### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
This reverts commit 92877c4ef2.
Closes#28602 from gengliangwang/revertSPARK-31765.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### 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>
This PR aims to upgrade Py4J to `0.10.9` for better Python 3.7 support in Apache Spark 3.0.0 (master/branch-3.0). This is not for `branch-2.4`.
- Apache Spark 3.0.0 is using `Py4J 0.10.8.1` (released on 2018-10-21) because `0.10.8.1` was the first official release to support Python 3.7.
- https://www.py4j.org/changelog.html#py4j-0-10-8-and-py4j-0-10-8-1
- `Py4J 0.10.9` was released on January 25th 2020 with better Python 3.7 support and `magic_member` bug fix.
- https://github.com/bartdag/py4j/releases/tag/0.10.9
- https://www.py4j.org/changelog.html#py4j-0-10-9
No.
Pass the Jenkins with the existing tests.
Closes#27641 from dongjoon-hyun/SPARK-30884.
Authored-by: Dongjoon Hyun <dhyun@apple.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?
Move some classes extending Scala collections into parallel source trees, to support 2.13; other minor collection-related modifications.
Modify some classes extending Scala collections to work with 2.13 as well as 2.12. In many cases, this means introducing parallel source trees, as the type hierarchy changed in ways that one class can't support both.
### Why are the changes needed?
To support building for Scala 2.13 in the future.
### Does this PR introduce any user-facing change?
There should be no behavior change.
### How was this patch tested?
Existing tests. Note that the 2.13 changes are not tested by the PR builder, of course. They compile in 2.13 but can't even be tested locally. Later, once the project can be compiled for 2.13, thus tested, it's possible the 2.13 implementations will need updates.
Closes#26728 from srowen/SPARK-30012.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Make separate source trees for Scala 2.12/2.13 in order to accommodate mutually-incompatible support for Ordering of double, float.
Note: This isn't the last change that will need a split source tree for 2.13. But this particular change could go several ways:
- (Split source tree)
- Inline the Scala 2.12 implementation
- Reflection
For this change alone any are possible, and splitting the source tree is a bit overkill. But if it will be necessary for other JIRAs (see umbrella SPARK-25075), then it might be the easiest way to implement this.
### Why are the changes needed?
Scala 2.13 split Ordering.Double into Ordering.Double.TotalOrdering and Ordering.Double.IeeeOrdering. Neither can be used in a single build that supports 2.12 and 2.13.
TotalOrdering works like java.lang.Double.compare. IeeeOrdering works like Scala 2.12 Ordering.Double. They differ in how NaN is handled - compares always above other values? or always compares as 'false'? In theory they have different uses: TotalOrdering is important if floating-point values are sorted. IeeeOrdering behaves like 2.12 and JVM comparison operators.
I chose TotalOrdering as I think we care more about stable sorting, and because elsewhere we rely on java.lang comparisons. It is also possible to support with two methods.
### Does this PR introduce any user-facing change?
Pending tests, will see if it obviously affects any sort order. We need to see if it changes NaN sort order.
### How was this patch tested?
Existing tests so far.
Closes#26654 from srowen/SPARK-30009.
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 remove the unused test dependency `commons-lang:commons-lang` from `core` module.
### Why are the changes needed?
SPARK-30030 already removed all usage of `Apache Commons Lang2` in `core`.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Pass the Jenkins.
Closes#26673 from dongjoon-hyun/SPARK-30030-2.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
# What changes were proposed in this pull request?
This PR aims to relocate the following internal dependencies to compile `sql/core` without `-Phive-2.3` profile.
1. Move the `hive-storage-api` to `sql/core` which is using `hive-storage-api` really.
**BEFORE (sql/core compilation)**
```
$ ./build/mvn -DskipTests --pl sql/core --am compile
...
[ERROR] [Error] /Users/dongjoon/APACHE/spark/sql/core/v2.3/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala:21: object hive is not a member of package org.apache.hadoop
...
[INFO] ------------------------------------------------------------------------
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
```
**AFTER (sql/core compilation)**
```
$ ./build/mvn -DskipTests --pl sql/core --am compile
...
