[HUDI-1104] Adding support for UserDefinedPartitioners and SortModes to BulkInsert with Rows (#3149)

hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieInternalConfig.java

@@ -0,0 +1,42 @@
+/*
+ * 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.hudi.config;
+
+import org.apache.hudi.common.config.HoodieConfig;
+
+/**
+ * Configs/params used for internal purposes.
+ */
+public class HoodieInternalConfig extends HoodieConfig {
+
+  private static final long serialVersionUID = 0L;
+
+  public static final String BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED = "hoodie.bulkinsert.are.partitioner.records.sorted";
+  public static final Boolean DEFAULT_BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED = false;
+
+  /**
+   * Returns if partition records are sorted or not.
+   * @param propertyValue value for property BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED.
+   * @return the property value.
+   */
+  public static Boolean getBulkInsertIsPartitionRecordsSorted(String propertyValue) {
+    return propertyValue != null ? Boolean.parseBoolean(propertyValue) : DEFAULT_BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED;
+  }
+
+}

hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieWriteConfig.java

@@ -1578,7 +1578,6 @@ public class HoodieWriteConfig extends HoodieConfig {
           HoodieLockConfig.newBuilder().fromProperties(writeConfig.getProps()).build());
 
       writeConfig.setDefaultValue(TIMELINE_LAYOUT_VERSION, String.valueOf(TimelineLayoutVersion.CURR_VERSION));
-
     }
 
     private void validate() {

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/BulkInsertInternalPartitionerWithRowsFactory.java

@@ -0,0 +1,44 @@
+/*
+ * 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.hudi.execution.bulkinsert;
+
+import org.apache.hudi.table.BulkInsertPartitioner;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+
+/**
+ * A factory to generate built-in partitioner to repartition input Rows into at least
+ * expected number of output spark partitions for bulk insert operation.
+ */
+public abstract class BulkInsertInternalPartitionerWithRowsFactory {
+
+  public static BulkInsertPartitioner<Dataset<Row>> get(BulkInsertSortMode sortMode) {
+    switch (sortMode) {
+      case NONE:
+        return new NonSortPartitionerWithRows();
+      case GLOBAL_SORT:
+        return new GlobalSortPartitionerWithRows();
+      case PARTITION_SORT:
+        return new PartitionSortPartitionerWithRows();
+      default:
+        throw new UnsupportedOperationException("The bulk insert sort mode \"" + sortMode.name() + "\" is not supported.");
+    }
+  }
+}

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/GlobalSortPartitionerWithRows.java

@@ -0,0 +1,45 @@
+/*
+ * 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.hudi.execution.bulkinsert;
+
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.table.BulkInsertPartitioner;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.functions;
+
+/**
+ * A built-in partitioner that does global sorting for the input Rows across partitions after repartition for bulk insert operation, corresponding to the {@code BulkInsertSortMode.GLOBAL_SORT} mode.
+ */
+public class GlobalSortPartitionerWithRows implements BulkInsertPartitioner<Dataset<Row>> {
+
+  @Override
+  public Dataset<Row> repartitionRecords(Dataset<Row> rows, int outputSparkPartitions) {
+    // Now, sort the records and line them up nicely for loading.
+    // Let's use "partitionPath + key" as the sort key.
+    return rows.sort(functions.col(HoodieRecord.PARTITION_PATH_METADATA_FIELD), functions.col(HoodieRecord.RECORD_KEY_METADATA_FIELD))
+        .coalesce(outputSparkPartitions);
+  }
+
+  @Override
+  public boolean arePartitionRecordsSorted() {
+    return true;
+  }
+}

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/NonSortPartitionerWithRows.java

@@ -0,0 +1,42 @@
+/*
+ * 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.hudi.execution.bulkinsert;
+
+import org.apache.hudi.table.BulkInsertPartitioner;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+
+/**
+ * A built-in partitioner that only does coalesce for input Rows for bulk insert operation,
+ * corresponding to the {@code BulkInsertSortMode.NONE} mode.
+ *
+ */
+public class NonSortPartitionerWithRows implements BulkInsertPartitioner<Dataset<Row>> {
+
+  @Override
+  public Dataset<Row> repartitionRecords(Dataset<Row> rows, int outputSparkPartitions) {
+    return rows.coalesce(outputSparkPartitions);
+  }
+
+  @Override
+  public boolean arePartitionRecordsSorted() {
+    return false;
+  }
+}

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/execution/bulkinsert/PartitionSortPartitionerWithRows.java

@@ -0,0 +1,41 @@
+/*
+ * 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.hudi.execution.bulkinsert;
+
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.table.BulkInsertPartitioner;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+
+/**
+ * A built-in partitioner that does local sorting for each spark partitions after coalesce for bulk insert operation, corresponding to the {@code BulkInsertSortMode.PARTITION_SORT} mode.
+ */
+public class PartitionSortPartitionerWithRows implements BulkInsertPartitioner<Dataset<Row>> {
+
+  @Override
+  public Dataset<Row> repartitionRecords(Dataset<Row> rows, int outputSparkPartitions) {
+    return rows.coalesce(outputSparkPartitions).sortWithinPartitions(HoodieRecord.PARTITION_PATH_METADATA_FIELD, HoodieRecord.RECORD_KEY_METADATA_FIELD);
+  }
+
+  @Override
+  public boolean arePartitionRecordsSorted() {
+    return true;
+  }
+}

hudi-client/hudi-spark-client/src/test/java/org/apache/hudi/execution/bulkinsert/TestBulkInsertInternalPartitionerForRows.java

