## What changes were proposed in this pull request?
Disable spark.reducer.maxReqSizeShuffleToMem because it breaks the old shuffle service.
Credits to wangyum
Closes#18466
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Author: Yuming Wang <wgyumg@gmail.com>
Closes#18467 from zsxwing/SPARK-21253.
## What changes were proposed in this pull request?
Currently we are running into an issue with Yarn work preserving enabled + external shuffle service.
In the work preserving enabled scenario, the failure of NM will not lead to the exit of executors, so executors can still accept and run the tasks. The problem here is when NM is failed, external shuffle service is actually inaccessible, so reduce tasks will always complain about the “Fetch failure”, and the failure of reduce stage will make the parent stage (map stage) rerun. The tricky thing here is Spark scheduler is not aware of the unavailability of external shuffle service, and will reschedule the map tasks on the executor where NM is failed, and again reduce stage will be failed with “Fetch failure”, and after 4 retries, the job is failed. This could also apply to other cluster manager with external shuffle service.
So here the main problem is that we should avoid assigning tasks to those bad executors (where shuffle service is unavailable). Current Spark's blacklist mechanism could blacklist executors/nodes by failure tasks, but it doesn't handle this specific fetch failure scenario. So here propose to improve the current application blacklist mechanism to handle fetch failure issue (especially with external shuffle service unavailable issue), to blacklist the executors/nodes where shuffle fetch is unavailable.
## How was this patch tested?
Unit test and small cluster verification.
Author: jerryshao <sshao@hortonworks.com>
Closes#17113 from jerryshao/SPARK-13669.
## What changes were proposed in this pull request?
Add lost `<tr>` tag for `configuration.md`.
## How was this patch tested?
N/A
Author: Yuming Wang <wgyumg@gmail.com>
Closes#18372 from wangyum/docs-missing-tr.
## What changes were proposed in this pull request?
Currently the shuffle service registration timeout and retry has been hardcoded. This works well for small workloads but under heavy workload when the shuffle service is busy transferring large amount of data we see significant delay in responding to the registration request, as a result we often see the executors fail to register with the shuffle service, eventually failing the job. We need to make these two parameters configurable.
## How was this patch tested?
* Updated `BlockManagerSuite` to test registration timeout and max attempts configuration actually works.
cc sitalkedia
Author: Li Yichao <lyc@zhihu.com>
Closes#18092 from liyichao/SPARK-20640.
## What changes were proposed in this pull request?
The description for several options of File Source for structured streaming appeared in the File Sink description instead.
This pull request has two commits: The first includes changes to the version as it appeared in spark 2.1 and the second handled an additional option added for spark 2.2
## How was this patch tested?
Built the documentation by SKIP_API=1 jekyll build and visually inspected the structured streaming programming guide.
The original documentation was written by tdas and lw-lin
Author: assafmendelson <assaf.mendelson@gmail.com>
Closes#18342 from assafmendelson/spark-21123.
## What changes were proposed in this pull request?
Update Running R Tests dependence packages to:
```bash
R -e "install.packages(c('knitr', 'rmarkdown', 'testthat', 'e1071', 'survival'), repos='http://cran.us.r-project.org')"
```
## How was this patch tested?
manual tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#18271 from wangyum/building-spark.
## What changes were proposed in this pull request?
Move Hadoop delegation token code from `spark-yarn` to `spark-core`, so that other schedulers (such as Mesos), may use it. In order to avoid exposing Hadoop interfaces in spark-core, the new Hadoop delegation token classes are kept private. In order to provider backward compatiblity, and to allow YARN users to continue to load their own delegation token providers via Java service loading, the old YARN interfaces, as well as the client code that uses them, have been retained.
Summary:
- Move registered `yarn.security.ServiceCredentialProvider` classes from `spark-yarn` to `spark-core`. Moved them into a new, private hierarchy under `HadoopDelegationTokenProvider`. Client code in `HadoopDelegationTokenManager` now loads credentials from a whitelist of three providers (`HadoopFSDelegationTokenProvider`, `HiveDelegationTokenProvider`, `HBaseDelegationTokenProvider`), instead of service loading, which means that users are not able to implement their own delegation token providers, as they are in the `spark-yarn` module.
- The `yarn.security.ServiceCredentialProvider` interface has been kept for backwards compatibility, and to continue to allow YARN users to implement their own delegation token provider implementations. Client code in YARN now fetches tokens via the new `YARNHadoopDelegationTokenManager` class, which fetches tokens from the core providers through `HadoopDelegationTokenManager`, as well as service loads them from `yarn.security.ServiceCredentialProvider`.
Old Hierarchy:
```
yarn.security.ServiceCredentialProvider (service loaded)
HadoopFSCredentialProvider
HiveCredentialProvider
HBaseCredentialProvider
yarn.security.ConfigurableCredentialManager
```
New Hierarchy:
```
HadoopDelegationTokenManager
HadoopDelegationTokenProvider (not service loaded)
HadoopFSDelegationTokenProvider
HiveDelegationTokenProvider
HBaseDelegationTokenProvider
yarn.security.ServiceCredentialProvider (service loaded)
yarn.security.YARNHadoopDelegationTokenManager
```
## How was this patch tested?
unit tests
Author: Michael Gummelt <mgummelt@mesosphere.io>
Author: Dr. Stefan Schimanski <sttts@mesosphere.io>
Closes#17723 from mgummelt/SPARK-20434-refactor-kerberos.
## What changes were proposed in this pull request?
doc only change
## How was this patch tested?
manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#18312 from felixcheung/sqljsonwholefiledoc.
## What changes were proposed in this pull request?
`df.groupBy.count()` should be `df.groupBy().count()` , otherwise there is an error :
ambiguous reference to overloaded definition, both method groupBy in class Dataset of type (col1: String, cols: String*) and method groupBy in class Dataset of type (cols: org.apache.spark.sql.Column*)
## How was this patch tested?
```scala
val df = spark.readStream.schema(...).json(...)
val dfCounts = df.groupBy().count()
```
Author: Ziyue Huang <zyhuang94@gmail.com>
Closes#18272 from ZiyueHuang/master.
## What changes were proposed in this pull request?
Add Mesos labels support to the Spark Dispatcher
## How was this patch tested?
unit tests
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#18220 from mgummelt/SPARK-21000-dispatcher-labels.
## What changes were proposed in this pull request?
Add a new property `spark.streaming.kafka.consumer.cache.enabled` that allows users to enable or disable the cache for Kafka consumers. This property can be especially handy in cases where issues like SPARK-19185 get hit, for which there isn't a solution committed yet. By default, the cache is still on, so this change doesn't change any out-of-box behavior.
