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A table format for huge analytic datasets
/*
* 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
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*/
package org.apache.iceberg.spark.actions;
import java.util.List;
import org.apache.iceberg.DistributionMode;
import org.apache.iceberg.FileScanTask;
import org.apache.iceberg.Table;
import org.apache.iceberg.spark.SparkReadOptions;
import org.apache.iceberg.spark.SparkWriteOptions;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
class SparkBinPackDataRewriter extends SparkSizeBasedDataRewriter {
SparkBinPackDataRewriter(SparkSession spark, Table table) {
super(spark, table);
}
@Override
public String description() {
return "BIN-PACK";
}
@Override
protected void doRewrite(String groupId, List group) {
// read the files packing them into splits of the required size
Dataset scanDF =
spark()
.read()
.format("iceberg")
.option(SparkReadOptions.SCAN_TASK_SET_ID, groupId)
.option(SparkReadOptions.SPLIT_SIZE, splitSize(inputSize(group)))
.option(SparkReadOptions.FILE_OPEN_COST, "0")
.load(groupId);
// write the packed data into new files where each split becomes a new file
scanDF
.write()
.format("iceberg")
.option(SparkWriteOptions.REWRITTEN_FILE_SCAN_TASK_SET_ID, groupId)
.option(SparkWriteOptions.TARGET_FILE_SIZE_BYTES, writeMaxFileSize())
.option(SparkWriteOptions.DISTRIBUTION_MODE, distributionMode(group).modeName())
.option(SparkWriteOptions.OUTPUT_SPEC_ID, outputSpecId())
.mode("append")
.save(groupId);
}
// invoke a shuffle if the original spec does not match the output spec
private DistributionMode distributionMode(List group) {
boolean requiresRepartition = !group.get(0).spec().equals(outputSpec());
return requiresRepartition ? DistributionMode.RANGE : DistributionMode.NONE;
}
}