[HUDI-4140] Fixing hive style partitioning and default partition with bulk insert row writer with SimpleKeyGen and virtual keys (#5664)

Bulk insert row writer code path had a gap wrt hive style partitioning and default partition when virtual keys are enabled with SimpleKeyGen.  This patch fixes the issue.

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

@@ -1064,6 +1064,10 @@ public class HoodieWriteConfig extends HoodieConfig {
     return MarkerType.valueOf(markerType.toUpperCase());
   }
 
+  public boolean isHiveStylePartitioningEnabled() {
+    return getBooleanOrDefault(KeyGeneratorOptions.HIVE_STYLE_PARTITIONING_ENABLE);
+  }
+
   public int getMarkersTimelineServerBasedBatchNumThreads() {
     return getInt(MARKERS_TIMELINE_SERVER_BASED_BATCH_NUM_THREADS);
   }

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

@@ -23,6 +23,7 @@ import org.apache.hudi.client.HoodieInternalWriteStatus;
 import org.apache.hudi.common.config.TypedProperties;
 import org.apache.hudi.common.model.HoodieRecord;
 import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.PartitionPathEncodeUtils;
 import org.apache.hudi.config.HoodieWriteConfig;
 import org.apache.hudi.exception.HoodieIOException;
 import org.apache.hudi.io.storage.row.HoodieRowCreateHandle;
@@ -128,7 +129,11 @@ public class BulkInsertDataInternalWriterHelper {
         if (!keyGeneratorOpt.isPresent()) { // NoPartitionerKeyGen
           partitionPath = "";
         } else if (simpleKeyGen) { // SimpleKeyGen
-          partitionPath = (record.get(simplePartitionFieldIndex, simplePartitionFieldDataType)).toString();
+          Object parititionPathValue = record.get(simplePartitionFieldIndex, simplePartitionFieldDataType);
+          partitionPath = parititionPathValue != null ? parititionPathValue.toString() : PartitionPathEncodeUtils.DEFAULT_PARTITION_PATH;
+          if (writeConfig.isHiveStylePartitioningEnabled()) {
+            partitionPath = (keyGeneratorOpt.get()).getPartitionPathFields().get(0) + "=" + partitionPath;
+          }
         } else {
           // only BuiltIn key generators are supported if meta fields are disabled.
           partitionPath = keyGeneratorOpt.get().getPartitionPath(record, structType);

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

@@ -70,6 +70,10 @@ public class HoodieBulkInsertInternalWriterTestBase extends HoodieClientTestHarn
   }
 
   protected HoodieWriteConfig getWriteConfig(boolean populateMetaFields) {
+    return getWriteConfig(populateMetaFields, DataSourceWriteOptions.HIVE_STYLE_PARTITIONING().defaultValue());
+  }
+
+  protected HoodieWriteConfig getWriteConfig(boolean populateMetaFields, String hiveStylePartitioningValue) {
     Properties properties = new Properties();
     if (!populateMetaFields) {
       properties.setProperty(DataSourceWriteOptions.KEYGENERATOR_CLASS_NAME().key(), SimpleKeyGenerator.class.getName());
@@ -77,6 +81,7 @@ public class HoodieBulkInsertInternalWriterTestBase extends HoodieClientTestHarn
       properties.setProperty(DataSourceWriteOptions.PARTITIONPATH_FIELD().key(), SparkDatasetTestUtils.PARTITION_PATH_FIELD_NAME);
       properties.setProperty(HoodieTableConfig.POPULATE_META_FIELDS.key(), "false");
     }
+    properties.setProperty(DataSourceWriteOptions.HIVE_STYLE_PARTITIONING().key(), hiveStylePartitioningValue);
     return getConfigBuilder(basePath, timelineServicePort).withProperties(properties).build();
   }
 

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

@@ -18,15 +18,18 @@
 
 package org.apache.hudi.internal;
 
+import org.apache.hudi.common.model.HoodieRecord;
 import org.apache.hudi.common.testutils.HoodieTestDataGenerator;
 import org.apache.hudi.common.util.Option;
 import org.apache.hudi.config.HoodieWriteConfig;
 import org.apache.hudi.table.HoodieSparkTable;
 import org.apache.hudi.table.HoodieTable;
+import org.apache.hudi.testutils.SparkDatasetTestUtils;
 
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.catalyst.InternalRow;
+import org.junit.jupiter.api.Assertions;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.params.ParameterizedTest;
 import org.junit.jupiter.params.provider.Arguments;
@@ -109,6 +112,51 @@ public class TestHoodieBulkInsertDataInternalWriter extends
     }
   }
 
+  @Test
+  public void testDataInternalWriterHiveStylePartitioning() throws Exception {
+    boolean sorted = true;
+    boolean populateMetaFields = false;
+    // init config and table
+    HoodieWriteConfig cfg = getWriteConfig(populateMetaFields, "true");
+    HoodieTable table = HoodieSparkTable.create(cfg, context, metaClient);
+    for (int i = 0; i < 1; i++) {
+      String instantTime = "00" + i;
+      // init writer
+      HoodieBulkInsertDataInternalWriter writer = new HoodieBulkInsertDataInternalWriter(table, cfg, instantTime, RANDOM.nextInt(100000), RANDOM.nextLong(), RANDOM.nextLong(),
+          STRUCT_TYPE, populateMetaFields, 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
+      int batches = 3;
+      Dataset<Row> totalInputRows = null;
+
+      for (int j = 0; j < batches; j++) {
+        String partitionPath = HoodieTestDataGenerator.DEFAULT_PARTITION_PATHS[j % 3];
+        Dataset<Row> inputRows = getRandomRows(sqlContext, size, partitionPath, false);
+        writeRows(inputRows, writer);
+        if (totalInputRows == null) {
+          totalInputRows = inputRows;
+        } else {
+          totalInputRows = totalInputRows.union(inputRows);
+        }
+      }
+
+      BaseWriterCommitMessage commitMetadata = (BaseWriterCommitMessage) writer.commit();
+      Option<List<String>> fileAbsPaths = Option.of(new ArrayList<>());
+      Option<List<String>> fileNames = Option.of(new ArrayList<>());
+
+      // verify write statuses
+      assertWriteStatuses(commitMetadata.getWriteStatuses(), batches, size, sorted, fileAbsPaths, fileNames);
+
+      // verify rows
+      Dataset<Row> result = sqlContext.read().parquet(fileAbsPaths.get().toArray(new String[0]));
+      assertOutput(totalInputRows, result, instantTime, fileNames, populateMetaFields);
+
+      result.collectAsList().forEach(entry -> Assertions.assertTrue(entry.getAs(HoodieRecord.PARTITION_PATH_METADATA_FIELD).toString()
+          .contains(SparkDatasetTestUtils.PARTITION_PATH_FIELD_NAME + "=")));
+    }
+  }
+
   /**
    * Issue some corrupted or wrong schematized InternalRow after few valid InternalRows so that global error is thrown. write batch 1 of valid records write batch2 of invalid records which is expected
    * to throw Global Error. Verify global error is set appropriately and only first batch of records are written to disk.