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[SPARK-26194][k8s] Auto generate auth secret for k8s apps. #23174

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@vanzin vanzin commented Nov 28, 2018

This change modifies the logic in the SecurityManager to do two
things:

  • generate unique app secrets also when k8s is being used
  • only store the secret in the user's UGI on YARN

The latter is needed so that k8s won't unnecessarily create
k8s secrets for the UGI credentials when only the auth token
is stored there.

On the k8s side, the secret is propagated to executors using
an environment variable instead. This ensures it works in both
client and cluster mode.

Security doc was updated to mention the feature and clarify that
proper access control in k8s should be enabled for it to be secure.

This change modifies the logic in the SecurityManager to do two
things:

- generate unique app secrets also when k8s is being used
- only store the secret in the user's UGI on YARN

The latter is needed so that k8s won't unnecessarily create
k8s secrets for the UGI credentials when only the auth token
is stored there.

On the k8s side, the secret is propagated to executors using
an environment variable instead. This ensures it works in both
client and cluster mode.

Security doc was updated to mention the feature and clarify that
proper access control in k8s should be enabled for it to be secure.
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SparkQA commented Nov 28, 2018

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SparkQA commented Nov 28, 2018

Kubernetes integration test status success
URL: https://amplab.cs.berkeley.edu/jenkins/job/testing-k8s-prb-make-spark-distribution-unified/5476/

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SparkQA commented Nov 29, 2018

Test build #99402 has finished for PR 23174 at commit 0e36a4b.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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mccheah commented Nov 29, 2018

Would it be possible to also provide support for passing this via a mounted file? Some users would prefer to avoid propagating sensitive information via environment variables. Also the user should be able to specify their own mounted file; spark-submit shouldn't always mount an auto-generated secret for the user.

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vanzin commented Nov 29, 2018

via a mounted file
Also the user should be able to specify their own mounted file

The point is that the user shouldn't need to set this at all. You enable auth, Spark takes care of it. There's no point in specifying a pre-defined file with the secret - in fact that makes things less secure, because you'd be reusing the secret in different apps.

Some users would prefer to avoid propagating sensitive information via environment variables

Why? And how are mounted files better?

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mccheah commented Nov 29, 2018

Why? And how are mounted files better?

Environment variables leak far more easily than file contents. One can accidentally printenv in a shell attached to the container and get the secret contents. System.getenv has a similar effect within the application code itself. For what it's worth I'm also not sure if the secret would be listed under the environment variables in the Spark UI (would have to test this).

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vanzin commented Nov 29, 2018

if the secret would be listed under the environment variables in the Spark UI

Secrets are redacted in the UI and event logs. We already use env variables in other contexts (e.g. standalone with auth enabled).

Environment variables don't leak unless you leak them. If you do, it's a security problem in your code, since the env is generally considered "sensitive information". They're not written to disk, unlike files, which some people have problems with (really paranoid orgs don't want sensitive information in unencrypted files on disk).

This could be stashed in a k8s secret, but then how does the client mode driver get it? More user configuration? That's exactly what this is trying to avoid.

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vanzin commented Nov 29, 2018

(In fact, env variables don't even show up in the UI or event logs, as far as I can see. Other configs - Spark config, system properties, e.g. - do show up, and are redacted to mask secrets.)

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The issue with requiring the use of secrets is quite a bit of work must be done in order to secure a cluster to ensure that the secrets are themselves secured. Most of the high level concerns are outlined here, but you then need to understand the implications of this in the context of how Spark is used. Its my understanding that Spark's implementation on Kubernetes doesn’t dictate how spark jobs should be run. As an example of where this can quickly break down:

  • Imagine a scenario where someone runs two drivers in the same namespace, and rely on the default svc token to allow the driver to create its executors.
  • The driver token will have GET access on the secret for its driver, but also other secrets within the same namespace – such as the secret for driver B.
  • If the executors in job B can use the same service token as their driver, then they have the ability of launching executors that can use the secret from job A to connect an executor at which point you have a compromise.

There are lots of things that can be done to prevent this kind of attack – run in different namespaces, don’t allow executors to have k8s permissions, etc., but it feels risky for spark to require the use of secrets while leaving it an exercise for the reader to understand how to properly run spark such that the secrets are actually secured.

At Palantir, we rely heavily on an external secret storage and bootstrapping system, built around Vault, to securely pass secrets into pods. Using external systems for these kinds of things, especially those built around Vault, is a common practice.

So really, what we'd like here is to avoid coupling the API for how spark containers read secrets so that alternative implementations can be used that some might consider more secure.

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vanzin commented Nov 30, 2018

while leaving it an exercise for the reader to understand how to properly run spark such that the secrets are actually secured.

I don't think that's an exercise for the user, but for the admin. If the admin has configured things properly, the user will be able to deploy secure applications without issue. This is not just the case in kubernetes. It's the case in any deployment.

Even your example of using Vault requires that. There's work needed to use it properly and securely.

avoid coupling the API for how spark containers read secrets

There doesn't need to be a single solution. This patch going in does not preclude adding more features later, one of which might be reading this from a pre-defined secret.

And in your example I don't see how Vault would actually solve the client-mode driver case. There's no kubernetes involved in the driver, which may be running anywhere, and it needs to know the secret.

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mccheah commented Nov 30, 2018

There doesn't need to be a single solution. This patch going in does not preclude adding more features later, one of which might be reading this from a pre-defined secret.

The way it's written now, if the user opts-in to using spark.authenticate with Kubernetes, the application will always automatically generate the secret and use that as the security mechanism. I think we'd prefer to see the various options that are available up front and this patch should probably introduce both the automatic secret creation version (if we agree that this is secure) and the manual provision version. If this change is merged into 3.x without any other changes, users will be forced to use the K8s secret based SASL scheme and this feature will be unusable for other users such as with the vault case discussed above.

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vanzin commented Nov 30, 2018

The way it's written now

Code can change after it's written...

If this change is merged into 3.x without any other changes, users will be forced to use the K8s secret based

If this change is not merged, users have no way to use authentication at all. So I don't see your point.

It will prevent you from using the Vault approach in the sense that support for that won't be implemented yet. But this change, again, does not put a block on adding support for what you're saying later. If you think that's important and want to do that in 3.x, then you're free to. But I don't see why this approach needs to be blocked because it doesn't cover the Vault use case.

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mccheah commented Nov 30, 2018

The trouble is the API proposed here and how it would have to change for future features. If we wanted to add the optionality to support authentication via mounted files later, then what's the API for that, and how would that change the API for users that were relying on this authentication mechanism? That's why it's important to see the optionality now, so it can be clear to us that are our options, and this is how we are going to use them.

A proposed scheme is to have spark.authenticate.k8s.secret.provider=autok8ssecret, then document what that does. Perhaps that's the default mode. Then add another scheme, say spark.authenticate.k8s.secret.provider=files and then further options for specifying where that file is located on both the driver and the executors.

It's helpful to put this patch in the context of where we want to go for authentication in general moving forward. Otherwise this feature taken in isolation will make it appear that Spark is being opinionated about using Kubernetes secrets and environment variables for authentication.

if it's not introduced in this patch, then at least we should file JIRA tickets and reference them as future add-ons to this and have a roadmap for what SASL on K8s will look like in the bigger picture for 3.x.

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vanzin commented Nov 30, 2018

A proposed scheme is to have spark.authenticate.k8s.secret.provider=autok8ssecret

If you're going to add a different way to get the auth secret later, then you can introduce that option with a default value. It does not mean it needs to be done in this change, which is my point.

