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https://issues.apache.org/jira/browse/BEAM-11213?focusedWorklogId=576071&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-576071
]
ASF GitHub Bot logged work on BEAM-11213:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 02/Apr/21 12:47
Start Date: 02/Apr/21 12:47
Worklog Time Spent: 10m
Work Description: iemejia commented on a change in pull request #14409:
URL: https://github.com/apache/beam/pull/14409#discussion_r606220672
##########
File path:
runners/spark/src/main/java/org/apache/beam/runners/spark/util/SparkCommon.java
##########
@@ -0,0 +1,79 @@
+/*
+ * 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.beam.runners.spark.util;
+
+import java.net.URI;
+import java.net.URISyntaxException;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.scheduler.EventLoggingListener;
+import org.apache.spark.scheduler.SparkListenerExecutorAdded;
+import org.apache.spark.scheduler.cluster.ExecutorInfo;
+import org.checkerframework.checker.nullness.qual.Nullable;
+import scala.Tuple2;
+
+/** Common methods to build Spark specific objects used by different runners.
*/
+@Internal
+@SuppressWarnings({
+ "nullness" // TODO(https://issues.apache.org/jira/browse/BEAM-10402)
+})
+public class SparkCommon {
+
+ /**
+ * Starts an EventLoggingListener to save Beam Metrics on Spark's History
Server if event logging
+ * is enabled.
+ *
+ * @return The associated EventLoggingListener or null if it could not be
started.
+ */
+ public static @Nullable EventLoggingListener startEventLoggingListener(
+ final JavaSparkContext jsc, SparkPipelineOptions pipelineOptions, long
startTime) {
+ EventLoggingListener eventLoggingListener = null;
+ try {
+ if (jsc.getConf().getBoolean("spark.eventLog.enabled", false)) {
Review comment:
This is the [official Spark way to
configure](https://spark.apache.org/docs/latest/configuration.html#spark-ui)
what the `eventLogEnabled` and `sparkHistoryDir` options were doing. So better
to use these.
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Issue Time Tracking
-------------------
Worklog Id: (was: 576071)
Time Spent: 12h 10m (was: 12h)
> Beam metrics should be displayed in Spark UI
> --------------------------------------------
>
> Key: BEAM-11213
> URL: https://issues.apache.org/jira/browse/BEAM-11213
> Project: Beam
> Issue Type: Wish
> Components: runner-spark
> Reporter: Kyle Weaver
> Assignee: Tomasz Szerszen
> Priority: P2
> Labels: portability-spark
> Fix For: 2.29.0
>
> Time Spent: 12h 10m
> Remaining Estimate: 0h
>
> All Beam metrics are visible in the Spark UI in a single accumulator value
> (in the "Accumulators" tab), which is a large, hard-to-read blob. Originally,
> this blob was rendered in a bespoke format
> (https://github.com/apache/beam/blob/ead80b469ffeeddcd8e9e5c8dc462eec0b0ffc6b/sdks/java/core/src/main/java/org/apache/beam/sdk/metrics/MetricQueryResults.java#L63-L72).
> I changed the format to JSON so it could be easily deserialized (BEAM-9600).
> But then an issue was filed (BEAM-10294) reporting that the new JSON format
> was harder to read than the original bespoke format. The temporary fix was to
> revert to the bespoke format in Spark, while allowing Flink to continue to
> use JSON. However, if Beam metrics are only visible as an accumulator, then
> they are also unreadable because the payloads are in binary form (BEAM-10719).
> Having metrics visible in Spark's "Metrics" tab would A) make metrics easier
> to read (even compared to the bespoke accumulator string format), and closer
> to what users of Beamless Spark expect, and B) free us to use the accumulator
> however we wish for Beam internal purposes, without worrying about
> readability.
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