[HUDI-3497] Adding Datatable validator tool (#4902)
This commit is contained in:
Sivabalan Narayanan
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GitHub
GitHub
parent
257052a94d
commit
f7088a957c
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.hudi.utilities;
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import org.apache.hudi.common.fs.FSUtils;
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import org.apache.hudi.metadata.HoodieTableMetadata;
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import org.apache.hadoop.fs.Path;
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import java.io.IOException;
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import java.util.Arrays;
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import java.util.List;
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import java.util.stream.Collectors;
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public class HoodieDataTableUtils {
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/**
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* @return All hoodie files of the table from the file system.
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* @throws IOException upon errors.
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*/
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static List<Path> getBaseAndLogFilePathsFromFileSystem(HoodieTableMetadata tableMetadata, String basePath) throws IOException {
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List<String> allPartitionPaths = tableMetadata.getAllPartitionPaths()
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.stream().map(partitionPath ->
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FSUtils.getPartitionPath(basePath, partitionPath).toString())
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.collect(Collectors.toList());
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return tableMetadata.getAllFilesInPartitions(allPartitionPaths).values().stream()
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.map(fileStatuses ->
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Arrays.stream(fileStatuses).map(fileStatus -> fileStatus.getPath()).collect(Collectors.toList()))
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.flatMap(list -> list.stream())
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.collect(Collectors.toList());
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}
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}
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@@ -0,0 +1,396 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.hudi.utilities;
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import org.apache.hudi.async.HoodieAsyncService;
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import org.apache.hudi.client.common.HoodieSparkEngineContext;
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import org.apache.hudi.common.config.TypedProperties;
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import org.apache.hudi.common.fs.FSUtils;
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import org.apache.hudi.common.table.HoodieTableMetaClient;
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import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
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import org.apache.hudi.common.table.timeline.HoodieInstant;
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import org.apache.hudi.common.table.timeline.HoodieTimeline;
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import org.apache.hudi.common.util.Option;
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import org.apache.hudi.common.util.collection.Pair;
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import org.apache.hudi.exception.HoodieException;
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import org.apache.hudi.exception.HoodieValidationException;
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import org.apache.hudi.metadata.FileSystemBackedTableMetadata;
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import org.apache.hudi.metadata.HoodieTableMetadata;
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import org.apache.hudi.table.repair.RepairUtils;
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import com.beust.jcommander.JCommander;
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import com.beust.jcommander.Parameter;
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import org.apache.hadoop.fs.Path;
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import org.apache.log4j.LogManager;
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import org.apache.log4j.Logger;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.JavaSparkContext;
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import java.io.Serializable;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.HashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Objects;
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import java.util.Set;
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import java.util.concurrent.CompletableFuture;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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import java.util.stream.Collectors;
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import java.util.stream.Stream;
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/**
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* A validator with spark-submit to ensure there are no dangling data files in the data table.
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* No data files found for commits prior to active timeline.
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* No extra data files found for completed commits more than whats present in commit metadata.
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*
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* <p>
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* - Default : This validator will validate the data files only once.
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* <p>
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* Example command:
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* ```
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* spark-submit \
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* --class org.apache.hudi.utilities.HoodieDataTableValidator \
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* --packages org.apache.spark:spark-avro_2.11:2.4.4 \
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* --master spark://xxxx:7077 \
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* --driver-memory 1g \
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* --executor-memory 1g \
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* $HUDI_DIR/hudi/packaging/hudi-utilities-bundle/target/hudi-utilities-bundle_2.11-0.11.0-SNAPSHOT.jar \
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* --base-path basePath
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* ```
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*
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* <p>
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* Also You can set `--continuous` for long running this validator.
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* And use `--min-validate-interval-seconds` to control the validation frequency, default is 10 minutes.
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* <p>
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* Example command:
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* ```
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* spark-submit \
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* --class org.apache.hudi.utilities.HoodieDataTableValidator \
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* --packages org.apache.spark:spark-avro_2.11:2.4.4 \
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* --master spark://xxxx:7077 \
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* --driver-memory 1g \
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* --executor-memory 1g \
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* $HUDI_DIR/hudi/packaging/hudi-utilities-bundle/target/hudi-utilities-bundle_2.11-0.11.0-SNAPSHOT.jar \
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* --base-path basePath
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* --continuous \
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* --min-validate-interval-seconds 60
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* ```
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*/
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public class HoodieDataTableValidator implements Serializable {
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private static final Logger LOG = LogManager.getLogger(HoodieDataTableValidator.class);
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// Spark context
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private transient JavaSparkContext jsc;
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// config
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private Config cfg;
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// Properties with source, hoodie client, key generator etc.
