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https://issues.apache.org/jira/browse/MAPREDUCE-7341?focusedWorklogId=624475&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-624475
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ASF GitHub Bot logged work on MAPREDUCE-7341:
---------------------------------------------
Author: ASF GitHub Bot
Created on: 19/Jul/21 16:26
Start Date: 19/Jul/21 16:26
Worklog Time Spent: 10m
Work Description: mukund-thakur commented on a change in pull request
#2971:
URL: https://github.com/apache/hadoop/pull/2971#discussion_r672449812
##########
File path:
hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/lib/output/committer/manifest/ManifestCommitterConfig.java
##########
@@ -0,0 +1,335 @@
+/*
+ * 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.hadoop.mapreduce.lib.output.committer.manifest;
+
+import java.io.IOException;
+import java.util.Objects;
+
+import org.apache.commons.lang3.tuple.Pair;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.fs.statistics.IOStatisticsSource;
+import org.apache.hadoop.fs.statistics.impl.IOStatisticsStore;
+import org.apache.hadoop.mapreduce.JobContext;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+import org.apache.hadoop.mapreduce.TaskAttemptID;
+import
org.apache.hadoop.thirdparty.com.google.common.annotations.VisibleForTesting;
+import
org.apache.hadoop.thirdparty.com.google.common.util.concurrent.ThreadFactoryBuilder;
+import org.apache.hadoop.util.Progressable;
+import org.apache.hadoop.util.concurrent.HadoopExecutors;
+
+import static
org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.SUCCESSFUL_JOB_OUTPUT_DIR_MARKER;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterConstants.DEFAULT_CREATE_SUCCESSFUL_JOB_DIR_MARKER;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterConstants.OPT_IO_PROCESSORS;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterConstants.OPT_IO_PROCESSORS_DEFAULT;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterConstants.OPT_VALIDATE_OUTPUT;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterConstants.OPT_VALIDATE_OUTPUT_DEFAULT;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterSupport.buildJobUUID;
+import static
org.apache.hadoop.mapreduce.lib.output.committer.manifest.ManifestCommitterSupport.getAppAttemptId;
+
+/**
+ * The configuration for the committer as built up from the job configuration
+ * and data passed down from the committer factory.
+ * Isolated for ease of dev/test
+ */
+final class ManifestCommitterConfig implements IOStatisticsSource {
+
+ /**
+ * Final destination of work.
+ * This is <i>unqualified</i>.
+ */
+ private final Path destinationDir;
+
+ /**
+ * Role: used in log/text messages.
+ */
+ private final String role;
+
+ /**
+ * This is the directory for all intermediate work: where the output
+ * format will write data.
+ */
+ private final Path taskAttemptDir;
+
+ /** Configuration of the job. */
+ private final Configuration conf;
+
+ /** The job context. For a task, this can be cast to a TaskContext. */
+ private final JobContext jobContext;
+
+ /** Should a job marker be created? */
+ private final boolean createJobMarker;
+
+ /**
+ * Job ID Or UUID -without any attempt suffix.
+ * This is expected/required to be unique, though
+ * Spark has had "issues" there until recently
+ * with lack of uniqueness of generated MR Job IDs.
+ */
+ private final String jobUniqueId;
+
+ /**
+ * Where did the job Unique ID come from?
+ */
+ private final String jobUniqueIdSource;
+
+ /**
+ * Number of this attempt; starts at zero.
+ */
+ private final int jobAttemptNumber;
+
+ /**
+ * Job ID + AttemptID.
+ */
+ private final String jobAttemptId;
+
+ /**
+ * Task ID: used as the filename of the manifest.
+ */
+ private final String taskId;
+
+ /**
+ * Task attempt ID. Determines the working
+ * directory for task attempts to write data into,
+ * and for the task committer to scan.
+ */
+ private final String taskAttemptId;
+
+ /** Any progressable for progress callbacks. */
+ private final Progressable progressable;
+
+ /**
+ * IOStatistics to update.
+ */
+ private final IOStatisticsStore iostatistics;
+
+ /** Should the output be validated after the commit? */
+ private final boolean validateOutput;
+
+ /**
+ * Attempt directory management.
+ */
+ private final ManifestCommitterSupport.AttemptDirectories dirs;
+
+ /**
+ * Callback when a stage is entered.
+ */
+ private final StageEventCallbacks stageEventCallbacks;
+
+ /**
+ * Constructor.
+ * @param outputPath destination path of the job.
+ * @param role role for log messages.
+ * @param context job/task context
+ * @param iostatistics IO Statistics
+ * @param stageEventCallbacks stage event callbacks.
