### What changes were proposed in this pull request? Add the following patch files in directory `incubator-celeborn/tree/spark3-patch/assets/spark-patch` : 1. Celeborn_Dynamic_Allocation_spark3_0.patch 2. Celeborn_Dynamic_Allocation_spark3_1.patch 3. Celeborn_Dynamic_Allocation_spark3_2.patch 4. Celeborn_Dynamic_Allocation_spark3_3.patch Delete a patch at the same time: 1. Celeborn_Dynamic_Allocation_spark3.patch Modified `Support Spark Dynamic Allocation` in incubator-celeborn/README.md :  ### Why are the changes needed? Convenient for customers to apply patches in Spark 3.X for `Support Spark Dynamic Allocation` ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? yes. All patch files can be applied to the corresponding version of spark source code through `git apply` without any code conflicts. Closes #2085 from lukeyan2023/spark3-patch. Authored-by: Luke Yan <108530647+lukeyan2023@users.noreply.github.com> Signed-off-by: zky.zhoukeyong <zky.zhoukeyong@alibaba-inc.com>
92 lines
5.3 KiB
Diff
92 lines
5.3 KiB
Diff
# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# 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, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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Subject: [PATCH] [CORE][SHUFFLE] Support enabling DRA with Apache Celeborn
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---
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Index: core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
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IDEA additional info:
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Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
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<+>UTF-8
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===================================================================
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diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
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--- a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala (revision d1f8a503a26bcfb4e466d9accc5fa241a7933667)
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+++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala (revision c8609fa08534e1cc6fd377b3573e5e65ddc79f15)
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@@ -210,7 +210,7 @@
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(decommissionEnabled &&
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conf.get(config.STORAGE_DECOMMISSION_SHUFFLE_BLOCKS_ENABLED))) {
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logWarning("Dynamic allocation without a shuffle service is an experimental feature.")
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- } else if (!testing) {
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+ } else if (!testing && !Utils.isCelebornEnabled(conf)) {
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throw new SparkException("Dynamic allocation of executors requires the external " +
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"shuffle service. You may enable this through spark.shuffle.service.enabled.")
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}
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Index: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
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IDEA additional info:
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Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
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<+>UTF-8
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===================================================================
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diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
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--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala (revision d1f8a503a26bcfb4e466d9accc5fa241a7933667)
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+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala (revision c8609fa08534e1cc6fd377b3573e5e65ddc79f15)
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@@ -2080,7 +2080,8 @@
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// if the cluster manager explicitly tells us that the entire worker was lost, then
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// we know to unregister shuffle output. (Note that "worker" specifically refers to the process
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// from a Standalone cluster, where the shuffle service lives in the Worker.)
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- val fileLost = workerHost.isDefined || !env.blockManager.externalShuffleServiceEnabled
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+ val fileLost = !Utils.isCelebornEnabled(sc.getConf) &&
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+ (workerHost.isDefined || !env.blockManager.externalShuffleServiceEnabled)
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removeExecutorAndUnregisterOutputs(
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execId = execId,
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fileLost = fileLost,
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Index: core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
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IDEA additional info:
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Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
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<+>UTF-8
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===================================================================
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diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
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--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala (revision d1f8a503a26bcfb4e466d9accc5fa241a7933667)
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+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala (revision c8609fa08534e1cc6fd377b3573e5e65ddc79f15)
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@@ -973,7 +973,8 @@
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// and we are not using an external shuffle server which could serve the shuffle outputs.
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// The reason is the next stage wouldn't be able to fetch the data from this dead executor
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// so we would need to rerun these tasks on other executors.
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- if (isShuffleMapTasks && !env.blockManager.externalShuffleServiceEnabled && !isZombie) {
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+ if (isShuffleMapTasks && !env.blockManager.externalShuffleServiceEnabled && !isZombie &&
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+ !Utils.isCelebornEnabled(conf)) {
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for ((tid, info) <- taskInfos if info.executorId == execId) {
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val index = taskInfos(tid).index
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// We may have a running task whose partition has been marked as successful,
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Index: core/src/main/scala/org/apache/spark/util/Utils.scala
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IDEA additional info:
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Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
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<+>UTF-8
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===================================================================
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diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
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--- a/core/src/main/scala/org/apache/spark/util/Utils.scala (revision d1f8a503a26bcfb4e466d9accc5fa241a7933667)
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+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala (revision c8609fa08534e1cc6fd377b3573e5e65ddc79f15)
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@@ -3057,7 +3057,12 @@
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0
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}
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}
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+
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+ def isCelebornEnabled(conf: SparkConf): Boolean =
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+ conf.get("spark.shuffle.manager", "sort").contains("celeborn")
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}
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+
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+
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private[util] object CallerContext extends Logging {
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val callerContextSupported: Boolean = {
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