@@ -0,0 +1,139 @@
+/*
+ * 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.hudi.execution.bulkinsert;
+
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.testutils.HoodieTestDataGenerator;
+import org.apache.hudi.table.BulkInsertPartitioner;
+import org.apache.hudi.testutils.HoodieClientTestHarness;
+import org.apache.hudi.testutils.SparkDatasetTestUtils;
+
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Stream;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+/**
+ * Unit tests {@link BulkInsertPartitioner}s with Rows.
+ */
+public class TestBulkInsertInternalPartitionerForRows extends HoodieClientTestHarness {
+
+  @BeforeEach
+  public void setUp() throws Exception {
+    initSparkContexts("TestBulkInsertInternalPartitionerForRows");
+    initPath();
+    initFileSystem();
+  }
+
+  @AfterEach
+  public void tearDown() throws Exception {
+    cleanupResources();
+  }
+
+  private static Stream<Arguments> configParams() {
+    Object[][] data = new Object[][] {
+        {BulkInsertSortMode.GLOBAL_SORT, true, true},
+        {BulkInsertSortMode.PARTITION_SORT, false, true},
+        {BulkInsertSortMode.NONE, false, false}
+    };
+    return Stream.of(data).map(Arguments::of);
+  }
+
+  @ParameterizedTest(name = "[{index}] {0}")
+  @MethodSource("configParams")
+  public void testBulkInsertInternalPartitioner(BulkInsertSortMode sortMode,
+      boolean isGloballySorted, boolean isLocallySorted)
+      throws Exception {
+    Dataset<Row> records1 = generateTestRecords();
+    Dataset<Row> records2 = generateTestRecords();
+    testBulkInsertInternalPartitioner(BulkInsertInternalPartitionerWithRowsFactory.get(sortMode),
+        records1, isGloballySorted, isLocallySorted, generateExpectedPartitionNumRecords(records1));
+    testBulkInsertInternalPartitioner(BulkInsertInternalPartitionerWithRowsFactory.get(sortMode),
+        records2, isGloballySorted, isLocallySorted, generateExpectedPartitionNumRecords(records2));
+  }
+
+  private void testBulkInsertInternalPartitioner(BulkInsertPartitioner partitioner,
+      Dataset<Row> rows,
+      boolean isGloballySorted, boolean isLocallySorted,
+      Map<String, Long> expectedPartitionNumRecords) {
+    int numPartitions = 2;
+    Dataset<Row> actualRecords = (Dataset<Row>) partitioner.repartitionRecords(rows, numPartitions);
+    List<Row> collectedActualRecords = actualRecords.collectAsList();
+    if (isGloballySorted) {
+      // Verify global order
+      verifyRowsAscendingOrder(collectedActualRecords);
+    } else if (isLocallySorted) {
+      // Verify local order
+      actualRecords.mapPartitions((MapPartitionsFunction<Row, Object>) input -> {
+        List<Row> partitionRows = new ArrayList<>();
+        while (input.hasNext()) {
+          partitionRows.add(input.next());
+        }
+        verifyRowsAscendingOrder(partitionRows);
+        return Collections.emptyList().iterator();
+      }, SparkDatasetTestUtils.ENCODER);
+    }
+
+    // Verify number of records per partition path
+    Map<String, Long> actualPartitionNumRecords = new HashMap<>();
+    for (Row record : collectedActualRecords) {
+      String partitionPath = record.getAs(HoodieRecord.PARTITION_PATH_METADATA_FIELD);
+      actualPartitionNumRecords.put(partitionPath,
+          actualPartitionNumRecords.getOrDefault(partitionPath, 0L) + 1);
+    }
+    assertEquals(expectedPartitionNumRecords, actualPartitionNumRecords);
+  }
+
+  public static Map<String, Long> generateExpectedPartitionNumRecords(Dataset<Row> rows) {
+    Dataset<Row> toReturn = rows.groupBy(HoodieRecord.PARTITION_PATH_METADATA_FIELD).count();
+    List<Row> result = toReturn.collectAsList();
+    Map<String, Long> returnMap = new HashMap<>();
+    for (Row row : result) {
+      returnMap.put(row.getAs(HoodieRecord.PARTITION_PATH_METADATA_FIELD), (Long) row.getAs("count"));
+    }
+    return returnMap;
+  }
+
+  public Dataset<Row> generateTestRecords() {
+    Dataset<Row> rowsPart1 = SparkDatasetTestUtils.getRandomRows(sqlContext, 100, HoodieTestDataGenerator.DEFAULT_FIRST_PARTITION_PATH, false);
+    Dataset<Row> rowsPart2 = SparkDatasetTestUtils.getRandomRows(sqlContext, 150, HoodieTestDataGenerator.DEFAULT_SECOND_PARTITION_PATH, false);
+    return rowsPart1.union(rowsPart2);
+  }
+
+  private void verifyRowsAscendingOrder(List<Row> records) {
+    List<Row> expectedRecords = new ArrayList<>(records);
+    Collections.sort(expectedRecords, Comparator.comparing(o -> (o.getAs(HoodieRecord.PARTITION_PATH_METADATA_FIELD) + "+" + o.getAs(HoodieRecord.RECORD_KEY_METADATA_FIELD))));
+    assertEquals(expectedRecords, records);
+  }
+
+}

hudi-spark-datasource/hudi-spark-common/src/main/java/org/apache/hudi/DataSourceUtils.java

@@ -49,6 +49,8 @@ import org.apache.log4j.LogManager;
 import org.apache.log4j.Logger;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
 
 import java.io.IOException;
 import java.util.ArrayList;
@@ -98,6 +100,25 @@ public class DataSourceUtils {
     }
   }
 
+  /**
+   * Create a UserDefinedBulkInsertPartitionerRows class via reflection,
+   * <br>
+   * if the class name of UserDefinedBulkInsertPartitioner is configured through the HoodieWriteConfig.
+   *
+   * @see HoodieWriteConfig#getUserDefinedBulkInsertPartitionerClass()
+   */
+  public static Option<BulkInsertPartitioner<Dataset<Row>>> createUserDefinedBulkInsertPartitionerWithRows(HoodieWriteConfig config)
+      throws HoodieException {
+    String bulkInsertPartitionerClass = config.getUserDefinedBulkInsertPartitionerClass();
+    try {
+      return StringUtils.isNullOrEmpty(bulkInsertPartitionerClass)
+          ? Option.empty() :
+          Option.of((BulkInsertPartitioner) ReflectionUtils.loadClass(bulkInsertPartitionerClass));
+    } catch (Throwable e) {
+      throw new HoodieException("Could not create UserDefinedBulkInsertPartitionerRows class " + bulkInsertPartitionerClass, e);
+    }
+  }
+
   /**
    * Create a payload class via reflection, passing in an ordering/precombine value.
    */

hudi-spark-datasource/hudi-spark-common/src/main/java/org/apache/hudi/internal/BulkInsertDataInternalWriterHelper.java

@@ -31,7 +31,9 @@ import org.apache.spark.sql.types.StructType;
 
 import java.io.IOException;
 import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 import java.util.UUID;
 
 /**
@@ -48,15 +50,17 @@ public class BulkInsertDataInternalWriterHelper {
   private final HoodieTable hoodieTable;
   private final HoodieWriteConfig writeConfig;
   private final StructType structType;
+  private final Boolean arePartitionRecordsSorted;
   private final List<HoodieInternalWriteStatus> writeStatusList = new ArrayList<>();
 
   private HoodieRowCreateHandle handle;
   private String lastKnownPartitionPath = null;
   private String fileIdPrefix;
   private int numFilesWritten = 0;
+  private Map<String, HoodieRowCreateHandle> handles = new HashMap<>();
 
   public BulkInsertDataInternalWriterHelper(HoodieTable hoodieTable, HoodieWriteConfig writeConfig,
-      String instantTime, int taskPartitionId, long taskId, long taskEpochId, StructType structType) {
+      String instantTime, int taskPartitionId, long taskId, long taskEpochId, StructType structType, boolean arePartitionRecordsSorted) {
     this.hoodieTable = hoodieTable;
     this.writeConfig = writeConfig;
     this.instantTime = instantTime;
@@ -64,6 +68,7 @@ public class BulkInsertDataInternalWriterHelper {
     this.taskId = taskId;
     this.taskEpochId = taskEpochId;
     this.structType = structType;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
     this.fileIdPrefix = UUID.randomUUID().toString();
   }
 
@@ -74,7 +79,7 @@ public class BulkInsertDataInternalWriterHelper {
 
       if ((lastKnownPartitionPath == null) || !lastKnownPartitionPath.equals(partitionPath) || !handle.canWrite()) {
         LOG.info("Creating new file for partition path " + partitionPath);
-        createNewHandle(partitionPath);
+        handle = getRowCreateHandle(partitionPath);
         lastKnownPartitionPath = partitionPath;
       }
       handle.write(record);
@@ -92,19 +97,30 @@ public class BulkInsertDataInternalWriterHelper {
   public void abort() {
   }
 
