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https://issues.apache.org/jira/browse/HUDI-1138?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17391378#comment-17391378
]
ASF GitHub Bot commented on HUDI-1138:
--------------------------------------
yihua commented on a change in pull request #3233:
URL: https://github.com/apache/hudi/pull/3233#discussion_r680693810
##########
File path:
hudi-timeline-service/src/main/java/org/apache/hudi/timeline/service/handlers/MarkerHandler.java
##########
@@ -0,0 +1,484 @@
+/*
+ * 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.timeline.service.handlers;
+
+import org.apache.hudi.common.config.SerializableConfiguration;
+import org.apache.hudi.common.engine.HoodieEngineContext;
+import org.apache.hudi.common.metrics.Registry;
+import org.apache.hudi.common.model.IOType;
+import org.apache.hudi.common.table.view.FileSystemViewManager;
+import org.apache.hudi.common.util.collection.ImmutablePair;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.exception.HoodieIOException;
+import org.apache.hudi.timeline.service.TimelineService;
+
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import io.javalin.Context;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FSDataInputStream;
+import org.apache.hadoop.fs.FSDataOutputStream;
+import org.apache.hadoop.fs.FileStatus;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.util.StringUtils;
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+
+import java.io.BufferedReader;
+import java.io.BufferedWriter;
+import java.io.Closeable;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.io.OutputStreamWriter;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import java.util.concurrent.CompletableFuture;
+import java.util.concurrent.Executors;
+import java.util.concurrent.ScheduledExecutorService;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
+import static org.apache.hudi.timeline.service.RequestHandler.jsonifyResult;
+
+/**
+ * REST Handler servicing marker requests.
+ *
+ * The marker creation requests are handled asynchronous, while other types of
requests
+ * are handled synchronous.
+ *
+ * Marker creation requests are batch processed periodically by a thread.
Each batch
+ * processing thread adds new markers to a marker file. Given that marker
file operation
+ * can take time, multiple concurrent threads can run at the same, while they
operate
+ * on different marker files storing mutually exclusive marker entries. At
any given
+ * time, a marker file is touched by at most one thread to guarantee
consistency.
+ * Below is an example of running batch processing threads.
+ *
+ * |-----| batch interval
+ * Thread 1 |-------------------------->| writing to MARKERS1
+ * Thread 2 |-------------------------->| writing to MARKERS2
+ * Thread 3 |-------------------------->| writing to MARKERS3
+ */
+public class MarkerHandler extends Handler {
+ public static final String MARKERS_FILENAME_PREFIX = "MARKERS";
+ private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
+ private static final Logger LOG = LogManager.getLogger(MarkerHandler.class);
+ // Margin time for scheduling the processing of the next batch of marker
creation requests
+ private static final long SCHEDULING_MARGIN_TIME_MS = 5L;
+
+ private final Registry metricsRegistry;
+ private final ScheduledExecutorService executorService;
+ // A cached copy of all markers in memory
+ // Mapping: {markerDirPath -> all markers}
+ private final Map<String, Set<String>> allMarkersMap = new HashMap<>();
+ // A cached copy of marker entries in each marker file, stored in
StringBuilder for efficient appending
+ // Mapping: {markerDirPath -> {markerFileIndex -> markers}}
+ private final Map<String, Map<Integer, StringBuilder>> fileMarkersMap = new
HashMap<>();
+ // A list of pending futures from async marker creation requests
+ private final List<CreateMarkerCompletableFuture> createMarkerFutures = new
ArrayList<>();
+ // A list of use status of marker files. {@code true} means the file is in
use by a {@code BatchCreateMarkerRunnable}
+ private final List<Boolean> markerFilesUseStatus;
Review comment:
Right. Fixed.
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> Re-implement marker files via timeline server
> ---------------------------------------------
>
> Key: HUDI-1138
> URL: https://issues.apache.org/jira/browse/HUDI-1138
> Project: Apache Hudi
> Issue Type: Improvement
> Components: Writer Core
> Affects Versions: 0.9.0
> Reporter: Vinoth Chandar
> Assignee: Ethan Guo
> Priority: Blocker
> Labels: pull-request-available
> Fix For: 0.9.0
>
>
> Even as you can argue that RFC-15/consolidated metadata, removes the need for
> deleting partial files written due to spark task failures/stage retries. It
> will still leave extra files inside the table (and users will pay for it
> every month) and we need the marker mechanism to be able to delete these
> partial files.
> Here we explore if we can improve the current marker file mechanism, that
> creates one marker file per data file written, by
> Delegating the createMarker() call to the driver/timeline server, and have it
> create marker metadata into a single file handle, that is flushed for
> durability guarantees
>
> P.S: I was tempted to think Spark listener mechanism can help us deal with
> failed tasks, but it has no guarantees. the writer job could die without
> deleting a partial file. i.e it can improve things, but cant provide
> guarantees
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