### What changes were proposed in this pull request?
This PR aims to support driver-owned on-demand PVC(Persistent Volume Claim)s. It means dynamically-created PVCs will have the `ownerReference` to `driver` pod instead of `executor` pod.
### Why are the changes needed?
This allows K8s backend scheduler can reuse this later.
**BEFORE**
```
$ k get pvc tpcds-pvc-exec-1-pvc-0 -oyaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
...
ownerReferences:
- apiVersion: v1
controller: true
kind: Pod
name: tpcds-pvc-exec-1
```
**AFTER**
```
$ k get pvc tpcds-pvc-exec-1-pvc-0 -oyaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
...
ownerReferences:
- apiVersion: v1
controller: true
kind: Pod
name: tpcds-pvc
```
### Does this PR introduce _any_ user-facing change?
No. (The default is `false`)
### How was this patch tested?
Manually check the above and pass K8s IT.
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
- Test basic decommissioning
- Test basic decommissioning with shuffle cleanup
- Test decommissioning with dynamic allocation & shuffle cleanups
- Test decommissioning timeouts
- Run SparkR on simple dataframe.R example
Run completed in 16 minutes, 40 seconds.
Total number of tests run: 27
Suites: completed 2, aborted 0
Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#32288 from dongjoon-hyun/SPARK-35182.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
In YARN, ship the `spark.jars.ivySettings` file to the driver when using `cluster` deploy mode so that `addJar` is able to find it in order to resolve ivy paths.
### Why are the changes needed?
SPARK-33084 introduced support for Ivy paths in `sc.addJar` or Spark SQL `ADD JAR`. If we use a custom ivySettings file using `spark.jars.ivySettings`, it is loaded at b26e7b510b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala (L1280). However, this file is only accessible on the client machine. In YARN cluster mode, this file is not available on the driver and so `addJar` fails to find it.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added unit tests to verify that the `ivySettings` file is localized by the YARN client and that a YARN cluster mode application is able to find to load the `ivySettings` file.
Closes#31591 from shardulm94/SPARK-34472.
Authored-by: Shardul Mahadik <smahadik@linkedin.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
On Running Spark job with yarn and deployment mode as client, Spark Driver and Spark Application master launch in two separate containers. In various scenarios there is need to see Spark Application master logs to see the resource allocation, Decommissioning status and other information shared between yarn RM and Spark Application master.
In Cluster mode Spark driver and Spark AM is on same container, So Log link of the driver already there to see the logs in Spark UI
This PR is for adding the spark AM log link for spark job running in the client mode for yarn. Instead of searching the container id and then find the logs. We can directly check in the Spark UI
This change is only for showing the AM log links in the Client mode when resource manager is yarn.
### Why are the changes needed?
Till now the only way to check this by finding the container id of the AM and check the logs either using Yarn utility or Yarn RM Application History server.
This PR is for adding the spark AM log link for spark job running in the client mode for yarn. Instead of searching the container id and then find the logs. We can directly check in the Spark UI
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added the unit test also checked the Spark UI
**In Yarn Client mode**
Before Change
After the Change - The AM info is there
AM Log
**In Yarn Cluster Mode** - The AM log link will not be there
Closes#31974 from SaurabhChawla100/SPARK-34877.
Authored-by: SaurabhChawla <s.saurabhtim@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR aims to support a new configuration, `spark.kubernetes.driver.service.deleteOnTermination`, to clean up `Driver Service` resource during app termination.
### Why are the changes needed?
The K8s service is one of the important resources and sometimes it's controlled by quota.
```
$ k describe quota
Name: service
Namespace: default
Resource Used Hard
-------- ---- ----
services 1 3
```
Apache Spark creates a service for driver whose lifecycle is the same with driver pod.
It means a new Spark job submission fails if the number of completed Spark jobs equals the number of service quota.
**BEFORE**
```
$ k get pod
NAME READY STATUS RESTARTS AGE
org-apache-spark-examples-sparkpi-a32c9278e7061b4d-driver 0/1 Completed 0 31m
org-apache-spark-examples-sparkpi-a9f1f578e721ef62-driver 0/1 Completed 0 78s
$ k get svc
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 80m
org-apache-spark-examples-sparkpi-a32c9278e7061b4d-driver-svc ClusterIP None <none> 7078/TCP,7079/TCP,4040/TCP 31m
org-apache-spark-examples-sparkpi-a9f1f578e721ef62-driver-svc ClusterIP None <none> 7078/TCP,7079/TCP,4040/TCP 80s
$ k describe quota
Name: service
Namespace: default
Resource Used Hard
-------- ---- ----
services 3 3
$ bin/spark-submit...
Exception in thread "main" io.fabric8.kubernetes.client.KubernetesClientException:
Failure executing: POST at: https://192.168.64.50:8443/api/v1/namespaces/default/services.
Message: Forbidden! User minikube doesn't have permission.
services "org-apache-spark-examples-sparkpi-843f6978e722819c-driver-svc" is forbidden:
exceeded quota: service, requested: services=1, used: services=3, limited: services=3.
```
**AFTER**
```
$ k get pod
NAME READY STATUS RESTARTS AGE
org-apache-spark-examples-sparkpi-23d5f278e77731a7-driver 0/1 Completed 0 26s
org-apache-spark-examples-sparkpi-d1292278e7768ed4-driver 0/1 Completed 0 67s
org-apache-spark-examples-sparkpi-e5bedf78e776ea9d-driver 0/1 Completed 0 44s
$ k get svc
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 172m
$ k describe quota
Name: service
Namespace: default
Resource Used Hard
-------- ---- ----
services 1 3
```
### Does this PR introduce _any_ user-facing change?
Yes, this PR adds a new configuration, `spark.kubernetes.driver.service.deleteOnTermination`, and enables it by default.
The change is documented at the migration guide.
### How was this patch tested?
Pass the CIs.
This is tested with K8s IT manually.
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
- Test basic decommissioning
- Test basic decommissioning with shuffle cleanup
- Test decommissioning with dynamic allocation & shuffle cleanups
- Test decommissioning timeouts
- Run SparkR on simple dataframe.R example
Run completed in 19 minutes, 9 seconds.
Total number of tests run: 27
Suites: completed 2, aborted 0
Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#32226 from dongjoon-hyun/SPARK-35131.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Although AS-IS master branch already works with K8s 1.20, this PR aims to upgrade K8s client to 5.3.0 to support K8s 1.20 officially.
- https://github.com/fabric8io/kubernetes-client#compatibility-matrix
The following are the notable breaking API changes.
1. Remove Doneable (5.0+):
- https://github.com/fabric8io/kubernetes-client/pull/2571
2. Change Watcher.onClose signature (5.0+):
- https://github.com/fabric8io/kubernetes-client/pull/2616
3. Change Readiness (5.1+)
- https://github.com/fabric8io/kubernetes-client/pull/2796
### Why are the changes needed?
According to the compatibility matrix, this makes Apache Spark and its external cluster manager extension support all K8s 1.20 features officially for Apache Spark 3.2.0.
### Does this PR introduce _any_ user-facing change?
Yes, this is a dev dependency change which affects K8s cluster extension users.
### How was this patch tested?
Pass the CIs.
This is manually tested with K8s IT.
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
- Test basic decommissioning
- Test basic decommissioning with shuffle cleanup
- Test decommissioning with dynamic allocation & shuffle cleanups
- Test decommissioning timeouts
- Run SparkR on simple dataframe.R example
Run completed in 17 minutes, 44 seconds.
Total number of tests run: 27
Suites: completed 2, aborted 0
Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#32221 from dongjoon-hyun/SPARK-K8S-530.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Introducing a new test construct:
```
withHttpServer() { baseURL =>
...
}
```
Which starts and stops a Jetty server to serve files via HTTP.
Moreover this PR uses this new construct in the test `Run SparkRemoteFileTest using a remote data file`.
### Why are the changes needed?
Before this PR github URLs was used like "https://raw.githubusercontent.com/apache/spark/master/data/mllib/pagerank_data.txt".
This connects two Spark version in an unhealthy way like connecting the "master" branch which is moving part with the committed test code which is a non-moving (as it might be even released).
So this way a test running for an earlier version of Spark expects something (filename, content, path) from a the latter release and what is worse when the moving version is changed the earlier test will break.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing unit test.
Closes#31935 from attilapiros/SPARK-34789.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR fixes two tests below:
https://github.com/apache/spark/runs/2320161984
```
[info] YarnShuffleIntegrationSuite:
[info] org.apache.spark.deploy.yarn.YarnShuffleIntegrationSuite *** ABORTED *** (228 milliseconds)
[info] org.apache.hadoop.yarn.exceptions.YarnRuntimeException: org.apache.hadoop.yarn.webapp.WebAppException: Error starting http server
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.startResourceManager(MiniYARNCluster.java:373)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.access$300(MiniYARNCluster.java:128)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster$ResourceManagerWrapper.serviceStart(MiniYARNCluster.java:503)
[info] at org.apache.hadoop.service.AbstractService.start(AbstractService.java:194)
[info] at org.apache.hadoop.service.CompositeService.serviceStart(CompositeService.java:121)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.serviceStart(MiniYARNCluster.java:322)
[info] at org.apache.hadoop.service.AbstractService.start(AbstractService.java:194)
[info] at org.apache.spark.deploy.yarn.BaseYarnClusterSuite.beforeAll(BaseYarnClusterSuite.scala:95)
...
[info] Cause: java.net.BindException: Port in use: fv-az186-831:0
[info] at org.apache.hadoop.http.HttpServer2.constructBindException(HttpServer2.java:1231)
[info] at org.apache.hadoop.http.HttpServer2.bindForSinglePort(HttpServer2.java:1253)
[info] at org.apache.hadoop.http.HttpServer2.openListeners(HttpServer2.java:1316)
[info] at org.apache.hadoop.http.HttpServer2.start(HttpServer2.java:1167)
[info] at org.apache.hadoop.yarn.webapp.WebApps$Builder.start(WebApps.java:449)
[info] at org.apache.hadoop.yarn.server.resourcemanager.ResourceManager.startWepApp(ResourceManager.java:1247)
[info] at org.apache.hadoop.yarn.server.resourcemanager.ResourceManager.serviceStart(ResourceManager.java:1356)
[info] at org.apache.hadoop.service.AbstractService.start(AbstractService.java:194)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.startResourceManager(MiniYARNCluster.java:365)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.access$300(MiniYARNCluster.java:128)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster$ResourceManagerWrapper.serviceStart(MiniYARNCluster.java:503)
[info] at org.apache.hadoop.service.AbstractService.start(AbstractService.java:194)
[info] at org.apache.hadoop.service.CompositeService.serviceStart(CompositeService.java:121)
[info] at org.apache.hadoop.yarn.server.MiniYARNCluster.serviceStart(MiniYARNCluster.java:322)
[info] at org.apache.hadoop.service.AbstractService.start(AbstractService.java:194)
[info] at org.apache.spark.deploy.yarn.BaseYarnClusterSuite.beforeAll(BaseYarnClusterSuite.scala:95)
[info] at org.scalatest.BeforeAndAfterAll.liftedTree1$1(BeforeAndAfterAll.scala:212)
[info] at org.scalatest.BeforeAndAfterAll.run(BeforeAndAfterAll.scala:210)
[info] at org.scalatest.BeforeAndAfterAll.run$(BeforeAndAfterAll.scala:208)
[info] at org.apache.spark.SparkFunSuite.run(SparkFunSuite.scala:61)
...
```
https://github.com/apache/spark/runs/2323342094
```
[info] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadSecret started
[error] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadSecret failed: java.lang.AssertionError: Connecting to /10.1.0.161:39895 timed out (120000 ms), took 120.081 sec
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadSecret(ExternalShuffleSecuritySuite.java:85)
[error] ...
[info] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadAppId started
[error] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadAppId failed: java.lang.AssertionError: Connecting to /10.1.0.198:44633 timed out (120000 ms), took 120.08 sec
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testBadAppId(ExternalShuffleSecuritySuite.java:76)
[error] ...
[info] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testValid started
[error] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testValid failed: java.io.IOException: Connecting to /10.1.0.119:43575 timed out (120000 ms), took 120.089 sec
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:285)
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
[error] at org.apache.spark.network.shuffle.ExternalBlockStoreClient.registerWithShuffleServer(ExternalBlockStoreClient.java:211)
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.validate(ExternalShuffleSecuritySuite.java:108)
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testValid(ExternalShuffleSecuritySuite.java:68)
[error] ...
[info] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testEncryption started
[error] Test org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testEncryption failed: java.io.IOException: Connecting to /10.1.0.248:35271 timed out (120000 ms), took 120.014 sec
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:285)
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
[error] at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
[error] at org.apache.spark.network.shuffle.ExternalBlockStoreClient.registerWithShuffleServer(ExternalBlockStoreClient.java:211)
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.validate(ExternalShuffleSecuritySuite.java:108)
[error] at org.apache.spark.network.shuffle.ExternalShuffleSecuritySuite.testEncryption(ExternalShu
```
For Yarn cluster suites, its difficult to fix. This PR makes it skipped if it fails to bind.
For shuffle related suites, it uses local host
### Why are the changes needed?
To make the tests stable
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Its tested in GitHub Actions: https://github.com/HyukjinKwon/spark/runs/2340210765Closes#32126 from HyukjinKwon/SPARK-35002-followup.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
### What changes were proposed in this pull request?
This PR aims to add `ownerReference` to the executor ConfigMap to fix leakage.
### Why are the changes needed?
SPARK-30985 maintains the executor config map explicitly inside Spark. However, this config map can be leaked when Spark drivers die accidentally or are killed by K8s. We need to add `ownerReference` to make K8s do the garbage collection these automatically.
The number of ConfigMap is one of the resource quota. So, the leaked configMaps currently cause Spark jobs submission failures.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs and check manually.
K8s IT is tested manually.
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
- Test basic decommissioning
- Test basic decommissioning with shuffle cleanup
- Test decommissioning with dynamic allocation & shuffle cleanups
- Test decommissioning timeouts
- Run SparkR on simple dataframe.R example
Run completed in 19 minutes, 2 seconds.
Total number of tests run: 27
Suites: completed 2, aborted 0
Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
**BEFORE**
```
$ k get cm spark-exec-450b417895b3b2c7-conf-map -oyaml | grep ownerReferences
```
**AFTER**
```
$ k get cm spark-exec-bb37a27895b1c26c-conf-map -oyaml | grep ownerReferences
f:ownerReferences:
```
Closes#32042 from dongjoon-hyun/SPARK-34948.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Add a new config, `spark.shuffle.service.name`, which allows for Spark applications to look for a YARN shuffle service which is defined at a name other than the default `spark_shuffle`.
Add a new config, `spark.yarn.shuffle.service.metrics.namespace`, which allows for configuring the namespace used when emitting metrics from the shuffle service into the NodeManager's `metrics2` system.
Add a new mechanism by which to override shuffle service configurations independently of the configurations in the NodeManager. When a resource `spark-shuffle-site.xml` is present on the classpath of the shuffle service, the configs present within it will be used to override the configs coming from `yarn-site.xml` (via the NodeManager).
### Why are the changes needed?
There are two use cases which can benefit from these changes.
One use case is to run multiple instances of the shuffle service side-by-side in the same NodeManager. This can be helpful, for example, when running a YARN cluster with a mixed workload of applications running multiple Spark versions, since a given version of the shuffle service is not always compatible with other versions of Spark (e.g. see SPARK-27780). With this PR, it is possible to run two shuffle services like `spark_shuffle` and `spark_shuffle_3.2.0`, one of which is "legacy" and one of which is for new applications. This is possible because YARN versions since 2.9.0 support the ability to run shuffle services within an isolated classloader (see YARN-4577), meaning multiple Spark versions can coexist.
Besides this, the separation of shuffle service configs into `spark-shuffle-site.xml` can be useful for administrators who want to change and/or deploy Spark shuffle service configurations independently of the configurations for the NodeManager (e.g., perhaps they are owned by two different teams).