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 02:04 min
[INFO] Finished at: 2019-11-25T00:20:11-08:00
[INFO] ------------------------------------------------------------------------
```
2. For (1), add `commons-lang:commons-lang` test dependency to `spark-core` module to manage the dependency explicitly. Without this, `core` module fails to build the test classes.
```
$ ./build/mvn -DskipTests --pl core --am package -Phadoop-3.2
...
[INFO] --- scala-maven-plugin:4.3.0:testCompile (scala-test-compile-first) spark-core_2.12 ---
[INFO] Using incremental compilation using Mixed compile order
[INFO] Compiler bridge file: /Users/dongjoon/.sbt/1.0/zinc/org.scala-sbt/org.scala-sbt-compiler-bridge_2.12-1.3.1-bin_2.12.10__52.0-1.3.1_20191012T045515.jar
[INFO] Compiling 271 Scala sources and 26 Java sources to /spark/core/target/scala-2.12/test-classes ...
[ERROR] [Error] /spark/core/src/test/scala/org/apache/spark/util/PropertiesCloneBenchmark.scala:23: object lang is not a member of package org.apache.commons
[ERROR] [Error] /spark/core/src/test/scala/org/apache/spark/util/PropertiesCloneBenchmark.scala:49: not found: value SerializationUtils
[ERROR] two errors found
```
**BEFORE (commons-lang:commons-lang)**
The following is the previous `core` module's `commons-lang:commons-lang` dependency.
1. **branch-2.4**
```
$ mvn dependency:tree -Dincludes=commons-lang:commons-lang
[INFO] --- maven-dependency-plugin:3.0.2:tree (default-cli) spark-core_2.11 ---
[INFO] org.apache.spark:spark-core_2.11🫙2.4.5-SNAPSHOT
[INFO] \- org.spark-project.hive:hive-exec:jar:1.2.1.spark2:provided
[INFO] \- commons-lang:commons-lang:jar:2.6:compile
```
2. **v3.0.0-preview (-Phadoop-3.2)**
```
$ mvn dependency:tree -Dincludes=commons-lang:commons-lang -Phadoop-3.2
[INFO] --- maven-dependency-plugin:3.1.1:tree (default-cli) spark-core_2.12 ---
[INFO] org.apache.spark:spark-core_2.12🫙3.0.0-preview
[INFO] \- org.apache.hive:hive-storage-api:jar:2.6.0:compile
[INFO] \- commons-lang:commons-lang:jar:2.6:compile
```
3. **v3.0.0-preview(default)**
```
$ mvn dependency:tree -Dincludes=commons-lang:commons-lang
[INFO] --- maven-dependency-plugin:3.1.1:tree (default-cli) spark-core_2.12 ---
[INFO] org.apache.spark:spark-core_2.12🫙3.0.0-preview
[INFO] \- org.apache.hadoop:hadoop-client:jar:2.7.4:compile
[INFO] \- org.apache.hadoop:hadoop-common:jar:2.7.4:compile
[INFO] \- commons-lang:commons-lang:jar:2.6:compile
```
**AFTER (commons-lang:commons-lang)**
```
$ mvn dependency:tree -Dincludes=commons-lang:commons-lang
[INFO] --- maven-dependency-plugin:3.1.1:tree (default-cli) spark-core_2.12 ---
[INFO] org.apache.spark:spark-core_2.12🫙3.0.0-SNAPSHOT
[INFO] \- commons-lang:commons-lang:jar:2.6:test
```
Since we wanted to verify that this PR doesn't change `hive-1.2` profile, we merged
[SPARK-30005 Update `test-dependencies.sh` to check `hive-1.2/2.3` profile](a1706e2fa7) before this PR.
### Why are the changes needed?
- Apache Spark 2.4's `sql/core` is using `Apache ORC (nohive)` jars including shaded `hive-storage-api` to access ORC data sources.
- Apache Spark 3.0's `sql/core` is using `Apache Hive` jars directly. Previously, `-Phadoop-3.2` hid this `hive-storage-api` dependency. Now, we are using `-Phive-2.3` instead. As I mentioned [previously](https://github.com/apache/spark/pull/26619#issuecomment-556926064), this PR is required to compile `sql/core` module without `-Phive-2.3`.
