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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2022/02/28 16:46:50 UTC
[GitHub] [hudi] nsivabalan commented on a change in pull request #4902: [HUDI-3497] Adding Datatable validator tool
nsivabalan commented on a change in pull request #4902:
URL: https://github.com/apache/hudi/pull/4902#discussion_r816066958
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File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/HoodieDataTableValidator.java
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+/*
+ * 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
+ * under the License.
+ */
+
+package org.apache.hudi.utilities;
+
+import org.apache.hudi.async.HoodieAsyncService;
+import org.apache.hudi.client.common.HoodieSparkEngineContext;
+import org.apache.hudi.common.config.HoodieMetadataConfig;
+import org.apache.hudi.common.config.TypedProperties;
+import org.apache.hudi.common.fs.FSUtils;
+import org.apache.hudi.common.model.FileSlice;
+import org.apache.hudi.common.model.HoodieBaseFile;
+import org.apache.hudi.common.model.HoodieFileGroup;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
+import org.apache.hudi.common.table.timeline.HoodieInstant;
+import org.apache.hudi.common.table.timeline.HoodieTimeline;
+import org.apache.hudi.common.table.view.FileSystemViewManager;
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.exception.HoodieValidationException;
+import org.apache.hudi.metadata.FileSystemBackedTableMetadata;
+import org.apache.hudi.metadata.HoodieTableMetadata;
+import org.apache.hudi.table.repair.RepairUtils;
+
+import com.beust.jcommander.JCommander;
+import com.beust.jcommander.Parameter;
+import org.apache.hadoop.fs.FileStatus;
+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.JavaSparkContext;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+import java.util.Set;
+import java.util.concurrent.CompletableFuture;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import java.util.stream.Collectors;
+import java.util.stream.Stream;
+
+/**
+ * A validator with spark-submit to ensure there are no dangling data files in the data table.
+ * No data files found for commits prior to active timeline.
+ * No extra data files found for completed commits more than whats present in commit metadata.
+ *
+ * <p>
+ * - Default : This validator will validate the data files only once.
+ * <p>
+ * Example command:
+ * ```
+ * spark-submit \
+ * --class org.apache.hudi.utilities.HoodieDataTableValidator \
+ * --packages org.apache.spark:spark-avro_2.11:2.4.4 \
+ * --master spark://xxxx:7077 \
+ * --driver-memory 1g \
+ * --executor-memory 1g \
+ * $HUDI_DIR/hudi/packaging/hudi-utilities-bundle/target/hudi-utilities-bundle_2.11-0.11.0-SNAPSHOT.jar \
+ * --base-path basePath
+ * ```
+ *
+ * <p>
+ * Also You can set `--continuous` for long running this validator.
+ * And use `--min-validate-interval-seconds` to control the validation frequency, default is 10 minutes.
+ * <p>
+ * Example command:
+ * ```
+ * spark-submit \
+ * --class org.apache.hudi.utilities.HoodieDataTableValidator \
+ * --packages org.apache.spark:spark-avro_2.11:2.4.4 \
+ * --master spark://xxxx:7077 \
+ * --driver-memory 1g \
+ * --executor-memory 1g \
+ * $HUDI_DIR/hudi/packaging/hudi-utilities-bundle/target/hudi-utilities-bundle_2.11-0.11.0-SNAPSHOT.jar \
+ * --base-path basePath
+ * --continuous \
+ * --min-validate-interval-seconds 60
+ * ```
+ */
+public class HoodieDataTableValidator implements Serializable {
+
+ private static final Logger LOG = LogManager.getLogger(HoodieDataTableValidator.class);
+
+ // Spark context
+ private transient JavaSparkContext jsc;
+ // config
+ private Config cfg;
+ // Properties with source, hoodie client, key generator etc.
+ private TypedProperties props;
+
+ private HoodieTableMetaClient metaClient;
+
+ protected transient Option<AsyncDataTableValidateService> asyncDataTableValidateService;
+
+ public HoodieDataTableValidator(HoodieTableMetaClient metaClient) {
+ this.metaClient = metaClient;
+ }
+
+ public HoodieDataTableValidator(JavaSparkContext jsc,Config cfg) {
+ this.jsc = jsc;
+ this.cfg = cfg;
+
+ this.props = cfg.propsFilePath == null
+ ? UtilHelpers.buildProperties(cfg.configs)
+ : readConfigFromFileSystem(jsc, cfg);
+
+ this.metaClient = HoodieTableMetaClient.builder()
+ .setConf(jsc.hadoopConfiguration()).setBasePath(cfg.basePath)
+ .setLoadActiveTimelineOnLoad(true)
+ .build();
+
+ this.asyncDataTableValidateService = cfg.continuous ? Option.of(new AsyncDataTableValidateService()) : Option.empty();
+ }
+
+ /**
+ * Reads config from the file system.
+ *
+ * @param jsc {@link JavaSparkContext} instance.
+ * @param cfg {@link Config} instance.
+ * @return the {@link TypedProperties} instance.
