org.apache.hudi.utilities.sources.SqlSource Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package org.apache.hudi.utilities.sources;
import org.apache.hudi.common.config.TypedProperties;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.table.checkpoint.Checkpoint;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.common.util.collection.Pair;
import org.apache.hudi.utilities.config.SqlSourceConfig;
import org.apache.hudi.utilities.schema.SchemaProvider;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.Arrays;
import java.util.Collections;
import static org.apache.hudi.common.util.ConfigUtils.checkRequiredConfigProperties;
import static org.apache.hudi.common.util.ConfigUtils.getStringWithAltKeys;
/**
* SQL Source that reads from any table, used mainly for backfill jobs which will process specific partition dates.
*
* Spark SQL should be configured using this hoodie config:
*
*
hoodie.streamer.source.sql.sql.query = 'select * from source_table'
*
*
SQL Source is used for one time backfill scenarios, this won't update the deltastreamer.checkpoint.key to the
* processed commit, instead it will fetch the latest successful checkpoint key and set that value as this backfill
* commits checkpoint so that it won't interrupt the regular incremental processing.
*
*
To fetch and use the latest incremental checkpoint, you need to also set this hoodie_conf for deltastremer jobs:
*
*
hoodie.write.meta.key.prefixes = 'deltastreamer.checkpoint.key'
*
* Also, users are expected to set --allow-commit-on-no-checkpoint-change while using this SqlSource.
*/
public class SqlSource extends RowSource {
private static final long serialVersionUID = 1L;
private static final Logger LOG = LoggerFactory.getLogger(SqlSource.class);
private final String sourceSql;
private final SparkSession spark;
public SqlSource(
TypedProperties props,
JavaSparkContext sparkContext,
SparkSession sparkSession,
SchemaProvider schemaProvider) {
super(props, sparkContext, sparkSession, schemaProvider);
checkRequiredConfigProperties(
props, Collections.singletonList(SqlSourceConfig.SOURCE_SQL));
sourceSql = getStringWithAltKeys(props, SqlSourceConfig.SOURCE_SQL);
spark = sparkSession;
}
@Override
protected Pair>, Checkpoint> fetchNextBatch(
Option lastCheckpoint, long sourceLimit) {
LOG.debug(sourceSql);
Dataset source = spark.sql(sourceSql);
LOG.debug(source.showString(10, 0, true));
// Remove Hoodie meta columns except partition path from input source.
if (Arrays.asList(source.columns()).contains(HoodieRecord.COMMIT_TIME_METADATA_FIELD)) {
source =
source.drop(
HoodieRecord.HOODIE_META_COLUMNS.stream()
.filter(x -> !x.equals(HoodieRecord.PARTITION_PATH_METADATA_FIELD))
.toArray(String[]::new));
}
return Pair.of(Option.of(source), null);
}
}