[SPARK-5182] [SPARK-5528] [SPARK-5509] [SPARK-3575] [SQL] Parquet data source improvements

This PR adds three major improvements to Parquet data source:

1.  Partition discovery

    While reading Parquet files resides in Hive style partition directories, `ParquetRelation2` automatically discovers partitioning information and infers partition column types.

    This is also a partial work for [SPARK-5182] [1], which aims to provide first class partitioning support for the data source API.  Related code in this PR can be easily extracted to the data source API level in future versions.

1.  Schema merging

    When enabled, Parquet data source collects schema information from all Parquet part-files and tries to merge them.  Exceptions are thrown when incompatible schemas are detected.  This feature is controlled by data source option `parquet.mergeSchema`, and is enabled by default.

1.  Metastore Parquet table conversion moved to analysis phase

    This greatly simplifies the conversion logic.  `ParquetConversion` strategy can be removed once the old Parquet implementation is removed in the future.

This version of Parquet data source aims to entirely replace the old Parquet implementation.  However, the old version hasn't been removed yet.  Users can fall back to the old version by turning off SQL configuration `spark.sql.parquet.useDataSourceApi`.

Other JIRA tickets fixed as side effects in this PR:

- [SPARK-5509] [3]: `EqualTo` now uses a proper `Ordering` to compare binary types.

- [SPARK-3575] [4]: Metastore schema is now preserved and passed to `ParquetRelation2` via data source option `parquet.metastoreSchema`.

TODO:

- [ ] More test cases for partition discovery
- [x] Fix write path after data source write support (#4294) is merged

      It turned out to be non-trivial to fall back to old Parquet implementation on the write path when Parquet data source is enabled.  Since we're planning to include data source write support in 1.3.0, I simply ignored two test cases involving Parquet insertion for now.

- [ ] Fix outdated comments and documentations

PS: This PR looks big, but more than a half of the changed lines in this PR are trivial changes to test cases. To test Parquet with and without the new data source, almost all Parquet test cases are moved into wrapper driver functions. This introduces hundreds of lines of changes.

[1]: https://issues.apache.org/jira/browse/SPARK-5182
[2]: https://issues.apache.org/jira/browse/SPARK-5528
[3]: https://issues.apache.org/jira/browse/SPARK-5509
[4]: https://issues.apache.org/jira/browse/SPARK-3575

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Author: Cheng Lian <lian@databricks.com>

Closes #4308 from liancheng/parquet-partition-discovery and squashes the following commits:

b6946e6 [Cheng Lian] Fixes MiMA issues, addresses comments
8232e17 [Cheng Lian] Write support for Parquet data source
a49bd28 [Cheng Lian] Fixes spelling typo in trait name "CreateableRelationProvider"
808380f [Cheng Lian] Fixes issues introduced while rebasing
50dd8d1 [Cheng Lian] Addresses @rxin's comment, fixes UDT schema merging
adf2aae [Cheng Lian] Fixes compilation error introduced while rebasing
4e0175f [Cheng Lian] Fixes Python Parquet API, we need Py4J array to call varargs method
0d8ec1d [Cheng Lian] Adds more test cases
b35c8c6 [Cheng Lian] Fixes some typos and outdated comments
dd704fd [Cheng Lian] Fixes Python Parquet API
596c312 [Cheng Lian] Uses switch to control whether use Parquet data source or not
7d0f7a2 [Cheng Lian] Fixes Metastore Parquet table conversion
a1896c7 [Cheng Lian] Fixes all existing Parquet test suites except for ParquetMetastoreSuite
5654c9d [Cheng Lian] Draft version of Parquet partition discovery and schema merging

4 files changed, 174 insertions, 133 deletions

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
index 243310686d..c78369d12c 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
@@ -38,6 +38,7 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.logical
 import org.apache.spark.sql.catalyst.plans.logical._
 import org.apache.spark.sql.catalyst.rules._
+import org.apache.spark.sql.parquet.ParquetRelation2
 import org.apache.spark.sql.sources.{DDLParser, LogicalRelation, ResolvedDataSource}
 import org.apache.spark.sql.types._
 import org.apache.spark.util.Utils
@@ -175,10 +176,25 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
           Nil
         }
 