+ */
+ private TypedProperties readConfigFromFileSystem(JavaSparkContext jsc, Config cfg) {
+ return UtilHelpers.readConfig(jsc.hadoopConfiguration(), new Path(cfg.propsFilePath), cfg.configs)
+ .getProps(true);
+ }
+
+ public static class Config implements Serializable {
+ @Parameter(names = {"--base-path", "-sp"}, description = "Base path for the table", required = true)
+ public String basePath = null;
+
+ @Parameter(names = {"--continuous"}, description = "Running MetadataTableValidator in continuous. "
+ + "Can use --min-validate-interval-seconds to control validation frequency", required = false)
+ public boolean continuous = false;
+
+ @Parameter(names = {"--min-validate-interval-seconds"},
+ description = "the min validate interval of each validate when set --continuous, default is 10 minutes.")
+ public Integer minValidateIntervalSeconds = 10 * 60;
+
+ @Parameter(names = {"--parallelism", "-pl"}, description = "Parallelism for valuation", required = false)
+ public int parallelism = 200;
+
+ @Parameter(names = {"--ignore-failed", "-ig"}, description = "Ignore data table validate failure and continue.", required = false)
+ public boolean ignoreFailed = false;
+
+ @Parameter(names = {"--assume-date-partitioning"}, description = "Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path."
+ + "This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually", required = false)
+ public Boolean assumeDatePartitioning = false;
+
+ @Parameter(names = {"--spark-master", "-ms"}, description = "Spark master", required = false)
+ public String sparkMaster = null;
+
+ @Parameter(names = {"--spark-memory", "-sm"}, description = "spark memory to use", required = false)
+ public String sparkMemory = "1g";
+
+ @Parameter(names = {"--props"}, description = "path to properties file on localfs or dfs, with configurations for "
+ + "hoodie client")
+ public String propsFilePath = null;
+
+ @Parameter(names = {"--hoodie-conf"}, description = "Any configuration that can be set in the properties file "
+ + "(using the CLI parameter \"--props\") can also be passed command line using this parameter. This can be repeated",
+ splitter = IdentitySplitter.class)
+ public List<String> configs = new ArrayList<>();
+
+ @Parameter(names = {"--help", "-h"}, help = true)
+ public Boolean help = false;
+
+ @Override
+ public String toString() {
+ return "MetadataTableValidatorConfig {\n"
+ + " --base-path " + basePath + ", \n"
+ + " --continuous " + continuous + ", \n"
+ + " --ignore-failed " + ignoreFailed + ", \n"
+ + " --min-validate-interval-seconds " + minValidateIntervalSeconds + ", \n"
+ + " --parallelism " + parallelism + ", \n"
+ + " --spark-master " + sparkMaster + ", \n"
+ + " --spark-memory " + sparkMemory + ", \n"
+ + " --assumeDatePartitioning-memory " + assumeDatePartitioning + ", \n"
+ + " --props " + propsFilePath + ", \n"
+ + " --hoodie-conf " + configs
+ + "\n}";
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ }
+ if (o == null || getClass() != o.getClass()) {
+ return false;
+ }
+ HoodieMetadataTableValidator.Config config = (HoodieMetadataTableValidator.Config) o;
+ return basePath.equals(config.basePath)
+ && Objects.equals(continuous, config.continuous)
+ && Objects.equals(minValidateIntervalSeconds, config.minValidateIntervalSeconds)
+ && Objects.equals(parallelism, config.parallelism)
+ && Objects.equals(ignoreFailed, config.ignoreFailed)
+ && Objects.equals(sparkMaster, config.sparkMaster)
+ && Objects.equals(sparkMemory, config.sparkMemory)
+ && Objects.equals(assumeDatePartitioning, config.assumeDatePartitioning)
+ && Objects.equals(propsFilePath, config.propsFilePath)
+ && Objects.equals(configs, config.configs);
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(basePath, continuous, minValidateIntervalSeconds, parallelism, ignoreFailed, sparkMaster, sparkMemory,
+ assumeDatePartitioning, propsFilePath, configs, help);
+ }
+ }
+
+ public static void main(String[] args) {
+ final Config cfg = new Config();
+ JCommander cmd = new JCommander(cfg, null, args);
+
+ if (cfg.help || args.length == 0) {
+ cmd.usage();
+ System.exit(1);
+ }
+
+ SparkConf sparkConf = UtilHelpers.buildSparkConf("Hoodie-Data-Table-Validator", cfg.sparkMaster);
+ sparkConf.set("spark.executor.memory", cfg.sparkMemory);
+ JavaSparkContext jsc = new JavaSparkContext(sparkConf);
+
+ HoodieDataTableValidator validator = new HoodieDataTableValidator(jsc, cfg);
+
+ try {
+ validator.run();
+ } catch (Throwable throwable) {
+ LOG.error("Fail to do hoodie Data table validation for " + validator.cfg, throwable);
