[SPARK-27453] Pass partitionBy as options in DataFrameWriter

## What changes were proposed in this pull request?

Pass partitionBy columns as options and feature-flag this behavior.

## How was this patch tested?

A new unit test.

Closes apache#24365 from liwensun/partitionby.

Authored-by: liwensun <liwen.sun@databricks.com>
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>

sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala

@@ -1673,6 +1673,15 @@ object SQLConf {
       .booleanConf
       .createWithDefault(false)
 
+  val LEGACY_PASS_PARTITION_BY_AS_OPTIONS =
+    buildConf("spark.sql.legacy.sources.write.passPartitionByAsOptions")
+      .internal()
+      .doc("Whether to pass the partitionBy columns as options in DataFrameWriter. " +
+        "Data source V1 now silently drops partitionBy columns for non-file-format sources; " +
+        "turning the flag on provides a way for these sources to see these partitionBy columns.")
+      .booleanConf
+      .createWithDefault(false)
+
   val NAME_NON_STRUCT_GROUPING_KEY_AS_VALUE =
     buildConf("spark.sql.legacy.dataset.nameNonStructGroupingKeyAsValue")
       .internal()

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

@@ -29,8 +29,9 @@ import org.apache.spark.sql.catalyst.expressions.Literal
 import org.apache.spark.sql.catalyst.plans.logical.{AppendData, InsertIntoTable, LogicalPlan, OverwriteByExpression}
 import org.apache.spark.sql.execution.SQLExecution
 import org.apache.spark.sql.execution.command.DDLUtils
-import org.apache.spark.sql.execution.datasources.{CreateTable, DataSource, LogicalRelation}
+import org.apache.spark.sql.execution.datasources.{CreateTable, DataSource, DataSourceUtils, LogicalRelation}
 import org.apache.spark.sql.execution.datasources.v2.{DataSourceV2Relation, DataSourceV2Utils, FileDataSourceV2, WriteToDataSourceV2}
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.sources.BaseRelation
 import org.apache.spark.sql.sources.v2._
 import org.apache.spark.sql.sources.v2.TableCapability._
@@ -315,6 +316,14 @@ final class DataFrameWriter[T] private[sql](ds: Dataset[T]) {
   }
 
   private def saveToV1Source(): Unit = {
+    if (SparkSession.active.sessionState.conf.getConf(
+      SQLConf.LEGACY_PASS_PARTITION_BY_AS_OPTIONS)) {
+      partitioningColumns.foreach { columns =>
+        extraOptions += (DataSourceUtils.PARTITIONING_COLUMNS_KEY ->
+          DataSourceUtils.encodePartitioningColumns(columns))
+      }
+    }
+
     // Code path for data source v1.
     runCommand(df.sparkSession, "save") {
       DataSource(

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala

@@ -18,12 +18,32 @@
 package org.apache.spark.sql.execution.datasources
 
 import org.apache.hadoop.fs.Path
+import org.json4s.NoTypeHints
+import org.json4s.jackson.Serialization
 
 import org.apache.spark.sql.AnalysisException
 import org.apache.spark.sql.types._
 
 
 object DataSourceUtils {
+  /**
+   * The key to use for storing partitionBy columns as options.
+   */
+  val PARTITIONING_COLUMNS_KEY = "__partition_columns"
+
+  /**
+   * Utility methods for converting partitionBy columns to options and back.
+   */
+  private implicit val formats = Serialization.formats(NoTypeHints)
+
+  def encodePartitioningColumns(columns: Seq[String]): String = {
+    Serialization.write(columns)
+  }
+
+  def decodePartitioningColumns(str: String): Seq[String] = {
+    Serialization.read[Seq[String]](str)
+  }
+
   /**
    * Verify if the schema is supported in datasource. This verification should be done
    * in a driver side.

sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala

@@ -38,6 +38,7 @@ import org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 import org.apache.spark.scheduler.{SparkListener, SparkListenerJobStart}
 import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.execution.datasources.DataSourceUtils
 import org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.sources._
@@ -219,6 +220,24 @@ class DataFrameReaderWriterSuite extends QueryTest with SharedSQLContext with Be
     assert(LastOptions.parameters("opt3") == "3")
   }
 
+  test("pass partitionBy as options") {
+    Seq(true, false).foreach { flag =>
+      withSQLConf(SQLConf.LEGACY_PASS_PARTITION_BY_AS_OPTIONS.key -> s"$flag") {
+        Seq(1).toDF.write
+          .format("org.apache.spark.sql.test")
+          .partitionBy("col1", "col2")
+          .save()
+
+        if (flag) {
+          val partColumns = LastOptions.parameters(DataSourceUtils.PARTITIONING_COLUMNS_KEY)
+          assert(DataSourceUtils.decodePartitioningColumns(partColumns) === Seq("col1", "col2"))
+        } else {
+          assert(!LastOptions.parameters.contains(DataSourceUtils.PARTITIONING_COLUMNS_KEY))
+        }
+      }
+    }
+  }
+
   test("save mode") {
     val df = spark.read
       .format("org.apache.spark.sql.test")