mridulm commented on code in PR #50230:
URL: https://github.com/apache/spark/pull/50230#discussion_r2040084155


##########
core/src/main/java/org/apache/spark/shuffle/checksum/RowBasedChecksum.scala:
##########
@@ -0,0 +1,125 @@
+/*
+ * 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.{ByteArrayOutputStream, 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
+
+/**
+ * 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) =>
+          logInfo("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.
+ *
+ * @param checksumAlgorithm the algorithm used for computing checksum.
+ */
+class OutputStreamRowBasedChecksum(checksumAlgorithm: String)
+  extends RowBasedChecksum() {
+
+  /** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
+  final private class MyByteArrayOutputStream(size: Int)
+    extends ByteArrayOutputStream(size) {
+    def getBuf: Array[Byte] = buf
+  }

Review Comment:
   We have other case of `MyByteArrayOutputStream` for this purpose.
   Refactor to reuse it.



##########
core/src/main/java/org/apache/spark/shuffle/checksum/RowBasedChecksum.scala:
##########
@@ -0,0 +1,125 @@
+/*
+ * 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.{ByteArrayOutputStream, 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
+
+/**
+ * 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) =>
+          logInfo("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.
+ *
+ * @param checksumAlgorithm the algorithm used for computing checksum.
+ */
+class OutputStreamRowBasedChecksum(checksumAlgorithm: String)
+  extends RowBasedChecksum() {
+
+  /** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
+  final private class MyByteArrayOutputStream(size: Int)
+    extends ByteArrayOutputStream(size) {
+    def getBuf: Array[Byte] = buf
+  }
+
+  private val DEFAULT_INITIAL_SER_BUFFER_SIZE = 32 * 1024
+
+  @transient private lazy val serBuffer =
+    new MyByteArrayOutputStream(DEFAULT_INITIAL_SER_BUFFER_SIZE)
+  @transient private lazy val objOut = new ObjectOutputStream(serBuffer)

Review Comment:
   Discuss:
   When there are large rows, we are increasing the memory footprint for each 
`MyByteArrayOutputStream` for the duration of the task. Can we do better ?



##########
core/src/main/java/org/apache/spark/shuffle/sort/BypassMergeSortShuffleWriter.java:
##########
@@ -171,7 +182,11 @@ 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) {

Review Comment:
   We should consistently use either `null` to indicate checksum is disabled, 
or `length == 0`



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##########
@@ -5724,6 +5724,21 @@ object SQLConf {
       .booleanConf
       .createWithDefault(true)
 
+  val SHUFFLE_ORDER_INDEPENDENT_CHECKSUM_ENABLED =
+    buildConf("spark.shuffle.orderIndependentChecksum.enabled")
+      .doc("Whether to calculate order independent checksum for the shuffle 
data or not. If " +
+        "enabled, Spark will calculate a checksum that is independent of the 
input row order for " +
+        "each mapper and returns the checksums from executors to driver. 
Different from the above" +
+        "checksum, the order independent remains the same even if the shuffle 
row order changes. " +
+        "While the above checksum is sensitive to shuffle data ordering to 
detect file " +
+        "corruption. This checksum is used to detect whether different task 
attempts of the same " +
+        "partition produce different output data or not (same set of keyValue 
pairs). In case " +
+        "the output data has changed across retries, Spark will need to retry 
all tasks of the " +
+        "consumer stages to avoid correctness issues.")
+      .version("4.1.0")

Review Comment:
   The change proposed is not specific to SQL - make it a spark config instead ?



##########
core/src/main/java/org/apache/spark/shuffle/checksum/RowBasedChecksum.scala:
##########
@@ -0,0 +1,125 @@
+/*
+ * 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.{ByteArrayOutputStream, 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
+
+/**
+ * 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) =>
+          logInfo("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.
+ *
+ * @param checksumAlgorithm the algorithm used for computing checksum.
+ */
+class OutputStreamRowBasedChecksum(checksumAlgorithm: String)
+  extends RowBasedChecksum() {
+
+  /** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
+  final private class MyByteArrayOutputStream(size: Int)
+    extends ByteArrayOutputStream(size) {
+    def getBuf: Array[Byte] = buf
+  }
+
+  private val DEFAULT_INITIAL_SER_BUFFER_SIZE = 32 * 1024
+
+  @transient private lazy val serBuffer =
+    new MyByteArrayOutputStream(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 createPartitionRowBasedChecksums(
+      numPartitions: Int,
+      checksumAlgorithm: String): Array[RowBasedChecksum] = {
+    val rowBasedChecksums: Array[RowBasedChecksum] = new 
Array[RowBasedChecksum](numPartitions)
+    for (i <- 0 until numPartitions) {
+      rowBasedChecksums(i) = new 
OutputStreamRowBasedChecksum(checksumAlgorithm)
+    }
+    rowBasedChecksums