The only real change being introduced here form the Spark status quo is that you don't need to provide your own auth secret in the configuration (i.e. it would work like YARN), which doesn't even work in k8s today because that is not propagated to the executors in any way. And if you think that is a problem I can gate the generation of the secret based on whether one is already defined in the config.

if it's not introduced in this patch, then at least we should file JIRA tickets

That is fine with me.

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vanzin commented Nov 30, 2018

I filed SPARK-26239.

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vanzin commented Dec 3, 2018

So, can we move forward with this and let any future new feature be handled in SPARK-26239?

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mccheah commented Dec 3, 2018

I think as long as we have one alternate mechanism proposed in SPARK-26239 this is ok to merge. I proposed one in this comment.

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vanzin commented Dec 3, 2018

As I suggested before, any alternative method can be added later. I don't see why does it need to block this PR.

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mccheah commented Dec 3, 2018

It's just to have the assurance that we will have some way to bypass this for auth at least for 3.x. I'd like to concretely determine this before merging if possible. But I hope that the suggestion proposed in SPARK-26239 could be agreed upon fairly quickly?

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vanzin commented Dec 3, 2018

I don't understand what you want.

Without this change, auth does not work, period.

With this, users at least have one choice.

If you want to add another choice, you're free to. But I don't see why the lack of another choice has any effect on this PR.

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mccheah commented Dec 3, 2018

Ok that's fine, with the caveat that we merge the subsequent optionality soon. I'll work on the file-based secret authentication and encryption this week. I'm very concerned that we'll ship with this but with no other security options if we're not rigorously moving SPARK-26239 forward.

Merging to master in a few hours, letting it stay open for a bit for any other commentary. @gdearment for SA.

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SparkQA commented Dec 3, 2018

Kubernetes integration test status failure
URL: https://amplab.cs.berkeley.edu/jenkins/job/testing-k8s-prb-make-spark-distribution-unified/5687/

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vanzin commented Dec 3, 2018

with the caveat that we merge the subsequent optionality soon

Again, and sorry for pounding on that key, but why does that matter? It has zero effect on the feature being added here. If the code added here is not good enough for your use case, you're in the exact same situation as if this change did not go in. But for those that can leverage the auth feature as added in this change, they're in a much, much better place.

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mccheah commented Dec 3, 2018

It matters because we're discussing direction - that is, what opinion Spark wants to take regarding how to set up security on K8s. It's not obvious from our discussion on SPARK-26239 that we agree that we should allow such optionality for other authentication schemes. In other words, if we just merge this PR without further discussion and consensus on SPARK-26239, we're effectively communicating that Spark is locked in to the authentication backed by K8s secrets. I want to emphasize that it's important to agree on the direction for the bigger picture early on, and then we say that this patch still fits into the bigger vision.

I also want to intend to take this patch and check that work on SPARK-26239 would work nicely with it, but to the best of my knowledge the additional options should layer on top of this default one just fine. Would like some concrete prototyping to confirm this though.

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vanzin commented Dec 3, 2018

It matters because we're discussing direction

I'm not, you guys are. I'm adding a missing feature with one particular implementation. If you want to add other implementations that enable different use cases, great.

we're effectively communicating that Spark is locked in to the authentication backed by K8s secrets

We're not locking into anything, and that's basically where I strongly disagree with you. You're free to add new ways, and when that's done, you're not "locked in" anymore.

Locked in would mean that pushing this PR means you cannot make changes to it later, and that's just not true.

Right now you're "locked in" to no auth at all, but somehow that's ok?

check that work on SPARK-26239 would work nicely with it

Anything needed to implement that feature is just code changes. Whether it "works nicely" is just a matter of not breaking this when that feature is implemented.

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mccheah commented Dec 3, 2018

Ok that's fine. Will merge to master if there are no further comments in the near future.

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vanzin commented Dec 3, 2018

I looked at the test failure, but the logs weren't super useful. This passed locally, but let me retrigger here.

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vanzin commented Dec 3, 2018

retest this please

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SparkQA commented Dec 4, 2018

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SparkQA commented Dec 4, 2018

Kubernetes integration test status success
URL: https://amplab.cs.berkeley.edu/jenkins/job/testing-k8s-prb-make-spark-distribution-unified/5691/

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SparkQA commented Dec 4, 2018

Test build #99629 has finished for PR 23174 at commit 791b5ee.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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SparkQA commented Dec 4, 2018

Test build #99634 has finished for PR 23174 at commit 791b5ee.

  • This patch fails Spark unit tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

@asfgit asfgit closed this in dbd90e5 Dec 6, 2018
Option(secMgr.getSecretKey()).map { authSecret =>
new EnvVarBuilder()
.withName(SecurityManager.ENV_AUTH_SECRET)
.withValue(authSecret)
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Ah I thought about this a bit more and realized that this is more insecure than I originally read it to be.

If the secret is put directly in the environment variable field itself, then anyone who has permission to get the pod metadata from the Kubernetes API server can now read the secret generated by this application. In practice permissioning on pod specs is often far looser than permissioning on Kubernetes secret objects. (Edit: For example a system administrator who performs maintenance and debugs issues should be able to read the pod spec object but often can't access sensitive information in Kubernetes secrets in the same namespace.) In this solution the administrator has to restrict access to pod specs to only the user.

I think at the very least we want this to be configured via creating a Kubernetes secret object, then loading the environment variable to point to the secret object.

In the meantime I'm going to push the PR that allows secrets to be specified as file paths directly. I will also file a Spark ticket to avoid putting the environment variable directly in the pod spec object itself.

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I filed https://issues.apache.org/jira/browse/SPARK-26301 to suggest the alternative scheme. Unlike SPARK-26139 this would change the functionality that was merged here.

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If the secret is put directly in the environment variable field itself, then anyone who has permission to get the pod metadata from the Kubernetes API server can now read the secret generated by this application.

Yes, and it's extremely annoying that k8s allows anybody with access to the pods to read env variables, instead of just the pod owner. In fact, it doesn't even seem to have the concept of who owns the pod.

Anyway, this isn't different from someone else being able to read secrets in the same namespace as the pod.

As I said before, it all depends on how you configure your cluster for security, and in k8s there seems to be a lot of different options.

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Anyway, this isn't different from someone else being able to read secrets in the same namespace as the pod.

It isn't in theory, but in practice my understanding is that secrets are often permissioned more strictly than pod objects in the cluster. We should be optimizing for the more common use case, which will work out of the box for more users and also is more secure in the context of more common configurations.

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the more common use case,

Which is?

There's a lot to think about when you give permissions like "users can view, create and delete pods". If you do that, for example, you can delete other people's pods. That is also considered a security issue, since you can DoS other users.

Anyway, my point is that we should give people the choice of how they deploy things, and set up security according to their own constraints. This was just one way of doing it, and was not meant to be the only way.

@vanzin vanzin deleted the SPARK-26194 branch December 12, 2018 20:38
jackylee-ch pushed a commit to jackylee-ch/spark that referenced this pull request Feb 18, 2019
This change modifies the logic in the SecurityManager to do two
things:

- generate unique app secrets also when k8s is being used
- only store the secret in the user's UGI on YARN

The latter is needed so that k8s won't unnecessarily create
k8s secrets for the UGI credentials when only the auth token
is stored there.

On the k8s side, the secret is propagated to executors using
an environment variable instead. This ensures it works in both
client and cluster mode.

