### What changes were proposed in this pull request?
Spark uses an old and deprecated API named `KafkaConsumer.poll(long)` which never returns and stays in live lock if metadata is not updated (for instance when broker disappears at consumer creation). Please see [Kafka documentation](https://kafka.apache.org/25/javadoc/org/apache/kafka/clients/consumer/KafkaConsumer.html#poll-long-) and [standalone test application](https://github.com/gaborgsomogyi/kafka-get-assignment) for further details.
In this PR I've applied the new `KafkaConsumer.poll(Duration)` API on executor side. Please note driver side still uses the old API which will be fixed in SPARK-32032.
### Why are the changes needed?
Infinite wait in `KafkaConsumer.poll(long)`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing unit tests.
Closes#28871 from gaborgsomogyi/SPARK-32033.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
It's quite annoying to be blocked by flaky tests in several PRs. This PR disables them. The tests come from 3 PRs I'm recently watching:
https://github.com/apache/spark/pull/28526https://github.com/apache/spark/pull/28463https://github.com/apache/spark/pull/28517
### Why are the changes needed?
To make PR builder more stable
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
N/A
Closes#28547 from cloud-fan/test.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This patch is to bump the master branch version to 3.1.0-SNAPSHOT.
### Why are the changes needed?
N/A
### Does this PR introduce any user-facing change?
N/A
### How was this patch tested?
N/A
Closes#27698 from gatorsmile/updateVersion.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This patch addresses review comments in #26960 (https://github.com/apache/spark/pull/26960#discussion_r360661930 / https://github.com/apache/spark/pull/26960#discussion_r360661947) which were not addressed in the patch. Addressing these review comments will let the code less dependent on actual implementation as it only relies on `Time` interface in Kafka.
### Why are the changes needed?
These were review comments in previous PR and they bring actual benefit though they're minors.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Existing tests.
Closes#26979 from HeartSaVioR/SPARK-29294-follow-up.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This patch upgrades the version of Kafka to 2.4, which supports Scala 2.13.
There're some incompatible changes in Kafka 2.4 which the patch addresses as well:
* `ZkUtils` is removed -> Replaced with `KafkaZkClient`
* Majority of methods are removed in `AdminUtils` -> Replaced with `AdminZkClient`
* Method signature of `Scheduler.schedule` is changed (return type) -> leverage `DeterministicScheduler` to avoid implementing `ScheduledFuture`
### Why are the changes needed?
* Kafka 2.4 supports Scala 2.13
### Does this PR introduce any user-facing change?
No, as Kafka API is known to be compatible across versions.
### How was this patch tested?
Existing UTs
Closes#26960 from HeartSaVioR/SPARK-29294.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
1. Revert "Preparing development version 3.0.1-SNAPSHOT": 56dcd79
2. Revert "Preparing Spark release v3.0.0-preview2-rc2": c216ef1
### Why are the changes needed?
Shouldn't change master.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
manual test:
https://github.com/apache/spark/compare/5de5e46..wangyum:revert-masterCloses#26915 from wangyum/revert-master.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Yuming Wang <wgyumg@gmail.com>
### What changes were proposed in this pull request?
Kafka producers are now closed when `spark.kafka.producer.cache.timeout` reached which could be significant problem when processing big SQL queries. The workaround was to increase `spark.kafka.producer.cache.timeout` to a number where the biggest SQL query can be finished.
In this PR I've adapted similar solution which already exists on the consumer side, namely applies Apache Commons Pool on the producer side as well. Main advantages choosing this solution:
* Producers are not closed until they're in use
* No manual reference counting needed (which may be error prone)
* Thread-safe by design
* Provides jmx connection to the pool where metrics can be fetched
What this PR contains:
* Introduced producer side parameters to configure pool
* Renamed `InternalKafkaConsumerPool` to `InternalKafkaConnectorPool` and made it abstract
* Created 2 implementations from it: `InternalKafkaConsumerPool` and `InternalKafkaProducerPool`
* Adapted `CachedKafkaProducer` to use `InternalKafkaProducerPool`
* Changed `KafkaDataWriter` and `KafkaDataWriteTask` to release producer even in failure scenario
* Added several new tests
* Extended `KafkaTest` to clear not only producers but consumers as well
* Renamed `InternalKafkaConsumerPoolSuite` to `InternalKafkaConnectorPoolSuite` where only consumer tests are checking the behavior (please see comment for reasoning)
What this PR not yet contains(but intended when the main concept is stable):