### Does this PR introduce _any_ user-facing change?
Yes. There are two new configurations related to the external shuffle service, and a new mechanism which can optionally be used to configure the shuffle service. `docs/running-on-yarn.md` has been updated to provide user instructions; please see this guide for more details.
### How was this patch tested?
In addition to the new unit tests added, I have deployed this to a live YARN cluster and successfully deployed two Spark shuffle services simultaneously, one running a modified version of Spark 2.3.0 (which supports some of the newer shuffle protocols) and one running Spark 3.1.1. Spark applications of both versions are able to communicate with their respective shuffle services without issue.
Closes#31936 from xkrogen/xkrogen-SPARK-34828-shufflecompat-config-from-classpath.
Authored-by: Erik Krogen <xkrogen@apache.org>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
Extending "EXTRA LOGS FOR THE FAILED TEST" section of k8s integration test log with `kubectl describe pods` output for the failed test.
### Why are the changes needed?
PR builds frequently fails as the k8s integration tests are very flaky now in Amplab Jenkins environment.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Locally by making temporary one of the test fail. The output is:
```
21/03/25 16:55:16.722 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite:
===== EXTRA LOGS FOR THE FAILED TEST
21/03/25 16:55:17.167 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite: BEGIN driver DESCRIBE POD
Name: spark-test-app-a2b03971b7c049e8a2629f6a3198842b
Namespace: 35bdb17e308743afaec17538f89a7c3e
Priority: 0
Node: minikube/192.168.64.119
Start Time: Thu, 25 Mar 2021 16:52:10 +0100
Labels: spark-app-locator=75f695685ae44314a99ec13bb39332bc
spark-app-selector=spark-150230742d364a77927a08eed0222065
spark-role=driver
Annotations: <none>
Status: Succeeded
IP: 172.17.0.4
Containers:
spark-kubernetes-driver:
Container ID: docker://d6d27b0551060d9b094f12d1e232dfb5ae78ce38559680c7126c548996da4d95
Image: docker.io/kubespark/spark:3.2.0-SNAPSHOT_9575B805-9CB0-4A16-8A31-AA2F8DDA8EE5
Image ID: docker://sha256:3fc556c73a0d5187b5a14dbdc2f69ef292e60b544b4b4d3715f6749417c20918
Ports: 7078/TCP, 7079/TCP, 4040/TCP
Host Ports: 0/TCP, 0/TCP, 0/TCP
Args:
driver
--properties-file
/opt/spark/conf/spark.properties
--class
org.apache.spark.examples.SparkPi
local:///opt/spark/examples/jars/spark-examples_2.12-3.2.0-SNAPSHOT.jar
State: Terminated
Reason: Completed
Exit Code: 0
Started: Thu, 25 Mar 2021 16:52:11 +0100
Finished: Thu, 25 Mar 2021 16:52:20 +0100
Ready: False
Restart Count: 0
Limits:
memory: 1408Mi
Requests:
cpu: 1
memory: 1408Mi
Environment:
SPARK_USER: attilazsoltpiros
SPARK_APPLICATION_ID: spark-150230742d364a77927a08eed0222065
SPARK_DRIVER_BIND_ADDRESS: (v1:status.podIP)
SPARK_LOCAL_DIRS: /var/data/spark-dab6f1c9-e538-40c8-a7d9-3e88f9b82cfa
SPARK_CONF_DIR: /opt/spark/conf
Mounts:
/opt/spark/conf from spark-conf-volume-driver (rw)
/var/data/spark-dab6f1c9-e538-40c8-a7d9-3e88f9b82cfa from spark-local-dir-1 (rw)
/var/run/secrets/kubernetes.io/serviceaccount from default-token-nmfwl (ro)
Conditions:
Type Status
Initialized True
Ready False
ContainersReady False
PodScheduled True
Volumes:
spark-local-dir-1:
Type: EmptyDir (a temporary directory that shares a pod's lifetime)
Medium:
SizeLimit: <unset>
spark-conf-volume-driver:
Type: ConfigMap (a volume populated by a ConfigMap)
Name: spark-drv-c60832786a15ffbe-conf-map
Optional: false
default-token-nmfwl:
Type: Secret (a volume populated by a Secret)
SecretName: default-token-nmfwl
Optional: false
QoS Class: Burstable
Node-Selectors: <none>
Tolerations: node.kubernetes.io/not-ready:NoExecute for 300s
node.kubernetes.io/unreachable:NoExecute for 300s
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Scheduled 3m7s default-scheduler Successfully assigned 35bdb17e308743afaec17538f89a7c3e/spark-test-app-a2b03971b7c049e8a2629f6a3198842b to minikube
Normal Pulled 3m7s kubelet, minikube Container image "docker.io/kubespark/spark:3.2.0-SNAPSHOT_9575B805-9CB0-4A16-8A31-AA2F8DDA8EE5" already present on machine
Normal Created 3m7s kubelet, minikube Created container spark-kubernetes-driver
Normal Started 3m6s kubelet, minikube Started container spark-kubernetes-driver
21/03/25 16:55:17.168 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite: END driver DESCRIBE POD
```
Closes#31962 from attilapiros/SPARK-34869.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Support submit to k8s only with token.
### Why are the changes needed?
Now, sumbit to k8s always need oauth files.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Before, submit job out of k8s cluster without correct ca.crt, we may get this exception:
```
Caused by: sun.security.validator.ValidatorException: PKIX path building failed: sun.security.provider.certpath.SunCertPathBuilderException: unable to find valid certification path to requested target
at sun.security.validator.PKIXValidator.doBuild(PKIXValidator.java:439)
at sun.security.validator.PKIXValidator.engineValidate(PKIXValidator.java:306)
at sun.security.validator.Validator.validate(Validator.java:271)
at sun.security.ssl.X509TrustManagerImpl.validate(X509TrustManagerImpl.java:312)
```
When set spark.kubernetes.trust.certificates = true, we can submit only with correct token, no need to config ca.crt in local env.
Submit as:
```
bin/spark-submit \
--master $master \
--name pi \
--deploy-mode cluster \
--conf spark.kubernetes.container.image=$image \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.authenticate.submission.oauthToken=$clusterToken \
--conf spark.kubernetes.trust.certificates=true \
local:///opt/spark/examples/src/main/python/pi.py 200
```
Closes#30684 from hddong/trust-certs.
Authored-by: hongdongdong <hongdongdong@cmss.chinamobile.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
We added the gnupg installation in https://github.com/apache/spark/pull/30130 , we should do apt update before gnupg isntallation, otherwise we will get a fetch error when package is updated.
See more in:
[1] http://apache-spark-developers-list.1001551.n3.nabble.com/K8s-Integration-test-is-unable-to-run-because-of-the-unavailable-libs-td30986.html
### Why are the changes needed?
add a apt-update cmd before gnupg installation to avoid invaild package cache list.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
K8s Integration test passed
Closes#31923 from Yikun/SPARK-34820.
Authored-by: Yikun Jiang <yikunkero@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to support remote driver/executor template files.
### Why are the changes needed?
Currently, `KubernetesUtils.loadPodFromTemplate` supports only local files.
With this PR, we can do the following.
```bash
bin/spark-submit \
...
-c spark.kubernetes.driver.podTemplateFile=s3a://dongjoon/driver.yml \
-c spark.kubernetes.executor.podTemplateFile=s3a://dongjoon/executor.yml \
...
```
### Does this PR introduce _any_ user-facing change?
Yes, this is an improvement.
### How was this patch tested?
Manual testing.
Closes#31877 from dongjoon-hyun/SPARK-34783-2.
Lead-authored-by: Dongjoon Hyun <dhyun@apple.com>
Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Fixing `IndexOutOfBoundsException` in `logForFailedTest` method when driver is not started.
### Why are the changes needed?
Before this PR when the driver is not started an `IndexOutOfBoundsException` as the first item is tried to be accessed from an empty list:
```
- PVs with local storage *** FAILED ***
java.lang.IndexOutOfBoundsException: Index: 0, Size: 0
at java.util.ArrayList.rangeCheck(ArrayList.java:659)
at java.util.ArrayList.get(ArrayList.java:435)
at org.apache.spark.deploy.k8s.integrationtest.KubernetesSuite.logForFailedTest(KubernetesSuite.scala:83)
at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:181)
at org.scalatest.funsuite.AnyFunSuiteLike.invokeWithFixture$1(AnyFunSuiteLike.scala:188)
at org.scalatest.funsuite.AnyFunSuiteLike.$anonfun$runTest$1(AnyFunSuiteLike.scala:200)
at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
at org.scalatest.funsuite.AnyFunSuiteLike.runTest(AnyFunSuiteLike.scala:200)
at org.scalatest.funsuite.AnyFunSuiteLike.runTest$(AnyFunSuiteLike.scala:182)
at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterEach$$super$runTest(SparkFunSuite.scala:61)
...
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Running integration tests.
After this changes the above error become:
```
- PVs with local storage *** FAILED ***
java.io.IOException: No such file or directory
at java.io.UnixFileSystem.createFileExclusively(Native Method)
at java.io.File.createTempFile(File.java:2026)
at org.apache.spark.deploy.k8s.integrationtest.Utils$.createTempFile(Utils.scala:103)
at org.apache.spark.deploy.k8s.integrationtest.PVTestsSuite.$anonfun$$init$$1(PVTestsSuite.scala:135)
at org.scalatest.OutcomeOf.outcomeOf(OutcomeOf.scala:85)
at org.scalatest.OutcomeOf.outcomeOf$(OutcomeOf.scala:83)
at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
at org.scalatest.Transformer.apply(Transformer.scala:22)
at org.scalatest.Transformer.apply(Transformer.scala:20)
at org.scalatest.funsuite.AnyFunSuiteLike$$anon$1.apply(AnyFunSuiteLike.scala:190)
...
```
Closes#31824 from attilapiros/SPARK-34732.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR modifies the POD allocator to use the scheduler backend to get the known executors and remove those from the pending and newly created list.
This is different from the normal `ExecutorAllocationManager` requested killing of executors where the `spark.dynamicAllocation.executorIdleTimeout` is used.
In this case POD allocator kills the executors which should be only responsible for terminating not satisfied POD allocations (new requests where no POD state is received yet and PODs in pending state).
### Why are the changes needed?
Because there is race between executor POD allocator and cluster scheduler backend.
Running several experiment during downscaling we experienced a lot of killed fresh executors wich has already running task on them.
The pattern in the log was the following (see executor 312 and TID 2079):
```
21/02/01 15:12:03 INFO ExecutorMonitor: New executor 312 has registered (new total is 138)
...
21/02/01 15:12:03 INFO TaskSetManager: Starting task 247.0 in stage 4.0 (TID 2079, 100.100.18.138, executor 312, partition 247, PROCESS_LOCAL, 8777 bytes)
21/02/01 15:12:03 INFO ExecutorPodsAllocator: Deleting 3 excess pod requests (408,312,307).
...
21/02/01 15:12:04 ERROR TaskSchedulerImpl: Lost executor 312 on 100.100.18.138: The executor with id 312 was deleted by a user or the framework.
21/02/01 15:12:04 INFO TaskSetManager: Task 2079 failed because while it was being computed, its executor exited for a reason unrelated to the task. Not counting this failure towards the maximum number of failures for the task.
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
#### Manually
With this change there was no executor lost with running task on it.
##### With unit test
A new test is added and existing test is modified to check these cases.
Closes#31513 from attilapiros/SPARK-34361.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This is kind of a followup of https://github.com/apache/spark/pull/24033 and https://github.com/apache/spark/pull/30945.
Many of references in `SecurityManager` were introduced from SPARK-1189, and related usages were removed later from https://github.com/apache/spark/pull/24033 and https://github.com/apache/spark/pull/30945. This PR proposes to remove them out.
### Why are the changes needed?
For better readability of codes.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually complied. GitHub Actions and Jenkins build should test it out as well.
Closes#31636 from HyukjinKwon/SPARK-34520.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
From [minikube version v1.1.0](https://github.com/kubernetes/minikube/blob/v1.1.0/CHANGELOG.md) kubectl is available as a command. So the kubeconfig settings can be accessed like:
```
$ minikube kubectl config view
apiVersion: v1
clusters:
- cluster:
certificate-authority: /Users/attilazsoltpiros/.minikube/ca.crt
server: https://127.0.0.1:32788
name: minikube
contexts:
- context:
cluster: minikube
namespace: default
user: minikube
name: minikube
current-context: minikube
kind: Config
preferences: {}
users:
- name: minikube
user:
client-certificate: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.crt
client-key: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.key
```
Here the vm-driver was docker and the server port (https://127.0.0.1:32788) is different from the hardcoded 8443.
So the main part of this PR is introducing kubernetes client configuration based on the kubeconfig (output of `minikube kubectl config view`) in case of minikube versions after v1.1.0 and the old legacy way of configuration is also kept as minikube version should be supported back to v0.34.1 .
Moreover as the old style of config parsing pattern wasn't sufficient in my case as when the `minikube kubectl config view` is called kubectl downloading message might be included before the first key I changed it even for the existent keys to be a consistent pattern in this file.
The old parsing in an example:
```
private val HOST_PREFIX = "host:"
val hostString = statusString.find(_.contains(s"$HOST_PREFIX "))
val status1 = hostString.get.split(HOST_PREFIX)(1)
```
The new parsing:
```
private val HOST_PREFIX = "host: "
val hostString = statusString.find(_.contains(HOST_PREFIX))
hostString.get.split(HOST_PREFIX)(1)
```
So the PREFIX is extended with the extra space at the declaration (this way the two separate string operation are more safe and consistent with each other) and the replace is changed to split and getting the 2nd string from the result (which is guaranteed to contain only the text after the PREFIX when the PREFIX is a contained substring).
Finally there is tiny change in `dev-run-integration-tests.sh` to introduce `--skip-building-dependencies` which switchs off building of maven dependencies of `kubernetes-integration-tests` from the Spark project.
This could be used when only the `kubernetes-integration-tests` should be rebuilded as only the tests are modified.
### Why are the changes needed?
Kubernetes client configuration based on kubeconfig settings is more reliable and provides a solution which is minikube version independent.
### Does this PR introduce _any_ user-facing change?
No. This is only test code.
### How was this patch tested?
tested manually on two minikube versions.
Minikube v0.34.1:
```
$ minikube version
minikube version: v0.34.1
$ grep "version\|building" resource-managers/kubernetes/integration-tests/target/integration-tests.log
20/12/12 12:52:25.135 ScalaTest-main-running-DiscoverySuite INFO Minikube: minikube version: v0.34.1
20/12/12 12:52:25.761 ScalaTest-main-running-DiscoverySuite INFO Minikube: building kubernetes config with apiVersion: v1, masterUrl: https://192.168.99.103:8443, caCertFile: /Users/attilazsoltpiros/.minikube/ca.crt, clientCertFile: /Users/attilazsoltpiros/.minikube/apiserver.crt, clientKeyFile: /Users/attilazsoltpiros/.minikube/apiserver.key
```
Minikube v1.15.1
```
$ minikube version
minikube version: v1.15.1
commit: 23f40a012abb52eff365ff99a709501a61ac5876
$ grep "version\|building" resource-managers/kubernetes/integration-tests/target/integration-tests.log
20/12/13 06:25:55.086 ScalaTest-main-running-DiscoverySuite INFO Minikube: minikube version: v1.15.1
20/12/13 06:25:55.597 ScalaTest-main-running-DiscoverySuite INFO Minikube: building kubernetes config with apiVersion: v1, masterUrl: https://192.168.64.4:8443, caCertFile: /Users/attilazsoltpiros/.minikube/ca.crt, clientCertFile: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.crt, clientKeyFile: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.key
$ minikube kubectl config view
apiVersion: v1
clusters:
- cluster:
certificate-authority: /Users/attilazsoltpiros/.minikube/ca.crt
server: https://192.168.64.4:8443
name: minikube
contexts:
- context:
cluster: minikube
namespace: default
user: minikube
name: minikube
current-context: minikube
kind: Config
preferences: {}
users:
- name: minikube
user:
client-certificate: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.crt
client-key: /Users/attilazsoltpiros/.minikube/profiles/minikube/client.key
```
Closes#30751 from attilapiros/SPARK-32617.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR aims to use the runtime Hadoop version in K8s integration test.