## How was this patch tested?
Running unit tests
Author: Mark Grover <mark@apache.org>
Author: Mark Grover <grover.markgrover@gmail.com>
Closes#18234 from markgrover/spark-19185.
## What changes were proposed in this pull request?
In our use case of launching Spark applications via REST APIs (Livy), there's no way for user to specify command line arguments, all Spark configurations are set through configurations map. For "--repositories" because there's no equivalent Spark configuration, so we cannot specify the custom repository through configuration.
So here propose to add "--repositories" equivalent configuration in Spark.
## How was this patch tested?
New UT added.
Author: jerryshao <sshao@hortonworks.com>
Closes#18201 from jerryshao/SPARK-20981.
## What changes were proposed in this pull request?
- Add Scala, Python and Java examples for `partitionBy`, `sortBy` and `bucketBy`.
- Add _Bucketing, Sorting and Partitioning_ section to SQL Programming Guide
- Remove bucketing from Unsupported Hive Functionalities.
## How was this patch tested?
Manual tests, docs build.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17938 from zero323/DOCS-BUCKETING-AND-PARTITIONING.
Now that Structured Streaming has been out for several Spark release and has large production use cases, the `Experimental` label is no longer appropriate. I've left `InterfaceStability.Evolving` however, as I think we may make a few changes to the pluggable Source & Sink API in Spark 2.3.
Author: Michael Armbrust <michael@databricks.com>
Closes#18065 from marmbrus/streamingGA.
## What changes were proposed in this pull request?
1, add an example for sparkr `decisionTree`
2, document it in user guide
## How was this patch tested?
local submit
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#18067 from zhengruifeng/dt_example.
(Link to Jira: https://issues.apache.org/jira/browse/SPARK-20888)
## What changes were proposed in this pull request?
Document change of default setting of spark.sql.hive.caseSensitiveInferenceMode configuration key from NEVER_INFO to INFER_AND_SAVE in the Spark SQL 2.1 to 2.2 migration notes.
Author: Michael Allman <michael@videoamp.com>
Closes#18112 from mallman/spark-20888-document_infer_and_save.
## What changes were proposed in this pull request?
Currently the whole block is fetched into memory(off heap by default) when shuffle-read. A block is defined by (shuffleId, mapId, reduceId). Thus it can be large when skew situations. If OOM happens during shuffle read, job will be killed and users will be notified to "Consider boosting spark.yarn.executor.memoryOverhead". Adjusting parameter and allocating more memory can resolve the OOM. However the approach is not perfectly suitable for production environment, especially for data warehouse.
Using Spark SQL as data engine in warehouse, users hope to have a unified parameter(e.g. memory) but less resource wasted(resource is allocated but not used). The hope is strong especially when migrating data engine to Spark from another one(e.g. Hive). Tuning the parameter for thousands of SQLs one by one is very time consuming.
It's not always easy to predict skew situations, when happen, it make sense to fetch remote blocks to disk for shuffle-read, rather than kill the job because of OOM.
In this pr, I propose to fetch big blocks to disk(which is also mentioned in SPARK-3019):
1. Track average size and also the outliers(which are larger than 2*avgSize) in MapStatus;
2. Request memory from `MemoryManager` before fetch blocks and release the memory to `MemoryManager` when `ManagedBuffer` is released.
3. Fetch remote blocks to disk when failing acquiring memory from `MemoryManager`, otherwise fetch to memory.
This is an improvement for memory control when shuffle blocks and help to avoid OOM in scenarios like below:
1. Single huge block;
2. Sizes of many blocks are underestimated in `MapStatus` and the actual footprint of blocks is much larger than the estimated.
## How was this patch tested?
Added unit test in `MapStatusSuite` and `ShuffleBlockFetcherIteratorSuite`.
Author: jinxing <jinxing6042@126.com>
Closes#16989 from jinxing64/SPARK-19659.
## What changes were proposed in this pull request?
Currently, when number of reduces is above 2000, HighlyCompressedMapStatus is used to store size of blocks. in HighlyCompressedMapStatus, only average size is stored for non empty blocks. Which is not good for memory control when we shuffle blocks. It makes sense to store the accurate size of block when it's above threshold.
## How was this patch tested?
Added test in MapStatusSuite.
Author: jinxing <jinxing6042@126.com>
Closes#18031 from jinxing64/SPARK-20801.
Quick follow up to #17996 - forgot to add the HTML links to the relevant sections of the guide in the highlights list.
## How was this patch tested?
Built docs locally and tested links.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#18043 from MLnick/SPARK-20506-2.2-migration-guide-2.
Update ML guide for migration `2.1` -> `2.2` and the previous version migration guide section.
## How was this patch tested?
Build doc locally.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#17996 from MLnick/SPARK-20506-2.2-migration-guide.
## What changes were proposed in this pull request?
The changes were merged as part of - https://github.com/apache/spark/pull/17467.
The documentation was missed somewhere in the review iterations. Adding the documentation where it belongs.
## How was this patch tested?
Docs. Not tested.
cc budde , brkyvz
Author: Yash Sharma <ysharma@atlassian.com>
Closes#18028 from yssharma/ysharma/kinesis_retry_docs.
## What changes were proposed in this pull request?
Add docs and examples for ```ml.stat.Correlation``` and ```ml.stat.ChiSquareTest```.
## How was this patch tested?
Generate docs and run examples manually, successfully.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#17994 from yanboliang/spark-20505.
## What changes were proposed in this pull request?
SPARK-13973 incorrectly removed the required PYSPARK_DRIVER_PYTHON_OPTS=notebook from documentation to use pyspark with Jupyter notebook. This patch corrects the documentation error.
## How was this patch tested?
Tested invocation locally with
```bash
PYSPARK_DRIVER_PYTHON=jupyter PYSPARK_DRIVER_PYTHON_OPTS=notebook ./bin/pyspark
```
Author: Andrew Ray <ray.andrew@gmail.com>
Closes#18001 from aray/patch-1.
## What changes were proposed in this pull request?
Any Dataset/DataFrame batch query with the operation `withWatermark` does not execute because the batch planner does not have any rule to explicitly handle the EventTimeWatermark logical plan.
The right solution is to simply remove the plan node, as the watermark should not affect any batch query in any way.
Changes:
- In this PR, we add a new rule `EliminateEventTimeWatermark` to check if we need to ignore the event time watermark. We will ignore watermark in any batch query.
Depends upon:
- [SPARK-20672](https://issues.apache.org/jira/browse/SPARK-20672). We can not add this rule into analyzer directly, because streaming query will be copied to `triggerLogicalPlan ` in every trigger, and the rule will be applied to `triggerLogicalPlan` mistakenly.
Others:
- A typo fix in example.
## How was this patch tested?
add new unit test.
Author: uncleGen <hustyugm@gmail.com>
Closes#17896 from uncleGen/SPARK-20373.