Security doc was updated to mention the feature and clarify that
proper access control in k8s should be enabled for it to be secure.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes apache#23174 from vanzin/SPARK-26194.
IceMimosa added a commit to growingio/spark that referenced this pull request Apr 12, 2019
…TA/pages/864879077/on+K8S

Fix ImplicitCastInputTypes

[SPARK-25222][K8S] Improve container status logging

[SPARK-25262][K8S] Allow SPARK_LOCAL_DIRS to be tmpfs backed on K8S

[SPARK-25021][K8S] Add spark.executor.pyspark.memory limit for K8S

[SPARK-25415][SQL] Make plan change log in RuleExecutor configurable by SQLConf

In RuleExecutor, after applying a rule, if the plan has changed, the before and after plan will be logged using level "trace". At times, however, such information can be very helpful for debugging. Hence, making the log level configurable in SQLConf would allow users to turn on the plan change log independently and save the trouble of tweaking log4j settings. Meanwhile, filtering plan change log for specific rules can also be very useful.
So this PR adds two SQL configurations:
1. spark.sql.optimizer.planChangeLog.level - set a specific log level for logging plan changes after a rule is applied.
2. spark.sql.optimizer.planChangeLog.rules - enable plan change logging only for a set of specified rules, separated by commas.

Added UT.

Closes apache#22406 from maryannxue/spark-25415.

Authored-by: maryannxue <maryannxue@apache.org>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>

[SPARK-25338][TEST] Ensure to call super.beforeAll() and super.afterAll() in test cases

This PR ensures to call `super.afterAll()` in `override afterAll()` method for test suites.

* Some suites did not call `super.afterAll()`
* Some suites may call `super.afterAll()` only under certain condition
* Others never call `super.afterAll()`.

This PR also ensures to call `super.beforeAll()` in `override beforeAll()` for test suites.

Existing UTs

Closes apache#22337 from kiszk/SPARK-25338.

Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>

[SPARK-25415][SQL][FOLLOW-UP] Add Locale.ROOT when toUpperCase

Add `Locale.ROOT` when `toUpperCase`.

manual tests

Closes apache#22531 from wangyum/SPARK-25415.

Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>

[SPARK-25514][SQL] Generating pretty JSON by to_json

The PR introduces new JSON option `pretty` which allows to turn on `DefaultPrettyPrinter` of `Jackson`'s Json generator. New option is useful in exploring of deep nested columns and in converting of JSON columns in more readable representation (look at the added test).

Added rount trip test which convert an JSON string to pretty representation via `from_json()` and `to_json()`.

Closes apache#22534 from MaxGekk/pretty-json.

Lead-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>

[SPARK-25262][DOC][FOLLOWUP] Fix missing markup tag

This adds a missing end markup tag. This should go `master` branch only.

This is a doc-only change. Manual via `SKIP_API=1 jekyll build`.

Closes apache#22584 from dongjoon-hyun/SPARK-25262.

Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>

[SPARK-23257][K8S] Kerberos Support for Spark on K8S

[SPARK-25682][K8S] Package example jars in same target for dev and distro images.

This way the image generated from both environments has the same layout,
with just a difference in contents that should not affect functionality.

Also added some minor error checking to the image script.

Closes apache#22681 from vanzin/SPARK-25682.

Authored-by: Marcelo Vanzin <vanzin@cloudera.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25745][K8S] Improve docker-image-tool.sh script

Adds error checking and handling to `docker` invocations ensuring the script terminates early in the event of any errors.  This avoids subtle errors that can occur e.g. if the base image fails to build the Python/R images can end up being built from outdated base images and makes it more explicit to the user that something went wrong.

Additionally the provided `Dockerfiles` assume that Spark was first built locally or is a runnable distribution however it didn't previously enforce this.  The script will now check the JARs folder to ensure that Spark JARs actually exist and if not aborts early reminding the user they need to build locally first.

- Tested with a `mvn clean` working copy and verified that the script now terminates early
- Tested with bad `Dockerfiles` that fail to build to see that early termination occurred

Closes apache#22748 from rvesse/SPARK-25745.

Authored-by: Rob Vesse <rvesse@dotnetrdf.org>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25730][K8S] Delete executor pods from kubernetes after figuring out why they died

`removeExecutorFromSpark` tries to fetch the reason the executor exited from Kubernetes, which may be useful if the pod was OOMKilled. However, the code previously deleted the pod from Kubernetes first which made retrieving this status impossible. This fixes the ordering.

On a separate but related note, it would be nice to wait some time before removing the pod - to let the operator examine logs and such.

Running on my local cluster.

Author: Mike Kaplinskiy <mike.kaplinskiy@gmail.com>

Closes apache#22720 from mikekap/patch-1.

[SPARK-25828][K8S] Bumping Kubernetes-Client version to 4.1.

[SPARK-24434][K8S] pod template files

[SPARK-25809][K8S][TEST] New K8S integration testing backends

[SPARK-25875][K8S] Merge code to set up driver command into a single step.

Right now there are 3 different classes dealing with building the driver
command to run inside the pod, one for each "binding" supported by Spark.
This has two main shortcomings:

- the code in the 3 classes is very similar; changing things in one place
  would probably mean making a similar change in the others.

- it gives the false impression that the step implementation is the only
  place where binding-specific logic is needed. That is not true; there
  was code in KubernetesConf that was binding-specific, and there's also
  code in the executor-specific config step. So the 3 classes weren't really
  working as a language-specific abstraction.

On top of that, the current code was propagating command line parameters in
a different way depending on the binding. That doesn't seem necessary, and
in fact using environment variables for command line parameters is in general
a really bad idea, since you can't handle special characters (e.g. spaces)
that way.

This change merges the 3 different code paths for Java, Python and R into
a single step, and also merges the 3 code paths to start the Spark driver
in the k8s entry point script. This increases the amount of shared code,
and also moves more feature logic into the step itself, so it doesn't live
in KubernetesConf.

Note that not all logic related to setting up the driver lives in that
step. For example, the memory overhead calculation still lives separately,
except it now happens in the driver config step instead of outside the
step hierarchy altogether.

Some of the noise in the diff is because of changes to KubernetesConf, which
will be addressed in a separate change.

Tested with new and updated unit tests + integration tests.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes apache#22897 from vanzin/SPARK-25875.

[SPARK-25897][K8S] Hook up k8s integration tests to sbt build.

The integration tests can now be run in sbt if the right profile
is enabled, using the "test" task under the respective project.

This avoids having to fall back to maven to run the tests, which
invalidates all your compiled stuff when you go back to sbt, making
development way slower than it should.

There's also a task to run the tests directly without refreshing
the docker images, which is helpful if you just made a change to
the submission code which should not affect the code in the images.

The sbt tasks currently are not very customizable; there's some
very minor things you can set in the sbt shell itself, but otherwise
it's hardcoded to run on minikube.

I also had to make some slight adjustments to the IT code itself,
mostly to remove assumptions about the existing harness.

Tested on sbt and maven.

Closes apache#22909 from vanzin/SPARK-25897.

Authored-by: Marcelo Vanzin <vanzin@cloudera.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25957][K8S] Make building alternate language binding docker images optional

bin/docker-image-tool.sh tries to build all docker images (JVM, PySpark
and SparkR) by default. But not all spark distributions are built with
SparkR and hence this script will fail on such distros.

With this change, we make building alternate language binding docker images (PySpark and SparkR) optional. User has to specify dockerfile for those language bindings using -p and -R flags accordingly, to build the binding docker images.