### Why are the changes needed?
SPARK-33212 upgrades Hadoop dependency from 3.2.0 to 3.2.2 and we will upgrade to 3.3.x+.
We had better use the runtime Hadoop version instead of having a static string.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the K8s IT.
This is tested locally like the following.
```
KubernetesSuite:
...
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
...
```
Closes#31604 from dongjoon-hyun/SPARK-34487.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `kubernetes-client` library from 4.12.0 to 4.13.2 for Apache Spark 3.2.0.
### Why are the changes needed?
This will bring [K8s 1.19.1](https://github.com/fabric8io/kubernetes-client/pull/2541) models officially and the latest bug fixes.
- https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.0
- https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.1
- https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.2
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the K8s IT and UT.
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- SPARK-33615: Launcher client archives
- SPARK-33748: Launcher python client respecting PYSPARK_PYTHON
- SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python
- Launcher python client dependencies using a zip file
- Test basic decommissioning
- Test basic decommissioning with shuffle cleanup
- Test decommissioning with dynamic allocation & shuffle cleanups
- Test decommissioning timeouts
- Run SparkR on simple dataframe.R example
Run completed in 19 minutes, 25 seconds.
Total number of tests run: 27
Suites: completed 2, aborted 0
Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#31602 from dongjoon-hyun/SPARK-34486.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR adds missing docs for ResourceProfile related APIs. Besides, it includes a few minor changes on API:
* ResourceProfileBuilder.build -> ResourceProfileBuilder.builder()
* Provides java specific API `allSupportedExecutorResourcesJList`
* private `ResourceAllocator` since it was mistakenly exposed previously
### Why are the changes needed?
Add missing API docs
### Does this PR introduce _any_ user-facing change?
No, as Apache Spark 3.1 hasn't officially released.
### How was this patch tested?
Updated unit tests due to the signature change of `build()`.
Closes#31496 from Ngone51/resource-profile-api-cleanup.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to make `KubernetesClusterSchedulerBackend` ignore `RegisterExecutor` message when `SparkContext` is stopped already.
### Why are the changes needed?
If `SparkDriver` is terminated, the executors will be removed by K8s automatically.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the newly added test case.
Closes#31587 from dongjoon-hyun/SPARK-34469.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR adds the following metrics to track executor remove reasons during dynamic allocation:
- `numberExecutorsGracefullyDecommissioned`: number of executors which reached the finished decommissioning state and shut itself down cleanly
- `numberExecutorsDecommissionUnfinished`: executors which requested to decommission but they stopped without reaching the finished decommissioning state
- `numberExecutorsKilledByDriver`: executors killed by the driver (requested to stop)
- `numberExecutorsExitedUnexpectedly`: executors exited without driver request
### Why are the changes needed?
For supporting monitoring of dynamic allocation better with these metrics.
### Does this PR introduce _any_ user-facing change?
Yes. The new metrics will be available for monitoring.
### How was this patch tested?
With unit and integration tests.
Finally manually checked the new metrics in jconsole:
<img width="1054" alt="jmx" src="https://user-images.githubusercontent.com/2017933/107458686-de8adf00-6b54-11eb-86f7-41faf2fb638f.png">
Closes#31450 from attilapiros/SPARK-33763-final.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR introduces a new protected method in `SparkFunSuite` which is only called when the test failed and can be used to collect logs for failed test. By this PR it is implemented in the Kubernetes tests by `KubernetesSuite` class where it collects all the POD logs and logs them out.
This unfortunately cannot be realized with a simple "after" method as in the "after" method the test outcome is not available.
Moreover this PR removes the `appLocator` as a method argument as `appLocator` is available as a member variable.
### Why are the changes needed?
Currently both the driver and executors logs are lost.
In [developer-tools](https://spark.apache.org/developer-tools.html) there is a hint:
"Getting logs from the pods and containers directly is an exercise left to the reader."
But when the test is executed by Jenkins and a failure happened we really need the POD logs to analyze problem.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
By integration testing. I have checked what would happen if one test fails, the output would be:
```
21/02/14 11:05:34.261 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite:
===== EXTRA LOGS FOR THE FAILED TEST
21/02/14 11:05:34.278 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite: BEGIN driver POD log
++ id -u
+ myuid=185
++ id -g
+ mygid=0
+ set +e
++ getent passwd 185
+ uidentry=
+ set -e
+ '[' -z '' ']'
+ '[' -w /etc/passwd ']'
+ echo '185❌185:0:anonymous uid:/opt/spark:/bin/false'
+ SPARK_CLASSPATH=':/opt/spark/jars/*'
+ env
+ grep SPARK_JAVA_OPT_
+ sort -t_ -k4 -n
+ sed 's/[^=]*=\(.*\)/\1/g'
+ readarray -t SPARK_EXECUTOR_JAVA_OPTS
+ '[' -n '' ']'
+ '[' -z ']'
+ '[' -z ']'
+ '[' -n '' ']'
+ '[' -z ']'
+ '[' -z x ']'
+ SPARK_CLASSPATH='/opt/spark/conf::/opt/spark/jars/*'
+ case "$1" in
+ shift 1
+ CMD=("$SPARK_HOME/bin/spark-submit" --conf "spark.driver.bindAddress=$SPARK_DRIVER_BIND_ADDRESS" --deploy-mode client "$")
+ exec /usr/bin/tini -s -- /opt/spark/bin/spark-submit --conf spark.driver.bindAddress=172.17.0.3 --deploy-mode client --properties-file /opt/spark/conf/spark.properties --class org.apache.spark.deploy.PythonRunner local:///opt/spark/tests/decommissioning.py
21/02/14 10:02:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Starting decom test
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
21/02/14 10:02:29 INFO SparkContext: Running Spark version 3.2.0-SNAPSHOT
21/02/14 10:02:29 INFO ResourceUtils: ==============================================================
21/02/14 10:02:29 INFO ResourceUtils: No custom resources configured for spark.driver.
21/02/14 10:02:29 INFO ResourceUtils: ==============================================================
...
21/02/14 10:03:17 INFO ShutdownHookManager: Deleting directory /var/data/spark-fa6961ed-a2c1-444c-bfeb-20e63ba0b5cf/spark-ab4b0287-6e24-4b39-837e-9b0b62c1f26f
21/02/14 10:03:17 INFO ShutdownHookManager: Deleting directory /tmp/spark-d6b11e7d-6a03-4a1d-8559-37cb853319bf
21/02/14 11:05:34.279 ScalaTest-main-running-KubernetesSuite INFO KubernetesSuite: END driver POD log
```
Closes#31561 from attilapiros/SPARK-34426.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
Allow users to have Spark attempt to decommission excluded executors.
Since excluded executors may be flaky, this also adds the ability for users to specify a time limit after which a decommissioning executor will be killed by Spark.
### Why are the changes needed?
This may help prevent fetch failures from excluded executors, and also handle the situation in which executors
### Does this PR introduce _any_ user-facing change?
Yes, two new configuration flags for the behaviour.
### How was this patch tested?
Extended unit and integration tests.
Closes#31539 from holdenk/re=enable-SPARK-34104-SPARK-34105.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
Allow users to have Spark attempt to decommission excluded executors.
Since excluded executors may be flaky, this also adds the ability for users to specify a time limit after which a decommissioning executor will be killed by Spark.
### Why are the changes needed?
This may help prevent fetch failures from excluded executors, and also handle the situation in which executors
### Does this PR introduce _any_ user-facing change?
Yes, two new configuration flags for the behaviour.
### How was this patch tested?
Extended unit and integration tests.
Closes#31249 from holdenk/configure-inaccessibleList-kill-to-use-decommissioning.
Lead-authored-by: Holden Karau <hkarau@apple.com>
Co-authored-by: Holden Karau <holden@pigscanfly.ca>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
Fixing identification of timed-out pending pod requests as excess requests to delete when the excess is higher than the newly created timed out requests and there is some non-timed out newly created requests too.
### Why are the changes needed?
After https://github.com/apache/spark/pull/29981 only timed out newly created requests and timed out pending requests are taken as excess request.
But there is small bug when the excess is higher than the newly created timed out requests and there is some non-timed out newly created requests as well. Because all the newly created requests are counted as excess request when items are chosen from the timed out pod pending requests.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
There is new unit test added: `SPARK-34334: correctly identify timed out pending pod requests as excess`.
Closes#31445 from attilapiros/SPARK-34334.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR aims to fix `KubernetesClusterSchedulerBackend.stop` to wrap `super.stop` with `Utils.tryLogNonFatalError`.
### Why are the changes needed?
[CoarseGrainedSchedulerBackend.stop](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala#L559) may throw `SparkException` and this causes K8s resource (pod and configmap) leakage.
### Does this PR introduce _any_ user-facing change?
No. This is a bug fix.
### How was this patch tested?
Pass the CI with the newly added test case.
Closes#31533 from dongjoon-hyun/SPARK-34407.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
`Mockito.initMocks(Object)` is a deprecated api, should use `Mockito.openMocks(Object).close()` instead.
### Why are the changes needed?
Cleanup deprecation api usage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#31487 from LuciferYang/mockito-api.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to add a new configuration `spark.kubernetes.executor.disableConfigMap`.
### Why are the changes needed?
This can be use to disable config map creating for executor pods due to https://github.com/apache/spark/pull/27735 .
### Does this PR introduce _any_ user-facing change?
No. By default, this doesn't change AS-IS behavior.
This is a new feature to add an ability to disable SPARK-30985.
### How was this patch tested?
Pass the newly added UT.
Closes#31428 from dongjoon-hyun/SPARK-34316.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Fixing the flaky `handle large number of containers and tasks (SPARK-18750)` by avoiding to use `DNSToSwitchMapping` as in some situation DNS lookup could be extremely slow.
### Why are the changes needed?
After https://github.com/apache/spark/pull/31363 was merged the flaky `handle large number of containers and tasks (SPARK-18750)` test failed again in some other PRs but now we have the exact place where the test is stuck.
It is in the DNS lookup:
```
[info] - handle large number of containers and tasks (SPARK-18750) *** FAILED *** (30 seconds, 4 milliseconds)
[info] Failed with an exception or a timeout at thread join:
[info]
[info] java.lang.RuntimeException: Timeout at waiting for thread to stop (its stack trace is added to the exception)
[info] at java.net.Inet6AddressImpl.lookupAllHostAddr(Native Method)
[info] at java.net.InetAddress$2.lookupAllHostAddr(InetAddress.java:929)
[info] at java.net.InetAddress.getAddressesFromNameService(InetAddress.java:1324)
[info] at java.net.InetAddress.getAllByName0(InetAddress.java:1277)
[info] at java.net.InetAddress.getAllByName(InetAddress.java:1193)
[info] at java.net.InetAddress.getAllByName(InetAddress.java:1127)
[info] at java.net.InetAddress.getByName(InetAddress.java:1077)
[info] at org.apache.hadoop.net.NetUtils.normalizeHostName(NetUtils.java:568)
[info] at org.apache.hadoop.net.NetUtils.normalizeHostNames(NetUtils.java:585)
[info] at org.apache.hadoop.net.CachedDNSToSwitchMapping.resolve(CachedDNSToSwitchMapping.java:109)
[info] at org.apache.spark.deploy.yarn.SparkRackResolver.coreResolve(SparkRackResolver.scala:75)
[info] at org.apache.spark.deploy.yarn.SparkRackResolver.resolve(SparkRackResolver.scala:66)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy.$anonfun$localityOfRequestedContainers$3(LocalityPreferredContainerPlacementStrategy.scala:142)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy$$Lambda$658/1080992036.apply$mcVI$sp(Unknown Source)
[info] at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:158)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy.localityOfRequestedContainers(LocalityPreferredContainerPlacementStrategy.scala:138)
[info] at org.apache.spark.deploy.yarn.LocalityPlacementStrategySuite.org$apache$spark$deploy$yarn$LocalityPlacementStrategySuite$$runTest(LocalityPlacementStrategySuite.scala:94)
[info] at org.apache.spark.deploy.yarn.LocalityPlacementStrategySuite$$anon$1.run(LocalityPlacementStrategySuite.scala:40)
[info] at java.lang.Thread.run(Thread.java:748) (LocalityPlacementStrategySuite.scala:61)
...
```
This could be because of the DNS servers used by those build machines are not configured to handle IPv6 queries and the client has to wait for the IPv6 query to timeout before falling back to IPv4.
This even make the tests more consistent. As when a single host was given to lookup via `resolve(hostName: String)` it gave a different answer from calling `resolve(hostNames: Seq[String])` with a `Seq` containing that single host.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit tests.
Closes#31397 from attilapiros/SPARK-34154-2nd.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to remove `internal()` from `spark.kubernetes.executor.podNamePrefix` in order to make it the configuration public.
### Why are the changes needed?
In line with K8s GA, this will allow some users control the full executor pod names officially.
This is useful when we want a custom executor pod name pattern independently from the app name.
### Does this PR introduce _any_ user-facing change?
No, this has been there since Apache Spark 2.3.0.
### How was this patch tested?
N/A.
Closes#31386 from dongjoon-hyun/SPARK-34281.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR extends the `handle large number of containers and tasks (SPARK-18750)` test with a time limit and in case of timeout it saves the stack trace of the running thread to provide extra information about the reason why it got stuck.
### Why are the changes needed?
This is a flaky test which sometime runs for hours without stopping.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I checked it with a temporary code change: by adding a `Thread.sleep` to `LocalityPreferredContainerPlacementStrategy#expectedHostToContainerCount`.
The stack trace showed the correct method:
```
[info] LocalityPlacementStrategySuite:
[info] - handle large number of containers and tasks (SPARK-18750) *** FAILED *** (30 seconds, 26 milliseconds)
[info] Failed with an exception or a timeout at thread join:
[info]
[info] java.lang.RuntimeException: Timeout at waiting for thread to stop (its stack trace is added to the exception)
[info] at java.lang.Thread.sleep(Native Method)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy.$anonfun$expectedHostToContainerCount$1(LocalityPreferredContainerPlacementStrategy.scala:198)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy$$Lambda$281/381161906.apply(Unknown Source)
[info] at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
[info] at scala.collection.TraversableLike$$Lambda$16/322836221.apply(Unknown Source)
[info] at scala.collection.immutable.HashMap$HashMap1.foreach(HashMap.scala:234)
[info] at scala.collection.immutable.HashMap$HashTrieMap.foreach(HashMap.scala:468)
[info] at scala.collection.immutable.HashMap$HashTrieMap.foreach(HashMap.scala:468)
[info] at scala.collection.TraversableLike.map(TraversableLike.scala:238)
[info] at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
[info] at scala.collection.AbstractTraversable.map(Traversable.scala:108)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy.expectedHostToContainerCount(LocalityPreferredContainerPlacementStrategy.scala:188)
[info] at org.apache.spark.deploy.yarn.LocalityPreferredContainerPlacementStrategy.localityOfRequestedContainers(LocalityPreferredContainerPlacementStrategy.scala:112)
[info] at org.apache.spark.deploy.yarn.LocalityPlacementStrategySuite.org$apache$spark$deploy$yarn$LocalityPlacementStrategySuite$$runTest(LocalityPlacementStrategySuite.scala:94)
[info] at org.apache.spark.deploy.yarn.LocalityPlacementStrategySuite$$anon$1.run(LocalityPlacementStrategySuite.scala:40)
[info] at java.lang.Thread.run(Thread.java:748) (LocalityPlacementStrategySuite.scala:61)
...
