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

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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.
This commit is contained in:
Sivabalan Narayanan
2022-06-06 13:21:00 -04:00
committed by GitHub
parent 4f7ea8c79a
commit 4f6fc726d0
4 changed files with 63 additions and 1 deletions
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48
hudi-spark-datasource/hudi-spark2/src/test/java/org/apache/hudi/internal/TestHoodieBulkInsertDataInternalWriter.java
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@@ -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.