-  private void createNewHandle(String partitionPath) throws IOException {
+  private HoodieRowCreateHandle getRowCreateHandle(String partitionPath) throws IOException {
-    if (null != handle) {
+    if (!handles.containsKey(partitionPath)) { // if there is no handle corresponding to the partition path
-      close();
+      // if records are sorted, we can close all existing handles
+      if (arePartitionRecordsSorted) {
+        close();
+      }
+      handles.put(partitionPath, new HoodieRowCreateHandle(hoodieTable, writeConfig, partitionPath, getNextFileId(),
+          instantTime, taskPartitionId, taskId, taskEpochId, structType));
+    } else if (!handles.get(partitionPath).canWrite()) {
+      // even if there is a handle to the partition path, it could have reached its max size threshold. So, we close the handle here and
+      // create a new one.
+      writeStatusList.add(handles.remove(partitionPath).close());
+      handles.put(partitionPath, new HoodieRowCreateHandle(hoodieTable, writeConfig, partitionPath, getNextFileId(),
+          instantTime, taskPartitionId, taskId, taskEpochId, structType));
     }
-    handle = new HoodieRowCreateHandle(hoodieTable, writeConfig, partitionPath, getNextFileId(),
+    return handles.get(partitionPath);
-        instantTime, taskPartitionId, taskId, taskEpochId, structType);
   }
 
   public void close() throws IOException {
-    if (null != handle) {
+    for (HoodieRowCreateHandle rowCreateHandle: handles.values()) {
-      writeStatusList.add(handle.close());
+      writeStatusList.add(rowCreateHandle.close());
-      handle = null;
     }
+    handles.clear();
+    handle = null;
   }
 
   private String getNextFileId() {

hudi-spark-datasource/hudi-spark-common/src/test/java/org/apache/hudi/internal/HoodieBulkInsertInternalWriterTestBase.java

@@ -30,7 +30,9 @@ import org.apache.spark.sql.Row;
 import org.junit.jupiter.api.AfterEach;
 import org.junit.jupiter.api.BeforeEach;
 
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 import java.util.Random;
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
@@ -61,13 +63,40 @@ public class HoodieBulkInsertInternalWriterTestBase extends HoodieClientTestHarn
   }
 
   protected void assertWriteStatuses(List<HoodieInternalWriteStatus> writeStatuses, int batches, int size,
-      Option<List<String>> fileAbsPaths, Option<List<String>> fileNames) {
+                                     Option<List<String>> fileAbsPaths, Option<List<String>> fileNames) {
-    assertEquals(batches, writeStatuses.size());
+    assertWriteStatuses(writeStatuses, batches, size, false, fileAbsPaths, fileNames);
+  }
+
+  protected void assertWriteStatuses(List<HoodieInternalWriteStatus> writeStatuses, int batches, int size, boolean areRecordsSorted,
+                                     Option<List<String>> fileAbsPaths, Option<List<String>> fileNames) {
+    if (areRecordsSorted) {
+      assertEquals(batches, writeStatuses.size());
+    } else {
+      assertEquals(Math.min(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS.length, batches), writeStatuses.size());
+    }
+
+    Map<String, Long> sizeMap = new HashMap<>();
+    if (!areRecordsSorted) {
+      // <size> no of records are written per batch. Every 4th batch goes into same writeStatus. So, populating the size expected
+      // per write status
+      for (int i = 0; i < batches; i++) {
+        String partitionPath = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[i % 3];
+        if (!sizeMap.containsKey(partitionPath)) {
+          sizeMap.put(partitionPath, 0L);
+        }
+        sizeMap.put(partitionPath, sizeMap.get(partitionPath) + size);
+      }
+    }
+
     int counter = 0;
     for (HoodieInternalWriteStatus writeStatus : writeStatuses) {
       // verify write status
       assertEquals(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[counter % 3], writeStatus.getPartitionPath());
-      assertEquals(writeStatus.getTotalRecords(), size);
+      if (areRecordsSorted) {
+        assertEquals(writeStatus.getTotalRecords(), size);
+      } else {
+        assertEquals(writeStatus.getTotalRecords(), sizeMap.get(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[counter % 3]));
+      }
       assertNull(writeStatus.getGlobalError());
       assertEquals(writeStatus.getFailedRowsSize(), 0);
       assertEquals(writeStatus.getTotalErrorRecords(), 0);
@@ -82,8 +111,13 @@ public class HoodieBulkInsertInternalWriterTestBase extends HoodieClientTestHarn
             .substring(writeStatus.getStat().getPath().lastIndexOf('/') + 1));
       }
       HoodieWriteStat writeStat = writeStatus.getStat();
-      assertEquals(size, writeStat.getNumInserts());
+      if (areRecordsSorted) {
-      assertEquals(size, writeStat.getNumWrites());
+        assertEquals(size, writeStat.getNumInserts());
+        assertEquals(size, writeStat.getNumWrites());
+      } else {
+        assertEquals(sizeMap.get(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[counter % 3]), writeStat.getNumInserts());
+        assertEquals(sizeMap.get(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[counter % 3]), writeStat.getNumWrites());
+      }
       assertEquals(fileId, writeStat.getFileId());
       assertEquals(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[counter++ % 3], writeStat.getPartitionPath());
       assertEquals(0, writeStat.getNumDeletes());

hudi-spark-datasource/hudi-spark/src/main/java/org/apache/hudi/HoodieDatasetBulkInsertHelper.java

@@ -18,17 +18,12 @@
 
 package org.apache.hudi;
 
-import static org.apache.spark.sql.functions.callUDF;
-
-import java.util.Arrays;
-import java.util.List;
-import java.util.stream.Collectors;
-import java.util.stream.Stream;
 import org.apache.hudi.common.config.TypedProperties;
 import org.apache.hudi.common.model.HoodieRecord;
 import org.apache.hudi.common.util.ReflectionUtils;
 import org.apache.hudi.config.HoodieWriteConfig;
 import org.apache.hudi.keygen.BuiltinKeyGenerator;
+import org.apache.hudi.table.BulkInsertPartitioner;
 
 import org.apache.log4j.LogManager;
 import org.apache.log4j.Logger;
@@ -40,8 +35,16 @@ import org.apache.spark.sql.api.java.UDF1;
 import org.apache.spark.sql.functions;
 import org.apache.spark.sql.types.DataTypes;
 import org.apache.spark.sql.types.StructType;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.stream.Collectors;
+import java.util.stream.Stream;
+
 import scala.collection.JavaConverters;
 
+import static org.apache.spark.sql.functions.callUDF;
+
 /**
  * Helper class to assist in preparing {@link Dataset<Row>}s for bulk insert with datasource implementation.
  */
@@ -60,12 +63,13 @@ public class HoodieDatasetBulkInsertHelper {
    *  4. Sorts input dataset by hoodie partition path and record key
    *
    * @param sqlContext SQL Context
-   * @param config  Hoodie Write Config
+   * @param config Hoodie Write Config
-   * @param rows    Spark Input dataset
+   * @param rows Spark Input dataset
    * @return hoodie dataset which is ready for bulk insert.
    */
   public static Dataset<Row> prepareHoodieDatasetForBulkInsert(SQLContext sqlContext,
-      HoodieWriteConfig config, Dataset<Row> rows, String structName, String recordNamespace) {
+      HoodieWriteConfig config, Dataset<Row> rows, String structName, String recordNamespace,
+                                                               BulkInsertPartitioner<Dataset<Row>> bulkInsertPartitionerRows) {
     List<Column> originalFields =
         Arrays.stream(rows.schema().fields()).map(f -> new Column(f.name())).collect(Collectors.toList());
 
@@ -101,8 +105,6 @@ public class HoodieDatasetBulkInsertHelper {
     Dataset<Row> colOrderedDataset = rowDatasetWithHoodieColumns.select(
         JavaConverters.collectionAsScalaIterableConverter(orderedFields).asScala().toSeq());
 