```
Closes#31363 from attilapiros/SPARK-34154.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Using a function like `.mkString` or `.getLines` directly on a `scala.io.Source` opened by `fromFile`, `fromURL`, `fromURI ` will leak the underlying file handle, this pr use the `Utils.tryWithResource` method wrap the `BufferedSource` to ensure these `BufferedSource` closed.
### Why are the changes needed?
Avoid file handle leak.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#31323 from LuciferYang/source-not-closed.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
`KubernetesClusterManager` and `ExecutorPodsLifecycleManager` are private Spark classes.
This PR aims to move `Guava Cache` from a constructor parameter to private field of `ExecutorPodsLifecycleManager`.
### Why are the changes needed?
1. Although `KubernetesClusterManager` creates `Guava Cache`, only `ExecutorPodsLifecycleManager` uses it.
2. Although `ExecutorPodsLifecycleManager` is a Spark private class, when some users implement a new cluster manager with `ExternalClusterManager` for K8s, they can reuse `ExecutorPodsLifecycleManager`. In this case, `Guava Cache` is not good as an interface because it's a shaded class.
### Does this PR introduce _any_ user-facing change?
No. This is an Spark private.
### How was this patch tested?
Pass the existing UTs.
Closes#31297 from dongjoon-hyun/SPARK-34206.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This:
1. switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x.
2. upgrade built-in version for Hadoop 3.x to Hadoop 3.2.2
Note that for Hadoop 2.7, we'll still use the same modules such as hadoop-client.
In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties:
```
hadoop-client-api.artifact
hadoop-client-runtime.artifact
hadoop-client-minicluster.artifact
```
which default to:
```
hadoop-client-api
hadoop-client-runtime
hadoop-client-minicluster
```
but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`.
Besides above, there are the following changes:
- explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars.
- removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API.
- modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests).
### Why are the changes needed?
Hadoop 3.2.2 is released with new features and bug fixes, so it's good for the Spark community to adopt it. However, latest Hadoop versions starting from Hadoop 3.2.1 have upgraded to use Guava 27+. In order to resolve Guava conflicts, this takes the approach by switching to shaded client jars provided by Hadoop. This also has the benefits of avoid pulling other 3rd party dependencies from Hadoop side so as to avoid more potential future conflicts.
### Does this PR introduce _any_ user-facing change?
When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts.
### How was this patch tested?
Relying on existing tests.
Closes#30701 from sunchao/test-hadoop-3.2.2.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
There are some redundant collection conversion can be removed, for version compatibility, clean up these with Scala-2.13 profile.
### Why are the changes needed?
Remove redundant collection conversion
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Pass the Jenkins or GitHub Action
- Manual test `core`, `graphx`, `mllib`, `mllib-local`, `sql`, `yarn`,`kafka-0-10` in Scala 2.13 passed
Closes#31125 from LuciferYang/SPARK-34068.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Missing POD detection is extended by timestamp (and time limit) based check to avoid wrongfully detection of missing POD detection.
The two new timestamps:
- `fullSnapshotTs` is introduced for the `ExecutorPodsSnapshot` which only updated by the pod polling snapshot source
- `registrationTs` is introduced for the `ExecutorData` and it is initialized at the executor registration at the scheduler backend
Moreover a new config `spark.kubernetes.executor.missingPodDetectDelta` is used to specify the accepted delta between the two.
### Why are the changes needed?
Watching a POD (`ExecutorPodsWatchSnapshotSource`) only inform about single POD changes. This could wrongfully lead to detecting of missing PODs (PODs known by scheduler backend but missing from POD snapshots) by the executor POD lifecycle manager.
A key indicator of this error is seeing this log message:
> "The executor with ID [some_id] was not found in the cluster but we didn't get a reason why. Marking the executor as failed. The executor may have been deleted but the driver missed the deletion event."
So one of the problem is running the missing POD detection check even when a single POD is changed without having a full consistent snapshot about all the PODs (see `ExecutorPodsPollingSnapshotSource`).
The other problem could be the race between the executor POD lifecycle manager and the scheduler backend: so even in case of a having a full snapshot the registration at the scheduler backend could precede the snapshot polling (and processing of those polled snapshots).
### Does this PR introduce _any_ user-facing change?
Yes. When the POD is missing then the reason message explaining the executor's exit is extended with both timestamps (the polling time and the executor registration time) and even the new config is mentioned.
### How was this patch tested?
The existing unit tests are extended.
Closes#30675 from attilapiros/SPARK-33711.
Authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR is basically a followup of https://github.com/apache/spark/pull/14332.
Calling `map` alone might leave it not executed due to lazy evaluation, e.g.)
```
scala> val foo = Seq(1,2,3)
foo: Seq[Int] = List(1, 2, 3)
scala> foo.map(println)
1
2
3
res0: Seq[Unit] = List((), (), ())
scala> foo.view.map(println)
res1: scala.collection.SeqView[Unit,Seq[_]] = SeqViewM(...)
scala> foo.view.foreach(println)
1
2
3
```
We should better use `foreach` to make sure it's executed where the output is unused or `Unit`.
### Why are the changes needed?
To prevent the potential issues by not executing `map`.
### Does this PR introduce _any_ user-facing change?
No, the current codes look not causing any problem for now.
### How was this patch tested?
I found these item by running IntelliJ inspection, double checked one by one, and fixed them. These should be all instances across the codebase ideally.
Closes#31110 from HyukjinKwon/SPARK-34059.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
Label both the statuses and ensure the ExecutorPodSnapshot starts with the default config to match.
### Why are the changes needed?
The current test depends on the order rather than testing the desired property.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Labeled the containers statuses, observed failures, added the default label as the initialization point, tests passed again.
Built Spark, ran on K8s cluster verified no NPE in driver log.
Closes#31071 from holdenk/SPARK-34018-finishedExecutorWithRunningSidecar-doesnt-correctly-constructt-the-test-case.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Skip files if they are binary or very large to fit the configMap's max size.
### Why are the changes needed?
Config map cannot hold binary files and there is also a limit on how much data a configMap can hold.
This limit can be configured by the k8s cluster admin. This PR, skips such files (with a warning) instead of failing with weird runtime errors.
If such files are not skipped, then it would result in mount errors or encoding errors (if binary files are submitted).
### Does this PR introduce _any_ user-facing change?
yes, in simple words avoids possible errors due to negligence (for example, placing a large file or a binary file in SPARK_CONF_DIR) and thus improves user experience.
### How was this patch tested?
Added relevant tests and improved existing tests.
Closes#30472 from ScrapCodes/SPARK-32221/avoid-conf-propagate-errors.
Lead-authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Co-authored-by: Prashant Sharma <prashant@apache.org>
Signed-off-by: Prashant Sharma <prashsh1@in.ibm.com>
### What changes were proposed in this pull request?
Switch log level from warn to debug when the spark container is not present in the pod's container statuses.
### Why are the changes needed?
There are many non-critical situations where the Spark container may not be present, and the warning log level is too high.
### Does this PR introduce _any_ user-facing change?
Log message change.
### How was this patch tested?
N/A
Closes#31047 from holdenk/SPARK-33874-follow-up.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
For liveness check when checkAllContainers is not set, we check the liveness status of the Spark container if we can find it.
### Why are the changes needed?
Some environments may deploy long lived logs collecting side cars which outlive the Spark application. Just because they remain alive does not mean the Spark executor should keep running.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Extended the existing pod status tests.
Closes#30892 from holdenk/SPARK-33874-handle-long-lived-sidecars.
Lead-authored-by: Holden Karau <hkarau@apple.com>
Co-authored-by: Holden Karau <holden@pigscanfly.ca>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a simple change to support allocating a specified amount of overhead memory for the driver's mesos container. This is already supported for executors.
### Why are the changes needed?
This is needed to keep the driver process from exceeding memory limits and being killed off when running on mesos.
### Does this PR introduce _any_ user-facing change?
Yes, it adds a `spark.mesos.driver.memoryOverhead` configuration option. Documentation changes for this option are included in the PR.
### How was this patch tested?
Test cases covering allocation of driver memory overhead are included in the changes.
### Other notes
This is a second attempt to get this change reviewed, accepted and merged. The original pull request was closed as stale back in January: https://github.com/apache/spark/pull/21006.
For this pull request, I took the original change by pmackles, rebased it onto the current master branch, and added a test case that was requested in the original code review.
I'm happy to make any further edits or do anything needed so that this can be included in a future spark release. I keep having to build custom spark distributions so that we can use spark within our mesos clusters.
Closes#30739 from dmcwhorter/dmcwhorter-SPARK-22256.
Lead-authored-by: David McWhorter <david_mcwhorter@premierinc.com>
Co-authored-by: Paul Mackles <pmackles@adobe.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR proposes:
- Respect `PYSPARK_PYTHON` and `PYSPARK_DRIVER_PYTHON` environment variables, or `spark.pyspark.python` and `spark.pyspark.driver.python` configurations in Kubernates just like other cluster types in Spark.
- Depreate `spark.kubernetes.pyspark.pythonVersion` and guide users to set the environment variables and configurations for Python executables.
NOTE that `spark.kubernetes.pyspark.pythonVersion` is already a no-op configuration without this PR. Default is `3` and other values are disallowed.
- In order for Python executable settings to be consistently used, fix `spark.archives` option to unpack into the current working directory in the driver of Kubernates' cluster mode. This behaviour is identical with Yarn's cluster mode. By doing this, users can leverage Conda or virtuenenv in cluster mode as below:
```python
conda create -y -n pyspark_conda_env -c conda-forge pyarrow pandas conda-pack
conda activate pyspark_conda_env
conda pack -f -o pyspark_conda_env.tar.gz
PYSPARK_PYTHON=./environment/bin/python spark-submit --archives pyspark_conda_env.tar.gz#environment app.py
```
- Removed several unused or useless codes such as `extractS3Key` and `renameResourcesToLocalFS`
### Why are the changes needed?
- To provide a consistent support of PySpark by using `PYSPARK_PYTHON` and `PYSPARK_DRIVER_PYTHON` environment variables, or `spark.pyspark.python` and `spark.pyspark.driver.python` configurations.
- To provide Conda and virtualenv support via `spark.archives` options.
### Does this PR introduce _any_ user-facing change?
Yes:
- `spark.kubernetes.pyspark.pythonVersion` is deprecated.
- `PYSPARK_PYTHON` and `PYSPARK_DRIVER_PYTHON` environment variables, and `spark.pyspark.python` and `spark.pyspark.driver.python` configurations are respected.
### How was this patch tested?
Manually tested via:
```bash
minikube delete
minikube start --cpus 12 --memory 16384
kubectl create namespace spark-integration-test
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ServiceAccount
metadata:
name: spark
namespace: spark-integration-test
EOF
kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount=spark-integration-test:spark --namespace=spark-integration-test
dev/make-distribution.sh --pip --tgz -Pkubernetes
resource-managers/kubernetes/integration-tests/dev/dev-run-integration-tests.sh --spark-tgz `pwd`/spark-3.2.0-SNAPSHOT-bin-3.2.0.tgz --service-account spark --namespace spark-integration-test
```
Unittests were also added.
Closes#30735 from HyukjinKwon/SPARK-33748.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Add a developer API for custom driver & executor feature steps.
### Why are the changes needed?
While we allow templates for the basis of pod creation, some deployments need more flexibility in how the pods are configured. This adds a developer API for custom deployments.
### Does this PR introduce _any_ user-facing change?
New developer API.
### How was this patch tested?
Extended tests to verify custom step is applied when configured.
Closes#30206 from holdenk/SPARK-33261-allow-people-to-extend-pod-feature-steps.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
Check that the pod state is not pending or running even if there is a deletion timestamp.
### Why are the changes needed?
This can occur when the pod state and deletion timestamp are not updated by etcd in sync & we get a pod snapshot during an inconsistent view.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manual testing with local version of Minikube on an overloaded computer that caused out of sync updates.
Closes#30693 from holdenk/SPARK-33716-decommissioning-race-condition-during-pod-snapshot.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
TO FIX flaky tests:
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/132345/testReport/
```
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.JDBC query execution
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.Checks Hive version
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.SPARK-24829 Checks cast as float
```
The root cause here is a jar conflict issue.
`NewCookie.isHttpOnly` is not defined in the `jsr311-api.jar` which conflicts
The transitive artifact `jsr311-api.jar` of `hadoop-client` is excluded at the maven side. See https://issues.apache.org/jira/browse/SPARK-27179.
The Jenkins PR builder and Github Action use `SBT` as the compiler tool.
First, the exclusion rule from maven is not followed by sbt, so I was able to see `jsr311-api.jar` from maven cache to be added to the classpath directly. **This seems to be a bug of `sbt-pom-reader` plugin but I'm not that sure.**
Then I added an `ExcludeRule` for the `hive-thriftserver` module at the SBT side and did see the `jsr311-api.jar` gone, but the CI jobs still failed with the same error.
I added a trace log in ThriftHttpServlet
```s
ERROR ThriftHttpServlet: !!!!!!!!! Suspect???????? --->
file:/home/jenkins/workspace/SparkPullRequestBuilder/assembly/target/scala-2.12/jars/jsr311-api-1.1.1.jar
```
And the log pointed out that the assembly phase copied it to `assembly/target/scala-2.12/jars/` which will be added to the classpath too. With the help of SBT `dependencyTree` tool, I saw the `jsr311-api` again as a transitive of `jersery-core` from `yarn` module with a `test` scope. So **This seems to be another bug from the SBT side of the `sbt-assembly` plugin.** It copied a test scope transitive artifact to the assembly output.
In this PR, I defined some rules in SparkBuild.scala to bypass the potential bugs from the SBT side.
First, exclude the `jsr311` from all over the project and then add it back separately to the YARN module for SBT.
Additionally, the HiveThriftServerSuites was reflected for reducing flakiness too, but not related to the bugs I have found so far.
### Why are the changes needed?
fix test here
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
passing jenkins and ga
Closes#30643 from yaooqinn/HiveThriftHttpServerSuite.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR updates `kubernetes/integration-tests/README.md`.
### Why are the changes needed?
To follow the current Hadoop profile (hadoop-3.2).
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I have confirmed that the integration tests pass with the following command for both Hadoop 3.2 an 2.7.
```
build/mvn integration-test -am -pl :spark-kubernetes-integration-tests_2.12 \
-Pkubernetes \
-Pkubernetes-integration-tests \
-Dspark.kubernetes.test.imageTag=${IMAGE_TAG} \
-Dspark.kubernetes.test.imageRepo=docker.io/kubespark \
-Dspark.kubernetes.test.namespace=default \
-Dspark.kubernetes.test.deployMode=minikube \
-Dtest.include.tags=k8s
```
Closes#30726 from sarutak/update-kube-integ-readme.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR changes `Minikube.scala` for Kubernetes integration tests to work with Minikube 1.9+.
`Minikube.scala` assumes that `apiserver.key` and `apiserver.crt` are in `~/.minikube/`.
But as of Minikube 1.9, they are in `~/.minikube/profiles/<profile>`.
### Why are the changes needed?
Currently, Kubernetes integration tests doesn't work with Minikube 1.9+.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I confirmed the following test passes.
```
$ build/sbt -Pkubernetes -Pkubernetes-integration-tests package 'kubernetes-integration-tests/testOnly -- -z "SparkPi with no"'
```
Closes#30700 from sarutak/minikube-1.9.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Makes the location of the decommission script used in Kubernetes for graceful shutdown configurable.
### Why are the changes needed?
Some environments don't use the Spark image builder and instead mount the decompressed Spark distro. In those envs configuring the location of the decommissioning script is required.
### Does this PR introduce _any_ user-facing change?
New configuration parameter.
### How was this patch tested?
Existing decommissioning integration test.