* User facing documentation
### Why are the changes needed?
Kafka producer closed after 10 minutes (with default settings).
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Existing + additional unit tests.
Cluster tests being started.
Closes#25853 from gaborgsomogyi/SPARK-21869.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
### What changes were proposed in this pull request?
Sort metadata by the number of messages in each Kafka partition
### Why are the changes needed?
help to find the data skewness problem.
### Does this PR introduce any user-facing change?
Yes, add a column count to the metadata and sort by count
If you set `minPartitions` configurations with structure structured-streaming which doesn't have the Streaming page, my code changes in `DirectKafkaInputDStream` won't affect the WEB UI page just as it shows in the follow image
### How was this patch tested?
Manual test
Closes#26266 from dengziming/feature_ui_optimize.
Lead-authored-by: dengziming <dengziming@growingio.com>
Co-authored-by: dengziming <swzmdeng@163.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
To push the built jars to maven release repository, we need to remove the 'SNAPSHOT' tag from the version name.
Made the following changes in this PR:
* Update all the `3.0.0-SNAPSHOT` version name to `3.0.0-preview`
* Update the sparkR version number check logic to allow jvm version like `3.0.0-preview`
**Please note those changes were generated by the release script in the past, but this time since we manually add tags on master branch, we need to manually apply those changes too.**
We shall revert the changes after 3.0.0-preview release passed.
### Why are the changes needed?
To make the maven release repository to accept the built jars.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A
### What changes were proposed in this pull request?
To push the built jars to maven release repository, we need to remove the 'SNAPSHOT' tag from the version name.
Made the following changes in this PR:
* Update all the `3.0.0-SNAPSHOT` version name to `3.0.0-preview`
* Update the PySpark version from `3.0.0.dev0` to `3.0.0`
**Please note those changes were generated by the release script in the past, but this time since we manually add tags on master branch, we need to manually apply those changes too.**
We shall revert the changes after 3.0.0-preview release passed.
### Why are the changes needed?
To make the maven release repository to accept the built jars.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A
Closes#26243 from jiangxb1987/3.0.0-preview-prepare.
Lead-authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Co-authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
This PR aims to remove `scalatest` deprecation warnings with the following changes.
- `org.scalatest.mockito.MockitoSugar` -> `org.scalatestplus.mockito.MockitoSugar`
- `org.scalatest.selenium.WebBrowser` -> `org.scalatestplus.selenium.WebBrowser`
- `org.scalatest.prop.Checkers` -> `org.scalatestplus.scalacheck.Checkers`
- `org.scalatest.prop.GeneratorDrivenPropertyChecks` -> `org.scalatestplus.scalacheck.ScalaCheckDrivenPropertyChecks`
### Why are the changes needed?
According to the Jenkins logs, there are 118 warnings about this.
```
grep "is deprecated" ~/consoleText | grep scalatest | wc -l
118
```
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
After Jenkins passes, we need to check the Jenkins log.
Closes#25982 from dongjoon-hyun/SPARK-29307.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Scala 2.13 emits a deprecation warning for procedure-like declarations:
```
def foo() {
...
```
This is equivalent to the following, so should be changed to avoid a warning:
```
def foo(): Unit = {
...
```
### Why are the changes needed?
It will avoid about a thousand compiler warnings when we start to support Scala 2.13. I wanted to make the change in 3.0 as there are less likely to be back-ports from 3.0 to 2.4 than 3.1 to 3.0, for example, minimizing that downside to touching so many files.