-      // Since HiveQL is case insensitive for table names we make them all lowercase.
-      MetastoreRelation(
+      val relation = MetastoreRelation(
         databaseName, tblName, alias)(
           table.getTTable, partitions.map(part => part.getTPartition))(hive)
+
+      if (hive.convertMetastoreParquet &&
+          hive.conf.parquetUseDataSourceApi &&
+          relation.tableDesc.getSerdeClassName.toLowerCase.contains("parquet")) {
+        val metastoreSchema = StructType.fromAttributes(relation.output)
+        val paths = if (relation.hiveQlTable.isPartitioned) {
+          relation.hiveQlPartitions.map(p => p.getLocation)
+        } else {
+          Seq(relation.hiveQlTable.getDataLocation.toString)
+        }
+
+        LogicalRelation(ParquetRelation2(
+          paths, Map(ParquetRelation2.METASTORE_SCHEMA -> metastoreSchema.json))(hive))
+      } else {
+        relation
+      }
     }
   }
 
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
index 7857a0252e..95abc363ae 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
@@ -87,7 +87,8 @@ private[hive] trait HiveStrategies {
     def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
       case PhysicalOperation(projectList, predicates, relation: MetastoreRelation)
           if relation.tableDesc.getSerdeClassName.contains("Parquet") &&
-             hiveContext.convertMetastoreParquet =>
+             hiveContext.convertMetastoreParquet &&
+             !hiveContext.conf.parquetUseDataSourceApi =>
 
         // Filter out all predicates that only deal with partition keys
         val partitionsKeys = AttributeSet(relation.partitionKeys)
@@ -136,8 +137,10 @@ private[hive] trait HiveStrategies {
               pruningCondition(inputData)
             }
 
+            val partitionLocations = partitions.map(_.getLocation)
+
             hiveContext
-              .parquetFile(partitions.map(_.getLocation).mkString(","))
+              .parquetFile(partitionLocations.head, partitionLocations.tail: _*)
               .addPartitioningAttributes(relation.partitionKeys)
               .lowerCase
               .where(unresolvedOtherPredicates)
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala
index 581f666399..eae69af586 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala
@@ -28,53 +28,55 @@ class HiveParquetSuite extends QueryTest with ParquetTest {
 
   import sqlContext._
 
-  test("Case insensitive attribute names") {
-    withParquetTable((1 to 4).map(i => Cases(i.toString, i.toString)), "cases") {
-      val expected = (1 to 4).map(i => Row(i.toString))
-      checkAnswer(sql("SELECT upper FROM cases"), expected)
-      checkAnswer(sql("SELECT LOWER FROM cases"), expected)
+  def run(prefix: String): Unit = {
+    test(s"$prefix: Case insensitive attribute names") {
+      withParquetTable((1 to 4).map(i => Cases(i.toString, i.toString)), "cases") {
+        val expected = (1 to 4).map(i => Row(i.toString))
+        checkAnswer(sql("SELECT upper FROM cases"), expected)
+        checkAnswer(sql("SELECT LOWER FROM cases"), expected)
+      }
     }
-  }
 
-  test("SELECT on Parquet table") {
-    val data = (1 to 4).map(i => (i, s"val_$i"))
-    withParquetTable(data, "t") {
-      checkAnswer(sql("SELECT * FROM t"), data.map(Row.fromTuple))
-    }
-  }
-
-  test("Simple column projection + filter on Parquet table") {
-    withParquetTable((1 to 4).map(i => (i % 2 == 0, i, s"val_$i")), "t") {
-      checkAnswer(
-        sql("SELECT `_1`, `_3` FROM t WHERE `_1` = true"),
-        Seq(Row(true, "val_2"), Row(true, "val_4")))
+    test(s"$prefix: SELECT on Parquet table") {
+      val data = (1 to 4).map(i => (i, s"val_$i"))
+      withParquetTable(data, "t") {
+        checkAnswer(sql("SELECT * FROM t"), data.map(Row.fromTuple))
+      }
     }
-  }
 
-  test("Converting Hive to Parquet Table via saveAsParquetFile") {
-    withTempPath { dir =>
-      sql("SELECT * FROM src").saveAsParquetFile(dir.getCanonicalPath)
-      parquetFile(dir.getCanonicalPath).registerTempTable("p")
-      withTempTable("p") {
+    test(s"$prefix: Simple column projection + filter on Parquet table") {
+      withParquetTable((1 to 4).map(i => (i % 2 == 0, i, s"val_$i")), "t") {
         checkAnswer(
-          sql("SELECT * FROM src ORDER BY key"),
-          sql("SELECT * from p ORDER BY key").collect().toSeq)
+          sql("SELECT `_1`, `_3` FROM t WHERE `_1` = true"),
+          Seq(Row(true, "val_2"), Row(true, "val_4")))
       }
     }
-  }
-
 