Closes#30694 from holdenk/SPARK-33724-allow-decommissioning-script-location-to-be-configured.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
While building R docker image if we can't fetch the key from gnupg.net fall back to openpgp.org
### Why are the changes needed?
gnupg.net key servers are flaky and sometimes fail to resolve or return keys.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Tried to add key on my desktop, it failed, then tried to add key with openpgp.org and it succeed.
Closes#30696 from holdenk/SPARK-33727-gnupg-server-is-flaky.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This change make InterruptedIOException to be treated as InterruptedException when closing YarnClientSchedulerBackend, which doesn't log error with "YARN application has exited unexpectedly xxx"
### Why are the changes needed?
For YarnClient mode, when stopping YarnClientSchedulerBackend, it first tries to interrupt Yarn application monitor thread. In MonitorThread.run() it catches InterruptedException to gracefully response to stopping request.
But client.monitorApplication method also throws InterruptedIOException when the hadoop rpc call is calling. In this case, MonitorThread will not know it is interrupted, a Yarn App failed is returned with "Failed to contact YARN for application xxxxx; YARN application has exited unexpectedly with state xxxxx" is logged with error level. which confuse user a lot.
### Does this PR introduce _any_ user-facing change?
Yes
### How was this patch tested?
very simple patch, seems no need?
Closes#30617 from sqlwindspeaker/yarn-client-interrupt-monitor.
Authored-by: suqilong <suqilong@qiyi.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
Fix flaky test "Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties."
The test is flaking, with multiple flaked instances - the reason for the failure has been similar to:
```
The code passed to eventually never returned normally. Attempted 109 times over 3.0079882413999997 minutes. Last failure message: Failure executing: GET at:
https://192.168.39.167:8443/api/v1/namespaces/b37fc72a991b49baa68a2eaaa1516463/pods/spark-pi-97a9bc76308e7fe3-exec-1/log?pretty=false. Message: pods "spark-pi-97a9bc76308e7fe3-exec-1" not found. Received status: Status(apiVersion=v1, code=404, details=StatusDetails(causes=[], group=null, kind=pods, name=spark-pi-97a9bc76308e7fe3-exec-1, retryAfterSeconds=null, uid=null, additionalProperties={}), kind=Status, message=pods "spark-pi-97a9bc76308e7fe3-exec-1" not found, metadata=ListMeta(_continue=null, remainingItemCount=null, resourceVersion=null, selfLink=null, additionalProperties={}), reason=NotFound, status=Failure, additionalProperties={}).. (KubernetesSuite.scala:402)
```
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/36854/consolehttps://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/36852/consolehttps://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/36850/consolehttps://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/36848/console
From the above failures, it seems, that executor finishes too quickly and is removed by spark before the test can complete.
So, in order to mitigate this situation, one way is to turn on the flag
"spark.kubernetes.executor.deleteOnTermination"
### Why are the changes needed?
Fixes a flaky test.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing tests.
May be a few runs of jenkins integration test, may reveal if the problem is resolved or not.
Closes#30616 from ScrapCodes/SPARK-33668/fix-flaky-k8s-integration-test.
Authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to update `master` branch version to 3.2.0-SNAPSHOT.
### Why are the changes needed?
Start to prepare Apache Spark 3.2.0.
### Does this PR introduce _any_ user-facing change?
N/A.
### How was this patch tested?
Pass the CIs.
Closes#30606 from dongjoon-hyun/SPARK-3.2.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR proposes to make `spark.archives` configuration working in Kubernates.
It works without a problem in standalone cluster but there seems a bug in Kubernates.
It fails to fetch the file on the driver side as below:
```
20/12/03 13:33:53 INFO SparkContext: Added JAR file:/tmp/spark-75004286-c83a-4369-b624-14c5d2d2a748/spark-examples_2.12-3.1.0-SNAPSHOT.jar at spark://spark-test-app-48ae737628cee6f8-driver-svc.spark-integration-test.svc:7078/jars/spark-examples_2.12-3.1.0-SNAPSHOT.jar with timestamp 1607002432558
20/12/03 13:33:53 INFO SparkContext: Added archive file:///tmp/tmp4542734800151332666.txt.tar.gz#test_tar_gz at spark://spark-test-app-48ae737628cee6f8-driver-svc.spark-integration-test.svc:7078/files/tmp4542734800151332666.txt.tar.gz with timestamp 1607002432558
20/12/03 13:33:53 INFO TransportClientFactory: Successfully created connection to spark-test-app-48ae737628cee6f8-driver-svc.spark-integration-test.svc/172.17.0.4:7078 after 83 ms (47 ms spent in bootstraps)
20/12/03 13:33:53 INFO Utils: Fetching spark://spark-test-app-48ae737628cee6f8-driver-svc.spark-integration-test.svc:7078/files/tmp4542734800151332666.txt.tar.gz to /tmp/spark-66573e24-27a3-427c-99f4-36f06d9e9cd5/fetchFileTemp2665785666227461849.tmp
20/12/03 13:33:53 ERROR SparkContext: Error initializing SparkContext.
java.lang.RuntimeException: Stream '/files/tmp4542734800151332666.txt.tar.gz' was not found.
at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:242)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:142)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:53)
```
This is because `spark.archives` was not actually added on the driver side correctly. The changes here fix it by adding and resolving URIs correctly.
### Why are the changes needed?
`spark.archives` feature can be leveraged for many things such as Conda support. We should make it working in Kubernates as well.
This is a bug fix too.
### Does this PR introduce _any_ user-facing change?
No, this feature is not out yet.
### How was this patch tested?
I manually tested with Minikube 1.15.1. For an environment issue (?), I had to use a custom namespace, service account and roles. `default` service account does not work for me and complains it doesn't have permissions to get/list pods, etc.
```bash
minikube delete
minikube start --cpus 12 --memory 16384
kubectl create namespace spark-integration-test
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ServiceAccount
metadata:
name: spark
namespace: spark-integration-test
EOF
kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount=spark-integration-test:spark --namespace=spark-integration-test
dev/make-distribution.sh --pip --tgz -Pkubernetes
resource-managers/kubernetes/integration-tests/dev/dev-run-integration-tests.sh --spark-tgz `pwd`/spark-3.1.0-SNAPSHOT-bin-3.2.0.tgz --service-account spark --namespace spark-integration-test
```
Closes#30581 from HyukjinKwon/SPARK-33615.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Allow k8s integration tests to assert both driver and executor logs for expected log(s)
### Why are the changes needed?
Some of the tests will be able to provide full coverage of the use case, by asserting both driver and executor logs.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
TBD
Closes#30568 from ScrapCodes/expectedDriverLogChanges.
Authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
As described in SPARK-33557, `HeartbeatReceiver` and `MesosCoarseGrainedSchedulerBackend` will always use `Network.NETWORK_TIMEOUT.defaultValueString` as value of `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT` when we configure `NETWORK_TIMEOUT` without configure `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT`, this is different from the relationship described in `configuration.md`.
To fix this problem，the main change of this pr as follow:
- Remove the explicitly default value of `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT`
- Use actual value of `NETWORK_TIMEOUT` as `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT` when `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT` not configured in `HeartbeatReceiver` and `MesosCoarseGrainedSchedulerBackend`
### Why are the changes needed?
To ensure the relationship between `NETWORK_TIMEOUT` and `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT` as we described in `configuration.md`
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Pass the Jenkins or GitHub Action
- Manual test configure `NETWORK_TIMEOUT` and `STORAGE_BLOCKMANAGER_HEARTBEAT_TIMEOUT` locally
Closes#30547 from LuciferYang/SPARK-33557.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This reverts commit SPARK-33212 (cb3fa6c936) mostly with three exceptions:
1. `SparkSubmitUtils` was updated recently by SPARK-33580
2. `resource-managers/yarn/pom.xml` was updated recently by SPARK-33104 to add `hadoop-yarn-server-resourcemanager` test dependency.
3. Adjust `com.fasterxml.jackson.module:jackson-module-jaxb-annotations` dependency in K8s module which is updated recently by SPARK-33471.
### Why are the changes needed?
According to [HADOOP-16080](https://issues.apache.org/jira/browse/HADOOP-16080) since Apache Hadoop 3.1.1, `hadoop-aws` doesn't work with `hadoop-client-api`. It fails at write operation like the following.
**1. Spark distribution with `-Phadoop-cloud`**
```scala
$ bin/spark-shell --conf spark.hadoop.fs.s3a.access.key=$AWS_ACCESS_KEY_ID --conf spark.hadoop.fs.s3a.secret.key=$AWS_SECRET_ACCESS_KEY
20/11/30 23:01:24 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context available as 'sc' (master = local[*], app id = local-1606806088715).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 3.1.0-SNAPSHOT
/_/
Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_272)
Type in expressions to have them evaluated.
Type :help for more information.
scala> spark.read.parquet("s3a://dongjoon/users.parquet").show
20/11/30 23:01:34 WARN MetricsConfig: Cannot locate configuration: tried hadoop-metrics2-s3a-file-system.properties,hadoop-metrics2.properties
+------+--------------+----------------+
| name|favorite_color|favorite_numbers|
+------+--------------+----------------+
|Alyssa| null| [3, 9, 15, 20]|
| Ben| red| []|
+------+--------------+----------------+
scala> Seq(1).toDF.write.parquet("s3a://dongjoon/out.parquet")
20/11/30 23:02:14 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)/ 1]
java.lang.NoSuchMethodError: org.apache.hadoop.util.SemaphoredDelegatingExecutor.<init>(Lcom/google/common/util/concurrent/ListeningExecutorService;IZ)V
```
**2. Spark distribution without `-Phadoop-cloud`**
```scala
$ bin/spark-shell --conf spark.hadoop.fs.s3a.access.key=$AWS_ACCESS_KEY_ID --conf spark.hadoop.fs.s3a.secret.key=$AWS_SECRET_ACCESS_KEY -c spark.eventLog.enabled=true -c spark.eventLog.dir=s3a://dongjoon/spark-events/ --packages org.apache.hadoop:hadoop-aws:3.2.0,org.apache.hadoop:hadoop-common:3.2.0
...
java.lang.NoSuchMethodError: org.apache.hadoop.util.SemaphoredDelegatingExecutor.<init>(Lcom/google/common/util/concurrent/ListeningExecutorService;IZ)V
at org.apache.hadoop.fs.s3a.S3AFileSystem.create(S3AFileSystem.java:772)
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI.
Closes#30508 from dongjoon-hyun/SPARK-33212-REVERT.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
TL;DR:
- This PR completes the support of archives in Spark itself instead of Yarn-only
- It makes `--archives` option work in other cluster modes too and adds `spark.archives` configuration.
- After this PR, PySpark users can leverage Conda to ship Python packages together as below:
```python
conda create -y -n pyspark_env -c conda-forge pyarrow==2.0.0 pandas==1.1.4 conda-pack==0.5.0
conda activate pyspark_env
conda pack -f -o pyspark_env.tar.gz
PYSPARK_DRIVER_PYTHON=python PYSPARK_PYTHON=./environment/bin/python pyspark --archives pyspark_env.tar.gz#environment
```
- Issue a warning that undocumented and hidden behavior of partial archive handling in `spark.files` / `SparkContext.addFile` will be deprecated, and users can use `spark.archives` and `SparkContext.addArchive`.
This PR proposes to add Spark's native `--archives` in Spark submit, and `spark.archives` configuration. Currently, both are supported only in Yarn mode:
```bash
./bin/spark-submit --help
```
```
Options:
...
Spark on YARN only:
--queue QUEUE_NAME The YARN queue to submit to (Default: "default").
--archives ARCHIVES Comma separated list of archives to be extracted into the
working directory of each executor.
```
This `archives` feature is useful often when you have to ship a directory and unpack into executors. One example is native libraries to use e.g. JNI. Another example is to ship Python packages together by Conda environment.
Especially for Conda, PySpark currently does not have a nice way to ship a package that works in general, please see also https://hyukjin-spark.readthedocs.io/en/stable/user_guide/python_packaging.html#using-zipped-virtual-environment (PySpark new documentation demo for 3.1.0).
The neatest way is arguably to use Conda environment by shipping zipped Conda environment but this is currently dependent on this archive feature. NOTE that we are able to use `spark.files` by relying on its undocumented behaviour that untars `tar.gz` but I don't think we should document such ways and promote people to more rely on it.
Also, note that this PR does not target to add the feature parity of `spark.files.overwrite`, `spark.files.useFetchCache`, etc. yet. I documented that this is an experimental feature as well.
### Why are the changes needed?
To complete the feature parity, and to provide a better support of shipping Python libraries together with Conda env.
### Does this PR introduce _any_ user-facing change?
Yes, this makes `--archives` works in Spark instead of Yarn-only, and adds a new configuration `spark.archives`.
### How was this patch tested?
I added unittests. Also, manually tested in standalone cluster, local-cluster, and local modes.
Closes#30486 from HyukjinKwon/native-archive.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a follow-on to PR #30096 which initially added support for printing direct links to the driver stdout/stderr logs from the application report output in `yarn.Client` using the `spark.yarn.includeDriverLogsLink` configuration. That PR made use of the ResourceManager's REST APIs to fetch the necessary information to construct the links. This PR proposes removing the dependency on the REST API, since the new logic is the only place in `yarn.Client` which makes use of this API, and instead leverages the RPC API via `YarnClient`, which brings the code in line with the rest of `yarn.Client`.
### Why are the changes needed?
While the old logic worked okay when running a Spark application in a "standard" environment with full access to Kerberos credentials, it can fail when run in an environment with restricted Kerberos credentials. In our case, this environment is represented by [Azkaban](https://azkaban.github.io/), but it likely affects other job scheduling systems as well. In such an environment, the application has delegation tokens which enabled it to communicate with services such as YARN, but the RM REST API is not typically covered by such delegation tokens (note that although YARN does actually support accessing the RM REST API via a delegation token as documented [here](https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/ResourceManagerRest.html#Cluster_Delegation_Tokens_API), it is a new feature in alpha phase, and most deployments are likely not retrieving this token today).
Besides this enhancement, leveraging the `YarnClient` APIs greatly simplifies the processing logic, such as removing all JSON parsing.
### Does this PR introduce _any_ user-facing change?
Very minimal user-facing changes on top of PR #30096. Basically expands the scope of environments in which that feature will operate correctly.
### How was this patch tested?
In addition to redoing the `spark-submit` testing as mentioned in PR #30096, I also tested this logic in a restricted-credentials environment (Azkaban). It succeeds where the previous logic would fail with a 401 error.
Closes#30450 from xkrogen/xkrogen-SPARK-33185-driverlogs-followon.
Authored-by: Erik Krogen <xkrogen@apache.org>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This PR intends to fix typos in the sub-modules:
* `R`
* `common`
* `dev`
* `mlib`
* `external`
* `project`
* `streaming`
* `resource-managers`
* `python`
Split per srowen https://github.com/apache/spark/pull/30323#issuecomment-728981618
NOTE: The misspellings have been reported at 706a726f87 (commitcomment-44064356)
### Why are the changes needed?
Misspelled words make it harder to read / understand content.
### Does this PR introduce _any_ user-facing change?
There are various fixes to documentation, etc...
### How was this patch tested?
No testing was performed
Closes#30402 from jsoref/spelling-R_common_dev_mlib_external_project_streaming_resource-managers_python.
Authored-by: Josh Soref <jsoref@users.noreply.github.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR aims the followings.
1. Upgrade from Scala 2.13.3 to 2.13.4 for Apache Spark 3.1
2. Fix exhaustivity issues in both Scala 2.12/2.13 (Scala 2.13.4 requires this for compilation.)
3. Enforce the improved exhaustive check by using the existing Scala 2.13 GitHub Action compilation job.
### Why are the changes needed?
Scala 2.13.4 is a maintenance release for 2.13 line and improves JDK 15 support.
- https://github.com/scala/scala/releases/tag/v2.13.4
Also, it improves exhaustivity check.