-    return colOrderedDataset
+    return bulkInsertPartitionerRows.repartitionRecords(colOrderedDataset, config.getBulkInsertShuffleParallelism());
-        .sort(functions.col(HoodieRecord.PARTITION_PATH_METADATA_FIELD), functions.col(HoodieRecord.RECORD_KEY_METADATA_FIELD))
-        .coalesce(config.getBulkInsertShuffleParallelism());
   }
 }

hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala

@@ -19,7 +19,6 @@ package org.apache.hudi
 
 import java.util
 import java.util.Properties
-
 import org.apache.avro.generic.GenericRecord
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileSystem, Path}
@@ -34,13 +33,15 @@ import org.apache.hudi.common.table.{HoodieTableConfig, HoodieTableMetaClient}
 import org.apache.hudi.common.table.timeline.HoodieActiveTimeline
 import org.apache.hudi.common.util.{CommitUtils, ReflectionUtils}
 import org.apache.hudi.config.HoodieBootstrapConfig.{BOOTSTRAP_BASE_PATH_PROP, BOOTSTRAP_INDEX_CLASS_PROP}
-import org.apache.hudi.config.HoodieWriteConfig
+import org.apache.hudi.config.{HoodieInternalConfig, HoodieWriteConfig}
 import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.execution.bulkinsert.BulkInsertInternalPartitionerWithRowsFactory
 import org.apache.hudi.hive.util.ConfigUtils
 import org.apache.hudi.hive.{HiveSyncConfig, HiveSyncTool}
 import org.apache.hudi.internal.DataSourceInternalWriterHelper
 import org.apache.hudi.keygen.factory.HoodieSparkKeyGeneratorFactory
 import org.apache.hudi.sync.common.AbstractSyncTool
+import org.apache.hudi.table.BulkInsertPartitioner
 import org.apache.log4j.LogManager
 import org.apache.spark.SPARK_VERSION
 import org.apache.spark.SparkContext
@@ -50,7 +51,7 @@ import org.apache.spark.sql.hudi.HoodieSqlUtils
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.internal.StaticSQLConf.SCHEMA_STRING_LENGTH_THRESHOLD
 import org.apache.spark.sql.types.StructType
-import org.apache.spark.sql.{DataFrame, SQLContext, SaveMode, SparkSession}
+import org.apache.spark.sql.{DataFrame, Dataset, Row, SQLContext, SaveMode, SparkSession}
 
 import scala.collection.JavaConversions._
 import scala.collection.mutable.ListBuffer
@@ -335,7 +336,17 @@ object HoodieSparkSqlWriter {
     }
     val params = parameters.updated(HoodieWriteConfig.AVRO_SCHEMA.key, schema.toString)
     val writeConfig = DataSourceUtils.createHoodieConfig(schema.toString, path.get, tblName, mapAsJavaMap(params))
-    val hoodieDF = HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, writeConfig, df, structName, nameSpace)
+    val userDefinedBulkInsertPartitionerOpt = DataSourceUtils.createUserDefinedBulkInsertPartitionerWithRows(writeConfig)
+    val bulkInsertPartitionerRows : BulkInsertPartitioner[Dataset[Row]] = if (userDefinedBulkInsertPartitionerOpt.isPresent)  {
+      userDefinedBulkInsertPartitionerOpt.get
+    }
+    else {
+      BulkInsertInternalPartitionerWithRowsFactory.get(writeConfig.getBulkInsertSortMode)
+    }
+    val arePartitionRecordsSorted = bulkInsertPartitionerRows.arePartitionRecordsSorted();
+    parameters.updated(HoodieInternalConfig.BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED, arePartitionRecordsSorted.toString)
+    val hoodieDF = HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, writeConfig, df, structName, nameSpace,
+      bulkInsertPartitionerRows)
     if (SPARK_VERSION.startsWith("2.")) {
       hoodieDF.write.format("org.apache.hudi.internal")
         .option(DataSourceInternalWriterHelper.INSTANT_TIME_OPT_KEY, instantTime)

hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/TestDataSourceUtils.java

@@ -35,6 +35,8 @@ import org.apache.avro.generic.GenericData;
 import org.apache.avro.generic.GenericFixed;
 import org.apache.avro.generic.GenericRecord;
 import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.extension.ExtendWith;
@@ -162,6 +164,25 @@ public class TestDataSourceUtils {
     assertThat(optionCaptor.getValue().get(), is(instanceOf(NoOpBulkInsertPartitioner.class)));
   }
 
+  @Test
+  public void testCreateUserDefinedBulkInsertPartitionerRowsWithInValidPartitioner() throws HoodieException {
+    config = HoodieWriteConfig.newBuilder().withPath("/").withUserDefinedBulkInsertPartitionerClass("NonExistantUserDefinedClass").build();
+
+    Exception exception = assertThrows(HoodieException.class, () -> {
+      DataSourceUtils.createUserDefinedBulkInsertPartitionerWithRows(config);
+    });
+
+    assertThat(exception.getMessage(), containsString("Could not create UserDefinedBulkInsertPartitionerRows"));
+  }
+
+  @Test
+  public void testCreateUserDefinedBulkInsertPartitionerRowsWithValidPartitioner() throws HoodieException {
+    config = HoodieWriteConfig.newBuilder().withPath("/").withUserDefinedBulkInsertPartitionerClass(NoOpBulkInsertPartitionerRows.class.getName()).build();
+
+    Option<BulkInsertPartitioner<Dataset<Row>>> partitioner = DataSourceUtils.createUserDefinedBulkInsertPartitionerWithRows(config);
+    assertThat(partitioner.isPresent(), is(true));
+  }
+
   private void setAndVerifyHoodieWriteClientWith(final String partitionerClassName) {
     config = HoodieWriteConfig.newBuilder().withPath(config.getBasePath())
         .withUserDefinedBulkInsertPartitionerClass(partitionerClassName)
@@ -184,4 +205,18 @@ public class TestDataSourceUtils {
       return false;
     }
   }
+
+  public static class NoOpBulkInsertPartitionerRows
+      implements BulkInsertPartitioner<Dataset<Row>> {
+
+    @Override
+    public Dataset<Row> repartitionRecords(Dataset<Row> records, int outputSparkPartitions) {
+      return records;
+    }
+
+    @Override
+    public boolean arePartitionRecordsSorted() {
+      return false;
+    }
+  }
 }

hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/TestHoodieDatasetBulkInsertHelper.java

@@ -20,6 +20,7 @@ package org.apache.hudi;
 import org.apache.hudi.common.model.HoodieRecord;
 import org.apache.hudi.common.util.FileIOUtils;
 import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.execution.bulkinsert.NonSortPartitionerWithRows;
 import org.apache.hudi.testutils.DataSourceTestUtils;
 import org.apache.hudi.testutils.HoodieClientTestBase;
 
