skonto commented on a change in pull request #23546: [SPARK-23153][K8s] Support
client dependencies with a Hadoop Compatible File System
URL: https://github.com/apache/spark/pull/23546#discussion_r259157717
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File path: core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala
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@@ -318,9 +319,25 @@ private[spark] class SparkSubmit extends Logging {
args.ivySettingsPath)
if (!StringUtils.isBlank(resolvedMavenCoordinates)) {
- args.jars = mergeFileLists(args.jars, resolvedMavenCoordinates)
- if (args.isPython || isInternal(args.primaryResource)) {
- args.pyFiles = mergeFileLists(args.pyFiles, resolvedMavenCoordinates)
+ // In K8s client mode, when in the driver, add resolved jars early as
we might need
+ // them at the submit time. For example we might use the dependencies
for downloading
+ // files from a Hadoop Compatible fs eg. S3. In this case the user
might pass:
+ // --packages
com.amazonaws:aws-java-sdk:1.7.4:org.apache.hadoop:hadoop-aws:2.7.6
+ if (isKubernetesClient &&
+ args.sparkProperties.getOrElse("spark.kubernetes.submitInDriver",
"false").toBoolean) {
Review comment:
It means its the first submit time in cluster mode (second is in the
container). So at this step the submit process needs to upload the files. In
practice this is user's machine. This is where I also need to make sure
`--packages` works because user may need to pass the dependencies needed for
accessing the remote system. There are a bunch of places this needs to work. So
I just make the same packages available at the user's machine and in the driver
because we also want to pass the deps in the there so the driver can download
the files. Of course user may have deps that are not related to the upload as
usual. The difference between the driver and the user's machine is what logic
is triggered and when. So for the user's machine I need to add early the jars
in the classpath. In the driver I let the pre-existing logic (before this PR)
to do the job as the uris are hadoop compatible.
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