- https://github.com/scala/scala/pull/9140 (Check exhaustivity of pattern matches with "if" guards and custom extractors)
- https://github.com/scala/scala/pull/9147 (Check all bindings exhaustively, e.g. tuples components)
### Does this PR introduce _any_ user-facing change?
Yep. Although it's a maintenance version change, it's a Scala version change.
### How was this patch tested?
Pass the CIs and do the manual testing.
- Scala 2.12 CI jobs(GitHub Action/Jenkins UT/Jenkins K8s IT) to check the validity of code change.
- Scala 2.13 Compilation job to check the compilation
Closes#30455 from dongjoon-hyun/SCALA_3.13.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Driver side changes for coordinating push based shuffle by selecting external shuffle services for merging partitions.
This PR includes changes related to `ShuffleMapStage` preparation which is selection of merger locations and initializing them as part of `ShuffleDependency`.
Currently this code is not used as some of the changes would come subsequently as part of https://issues.apache.org/jira/browse/SPARK-32917 (shuffle blocks push as part of `ShuffleMapTask`), https://issues.apache.org/jira/browse/SPARK-32918 (support for finalize API) and https://issues.apache.org/jira/browse/SPARK-32920 (finalization of push/merge phase). This is why the tests here are also partial, once these above mentioned changes are raised as PR we will have enough tests for DAGScheduler piece of code as well.
### Why are the changes needed?
Added a new API in `SchedulerBackend` to get merger locations for push based shuffle. This is currently implemented for Yarn and other cluster managers can have separate implementations which is why a new API is introduced.
### Does this PR introduce _any_ user-facing change?
Yes, user facing config to enable push based shuffle is introduced
### How was this patch tested?
Added unit tests partially and some of the changes in DAGScheduler depends on future changes, DAGScheduler tests will be added along with those changes.
Lead-authored-by: Venkata krishnan Sowrirajan vsowrirajanlinkedin.com
Co-authored-by: Min Shen mshenlinkedin.com
Closes#30164 from venkata91/upstream-SPARK-32919.
Lead-authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com>
Co-authored-by: Min Shen <mshen@linkedin.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This pr add a new Scala compile arg to `pom.xml` to defense against new unused imports:
- `-Ywarn-unused-import` for Scala 2.12
- `-Wconf:cat=unused-imports:e` for Scala 2.13
The other fIles change are remove all unused imports in Spark code
### Why are the changes needed?
Cleanup code and add guarantee to defense against new unused imports
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#30351 from LuciferYang/remove-imports-core-module.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
Supports python client deps from the launcher fs.
This is a feature that was added for java deps. This PR adds support fo rpythona s well.
yes
Manually running different scenarios and via examining the driver & executors logs. Also there is an integration test added.
I verified that the python resources are added to the spark file server and they are named properly so they dont fail the executors. Note here that as previously the following will not work:
primary resource `A.py`: uses a closure defined in submited pyfile `B.py`, context.py only adds to the pythonpath files with certain extension eg. zip, egg, jar.
Closes#25870 from skonto/python-deps.
Lead-authored-by: Stavros Kontopoulos <skontopo@redhat.com>
Co-authored-by: Stavros Kontopoulos <st.kontopoulos@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade Kubernetes-client from 4.11.1 to 4.12.0
### Why are the changes needed?
This upgrades the dependency for Apache Spark 3.1.0.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#30401 from ramesh-muthusamy/SPARK-33471-k8s-clientupgrade.
Authored-by: Rameshkrishnan Muthusamy <rameshkrishnan_muthusamy@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Added integration test - which tries to configure a log4j.properties and checks if, it is the one pickup by the driver.
### Why are the changes needed?
Improved test coverage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running integration tests.
Closes#30388 from ScrapCodes/SPARK-32222/k8s-it-spark-conf-propagate.
Authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
I push this PR as I could not re-open the stale one https://github.com/apache/spark/pull/20665 .
As for Yarn or Kubernetes, Mesos users should be able to specify priority queues to define a workload management policy for queued drivers in the Mesos Cluster Dispatcher.
This would ensure scheduling order while enqueuing Spark applications for a Mesos cluster.
### Why are the changes needed?
Currently, submitted drivers are kept in order of their submission: the first driver added to the queue will be the first one to be executed (FIFO), regardless of their priority.
See https://issues.apache.org/jira/projects/SPARK/issues/SPARK-23499 for more details.
### Does this PR introduce _any_ user-facing change?
The MesosClusterDispatcher UI shows now Spark jobs along with the queue to which they are submitted.
### How was this patch tested?
Unit tests.
Also, this feature has been in production for 3 years now as we use a modified Spark 2.4.0 since then.
Closes#30352 from pgillet/mesos-scheduler-priority-queue.
Lead-authored-by: Pascal Gillet <pascal.gillet@stack-labs.com>
Co-authored-by: pgillet <pascalgillet@ymail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This is an improvement, we mount all the user specific configuration files(except the templates and spark properties files) from `SPARK_CONF_DIR` at the point of spark-submit, to both executor and driver pods. Currently, only `spark.properties` is mounted, only on driver.
### Why are the changes needed?
`SPARK_CONF_DIR` hosts several configuration files, for example,
1) `spark-defaults.conf` - containing all the spark properties.
2) `log4j.properties` - Logger configuration.
3) `core-site.xml` - Hadoop related configuration.
4) `fairscheduler.xml` - Spark's fair scheduling policy at the job level.
5) `metrics.properties` - Spark metrics.
6) Any user specific - library or framework specific configuration file.
At the moment, we can cannot propagate these files to the driver and executor configuration directory.
There is a design doc, with more details, and this patch is currently providing a reference implementation. Please take a look at the doc and comment, how we can improve. [google docs link to the doc](https://bit.ly/spark-30985)
### Further scope
Support user defined configMaps.
### Does this PR introduce any user-facing change?
Yes, previously the user configuration files(e.g. hdfs-site.xml, log4j.properties etc...) were not propagated by default, now after this patch it is propagated to driver and executor pods' `SPARK_CONF_DIR`.
### How was this patch tested?
Added tests.
Also manually tested, by deploying it to a minikube cluster and observing the additional configuration files were present, and taking effect. For example, changes to log4j.properties was properly applied to executors.
Closes#27735 from ScrapCodes/SPARK-30985/spark-conf-k8s-propagate.
Authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This pr fix type mismatch error:
```
[error] /home/jenkins/workspace/spark-master-test-sbt-hadoop-2.7-hive-2.3/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala:320:52: type mismatch;
[error] found : Long
[error] required: Int
[error] Resource.newInstance(resourcesWithDefaults.totalMemMiB, resourcesWithDefaults.cores)
[error] ^
[error] one error found
```
### Why are the changes needed?
Fix compile issue.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing test.
Closes#30375 from wangyum/SPARK-33288.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
### What changes were proposed in this pull request?
This is a follow-up fix for the failing tests in `YarnShuffleServiceSuite.java`. This java class was introduced in https://github.com/apache/spark/pull/30062. The tests in the class fail when run with hadoop-2.7 profile:
```
[ERROR] testCreateDefaultMergedShuffleFileManagerInstance(org.apache.spark.network.yarn.YarnShuffleServiceSuite) Time elapsed: 0.627 s <<< ERROR!
java.lang.NoClassDefFoundError: org/apache/commons/logging/LogFactory
at org.apache.spark.network.yarn.YarnShuffleServiceSuite.testCreateDefaultMergedShuffleFileManagerInstance(YarnShuffleServiceSuite.java:37)
Caused by: java.lang.ClassNotFoundException: org.apache.commons.logging.LogFactory
at org.apache.spark.network.yarn.YarnShuffleServiceSuite.testCreateDefaultMergedShuffleFileManagerInstance(YarnShuffleServiceSuite.java:37)
[ERROR] testCreateRemoteBlockPushResolverInstance(org.apache.spark.network.yarn.YarnShuffleServiceSuite) Time elapsed: 0 s <<< ERROR!
java.lang.NoClassDefFoundError: Could not initialize class org.apache.spark.network.yarn.YarnShuffleService
at org.apache.spark.network.yarn.YarnShuffleServiceSuite.testCreateRemoteBlockPushResolverInstance(YarnShuffleServiceSuite.java:47)
[ERROR] testInvalidClassNameOfMergeManagerWillUseNoOpInstance(org.apache.spark.network.yarn.YarnShuffleServiceSuite) Time elapsed: 0.001 s <<< ERROR!
java.lang.NoClassDefFoundError: Could not initialize class org.apache.spark.network.yarn.YarnShuffleService
at org.apache.spark.network.yarn.YarnShuffleServiceSuite.testInvalidClassNameOfMergeManagerWillUseNoOpInstance(YarnShuffleServiceSuite.java:57)
```
A test suit for `YarnShuffleService` did exist here:
`resource-managers/yarn/src/test/scala/org/apache/spark/network/yarn/YarnShuffleServiceSuite.scala`
I missed this when I created `common/network-yarn/src/test/java/org/apache/spark/network/yarn/YarnShuffleServiceSuite.java`. Moving all the new tests to the earlier test suite fixes the failures with hadoop-2.7 even though why this happened is not clear.
### Why are the changes needed?
The newly added tests are failing when run with hadoop profile 2.7
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Ran the unit tests with the default profile as well as hadoop 2.7 profile.
`build/mvn test -Dtest=none -DwildcardSuites=org.apache.spark.network.yarn.YarnShuffleServiceSuite -Phadoop-2.7 -Pyarn`
```
Run starting. Expected test count is: 11
YarnShuffleServiceSuite:
- executor state kept across NM restart
- removed applications should not be in registered executor file
- shuffle service should be robust to corrupt registered executor file
- get correct recovery path
- moving recovery file from NM local dir to recovery path
- service throws error if cannot start
- recovery db should not be created if NM recovery is not enabled
- SPARK-31646: metrics should be registered into Node Manager's metrics system
- create default merged shuffle file manager instance
- create remote block push resolver instance
- invalid class name of merge manager will use noop instance
Run completed in 2 seconds, 572 milliseconds.
Total number of tests run: 11
Suites: completed 2, aborted 0
Tests: succeeded 11, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#30349 from otterc/SPARK-32916-followup.
Authored-by: Chandni Singh <singh.chandni@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This adds support for Stage level scheduling to kubernetes. Kubernetes can support dynamic allocation via the shuffle tracking option which means we can support stage level scheduling by getting new executors.
The main changes here are having the k8s cluster manager pass the resource profile id into the executors and then the ExecutorsPodsAllocator has to request executors based on the individual resource profiles. I tried to keep code changes here to a minimum. I specifically choose to leave the ExecutorPodsSnapshot the way it was and construct the resource profile to pod states on the fly, with a fast path when not using other resource profiles, to keep the impact to a minimum. This results in the main changes required are just wrapping the allocation logic in a for loop over each profile. The other main change is in the basic feature step we have to look at the resources in the ResourceProfile to request pods with the correct resources. Much of the other logic like in the executor life cycle manager doesn't need to be resource profile.
This also adds support for [SPARK-32661]Spark executors on K8S should request extra memory for off-heap allocations because the stage level scheduling api has support for this and it made sense to make consistent with YARN. This was started with PR https://github.com/apache/spark/pull/29477 but never updated so I just did it here. To do this I moved a few functions around that were now used by both YARN and kubernetes so you will see some changes in Utils.
### Why are the changes needed?
Add the feature to Kubernetes based on customer feedback.
### Does this PR introduce _any_ user-facing change?
Yes the feature now works with K8s, but not underlying API changes.
### How was this patch tested?
Tested manually on kubernetes cluster and with unit tests.
Closes#30204 from tgravescs/stagek8sOrigSnapshotsRebase.
Lead-authored-by: Thomas Graves <tgraves@apache.org>
Co-authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR aims to use R 3.6.3 in K8s R image and re-enable `RTestsSuite`.
### Why are the changes needed?
Jenkins Server is using `R 3.6.3`.
```
+ SPARK_HOME=/home/jenkins/workspace/SparkPullRequestBuilder-K8s
+ /usr/bin/R CMD check --as-cran --no-tests SparkR_3.1.0.tar.gz
* using log directory ‘/home/jenkins/workspace/SparkPullRequestBuilder-K8s/R/SparkR.Rcheck’
* using R version 3.6.3 (2020-02-29)
```
OpenJDK docker image is using `R 3.5.2 (2018-12-20)` which is old and currently `spark-3.0.1` fails to run SparkR.
```
$ cd spark-3.0.1-bin-hadoop3.2
$ bin/docker-image-tool.sh -R kubernetes/dockerfiles/spark/bindings/R/Dockerfile -n build
...
exit code: 1
termination reason: Error
...
$ bin/spark-submit --master k8s://https://192.168.64.49:8443 --deploy-mode cluster --conf spark.kubernetes.container.image=spark-r:latest local:///opt/spark/examples/src/main/r/dataframe.R
$ k logs dataframe-r-b1c14b75b0c09eeb-driver
...
+ exec /usr/bin/tini -s -- /opt/spark/bin/spark-submit --conf spark.driver.bindAddress=172.17.0.4 --deploy-mode client --properties-file /opt/spark/conf/spark.properties --class org.apache.spark.deploy.RRunner local:///opt/spark/examples/src/main/r/dataframe.R
20/11/10 06:03:58 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
log4j:WARN No appenders could be found for logger (io.netty.util.internal.logging.InternalLoggerFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Error: package or namespace load failed for ‘SparkR’ in rbind(info, getNamespaceInfo(env, "S3methods")):
number of columns of matrices must match (see arg 2)
In addition: Warning message:
package ‘SparkR’ was built under R version 4.0.2
Execution halted
```
In addition, this PR aims to recover the test coverage.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass K8S IT Jenkins job.
Closes#30130 from dongjoon-hyun/SPARK-32354.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
There are two similar compilation warnings about procedure-like declaration in Scala 2.13:
```
[WARNING] [Warn] /spark/core/src/main/scala/org/apache/spark/HeartbeatReceiver.scala:70: procedure syntax is deprecated for constructors: add `=`, as in method definition
```
and
```
[WARNING] [Warn] /spark/core/src/main/scala/org/apache/spark/storage/BlockManagerDecommissioner.scala:211: procedure syntax is deprecated: instead, add `: Unit =` to explicitly declare `run`'s return type
```
this pr is the first part to resolve SPARK-33352：
- For constructors method definition add `=` to convert to function syntax
- For without `return type` methods definition add `: Unit =` to convert to function syntax
### Why are the changes needed?
Eliminate compilation warnings in Scala 2.13 and this change should be compatible with Scala 2.12
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#30255 from LuciferYang/SPARK-29392-FOLLOWUP.1.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Currently when run in `cluster` mode on YARN, the Spark `yarn.Client` will print out the application report into the logs, to be easily viewed by users. For example:
```
INFO yarn.Client:
client token: Token { kind: YARN_CLIENT_TOKEN, service: }
diagnostics: N/A
ApplicationMaster host: X.X.X.X
ApplicationMaster RPC port: 0
queue: default
start time: 1602782566027
final status: UNDEFINED
tracking URL: http://hostname:8888/proxy/application_<id>/
user: xkrogen
```
I propose adding, alongside the application report, some additional lines like:
```
Driver Logs (stdout): http://hostname:8042/node/containerlogs/container_<id>/xkrogen/stdout?start=-4096
Driver Logs (stderr): http://hostname:8042/node/containerlogs/container_<id>/xkrogen/stderr?start=-4096
```
This information isn't contained in the `ApplicationReport`, so it's necessary to query the ResourceManager REST API. For now I have added this as an always-on feature, but if there is any concern about adding this REST dependency, I think hiding this feature behind an off-by-default flag is reasonable.
### Why are the changes needed?
Typically, the tracking URL can be used to find the logs of the ApplicationMaster/driver while the application is running. Later, the Spark History Server can be used to track this information down, using the stdout/stderr links on the Executors page.
However, in the situation when the driver crashed _before_ writing out a history file, the SHS may not be aware of this application, and thus does not contain links to the driver logs. When this situation arises, it can be difficult for users to debug further, since they can't easily find their driver logs.