Review Comment:
   ```suggestion
       Array.tabulate(numPartitions)(_ => new 
OutputStreamRowBasedChecksum(checksumAlgorithm))
   ```



##########
core/src/main/java/org/apache/spark/shuffle/checksum/RowBasedChecksum.scala:
##########
@@ -0,0 +1,125 @@
+/*
+ * 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.{ByteArrayOutputStream, 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
+
+/**
+ * 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) =>
+          logInfo("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.
+ *
+ * @param checksumAlgorithm the algorithm used for computing checksum.
+ */
+class OutputStreamRowBasedChecksum(checksumAlgorithm: String)
+  extends RowBasedChecksum() {
+
+  /** Subclass of ByteArrayOutputStream that exposes `buf` directly. */
+  final private class MyByteArrayOutputStream(size: Int)
+    extends ByteArrayOutputStream(size) {
+    def getBuf: Array[Byte] = buf
+  }
+
+  private val DEFAULT_INITIAL_SER_BUFFER_SIZE = 32 * 1024
+
+  @transient private lazy val serBuffer =
+    new MyByteArrayOutputStream(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 createPartitionRowBasedChecksums(
+      numPartitions: Int,
+      checksumAlgorithm: String): Array[RowBasedChecksum] = {
+    val rowBasedChecksums: Array[RowBasedChecksum] = new 
Array[RowBasedChecksum](numPartitions)
+    for (i <- 0 until numPartitions) {
+      rowBasedChecksums(i) = new 
OutputStreamRowBasedChecksum(checksumAlgorithm)
+    }
+    rowBasedChecksums
+  }
+
+  def getAggregatedChecksumValue(rowBasedChecksums: Array[RowBasedChecksum]): 
Long = {
+    val numPartitions: Int = if (rowBasedChecksums != null) 
rowBasedChecksums.length else 0
+    var aggregatedChecksum: Long = 0
+    if (numPartitions > 0) {
+      for (i <- 0 until numPartitions) {
+        aggregatedChecksum = aggregatedChecksum * 31 + 
rowBasedChecksums(i).getValue
+      }
+    }
+    return aggregatedChecksum

Review Comment:
   ```suggestion
       Option(rowBasedChecksums).map { checksums =>
         checksums.fold(0L)(_ * 31L + _.getValue)
       }.getOrElse(0L)
   ```



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##########
@@ -5724,6 +5724,21 @@ object SQLConf {
       .booleanConf
       .createWithDefault(true)
 
+  val SHUFFLE_ORDER_INDEPENDENT_CHECKSUM_ENABLED =
+    buildConf("spark.shuffle.orderIndependentChecksum.enabled")
+      .doc("Whether to calculate order independent checksum for the shuffle 
data or not. If " +
+        "enabled, Spark will calculate a checksum that is independent of the 
input row order for " +
+        "each mapper and returns the checksums from executors to driver. 
Different from the above" +
+        "checksum, the order independent remains the same even if the shuffle 
row order changes. " +
+        "While the above checksum is sensitive to shuffle data ordering to 
detect file " +
+        "corruption. This checksum is used to detect whether different task 
attempts of the same " +
+        "partition produce different output data or not (same set of keyValue 
pairs). In case " +
+        "the output data has changed across retries, Spark will need to retry 
all tasks of the " +
+        "consumer stages to avoid correctness issues.")
+      .version("4.1.0")
+      .booleanConf
+      .createWithDefault(true)

Review Comment:
   default to `false`.



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##########
@@ -5724,6 +5724,21 @@ object SQLConf {
       .booleanConf
       .createWithDefault(true)
 
+  val SHUFFLE_ORDER_INDEPENDENT_CHECKSUM_ENABLED =
+    buildConf("spark.shuffle.orderIndependentChecksum.enabled")
+      .doc("Whether to calculate order independent checksum for the shuffle 
data or not. If " +
+        "enabled, Spark will calculate a checksum that is independent of the 
input row order for " +
+        "each mapper and returns the checksums from executors to driver. 
Different from the above" +
+        "checksum, the order independent remains the same even if the shuffle 
row order changes. " +
+        "While the above checksum is sensitive to shuffle data ordering to 
detect file " +
+        "corruption. This checksum is used to detect whether different task 
attempts of the same " +
+        "partition produce different output data or not (same set of keyValue 
pairs). In case " +
+        "the output data has changed across retries, Spark will need to retry 
all tasks of the " +
+        "consumer stages to avoid correctness issues.")
+      .version("4.1.0")

Review Comment:
   @cloud-fan, it is too late for 4.0 - let us move it to 4.1



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