[SPARK-54663][CORE] Computes RowBasedChecksum in ShuffleWriters

core/src/main/java/org/apache/spark/shuffle/checksum/RowBasedChecksum.scala

@@ -0,0 +1,108 @@
+/*
+ * 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.shuffle.checksum
+
+import java.io.ObjectOutputStream
+import java.util.zip.Checksum
+
+import scala.util.control.NonFatal
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.network.shuffle.checksum.ShuffleChecksumHelper
+import org.apache.spark.util.ExposedBufferByteArrayOutputStream
+
+/**
+ * A class for computing checksum for input (key, value) pairs. The checksum is independent of
+ * the order of the input (key, value) pairs. It is done by computing a checksum for each row
+ * first, and then computing the XOR for all the row checksums.
+ */
+abstract class RowBasedChecksum() extends Serializable with Logging {
+  private var hasError: Boolean = false
+  private var checksumValue: Long = 0
+  /** Returns the checksum value computed. Tt returns the default checksum value (0) if there
+   * are any errors encountered during the checksum computation.
+   */
+  def getValue: Long = {
+    if (!hasError) checksumValue else 0
+  }
+
+  /** Updates the row-based checksum with the given (key, value) pair */
+  def update(key: Any, value: Any): Unit = {
+    if (!hasError) {
+      try {
+        val rowChecksumValue = calculateRowChecksum(key, value)
+        checksumValue = checksumValue ^ rowChecksumValue
+      } catch {
+        case NonFatal(e) =>
+          logError("Checksum computation encountered error: ", e)
+          hasError = true
+      }
+    }
+  }
+
+  /** Computes and returns the checksum value for the given (key, value) pair */
+  protected def calculateRowChecksum(key: Any, value: Any): Long
+}
+
+/**
+ * A Concrete implementation of RowBasedChecksum. The checksum for each row is
+ * computed by first converting the (key, value) pair to byte array using OutputStreams,
+ * and then computing the checksum for the byte array.
+ * Note that this checksum computation is very expensive, and it is used only in tests
+ * in the core component. A much cheaper implementation of RowBasedChecksum is in
+ * UnsafeRowChecksum.
+ *
+ * @param checksumAlgorithm the algorithm used for computing checksum.
+ */
+class OutputStreamRowBasedChecksum(checksumAlgorithm: String)
+  extends RowBasedChecksum() {
+
+  private val DEFAULT_INITIAL_SER_BUFFER_SIZE = 32 * 1024
+
+  @transient private lazy val serBuffer =
+    new ExposedBufferByteArrayOutputStream(DEFAULT_INITIAL_SER_BUFFER_SIZE)
+  @transient private lazy val objOut = new ObjectOutputStream(serBuffer)
+
+  @transient
+  protected lazy val checksum: Checksum =
+    ShuffleChecksumHelper.getChecksumByAlgorithm(checksumAlgorithm)
+
+  override protected def calculateRowChecksum(key: Any, value: Any): Long = {
+    assert(checksum != null, "Checksum is null")
+
+    // Converts the (key, value) pair into byte array.
+    objOut.reset()
+    serBuffer.reset()
+    objOut.writeObject((key, value))
+    objOut.flush()
+    serBuffer.flush()
+
+    // Computes and returns the checksum for the byte array.
+    checksum.reset()
+    checksum.update(serBuffer.getBuf, 0, serBuffer.size())
+    checksum.getValue
+  }
+}
+
+object RowBasedChecksum {
+  def getAggregatedChecksumValue(rowBasedChecksums: Array[RowBasedChecksum]): Long = {
+    Option(rowBasedChecksums)
+      .map(_.foldLeft(0L)((acc, c) => acc * 31L + c.getValue))
+      .getOrElse(0L)
+  }
+}

core/src/main/java/org/apache/spark/shuffle/sort/BypassMergeSortShuffleWriter.java

@@ -32,6 +32,7 @@
 import scala.Tuple2;
 import scala.collection.Iterator;
 
+import com.google.common.annotations.VisibleForTesting;
 import com.google.common.io.Closeables;
 
 import org.apache.spark.internal.SparkLogger;
@@ -53,6 +54,7 @@
 import org.apache.spark.scheduler.MapStatus$;
 import org.apache.spark.serializer.Serializer;
 import org.apache.spark.serializer.SerializerInstance;
+import org.apache.spark.shuffle.checksum.RowBasedChecksum;
 import org.apache.spark.shuffle.ShuffleWriteMetricsReporter;
 import org.apache.spark.shuffle.ShuffleWriter;
 import org.apache.spark.storage.*;
@@ -104,6 +106,13 @@ final class BypassMergeSortShuffleWriter<K, V>
   private long[] partitionLengths;
   /** Checksum calculator for each partition. Empty when shuffle checksum disabled. */
   private final Checksum[] partitionChecksums;
+  /**
+   * Checksum calculator for each partition. Different from the above Checksum,
+   * RowBasedChecksum is independent of the input row order, which is used to
+   * detect whether different task attempts of the same partition produce different
+   * output data or not.
+   */
+  private final RowBasedChecksum[] rowBasedChecksums;
 