Unfortunately, that makes this quite a big change.
### Does this PR introduce any user-facing change?
No behavior change at all.
### How was this patch tested?
Existing tests.
Closes#25968 from srowen/SPARK-29291.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This patch enforces tests to prevent leaking newly created SparkContext while is created via initializing StreamingContext. Leaking SparkContext in test would make most of following tests being failed as well, so this patch applies defensive programming, trying its best to ensure SparkContext is cleaned up.
### Why are the changes needed?
We got some case in CI build where SparkContext is being leaked and other tests are affected by leaked SparkContext. Ideally we should isolate the environment among tests if possible.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Modified UTs.
Closes#25709 from HeartSaVioR/SPARK-29007.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
### What changes were proposed in this pull request?
When Task retry happens with Kafka source then it's not known whether the consumer is the issue so the old consumer removed from cache and new consumer created. The feature works fine but not covered with tests.
In this PR I've added such test for DStreams + Structured Streaming.
### Why are the changes needed?
No such tests are there.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Existing + new unit tests.
Closes#25582 from gaborgsomogyi/SPARK-28875.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
This PR fixed typos in comments and replace the explicit type with '<>' for Java 8+.
## How was this patch tested?
Manually tested.
Closes#25338 from younggyuchun/younggyu.
Authored-by: younggyu chun <younggyuchun@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
`DirectKafkaStreamSuite.offset recovery from kafka` commits offsets to Kafka with `Consumer.commitAsync` API (and then reads it back). Since this API is asynchronous it may send notifications late(or not at all). The actual test makes the assumption if the data sent and collected then the offset must be committed as well. This is not true.
In this PR I've made the following modifications:
* Wait for async offset commit before context stopped
* Added commit succeed log to see whether it arrived at all
* Using `ConcurrentHashMap` for committed offsets because 2 threads are using the variable (`JobGenerator` and `ScalaTest...`)
## How was this patch tested?
Existing unit test in a loop + jenkins runs.
Closes#25100 from gaborgsomogyi/SPARK-28335.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
The actual implementation doesn't support multi-cluster Kafka connection with delegation token. In this PR I've added this functionality.
What this PR contains:
* New way of configuration
* Multiple delegation token obtain/store/use functionality
* Documentation
* The change works on DStreams also
## How was this patch tested?
Existing + additional unit tests.
Additionally tested on cluster.
Test scenario:
* 2 * 4 node clusters
* The 4-4 nodes are in different kerberos realms
* Cross-Realm trust between the 2 realms
* Yarn
* Kafka broker version 2.1.0
* security.protocol = SASL_SSL
* sasl.mechanism = SCRAM-SHA-512
* Artificial exceptions during processing
* Source reads from realm1 sink writes to realm2
Kafka broker settings:
* delegation.token.expiry.time.ms=600000 (10 min)
* delegation.token.max.lifetime.ms=1200000 (20 min)
* delegation.token.expiry.check.interval.ms=300000 (5 min)
Closes#24305 from gaborgsomogyi/SPARK-27294.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
Fix build warnings -- see some details below.
But mostly, remove use of postfix syntax where it causes warnings without the `scala.language.postfixOps` import. This is mostly in expressions like "120000 milliseconds". Which, I'd like to simplify to things like "2.minutes" anyway.
## How was this patch tested?
Existing tests.
Closes#24314 from srowen/SPARK-27404.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
I found a lot scattered config in `Kafka` streaming.I think should arrange these config in unified position.
## How was this patch tested?
No need UT.
Closes#24267 from beliefer/arrange-scattered-streaming-kafka-config.
Authored-by: gengjiaan <gengjiaan@360.cn>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Use Single Abstract Method syntax where possible (and minor related cleanup). Comments below. No logic should change here.
## How was this patch tested?
Existing tests.
Closes#24241 from srowen/SPARK-27323.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR aims to update Kafka dependency to 2.2.0 to bring the following improvement and bug fixes.
