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new 131d5e0 [SPARK-58599] Add `Recovery-mode Executor` example
131d5e0 is described below
commit 131d5e06572dc0079bb869663fff25de299d92da
Author: Dongjoon Hyun <[email protected]>
AuthorDate: Wed Aug 5 23:35:50 2026 -0700
[SPARK-58599] Add `Recovery-mode Executor` example
### What changes were proposed in this pull request?
This PR aims to add a new example, `group-by-with-recovery-mode.yaml`,
which demonstrates
`spark.kubernetes.allocation.recoveryMode.enabled` (SPARK-55639, Apache
Spark 4.2.0).
- https://github.com/apache/spark/pull/54558
The example runs `GroupByTest` where each mapper task materializes about
450MiB. With
`spark.executor.cores=3` and `spark.executor.memory=1g`, three concurrent
tasks exceed the
executor heap and cause OOM. With the recovery mode enabled, every executor
accepts only a
single task per executor JVM (`SPARK_EXECUTOR_CORES=1` while the pod still
requests 3 CPUs),
so the whole heap serves one task and the job succeeds.
### Why are the changes needed?
To help users try out the recovery-mode executor feature of Apache Spark
4.2.0 with a
self-contained example that actually exercises the OOM boundary:
- As-is (`"true"`): the job succeeds with single-task executors.
- Set to `"false"`: the job fails with executor OOM (exit code 52).
- Removed: the recovery mode is activated automatically when the driver
detects the OOM.
### Does this PR introduce _any_ user-facing change?
No. This is an example addition.
### How was this patch tested?
Manually tested on a local Kubernetes cluster with the operator built from
this repository.
```
$ sed 's/{{SPARK_VERSION}}/4.2.0/'
examples/group-by-with-recovery-mode.yaml | kubectl apply -f -
```
- `enabled: "true"` (as-is): executor pods request 3 CPUs but run with
`SPARK_EXECUTOR_CORES=1`;
the application reached `Succeeded` and then `ResourceReleased`.
- `enabled: "false"`: all executors terminated with exit code 52 (`JVM
OOM`) and the job failed
after task retries, as described in the example comment.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Fable 5
Closes #786 from dongjoon-hyun/SPARK-58599.
Authored-by: Dongjoon Hyun <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
---
examples/group-by-with-recovery-mode.yaml | 39 +++++++++++++++++++++++++++++++
1 file changed, 39 insertions(+)
diff --git a/examples/group-by-with-recovery-mode.yaml
b/examples/group-by-with-recovery-mode.yaml
new file mode 100644
index 0000000..cdde7c1
--- /dev/null
+++ b/examples/group-by-with-recovery-mode.yaml
@@ -0,0 +1,39 @@
+# 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.
+apiVersion: spark.apache.org/v1
+kind: SparkApplication
+metadata:
+ name: group-by-with-recovery-mode
+spec:
+ mainClass: "org.apache.spark.examples.GroupByTest"
+ # numMappers, numKVPairs, valueSize, numReducers
+ # Each mapper task materializes ~450MiB. Three concurrent tasks exceed the 1g
+ # executor heap and cause OOM. A recovery-mode executor accepts only a single
+ # task per executor JVM, so the whole heap serves one task and the job
succeeds.
+ # If the conf below is removed, the recovery mode is activated automatically
+ # when the driver detects the OOM. Set it to `false` to see the job fail
with OOM.
+ driverArgs: ["6", "450000", "1000", "6"]
+ jars: "local:///opt/spark/examples/jars/spark-examples.jar"
+ sparkConf:
+ spark.kubernetes.allocation.recoveryMode.enabled: "true"
+ spark.executor.instances: "2"
+ spark.executor.cores: "3"
+ spark.executor.memory: "1g"
+ spark.kubernetes.authenticate.driver.serviceAccountName: "spark"
+ spark.kubernetes.container.image: "apache/spark:{{SPARK_VERSION}}-scala"
+ applicationTolerations:
+ resourceRetainPolicy: OnFailure
+ runtimeVersions:
+ sparkVersion: "4.2.0"
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