org.apache.hudi.execution.bulkinsert.PartitionPathRepartitionPartitionerWithRows Maven / Gradle / Ivy
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package org.apache.hudi.execution.bulkinsert;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.config.HoodieWriteConfig;
import org.apache.hudi.exception.HoodieException;
import org.apache.hudi.table.BulkInsertPartitioner;
import org.apache.spark.sql.Column;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import static org.apache.hudi.execution.bulkinsert.BulkInsertSortMode.PARTITION_PATH_REPARTITION;
/**
* A built-in partitioner that does the following for input rows for bulk insert operation
*
* - For physically partitioned table, repartition the input rows based on the partition path,
* limiting the shuffle parallelism to specified `outputSparkPartitions`
*
* - For physically non-partitioned table, simply does coalesce for the input rows with
* `outputSparkPartitions`
*
* Corresponding to the {@code BulkInsertSortMode.PARTITION_PATH_REPARTITION} mode.
*/
public class PartitionPathRepartitionPartitionerWithRows implements BulkInsertPartitioner> {
private final boolean isTablePartitioned;
private final boolean shouldPopulateMetaFields;
public PartitionPathRepartitionPartitionerWithRows(boolean isTablePartitioned, HoodieWriteConfig config) {
this.isTablePartitioned = isTablePartitioned;
this.shouldPopulateMetaFields = config.populateMetaFields();
}
@Override
public Dataset repartitionRecords(Dataset rows, int outputSparkPartitions) {
if (!shouldPopulateMetaFields) {
throw new HoodieException(PARTITION_PATH_REPARTITION.name() + " mode requires meta-fields to be enabled");
}
if (isTablePartitioned) {
return rows.repartition(outputSparkPartitions, new Column(HoodieRecord.PARTITION_PATH_METADATA_FIELD));
}
return rows.coalesce(outputSparkPartitions);
}
@Override
public boolean arePartitionRecordsSorted() {
return false;
}
}