- https://issues.apache.org/jira/projects/KAFKA/versions/12344063
Due to [KAFKA-4453](https://issues.apache.org/jira/browse/KAFKA-4453), data plane API and controller plane API are separated. Apache Spark needs the following changes.
```scala
- servers.head.apis.metadataCache
+ servers.head.dataPlaneRequestProcessor.metadataCache
```
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#24190 from dongjoon-hyun/SPARK-27260.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
It adds Kafka delegation token support for DStreams. Please be aware as Kafka native sink is not available for DStreams this PR contains delegation token usage only on consumer side.
What this PR contains:
* Usage of token through dynamic JAAS configuration
* `KafkaConfigUpdater` moved to `kafka-0-10-token-provider`
* `KafkaSecurityHelper` functionality moved into `KafkaTokenUtil`
* Documentation
## How was this patch tested?
Existing unit tests + on cluster.
Long running Kafka to file tests on 4 node cluster with randomly thrown artificial exceptions.
Test scenario:
* 4 node cluster
* Yarn
* Kafka broker version 2.1.0
* security.protocol = SASL_SSL
* sasl.mechanism = SCRAM-SHA-512
Kafka broker settings:
* delegation.token.expiry.time.ms=600000 (10 min)
* delegation.token.max.lifetime.ms=1200000 (20 min)
* delegation.token.expiry.check.interval.ms=300000 (5 min)
After each 7.5 minutes new delegation token obtained from Kafka broker (10 min * 0.75).
When token expired after 10 minutes (Spark obtains new one and doesn't renew the old), the brokers expiring thread comes after each 5 minutes (invalidates expired tokens) and artificial exception has been thrown inside the Spark application (such case Spark closes connection), then the latest delegation token picked up correctly.
cd docs/
SKIP_API=1 jekyll build
Manual webpage check.
Closes#23929 from gaborgsomogyi/SPARK-27022.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
In the PR, I propose to use `System.nanoTime()` instead of `System.currentTimeMillis()` in measurements of time intervals.
`System.currentTimeMillis()` returns current wallclock time and will follow changes to the system clock. Thus, negative wallclock adjustments can cause timeouts to "hang" for a long time (until wallclock time has caught up to its previous value again). This can happen when ntpd does a "step" after the network has been disconnected for some time. The most canonical example is during system bootup when DHCP takes longer than usual. This can lead to failures that are really hard to understand/reproduce. `System.nanoTime()` is guaranteed to be monotonically increasing irrespective of wallclock changes.
## How was this patch tested?
By existing test suites.
Closes#23727 from MaxGekk/system-nanotime.
Lead-authored-by: Maxim Gekk <max.gekk@gmail.com>
Co-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
It adds kafka delegation token support for structured streaming. Please see the relevant [SPIP](https://docs.google.com/document/d/1ouRayzaJf_N5VQtGhVq9FURXVmRpXzEEWYHob0ne3NY/edit?usp=sharing)
What this PR contains:
* Configuration parameters for the feature
* Delegation token fetching from broker
* Usage of token through dynamic JAAS configuration
* Minor refactoring in the existing code
What this PR doesn't contain:
* Documentation changes because design can change
## How was this patch tested?
Existing tests + added small amount of additional unit tests.
Because it's an external service integration mainly tested on cluster.
* 4 node cluster
* Kafka broker version 1.1.0
* Topic with 4 partitions
* security.protocol = SASL_SSL
* sasl.mechanism = SCRAM-SHA-256
An example of obtaining a token:
```
18/10/01 01:07:49 INFO kafka010.TokenUtil: TOKENID HMAC OWNER RENEWERS ISSUEDATE EXPIRYDATE MAXDATE
18/10/01 01:07:49 INFO kafka010.TokenUtil: D1-v__Q5T_uHx55rW16Jwg [hidden] User:user [] 2018-10-01T01:07 2018-10-02T01:07 2018-10-08T01:07
18/10/01 01:07:49 INFO security.KafkaDelegationTokenProvider: Get token from Kafka: Kind: KAFKA_DELEGATION_TOKEN, Service: kafka.server.delegation.token, Ident: 44 31 2d 76 5f 5f 51 35 54 5f 75 48 78 35 35 72 57 31 36 4a 77 67
```
An example token usage:
```
18/10/01 01:08:07 INFO kafka010.KafkaSecurityHelper: Scram JAAS params: org.apache.kafka.common.security.scram.ScramLoginModule required tokenauth=true serviceName="kafka" username="D1-v__Q5T_uHx55rW16Jwg" password="[hidden]";
18/10/01 01:08:07 INFO kafka010.KafkaSourceProvider: Delegation token detected, using it for login.