## What changes were proposed in this pull request?
After SPARK-10997, client mode Netty RpcEnv doesn't require to start server, so port configurations are not used any more, here propose to remove these two configurations: "spark.executor.port" and "spark.am.port".
## How was this patch tested?
Existing UTs.
Author: jerryshao <sshao@hortonworks.com>
Closes#17866 from jerryshao/SPARK-20605.
## What changes were proposed in this pull request?
Add a new `spark-hadoop-cloud` module and maven profile to pull in object store support from `hadoop-openstack`, `hadoop-aws` and `hadoop-azure` (Hadoop 2.7+) JARs, along with their dependencies, fixing up the dependencies so that everything works, in particular Jackson.
It restores `s3n://` access to S3, adds its `s3a://` replacement, OpenStack `swift://` and azure `wasb://`.
There's a documentation page, `cloud_integration.md`, which covers the basic details of using Spark with object stores, referring the reader to the supplier's own documentation, with specific warnings on security and the possible mismatch between a store's behavior and that of a filesystem. In particular, users are advised be very cautious when trying to use an object store as the destination of data, and to consult the documentation of the storage supplier and the connector.
(this is the successor to #12004; I can't re-open it)
## How was this patch tested?
Downstream tests exist in [https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples](https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples)
Those verify that the dependencies are sufficient to allow downstream applications to work with s3a, azure wasb and swift storage connectors, and perform basic IO & dataframe operations thereon. All seems well.
Manually clean build & verify that assembly contains the relevant aws-* hadoop-* artifacts on Hadoop 2.6; azure on a hadoop-2.7 profile.
SBT build: `build/sbt -Phadoop-cloud -Phadoop-2.7 package`
maven build `mvn install -Phadoop-cloud -Phadoop-2.7`
This PR *does not* update `dev/deps/spark-deps-hadoop-2.7` or `dev/deps/spark-deps-hadoop-2.6`, because unless the hadoop-cloud profile is enabled, no extra JARs show up in the dependency list. The dependency check in Jenkins isn't setting the property, so the new JARs aren't visible.
Author: Steve Loughran <stevel@apache.org>
Author: Steve Loughran <stevel@hortonworks.com>
Closes#17834 from steveloughran/cloud/SPARK-7481-current.
## What changes were proposed in this pull request?
Add
- R vignettes
- R programming guide
- SS programming guide
- R example
Also disable spark.als in vignettes for now since it's failing (SPARK-20402)
## How was this patch tested?
manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17814 from felixcheung/rdocss.
Add PCA and SVD to PySpark's wrappers for `RowMatrix` and `IndexedRowMatrix` (SVD only).
Based on #7963, updated.
## How was this patch tested?
New doc tests and unit tests. Ran all examples locally.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#17621 from MLnick/SPARK-6227-pyspark-svd-pca.
## What changes were proposed in this pull request?
Updating R Programming Guide
## How was this patch tested?
manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17816 from felixcheung/r22relnote.
## What changes were proposed in this pull request?
Currently, our project needs to be set to clean up the worker directory cleanup cycle is three days.
When I follow http://spark.apache.org/docs/latest/spark-standalone.html, configure the 'spark.worker.cleanup.appDataTtl' parameter, I configured to 3 * 24 * 3600.
When I start the spark service, the startup fails, and the worker log displays the error log as follows:
2017-04-28 15:02:03,306 INFO Utils: Successfully started service 'sparkWorker' on port 48728.
Exception in thread "main" java.lang.NumberFormatException: For input string: "3 * 24 * 3600"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Long.parseLong(Long.java:430)
at java.lang.Long.parseLong(Long.java:483)
at scala.collection.immutable.StringLike$class.toLong(StringLike.scala:276)
at scala.collection.immutable.StringOps.toLong(StringOps.scala:29)
at org.apache.spark.SparkConf$$anonfun$getLong$2.apply(SparkConf.scala:380)
at org.apache.spark.SparkConf$$anonfun$getLong$2.apply(SparkConf.scala:380)
at scala.Option.map(Option.scala:146)
at org.apache.spark.SparkConf.getLong(SparkConf.scala:380)
at org.apache.spark.deploy.worker.Worker.<init>(Worker.scala:100)
at org.apache.spark.deploy.worker.Worker$.startRpcEnvAndEndpoint(Worker.scala:730)
at org.apache.spark.deploy.worker.Worker$.main(Worker.scala:709)
at org.apache.spark.deploy.worker.Worker.main(Worker.scala)
**Because we put 7 * 24 * 3600 as a string, forced to convert to the dragon type, will lead to problems in the program.**
**So I think the default value of the current configuration should be a specific long value, rather than 7 * 24 * 3600,should be 604800. Because it would mislead users for similar configurations, resulting in spark start failure.**
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: 郭小龙 10207633 <guo.xiaolong1@zte.com.cn>
Author: guoxiaolong <guo.xiaolong1@zte.com.cn>
Author: guoxiaolongzte <guo.xiaolong1@zte.com.cn>
Closes#17798 from guoxiaolongzte/SPARK-20521.
## What changes were proposed in this pull request?
Add a new section for fpm
Add Example for FPGrowth in scala and Java
updated: Rewrite transform to be more compact.
## How was this patch tested?
local doc generation.
Author: Yuhao Yang <yuhao.yang@intel.com>
Closes#17130 from hhbyyh/fpmdoc.
## What changes were proposed in this pull request?
Add hyper link in the SparkR programming guide.
## How was this patch tested?
Build doc and manually check the doc link.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#17805 from wangmiao1981/doc.
## What changes were proposed in this pull request?
add link to svmLinear in the SparkR programming document.
## How was this patch tested?
Build doc manually and click the link to the document. It looks good.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#17797 from wangmiao1981/doc.
## What changes were proposed in this pull request?
Add `spark.fpGrowth` to SparkR programming guide.
## How was this patch tested?
Manual tests.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17775 from zero323/SPARK-20208-FOLLOW-UP.
This change does a more thorough redaction of sensitive information from logs and UI
Add unit tests that ensure that no regressions happen that leak sensitive information to the logs.
The motivation for this change was appearance of password like so in `SparkListenerEnvironmentUpdate` in event logs under some JVM configurations:
`"sun.java.command":"org.apache.spark.deploy.SparkSubmit ... --conf spark.executorEnv.HADOOP_CREDSTORE_PASSWORD=secret_password ..."
`
Previously redaction logic was only checking if the key matched the secret regex pattern, it'd redact it's value. That worked for most cases. However, in the above case, the key (sun.java.command) doesn't tell much, so the value needs to be searched. This PR expands the check to check for values as well.