Tested following scenarios.
*bin/docker-image-tool.sh -r <repo> -t <tag> build* --> Builds only JVM docker image (default behavior)

*bin/docker-image-tool.sh -r <repo> -t <tag> -p kubernetes/dockerfiles/spark/bindings/python/Dockerfile build* --> Builds both JVM and PySpark docker images

*bin/docker-image-tool.sh -r <repo> -t <tag> -p kubernetes/dockerfiles/spark/bindings/python/Dockerfile -R kubernetes/dockerfiles/spark/bindings/R/Dockerfile build* --> Builds JVM, PySpark and SparkR docker images.

Author: Nagaram Prasad Addepally <ram@cloudera.com>

Closes apache#23053 from ramaddepally/SPARK-25957.

[SPARK-25960][K8S] Support subpath mounting with Kubernetes

This PR adds configurations to use subpaths with Spark on k8s. Subpaths (https://kubernetes.io/docs/concepts/storage/volumes/#using-subpath) allow the user to specify a path within a volume to use instead of the volume's root.

Added unit tests. Ran SparkPi on a cluster with event logging pointed at a subpath-mount and verified the driver host created and used the subpath.

Closes apache#23026 from NiharS/k8s_subpath.

Authored-by: Nihar Sheth <niharrsheth@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26025][K8S] Speed up docker image build on dev repo.

[SPARK-26015][K8S] Set a default UID for Spark on K8S Images

Adds USER directives to the Dockerfiles which is configurable via build argument (`spark_uid`) for easy customisation.  A `-u` flag is added to `bin/docker-image-tool.sh` to make it easy to customise this e.g.

```
> bin/docker-image-tool.sh -r rvesse -t uid -u 185 build
> bin/docker-image-tool.sh -r rvesse -t uid push
```

If no UID is explicitly specified it defaults to `185` - this is per skonto's suggestion to align with the OpenShift standard reserved UID for Java apps (
https://lists.openshift.redhat.com/openshift-archives/users/2016-March/msg00283.html)

Notes:
- We have to make the `WORKDIR` writable by the root group or otherwise jobs will fail with `AccessDeniedException`

To Do:
- [x] Debug and resolve issue with client mode test
- [x] Consider whether to always propagate `SPARK_USER_NAME` to environment of driver and executor pods so `entrypoint.sh` can insert that into `/etc/passwd` entry
- [x] Rebase once PR apache#23013 is merged and update documentation accordingly

Built the Docker images with the new Dockerfiles that include the `USER` directives.  Ran the Spark on K8S integration tests against the new images.  All pass except client mode which I am currently debugging further.

Also manually dropped myself into the resulting container images via `docker run` and checked `id -u` output to see that UID is as expected.

Tried customising the UID from the default via the new `-u` argument to `docker-image-tool.sh` and again checked the resulting image for the correct runtime UID.

cc felixcheung skonto vanzin

Closes apache#23017 from rvesse/SPARK-26015.

Authored-by: Rob Vesse <rvesse@dotnetrdf.org>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25876][K8S] Simplify kubernetes configuration types.

[SPARK-23781][CORE] Merge token renewer functionality into HadoopDelegationTokenManager.

[SPARK-25515][K8S] Adds a config option to keep executor pods for debugging

[SPARK-26083][K8S] Add Copy pyspark into corresponding dir cmd in pyspark Dockerfile

When I try to run `./bin/pyspark` cmd in a pod in Kubernetes(image built without change from pyspark Dockerfile), I'm getting an error:
```
$SPARK_HOME/bin/pyspark --deploy-mode client --master k8s://https://$KUBERNETES_SERVICE_HOST:$KUBERNETES_SERVICE_PORT_HTTPS ...
Python 2.7.15 (default, Aug 22 2018, 13:24:18)
[GCC 6.4.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Could not open PYTHONSTARTUP
IOError: [Errno 2] No such file or directory: '/opt/spark/python/pyspark/shell.py'
```
This is because `pyspark` folder doesn't exist under `/opt/spark/python/`

Added `COPY python/pyspark ${SPARK_HOME}/python/pyspark` to pyspark Dockerfile to resolve issue above.

Google Kubernetes Engine

Closes apache#23037 from AzureQ/master.

Authored-by: Qi Shao <qi.shao.nyu@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26194][K8S] Auto generate auth secret for k8s apps.

This change modifies the logic in the SecurityManager to do two
things:

- generate unique app secrets also when k8s is being used
- only store the secret in the user's UGI on YARN

The latter is needed so that k8s won't unnecessarily create
k8s secrets for the UGI credentials when only the auth token
is stored there.

On the k8s side, the secret is propagated to executors using
an environment variable instead. This ensures it works in both
client and cluster mode.

Security doc was updated to mention the feature and clarify that
proper access control in k8s should be enabled for it to be secure.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes apache#23174 from vanzin/SPARK-26194.

[SPARK-25877][K8S] Move all feature logic to feature classes.

[SPARK-25922][K8] Spark Driver/Executor "spark-app-selector" label mismatch

In K8S Cluster mode, the algorithm to generate spark-app-selector/spark.app.id of spark driver is different with spark executor.
This patch makes sure spark driver and executor to use the same spark-app-selector/spark.app.id if spark.app.id is set, otherwise it will use superclass applicationId.

In K8S Client mode, spark-app-selector/spark.app.id for executors will use superclass applicationId.

Manually run."

Closes apache#23322 from suxingfate/SPARK-25922.

Lead-authored-by: suxingfate <suxingfate@163.com>
Co-authored-by: xinglwang <xinglwang@ebay.com>
Signed-off-by: Yinan Li <ynli@google.com>

[SPARK-26642][K8S] Add --num-executors option to spark-submit for Spark on K8S.

[SPARK-25887][K8S] Configurable K8S context support

This enhancement allows for specifying the desired context to use for the initial K8S client auto-configuration.  This allows users to more easily access alternative K8S contexts without having to first
explicitly change their current context via kubectl.

Explicitly set my K8S context to a context pointing to a non-existent cluster, then launched Spark jobs with explicitly specified contexts via the new `spark.kubernetes.context` configuration property.

Example Output:

```
> kubectl config current-context
minikube
> minikube status
minikube: Stopped
cluster:
kubectl:
> ./spark-submit --master k8s://https://localhost:6443 --deploy-mode cluster --name spark-pi --class org.apache.spark.examples.SparkPi --conf spark.executor.instances=2 --conf spark.kubernetes.context=docker-for-desktop --conf spark.kubernetes.container.image=rvesse/spark:debian local:///opt/spark/examples/jars/spark-examples_2.11-3.0.0-SNAPSHOT.jar 4
18/10/31 11:57:51 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/10/31 11:57:51 INFO SparkKubernetesClientFactory: Auto-configuring K8S client using context docker-for-desktop from users K8S config file
18/10/31 11:57:52 INFO LoggingPodStatusWatcherImpl: State changed, new state:
	 pod name: spark-pi-1540987071845-driver
	 namespace: default
	 labels: spark-app-selector -> spark-2c4abc226ed3415986eb602bd13f3582, spark-role -> driver
	 pod uid: 32462cac-dd04-11e8-b6c6-025000000001
	 creation time: 2018-10-31T11:57:52Z
	 service account name: default
	 volumes: spark-local-dir-1, spark-conf-volume, default-token-glpfv
	 node name: N/A
	 start time: N/A
	 phase: Pending
	 container status: N/A
18/10/31 11:57:52 INFO LoggingPodStatusWatcherImpl: State changed, new state:
	 pod name: spark-pi-1540987071845-driver
	 namespace: default
	 labels: spark-app-selector -> spark-2c4abc226ed3415986eb602bd13f3582, spark-role -> driver
	 pod uid: 32462cac-dd04-11e8-b6c6-025000000001
	 creation time: 2018-10-31T11:57:52Z
	 service account name: default
	 volumes: spark-local-dir-1, spark-conf-volume, default-token-glpfv
	 node name: docker-for-desktop
	 start time: N/A
	 phase: Pending
	 container status: N/A
...
18/10/31 11:58:03 INFO LoggingPodStatusWatcherImpl: State changed, new state:
	 pod name: spark-pi-1540987071845-driver
	 namespace: default
	 labels: spark-app-selector -> spark-2c4abc226ed3415986eb602bd13f3582, spark-role -> driver
	 pod uid: 32462cac-dd04-11e8-b6c6-025000000001
	 creation time: 2018-10-31T11:57:52Z
	 service account name: default
	 volumes: spark-local-dir-1, spark-conf-volume, default-token-glpfv
	 node name: docker-for-desktop
	 start time: 2018-10-31T11:57:52Z
	 phase: Succeeded
	 container status:
		 container name: spark-kubernetes-driver
		 container image: rvesse/spark:debian
		 container state: terminated
		 container started at: 2018-10-31T11:57:54Z
		 container finished at: 2018-10-31T11:58:02Z
		 exit code: 0
		 termination reason: Completed
```