It is possible to reach the logs by using the `yarn logs` commands, but the average Spark user isn't aware of this and shouldn't have to be.
With this information readily available in the logs, users can quickly jump to their driver logs, even if it crashed before the SHS became aware of the application. This has the additional benefit of providing a quick way to access driver logs, which often contain useful information, in a single click (instead of navigating through the Spark UI).
### Does this PR introduce _any_ user-facing change?
Yes, some additional print statements will be created in the application report when using YARN in cluster mode.
### How was this patch tested?
Added unit tests for the parsing logic in `yarn.ClientSuite`. Also tested against a live cluster. When the driver is running:
```
INFO Client: Application report for application_XXXXXXXXX_YYYYYY (state: RUNNING)
INFO Client:
client token: Token { kind: YARN_CLIENT_TOKEN, service: }
diagnostics: N/A
ApplicationMaster host: host.example.com
ApplicationMaster RPC port: ######
queue: queue_name
start time: 1604529046091
final status: UNDEFINED
tracking URL: http://host.example.com:8080/proxy/application_XXXXXXXXX_YYYYYY/
user: xkrogen
Driver Logs (stdout): http://host.example.com:8042/node/containerlogs/container_e07_XXXXXXXXX_YYYYYY_01_000001/xkrogen/stdout?start=-4096
Driver Logs (stderr): http://host.example.com:8042/node/containerlogs/container_e07_XXXXXXXXX_YYYYYY_01_000001/xkrogen/stderr?start=-4096
INFO Client: Application report for application_XXXXXXXXX_YYYYYY (state: RUNNING)
```
I confirmed that when the driver has not yet launched, the report does not include the two Driver Logs items. Will omit the output here for brevity since it looks the same.
Closes#30096 from xkrogen/xkrogen-SPARK-33185-yarn-client-print.
Authored-by: Erik Krogen <xkrogen@apache.org>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `Kubernetes-client` from 4.10.3 to 4.11.1.
### Why are the changes needed?
This upgrades the dependency for Apache Spark 3.1.0.
Since 4.12.0 is still new and has a breaking API changes, this PR chooses the latest compatible one.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the all CIs including K8s IT.
Closes#30233 from dongjoon-hyun/SPARK-33324.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
this PR renames the blacklisting feature. I ended up using "excludeOnFailure" or "excluded" in most cases but there is a mix. I renamed the BlacklistTracker to HealthTracker, but for the TaskSetBlacklist HealthTracker didn't make sense to me since its not the health of the taskset itself but rather tracking the things its excluded on so I renamed it to be TaskSetExcludeList. Everything else I tried to use the context and in most cases excluded made sense. It made more sense to me then blocked since you are basically excluding those executors and nodes from scheduling tasks on them. Then can be unexcluded later after timeouts and such. The configs I changed the name to use excludeOnFailure which I thought explained it.
I unfortunately couldn't get rid of some of them because its part of the event listener and history files. To keep backwards compatibility I kept the events and some of the parsing so that the history server would still properly read older history files. It is not forward compatible though - meaning a new application write the "Excluded" events so the older history server won't properly read display them as being blacklisted.
A few of the files below are showing up as deleted and recreated even though I did a git mv on them. I'm not sure why.
### Why are the changes needed?
get rid of problematic language
### Does this PR introduce _any_ user-facing change?
Config name changes but the old configs still work but are deprecated.
### How was this patch tested?
updated tests and also manually tested the UI changes and manually tested the history server reading older versions of history files and vice versa.
Closes#29906 from tgravescs/SPARK-32037.
Lead-authored-by: Thomas Graves <tgraves@nvidia.com>
Co-authored-by: Thomas Graves <tgraves@apache.org>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
Add a test that pending executor does not stall pod allocation.
### Why are the changes needed?
Better test coverage
### Does this PR introduce _any_ user-facing change?
Test only change.
### How was this patch tested?
New test passes.
Closes#30205 from holdenk/verify-pod-allocation-does-not-stall.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Make pod allocation executor timeouts configurable. Keep all known pods in mind when allocating executors to avoid over-allocating if the pending time is much higher than the allocation interval.
This PR increases the default wait time to 600s from the current 60s.
Since nodes can now remain "pending" for long periods of time, we allow additional batches to be scheduled during pending allocation but keep the total number of pods in account.
### Why are the changes needed?
The current executor timeouts do not match that of all real world clusters especially under load. While this can be worked around by increasing the allocation batch delay, that will decrease the speed at which the total number of executors will be able to be requested.
The increase in default timeout is needed to handle real-world testing environments I've encountered on moderately busy clusters and K8s clusters with their own underlying dynamic scale-up of hardware (e.g. GKE, EKS, etc.)
### Does this PR introduce _any_ user-facing change?
Yes new configuration property
### How was this patch tested?
Updated existing test to use the timeout from the new configuration property. Verified test failed without the update.
Closes#30155 from holdenk/SPARK-33231-make-pod-creation-timeout-configurable.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to use `hadoop-3.2` profile in K8s IT Jenkins jobs.
- [x] Switch the default value of `HADOOP_PROFILE` from `hadoop-2.7` to `hadoop-3.2`.
- [x] Remove `-Phadoop2.7` from Jenkins K8s IT job.
- https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/configure
**BEFORE**
```
./dev/make-distribution.sh --name ${DATE}-${REVISION} --r --pip --tgz -DzincPort=${ZINC_PORT} \
-Phadoop-2.7 -Pkubernetes -Pkinesis-asl -Phive -Phive-thriftserver
```
**AFTER**
```
./dev/make-distribution.sh --name ${DATE}-${REVISION} --r --pip --tgz -DzincPort=${ZINC_PORT} \
-Pkubernetes -Pkinesis-asl -Phive -Phive-thriftserver
```
### Why are the changes needed?
Since Apache Spark 3.1.0, Hadoop 3 is the default.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Check the Jenkins K8s IT log and result.
- https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/34899/
```
+ /home/jenkins/workspace/SparkPullRequestBuilder-K8s/build/mvn clean package -DskipTests -DzincPort=4021 -Pkubernetes -Pkinesis-asl -Phive -Phive-thriftserver
Using `mvn` from path: /home/jenkins/tools/hudson.tasks.Maven_MavenInstallation/Maven_3.6.3/bin/mvn
[INFO] Scanning for projects...
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Build Order:
[INFO]
```
Closes#30153 from dongjoon-hyun/SPARK-33237.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
Handle executor failure with multiple containers
Added a spark property spark.kubernetes.executor.checkAllContainers,
with default being false. When it's true, the executor snapshot will
take all containers in the executor into consideration when deciding
whether the executor is in "Running" state, if the pod restart policy is
"Never". Also, added the new spark property to the doc.
### What changes were proposed in this pull request?
Checking of all containers in the executor pod when reporting executor status, if the `spark.kubernetes.executor.checkAllContainers` property is set to true.
### Why are the changes needed?
Currently, a pod remains "running" as long as there is at least one running container. This prevents Spark from noticing when a container has failed in an executor pod with multiple containers. With this change, user can configure the behavior to be different. Namely, if any container in the executor pod has failed, either the executor process or one of its sidecars, the pod is considered to be failed, and it will be rescheduled.
### Does this PR introduce _any_ user-facing change?
Yes, new spark property added.
User is now able to choose whether to turn on this feature using the `spark.kubernetes.executor.checkAllContainers` property.
### How was this patch tested?
Unit test was added and all passed.
I tried to run integration test by following the instruction [here](https://spark.apache.org/developer-tools.html) (section "Testing K8S") and also [here](https://github.com/apache/spark/blob/master/resource-managers/kubernetes/integration-tests/README.md), but I wasn't able to run it smoothly as it fails to talk with minikube cluster. Maybe it's because my minikube version is too new (I'm using v1.13.1)...? Since I've been trying it for two days and still can't make it work, I decided to submit this PR and hopefully the Jenkins test will pass.
Closes#29924 from huskysun/exec-sidecar-failure.
Authored-by: Shiqi Sun <s.sun@salesforce.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR proposes to exclude `org.apache.hadoop:hadoop-yarn-server-resourcemanager:jar:tests` from `hadoop-yarn-server-tests` when we use Hadoop 2 profile.
For some reasons, after SBT 1.3 upgrade at SPARK-21708, SBT starts to pull the dependencies of 'hadoop-yarn-server-tests' with 'tests' classifier:
```
org/apache/hadoop/hadoop-common/2.7.4/hadoop-common-2.7.4-tests.jar
org/apache/hadoop/hadoop-yarn-common/2.7.4/hadoop-yarn-common-2.7.4-tests.jar
org/apache/hadoop/hadoop-yarn-server-resourcemanager/2.7.4/hadoop-yarn-server-resourcemanager-2.7.4-tests.jar
```
these were not pulled before the upgrade.
This specific `hadoop-yarn-server-resourcemanager-2.7.4-tests.jar` causes the problem (SPARK-33104)
1. When the test case creates the Hadoop configuration here,
cc06266ade/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala (L122)
2. Such jars above have higher precedence in the class path, instead of the specified custom `core-site.xml` in the test:
e93b8f02cd/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala (L1375)
3. Later, `core-site.xml` in the jar is picked instead in Hadoop's `Configuration`:
Before this fix:
```
jar:file:/.../https/maven-central.storage-download.googleapis.com/maven2/org/apache/hadoop/
hadoop-yarn-server-resourcemanager/2.7.4/hadoop-yarn-server-resourcemanager-2.7.4-tests.jar!/core-site.xml
```
After this fix:
```
file:/.../spark/resource-managers/yarn/target/org.apache.spark.deploy.yarn.YarnClusterSuite/
org.apache.spark.deploy.yarn.YarnClusterSuite-localDir-nm-0_0/
usercache/.../filecache/10/__spark_conf__.zip/__hadoop_conf__/core-site.xml
```
4. the `core-site.xml` in the jar of course does not contain:
2cfd215dc4/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala (L133-L141)
and the specific test fails.
This PR uses some kind of hacky approach. It was excluded from 'hadoop-yarn-server-tests' with 'tests' classifier, and then added back as a proper dependency (when Hadoop 2 profile is used). In this way, SBT does not pull `hadoop-yarn-server-resourcemanager` with `tests` classifier anymore.
### Why are the changes needed?
To make the build pass. This is a blocker.
### Does this PR introduce _any_ user-facing change?
No, test-only.
### How was this patch tested?
Manually tested and debugged:
```bash
build/sbt clean "yarn/testOnly *.YarnClusterSuite -- -z SparkHadoopUtil" -Pyarn -Phadoop-2.7 -Phive -Phive-2.3
```
Closes#30133 from HyukjinKwon/SPARK-33104.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR cleans up the RPC message flow among the multiple decommission use cases, it includes changes:
* Keep `Worker`'s decommission status be consistent between the case where decommission starts from `Worker` and the case where decommission starts from the `MasterWebUI`: sending `DecommissionWorker` from `Master` to `Worker` in the latter case.
* Change from two-way communication to one-way communication when notifying decommission between driver and executor: it's obviously unnecessary for the executor to acknowledge the decommission status to the driver since the decommission request is from the driver. And it's same in reverse.
* Only send one message instead of two(`DecommissionSelf`/`DecommissionBlockManager`) when decommission the executor: executor and `BlockManager` are in the same JVM.
* Clean up codes around here.
### Why are the changes needed?
Before:
<img width="1948" alt="WeChat56c00cc34d9785a67a544dca036d49da" src="https://user-images.githubusercontent.com/16397174/92850308-dc461c80-f41e-11ea-8ac0-287825f4e0c4.png">
After:
<img width="1968" alt="WeChat05f7afb017e3f0132394c5e54245e49e" src="https://user-images.githubusercontent.com/16397174/93189571-de88dd80-f774-11ea-9300-1943920aa27d.png">
(Note the diagrams only counts those RPC calls that needed to go through the network. Local RPC calls are not counted here.)
After this change, We reduced 6 original RPC calls and added one more RPC call for keeping the consistent decommission status for the Worker. And the RPC flow becomes more clear.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated existing tests.
Closes#29817 from Ngone51/simplify-decommission-rpc.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x. For Hadoop 2.7, we'll still use the same modules such as hadoop-client.
In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties:
```
hadoop-client-api.artifact
hadoop-client-runtime.artifact
hadoop-client-minicluster.artifact
```
which default to:
```
hadoop-client-api
hadoop-client-runtime
hadoop-client-minicluster
```
but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`.
Besides above, there are the following changes:
- explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars.
- removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API.
- modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests).
### Why are the changes needed?
This serves two purposes:
- to unblock Spark from upgrading to Hadoop 3.2.2/3.3.0+. Latest Hadoop versions have upgraded to use Guava 27+ and in order to adopt the latest Hadoop versions in Spark, we'll need to resolve the Guava conflicts. This takes the approach by switching to shaded client jars provided by Hadoop.
- avoid pulling 3rd party dependencies from Hadoop and avoid potential future conflicts.
### Does this PR introduce _any_ user-facing change?
When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts.
### How was this patch tested?
Relying on existing tests.
Closes#29843 from sunchao/SPARK-29250.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
### What changes were proposed in this pull request?
This PR proposes to fix:
```
org.apache.spark.deploy.yarn.YarnClusterSuite.run Python application in yarn-client mode
org.apache.spark.deploy.yarn.YarnClusterSuite.run Python application in yarn-cluster mode
org.apache.spark.deploy.yarn.YarnClusterSuite.run Python application in yarn-cluster mode using spark.yarn.appMasterEnv to override local envvar
```
it currently fails as below:
```
20/10/16 19:20:36 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (amp-jenkins-worker-03.amp executor 1): org.apache.spark.SparkException:
Error from python worker:
Traceback (most recent call last):
File "/usr/lib64/python2.6/runpy.py", line 104, in _run_module_as_main
loader, code, fname = _get_module_details(mod_name)
File "/usr/lib64/python2.6/runpy.py", line 79, in _get_module_details
loader = get_loader(mod_name)
File "/usr/lib64/python2.6/pkgutil.py", line 456, in get_loader
return find_loader(fullname)
File "/usr/lib64/python2.6/pkgutil.py", line 466, in find_loader
for importer in iter_importers(fullname):
File "/usr/lib64/python2.6/pkgutil.py", line 422, in iter_importers
__import__(pkg)
File "/home/jenkins/workspace/SparkPullRequestBuilder2/python/pyspark/__init__.py", line 53, in <module>
from pyspark.rdd import RDD, RDDBarrier
File "/home/jenkins/workspace/SparkPullRequestBuilder2/python/pyspark/rdd.py", line 34, in <module>
from pyspark.java_gateway import local_connect_and_auth
File "/home/jenkins/workspace/SparkPullRequestBuilder2/python/pyspark/java_gateway.py", line 29, in <module>
from py4j.java_gateway import java_import, JavaGateway, JavaObject, GatewayParameters
File "/home/jenkins/workspace/SparkPullRequestBuilder2/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 60
PY4J_TRUE = {"yes", "y", "t", "true"}
^
SyntaxError: invalid syntax
```
I think this was broken when Python 2 was dropped but was not caught because this specific test does not run when there's no change in YARN codes. See also https://github.com/apache/spark/pull/29843#issuecomment-712540024
The root cause seems like the paths are different, see https://github.com/apache/spark/pull/29843#pullrequestreview-502595199. I _think_ Jenkins uses a different Python executable via Anaconda and the executor side does not know where it is for some reasons.
This PR proposes to fix it just by explicitly specifying the absolute path for Python executable so the tests should pass in any environment.
### Why are the changes needed?
To make tests pass.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
This issue looks specific to Jenkins. It should run the tests on Jenkins.
Closes#30099 from HyukjinKwon/SPARK-33191.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to detect duplicate `mountPath`s and stop the job.
### Why are the changes needed?
If there is a conflict on `mountPath`, the pod is created and repeats the following error messages and keeps running. Spark job should not keep running and wasting the cluster resources. We had better fail at Spark side.