## How was this patch tested?
New unit tests added that ensure that no sensitive information is present in the event logs or the yarn logs. Old unit test in UtilsSuite was modified because the test was asserting that a non-sensitive property's value won't be redacted. However, the non-sensitive value had the literal "secret" in it which was causing it to redact. Simply updating the non-sensitive property's value to another arbitrary value (that didn't have "secret" in it) fixed it.
Author: Mark Grover <mark@apache.org>
Closes#17725 from markgrover/spark-20435.
## What changes were proposed in this pull request?
Simple documentation change to remove explicit vendor references.
## How was this patch tested?
NA
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: anabranch <bill@databricks.com>
Closes#17695 from anabranch/remove-vendor.
## What changes were proposed in this pull request?
- Add `rollup` and `cube` methods and corresponding generics.
- Add short description to the vignette.
## How was this patch tested?
- Existing unit tests.
- Additional unit tests covering new features.
- `check-cran.sh`.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17728 from zero323/SPARK-20437.
## What changes were proposed in this pull request?
Pregel-based iterative algorithms with more than ~50 iterations begin to slow down and eventually fail with a StackOverflowError due to Spark's lack of support for long lineage chains.
This PR causes Pregel to checkpoint the graph periodically if the checkpoint directory is set.
This PR moves PeriodicGraphCheckpointer.scala from mllib to graphx, moves PeriodicRDDCheckpointer.scala, PeriodicCheckpointer.scala from mllib to core
## How was this patch tested?
unit tests, manual tests
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: ding <ding@localhost.localdomain>
Author: dding3 <ding.ding@intel.com>
Author: Michael Allman <michael@videoamp.com>
Closes#15125 from dding3/cp2_pregel.
## What changes were proposed in this pull request?
Just added the Maven `test`goal.
## How was this patch tested?
No test needed, just a trivial documentation fix.
Author: Armin Braun <me@obrown.io>
Closes#17756 from original-brownbear/SPARK-20455.
## What changes were proposed in this pull request?
Use the REST interface submits the spark job.
e.g.
curl -X POST http://10.43.183.120:6066/v1/submissions/create --header "Content-Type:application/json;charset=UTF-8" --data'{
"action": "CreateSubmissionRequest",
"appArgs": [
"myAppArgument"
],
"appResource": "/home/mr/gxl/test.jar",
"clientSparkVersion": "2.2.0",
"environmentVariables": {
"SPARK_ENV_LOADED": "1"
},
"mainClass": "cn.zte.HdfsTest",
"sparkProperties": {
"spark.jars": "/home/mr/gxl/test.jar",
**"spark.driver.supervise": "true",**
"spark.app.name": "HdfsTest",
"spark.eventLog.enabled": "false",
"spark.submit.deployMode": "cluster",
"spark.master": "spark://10.43.183.120:6066"
}
}'
**I hope that make sure that the driver is automatically restarted if it fails with non-zero exit code.
But I can not find the 'spark.driver.supervise' configuration parameter specification and default values from the spark official document.**
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: 郭小龙 10207633 <guo.xiaolong1@zte.com.cn>
Author: guoxiaolong <guo.xiaolong1@zte.com.cn>
Author: guoxiaolongzte <guo.xiaolong1@zte.com.cn>
Closes#17696 from guoxiaolongzte/SPARK-20401.
Hello
PR #10991 removed the built-in history view from Spark Standalone, so the history server is no longer useful to Yarn or Mesos only.
Author: Hervé <dud225@users.noreply.github.com>
Closes#17709 from dud225/patch-1.
## What changes were proposed in this pull request?
Typos at a couple of place in the docs.
## How was this patch tested?
build including docs
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: ymahajan <ymahajan@snappydata.io>
Closes#17690 from ymahajan/master.
## What changes were proposed in this pull request?
Note that you shouldn't manually add dependencies on org.apache.kafka artifacts
## How was this patch tested?
Doc only change, did jekyll build and looked at the page.
Author: cody koeninger <cody@koeninger.org>
Closes#17675 from koeninger/SPARK-20036.
## What changes were proposed in this pull request?
Allow passing in arbitrary parameters into docker when launching spark executors on mesos with docker containerizer tnachen
## How was this patch tested?
Manually built and tested with passed in parameter
Author: Ji Yan <jiyan@Jis-MacBook-Air.local>
Closes#17109 from yanji84/ji/allow_set_docker_user.
## What changes were proposed in this pull request?
This PR proposes corrections related to JSON APIs as below:
- Rendering links in Python documentation
- Replacing `RDD` to `Dataset` in programing guide
- Adding missing description about JSON Lines consistently in `DataFrameReader.json` in Python API
- De-duplicating little bit of `DataFrameReader.json` in Scala/Java API
## How was this patch tested?
Manually build the documentation via `jekyll build`. Corresponding snapstops will be left on the codes.
Note that currently there are Javadoc8 breaks in several places. These are proposed to be handled in https://github.com/apache/spark/pull/17477. So, this PR does not fix those.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17602 from HyukjinKwon/minor-json-documentation.
## What changes were proposed in this pull request?
1. Omitted space between the sentences: `... on static data.The Spark SQL engine will ...` -> `... on static data. The Spark SQL engine will ...`
2. Omitted colon in Output Model section.
## How was this patch tested?
None.
Author: Lee Dongjin <dongjin@apache.org>
Closes#17564 from dongjinleekr/feature/fix-programming-guide.
## What changes were proposed in this pull request?
Since SPARK-18112 and SPARK-13446, Apache Spark starts to support reading Hive metastore 2.0 ~ 2.1.1. This updates the docs.
## How was this patch tested?
N/A
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#17612 from dongjoon-hyun/metastore.
## What changes were proposed in this pull request?
Add documentation for adding master url in multi host, port format for standalone cluster with high availability with zookeeper.
Referring documentation [Standby Masters with ZooKeeper](http://spark.apache.org/docs/latest/spark-standalone.html#standby-masters-with-zookeeper)
## How was this patch tested?
Documenting the functionality already present.
Author: MirrorZ <chandrika3437@gmail.com>
Closes#17584 from MirrorZ/master.
## What changes were proposed in this pull request?
1. '/applications/[app-id]/stages' in rest api.status should add description '?status=[active|complete|pending|failed] list only stages in the state.'
Now the lack of this description, resulting in the use of this api do not know the use of the status through the brush stage list.
2.'/applications/[app-id]/stages/[stage-id]' in REST API,remove redundant description ‘?status=[active|complete|pending|failed] list only stages in the state.’.