@@ -62,7 +63,8 @@ public class TestHoodieDatasetBulkInsertHelper extends HoodieClientTestBase {
     HoodieWriteConfig config = getConfigBuilder(schemaStr).withProps(getPropsAllSet()).build();
     List<Row> rows = DataSourceTestUtils.generateRandomRows(10);
     Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
-    Dataset<Row> result = HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace");
+    Dataset<Row> result = HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace",
+        new NonSortPartitionerWithRows());
     StructType resultSchema = result.schema();
 
     assertEquals(result.count(), 10);
@@ -117,7 +119,8 @@ public class TestHoodieDatasetBulkInsertHelper extends HoodieClientTestBase {
     List<Row> rows = DataSourceTestUtils.generateRandomRows(10);
     Dataset<Row> dataset = sqlContext.createDataFrame(rows, structType);
     try {
-      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace");
+      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName",
+          "testNamespace", new NonSortPartitionerWithRows());
       fail("Should have thrown exception");
     } catch (Exception e) {
       // ignore
@@ -127,7 +130,8 @@ public class TestHoodieDatasetBulkInsertHelper extends HoodieClientTestBase {
     rows = DataSourceTestUtils.generateRandomRows(10);
     dataset = sqlContext.createDataFrame(rows, structType);
     try {
-      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace");
+      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName",
+          "testNamespace", new NonSortPartitionerWithRows());
       fail("Should have thrown exception");
     } catch (Exception e) {
       // ignore
@@ -137,7 +141,8 @@ public class TestHoodieDatasetBulkInsertHelper extends HoodieClientTestBase {
     rows = DataSourceTestUtils.generateRandomRows(10);
     dataset = sqlContext.createDataFrame(rows, structType);
     try {
-      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace");
+      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName",
+          "testNamespace", new NonSortPartitionerWithRows());
       fail("Should have thrown exception");
     } catch (Exception e) {
       // ignore
@@ -147,7 +152,8 @@ public class TestHoodieDatasetBulkInsertHelper extends HoodieClientTestBase {
     rows = DataSourceTestUtils.generateRandomRows(10);
     dataset = sqlContext.createDataFrame(rows, structType);
     try {
-      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName", "testNamespace");
+      HoodieDatasetBulkInsertHelper.prepareHoodieDatasetForBulkInsert(sqlContext, config, dataset, "testStructName",
+          "testNamespace", new NonSortPartitionerWithRows());
       fail("Should have thrown exception");
     } catch (Exception e) {
       // ignore

hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/HoodieSparkSqlWriterSuite.scala

@@ -29,6 +29,7 @@ import org.apache.hudi.common.model.{HoodieRecord, HoodieRecordPayload}
 import org.apache.hudi.common.testutils.HoodieTestDataGenerator
 import org.apache.hudi.config.{HoodieBootstrapConfig, HoodieWriteConfig}
 import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.execution.bulkinsert.BulkInsertSortMode
 import org.apache.hudi.keygen.{NonpartitionedKeyGenerator, SimpleKeyGenerator}
 import org.apache.hudi.hive.HiveSyncConfig
 import org.apache.hudi.testutils.DataSourceTestUtils
@@ -119,9 +120,9 @@ class HoodieSparkSqlWriterSuite extends FunSuite with Matchers {
     }
   }
 
-  List(DataSourceWriteOptions.COW_TABLE_TYPE_OPT_VAL, DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL)
+  List(BulkInsertSortMode.GLOBAL_SORT.name(), BulkInsertSortMode.NONE.name(), BulkInsertSortMode.PARTITION_SORT.name())
-    .foreach(tableType => {
+    .foreach(sortMode => {
-      test("test bulk insert dataset with datasource impl for " + tableType) {
+      test("test_bulk_insert_for_" + sortMode) {
         initSparkContext("test_bulk_insert_datasource")
         val path = java.nio.file.Files.createTempDirectory("hoodie_test_path")
         try {
@@ -131,7 +132,7 @@ class HoodieSparkSqlWriterSuite extends FunSuite with Matchers {
           //create a new table
           val fooTableModifier = Map("path" -> path.toAbsolutePath.toString,
             HoodieWriteConfig.TABLE_NAME.key -> hoodieFooTableName,
-            DataSourceWriteOptions.TABLE_TYPE_OPT_KEY.key -> tableType,
+            DataSourceWriteOptions.TABLE_TYPE_OPT_KEY.key -> DataSourceWriteOptions.COW_TABLE_TYPE_OPT_VAL,
             "hoodie.bulkinsert.shuffle.parallelism" -> "4",
             DataSourceWriteOptions.OPERATION_OPT_KEY.key -> DataSourceWriteOptions.BULK_INSERT_OPERATION_OPT_VAL,
             DataSourceWriteOptions.ENABLE_ROW_WRITER_OPT_KEY.key -> "true",
@@ -143,7 +144,7 @@ class HoodieSparkSqlWriterSuite extends FunSuite with Matchers {
           // generate the inserts
           val schema = DataSourceTestUtils.getStructTypeExampleSchema
           val structType = AvroConversionUtils.convertAvroSchemaToStructType(schema)
-          val records = DataSourceTestUtils.generateRandomRows(100)
+          val records = DataSourceTestUtils.generateRandomRows(1000)
           val recordsSeq = convertRowListToSeq(records)
           val df = spark.createDataFrame(sc.parallelize(recordsSeq), structType)
           // write to Hudi

hudi-spark-datasource/hudi-spark2/pom.xml

@@ -253,6 +253,11 @@
       <artifactId>junit-jupiter-api</artifactId>
       <scope>test</scope>
     </dependency>
+    <dependency>
+      <groupId>org.junit.jupiter</groupId>
+      <artifactId>junit-jupiter-params</artifactId>
+      <scope>test</scope>
+    </dependency>
   </dependencies>
 
 </project>

hudi-spark-datasource/hudi-spark2/src/main/java/org/apache/hudi/internal/DefaultSource.java

@@ -19,6 +19,7 @@
 package org.apache.hudi.internal;
 
 import org.apache.hudi.DataSourceUtils;
+import org.apache.hudi.config.HoodieInternalConfig;
 import org.apache.hudi.config.HoodieWriteConfig;
 
 import org.apache.spark.sql.SaveMode;
@@ -62,7 +63,10 @@ public class DefaultSource extends BaseDefaultSource implements DataSourceV2,
     String tblName = options.get(HoodieWriteConfig.TABLE_NAME.key()).get();
     // 1st arg to createHooodieConfig is not really reuqired to be set. but passing it anyways.
     HoodieWriteConfig config = DataSourceUtils.createHoodieConfig(options.get(HoodieWriteConfig.AVRO_SCHEMA.key()).get(), path, tblName, options.asMap());
+    boolean arePartitionRecordsSorted = HoodieInternalConfig.getBulkInsertIsPartitionRecordsSorted(
+        options.get(HoodieInternalConfig.BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED).isPresent()
+            ? options.get(HoodieInternalConfig.BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED).get() : null);
     return Optional.of(new HoodieDataSourceInternalWriter(instantTime, config, schema, getSparkSession(),
-            getConfiguration()));
+            getConfiguration(), arePartitionRecordsSorted));
   }
 }

hudi-spark-datasource/hudi-spark2/src/main/java/org/apache/hudi/internal/HoodieBulkInsertDataInternalWriter.java

@@ -37,9 +37,9 @@ public class HoodieBulkInsertDataInternalWriter implements DataWriter<InternalRo
 
   public HoodieBulkInsertDataInternalWriter(HoodieTable hoodieTable, HoodieWriteConfig writeConfig,
       String instantTime, int taskPartitionId, long taskId, long taskEpochId,
-      StructType structType) {
+      StructType structType, boolean arePartitionRecordsSorted) {
     this.bulkInsertWriterHelper = new BulkInsertDataInternalWriterHelper(hoodieTable,
-        writeConfig, instantTime, taskPartitionId, taskId, taskEpochId, structType);
+        writeConfig, instantTime, taskPartitionId, taskId, taskEpochId, structType, arePartitionRecordsSorted);
   }
 