```
$ k get pod -l 'spark-role in (driver,executor)'
NAME READY STATUS RESTARTS AGE
tpcds 1/1 Running 0 33m
```
```
20/10/18 05:09:26 WARN ExecutorPodsSnapshotsStoreImpl: Exception when notifying snapshot subscriber.
io.fabric8.kubernetes.client.KubernetesClientException: Failure executing: POST at: ...
Message: Pod "tpcds-exec-1" is invalid: spec.containers[0].volumeMounts[1].mountPath:
Invalid value: "/data1": must be unique.
...
```
**AFTER THIS PR**
The job will stop with the following error message instead of keeping running.
```
20/10/18 06:58:45 ERROR ExecutorPodsSnapshotsStoreImpl: Going to stop due to IllegalArgumentException
java.lang.IllegalArgumentException: requirement failed: Found duplicated mountPath: `/data1`
```
### Does this PR introduce _any_ user-facing change?
Yes, but this is a bug fix.
### How was this patch tested?
Pass the CI with the newly added test case.
Closes#30084 from dongjoon-hyun/SPARK-33175-2.
Lead-authored-by: Dongjoon Hyun <dhyun@apple.com>
Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to use `openjdk:11-jre-slim` as default in K8s Dockerfile.
### Why are the changes needed?
Although Apache Spark supports both Java8/Java11, there is a difference.
1. Java8-built distribution can run both Java8/Java11
2. Java11-built distribution can run on Java11, but not Java8.
In short, we had better use Java11 in Dockerfile to embrace both cases without any issues.
### Does this PR introduce _any_ user-facing change?
Yes. This will remove the change of user frustration when they build with JDK11 and build the image without overriding Java base image.
### How was this patch tested?
Pass the K8s IT.
Closes#30083 from dongjoon-hyun/SPARK-33176.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
If a block is removed between discovery to transfer fo the block, we short circuit that block and remove it from the list to transfer and increment the transferred blocks. This is complicated since both RPC errors and local read errors may be reported with the same exception class.
### Why are the changes needed?
Slow shuffle refreshes could waste time when decommissioning has already finished. Decommissioning might avoid transferring some some blocks to an otherwise live host which is marked as "full" if a deleted block fails to transfer to that host.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New unit and integration tests.
Closes#30046 from holdenk/handle-cleaned-shuffles-during0migration.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This is the first patch for SPIP SPARK-30602 for push-based shuffle.
Summary of changes:
* Introduce new API in ExternalBlockStoreClient to push blocks to a remote shuffle service.
* Leveraging the streaming upload functionality in SPARK-6237, it also enables the ExternalBlockHandler to delegate the handling of block push requests to MergedShuffleFileManager.
* Propose the API for MergedShuffleFileManager, where the core logic on the shuffle service side to handle block push requests is defined. The actual implementation of this API is deferred into a later RB to restrict the size of this PR.
* Introduce OneForOneBlockPusher to enable pushing blocks to remote shuffle services in shuffle RPC layer.
* New protocols in shuffle RPC layer to support the functionalities.
### Why are the changes needed?
Refer to the SPIP in SPARK-30602
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added unit tests.
The reference PR with the consolidated changes covering the complete implementation is also provided in SPARK-30602.
We have already verified the functionality and the improved performance as documented in the SPIP doc.
Lead-authored-by: Min Shen <mshenlinkedin.com>
Co-authored-by: Chandni Singh <chsinghlinkedin.com>
Co-authored-by: Ye Zhou <yezhoulinkedin.com>
Closes#29855 from Victsm/SPARK-32915.
Lead-authored-by: Min Shen <mshen@linkedin.com>
Co-authored-by: Chandni Singh <chsingh@linkedin.com>
Co-authored-by: Ye Zhou <yezhou@linkedin.com>
Co-authored-by: Chandni Singh <singh.chandni@gmail.com>
Co-authored-by: Min Shen <victor.nju@gmail.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This PR makes `spark.kubernetes.pyspark.pythonVersion` allow only `3`. In other words, it will reject `2` for `Python 2`.
- [x] Configuration description and check is updated.
- [x] Documentation is updated
- [x] Unit test cases are updated.
- [x] Docker image script is updated.
### Why are the changes needed?
After SPARK-32138, Apache Spark 3.1 dropped Python 2 support.
### Does this PR introduce _any_ user-facing change?
Yes, but Python 2 support is already dropped officially.
### How was this patch tested?
Pass the CI.
Closes#30049 from dongjoon-hyun/SPARK-DROP-PYTHON2.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to protect the executor pod request or pending pod during executor idle timeout.
### Why are the changes needed?
In case of dynamic allocation, Apache Spark K8s `ExecutorPodsAllocator` cancels the pod requests or pending pods too eagerly. Like the following example, `ExecutorPodsAllocator` received the new total executor adjust request rapidly in two minutes. Sometimes, it's called 3 times in a single second. It repeats `request` and `delete` on that request or pending pod frequently. This PR is reusing `spark.dynamicAllocation.executorIdleTimeout (default: 60s)` to keep the pod request or pending pod.
```
20/10/08 05:58:08 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:58:08 INFO ExecutorPodsAllocator: Going to request 3 executors from Kubernetes.
20/10/08 05:58:09 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:58:43 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 1
20/10/08 05:58:47 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 0
20/10/08 05:59:26 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:59:30 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 2
20/10/08 05:59:31 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:59:44 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 2
20/10/08 05:59:44 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 0
20/10/08 05:59:45 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:59:50 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 2
20/10/08 05:59:50 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 1
20/10/08 05:59:50 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 0
20/10/08 05:59:54 INFO ExecutorPodsAllocator: Set totalExpectedExecutors to 3
20/10/08 05:59:54 INFO ExecutorPodsAllocator: Going to request 1 executors from Kubernetes.
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the newly added test case.
Closes#29981 from dongjoon-hyun/SPARK-K8S-INITIAL.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to use `LinkedHashMap` instead of `Map` for `newlyCreatedExecutors`.
### Why are the changes needed?
This makes log messages (INFO/DEBUG) more readable. This is helpful when `spark.kubernetes.allocation.batch.size` is large and especially when K8s dynamic allocation is used.
**BEFORE**
```
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 8 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 2 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 5 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 4 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 7 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 10 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 9 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 3 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 DEBUG ExecutorPodsAllocator: Executor with id 6 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:24:21 INFO ExecutorPodsAllocator: Deleting 9 excess pod requests (5,10,6,9,2,7,3,8,4).
```
**AFTER**
```
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 2 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 3 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 4 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 5 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 6 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 7 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 8 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 9 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 DEBUG ExecutorPodsAllocator: Executor with id 10 was not found in the Kubernetes cluster since it was created 0 milliseconds ago.
20/10/08 10:25:17 INFO ExecutorPodsAllocator: Deleting 9 excess pod requests (2,3,4,5,6,7,8,9,10).
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI or `build/sbt -Pkubernetes "kubernetes/test"`
Closes#29979 from dongjoon-hyun/SPARK-K8S-LOG.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
The pod template configmap always had the same name. This PR makes it unique.
### Why are the changes needed?
If you scheduled 2 spark jobs they will both use the same configmap name this will result in conflicts. This PR fixes that
**BEFORE**
```
$ kubectl get cm --all-namespaces -w | grep podspec
podspec-configmap 1 65s
```
**AFTER**
```
$ kubectl get cm --all-namespaces -w | grep podspec
aaece65ef82e4a30b7b7800aad600d4f spark-test-app-aac9f37502b2ca55-driver-podspec-conf-map 1 0s
```
This can be seen when running the integration tests
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit tests and the integration tests test if this works
Closes#29934 from stijndehaes/bugfix/SPARK-32067-unique-name-for-template-configmap.
Authored-by: Stijn De Haes <stijndehaes@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Provide error handling when creating kubernetes volumes. Right now they keys are expected to be there and if not it fails with a `key not found` error, but not knowing why do you need that `key`.
Also I renamed some tests that didn't indicate the kind of kubernetes volume
### Why are the changes needed?
Easier for the users to understand why `spark-submit` command is failing if not providing they right kubernetes volumes properties.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
It was tested with the current tests plus added one more.
[Jira ticket](https://issues.apache.org/jira/browse/SPARK-33063)
Closes#29941 from Gschiavon/SPARK-33063-provide-error-handling-k8s-volumes.
Authored-by: gschiavon <germanschiavon@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR fixes an issue that a test in `LocalityPlacementStrategySuite` fails with Java 11 due to `StackOverflowError`.
```
[info] - handle large number of containers and tasks (SPARK-18750) *** FAILED *** (170 milliseconds)
[info] StackOverflowError should not be thrown; however, got:
[info]
[info] java.lang.StackOverflowError
[info] at java.base/java.util.concurrent.ConcurrentHashMap.putVal(ConcurrentHashMap.java:1012)
[info] at java.base/java.util.concurrent.ConcurrentHashMap.putIfAbsent(ConcurrentHashMap.java:1541)
[info] at java.base/java.lang.ClassLoader.getClassLoadingLock(ClassLoader.java:668)
[info] at java.base/jdk.internal.loader.BuiltinClassLoader.loadClassOrNull(BuiltinClassLoader.java:591)
[info] at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:579)
[info] at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:178)
[info] at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)
```
The solution is to expand the stack size of a thread in the test from 32KB to 256KB.
Currently, the stack size is specified as 32KB but the actual stack size can be greater than 32KB.
According to the code of Hotspot, the minimum stack size is prefer to the specified size.
Java 8: https://hg.openjdk.java.net/jdk8u/jdk8u/hotspot/file/c92ba514724d/src/os/linux/vm/os_linux.cpp#l900
Java 11: https://hg.openjdk.java.net/jdk-updates/jdk11u/file/73edf743a93a/src/hotspot/os/posix/os_posix.cpp#l1555
For Linux on x86_64, the minimum stack size seems to be 224KB and 136KB for Java 8 and Java 11 respectively. So, the actual stack size should be 224KB rather than 32KB for Java 8 on x86_64/Linux.
As the test passes for Java 8 but doesn't for Java 11, 224KB is enough while 136KB is not.
So I think specifing 256KB is reasonable for the new stack size.
### Why are the changes needed?
To pass the test for Java 11.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Following command with Java 11.
```
build/sbt -Pyarn clean package "testOnly org.apache.spark.deploy.yarn.LocalityPlacementStrategySuite"
```
Closes#29943 from sarutak/fix-stack-size.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `kubernetes-client` library to track fabric8's declared compatibility for k8s 1.18.0:
https://github.com/fabric8io/kubernetes-client#compatibility-matrix
### Why are the changes needed?
According to fabric8, 4.9.2 is incompatible with k8s 1.18.0.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Not tested yet.
Closes#29888 from laflechejonathan/jlf/fabric8Ugprade.
Authored-by: jlafleche <jlafleche@palantir.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to support dynamic PVC creation and deletion in K8s driver.
**Configuration**
This PR reuses the existing PVC volume configs.
```
spark.kubernetes.driver.volumes.persistentVolumeClaim.spark-local-dir-1.options.claimName=OnDemand
spark.kubernetes.driver.volumes.persistentVolumeClaim.spark-local-dir-1.options.storageClass=gp2
spark.kubernetes.driver.volumes.persistentVolumeClaim.spark-local-dir-1.options.sizeLimit=200Gi
spark.kubernetes.driver.volumes.persistentVolumeClaim.spark-local-dir-1.mount.path=/data
spark.kubernetes.driver.volumes.persistentVolumeClaim.spark-local-dir-1.mount.readOnly=false
```
**PVC**
```
$ kubectl get pvc | grep driver
tpcds-d6087874c6705564-driver-pvc-0 Bound pvc-fae914a2-ca5c-4e1e-8aba-54a35357d072 200Gi RWO gp2 12m
```
**Disk**
```
$ k exec -it tpcds-d6087874c6705564-driver -- df -h | grep data
/dev/nvme5n1 197G 61M 197G 1% /data
```
```
$ k exec -it tpcds-d6087874c6705564-driver -- ls -al /data
total 28
drwxr-xr-x 5 root root 4096 Sep 25 18:06 .
drwxr-xr-x 1 root root 63 Sep 25 18:06 ..
drwxr-xr-x 66 root root 4096 Sep 25 18:09 blockmgr-2c9a8cc5-a05c-45fe-a58e-b8f42da88a57
drwx------ 2 root root 16384 Sep 25 18:06 lost+found
drwx------ 4 root root 4096 Sep 25 18:07 spark-0448efe7-da2c-4f3a-bd3c-769aadb11dd6
```
**NOTE**
This should be used carefully because Apache Spark doesn't delete driver pod automatically. Since the driver PVC shares the lifecycle of driver pod, it will exist after the job completion until the pod deletion. However, if the users are already using pre-populated PVCs, this isn't a regression at all in terms of the cost.
```
$ k get pod -l spark-role=driver
NAME READY STATUS RESTARTS AGE
tpcds-d6087874c6705564-driver 0/1 Completed 0 35m
```
### Why are the changes needed?
Like executors, driver also needs larger PVC.
### Does this PR introduce _any_ user-facing change?
Yes. This is a new feature.
### How was this patch tested?
Pass the newly added test case.
Closes#29873 from dongjoon-hyun/SPARK-32997.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
When I tried to verify that the `resource-managers/yarn` module passed all UTs in Scala 2.13 , I found that there is a
issue related to classpath order maybe blocked the UTs because there are more than one `servlet-api` dependency in spark now:
- One is `javax.servlet:javax.servlet-api:3.10:compile` config in core/pom.xml,
- The other is `jakarta.servlet:jakarta.servlet-api:4.0.3:test` cascaded by `org.glassfish.jersey.test-framework.providers`
we can use `mvn dependency:tree` to check it .
So when we execute `resource-managers/yarn` module test use
```
mvn clean test -pl resource-managers/yarn -Pyarn
```
or
```
mvn clean test -pl resource-managers/yarn -Pyarn -Pscala-2.13
```
and if the position of `javax.servlet-api` in the in classpath is before `jakarta.servlet-api`, there are some cases failed in `YarnClusterSuite`, `YarnShuffleIntegrationSuite` and `YarnShuffleAuthSuite`.
The failed reason as follow:
```
20/09/18 19:14:07.486 launcher-proc-1 INFO YarnClusterDriver: Exception in thread "main" java.lang.ExceptionInInitializerError
...
20/09/18 19:14:07.486 launcher-proc-1 INFO YarnClusterDriver: Caused by: java.lang.SecurityException: class "javax.servlet.http.HttpSessionIdListener"'s signer information does not match signer information of other classes in the same package
...
```
### Why are the changes needed?
Avoid UTs error caused by classpath order .
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Scala 2.12: Pass the Jenkins or GitHub Action
- Scala 2.13: Pass 2.13 Build GitHub Action and do the following:
```
dev/change-scala-version.sh 2.13
mvn clean install -DskipTests -pl resource-managers/yarn -Pyarn -Pscala-2.13 -am
mvn clean test -pl resource-managers/yarn -Pyarn -Pscala-2.13
```
```
Tests: succeeded 136, failed 0, canceled 1, ignored 0, pending 0
All tests passed.
```
Closes#29824 from LuciferYang/yarn-tests-deps.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
Dongjoon Hyun
Shardul Mahadik
SaurabhChawla
“attilapiros”
HyukjinKwon
Erik Krogen
hongdongdong
Yikun Jiang
yi.wu
Holden Karau
yangjie01
Chao Sun
Prashant Sharma
David McWhorter
Kent Yao
Kousuke Saruta
suqilong
Dongjoon Hyun
Josh Soref
Venkata krishnan Sowrirajan
Stavros Kontopoulos
Rameshkrishnan Muthusamy
Pascal Gillet
Yuming Wang
Chandni Singh
Thomas Graves
Thomas Graves
Shiqi Sun
Min Shen
Stijn De Haes
gschiavon
jlafleche