   /**
    * Are we in the process of stopping? Because map tasks can call stop() with success = true
@@ -132,6 +141,7 @@ final class BypassMergeSortShuffleWriter<K, V>
     this.serializer = dep.serializer();
     this.shuffleExecutorComponents = shuffleExecutorComponents;
     this.partitionChecksums = createPartitionChecksums(numPartitions, conf);
+    this.rowBasedChecksums = dep.rowBasedChecksums();
   }
 
   @Override
@@ -144,7 +154,7 @@ public void write(Iterator<Product2<K, V>> records) throws IOException {
         partitionLengths = mapOutputWriter.commitAllPartitions(
           ShuffleChecksumHelper.EMPTY_CHECKSUM_VALUE).getPartitionLengths();
         mapStatus = MapStatus$.MODULE$.apply(
-          blockManager.shuffleServerId(), partitionLengths, mapId);
+          blockManager.shuffleServerId(), partitionLengths, mapId, getAggregatedChecksumValue());
         return;
       }
       final SerializerInstance serInstance = serializer.newInstance();
@@ -171,7 +181,11 @@ public void write(Iterator<Product2<K, V>> records) throws IOException {
       while (records.hasNext()) {
         final Product2<K, V> record = records.next();
         final K key = record._1();
-        partitionWriters[partitioner.getPartition(key)].write(key, record._2());
+        final int partitionId = partitioner.getPartition(key);
+        partitionWriters[partitionId].write(key, record._2());
+        if (rowBasedChecksums.length > 0) {
+          rowBasedChecksums[partitionId].update(key, record._2());
+        }
       }
 
       for (int i = 0; i < numPartitions; i++) {
@@ -182,7 +196,7 @@ public void write(Iterator<Product2<K, V>> records) throws IOException {
 
       partitionLengths = writePartitionedData(mapOutputWriter);
       mapStatus = MapStatus$.MODULE$.apply(
-        blockManager.shuffleServerId(), partitionLengths, mapId);
+        blockManager.shuffleServerId(), partitionLengths, mapId, getAggregatedChecksumValue());
     } catch (Exception e) {
       try {
         mapOutputWriter.abort(e);
@@ -199,6 +213,17 @@ public long[] getPartitionLengths() {
     return partitionLengths;
   }
 
+  // For test only.
+  @VisibleForTesting
+  RowBasedChecksum[] getRowBasedChecksums() {
+    return rowBasedChecksums;
+  }
+
+  @VisibleForTesting
+  long getAggregatedChecksumValue() {
+    return RowBasedChecksum.getAggregatedChecksumValue(rowBasedChecksums);
+  }
+
   /**
    * Concatenate all of the per-partition files into a single combined file.
    *

core/src/main/java/org/apache/spark/shuffle/sort/UnsafeShuffleWriter.java

@@ -59,9 +59,11 @@
 import org.apache.spark.shuffle.api.ShufflePartitionWriter;
 import org.apache.spark.shuffle.api.SingleSpillShuffleMapOutputWriter;
 import org.apache.spark.shuffle.api.WritableByteChannelWrapper;
+import org.apache.spark.shuffle.checksum.RowBasedChecksum;
 import org.apache.spark.storage.BlockManager;
 import org.apache.spark.storage.TimeTrackingOutputStream;
 import org.apache.spark.unsafe.Platform;
+import org.apache.spark.util.ExposedBufferByteArrayOutputStream;
 import org.apache.spark.util.Utils;
 
 @Private
@@ -93,15 +95,16 @@ public class UnsafeShuffleWriter<K, V> extends ShuffleWriter<K, V> {
   @Nullable private long[] partitionLengths;
   private long peakMemoryUsedBytes = 0;
 
-  /** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
-  private static final class MyByteArrayOutputStream extends ByteArrayOutputStream {
-    MyByteArrayOutputStream(int size) { super(size); }
-    public byte[] getBuf() { return buf; }
-  }
-
-  private MyByteArrayOutputStream serBuffer;
+  private ExposedBufferByteArrayOutputStream serBuffer;
   private SerializationStream serOutputStream;
 
+  /**
+   * RowBasedChecksum calculator for each partition. RowBasedChecksum is independent
+   * of the input row order, which is used to detect whether different task attempts
+   * of the same partition produce different output data or not.
+   */
+  private final RowBasedChecksum[] rowBasedChecksums;
+
   /**
    * Are we in the process of stopping? Because map tasks can call stop() with success = true
    * and then call stop() with success = false if they get an exception, we want to make sure
@@ -141,6 +144,7 @@ public UnsafeShuffleWriter(
       (int) (long) sparkConf.get(package$.MODULE$.SHUFFLE_SORT_INIT_BUFFER_SIZE());
     this.mergeBufferSizeInBytes =
       (int) (long) sparkConf.get(package$.MODULE$.SHUFFLE_FILE_MERGE_BUFFER_SIZE()) * 1024;
+    this.rowBasedChecksums = dep.rowBasedChecksums();
     open();
   }
 
@@ -162,6 +166,17 @@ public long getPeakMemoryUsedBytes() {
     return peakMemoryUsedBytes;
   }
 