   @Override

hudi-spark-datasource/hudi-spark2/src/main/java/org/apache/hudi/internal/HoodieBulkInsertDataInternalWriterFactory.java

@@ -35,18 +35,20 @@ public class HoodieBulkInsertDataInternalWriterFactory implements DataWriterFact
   private final HoodieTable hoodieTable;
   private final HoodieWriteConfig writeConfig;
   private final StructType structType;
+  private final boolean arePartitionRecordsSorted;
 
   public HoodieBulkInsertDataInternalWriterFactory(HoodieTable hoodieTable, HoodieWriteConfig writeConfig,
-                                                   String instantTime, StructType structType) {
+                                                   String instantTime, StructType structType, boolean arePartitionRecordsSorted) {
     this.hoodieTable = hoodieTable;
     this.writeConfig = writeConfig;
     this.instantTime = instantTime;
     this.structType = structType;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
   }
 
   @Override
   public DataWriter<InternalRow> createDataWriter(int partitionId, long taskId, long epochId) {
     return new HoodieBulkInsertDataInternalWriter(hoodieTable, writeConfig, instantTime, partitionId, taskId, epochId,
-            structType);
+            structType, arePartitionRecordsSorted);
   }
 }

hudi-spark-datasource/hudi-spark2/src/main/java/org/apache/hudi/internal/HoodieDataSourceInternalWriter.java

@@ -45,12 +45,14 @@ public class HoodieDataSourceInternalWriter implements DataSourceWriter {
   private final HoodieWriteConfig writeConfig;
   private final StructType structType;
   private final DataSourceInternalWriterHelper dataSourceInternalWriterHelper;
+  private final Boolean arePartitionRecordsSorted;
 
   public HoodieDataSourceInternalWriter(String instantTime, HoodieWriteConfig writeConfig, StructType structType,
-                                        SparkSession sparkSession, Configuration configuration) {
+                                        SparkSession sparkSession, Configuration configuration, boolean arePartitionRecordsSorted) {
     this.instantTime = instantTime;
     this.writeConfig = writeConfig;
     this.structType = structType;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
     this.dataSourceInternalWriterHelper = new DataSourceInternalWriterHelper(instantTime, writeConfig, structType,
         sparkSession, configuration);
   }
@@ -60,7 +62,7 @@ public class HoodieDataSourceInternalWriter implements DataSourceWriter {
     dataSourceInternalWriterHelper.createInflightCommit();
     if (WriteOperationType.BULK_INSERT == dataSourceInternalWriterHelper.getWriteOperationType()) {
       return new HoodieBulkInsertDataInternalWriterFactory(dataSourceInternalWriterHelper.getHoodieTable(),
-          writeConfig, instantTime, structType);
+          writeConfig, instantTime, structType, arePartitionRecordsSorted);
     } else {
       throw new IllegalArgumentException("Write Operation Type + " + dataSourceInternalWriterHelper.getWriteOperationType() + " not supported ");
     }

hudi-spark-datasource/hudi-spark2/src/test/java/org/apache/hudi/internal/TestHoodieBulkInsertDataInternalWriter.java

@@ -28,9 +28,13 @@ import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.catalyst.InternalRow;
 import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
 
 import java.util.ArrayList;
 import java.util.List;
+import java.util.stream.Stream;
 
 import static org.apache.hudi.testutils.SparkDatasetTestUtils.ENCODER;
 import static org.apache.hudi.testutils.SparkDatasetTestUtils.STRUCT_TYPE;
@@ -46,16 +50,26 @@ import static org.junit.jupiter.api.Assertions.fail;
 public class TestHoodieBulkInsertDataInternalWriter extends
     HoodieBulkInsertInternalWriterTestBase {
 
-  @Test
+  private static Stream<Arguments> configParams() {
-  public void testDataInternalWriter() throws Exception {
+    Object[][] data = new Object[][] {
+        {true},
+        {false}
+    };
+    return Stream.of(data).map(Arguments::of);
+  }
+
+  @ParameterizedTest
+  @MethodSource("configParams")
+  public void testDataInternalWriter(boolean sorted) throws Exception {
     // init config and table
     HoodieWriteConfig cfg = getConfigBuilder(basePath).build();
     HoodieTable table = HoodieSparkTable.create(cfg, context, metaClient);
     // execute N rounds
-    for (int i = 0; i < 5; i++) {
+    for (int i = 0; i < 3; i++) {
       String instantTime = "00" + i;
       // init writer
-      HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), RANDOM.nextLong(), STRUCT_TYPE);
+      HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), RANDOM.nextLong(), STRUCT_TYPE,
+          sorted);
 
       int size = 10 + RANDOM.nextInt(1000);
       // write N rows to partition1, N rows to partition2 and N rows to partition3 ... Each batch should create a new RowCreateHandle and a new file
@@ -78,7 +92,7 @@ public class TestHoodieBulkInsertDataInternalWriter extends
       Option<List<String>> fileNames = Option.of(new ArrayList<>());
 
       // verify write statuses
-      assertWriteStatuses(commitMetadata.getWriteStatuses(), batches, size, fileAbsPaths, fileNames);
+      assertWriteStatuses(commitMetadata.getWriteStatuses(), batches, size, sorted, fileAbsPaths, fileNames);
 
       // verify rows
       Dataset<Row> result = sqlContext.read().parquet(fileAbsPaths.get().toArray(new String[0]));
@@ -99,7 +113,8 @@ public class TestHoodieBulkInsertDataInternalWriter extends
     String partitionPath = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[0];
 
     String instantTime = "001";
-    HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), RANDOM.nextLong(), STRUCT_TYPE);
+    HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), RANDOM.nextLong(), STRUCT_TYPE,
+        false);
 
     int size = 10 + RANDOM.nextInt(100);
     int totalFailures = 5;
@@ -131,7 +146,7 @@ public class TestHoodieBulkInsertDataInternalWriter extends
     Option<List<String>> fileAbsPaths = Option.of(new ArrayList<>());
     Option<List<String>> fileNames = Option.of(new ArrayList<>());
     // verify write statuses
-    assertWriteStatuses(commitMetadata.getWriteStatuses(), 1, size / 2, fileAbsPaths, fileNames);
+    assertWriteStatuses(commitMetadata.getWriteStatuses(), 1, size / 2, false, fileAbsPaths, fileNames);
 
     // verify rows
     Dataset<Row> result = sqlContext.read().parquet(fileAbsPaths.get().toArray(new String[0]));

hudi-spark-datasource/hudi-spark2/src/test/java/org/apache/hudi/internal/TestHoodieDataSourceInternalWriter.java

@@ -52,7 +52,7 @@ public class TestHoodieDataSourceInternalWriter extends
     String instantTime = "001";
     // init writer
     HoodieDataSourceInternalWriter dataSourceInternalWriter =
-        new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
     DataWriter<InternalRow> writer = dataSourceInternalWriter.createWriterFactory().createDataWriter(0, RANDOM.nextLong(), RANDOM.nextLong());
 
     String[] partitionPaths = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS;
@@ -98,7 +98,7 @@ public class TestHoodieDataSourceInternalWriter extends
       String instantTime = "00" + i;
       // init writer
       HoodieDataSourceInternalWriter dataSourceInternalWriter =
-          new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+          new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
 