+ */
+ ManifestCommitterConfig(
+ final Path outputPath,
+ final String role,
+ final JobContext context,
+ final IOStatisticsStore iostatistics,
+ final StageEventCallbacks stageEventCallbacks) {
+ this.role = role;
+ this.jobContext = context;
+ this.conf = context.getConfiguration();
+ this.destinationDir = outputPath;
+ this.iostatistics = iostatistics;
+ this.stageEventCallbacks = stageEventCallbacks;
+ this.createJobMarker = conf.getBoolean(
+ SUCCESSFUL_JOB_OUTPUT_DIR_MARKER,
+ DEFAULT_CREATE_SUCCESSFUL_JOB_DIR_MARKER);
+ this.validateOutput = conf.getBoolean(
+ OPT_VALIDATE_OUTPUT,
+ OPT_VALIDATE_OUTPUT_DEFAULT);
+ Pair<String, String> pair = buildJobUUID(conf, context.getJobID());
+ this.jobUniqueId = pair.getLeft();
+ this.jobUniqueIdSource = pair.getRight();
+ this.jobAttemptNumber = getAppAttemptId(context);
+ this.jobAttemptId = this.jobUniqueId + "_" + jobAttemptNumber;
+
+ // build directories
+ this.dirs = new ManifestCommitterSupport.AttemptDirectories(outputPath,
+ this.jobUniqueId, jobAttemptNumber);
+
+ // if constructed with a task attempt, build the task ID and path.
+ if (context instanceof TaskAttemptContext) {
+ // it's a task
+ final TaskAttemptContext tac = (TaskAttemptContext) context;
+ TaskAttemptID taskAttempt = Objects.requireNonNull(
+ tac.getTaskAttemptID());
+ taskAttemptId = taskAttempt.toString();
+ taskId = taskAttempt.getTaskID().toString();
+ // Task attempt dir; must be different across instances
+ taskAttemptDir = dirs.getTaskAttemptPath(taskAttemptId);
+ // the context is also the progress callback.
+ progressable = tac;
+
+ } else {
Review comment:
That will reduce the casting and null assignments.
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Issue Time Tracking
-------------------
Worklog Id: (was: 624475)
Time Spent: 8h 50m (was: 8h 40m)
> Add a task-manifest output committer for Azure and GCS
> ------------------------------------------------------
>
> Key: MAPREDUCE-7341
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-7341
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Components: client
> Affects Versions: 3.3.1
> Reporter: Steve Loughran
> Assignee: Steve Loughran
> Priority: Major
> Labels: pull-request-available
> Time Spent: 8h 50m
> Remaining Estimate: 0h
>
> Add a task-manifest output committer for Azure and GCS
> The S3A committers are very popular in Spark on S3, as they are both correct
> and fast.
> The classic FileOutputCommitter v1 and v2 algorithms are all that is
> available for Azure ABFS and Google GCS, and they have limitations.
> The v2 algorithm isn't safe in the presence of failed task attempt commits,
> so we
> recommend the v1 algorithm for Azure. But that is slow because it
> sequentially lists
> then renames files and directories, one-by-one. The latencies of list
> and rename make things slow.
> Google GCS lacks the atomic directory rename required for v1 correctness;
> v2 can be used (which doesn't have the job commit performance limitations),
> but it's not safe.
> Proposed
> * Add a new FileOutputFormat committer which uses an intermediate manifest to
> pass the list of files created by a TA to the job committer.
> * Job committer to parallelise reading these task manifests and submit all the
> rename operations into a pool of worker threads. (also: mkdir, directory
> deletions on cleanup)
> * Use the committer plugin mechanism added for s3a to make this the default
> committer for ABFS
> (i.e. no need to make any changes to FileOutputCommitter)
> * Add lots of IOStatistics instrumentation + logging of operations in the
> JobCommit
> for visibility of where delays are occurring.
> * Reuse the S3A committer _SUCCESS JSON structure to publish IOStats & other
> data
> for testing/support.
> This committer will be faster than the V1 algorithm because of the
> parallelisation, and
> because a manifest written by create-and-rename will be exclusive to a single
> task
> attempt, delivers the isolation which the v2 committer lacks.
> This is not an attempt to do an iceberg/hudi/delta-lake style manifest-only
> format
> for describing the contents of a table; the final output is still a directory
> tree
> which must be scanned during query planning.
> As such the format is still suboptimal for cloud storage -but at least we
> will have
> faster job execution during the commit phases.
>
> Note: this will also work on HDFS, where again, it should be faster than
> the v1 committer. However the target is very much Spark with ABFS and GCS; no
> plans to worry about MR as that simplifies the challenge of dealing with job
> restart (i.e. you don't have to)
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