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private TypedProperties props;
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private HoodieTableMetaClient metaClient;
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protected transient Option<AsyncDataTableValidateService> asyncDataTableValidateService;
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public HoodieDataTableValidator(HoodieTableMetaClient metaClient) {
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this.metaClient = metaClient;
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}
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public HoodieDataTableValidator(JavaSparkContext jsc, Config cfg) {
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this.jsc = jsc;
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this.cfg = cfg;
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this.props = cfg.propsFilePath == null
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? UtilHelpers.buildProperties(cfg.configs)
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: readConfigFromFileSystem(jsc, cfg);
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this.metaClient = HoodieTableMetaClient.builder()
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.setConf(jsc.hadoopConfiguration()).setBasePath(cfg.basePath)
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.setLoadActiveTimelineOnLoad(true)
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.build();
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this.asyncDataTableValidateService = cfg.continuous ? Option.of(new AsyncDataTableValidateService()) : Option.empty();
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}
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/**
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* Reads config from the file system.
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*
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* @param jsc {@link JavaSparkContext} instance.
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* @param cfg {@link Config} instance.
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* @return the {@link TypedProperties} instance.
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*/
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private TypedProperties readConfigFromFileSystem(JavaSparkContext jsc, Config cfg) {
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return UtilHelpers.readConfig(jsc.hadoopConfiguration(), new Path(cfg.propsFilePath), cfg.configs)
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.getProps(true);
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}
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public static class Config implements Serializable {
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@Parameter(names = {"--base-path", "-sp"}, description = "Base path for the table", required = true)
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public String basePath = null;
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@Parameter(names = {"--continuous"}, description = "Running MetadataTableValidator in continuous. "
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+ "Can use --min-validate-interval-seconds to control validation frequency", required = false)
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public boolean continuous = false;
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@Parameter(names = {"--min-validate-interval-seconds"},
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description = "the min validate interval of each validate when set --continuous, default is 10 minutes.")
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public Integer minValidateIntervalSeconds = 10 * 60;
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@Parameter(names = {"--parallelism", "-pl"}, description = "Parallelism for validation", required = false)
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public int parallelism = 200;
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@Parameter(names = {"--ignore-failed", "-ig"}, description = "Ignore data table validate failure and continue.", required = false)
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public boolean ignoreFailed = false;
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@Parameter(names = {"--assume-date-partitioning"}, description = "Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path."
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+ "This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually", required = false)
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public Boolean assumeDatePartitioning = false;
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@Parameter(names = {"--spark-master", "-ms"}, description = "Spark master", required = false)
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public String sparkMaster = null;
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@Parameter(names = {"--spark-memory", "-sm"}, description = "spark memory to use", required = false)
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public String sparkMemory = "1g";
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@Parameter(names = {"--props"}, description = "path to properties file on localfs or dfs, with configurations for "
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+ "hoodie client")
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public String propsFilePath = null;
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@Parameter(names = {"--hoodie-conf"}, description = "Any configuration that can be set in the properties file "
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+ "(using the CLI parameter \"--props\") can also be passed command line using this parameter. This can be repeated",
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splitter = IdentitySplitter.class)
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public List<String> configs = new ArrayList<>();
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@Parameter(names = {"--help", "-h"}, help = true)
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public Boolean help = false;
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@Override
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public String toString() {
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return "MetadataTableValidatorConfig {\n"
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+ " --base-path " + basePath + ", \n"
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+ " --continuous " + continuous + ", \n"
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+ " --ignore-failed " + ignoreFailed + ", \n"
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+ " --min-validate-interval-seconds " + minValidateIntervalSeconds + ", \n"
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+ " --parallelism " + parallelism + ", \n"
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+ " --spark-master " + sparkMaster + ", \n"
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+ " --spark-memory " + sparkMemory + ", \n"
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+ " --assumeDatePartitioning-memory " + assumeDatePartitioning + ", \n"
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+ " --props " + propsFilePath + ", \n"
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+ " --hoodie-conf " + configs
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+ "\n}";
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}
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@Override
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public boolean equals(Object o) {
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if (this == o) {
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return true;
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}
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if (o == null || getClass() != o.getClass()) {
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return false;
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}
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HoodieMetadataTableValidator.Config config = (HoodieMetadataTableValidator.Config) o;
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return basePath.equals(config.basePath)
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&& Objects.equals(continuous, config.continuous)
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&& Objects.equals(minValidateIntervalSeconds, config.minValidateIntervalSeconds)
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&& Objects.equals(parallelism, config.parallelism)
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&& Objects.equals(ignoreFailed, config.ignoreFailed)
