[SPARK-23144][SS] Added console sink for continuous processing

## What changes were proposed in this pull request?
Refactored ConsoleWriter into ConsoleMicrobatchWriter and ConsoleContinuousWriter.

## How was this patch tested?
new unit test

Author: Tathagata Das <[email protected]>

Closes apache#20311 from tdas/SPARK-23144.

Author: tdas

sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/console.scala

@@ -19,13 +19,12 @@ package org.apache.spark.sql.execution.streaming
 
 import java.util.Optional
 
-import scala.collection.JavaConverters._
-
 import org.apache.spark.sql._
-import org.apache.spark.sql.execution.streaming.sources.ConsoleWriter
+import org.apache.spark.sql.execution.streaming.sources.{ConsoleContinuousWriter, ConsoleMicroBatchWriter, ConsoleWriter}
 import org.apache.spark.sql.sources.{BaseRelation, CreatableRelationProvider, DataSourceRegister}
 import org.apache.spark.sql.sources.v2.{DataSourceV2, DataSourceV2Options}
-import org.apache.spark.sql.sources.v2.streaming.MicroBatchWriteSupport
+import org.apache.spark.sql.sources.v2.streaming.{ContinuousWriteSupport, MicroBatchWriteSupport}
+import org.apache.spark.sql.sources.v2.streaming.writer.ContinuousWriter
 import org.apache.spark.sql.sources.v2.writer.DataSourceV2Writer
 import org.apache.spark.sql.streaming.OutputMode
 import org.apache.spark.sql.types.StructType
@@ -37,16 +36,25 @@ case class ConsoleRelation(override val sqlContext: SQLContext, data: DataFrame)
 
 class ConsoleSinkProvider extends DataSourceV2
   with MicroBatchWriteSupport
+  with ContinuousWriteSupport
   with DataSourceRegister
   with CreatableRelationProvider {
 
   override def createMicroBatchWriter(
       queryId: String,
-      epochId: Long,
+      batchId: Long,
       schema: StructType,
       mode: OutputMode,
       options: DataSourceV2Options): Optional[DataSourceV2Writer] = {
-    Optional.of(new ConsoleWriter(epochId, schema, options))
+    Optional.of(new ConsoleMicroBatchWriter(batchId, schema, options))
+  }
+
+  override def createContinuousWriter(
+      queryId: String,
+      schema: StructType,
+      mode: OutputMode,
+      options: DataSourceV2Options): Optional[ContinuousWriter] = {
+    Optional.of(new ConsoleContinuousWriter(schema, options))
   }
 
   def createRelation(

sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/sources/ConsoleWriter.scala

@@ -20,45 +20,85 @@ package org.apache.spark.sql.execution.streaming.sources
 import org.apache.spark.internal.Logging
 import org.apache.spark.sql.{Row, SparkSession}
 import org.apache.spark.sql.sources.v2.DataSourceV2Options
+import org.apache.spark.sql.sources.v2.streaming.writer.ContinuousWriter
 import org.apache.spark.sql.sources.v2.writer.{DataSourceV2Writer, DataWriterFactory, WriterCommitMessage}
 import org.apache.spark.sql.types.StructType
 
-/**
- * A [[DataSourceV2Writer]] that collects results to the driver and prints them in the console.
- * Generated by [[org.apache.spark.sql.execution.streaming.ConsoleSinkProvider]].
- *
- * This sink should not be used for production, as it requires sending all rows to the driver
- * and does not support recovery.
- */
-class ConsoleWriter(batchId: Long, schema: StructType, options: DataSourceV2Options)
-    extends DataSourceV2Writer with Logging {
+/** Common methods used to create writes for the the console sink */
+trait ConsoleWriter extends Logging {
+
+  def options: DataSourceV2Options
+
   // Number of rows to display, by default 20 rows
-  private val numRowsToShow = options.getInt("numRows", 20)
+  protected val numRowsToShow = options.getInt("numRows", 20)
 
   // Truncate the displayed data if it is too long, by default it is true
-  private val isTruncated = options.getBoolean("truncate", true)
+  protected val isTruncated = options.getBoolean("truncate", true)
 
   assert(SparkSession.getActiveSession.isDefined)
-  private val spark = SparkSession.getActiveSession.get
+  protected val spark = SparkSession.getActiveSession.get
+
+  def createWriterFactory(): DataWriterFactory[Row] = PackedRowWriterFactory
 
-  override def createWriterFactory(): DataWriterFactory[Row] = PackedRowWriterFactory
+  def abort(messages: Array[WriterCommitMessage]): Unit = {}
 