-  test("INSERT OVERWRITE TABLE Parquet table") {
-    withParquetTable((1 to 4).map(i => (i, s"val_$i")), "t") {
-      withTempPath { file =>
-        sql("SELECT * FROM t LIMIT 1").saveAsParquetFile(file.getCanonicalPath)
-        parquetFile(file.getCanonicalPath).registerTempTable("p")
+    test(s"$prefix: Converting Hive to Parquet Table via saveAsParquetFile") {
+      withTempPath { dir =>
+        sql("SELECT * FROM src").saveAsParquetFile(dir.getCanonicalPath)
+        parquetFile(dir.getCanonicalPath).registerTempTable("p")
         withTempTable("p") {
-          // let's do three overwrites for good measure
-          sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
-          sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
-          sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
-          checkAnswer(sql("SELECT * FROM p"), sql("SELECT * FROM t").collect().toSeq)
+          checkAnswer(
+            sql("SELECT * FROM src ORDER BY key"),
+            sql("SELECT * from p ORDER BY key").collect().toSeq)
+        }
+      }
+    }
+
+    // TODO Re-enable this after data source insertion API is merged
+    ignore(s"$prefix: INSERT OVERWRITE TABLE Parquet table") {
+      withParquetTable((1 to 10).map(i => (i, s"val_$i")), "t") {
+        withTempPath { file =>
+          sql("SELECT * FROM t LIMIT 1").saveAsParquetFile(file.getCanonicalPath)
+          parquetFile(file.getCanonicalPath).registerTempTable("p")
+          withTempTable("p") {
+            // let's do three overwrites for good measure
+            sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
+            sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
+            sql("INSERT OVERWRITE TABLE p SELECT * FROM t")
+            checkAnswer(sql("SELECT * FROM p"), sql("SELECT * FROM t").collect().toSeq)
+          }
         }
       }
     }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala
index 30441bbbdf..a7479a5b95 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala
@@ -23,7 +23,8 @@ import java.io.File
 import org.apache.spark.sql.catalyst.expressions.Row
 import org.scalatest.BeforeAndAfterAll
 
-import org.apache.spark.sql.QueryTest
+import org.apache.spark.sql.{SQLConf, QueryTest}
+import org.apache.spark.sql.execution.PhysicalRDD
 import org.apache.spark.sql.hive.execution.HiveTableScan
 import org.apache.spark.sql.hive.test.TestHive._
 
@@ -79,7 +80,7 @@ class ParquetMetastoreSuite extends ParquetPartitioningTest {
        STORED AS
        INPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
        OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
-      location '${new File(partitionedTableDir, "p=1").getCanonicalPath}'
+      location '${new File(normalTableDir, "normal").getCanonicalPath}'
     """)
 
     (1 to 10).foreach { p =>
@@ -97,7 +98,7 @@ class ParquetMetastoreSuite extends ParquetPartitioningTest {
     setConf("spark.sql.hive.convertMetastoreParquet", "false")
   }
 
-  test("conversion is working") {
+  test(s"conversion is working") {
     assert(
       sql("SELECT * FROM normal_parquet").queryExecution.executedPlan.collect {
         case _: HiveTableScan => true
@@ -105,6 +106,7 @@ class ParquetMetastoreSuite extends ParquetPartitioningTest {
     assert(
       sql("SELECT * FROM normal_parquet").queryExecution.executedPlan.collect {
         case _: ParquetTableScan => true
+        case _: PhysicalRDD => true
       }.nonEmpty)
   }
 }
@@ -147,6 +149,7 @@ class ParquetSourceSuite extends ParquetPartitioningTest {
  */
 abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll {
   var partitionedTableDir: File = null
+  var normalTableDir: File = null
   var partitionedTableDirWithKey: File = null
 
   import org.apache.spark.sql.hive.test.TestHive.implicits._
@@ -156,6 +159,10 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll
     partitionedTableDir.delete()
     partitionedTableDir.mkdir()
 
+    normalTableDir = File.createTempFile("parquettests", "sparksql")
+    normalTableDir.delete()
+    normalTableDir.mkdir()
+
     (1 to 10).foreach { p =>
       val partDir = new File(partitionedTableDir, s"p=$p")
       sparkContext.makeRDD(1 to 10)
@@ -163,6 +170,11 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll
         .saveAsParquetFile(partDir.getCanonicalPath)
     }
 