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&& Objects.equals(sparkMaster, config.sparkMaster)
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&& Objects.equals(sparkMemory, config.sparkMemory)
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&& Objects.equals(assumeDatePartitioning, config.assumeDatePartitioning)
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&& Objects.equals(propsFilePath, config.propsFilePath)
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&& Objects.equals(configs, config.configs);
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}
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@Override
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public int hashCode() {
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return Objects.hash(basePath, continuous, minValidateIntervalSeconds, parallelism, ignoreFailed, sparkMaster, sparkMemory,
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assumeDatePartitioning, propsFilePath, configs, help);
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}
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}
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public static void main(String[] args) {
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final Config cfg = new Config();
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JCommander cmd = new JCommander(cfg, null, args);
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if (cfg.help || args.length == 0) {
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cmd.usage();
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System.exit(1);
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}
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SparkConf sparkConf = UtilHelpers.buildSparkConf("Hoodie-Data-Table-Validator", cfg.sparkMaster);
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sparkConf.set("spark.executor.memory", cfg.sparkMemory);
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JavaSparkContext jsc = new JavaSparkContext(sparkConf);
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HoodieDataTableValidator validator = new HoodieDataTableValidator(jsc, cfg);
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try {
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validator.run();
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} catch (Throwable throwable) {
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LOG.error("Fail to do hoodie Data table validation for " + validator.cfg, throwable);
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} finally {
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jsc.stop();
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}
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}
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public void run() {
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try {
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LOG.info(cfg);
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if (cfg.continuous) {
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LOG.info(" ****** do hoodie data table validation in CONTINUOUS mode ******");
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doHoodieDataTableValidationContinuous();
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} else {
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LOG.info(" ****** do hoodie data table validation once ******");
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doHoodieDataTableValidationOnce();
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}
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} catch (Exception e) {
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throw new HoodieException("Unable to do hoodie data table validation in " + cfg.basePath, e);
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} finally {
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if (asyncDataTableValidateService.isPresent()) {
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asyncDataTableValidateService.get().shutdown(true);
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}
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}
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}
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private void doHoodieDataTableValidationOnce() {
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try {
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doDataTableValidation();
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} catch (HoodieValidationException e) {
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LOG.error("Metadata table validation failed to HoodieValidationException", e);
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if (!cfg.ignoreFailed) {
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throw e;
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}
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}
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}
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private void doHoodieDataTableValidationContinuous() {
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asyncDataTableValidateService.ifPresent(service -> {
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service.start(null);
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try {
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service.waitForShutdown();
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} catch (Exception e) {
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throw new HoodieException(e.getMessage(), e);
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}
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});
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}
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public void doDataTableValidation() {
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boolean finalResult = true;
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metaClient.reloadActiveTimeline();
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String basePath = metaClient.getBasePath();
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HoodieSparkEngineContext engineContext = new HoodieSparkEngineContext(jsc);
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try {
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HoodieTableMetadata tableMetadata = new FileSystemBackedTableMetadata(
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engineContext, engineContext.getHadoopConf(), cfg.basePath, cfg.assumeDatePartitioning);
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List<Path> allDataFilePaths = HoodieDataTableUtils.getBaseAndLogFilePathsFromFileSystem(tableMetadata, cfg.basePath);
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// verify that no data files present with commit time < earliest commit in active timeline.
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if (metaClient.getActiveTimeline().firstInstant().isPresent()) {
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String earliestInstant = metaClient.getActiveTimeline().firstInstant().get().getTimestamp();
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List<Path> danglingFilePaths = allDataFilePaths.stream().filter(path -> {
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String instantTime = FSUtils.getCommitTime(path.getName());
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return HoodieTimeline.compareTimestamps(instantTime, HoodieTimeline.LESSER_THAN, earliestInstant);
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}).collect(Collectors.toList());
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if (!danglingFilePaths.isEmpty() && danglingFilePaths.size() > 0) {
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LOG.error("Data table validation failed due to dangling files count " + danglingFilePaths.size() + ", found before active timeline");
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danglingFilePaths.forEach(entry -> LOG.error("Dangling file: " + entry.toString()));
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finalResult = false;
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if (!cfg.ignoreFailed) {
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throw new HoodieValidationException("Data table validation failed due to dangling files " + danglingFilePaths.size());
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}
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}
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// Verify that for every completed commit in active timeline, there are no extra files found apart from what is present in
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// commit metadata.