- For `sql/hive` and `sql/hive-thriftserver`, it's natural that we need `-Phive-1.2` or `-Phive-2.3`.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
This will pass the Jenkins (with the dependency check and unit tests).
We need to check manually with `./build/mvn -DskipTests --pl sql/core --am compile`.
This closes#26657 .
Closes#26658 from dongjoon-hyun/SPARK-30015.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Update the version of dropwizard metrics that Spark uses for metrics to 4.1.x, from 3.2.x.
### Why are the changes needed?
This helps JDK 9+ support, per for example https://github.com/dropwizard/metrics/pull/1236
### Does this PR introduce any user-facing change?
No, although downstream users with custom metrics may be affected.
### How was this patch tested?
Existing tests.
Closes#26332 from srowen/SPARK-29674.
Authored-by: Sean Owen <sean.owen@databricks.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?
Scala 2.13 removes the parallel collections classes to a separate library, so first, this establishes a `scala-2.13` profile to bring it back, for future use.
However the library enables use of `.par` implicit conversions via a new class that is not in 2.12, which makes cross-building hard. This implements a suggested workaround from https://github.com/scala/scala-parallel-collections/issues/22 to avoid `.par` entirely.
### Why are the changes needed?
To compile for 2.13 and later to work with 2.13.
### Does this PR introduce any user-facing change?
Should not, no.
### How was this patch tested?
Existing tests.
Closes#25980 from srowen/SPARK-29296.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
This PR is an enhanced version of https://github.com/apache/spark/pull/25805 so I've kept the original text. The problem with the original PR can be found in comment.
This situation can happen when an external system (e.g. Oozie) generates
delegation tokens for a Spark application. The Spark driver will then run
against secured services, have proper credentials (the tokens), but no
kerberos credentials. So trying to do things that requires a kerberos
credential fails.
Instead, if no kerberos credentials are detected, just skip the whole
delegation token code.
Tested with an application that simulates Oozie; fails before the fix,
passes with the fix. Also with other DT-related tests to make sure other
functionality keeps working.
Closes#25901 from gaborgsomogyi/SPARK-29082.
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?
Spark uses Netty 4 directly, but also includes Netty 3 only because transitive dependencies do. The dependencies (Hadoop HDFS, Zookeeper, Avro) don't seem to need this dependency as used in Spark. I think we can forcibly remove it to slim down the dependencies.
Previous attempts were blocked by its usage in Flume, but that dependency has gone away.
https://github.com/apache/spark/pull/15436
### Why are the changes needed?
Mostly to reduce the transitive dependency size and complexity a little bit and avoid triggering spurious security alerts on Netty 3.x usage.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing tests
Closes#25544 from srowen/SPARK-17875.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Update Jersey to 2.27+, ideally 2.29, for possible JDK 11 fixes.
## How was this patch tested?
Existing tests.
Closes#25455 from srowen/SPARK-28737.
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 upgraded to a newer version of Pyrolite. Most updates [1] in the newer version are for dotnot. For java, it includes a bug fix to Unpickler regarding cleaning up Unpickler memo, and support of protocol 5.
After upgrading, we can remove the fix at SPARK-27629 for the bug in Unpickler.
[1] https://github.com/irmen/Pyrolite/compare/pyrolite-4.23...master
## How was this patch tested?
Manually tested on Python 3.6 in local on existing tests.
Closes#25143 from viirya/upgrade-pyrolite.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
We're using an old-ish jQuery, 1.12.4, and should probably update for Spark 3 to keep up in general, but also to keep up with CVEs. In fact, we know of at least one resolved in only 3.4.0+ (https://nvd.nist.gov/vuln/detail/CVE-2019-11358). They may not affect Spark, but, if the update isn't painful, maybe worthwhile in order to make future 3.x updates easier.
jQuery 1 -> 2 doesn't sound like a breaking change, as 2.0 is supposed to maintain compatibility with 1.9+ (https://blog.jquery.com/2013/04/18/jquery-2-0-released/)
2 -> 3 has breaking changes: https://jquery.com/upgrade-guide/3.0/. It's hard to evaluate each one, but the most likely area for problems is in ajax(). However, our usage of jQuery (and plugins) is pretty simple.