+ } finally {
+ jsc.stop();
+ }
+ }
+
+ public void run() {
+ try {
+ LOG.info(cfg);
+ if (cfg.continuous) {
+ LOG.info(" ****** do hoodie data table validation in CONTINUOUS mode ******");
+ doHoodieDataTableValidationContinuous();
+ } else {
+ LOG.info(" ****** do hoodie data table validation once ******");
+ doHoodieDataTableValidationOnce();
+ }
+ } catch (Exception e) {
+ throw new HoodieException("Unable to do hoodie data table validation in " + cfg.basePath, e);
+ } finally {
+
+ if (asyncDataTableValidateService.isPresent()) {
+ asyncDataTableValidateService.get().shutdown(true);
+ }
+ }
+ }
+
+ private void doHoodieDataTableValidationOnce() {
+ try {
+ doDataTableValidation();
+ } catch (HoodieValidationException e) {
+ LOG.error("Metadata table validation failed to HoodieValidationException", e);
+ if (!cfg.ignoreFailed) {
+ throw e;
+ }
+ }
+ }
+
+ private void doHoodieDataTableValidationContinuous() {
+ asyncDataTableValidateService.ifPresent(service -> {
+ service.start(null);
+ try {
+ service.waitForShutdown();
+ } catch (Exception e) {
+ throw new HoodieException(e.getMessage(), e);
+ }
+ });
+ }
+
+ public void doDataTableValidation() {
+ boolean finalResult = true;
+ metaClient.reloadActiveTimeline();
+ String basePath = metaClient.getBasePath();
+ HoodieSparkEngineContext engineContext = new HoodieSparkEngineContext(jsc);
+ try {
+ HoodieTableMetadata tableMetadata = new FileSystemBackedTableMetadata(
+ engineContext, engineContext.getHadoopConf(), cfg.basePath, cfg.assumeDatePartitioning);
+ List<Path> allDataFilePaths = HoodieDataTableUtils.getBaseAndLogFilePathsFromFileSystem(tableMetadata, cfg.basePath);
+ // verify that no data files present with commit time < earliest commit in active timeline.
+ if (metaClient.getActiveTimeline().firstInstant().isPresent()) {
+ String earliestInstant = metaClient.getActiveTimeline().firstInstant().get().getTimestamp();
+ List<Path> danglingFilePaths = allDataFilePaths.stream().filter(path -> {
+ String instantTime = FSUtils.getCommitTime(path.getName());
+ return HoodieTimeline.compareTimestamps(instantTime, HoodieTimeline.LESSER_THAN, earliestInstant);
+ }).collect(Collectors.toList());
+
+ if (!danglingFilePaths.isEmpty() && danglingFilePaths.size() > 0) {
+ LOG.error("Data table validation failed due to dangling files count " + danglingFilePaths.size() + ", found before active timeline");
+ danglingFilePaths.forEach(entry -> LOG.error("Dangling file: " + entry.toString()));
+ finalResult = false;
+ if (!cfg.ignoreFailed) {
+ throw new HoodieValidationException("Data table validation failed due to dangling files " + danglingFilePaths.size());
+ }
+ }
+
+ // Verify that for every completed commit in active timeline, there are no extra files found apart from what is present in
+ // commit metadata.
+ Map<String, List<String>> instantToFilesMap = RepairUtils.tagInstantsOfBaseAndLogFiles(
+ metaClient.getBasePath(), allDataFilePaths);
+ HoodieActiveTimeline activeTimeline = metaClient.getActiveTimeline();
+ List<HoodieInstant> hoodieInstants = activeTimeline.filterCompletedInstants().getInstants().collect(Collectors.toList());
+
+ List<String> danglingFiles = engineContext.flatMap(hoodieInstants, instant -> {
+ Option<Set<String>> filesFromTimeline = RepairUtils.getBaseAndLogFilePathsFromTimeline(
+ activeTimeline, instant);
+ List<String> baseAndLogFilesFromFs = instantToFilesMap.containsKey(instant.getTimestamp()) ? instantToFilesMap.get(instant.getTimestamp())
+ : Collections.emptyList();
+ if (!baseAndLogFilesFromFs.isEmpty()) {
+ Set<String> danglingInstantFiles = new HashSet<>(baseAndLogFilesFromFs);
+ if (filesFromTimeline.isPresent()) {
+ danglingInstantFiles.removeAll(filesFromTimeline.get());
+ }
+ return new ArrayList<>(danglingInstantFiles).stream();
+ } else {
+ return Stream.empty();
+ }
+ }, hoodieInstants.size()).stream().collect(Collectors.toList());
+
+ if (!danglingFiles.isEmpty()) {
+ LOG.error("Data table validation failed due to extra files found for completed commits " + danglingFiles.size());
+ danglingFiles.forEach(entry -> LOG.error("Dangling file: " + entry.toString()));
+ finalResult = false;
+ if (!cfg.ignoreFailed) {
Review comment:
yes, I am throwing HoodieValidationException. not sure I understand your feedback. I also want to catch any other exceptions in general and not just HoodieValidationException. hence I had to throw here and again catch in catch block and again throw if cfg.ignoreFailed is set to false.
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