+    sparkContext
+      .makeRDD(1 to 10)
+      .map(i => ParquetData(i, s"part-1"))
+      .saveAsParquetFile(new File(normalTableDir, "normal").getCanonicalPath)
+
     partitionedTableDirWithKey = File.createTempFile("parquettests", "sparksql")
     partitionedTableDirWithKey.delete()
     partitionedTableDirWithKey.mkdir()
@@ -175,99 +187,107 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll
     }
   }
 
-  Seq("partitioned_parquet", "partitioned_parquet_with_key").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 $table"),
-        Row(100))
+  def run(prefix: String): Unit = {
+    Seq("partitioned_parquet", "partitioned_parquet_with_key").foreach { table =>
+      test(s"$prefix: 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 $table WHERE p = 1"),
+          Seq.fill(10)(Row("part-1", 1))
+        )
+      }
+
+      test(s"$prefix: project the partitioning column $table") {
+        checkAnswer(
+          sql(s"SELECT p, count(*) FROM $table group by p"),
+          Row(1, 10) ::
+            Row(2, 10) ::
+            Row(3, 10) ::
+            Row(4, 10) ::
+            Row(5, 10) ::
+            Row(6, 10) ::
+            Row(7, 10) ::
+            Row(8, 10) ::
+            Row(9, 10) ::
+            Row(10, 10) :: Nil
+        )
+      }
+
+      test(s"$prefix: project partitioning and non-partitioning columns $table") {
+        checkAnswer(
+          sql(s"SELECT stringField, p, count(intField) FROM $table GROUP BY p, stringField"),
+          Row("part-1", 1, 10) ::
+            Row("part-2", 2, 10) ::
+            Row("part-3", 3, 10) ::
+            Row("part-4", 4, 10) ::
+            Row("part-5", 5, 10) ::
+            Row("part-6", 6, 10) ::
+            Row("part-7", 7, 10) ::
+            Row("part-8", 8, 10) ::
+            Row("part-9", 9, 10) ::
+            Row("part-10", 10, 10) :: Nil
+        )
+      }
+
+      test(s"$prefix: simple count $table") {
+        checkAnswer(
+          sql(s"SELECT COUNT(*) FROM $table"),
+          Row(100))
+      }
+
+      test(s"$prefix: pruned count $table") {
+        checkAnswer(
+          sql(s"SELECT COUNT(*) FROM $table WHERE p = 1"),
+          Row(10))
+      }
+
+      test(s"$prefix: non-existent partition $table") {
+        checkAnswer(
+          sql(s"SELECT COUNT(*) FROM $table WHERE p = 1000"),
+          Row(0))
+      }
+
+      test(s"$prefix: multi-partition pruned count $table") {
+        checkAnswer(
+          sql(s"SELECT COUNT(*) FROM $table WHERE p IN (1,2,3)"),
+          Row(30))
+      }
+
+      test(s"$prefix: non-partition predicates $table") {
+        checkAnswer(
+          sql(s"SELECT COUNT(*) FROM $table WHERE intField IN (1,2,3)"),
+          Row(30))
+      }
+
+      test(s"$prefix: sum $table") {
+        checkAnswer(
+          sql(s"SELECT SUM(intField) FROM $table WHERE intField IN (1,2,3) AND p = 1"),
+          Row(1 + 2 + 3))
+      }
+
+      test(s"$prefix: hive udfs $table") {
+        checkAnswer(
+          sql(s"SELECT concat(stringField, stringField) FROM $table"),
+          sql(s"SELECT stringField FROM $table").map {
+            case Row(s: String) => Row(s + s)
+          }.collect().toSeq)
+      }
     }
 
-    test(s"pruned count $table") {
+    test(s"$prefix: $prefix: non-part select(*)") {
       checkAnswer(
-        sql(s"SELECT COUNT(*) FROM $table WHERE p = 1"),
+        sql("SELECT COUNT(*) FROM normal_parquet"),
         Row(10))
     }
-
-    test(s"non-existant 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").map {
-          case Row(s: String) => Row(s + s)
-        }.collect().toSeq)
-    }
   }
 
-  test("non-part select(*)") {
-    checkAnswer(
-      sql("SELECT COUNT(*) FROM normal_parquet"),
-      Row(10))
-  }
+  setConf(SQLConf.PARQUET_USE_DATA_SOURCE_API, "false")
+  run("Parquet data source enabled")
+
+  setConf(SQLConf.PARQUET_USE_DATA_SOURCE_API, "true")
+  run("Parquet data source disabled")
 }