Update jquery to 3.4.1; update jquery blockUI and mustache to latest
## How was this patch tested?
Manual testing of docs build (except R docs), worker/master UI, spark application UI.
Note: this really doesn't guarantee it works, as our tests can't test javascript, and this is merely anecdotal testing, although I clicked about every link I could find. There's a risk this breaks a minor part of the UI; it does seem to work fine in the main.
Closes#24843 from srowen/SPARK-28004.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Move to json4s version 3.6.6
Add scala-xml 1.2.0
## How was this patch tested?
Pass the Jenkins
Closes#24736 from igreenfield/master.
Authored-by: Izek Greenfield <igreenfield@axiomsl.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Update pyrolite to 4.23 to pick up bug and security fixes.
## How was this patch tested?
Existing tests.
Closes#24381 from srowen/SPARK-27470.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
As we all know that spark on Yarn uses DB https://github.com/apache/spark/pull/7943 to record RegisteredExecutors information which can be reloaded and used again when the ExternalShuffleService is restarted .
The RegisteredExecutors information can't be recorded both in the mode of spark's standalone and spark on k8s , which will cause the RegisteredExecutors information to be lost ,when the ExternalShuffleService is restarted.
To solve the problem above, a method is proposed and is committed .
## How was this patch tested?
new unit tests
Closes#23393 from weixiuli/SPARK-26288.
Authored-by: weixiuli <weixiuli@jd.com>
Signed-off-by: Imran Rashid <irashid@cloudera.com>
## What changes were proposed in this pull request?
Fasterxml Jackson version before 2.9.8 is affected by multiple [CVEs](https://github.com/FasterXML/jackson-databind/issues/2186), we need to fix bump the dependent Jackson to 2.9.8.
## How was this patch tested?
Existing tests and offline benchmark.
I have run ```SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.datasources.json.JSONBenchmark"``` to check there is no performance degradation for this upgrade.
Closes#23965 from yanboliang/SPARK-27051.
Authored-by: Yanbo Liang <ybliang8@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
There are ugly provided dependencies inside core for the following:
* Hive
* Kafka
In this PR I've extracted them out. This PR contains the following:
* Token providers are now loaded with service loader
* Hive token provider moved to hive project
* Kafka token provider extracted into a new project
## How was this patch tested?
Existing + newly added unit tests.
Additionally tested on cluster.
Closes#23499 from gaborgsomogyi/SPARK-26254.
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?
With Scala-2.12 profile, Spark application fails while Spark is okay. For example, our documented `SimpleApp` Java example succeeds to compile but it fails at runtime because it doesn't use `paranamer 2.8` and hits [SPARK-22128](https://issues.apache.org/jira/browse/SPARK-22128). This PR aims to declare it explicitly for the Spark applications. Note that this doesn't introduce new dependency to Spark itself.
https://dist.apache.org/repos/dist/dev/spark/3.0.0-SNAPSHOT-2019_01_09_13_59-e853afb-docs/_site/quick-start.html
The following is the dependency tree from the Spark application.
**BEFORE**
```
$ mvn dependency:tree -Dincludes=com.thoughtworks.paranamer
[INFO] --- maven-dependency-plugin:2.8:tree (default-cli) simple ---
[INFO] my.test:simple:jar:1.0-SNAPSHOT
[INFO] \- org.apache.spark:spark-sql_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.spark:spark-core_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.avro:avro:jar:1.8.2:compile
[INFO] \- com.thoughtworks.paranamer:paranamer:jar:2.7:compile
```
**AFTER**
```
[INFO] --- maven-dependency-plugin:2.8:tree (default-cli) simple ---
[INFO] my.test:simple:jar:1.0-SNAPSHOT
[INFO] \- org.apache.spark:spark-sql_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.spark:spark-core_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- com.thoughtworks.paranamer:paranamer:jar:2.8:compile
```
## How was this patch tested?
Pass the Jenkins. And manually test with the sample app is running.
Closes#23502 from dongjoon-hyun/SPARK-26583.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## 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 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?