       List<HoodieWriterCommitMessage> commitMessages = new ArrayList<>();
       Dataset<Row> totalInputRows = null;
@@ -142,7 +142,7 @@ public class TestHoodieDataSourceInternalWriter extends
       String instantTime = "00" + i;
       // init writer
       HoodieDataSourceInternalWriter dataSourceInternalWriter =
-          new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+          new HoodieDataSourceInternalWriter(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
 
       List<HoodieWriterCommitMessage> commitMessages = new ArrayList<>();
       Dataset<Row> totalInputRows = null;
@@ -189,7 +189,7 @@ public class TestHoodieDataSourceInternalWriter extends
     String instantTime0 = "00" + 0;
     // init writer
     HoodieDataSourceInternalWriter dataSourceInternalWriter =
-        new HoodieDataSourceInternalWriter(instantTime0, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalWriter(instantTime0, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
     DataWriter<InternalRow> writer = dataSourceInternalWriter.createWriterFactory().createDataWriter(0, RANDOM.nextLong(), RANDOM.nextLong());
 
     List<String> partitionPaths = Arrays.asList(HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS);
@@ -227,7 +227,7 @@ public class TestHoodieDataSourceInternalWriter extends
     // 2nd batch. abort in the end
     String instantTime1 = "00" + 1;
     dataSourceInternalWriter =
-        new HoodieDataSourceInternalWriter(instantTime1, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalWriter(instantTime1, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
     writer = dataSourceInternalWriter.createWriterFactory().createDataWriter(1, RANDOM.nextLong(), RANDOM.nextLong());
 
     for (int j = 0; j < batches; j++) {

hudi-spark-datasource/hudi-spark3/pom.xml

@@ -226,6 +226,11 @@
       <artifactId>junit-jupiter-api</artifactId>
       <scope>test</scope>
     </dependency>
+    <dependency>
+      <groupId>org.junit.jupiter</groupId>
+      <artifactId>junit-jupiter-params</artifactId>
+      <scope>test</scope>
+    </dependency>
   </dependencies>
 
 </project> 

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/DefaultSource.java

@@ -19,6 +19,7 @@
 package org.apache.hudi.spark3.internal;
 
 import org.apache.hudi.DataSourceUtils;
+import org.apache.hudi.config.HoodieInternalConfig;
 import org.apache.hudi.config.HoodieWriteConfig;
 import org.apache.hudi.internal.BaseDefaultSource;
 import org.apache.hudi.internal.DataSourceInternalWriterHelper;
@@ -47,9 +48,11 @@ public class DefaultSource extends BaseDefaultSource implements TableProvider {
     String instantTime = properties.get(DataSourceInternalWriterHelper.INSTANT_TIME_OPT_KEY);
     String path = properties.get("path");
     String tblName = properties.get(HoodieWriteConfig.TABLE_NAME.key());
+    boolean arePartitionRecordsSorted = Boolean.parseBoolean(properties.getOrDefault(HoodieInternalConfig.BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED,
+        Boolean.toString(HoodieInternalConfig.DEFAULT_BULKINSERT_ARE_PARTITIONER_RECORDS_SORTED)));
     // 1st arg to createHooodieConfig is not really reuqired to be set. but passing it anyways.
     HoodieWriteConfig config = DataSourceUtils.createHoodieConfig(properties.get(HoodieWriteConfig.AVRO_SCHEMA.key()), path, tblName, properties);
     return new HoodieDataSourceInternalTable(instantTime, config, schema, getSparkSession(),
-        getConfiguration());
+        getConfiguration(), arePartitionRecordsSorted);
   }
 }

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/HoodieBulkInsertDataInternalWriter.java

@@ -37,9 +37,9 @@ public class HoodieBulkInsertDataInternalWriter implements DataWriter<InternalRo
   private final BulkInsertDataInternalWriterHelper bulkInsertWriterHelper;
 
   public HoodieBulkInsertDataInternalWriter(HoodieTable hoodieTable, HoodieWriteConfig writeConfig,
-      String instantTime, int taskPartitionId, long taskId, StructType structType) {
+      String instantTime, int taskPartitionId, long taskId, StructType structType, boolean arePartitionRecordsSorted) {
     this.bulkInsertWriterHelper = new BulkInsertDataInternalWriterHelper(hoodieTable,
-        writeConfig, instantTime, taskPartitionId, taskId, 0, structType);
+        writeConfig, instantTime, taskPartitionId, taskId, 0, structType, arePartitionRecordsSorted);
   }
 
   @Override

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/HoodieBulkInsertDataInternalWriterFactory.java

@@ -35,18 +35,20 @@ public class HoodieBulkInsertDataInternalWriterFactory implements DataWriterFact
   private final HoodieTable hoodieTable;
   private final HoodieWriteConfig writeConfig;
   private final StructType structType;
+  private final boolean arePartitionRecordsSorted;
 
   public HoodieBulkInsertDataInternalWriterFactory(HoodieTable hoodieTable, HoodieWriteConfig writeConfig,
-      String instantTime, StructType structType) {
+      String instantTime, StructType structType, boolean arePartitionRecordsSorted) {
     this.hoodieTable = hoodieTable;
     this.writeConfig = writeConfig;
     this.instantTime = instantTime;
     this.structType = structType;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
   }
 
   @Override
   public DataWriter<InternalRow> createWriter(int partitionId, long taskId) {
     return new HoodieBulkInsertDataInternalWriter(hoodieTable, writeConfig, instantTime, partitionId, taskId,
-        structType);
+        structType, arePartitionRecordsSorted);
   }
 }

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/HoodieDataSourceInternalBatchWrite.java

@@ -45,13 +45,15 @@ public class HoodieDataSourceInternalBatchWrite implements BatchWrite {
   private final String instantTime;
   private final HoodieWriteConfig writeConfig;
   private final StructType structType;
+  private final boolean arePartitionRecordsSorted;
   private final DataSourceInternalWriterHelper dataSourceInternalWriterHelper;
 
   public HoodieDataSourceInternalBatchWrite(String instantTime, HoodieWriteConfig writeConfig, StructType structType,
-      SparkSession jss, Configuration hadoopConfiguration) {
+      SparkSession jss, Configuration hadoopConfiguration, boolean arePartitionRecordsSorted) {
     this.instantTime = instantTime;
     this.writeConfig = writeConfig;
     this.structType = structType;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
     this.dataSourceInternalWriterHelper = new DataSourceInternalWriterHelper(instantTime, writeConfig, structType,
         jss, hadoopConfiguration);
   }
@@ -61,7 +63,7 @@ public class HoodieDataSourceInternalBatchWrite implements BatchWrite {
     dataSourceInternalWriterHelper.createInflightCommit();
     if (WriteOperationType.BULK_INSERT == dataSourceInternalWriterHelper.getWriteOperationType()) {
       return new HoodieBulkInsertDataInternalWriterFactory(dataSourceInternalWriterHelper.getHoodieTable(),
-          writeConfig, instantTime, structType);
+          writeConfig, instantTime, structType, arePartitionRecordsSorted);
     } else {
       throw new IllegalArgumentException("Write Operation Type + " + dataSourceInternalWriterHelper.getWriteOperationType() + " not supported ");
     }

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/HoodieDataSourceInternalBatchWriteBuilder.java