+  // For test only.
+  @VisibleForTesting
+  RowBasedChecksum[] getRowBasedChecksums() {
+    return rowBasedChecksums;
+  }
+
+  @VisibleForTesting
+  long getAggregatedChecksumValue() {
+    return RowBasedChecksum.getAggregatedChecksumValue(rowBasedChecksums);
+  }
+
   /**
    * This convenience method should only be called in test code.
    */
@@ -210,7 +225,7 @@ private void open() throws SparkException {
       partitioner.numPartitions(),
       sparkConf,
       writeMetrics);
-    serBuffer = new MyByteArrayOutputStream(DEFAULT_INITIAL_SER_BUFFER_SIZE);
+    serBuffer = new ExposedBufferByteArrayOutputStream(DEFAULT_INITIAL_SER_BUFFER_SIZE);
     serOutputStream = serializer.serializeStream(serBuffer);
   }
 
@@ -233,7 +248,7 @@ void closeAndWriteOutput() throws IOException {
       }
     }
     mapStatus = MapStatus$.MODULE$.apply(
-      blockManager.shuffleServerId(), partitionLengths, mapId);
+      blockManager.shuffleServerId(), partitionLengths, mapId, getAggregatedChecksumValue());
   }
 
   @VisibleForTesting
@@ -251,6 +266,9 @@ void insertRecordIntoSorter(Product2<K, V> record) throws IOException {
 
     sorter.insertRecord(
       serBuffer.getBuf(), Platform.BYTE_ARRAY_OFFSET, serializedRecordSize, partitionId);
+    if (rowBasedChecksums.length > 0) {
+      rowBasedChecksums[partitionId].update(key, record._2());
+    }
   }
 
   @VisibleForTesting

core/src/main/java/org/apache/spark/util/ExposedBufferByteArrayOutputStream.java

@@ -0,0 +1,26 @@
+/*
+ * 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.util;
+
+import java.io.ByteArrayOutputStream;
+
+/** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
+public final class ExposedBufferByteArrayOutputStream extends ByteArrayOutputStream {
+    public ExposedBufferByteArrayOutputStream(int size) { super(size); }
+    public byte[] getBuf() { return buf; }
+}

core/src/main/scala/org/apache/spark/Dependency.scala

@@ -29,6 +29,7 @@ import org.apache.spark.internal.LogKeys._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.serializer.Serializer
 import org.apache.spark.shuffle.{ShuffleHandle, ShuffleWriteProcessor}
+import org.apache.spark.shuffle.checksum.RowBasedChecksum
 import org.apache.spark.storage.BlockManagerId
 import org.apache.spark.util.Utils
 
@@ -59,6 +60,9 @@ abstract class NarrowDependency[T](_rdd: RDD[T]) extends Dependency[T] {
   override def rdd: RDD[T] = _rdd
 }
 
+object ShuffleDependency {
+  private val EMPTY_ROW_BASED_CHECKSUMS: Array[RowBasedChecksum] = Array.empty
+}
 
 /**
  * :: DeveloperApi ::
@@ -74,6 +78,7 @@ abstract class NarrowDependency[T](_rdd: RDD[T]) extends Dependency[T] {
  * @param aggregator map/reduce-side aggregator for RDD's shuffle
  * @param mapSideCombine whether to perform partial aggregation (also known as map-side combine)
  * @param shuffleWriterProcessor the processor to control the write behavior in ShuffleMapTask
+ * @param rowBasedChecksums the row-based checksums for each shuffle partition
  */
 @DeveloperApi
 class ShuffleDependency[K: ClassTag, V: ClassTag, C: ClassTag](
@@ -83,9 +88,30 @@ class ShuffleDependency[K: ClassTag, V: ClassTag, C: ClassTag](
     val keyOrdering: Option[Ordering[K]] = None,
     val aggregator: Option[Aggregator[K, V, C]] = None,
     val mapSideCombine: Boolean = false,
-    val shuffleWriterProcessor: ShuffleWriteProcessor = new ShuffleWriteProcessor)
+    val shuffleWriterProcessor: ShuffleWriteProcessor = new ShuffleWriteProcessor,
+    val rowBasedChecksums: Array[RowBasedChecksum] = ShuffleDependency.EMPTY_ROW_BASED_CHECKSUMS)
   extends Dependency[Product2[K, V]] with Logging {
 
+  def this(
+      rdd: RDD[_ <: Product2[K, V]],
+      partitioner: Partitioner,
+      serializer: Serializer,
+      keyOrdering: Option[Ordering[K]],
+      aggregator: Option[Aggregator[K, V, C]],
+      mapSideCombine: Boolean,
+      shuffleWriterProcessor: ShuffleWriteProcessor) = {
+    this(
+      rdd,
+      partitioner,
+      serializer,
+      keyOrdering,
+      aggregator,
+      mapSideCombine,
+      shuffleWriterProcessor,
+      Array.empty
+    )
+  }
+
   if (mapSideCombine) {
     require(aggregator.isDefined, "Map-side combine without Aggregator specified!")
   }