[SPARK-16033][SQL] insertInto() can't be used together with partitionBy()

## What changes were proposed in this pull request?

When inserting into an existing partitioned table, partitioning columns should always be determined by catalog metadata of the existing table to be inserted. Extra `partitionBy()` calls don't make sense, and mess up existing data because newly inserted data may have wrong partitioning directory layout.

## How was this patch tested?

New test case added in `InsertIntoHiveTableSuite`.

Author: Cheng Lian <lian@databricks.com>

Closes apache#13747 from liancheng/spark-16033-insert-into-without-partition-by.

Author: liancheng

sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala

@@ -21,8 +21,6 @@ import java.util.Properties
 
 import scala.collection.JavaConverters._
 
-import org.apache.hadoop.fs.Path
-
 import org.apache.spark.sql.catalyst.TableIdentifier
 import org.apache.spark.sql.catalyst.analysis.UnresolvedRelation
 import org.apache.spark.sql.catalyst.plans.logical.{InsertIntoTable, Project}
@@ -243,7 +241,15 @@ final class DataFrameWriter[T] private[sql](ds: Dataset[T]) {
 
   private def insertInto(tableIdent: TableIdentifier): Unit = {
     assertNotBucketed("insertInto")
-    val partitions = normalizedParCols.map(_.map(col => col -> (Option.empty[String])).toMap)
+
+    if (partitioningColumns.isDefined) {
+      throw new AnalysisException(
+        "insertInto() can't be used together with partitionBy(). " +
+          "Partition columns are defined by the table into which is being inserted."
+      )
+    }
+
+    val partitions = normalizedParCols.map(_.map(col => col -> Option.empty[String]).toMap)
     val overwrite = mode == SaveMode.Overwrite
 
     // A partitioned relation's schema can be different from the input logicalPlan, since

sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala

@@ -346,6 +346,43 @@ class InsertIntoHiveTableSuite extends QueryTest with TestHiveSingleton with Bef
     }
   }
 
+  private def testPartitionedHiveSerDeTable(testName: String)(f: String => Unit): Unit = {
+    test(s"Hive SerDe table - $testName") {
+      val hiveTable = "hive_table"
+
+      withTable(hiveTable) {
+        withSQLConf("hive.exec.dynamic.partition.mode" -> "nonstrict") {
+          sql(s"CREATE TABLE $hiveTable (a INT) PARTITIONED BY (b INT, c INT) STORED AS TEXTFILE")
+          f(hiveTable)
+        }
+      }
+    }
+  }
+
+  private def testPartitionedDataSourceTable(testName: String)(f: String => Unit): Unit = {
+    test(s"Data source table - $testName") {
+      val dsTable = "ds_table"
+
+      withTable(dsTable) {
+        sql(s"CREATE TABLE $dsTable (a INT, b INT, c INT) USING PARQUET PARTITIONED BY (b, c)")
+        f(dsTable)
+      }
+    }
+  }
+
+  private def testPartitionedTable(testName: String)(f: String => Unit): Unit = {
+    testPartitionedHiveSerDeTable(testName)(f)
+    testPartitionedDataSourceTable(testName)(f)
+  }
+
+  testPartitionedTable("partitionBy() can't be used together with insertInto()") { tableName =>
+    val cause = intercept[AnalysisException] {
+      Seq((1, 2, 3)).toDF("a", "b", "c").write.partitionBy("b", "c").insertInto(tableName)
+    }
+
+    assert(cause.getMessage.contains("insertInto() can't be used together with partitionBy()."))
+  }
+
   test("InsertIntoTable#resolved should include dynamic partitions") {
     withSQLConf(("hive.exec.dynamic.partition.mode", "nonstrict")) {
       sql("CREATE TABLE partitioned (id bigint, data string) PARTITIONED BY (part string)")