Because only one stage is determined based on stage-id.
code:
GET
def stageList(QueryParam("status") statuses: JList[StageStatus]): Seq[StageData] = {
val listener = ui.jobProgressListener
val stageAndStatus = AllStagesResource.stagesAndStatus(ui)
val adjStatuses = {
if (statuses.isEmpty()) {
Arrays.asList(StageStatus.values(): _*)
} else {
statuses
}
};
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: 郭小龙 10207633 <guo.xiaolong1@zte.com.cn>
Closes#17534 from guoxiaolongzte/SPARK-20218.
## What changes were proposed in this pull request?
Add spark.mesos.task.labels configuration option to add mesos key:value labels to the executor.
"k1:v1,k2:v2" as the format, colons separating key-value and commas to list out more than one.
Discussion of labels with mgummelt at #17404
## How was this patch tested?
Added unit tests to verify labels were added correctly, with incorrect labels being ignored and added a test to test the name of the executor.
Tested with: `./build/sbt -Pmesos mesos/test`
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Kalvin Chau <kalvin.chau@viasat.com>
Closes#17413 from kalvinnchau/mesos-labels.
## What changes were proposed in this pull request?
- Fixed bug in Java API not passing timeout conf to scala API
- Updated markdown docs
- Updated scala docs
- Added scala and Java example
## How was this patch tested?
Manually ran examples.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#17539 from tdas/SPARK-20224.
## What changes were proposed in this pull request?
Adding documentation to point to Kubernetes cluster scheduler being developed out-of-repo in https://github.com/apache-spark-on-k8s/spark
cc rxin srowen tnachen ash211 mccheah erikerlandson
## How was this patch tested?
Docs only change
Author: Anirudh Ramanathan <foxish@users.noreply.github.com>
Author: foxish <ramanathana@google.com>
Closes#17522 from foxish/upstream-doc.
…ucceeded|failed|unknown]
## What changes were proposed in this pull request?
'/applications/[app-id]/jobs' in rest api.status should be'[running|succeeded|failed|unknown]'.
now status is '[complete|succeeded|failed]'.
but '/applications/[app-id]/jobs?status=complete' the server return 'HTTP ERROR 404'.
Added '?status=running' and '?status=unknown'.
code ：
public enum JobExecutionStatus {
RUNNING,
SUCCEEDED,
FAILED,
UNKNOWN;
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: guoxiaolongzte <guo.xiaolong1@zte.com.cn>
Closes#17507 from guoxiaolongzte/SPARK-20190.
## What changes were proposed in this pull request?
Add docs and examples for spark.ml.feature.Imputer. Currently scala and Java examples are included. Python example will be added after https://github.com/apache/spark/pull/17316
## How was this patch tested?
local doc generation and example execution
Author: Yuhao Yang <yuhao.yang@intel.com>
Closes#17324 from hhbyyh/imputerdoc.
# What changes were proposed in this pull request?
It seems there are several non-breaking spaces were inserted into several `.md`s and they look breaking rendering markdown files.
These are different. For example, this can be checked via `python` as below:
```python
>>> " "
'\xc2\xa0'
>>> " "
' '
```
_Note that it seems this PR description automatically replaces non-breaking spaces into normal spaces. Please open a `vi` and copy and paste it into `python` to verify this (do not copy the characters here)._
I checked the output below in Sapari and Chrome on Mac OS and, Internal Explorer on Windows 10.
**Before**
**After**
## How was this patch tested?
Manually checking.
These instances were found via
```
grep --include=*.scala --include=*.python --include=*.java --include=*.r --include=*.R --include=*.md --include=*.r -r -I " " .
```
in Mac OS.
It seems there are several instances more as below:
```
./docs/sql-programming-guide.md: │ ├── ...
./docs/sql-programming-guide.md: │ │
./docs/sql-programming-guide.md: │ ├── country=US
./docs/sql-programming-guide.md: │ │ └── data.parquet
./docs/sql-programming-guide.md: │ ├── country=CN
./docs/sql-programming-guide.md: │ │ └── data.parquet
./docs/sql-programming-guide.md: │ └── ...
./docs/sql-programming-guide.md: ├── ...
./docs/sql-programming-guide.md: │
./docs/sql-programming-guide.md: ├── country=US
./docs/sql-programming-guide.md: │ └── data.parquet
./docs/sql-programming-guide.md: ├── country=CN
./docs/sql-programming-guide.md: │ └── data.parquet
./docs/sql-programming-guide.md: └── ...
./sql/core/src/test/README.md:│ ├── *.avdl # Testing Avro IDL(s)
./sql/core/src/test/README.md:│ └── *.avpr # !! NO TOUCH !! Protocol files generated from Avro IDL(s)
./sql/core/src/test/README.md:│ ├── gen-avro.sh # Script used to generate Java code for Avro
./sql/core/src/test/README.md:│ └── gen-thrift.sh # Script used to generate Java code for Thrift
```
These seems generated via `tree` command which inserts non-breaking spaces. They do not look causing any problem for rendering within code blocks and I did not fix it to reduce the overhead to manually replace it when it is overwritten via `tree` command in the future.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17517 from HyukjinKwon/non-breaking-space.
…anges.
## What changes were proposed in this pull request?
Document compression way little detail changes.
1.spark.eventLog.compress add 'Compression will use spark.io.compression.codec.'
2.spark.broadcast.compress add 'Compression will use spark.io.compression.codec.'
3,spark.rdd.compress add 'Compression will use spark.io.compression.codec.'
4.spark.io.compression.codec add 'event log describe'.
eg
Through the documents, I don't know what is compression mode about 'event log'.
## How was this patch tested?
manual tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: 郭小龙 10207633 <guo.xiaolong1@zte.com.cn>
Closes#17498 from guoxiaolongzte/SPARK-20177.
Fixed a few typos.
There is one more I'm not sure of:
```
Append mode uses watermark to drop old aggregation state. But the output of a
windowed aggregation is delayed the late threshold specified in `withWatermark()` as by
the modes semantics, rows can be added to the Result Table only once after they are
```
Not sure how to change `is delayed the late threshold`.
Author: Seigneurin, Alexis (CONT) <Alexis.Seigneurin@capitalone.com>
Closes#17443 from aseigneurin/typos.
## What changes were proposed in this pull request?
Currently JDBC data source creates tables in the target database using the default type mapping, and the JDBC dialect mechanism. If users want to specify different database data type for only some of columns, there is no option available. In scenarios where default mapping does not work, users are forced to create tables on the target database before writing. This workaround is probably not acceptable from a usability point of view. This PR is to provide a user-defined type mapping for specific columns.
The solution is to allow users to specify database column data type for the create table as JDBC datasource option(createTableColumnTypes) on write. Data type information can be specified in the same format as table schema DDL format (e.g: `name CHAR(64), comments VARCHAR(1024)`).
All supported target database types can not be specified , the data types has to be valid spark sql data types also. For example user can not specify target database CLOB data type. This will be supported in the follow-up PR.