```
Closes#22598 from gaborgsomogyi/SPARK-25501.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
This is a followup of #23099 . After upgrading to Kafka 2.1.0, maven test fails due to Zookeeper test dependency while sbt test succeeds.
- [sbt test on master branch](https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-sbt-hadoop-2.7/5203/)
- [maven test on master branch](https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-2.7/5653/)
The root cause is that the embedded Kafka server is using [Zookeepr 3.4.7 API](https://zookeeper.apache.org/doc/r3.4.7/api/org/apache/zookeeper/AsyncCallback.MultiCallback.html
) while Apache Spark provides Zookeeper 3.4.6. This PR adds a test dependency.
```
KafkaMicroBatchV2SourceSuite:
*** RUN ABORTED ***
...
org.apache.spark.sql.kafka010.KafkaTestUtils.setupEmbeddedKafkaServer(KafkaTestUtils.scala:123)
...
Cause: java.lang.ClassNotFoundException: org.apache.zookeeper.AsyncCallback$MultiCallback
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:331)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at kafka.zk.KafkaZkClient$.apply(KafkaZkClient.scala:1693)
at kafka.server.KafkaServer.createZkClient$1(KafkaServer.scala:348)
at kafka.server.KafkaServer.initZkClient(KafkaServer.scala:372)
at kafka.server.KafkaServer.startup(KafkaServer.scala:202)
at org.apache.spark.sql.kafka010.KafkaTestUtils.$anonfun$setupEmbeddedKafkaServer$2(KafkaTestUtils.scala:120)
at org.apache.spark.sql.kafka010.KafkaTestUtils.$anonfun$setupEmbeddedKafkaServer$2$adapted(KafkaTestUtils.scala:116)
...
```
## How was this patch tested?
Pass the maven Jenkins test.
Closes#23119 from dongjoon-hyun/SPARK-25954-2.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
The build has a lot of deprecation warnings. Some are new in Scala 2.12 and Java 11. We've fixed some, but I wanted to take a pass at fixing lots of easy miscellaneous ones here.
They're too numerous and small to list here; see the pull request. Some highlights:
- `BeanInfo` is deprecated in 2.12, and BeanInfo classes are pretty ancient in Java. Instead, case classes can explicitly declare getters
- Eta expansion of zero-arg methods; foo() becomes () => foo() in many cases
- Floating-point Range is inexact and deprecated, like 0.0 to 100.0 by 1.0
- finalize() is finally deprecated (just needs to be suppressed)
- StageInfo.attempId was deprecated and easiest to remove here
I'm not now going to touch some chunks of deprecation warnings:
- Parquet deprecations
- Hive deprecations (particularly serde2 classes)
- Deprecations in generated code (mostly Thriftserver CLI)
- ProcessingTime deprecations (we may need to revive this class as internal)
- many MLlib deprecations because they concern methods that may be removed anyway
- a few Kinesis deprecations I couldn't figure out
- Mesos get/setRole, which I don't know well
- Kafka/ZK deprecations (e.g. poll())
- Kinesis
- a few other ones that will probably resolve by deleting a deprecated method
## How was this patch tested?
Existing tests, including manual testing with the 2.11 build and Java 11.
Closes#23065 from srowen/SPARK-26090.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR makes Spark's default Scala version as 2.12, and Scala 2.11 will be the alternative version. This implies that Scala 2.12 will be used by our CI builds including pull request builds.