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Map<String, List<String>> instantToFilesMap = RepairUtils.tagInstantsOfBaseAndLogFiles(
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metaClient.getBasePath(), allDataFilePaths);
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HoodieActiveTimeline activeTimeline = metaClient.getActiveTimeline();
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List<HoodieInstant> hoodieInstants = activeTimeline.filterCompletedInstants().getInstants().collect(Collectors.toList());
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List<String> danglingFiles = engineContext.flatMap(hoodieInstants, instant -> {
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Option<Set<String>> filesFromTimeline = RepairUtils.getBaseAndLogFilePathsFromTimeline(
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activeTimeline, instant);
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List<String> baseAndLogFilesFromFs = instantToFilesMap.containsKey(instant.getTimestamp()) ? instantToFilesMap.get(instant.getTimestamp())
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: Collections.emptyList();
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if (!baseAndLogFilesFromFs.isEmpty()) {
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Set<String> danglingInstantFiles = new HashSet<>(baseAndLogFilesFromFs);
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if (filesFromTimeline.isPresent()) {
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danglingInstantFiles.removeAll(filesFromTimeline.get());
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}
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return new ArrayList<>(danglingInstantFiles).stream();
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} else {
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return Stream.empty();
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}
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}, hoodieInstants.size()).stream().collect(Collectors.toList());
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if (!danglingFiles.isEmpty()) {
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LOG.error("Data table validation failed due to extra files found for completed commits " + danglingFiles.size());
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danglingFiles.forEach(entry -> LOG.error("Dangling file: " + entry.toString()));
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finalResult = false;
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if (!cfg.ignoreFailed) {
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throw new HoodieValidationException("Data table validation failed due to dangling files " + danglingFiles.size());
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}
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}
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}
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} catch (Exception e) {
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LOG.error("Data table validation failed due to " + e.getMessage(), e);
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if (!cfg.ignoreFailed) {
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throw new HoodieValidationException("Data table validation failed due to " + e.getMessage(), e);
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}
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}
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if (finalResult) {
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LOG.info("Data table validation succeeded.");
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} else {
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LOG.warn("Data table validation failed.");
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}
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}
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public class AsyncDataTableValidateService extends HoodieAsyncService {
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private final transient ExecutorService executor = Executors.newSingleThreadExecutor();
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@Override
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protected Pair<CompletableFuture, ExecutorService> startService() {
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return Pair.of(CompletableFuture.supplyAsync(() -> {
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while (true) {
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try {
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long start = System.currentTimeMillis();
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doDataTableValidation();
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long toSleepMs = cfg.minValidateIntervalSeconds * 1000 - (System.currentTimeMillis() - start);
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if (toSleepMs > 0) {
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LOG.info("Last validate ran less than min validate interval: " + cfg.minValidateIntervalSeconds + " s, sleep: "
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+ toSleepMs + " ms.");
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Thread.sleep(toSleepMs);
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}
|
||||
} catch (HoodieValidationException e) {
|
||||
LOG.error("Shutting down AsyncDataTableValidateService due to HoodieValidationException", e);
|
||||
if (!cfg.ignoreFailed) {
|
||||
throw e;
|
||||
}
|
||||
} catch (InterruptedException e) {
|
||||
// ignore InterruptedException here.
|
||||
}
|
||||
}
|
||||
}, executor), executor);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -48,7 +48,6 @@ import java.io.IOException;
|
||||
import java.io.Serializable;
|
||||
import java.security.SecureRandom;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Arrays;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.stream.Collectors;
|
||||
@@ -345,7 +344,7 @@ public class HoodieRepairTool {
|
||||
boolean doRepair(
|
||||
Option<String> startingInstantOption, Option<String> endingInstantOption, boolean isDryRun) throws IOException {
|
||||
// Scans all partitions to find base and log files in the base path
|
||||
List<Path> allFilesInPartitions = getBaseAndLogFilePathsFromFileSystem();
|
||||
List<Path> allFilesInPartitions = HoodieDataTableUtils.getBaseAndLogFilePathsFromFileSystem(tableMetadata, cfg.basePath);
|
||||
// Buckets the files based on instant time
|
||||
// instant time -> relative paths of base and log files to base path
|
||||
Map<String, List<String>> instantToFilesMap = RepairUtils.tagInstantsOfBaseAndLogFiles(
|
||||
@@ -388,22 +387,6 @@ public class HoodieRepairTool {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* @return All hoodie files of the table from the file system.
|
||||
* @throws IOException upon errors.
|
||||
*/
|
||||
List<Path> getBaseAndLogFilePathsFromFileSystem() throws IOException {
|
||||
List<String> allPartitionPaths = tableMetadata.getAllPartitionPaths()
|
||||
.stream().map(partitionPath ->
|
||||
FSUtils.getPartitionPath(cfg.basePath, partitionPath).toString())
|
||||
.collect(Collectors.toList());
|
||||
return tableMetadata.getAllFilesInPartitions(allPartitionPaths).values().stream()
|
||||
.map(fileStatuses ->
|
||||
Arrays.stream(fileStatuses).map(fileStatus -> fileStatus.getPath()).collect(Collectors.toList()))
|
||||
.flatMap(list -> list.stream())
|
||||
.collect(Collectors.toList());
|
||||
}
|
||||
|
||||
/**
|
||||
* Undoes repair for UNDO mode.
|
||||
*
|
||||
|
||||
Reference in New Issue
Block a user