Without the `spark.kubernetes.context` setting this will fail because the current context - `minikube` - is pointing to a non-running cluster e.g.

```
> ./spark-submit --master k8s://https://localhost:6443 --deploy-mode cluster --name spark-pi --class org.apache.spark.examples.SparkPi --conf spark.executor.instances=2 --conf spark.kubernetes.container.image=rvesse/spark:debian local:///opt/spark/examples/jars/spark-examples_2.11-3.0.0-SNAPSHOT.jar 4
18/10/31 12:02:30 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/10/31 12:02:30 INFO SparkKubernetesClientFactory: Auto-configuring K8S client using current context from users K8S config file
18/10/31 12:02:31 WARN WatchConnectionManager: Exec Failure
javax.net.ssl.SSLHandshakeException: 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.ssl.Alerts.getSSLException(Alerts.java:192)
	at sun.security.ssl.SSLSocketImpl.fatal(SSLSocketImpl.java:1949)
	at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:302)
	at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:296)
	at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1509)
	at sun.security.ssl.ClientHandshaker.processMessage(ClientHandshaker.java:216)
	at sun.security.ssl.Handshaker.processLoop(Handshaker.java:979)
	at sun.security.ssl.Handshaker.process_record(Handshaker.java:914)
	at sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:1062)
	at sun.security.ssl.SSLSocketImpl.performInitialHandshake(SSLSocketImpl.java:1375)
	at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1403)
	at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1387)
	at okhttp3.internal.connection.RealConnection.connectTls(RealConnection.java:281)
	at okhttp3.internal.connection.RealConnection.establishProtocol(RealConnection.java:251)
	at okhttp3.internal.connection.RealConnection.connect(RealConnection.java:151)
	at okhttp3.internal.connection.StreamAllocation.findConnection(StreamAllocation.java:195)
	at okhttp3.internal.connection.StreamAllocation.findHealthyConnection(StreamAllocation.java:121)
	at okhttp3.internal.connection.StreamAllocation.newStream(StreamAllocation.java:100)
	at okhttp3.internal.connection.ConnectInterceptor.intercept(ConnectInterceptor.java:42)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.internal.cache.CacheInterceptor.intercept(CacheInterceptor.java:93)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.internal.http.BridgeInterceptor.intercept(BridgeInterceptor.java:93)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RetryAndFollowUpInterceptor.intercept(RetryAndFollowUpInterceptor.java:120)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.BackwardsCompatibilityInterceptor.intercept(BackwardsCompatibilityInterceptor.java:119)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.ImpersonatorInterceptor.intercept(ImpersonatorInterceptor.java:66)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.HttpClientUtils$2.intercept(HttpClientUtils.java:109)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.RealCall.getResponseWithInterceptorChain(RealCall.java:185)
	at okhttp3.RealCall$AsyncCall.execute(RealCall.java:135)
	at okhttp3.internal.NamedRunnable.run(NamedRunnable.java:32)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused by: sun.security.validator.ValidatorException: PKIX path building failed: sun.security.provider.certpath.SunCertPathBuilderException: unable to find valid certification path to requested target
	at sun.security.validator.PKIXValidator.doBuild(PKIXValidator.java:387)
	at sun.security.validator.PKIXValidator.engineValidate(PKIXValidator.java:292)
	at sun.security.validator.Validator.validate(Validator.java:260)
	at sun.security.ssl.X509TrustManagerImpl.validate(X509TrustManagerImpl.java:324)
	at sun.security.ssl.X509TrustManagerImpl.checkTrusted(X509TrustManagerImpl.java:229)
	at sun.security.ssl.X509TrustManagerImpl.checkServerTrusted(X509TrustManagerImpl.java:124)
	at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1491)
	... 39 more
Caused by: sun.security.provider.certpath.SunCertPathBuilderException: unable to find valid certification path to requested target
	at sun.security.provider.certpath.SunCertPathBuilder.build(SunCertPathBuilder.java:141)
	at sun.security.provider.certpath.SunCertPathBuilder.engineBuild(SunCertPathBuilder.java:126)
	at java.security.cert.CertPathBuilder.build(CertPathBuilder.java:280)
	at sun.security.validator.PKIXValidator.doBuild(PKIXValidator.java:382)
	... 45 more
Exception in thread "kubernetes-dispatcher-0" Exception in thread "main" java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask611a9c09 rejected from java.util.concurrent.ScheduledThreadPoolExecutor404819e4[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 0]
	at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2047)
	at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:823)
	at java.util.concurrent.ScheduledThreadPoolExecutor.delayedExecute(ScheduledThreadPoolExecutor.java:326)
	at java.util.concurrent.ScheduledThreadPoolExecutor.schedule(ScheduledThreadPoolExecutor.java:533)
	at java.util.concurrent.ScheduledThreadPoolExecutor.submit(ScheduledThreadPoolExecutor.java:632)
	at java.util.concurrent.Executors$DelegatedExecutorService.submit(Executors.java:678)
	at io.fabric8.kubernetes.client.dsl.internal.WatchConnectionManager.scheduleReconnect(WatchConnectionManager.java:300)
	at io.fabric8.kubernetes.client.dsl.internal.WatchConnectionManager.access$800(WatchConnectionManager.java:48)
	at io.fabric8.kubernetes.client.dsl.internal.WatchConnectionManager$2.onFailure(WatchConnectionManager.java:213)
	at okhttp3.internal.ws.RealWebSocket.failWebSocket(RealWebSocket.java:543)
	at okhttp3.internal.ws.RealWebSocket$2.onFailure(RealWebSocket.java:208)
	at okhttp3.RealCall$AsyncCall.execute(RealCall.java:148)
	at okhttp3.internal.NamedRunnable.run(NamedRunnable.java:32)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
io.fabric8.kubernetes.client.KubernetesClientException: Failed to start websocket
	at io.fabric8.kubernetes.client.dsl.internal.WatchConnectionManager$2.onFailure(WatchConnectionManager.java:204)
	at okhttp3.internal.ws.RealWebSocket.failWebSocket(RealWebSocket.java:543)
	at okhttp3.internal.ws.RealWebSocket$2.onFailure(RealWebSocket.java:208)
	at okhttp3.RealCall$AsyncCall.execute(RealCall.java:148)
	at okhttp3.internal.NamedRunnable.run(NamedRunnable.java:32)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused by: javax.net.ssl.SSLHandshakeException: 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.ssl.Alerts.getSSLException(Alerts.java:192)
	at sun.security.ssl.SSLSocketImpl.fatal(SSLSocketImpl.java:1949)
	at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:302)
	at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:296)
	at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1509)
	at sun.security.ssl.ClientHandshaker.processMessage(ClientHandshaker.java:216)
	at sun.security.ssl.Handshaker.processLoop(Handshaker.java:979)
	at sun.security.ssl.Handshaker.process_record(Handshaker.java:914)
	at sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:1062)
	at sun.security.ssl.SSLSocketImpl.performInitialHandshake(SSLSocketImpl.java:1375)
	at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1403)
	at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1387)
	at okhttp3.internal.connection.RealConnection.connectTls(RealConnection.java:281)
	at okhttp3.internal.connection.RealConnection.establishProtocol(RealConnection.java:251)
	at okhttp3.internal.connection.RealConnection.connect(RealConnection.java:151)
	at okhttp3.internal.connection.StreamAllocation.findConnection(StreamAllocation.java:195)
	at okhttp3.internal.connection.StreamAllocation.findHealthyConnection(StreamAllocation.java:121)
	at okhttp3.internal.connection.StreamAllocation.newStream(StreamAllocation.java:100)
	at okhttp3.internal.connection.ConnectInterceptor.intercept(ConnectInterceptor.java:42)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.internal.cache.CacheInterceptor.intercept(CacheInterceptor.java:93)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.internal.http.BridgeInterceptor.intercept(BridgeInterceptor.java:93)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RetryAndFollowUpInterceptor.intercept(RetryAndFollowUpInterceptor.java:120)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.BackwardsCompatibilityInterceptor.intercept(BackwardsCompatibilityInterceptor.java:119)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.ImpersonatorInterceptor.intercept(ImpersonatorInterceptor.java:66)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at io.fabric8.kubernetes.client.utils.HttpClientUtils$2.intercept(HttpClientUtils.java:109)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:92)
	at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.java:67)
	at okhttp3.RealCall.getResponseWithInterceptorChain(RealCall.java:185)
	at okhttp3.RealCall$AsyncCall.execute(RealCall.java:135)
	... 4 more
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:387)
	at sun.security.validator.PKIXValidator.engineValidate(PKIXValidator.java:292)
	at sun.security.validator.Validator.validate(Validator.java:260)
	at sun.security.ssl.X509TrustManagerImpl.validate(X509TrustManagerImpl.java:324)
	at sun.security.ssl.X509TrustManagerImpl.checkTrusted(X509TrustManagerImpl.java:229)
	at sun.security.ssl.X509TrustManagerImpl.checkServerTrusted(X509TrustManagerImpl.java:124)
	at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1491)
	... 39 more
Caused by: sun.security.provider.certpath.SunCertPathBuilderException: unable to find valid certification path to requested target
	at sun.security.provider.certpath.SunCertPathBuilder.build(SunCertPathBuilder.java:141)
	at sun.security.provider.certpath.SunCertPathBuilder.engineBuild(SunCertPathBuilder.java:126)
	at java.security.cert.CertPathBuilder.build(CertPathBuilder.java:280)
	at sun.security.validator.PKIXValidator.doBuild(PKIXValidator.java:382)
	... 45 more
18/10/31 12:02:31 INFO ShutdownHookManager: Shutdown hook called
18/10/31 12:02:31 INFO ShutdownHookManager: Deleting directory /private/var/folders/6b/y1010qp107j9w2dhhy8csvz0000xq3/T/spark-5e649891-8a0f-4f17-bf3a-33b34082eba8
```