Example:
```Scala
df.write
.option("createTableColumnTypes", "name CHAR(64), comments VARCHAR(1024)")
.jdbc(url, "TEST.DBCOLTYPETEST", properties)
```
## How was this patch tested?
Added new test cases to the JDBCWriteSuite
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#16209 from sureshthalamati/jdbc_custom_dbtype_option_json-spark-10849.
## What changes were proposed in this pull request?
Add backslash for line continuation in python code.
## How was this patch tested?
Jenkins.
Author: uncleGen <hustyugm@gmail.com>
Author: dylon <hustyugm@gmail.com>
Closes#17352 from uncleGen/python-example-doc.
## What changes were proposed in this pull request?
API documentation and collaborative filtering documentation page changes to clarify inconsistent description of ALS rank parameter.
- [DOCS] was previously: "rank is the number of latent factors in the model."
- [API] was previously: "rank - number of features to use"
This change describes rank in both places consistently as:
- "Number of features to use (also referred to as the number of latent factors)"
Author: Chris Snow <chris.snowuk.ibm.com>
Author: christopher snow <chsnow123@gmail.com>
Closes#17345 from snowch/SPARK-20011.
## What changes were proposed in this pull request?
Add documentation that describes how to write streaming and batch queries to Kafka.
zsxwing tdas
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Tyson Condie <tcondie@gmail.com>
Closes#17246 from tcondie/kafka-write-docs.
The previously hardcoded max 4 retries per stage is not suitable for all cluster configurations. Since spark retries a stage at the sign of the first fetch failure, you can easily end up with many stage retries to discover all the failures. In particular, two scenarios this value should change are (1) if there are more than 4 executors per node; in that case, it may take 4 retries to discover the problem with each executor on the node and (2) during cluster maintenance on large clusters, where multiple machines are serviced at once, but you also cannot afford total cluster downtime. By making this value configurable, cluster managers can tune this value to something more appropriate to their cluster configuration.
Unit tests
Author: Sital Kedia <skedia@fb.com>
Closes#17307 from sitalkedia/SPARK-13369.
## What changes were proposed in this pull request?
- SS python example: `TypeError: 'xxx' object is not callable`
- some other doc issue.
## How was this patch tested?
Jenkins.
Author: uncleGen <hustyugm@gmail.com>
Closes#17257 from uncleGen/docs-ss-python.
## What changes were proposed in this pull request?
Today, we compare the whole path when deciding if a file is new in the FileSource for structured streaming. However, this would cause false negatives in the case where the path has changed in a cosmetic way (i.e. changing `s3n` to `s3a`).
This patch adds an option `fileNameOnly` that causes the new file check to be based only on the filename (but still store the whole path in the log).
## Usage
```scala
spark
.readStream
.option("fileNameOnly", true)
.text("s3n://bucket/dir1/dir2")
.writeStream
...
```
## How was this patch tested?
Added a test case
Author: Liwei Lin <lwlin7@gmail.com>
Closes#17120 from lw-lin/filename-only.
## What changes were proposed in this pull request?
After Spark 2.0, `SparkSession` becomes the new entry point for Spark applications. We should update the public documents to reflect this.
## How was this patch tested?
N/A
Author: Wenchen Fan <wenchen@databricks.com>
Closes#16856 from cloud-fan/doc.
## What changes were proposed in this pull request?
This PR is an enhancement to ML StringIndexer.
Before this PR, String Indexer only supports "skip"/"error" options to deal with unseen records.
But those unseen records might still be useful and user would like to keep the unseen labels in
certain use cases, This PR enables StringIndexer to support keeping unseen labels as
indices [numLabels].
'''Before
StringIndexer().setHandleInvalid("skip")
StringIndexer().setHandleInvalid("error")
'''After
support the third option "keep"
StringIndexer().setHandleInvalid("keep")
## How was this patch tested?
Test added in StringIndexerSuite
Signed-off-by: VinceShieh <vincent.xieintel.com>
(Please fill in changes proposed in this fix)
Author: VinceShieh <vincent.xie@intel.com>
Closes#16883 from VinceShieh/spark-17498.
## What changes were proposed in this pull request?
Doc about enabling web UI https is not correct, "spark.ui.https.enabled" is not existed, actually enabling SSL is enough for https.
## How was this patch tested?
N/A
Author: jerryshao <sshao@hortonworks.com>
Closes#17147 from jerryshao/fix-doc-ssl.
## What changes were proposed in this pull request?
Description about pipeline in this paragraph is incorrect https://spark.apache.org/docs/latest/ml-pipeline.html#how-it-works
> If the Pipeline had more **stages**, it would call the LogisticRegressionModel’s transform() method on the DataFrame before passing the DataFrame to the next stage.
Reason: Transformer could also be a stage. But only another Estimator will invoke an transform call and pass the data to next stage. The description in the document misleads ML pipeline users.
## How was this patch tested?
This is a tiny modification of **docs/ml-pipelines.md**. I jekyll build the modification and check the compiled document.
Author: Zhe Sun <ymwdalex@gmail.com>
Closes#17137 from ymwdalex/SPARK-19797-ML-pipeline-document-correction.
[SPARK-14489](https://issues.apache.org/jira/browse/SPARK-14489) added the ability to skip `NaN` predictions during `ALSModel.transform`. This PR adds documentation for the `coldStartStrategy` param to the ALS user guide, and add code to the examples to illustrate usage.
## How was this patch tested?
Doc and example change only. Build HTML doc locally and verified example code builds, and runs in shell for Scala/Python.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#17102 from MLnick/SPARK-19345-coldstart-doc.
## What changes were proposed in this pull request?
Update doc for R, programming guide. Clarify default behavior for all languages.
## How was this patch tested?
manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17128 from felixcheung/jsonwholefiledoc.
## What changes were proposed in this pull request?
This change addresses the renaming of the `simple.sbt` build file to
`build.sbt`. Newer versions of the sbt tool are not finding the older
named file and are looking for the `build.sbt`. The quickstart
instructions for self-contained applications is updated with this
change.
## How was this patch tested?
As this is a relatively minor change of a few words, the markdown was checked for syntax and spelling. Site was built with `SKIP_API=1 jekyll serve` for testing purposes.
Author: Michael McCune <msm@redhat.com>
Closes#17101 from elmiko/spark-19769.
Update GLM documentation to include the Tweedie distribution. #16344
jkbradley yanboliang
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#17103 from actuaryzhang/doc.
## What changes were proposed in this pull request?
Removed duplicated lines in sql python example and found a typo.
## How was this patch tested?
Searched for other typo's in the page to minimize PR's.
Author: Boaz Mohar <boazmohar@gmail.com>
Closes#17066 from boazmohar/doc-fix.
