextypes",
    +    "partitioned_parquet_with_complextypes").foreach { table =>
    +
    +    test(s"SPARK-5775 read struct from $table") {
    +      checkAnswer(
    +        sql(
    +          s"""
    +             |SELECT p, structField.intStructField, 
structField.stringStructField
    +             |FROM $table WHERE p = 1
    +           """.stripMargin),
    +        (1 to 10).map(i => Row(1, i, f"${i}_string")))
    +    }
    +
    +    test(s"SPARK-5775 read array from $table") {
    +      checkAnswer(
    +        sql(s"SELECT arrayField, p FROM $table WHERE p = 1"),
    +        (1 to 10).map(i => Row((1 to i).toArray, 1)))
    +    }
    +  }
    +
    --- End diff --
    
    extra line.


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