Suggested reviews: mccheah liyinan926 - this is the follow up fix to the bug discovered while working on SPARK-25809 (PR apache#22805)

Closes apache#22904 from rvesse/SPARK-25887.

Authored-by: Rob Vesse <rvesse@dotnetrdf.org>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26685][K8S] Correct placement of ARG declaration

Latest Docker releases are stricter in their enforcement of build argument scope.  The location of the `ARG spark_uid` declaration in the Python and R Dockerfiles means the variable is out of scope by the time it is used in a `USER` declaration resulting in a container running as root rather than the default/configured UID.

Also with some of the refactoring of the script that has happened since my PR that introduced the configurable UID it turns out the `-u <uid>` argument is not being properly passed to the Python and R image builds when those are opted into

This commit moves the `ARG` declaration to just before the argument is used such that it is in scope.  It also ensures that Python and R image builds receive the build arguments that include the `spark_uid` argument where relevant

Prior to the patch images are produced where the Python and R images ignore the default/configured UID:

```
> docker run -it --entrypoint /bin/bash rvesse/spark-py:uid456
bash-4.4# whoami
root
bash-4.4# id -u
0
bash-4.4# exit
> docker run -it --entrypoint /bin/bash rvesse/spark:uid456
bash-4.4$ id -u
456
bash-4.4$ exit
```

Note that the Python image is still running as `root` having ignored the configured UID of 456 while the base image has the correct UID because the relevant `ARG` declaration is correctly in scope.

After the patch the correct UID is observed:

```
> docker run -it --entrypoint /bin/bash rvesse/spark-r:uid456
bash-4.4$ id -u
456
bash-4.4$ exit
exit
> docker run -it --entrypoint /bin/bash rvesse/spark-py:uid456
bash-4.4$ id -u
456
bash-4.4$ exit
exit
> docker run -it --entrypoint /bin/bash rvesse/spark:uid456
bash-4.4$ id -u
456
bash-4.4$ exit
```

Closes apache#23611 from rvesse/SPARK-26685.

Authored-by: Rob Vesse <rvesse@dotnetrdf.org>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26687][K8S] Fix handling of custom Dockerfile paths

With the changes from vanzin's PR apache#23019 (SPARK-26025) we use a pared down temporary Docker build context which significantly improves build times.  However the way this is implemented leads to non-intuitive behaviour when supplying custom Docker file paths.  This is because of the following code snippets:

```
(cd $(img_ctx_dir base) && docker build $NOCACHEARG "${BUILD_ARGS[]}" \
    -t $(image_ref spark) \
    -f "$BASEDOCKERFILE" .)
```

Since the script changes to the temporary build context directory and then runs `docker build` there any path given for the Docker file is taken as relative to the temporary build context directory rather than to the directory where the user invoked the script.  This is rather unintuitive and produces somewhat unhelpful errors e.g.

```
> ./bin/docker-image-tool.sh -r rvesse -t badpath -p resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile build
Sending build context to Docker daemon  218.4MB
Step 1/15 : FROM openjdk:8-alpine
 ---> 5801f7d008e5
Step 2/15 : ARG spark_uid=185
 ---> Using cache
 ---> 5fd63df1ca39
...
Successfully tagged rvesse/spark:badpath
unable to prepare context: unable to evaluate symlinks in Dockerfile path: lstat /Users/rvesse/Documents/Work/Code/spark/target/tmp/docker/pyspark/resource-managers: no such file or directory
Failed to build PySpark Docker image, please refer to Docker build output for details.
```

Here we can see that the relative path that was valid where the user typed the command was not valid inside the build context directory.