Upgrade ASM to 7.x to support JDK11
## How was this patch tested?
Existing tests.
Closes#22953 from dbtsai/asm7.
Authored-by: DB Tsai <d_tsai@apple.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
## What changes were proposed in this pull request?
Py4J 0.10.8.1 is released on October 21st and is the first release of Py4J to support Python 3.7 officially. We had better have this to get the official support. Also, there are some patches related to garbage collections.
https://www.py4j.org/changelog.html#py4j-0-10-8-and-py4j-0-10-8-1
## How was this patch tested?
Pass the Jenkins.
Closes#22901 from dongjoon-hyun/SPARK-25891.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
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 3.0.0-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?
Remove jets3t dependency, and bouncy castle which it brings in; update licenses and deps
Note this just takes over https://github.com/apache/spark/pull/21146
## How was this patch tested?
Existing tests.
Closes#22081 from srowen/SPARK-23654.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Upgrade ASM to 6.1 to support JDK9+
## How was this patch tested?
Existing tests.
Author: DB Tsai <d_tsai@apple.com>
Closes#21459 from dbtsai/asm.
## What changes were proposed in this pull request?
1. Adds a `hadoop-3.1` profile build depending on the hadoop-3.1 artifacts.
1. In the hadoop-cloud module, adds an explicit hadoop-3.1 profile which switches from explicitly pulling in cloud connectors (hadoop-openstack, hadoop-aws, hadoop-azure) to depending on the hadoop-cloudstorage POM artifact, which pulls these in, has pre-excluded things like hadoop-common, and stays up to date with new connectors (hadoop-azuredatalake, hadoop-allyun). Goal: it becomes the Hadoop projects homework of keeping this clean, and the spark project doesn't need to handle new hadoop releases adding more dependencies.
1. the hadoop-cloud/hadoop-3.1 profile also declares support for jetty-ajax and jetty-util to ensure that these jars get into the distribution jar directory when needed by unshaded libraries.
1. Increases the curator and zookeeper versions to match those in hadoop-3, fixing spark core to build in sbt with the hadoop-3 dependencies.
## How was this patch tested?
* Everything this has been built and tested against both ASF Hadoop branch-3.1 and hadoop trunk.
* spark-shell was used to create connectors to all the stores and verify that file IO could take place.
The spark hive-1.2.1 JAR has problems here, as it's version check logic fails for Hadoop versions > 2.
This can be avoided with either of
* The hadoop JARs built to declare their version as Hadoop 2.11 `mvn install -DskipTests -DskipShade -Ddeclared.hadoop.version=2.11` . This is safe for local test runs, not for deployment (HDFS is very strict about cross-version deployment).
* A modified version of spark hive whose version check switch statement is happy with hadoop 3.
I've done both, with maven and SBT.
Three issues surfaced
1. A spark-core test failure —fixed in SPARK-23787.
1. SBT only: Zookeeper not being found in spark-core. Somehow curator 2.12.0 triggers some slightly different dependency resolution logic from previous versions, and Ivy was missing zookeeper.jar entirely. This patch adds the explicit declaration for all spark profiles, setting the ZK version = 3.4.9 for hadoop-3.1
1. Marking jetty-utils as provided in spark was stopping hadoop-azure from being able to instantiate the azure wasb:// client; it was using jetty-util-ajax, which could then not find a class in jetty-util.
Author: Steve Loughran <stevel@hortonworks.com>
Closes#20923 from steveloughran/cloud/SPARK-23807-hadoop-31.
## What changes were proposed in this pull request?
This patch bumps the master branch version to `2.4.0-SNAPSHOT`.
## How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#20222 from gatorsmile/bump24.
This change adds a new launcher that allows applications to be run
in a separate thread in the same process as the calling code. To
achieve that, some code from the child process implementation was
moved to abstract classes that implement the common functionality,
and the new launcher inherits from those.
The new launcher was added as a new class, instead of implemented
as a new option to the existing SparkLauncher, to avoid ambigous
APIs. For example, SparkLauncher has ways to set the child app's
environment, modify SPARK_HOME, or control the logging of the
child process, none of which apply to in-process apps.