-  override def commit(messages: Array[WriterCommitMessage]): Unit = synchronized {
-    val batch = messages.collect {
+  protected def printRows(
+      commitMessages: Array[WriterCommitMessage],
+      schema: StructType,
+      printMessage: String): Unit = {
+    val rows = commitMessages.collect {
       case PackedRowCommitMessage(rows) => rows
     }.flatten
 
     // scalastyle:off println
     println("-------------------------------------------")
-    println(s"Batch: $batchId")
+    println(printMessage)
     println("-------------------------------------------")
     // scalastyle:off println
-    spark.createDataFrame(
-      spark.sparkContext.parallelize(batch), schema)
+    spark
+      .createDataFrame(spark.sparkContext.parallelize(rows), schema)
       .show(numRowsToShow, isTruncated)
   }
+}
+
+
+/**
+ * A [[DataSourceV2Writer]] that collects results from a micro-batch query to the driver and
+ * prints them in the console. Created by
+ * [[org.apache.spark.sql.execution.streaming.ConsoleSinkProvider]].
+ *
+ * This sink should not be used for production, as it requires sending all rows to the driver
+ * and does not support recovery.
+ */
+class ConsoleMicroBatchWriter(batchId: Long, schema: StructType, val options: DataSourceV2Options)
+  extends DataSourceV2Writer with ConsoleWriter {
+
+  override def commit(messages: Array[WriterCommitMessage]): Unit = {
+    printRows(messages, schema, s"Batch: $batchId")
+  }
+
+  override def toString(): String = {
+    s"ConsoleMicroBatchWriter[numRows=$numRowsToShow, truncate=$isTruncated]"
+  }
+}
 
-  override def abort(messages: Array[WriterCommitMessage]): Unit = {}
 
-  override def toString(): String = s"ConsoleWriter[numRows=$numRowsToShow, truncate=$isTruncated]"
+/**
+ * A [[DataSourceV2Writer]] that collects results from a continuous query to the driver and
+ * prints them in the console. Created by
+ * [[org.apache.spark.sql.execution.streaming.ConsoleSinkProvider]].
+ *
+ * This sink should not be used for production, as it requires sending all rows to the driver
+ * and does not support recovery.
+ */
+class ConsoleContinuousWriter(schema: StructType, val options: DataSourceV2Options)
+  extends ContinuousWriter with ConsoleWriter {
+
+  override def commit(epochId: Long, messages: Array[WriterCommitMessage]): Unit = {
+    printRows(messages, schema, s"Continuous processing epoch $epochId")
+  }
+
+  override def toString(): String = {
+    s"ConsoleContinuousWriter[numRows=$numRowsToShow, truncate=$isTruncated]"
+  }
 }

sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ConsoleWriterSuite.scala

@@ -19,13 +19,15 @@ package org.apache.spark.sql.execution.streaming.sources
 
 import java.io.ByteArrayOutputStream
 
+import org.scalatest.time.SpanSugar._
+
 import org.apache.spark.sql.execution.streaming.MemoryStream
-import org.apache.spark.sql.streaming.StreamTest
+import org.apache.spark.sql.streaming.{StreamTest, Trigger}
 
 class ConsoleWriterSuite extends StreamTest {
   import testImplicits._
 
-  test("console") {
+  test("microbatch - default") {
     val input = MemoryStream[Int]
 
     val captured = new ByteArrayOutputStream()
@@ -77,7 +79,7 @@ class ConsoleWriterSuite extends StreamTest {
         |""".stripMargin)
   }
 
-  test("console with numRows") {
+  test("microbatch - with numRows") {
     val input = MemoryStream[Int]
 
     val captured = new ByteArrayOutputStream()
@@ -106,7 +108,7 @@ class ConsoleWriterSuite extends StreamTest {
         |""".stripMargin)
   }
 
-  test("console with truncation") {
+  test("microbatch - truncation") {
     val input = MemoryStream[String]
 
     val captured = new ByteArrayOutputStream()
@@ -132,4 +134,20 @@ class ConsoleWriterSuite extends StreamTest {
         |
         |""".stripMargin)
   }
+
+  test("continuous - default") {
+    val captured = new ByteArrayOutputStream()
+    Console.withOut(captured) {
+      val input = spark.readStream
+        .format("rate")
+        .option("numPartitions", "1")
+        .option("rowsPerSecond", "5")
+        .load()
+        .select('value)
+
+      val query = input.writeStream.format("console").trigger(Trigger.Continuous(200)).start()
+      assert(query.isActive)
+      query.stop()
+    }
+  }
 }