To resolve this we need to ensure that we are resolving relative paths to Docker files appropriately which we do by adding a `resolve_file` function to the script and invoking that on the supplied Docker file paths

Validated that relative paths now work as expected:

```
> ./bin/docker-image-tool.sh -r rvesse -t badpath -p resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile build
Sending build context to Docker daemon  218.4MB
Step 1/15 : FROM openjdk:8-alpine
 ---> 5801f7d008e5
Step 2/15 : ARG spark_uid=185
 ---> Using cache
 ---> 5fd63df1ca39
Step 3/15 : RUN set -ex &&     apk upgrade --no-cache &&     apk add --no-cache bash tini libc6-compat linux-pam krb5 krb5-libs &&     mkdir -p /opt/spark &&     mkdir -p /opt/spark/examples &&     mkdir -p /opt/spark/work-dir &&     touch /opt/spark/RELEASE &&     rm /bin/sh &&     ln -sv /bin/bash /bin/sh &&     echo "auth required pam_wheel.so use_uid" >> /etc/pam.d/su &&     chgrp root /etc/passwd && chmod ug+rw /etc/passwd
 ---> Using cache
 ---> eb0a568e032f
Step 4/15 : COPY jars /opt/spark/jars
...
Successfully tagged rvesse/spark:badpath
Sending build context to Docker daemon  6.599MB
Step 1/13 : ARG base_img
Step 2/13 : ARG spark_uid=185
Step 3/13 : FROM $base_img
 ---> 8f4fff16f903
Step 4/13 : WORKDIR /
 ---> Running in 25466e66f27f
Removing intermediate container 25466e66f27f
 ---> 1470b6efae61
Step 5/13 : USER 0
 ---> Running in b094b739df37
Removing intermediate container b094b739df37
 ---> 6a27eb4acad3
Step 6/13 : RUN mkdir ${SPARK_HOME}/python
 ---> Running in bc8002c5b17c
Removing intermediate container bc8002c5b17c
 ---> 19bb12f4286a
Step 7/13 : RUN apk add --no-cache python &&     apk add --no-cache python3 &&     python -m ensurepip &&     python3 -m ensurepip &&     rm -r /usr/lib/python*/ensurepip &&     pip install --upgrade pip setuptools &&     rm -r /root/.cache
 ---> Running in 12dcba5e527f
...
Successfully tagged rvesse/spark-py:badpath
```

Closes apache#23613 from rvesse/SPARK-26687.

Authored-by: Rob Vesse <rvesse@dotnetrdf.org>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26794][SQL] SparkSession enableHiveSupport does not point to hive but in-memory while the SparkContext exists

```java
public class SqlDemo {
    public static void main(final String[] args) throws Exception {
        SparkConf conf = new SparkConf().setAppName("spark-sql-demo");
        JavaSparkContext sc = new JavaSparkContext(conf);
        SparkSession ss = SparkSession.builder().enableHiveSupport().getOrCreate();
        ss.sql("show databases").show();
    }
}
```
Before https://issues.apache.org/jira/browse/SPARK-20946, the demo above point to the right hive metastore if the hive-site.xml is present. But now it can only point to the default in-memory one.

Catalog is now as a variable shared across SparkSessions, it is instantiated with SparkContext's conf. After https://issues.apache.org/jira/browse/SPARK-20946, Session level configs are not pass to SparkContext's conf anymore, so the enableHiveSupport API takes no affect on the catalog instance.

You can set spark.sql.catalogImplementation=hive application wide to solve the problem, or never create a sc before you call SparkSession.builder().enableHiveSupport().getOrCreate()

Here we respect the SparkSession level configuration at the first time to generate catalog within SharedState

1. add ut
2. manually
```scala
test("enableHiveSupport has right to determine the catalog while using an existing sc") {
    val conf = new SparkConf().setMaster("local").setAppName("SharedState Test")
    val sc = SparkContext.getOrCreate(conf)
    val ss = SparkSession.builder().enableHiveSupport().getOrCreate()
    assert(ss.sharedState.externalCatalog.unwrapped.isInstanceOf[HiveExternalCatalog],
      "The catalog should be hive ")

    val ss2 = SparkSession.builder().getOrCreate()
    assert(ss2.sharedState.externalCatalog.unwrapped.isInstanceOf[HiveExternalCatalog],
      "The catalog should be shared across sessions")
  }
```

Without this fix, the above test will fail.
You can apply it to `org.apache.spark.sql.hive.HiveSharedStateSuite`,
and run,
```sbt
./build/sbt  -Phadoop-2.7 -Phive  "hive/testOnly org.apache.spark.sql.hive.HiveSharedStateSuite"
```
to verify.

Closes apache#23709 from yaooqinn/SPARK-26794.

Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

[SPARK-24894][K8S] Make sure valid host names are created for executors.

Since the host name is derived from the app name, which can contain arbitrary
characters, it needs to be sanitized so that only valid characters are allowed.

On top of that, take extra care that truncation doesn't leave characters that
are valid except at the start of a host name.

Closes apache#23781 from vanzin/SPARK-24894.

Authored-by: Marcelo Vanzin <vanzin@cloudera.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25394][CORE] Add an application status metrics source

- Exposes several metrics regarding application status as a source, useful to scrape them via jmx instead of mining the metrics rest api.  Example use case: prometheus + jmx exporter.
- Metrics are gathered when a job ends at the AppStatusListener side, could be more fine-grained but most metrics like tasks completed are also counted by executors. More metrics could be exposed in the future to avoid scraping executors in some scenarios.
- a config option `spark.app.status.metrics.enabled` is added to disable/enable these metrics, by default they are disabled.

This was manually tested with jmx source enabled and prometheus server on k8s:
![metrics](https://user-images.githubusercontent.com/7945591/45300945-63064d00-b518-11e8-812a-d9b4155ba0c0.png)
In the next pic the job delay is shown for repeated pi calculation (Spark action).
![pi](https://user-images.githubusercontent.com/7945591/45329927-89a1a380-b56b-11e8-9cc1-5e76cb83969f.png)

Closes apache#22381 from skonto/add_app_status_metrics.

Authored-by: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-25926][CORE] Move config entries in core module to internal.config.

[SPARK-26489][CORE] Use ConfigEntry for hardcoded configs for python/r categories

[SPARK-26445][CORE] Use ConfigEntry for hardcoded configs for driver/executor categories.

[SPARK-20327][CORE][YARN] Add CLI support for YARN custom resources, like GPUs

[SPARK-26239] File-based secret key loading for SASL.

[SPARK-26482][CORE] Use ConfigEntry for hardcoded configs for ui categories

[SPARK-26466][CORE] Use ConfigEntry for hardcoded configs for submit categories.

[SPARK-24736][K8S] Let spark-submit handle dependency resolution.

[SPARK-26420][K8S] Generate more unique IDs when creating k8s resource names.

Using the current time as an ID is more prone to clashes than people generally
realize, so try to make things a bit more unique without necessarily using a
UUID, which would eat too much space in the names otherwise.

The implemented approach uses some bits from the current time, plus some random
bits, which should be more resistant to clashes.

Closes apache#23805 from vanzin/SPARK-26420.

Authored-by: Marcelo Vanzin <vanzin@cloudera.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

[K8S][MINOR] Log minikube version when running integration tests.

Closes apache#23893 from vanzin/minikube-version.

Authored-by: Marcelo Vanzin <vanzin@cloudera.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26995][K8S] Make ld-linux-x86-64.so.2 visible to snappy native library under /lib in docker image with Alpine Linux

[SPARK-27023][K8S] Make k8s client timeouts configurable

Make k8s client timeouts configurable. No test suite exists for the client factory class, happy to add one if needed

Closes apache#23928 from onursatici/os/k8s-client-timeouts.