We'll update the Jenkins to include a new compile-only jobs for Scala 2.11 to ensure the code can be still compiled with Scala 2.11.
## How was this patch tested?
existing tests
Closes#22967 from dbtsai/scala2.12.
Authored-by: DB Tsai <d_tsai@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Add scala and java lint check rules to ban the usage of `throw new xxxErrors` and fix up all exists instance followed by https://github.com/apache/spark/pull/22989#issuecomment-437939830. See more details in https://github.com/apache/spark/pull/22969.
## How was this patch tested?
Local test with lint-scala and lint-java.
Closes#22989 from xuanyuanking/SPARK-25986.
Authored-by: Yuanjian Li <xyliyuanjian@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Deprecated in Java 11, replace Class.newInstance with Class.getConstructor.getInstance, and primtive wrapper class constructors with valueOf or equivalent
## How was this patch tested?
Existing tests.
Closes#22988 from srowen/SPARK-25984.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Set a reasonable poll timeout thats used while consuming topics/partitions from kafka. In the
absence of it, a default of 2 minute is used as the timeout values. And all the negative tests take a minimum of 2 minute to execute.
After this change, we save about 4 minutes in this suite.
## How was this patch tested?
Test fix.
Closes#22670 from dilipbiswal/SPARK-25631.
Authored-by: Dilip Biswal <dbiswal@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Remove Kafka 0.8 integration
## How was this patch tested?
Existing tests, build scripts
Closes#22703 from srowen/SPARK-25705.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Removes all vestiges of Flume in the build, for Spark 3.
I don't think this needs Jenkins config changes.
## How was this patch tested?
Existing tests.
Closes#22692 from srowen/SPARK-25598.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This patch is to bump the master branch version to 3.0.0-SNAPSHOT.
## How was this patch tested?
N/A
Closes#22606 from gatorsmile/bump3.0.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
In the dev list, we can still discuss whether the next version is 2.5.0 or 3.0.0. Let us first bump the master branch version to `2.5.0-SNAPSHOT`.
## How was this patch tested?
N/A
Closes#22426 from gatorsmile/bumpVersionMaster.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
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.
## How was this patch tested?
Existing UTs
Closes#22337 from kiszk/SPARK-25338.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
After SPARK-18371, it is guaranteed that there would be at least one message per partition per batch using direct kafka API when new messages exist in the topics. This change will give the user the option of setting the minimum instead of just a hard coded 1 limit
The related unit test is updated and some internal tests verified that the topic partitions with new messages will be progressed by the specified minimum.
Author: Reza Safi <rezasafi@cloudera.com>
Closes#22223 from rezasafi/streaminglag.
## What changes were proposed in this pull request?
KafkaContinuousSinkSuite leaks a Kafka cluster because both KafkaSourceTest and KafkaContinuousSinkSuite create a Kafka cluster but `afterAll` only shuts down one cluster. This leaks a Kafka cluster and causes that some Kafka thread crash and kill JVM when SBT is trying to clean up tests.
This PR fixes the leak and also adds a shut down hook to detect Kafka cluster leak.
In additions, it also fixes `AdminClient` leak and cleans up cached producers (When a record is writtn using a producer, the producer will keep refreshing the topic and I don't find an API to clear it except closing the producer) to eliminate the following annoying logs:
```
8/13 15:34:42.568 kafka-admin-client-thread | adminclient-4 WARN NetworkClient: [AdminClient clientId=adminclient-4] Connection to node 0 could not be established. Broker may not be available.
18/08/13 15:34:42.570 kafka-admin-client-thread | adminclient-6 WARN NetworkClient: [AdminClient clientId=adminclient-6] Connection to node 0 could not be established. Broker may not be available.
18/08/13 15:34:42.606 kafka-admin-client-thread | adminclient-8 WARN NetworkClient: [AdminClient clientId=adminclient-8] Connection to node -1 could not be established. Broker may not be available.