## What changes were proposed in this pull request?
Minor typo in `even-time`, which is changed to `event-time` and a couple of grammatical errors fix.
## How was this patch tested?
N/A - since this is a doc fix. I did a jekyll build locally though.
Author: Ramkumar Venkataraman <rvenkataraman@paypal.com>
Closes#17037 from ramkumarvenkat/doc-fix.
## What changes were proposed in this pull request?
We are proposing addition of pro-active block replication in case of executor failures. BlockManagerMasterEndpoint does all the book-keeping to keep a track of all the executors and the blocks they hold. It also keeps a track of which executors are alive through heartbeats. When an executor is removed, all this book-keeping state is updated to reflect the lost executor. This step can be used to identify executors that are still in possession of a copy of the cached data and a message could be sent to them to use the existing "replicate" function to find and place new replicas on other suitable hosts. Blocks replicated this way will let the master know of their existence.
This can happen when an executor is lost, and would that way be pro-active as opposed be being done at query time.
## How was this patch tested?
This patch was tested with existing unit tests along with new unit tests added to test the functionality.
Author: Shubham Chopra <schopra31@bloomberg.net>
Closes#14412 from shubhamchopra/ProactiveBlockReplication.
## What changes were proposed in this pull request?
follow up pr of #16949.
## How was this patch tested?
jenkins
Author: uncleGen <hustyugm@gmail.com>
Closes#17033 from uncleGen/doc-restapi-environment.
This commit moves developer-specific information from the release-
specific documentation in this repo to the developer tools page on
the main Spark website. This commit relies on this PR on the
Spark website: https://github.com/apache/spark-website/pull/33.
srowen
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#17018 from kayousterhout/SPARK-19684.
Allow an application to use the History Server URL as the tracking
URL in the YARN RM, so there's still a link to the web UI somewhere
in YARN even if the driver's UI is disabled. This is useful, for
example, if an admin wants to disable the driver UI by default for
applications, since it's harder to secure it (since it involves non
trivial ssl certificate and auth management that admins may not want
to expose to user apps).
This needs to be opt-in, because of the way the YARN proxy works, so
a new configuration was added to enable the option.
The YARN RM will proxy requests to live AMs instead of redirecting
the client, so pages in the SHS UI will not render correctly since
they'll reference invalid paths in the RM UI. The proxy base support
in the SHS cannot be used since that would prevent direct access to
the SHS.
So, to solve this problem, for the feature to work end-to-end, a new
YARN-specific filter was added that detects whether the requests come
from the proxy and redirects the client appropriatly. The SHS admin has
to add this filter manually if they want the feature to work.
Tested with new unit test, and by running with the documented configuration
set in a test cluster. Also verified the driver UI is used when it's
enabled.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16946 from vanzin/SPARK-19554.
## What changes were proposed in this pull request?
Documentation and examples (Java, scala, python, R) for LinearSVC
## How was this patch tested?
local doc generation
Author: Yuhao Yang <yuhao.yang@intel.com>
Closes#16968 from hhbyyh/mlsvmdoc.
- Move external/java8-tests tests into core, streaming, sql and remove
- Remove MaxPermGen and related options
- Fix some reflection / TODOs around Java 8+ methods
- Update doc references to 1.7/1.8 differences
- Remove Java 7/8 related build profiles
- Update some plugins for better Java 8 compatibility
- Fix a few Java-related warnings
For the future:
- Update Java 8 examples to fully use Java 8
- Update Java tests to use lambdas for simplicity
- Update Java internal implementations to use lambdas
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16871 from srowen/SPARK-19493.
## What changes were proposed in this pull request?
This pull request includes python API and examples for LSH. The API changes was based on yanboliang 's PR #15768 and resolved conflicts and API changes on the Scala API. The examples are consistent with Scala examples of MinHashLSH and BucketedRandomProjectionLSH.
## How was this patch tested?
API and examples are tested using spark-submit:
`bin/spark-submit examples/src/main/python/ml/min_hash_lsh.py`
`bin/spark-submit examples/src/main/python/ml/bucketed_random_projection_lsh.py`
User guide changes are generated and manually inspected:
`SKIP_API=1 jekyll build`
Author: Yun Ni <yunn@uber.com>
Author: Yanbo Liang <ybliang8@gmail.com>
Author: Yunni <Euler57721@gmail.com>
Closes#16715 from Yunni/spark-18080.
## What changes were proposed in this pull request?
Revision to structured-streaming-kafka-integration.md to reflect new Batch query specification and options.
zsxwing tdas
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Tyson Condie <tcondie@gmail.com>
Closes#16918 from tcondie/kafka-docs.
## What changes were proposed in this pull request?
https://spark.apache.org/docs/latest/sql-programming-guide.html#caching-data-in-memory
In the doc, the call spark.cacheTable(“tableName”) and spark.uncacheTable(“tableName”) actually needs to be spark.catalog.cacheTable and spark.catalog.uncacheTable
## How was this patch tested?
Built the docs and verified the change shows up fine.
Author: Sunitha Kambhampati <skambha@us.ibm.com>
Closes#16919 from skambha/docChange.
Spark's I/O encryption uses an ephemeral key for each driver instance.
So driver B cannot decrypt data written by driver A since it doesn't
have the correct key.
The write ahead log is used for recovery, thus needs to be readable by
a different driver. So it cannot be encrypted by Spark's I/O encryption
code.
The BlockManager APIs used by the WAL code to write the data automatically
encrypt data, so changes are needed so that callers can to opt out of
encryption.
Aside from that, the "putBytes" API in the BlockManager does not do
encryption, so a separate situation arised where the WAL would write
unencrypted data to the BM and, when those blocks were read, decryption
would fail. So the WAL code needs to ask the BM to encrypt that data
when encryption is enabled; this code is not optimal since it results
in a (temporary) second copy of the data block in memory, but should be
OK for now until a more performant solution is added. The non-encryption
case should not be affected.
Tested with new unit tests, and by running streaming apps that do
recovery using the WAL data with I/O encryption turned on.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16862 from vanzin/SPARK-19520.
Hello
According to my understanding of commits 4b4e329e49 & 8b325b17ec, one may now encrypt shuffle files regardless of the cluster manager in use.
However I have limited understanding of the code, I'm not able to find out whether theses changes also comprise all "temporary local storage, such as shuffle files, cached data, and other application files".
Please feel free to amend or reject my PR if I'm wrong.
dud
Author: Hervé <dud225@users.noreply.github.com>
Closes#16885 from dud225/patch-1.
## What changes were proposed in this pull request?
Due to the newly added API in Hadoop 2.6.4+, Spark builds against Hadoop 2.6.0~2.6.3 will meet compile error. So here still reverting back to use reflection to handle this issue.
