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* Licensed to the Apache Software Foundation (ASF) under one
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* 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 under the License.
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package org.apache.hudi.examples.spark;
import org.apache.hudi.client.SparkRDDWriteClient;
import org.apache.hudi.client.WriteStatus;
import org.apache.hudi.client.common.HoodieSparkEngineContext;
import org.apache.hudi.common.fs.FSUtils;
import org.apache.hudi.common.model.HoodieAvroPayload;
import org.apache.hudi.common.model.HoodieKey;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.model.HoodieTableType;
import org.apache.hudi.common.table.HoodieTableMetaClient;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.config.HoodieCompactionConfig;
import org.apache.hudi.config.HoodieIndexConfig;
import org.apache.hudi.config.HoodieWriteConfig;
import org.apache.hudi.examples.common.HoodieExampleDataGenerator;
import org.apache.hudi.examples.common.HoodieExampleSparkUtils;
import org.apache.hudi.index.HoodieIndex;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.log4j.LogManager;
import org.apache.log4j.Logger;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;
/**
* Simple examples of #{@link SparkRDDWriteClient}.
*
* To run this example, you should
* <pre>
* 1. For running in IDE, set VM options `-Dspark.master=local[2]`;
* 2. For running in shell, using `spark-submit`.
*</pre>
*
* Usage: HoodieWriteClientExample <tablePath> <tableName>
* <tablePath> and <tableName> describe root path of hudi and table name
* for example, `HoodieWriteClientExample file:///tmp/hoodie/sample-table hoodie_rt`
*/
public class HoodieWriteClientExample {
private static final Logger LOG = LogManager.getLogger(HoodieWriteClientExample.class);
private static String tableType = HoodieTableType.COPY_ON_WRITE.name();
public static void main(String[] args) throws Exception {
if (args.length < 2) {
System.err.println("Usage: HoodieWriteClientExample <tablePath> <tableName>");
System.exit(1);
}
String tablePath = args[0];
String tableName = args[1];
SparkConf sparkConf = HoodieExampleSparkUtils.defaultSparkConf("hoodie-client-example");
try (JavaSparkContext jsc = new JavaSparkContext(sparkConf)) {
// Generator of some records to be loaded in.
HoodieExampleDataGenerator<HoodieAvroPayload> dataGen = new HoodieExampleDataGenerator<>();
// initialize the table, if not done already
Path path = new Path(tablePath);
FileSystem fs = FSUtils.getFs(tablePath, jsc.hadoopConfiguration());
if (!fs.exists(path)) {
HoodieTableMetaClient.initTableType(jsc.hadoopConfiguration(), tablePath, HoodieTableType.valueOf(tableType),
tableName, HoodieAvroPayload.class.getName());
}
// Create the write client to write some records in
HoodieWriteConfig cfg = HoodieWriteConfig.newBuilder().withPath(tablePath)
.withSchema(HoodieExampleDataGenerator.TRIP_EXAMPLE_SCHEMA).withParallelism(2, 2)
.withDeleteParallelism(2).forTable(tableName)
.withIndexConfig(HoodieIndexConfig.newBuilder().withIndexType(HoodieIndex.IndexType.BLOOM).build())
.withCompactionConfig(HoodieCompactionConfig.newBuilder().archiveCommitsWith(20, 30).build()).build();
SparkRDDWriteClient<HoodieAvroPayload> client = new SparkRDDWriteClient<>(new HoodieSparkEngineContext(jsc), cfg);
// inserts
String newCommitTime = client.startCommit();
LOG.info("Starting commit " + newCommitTime);
List<HoodieRecord<HoodieAvroPayload>> records = dataGen.generateInserts(newCommitTime, 10);
List<HoodieRecord<HoodieAvroPayload>> recordsSoFar = new ArrayList<>(records);
JavaRDD<HoodieRecord<HoodieAvroPayload>> writeRecords = jsc.parallelize(records, 1);
client.upsert(writeRecords, newCommitTime);
// updates
newCommitTime = client.startCommit();
LOG.info("Starting commit " + newCommitTime);
List<HoodieRecord<HoodieAvroPayload>> toBeUpdated = dataGen.generateUpdates(newCommitTime, 2);
records.addAll(toBeUpdated);
recordsSoFar.addAll(toBeUpdated);
writeRecords = jsc.parallelize(records, 1);
client.upsert(writeRecords, newCommitTime);
// Delete
newCommitTime = client.startCommit();
LOG.info("Starting commit " + newCommitTime);
// just delete half of the records
int numToDelete = recordsSoFar.size() / 2;
List<HoodieKey> toBeDeleted = recordsSoFar.stream().map(HoodieRecord::getKey).limit(numToDelete).collect(Collectors.toList());
JavaRDD<HoodieKey> deleteRecords = jsc.parallelize(toBeDeleted, 1);
client.delete(deleteRecords, newCommitTime);
// compaction
if (HoodieTableType.valueOf(tableType) == HoodieTableType.MERGE_ON_READ) {
Option<String> instant = client.scheduleCompaction(Option.empty());
JavaRDD<WriteStatus> writeStatues = client.compact(instant.get());
client.commitCompaction(instant.get(), writeStatues, Option.empty());
}
}
}
}