@@ -37,19 +37,21 @@ public class HoodieDataSourceInternalBatchWriteBuilder implements WriteBuilder {
   private final StructType structType;
   private final SparkSession jss;
   private final Configuration hadoopConfiguration;
+  private final boolean arePartitionRecordsSorted;
 
   public HoodieDataSourceInternalBatchWriteBuilder(String instantTime, HoodieWriteConfig writeConfig, StructType structType,
-      SparkSession jss, Configuration hadoopConfiguration) {
+      SparkSession jss, Configuration hadoopConfiguration, boolean arePartitionRecordsSorted) {
     this.instantTime = instantTime;
     this.writeConfig = writeConfig;
     this.structType = structType;
     this.jss = jss;
     this.hadoopConfiguration = hadoopConfiguration;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
   }
 
   @Override
   public BatchWrite buildForBatch() {
     return new HoodieDataSourceInternalBatchWrite(instantTime, writeConfig, structType, jss,
-        hadoopConfiguration);
+        hadoopConfiguration, arePartitionRecordsSorted);
   }
 }

hudi-spark-datasource/hudi-spark3/src/main/java/org/apache/hudi/spark3/internal/HoodieDataSourceInternalTable.java

@@ -41,14 +41,16 @@ class HoodieDataSourceInternalTable implements SupportsWrite {
   private final StructType structType;
   private final SparkSession jss;
   private final Configuration hadoopConfiguration;
+  private final boolean arePartitionRecordsSorted;
 
   public HoodieDataSourceInternalTable(String instantTime, HoodieWriteConfig config,
-      StructType schema, SparkSession jss, Configuration hadoopConfiguration) {
+      StructType schema, SparkSession jss, Configuration hadoopConfiguration, boolean arePartitionRecordsSorted) {
     this.instantTime = instantTime;
     this.writeConfig = config;
     this.structType = schema;
     this.jss = jss;
     this.hadoopConfiguration = hadoopConfiguration;
+    this.arePartitionRecordsSorted = arePartitionRecordsSorted;
   }
 
   @Override
@@ -73,6 +75,6 @@ class HoodieDataSourceInternalTable implements SupportsWrite {
   @Override
   public WriteBuilder newWriteBuilder(LogicalWriteInfo logicalWriteInfo) {
     return new HoodieDataSourceInternalBatchWriteBuilder(instantTime, writeConfig, structType, jss,
-        hadoopConfiguration);
+        hadoopConfiguration, arePartitionRecordsSorted);
   }
 }

hudi-spark-datasource/hudi-spark3/src/test/java/org/apache/hudi/spark3/internal/TestHoodieBulkInsertDataInternalWriter.java

@@ -29,9 +29,13 @@ import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.catalyst.InternalRow;
 import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
 
 import java.util.ArrayList;
 import java.util.List;
+import java.util.stream.Stream;
 
 import static org.apache.hudi.testutils.SparkDatasetTestUtils.ENCODER;
 import static org.apache.hudi.testutils.SparkDatasetTestUtils.STRUCT_TYPE;
@@ -47,8 +51,17 @@ import static org.junit.jupiter.api.Assertions.fail;
 public class TestHoodieBulkInsertDataInternalWriter extends
     HoodieBulkInsertInternalWriterTestBase {
 
-  @Test
+  private static Stream<Arguments> configParams() {
-  public void testDataInternalWriter() throws Exception {
+    Object[][] data = new Object[][] {
+        {true},
+        {false}
+    };
+    return Stream.of(data).map(Arguments::of);
+  }
+
+  @ParameterizedTest
+  @MethodSource("configParams")
+  public void testDataInternalWriter(boolean sorted) throws Exception {
     // init config and table
     HoodieWriteConfig cfg = getConfigBuilder(basePath).build();
     HoodieTable table = HoodieSparkTable.create(cfg, context, metaClient);
@@ -56,7 +69,8 @@ public class TestHoodieBulkInsertDataInternalWriter extends
     for (int i = 0; i < 5; i++) {
       String instantTime = "00" + i;
       // init writer
-      HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), STRUCT_TYPE);
+      HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), STRUCT_TYPE,
+          sorted);
 
       int size = 10 + RANDOM.nextInt(1000);
       // write N rows to partition1, N rows to partition2 and N rows to partition3 ... Each batch should create a new RowCreateHandle and a new file
@@ -79,7 +93,7 @@ public class TestHoodieBulkInsertDataInternalWriter extends
       Option<List<String>> fileNames = Option.of(new ArrayList<>());
 
       // verify write statuses
-      assertWriteStatuses(commitMetadata.getWriteStatuses(), batches, size, fileAbsPaths, fileNames);
+      assertWriteStatuses(commitMetadata.getWriteStatuses(), batches, size, sorted, fileAbsPaths, fileNames);
 
       // verify rows
       Dataset<Row> result = sqlContext.read().parquet(fileAbsPaths.get().toArray(new String[0]));
@@ -100,7 +114,7 @@ public class TestHoodieBulkInsertDataInternalWriter extends
     String partitionPath = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[0];
 
     String instantTime = "001";
-    HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), STRUCT_TYPE);
+    HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), STRUCT_TYPE, false);
 
     int size = 10 + RANDOM.nextInt(100);
     int totalFailures = 5;

hudi-spark-datasource/hudi-spark3/src/test/java/org/apache/hudi/spark3/internal/TestHoodieDataSourceInternalBatchWrite.java

@@ -56,7 +56,7 @@ public class TestHoodieDataSourceInternalBatchWrite extends
     String instantTime = "001";
     // init writer
     HoodieDataSourceInternalBatchWrite dataSourceInternalBatchWrite =
-        new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
     DataWriter<InternalRow> writer = dataSourceInternalBatchWrite.createBatchWriterFactory(null).createWriter(0, RANDOM.nextLong());
 
     String[] partitionPaths = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS;
@@ -103,7 +103,7 @@ public class TestHoodieDataSourceInternalBatchWrite extends
       String instantTime = "00" + i;
       // init writer
       HoodieDataSourceInternalBatchWrite dataSourceInternalBatchWrite =
-          new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+          new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
 
       List<HoodieWriterCommitMessage> commitMessages = new ArrayList<>();
       Dataset<Row> totalInputRows = null;
@@ -148,7 +148,7 @@ public class TestHoodieDataSourceInternalBatchWrite extends
       String instantTime = "00" + i;
       // init writer
       HoodieDataSourceInternalBatchWrite dataSourceInternalBatchWrite =
-          new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+          new HoodieDataSourceInternalBatchWrite(instantTime, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
 
       List<HoodieWriterCommitMessage> commitMessages = new ArrayList<>();
       Dataset<Row> totalInputRows = null;
@@ -195,7 +195,7 @@ public class TestHoodieDataSourceInternalBatchWrite extends
     String instantTime0 = "00" + 0;
     // init writer
     HoodieDataSourceInternalBatchWrite dataSourceInternalBatchWrite =
-        new HoodieDataSourceInternalBatchWrite(instantTime0, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalBatchWrite(instantTime0, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
 
     DataWriter<InternalRow> writer = dataSourceInternalBatchWrite.createBatchWriterFactory(null).createWriter(0, RANDOM.nextLong());
 
@@ -234,7 +234,7 @@ public class TestHoodieDataSourceInternalBatchWrite extends
     // 2nd batch. abort in the end
     String instantTime1 = "00" + 1;
     dataSourceInternalBatchWrite =
-        new HoodieDataSourceInternalBatchWrite(instantTime1, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf);
+        new HoodieDataSourceInternalBatchWrite(instantTime1, cfg, STRUCT_TYPE, sqlContext.sparkSession(), hadoopConf, false);
     writer = dataSourceInternalBatchWrite.createBatchWriterFactory(null).createWriter(1, RANDOM.nextLong());
 
     for (int j = 0; j < batches; j++) {