18/08/13 15:34:42.729 kafka-producer-network-thread | producer-797 WARN NetworkClient: [Producer clientId=producer-797] Connection to node -1 could not be established. Broker may not be available.
18/08/13 15:34:42.906 kafka-producer-network-thread | producer-1598 WARN NetworkClient: [Producer clientId=producer-1598] Connection to node 0 could not be established. Broker may not be available.
```
I also reverted b5eb54244e introduced by #22097 since it doesn't help.
## How was this patch tested?
Jenkins
Closes#22106 from zsxwing/SPARK-25116.
Authored-by: Shixiong Zhu <zsxwing@gmail.com>
Signed-off-by: Shixiong Zhu <zsxwing@gmail.com>
## What changes were proposed in this pull request?
I'm still seeing the Kafka tests failed randomly due to `kafka.zookeeper.ZooKeeperClientTimeoutException: Timed out waiting for connection while in state: CONNECTING`. I checked the test output and saw zookeeper picked up an ipv6 address. Most details can be found in https://issues.apache.org/jira/browse/KAFKA-7193
This PR just uses `127.0.0.1` rather than `localhost` to make sure zookeeper will never use an ipv6 address.
## How was this patch tested?
Jenkins
Closes#22097 from zsxwing/fix-zookeeper-connect.
Authored-by: Shixiong Zhu <zsxwing@gmail.com>
Signed-off-by: Shixiong Zhu <zsxwing@gmail.com>
## What changes were proposed in this pull request?
Increase ZK timeout and harmonize configs across Kafka tests to resol…ve potentially flaky test failure
## How was this patch tested?
Existing tests
Author: Sean Owen <srowen@gmail.com>
Closes#21995 from srowen/SPARK-18057.3.
## What changes were proposed in this pull request?
Update to kafka 2.0.0 in streaming-kafka module, and remove override for Scala 2.12. It won't compile for 2.12 otherwise.
## How was this patch tested?
Existing tests.
Author: Sean Owen <srowen@gmail.com>
Closes#21955 from srowen/SPARK-18057.2.
## What changes were proposed in this pull request?
This PR addresses issues 2,3 in this [document](https://docs.google.com/document/d/1fbkjEL878witxVQpOCbjlvOvadHtVjYXeB-2mgzDTvk).
* We modified the closure cleaner to identify closures that are implemented via the LambdaMetaFactory mechanism (serializedLambdas) (issue2).
* We also fix the issue due to scala/bug#11016. There are two options for solving the Unit issue, either add () at the end of the closure or use the trick described in the doc. Otherwise overloading resolution does not work (we are not going to eliminate either of the methods) here. Compiler tries to adapt to Unit and makes these two methods candidates for overloading, when there is polymorphic overloading there is no ambiguity (that is the workaround implemented). This does not look that good but it serves its purpose as we need to support two different uses for method: `addTaskCompletionListener`. One that passes a TaskCompletionListener and one that passes a closure that is wrapped with a TaskCompletionListener later on (issue3).
Note: regarding issue 1 in the doc the plan is:
> Do Nothing. Don’t try to fix this as this is only a problem for Java users who would want to use 2.11 binaries. In that case they can cast to MapFunction to be able to utilize lambdas. In Spark 3.0.0 the API should be simplified so that this issue is removed.
## How was this patch tested?
This was manually tested:
```./dev/change-scala-version.sh 2.12
./build/mvn -DskipTests -Pscala-2.12 clean package
./build/mvn -Pscala-2.12 clean package -DwildcardSuites=org.apache.spark.serializer.ProactiveClosureSerializationSuite -Dtest=None
./build/mvn -Pscala-2.12 clean package -DwildcardSuites=org.apache.spark.util.ClosureCleanerSuite -Dtest=None
./build/mvn -Pscala-2.12 clean package -DwildcardSuites=org.apache.spark.streaming.DStreamClosureSuite -Dtest=None```
Author: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Closes#21930 from skonto/scala2.12-sup.