Lead-authored-by: Onur Satici <osatici@palantir.com>
Co-authored-by: Onur Satici <onursatici@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

[SPARK-27061][K8S] Expose Driver UI port on driver service to access …

Expose Spark UI port on driver service to access logs from service.

The patch was tested using unit tests being contributed as a part of the PR

Closes apache#23990 from chandulal/SPARK-27061.

Authored-by: chandulal.kavar <cckavar@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26343][K8S] Try to speed up running local k8s integration tests

Speed up running k8s integration tests locally by allowing folks to skip the tgz dist build and extraction

Run tests locally without a distribution of Spark, just a local build

Closes apache#23380 from holdenk/SPARK-26343-Speed-up-running-the-kubernetes-integration-tests-locally.

Authored-by: Holden Karau <holden@pigscanfly.ca>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-26729][K8S] Make image names under test configurable

[SPARK-24793][K8S] Enhance spark-submit for app management

- supports `--kill` & `--status` flags.
- supports globs which is useful in general check this long standing [issue](kubernetes/kubernetes#17144 (comment)) for kubectl.

Manually against running apps. Example output:

Submission Id reported at launch time:

```
2019-01-20 23:47:56 INFO  Client:58 - Waiting for application spark-pi with submissionId spark:spark-pi-1548020873671-driver to finish...
```

Killing the app:

```
./bin/spark-submit --kill spark:spark-pi-1548020873671-driver --master  k8s://https://192.168.2.8:8443
2019-01-20 23:48:07 WARN  Utils:70 - Your hostname, universe resolves to a loopback address: 127.0.0.1; using 192.168.2.8 instead (on interface wlp2s0)
2019-01-20 23:48:07 WARN  Utils:70 - Set SPARK_LOCAL_IP if you need to bind to another address

```

App terminates with 143 (SIGTERM, since we have tiny this should lead to [graceful shutdown](https://cloud.google.com/solutions/best-practices-for-building-containers)):

```
2019-01-20 23:48:08 INFO  LoggingPodStatusWatcherImpl:58 - State changed, new state:
	 pod name: spark-pi-1548020873671-driver
	 namespace: spark
	 labels: spark-app-selector -> spark-e4730c80e1014b72aa77915a2203ae05, spark-role -> driver
	 pod uid: 0ba9a794-1cfd-11e9-8215-a434d9270a65
	 creation time: 2019-01-20T21:47:55Z
	 service account name: spark-sa
	 volumes: spark-local-dir-1, spark-conf-volume, spark-sa-token-b7wcm
	 node name: minikube
	 start time: 2019-01-20T21:47:55Z
	 phase: Running
	 container status:
		 container name: spark-kubernetes-driver
		 container image: skonto/spark:k8s-3.0.0
		 container state: running
		 container started at: 2019-01-20T21:48:00Z
2019-01-20 23:48:09 INFO  LoggingPodStatusWatcherImpl:58 - State changed, new state:
	 pod name: spark-pi-1548020873671-driver
	 namespace: spark
	 labels: spark-app-selector -> spark-e4730c80e1014b72aa77915a2203ae05, spark-role -> driver
	 pod uid: 0ba9a794-1cfd-11e9-8215-a434d9270a65
	 creation time: 2019-01-20T21:47:55Z
	 service account name: spark-sa
	 volumes: spark-local-dir-1, spark-conf-volume, spark-sa-token-b7wcm
	 node name: minikube
	 start time: 2019-01-20T21:47:55Z
	 phase: Failed
	 container status:
		 container name: spark-kubernetes-driver
		 container image: skonto/spark:k8s-3.0.0
		 container state: terminated
		 container started at: 2019-01-20T21:48:00Z
		 container finished at: 2019-01-20T21:48:08Z
		 exit code: 143
		 termination reason: Error
2019-01-20 23:48:09 INFO  LoggingPodStatusWatcherImpl:58 - Container final statuses:
	 container name: spark-kubernetes-driver
	 container image: skonto/spark:k8s-3.0.0
	 container state: terminated
	 container started at: 2019-01-20T21:48:00Z
	 container finished at: 2019-01-20T21:48:08Z
	 exit code: 143
	 termination reason: Error
2019-01-20 23:48:09 INFO  Client:58 - Application spark-pi with submissionId spark:spark-pi-1548020873671-driver finished.
2019-01-20 23:48:09 INFO  ShutdownHookManager:58 - Shutdown hook called
2019-01-20 23:48:09 INFO  ShutdownHookManager:58 - Deleting directory /tmp/spark-f114b2e0-5605-4083-9203-a4b1c1f6059e

```

Glob scenario:

```
./bin/spark-submit --status spark:spark-pi* --master  k8s://https://192.168.2.8:8443
2019-01-20 22:27:44 WARN  Utils:70 - Your hostname, universe resolves to a loopback address: 127.0.0.1; using 192.168.2.8 instead (on interface wlp2s0)
2019-01-20 22:27:44 WARN  Utils:70 - Set SPARK_LOCAL_IP if you need to bind to another address
Application status (driver):
	 pod name: spark-pi-1547948600328-driver
	 namespace: spark
	 labels: spark-app-selector -> spark-f13f01702f0b4503975ce98252d59b94, spark-role -> driver
	 pod uid: c576e1c6-1c54-11e9-8215-a434d9270a65
	 creation time: 2019-01-20T01:43:22Z
	 service account name: spark-sa
	 volumes: spark-local-dir-1, spark-conf-volume, spark-sa-token-b7wcm
	 node name: minikube
	 start time: 2019-01-20T01:43:22Z
	 phase: Running
	 container status:
		 container name: spark-kubernetes-driver
		 container image: skonto/spark:k8s-3.0.0
		 container state: running
		 container started at: 2019-01-20T01:43:27Z
Application status (driver):
	 pod name: spark-pi-1547948792539-driver
	 namespace: spark
	 labels: spark-app-selector -> spark-006d252db9b24f25b5069df357c30264, spark-role -> driver
	 pod uid: 38375b4b-1c55-11e9-8215-a434d9270a65
	 creation time: 2019-01-20T01:46:35Z
	 service account name: spark-sa
	 volumes: spark-local-dir-1, spark-conf-volume, spark-sa-token-b7wcm
	 node name: minikube
	 start time: 2019-01-20T01:46:35Z
	 phase: Succeeded
	 container status:
		 container name: spark-kubernetes-driver
		 container image: skonto/spark:k8s-3.0.0
		 container state: terminated
		 container started at: 2019-01-20T01:46:39Z
		 container finished at: 2019-01-20T01:46:56Z
		 exit code: 0
		 termination reason: Completed

```

Closes apache#23599 from skonto/submit_ops_extension.

Authored-by: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>

[SPARK-24902][K8S] Add PV integration tests

- Adds persistent volume integration tests
- Adds a custom tag to the test to exclude it if it is run against a cloud backend.
- Assumes default fs type for the host, AFAIK that is ext4.

Manually run the tests against minikube as usual:
```
[INFO] --- scalatest-maven-plugin:1.0:test (integration-test)  spark-kubernetes-integration-tests_2.12 ---
Discovery starting.
Discovery completed in 192 milliseconds.
Run starting. Expected test count is: 16
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.
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark with Python2 to test a pyfiles example
- Run PySpark with Python3 to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- Test PVs with local storage
```

Closes apache#23514 from skonto/pvctests.

Authored-by: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Signed-off-by: shane knapp <incomplete@gmail.com>

[SPARK-27216][CORE][BACKPORT-2.4] Upgrade RoaringBitmap to 0.7.45 to fix Kryo unsafe ser/dser issue

Fix ImplicitCastInputTypes
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5 participants