The in-process launcher has limitations: it needs Spark in the
context class loader of the calling thread, and it's bound by
Spark's current limitation of a single client-mode application
per JVM. It also relies on the recently added SparkApplication
trait to make sure different apps don't mess up each other's
configuration, so config isolation is currently limited to cluster mode.
I also chose to keep the same socket-based communication for in-process
apps, even though it might be possible to avoid it for in-process
mode. That helps both implementations share more code.
Tested with new and existing unit tests, and with a simple app that
uses the launcher; also made sure the app ran fine with older launcher
jar to check binary compatibility.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#19591 from vanzin/SPARK-11035.
## What changes were proposed in this pull request?
Using zstd compression for Spark jobs spilling 100s of TBs of data, we could reduce the amount of data written to disk by as much as 50%. This translates to significant latency gain because of reduced disk io operations. There is a degradation CPU time by 2 - 5% because of zstd compression overhead, but for jobs which are bottlenecked by disk IO, this hit can be taken.
## Benchmark
Please note that this benchmark is using real world compute heavy production workload spilling TBs of data to disk
| | zstd performance as compred to LZ4 |
| ------------- | -----:|
| spill/shuffle bytes | -48% |
| cpu time | + 3% |
| cpu reservation time | -40%|
| latency | -40% |
## How was this patch tested?
Tested by running few jobs spilling large amount of data on the cluster and amount of intermediate data written to disk reduced by as much as 50%.
Author: Sital Kedia <skedia@fb.com>
Closes#18805 from sitalkedia/skedia/upstream_zstd.
## What changes were proposed in this pull request?
When zinc is running the pwd might be in the root of the project. A quick solution to this is to not go a level up incase we are in the root rather than root/core/. If we are in the root everything works fine, if we are in core add a script which goes and runs the level up
## How was this patch tested?
set -x in the SparkR install scripts.
Author: Holden Karau <holden@us.ibm.com>
Closes#19402 from holdenk/SPARK-22167-sparkr-packaging-issue-allow-zinc.
The application listing is still generated from event logs, but is now stored
in a KVStore instance. By default an in-memory store is used, but a new config
allows setting a local disk path to store the data, in which case a LevelDB
store will be created.
The provider stores things internally using the public REST API types; I believe
this is better going forward since it will make it easier to get rid of the
internal history server API which is mostly redundant at this point.
I also added a finalizer to LevelDBIterator, to make sure that resources are
eventually released. This helps when code iterates but does not exhaust the
iterator, thus not triggering the auto-close code.
HistoryServerSuite was modified to not re-start the history server unnecessarily;
this makes the json validation tests run more quickly.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#18887 from vanzin/SPARK-20642.
## What changes were proposed in this pull request?
Update plugins, including scala-maven-plugin, to latest versions. Update checkstyle to 8.2. Remove bogus checkstyle config and enable it. Fix existing and new Java checkstyle errors.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19282 from srowen/SPARK-22066.
## What changes were proposed in this pull request?
This pr updated `lz4-java` to the latest (v1.4.0) and removed custom `LZ4BlockInputStream`. We currently use custom `LZ4BlockInputStream` to read concatenated byte stream in shuffle. But, this functionality has been implemented in the latest lz4-java (https://github.com/lz4/lz4-java/pull/105). So, we might update the latest to remove the custom `LZ4BlockInputStream`.
Major diffs between the latest release and v1.3.0 in the master are as follows (62f7547abb...6d4693f562);
- fixed NPE in XXHashFactory similarly
- Don't place resources in default package to support shading
- Fixes ByteBuffer methods failing to apply arrayOffset() for array-backed
- Try to load lz4-java from java.library.path, then fallback to bundled
- Add ppc64le binary
- Add s390x JNI binding
- Add basic LZ4 Frame v1.5.0 support
- enable aarch64 support for lz4-java
- Allow unsafeInstance() for ppc64le archiecture
- Add unsafeInstance support for AArch64
- Support 64-bit JNI build on Solaris
- Avoid over-allocating a buffer
- Allow EndMark to be incompressible for LZ4FrameInputStream.
- Concat byte stream
## How was this patch tested?
Existing tests.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#18883 from maropu/SPARK-21276.