## How was this patch tested?
Manual verification.
Author: jerryshao <sshao@hortonworks.com>
Closes#16884 from jerryshao/SPARK-19545.
## What changes were proposed in this pull request?
In SPARK-8425, we introduced a mechanism for blacklisting executors and nodes (hosts). After a certain number of failures, these resources would be "blacklisted" and no further work would be assigned to them for some period of time.
In some scenarios, it is better to fail fast, and to simply kill these unreliable resources. This changes proposes to do so by having the BlacklistTracker kill unreliable resources when they would otherwise be "blacklisted".
In order to be thread safe, this code depends on the CoarseGrainedSchedulerBackend sending a message to the driver backend in order to do the actual killing. This also helps to prevent a race which would permit work to begin on a resource (executor or node), between the time the resource is marked for killing and the time at which it is finally killed.
## How was this patch tested?
./dev/run-tests
Ran https://github.com/jsoltren/jose-utils/blob/master/blacklist/test-blacklist.sh, and checked logs to see executors and nodes being killed.
Testing can likely be improved here; suggestions welcome.
Author: José Hiram Soltren <jose@cloudera.com>
Closes#16650 from jsoltren/SPARK-16554-submit.
Make the SSL port configuration explicit, instead of deriving it
from the non-SSL port, but retain the existing functionality in
case anyone depends on it.
The change starts the HTTPS and HTTP connectors separately, so
that it's possible to use independent ports for each. For that to
work, the initialization of the server needs to be shuffled around
a bit. The change also makes it so the initialization of both
connectors is similar, and end up using the same Scheduler - previously
only the HTTP connector would use the correct one.
Also fixed some outdated documentation about a couple of services
that were removed long ago.
Tested with unit tests and by running spark-shell with SSL configs.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16625 from vanzin/SPARK-17874.
## What changes were proposed in this pull request?
- Remove support for Hadoop 2.5 and earlier
- Remove reflection and code constructs only needed to support multiple versions at once
- Update docs to reflect newer versions
- Remove older versions' builds and profiles.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16810 from srowen/SPARK-19464.
## What changes were proposed in this pull request?
Update programming guide, example and vignette with Bisecting k-means.
Author: krishnakalyan3 <krishnakalyan3@gmail.com>
Closes#16767 from krishnakalyan3/bisecting-kmeans.
## What changes were proposed in this pull request?
Fix brokens links in ml-pipeline and ml-tuning
`<div data-lang="scala">` -> `<div data-lang="scala" markdown="1">`
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#16754 from zhengruifeng/doc_api_fix.
## What changes were proposed in this pull request?
This PR proposes three things as below:
- Support LaTex inline-formula, `\( ... \)` in Scala API documentation
It seems currently,
```
\( ... \)
```
are rendered as they are, for example,
<img width="345" alt="2017-01-30 10 01 13" src="https://cloud.githubusercontent.com/assets/6477701/22423960/ab37d54a-e737-11e6-9196-4f6229c0189c.png">
It seems mistakenly more backslashes were added.
- Fix warnings Scaladoc/Javadoc generation
This PR fixes t two types of warnings as below:
```
[warn] .../spark/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala:335: Could not find any member to link for "UnsupportedOperationException".
[warn] /**
[warn] ^
```
```
[warn] .../spark/sql/core/src/main/scala/org/apache/spark/sql/internal/VariableSubstitution.scala:24: Variable var undefined in comment for class VariableSubstitution in class VariableSubstitution
[warn] * `${var}`, `${system:var}` and `${env:var}`.
[warn] ^
```
- Fix Javadoc8 break
```
[error] .../spark/mllib/target/java/org/apache/spark/ml/PredictionModel.java:7: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/mllib/target/java/org/apache/spark/ml/PredictorParams.java:12: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/mllib/target/java/org/apache/spark/ml/Predictor.java:10: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/sql/hive/target/java/org/apache/spark/sql/hive/HiveAnalysis.java:5: error: reference not found
[error] * Note that, this rule must be run after {link PreprocessTableInsertion}.
[error] ^
```
## How was this patch tested?
Manually via `sbt unidoc` and `jeykil build`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16741 from HyukjinKwon/warn-and-break.
### What changes were proposed in this pull request?
The case are not sensitive in JDBC options, after the PR https://github.com/apache/spark/pull/15884 is merged to Spark 2.1.
### How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#16734 from gatorsmile/fixDocCaseInsensitive.
## What changes were proposed in this pull request?
- A separate subsection for Aggregations under “Getting Started” in the Spark SQL programming guide. It mentions which aggregate functions are predefined and how users can create their own.
- Examples of using the `UserDefinedAggregateFunction` abstract class for untyped aggregations in Java and Scala.
- Examples of using the `Aggregator` abstract class for type-safe aggregations in Java and Scala.
- Python is not covered.
- The PR might not resolve the ticket since I do not know what exactly was planned by the author.
In total, there are four new standalone examples that can be executed via `spark-submit` or `run-example`. The updated Spark SQL programming guide references to these examples and does not contain hard-coded snippets.
## How was this patch tested?
The patch was tested locally by building the docs. The examples were run as well.
Author: aokolnychyi <okolnychyyanton@gmail.com>
Closes#16329 from aokolnychyi/SPARK-16046.
This change introduces a new auth mechanism to the transport library,
to be used when users enable strong encryption. This auth mechanism
has better security than the currently used DIGEST-MD5.
The new protocol uses symmetric key encryption to mutually authenticate
the endpoints, and is very loosely based on ISO/IEC 9798.
The new protocol falls back to SASL when it thinks the remote end is old.
Because SASL does not support asking the server for multiple auth protocols,
which would mean we could re-use the existing SASL code by just adding a
new SASL provider, the protocol is implemented outside of the SASL API
to avoid the boilerplate of adding a new provider.
Details of the auth protocol are discussed in the included README.md
file.
This change partly undos the changes added in SPARK-13331; AES encryption
is now decoupled from SASL authentication. The encryption code itself,
though, has been re-used as part of this change.
## How was this patch tested?
- Unit tests
- Tested Spark 2.2 against Spark 1.6 shuffle service with SASL enabled
- Tested Spark 2.2 against Spark 2.2 shuffle service with SASL fallback disabled
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16521 from vanzin/SPARK-19139.
## What changes were proposed in this pull request?
Currently, spark history server REST API provides functionality to query applications by application start time range based on minDate and maxDate query parameters, but it lacks support to query applications by their end time. In this pull request we are proposing optional minEndDate and maxEndDate query parameters and filtering capability based on these parameters to spark history server REST API. This functionality can be used for following queries,
1. Applications finished in last 'x' minutes
2. Applications finished before 'y' time
3. Applications finished between 'x' time to 'y' time
4. Applications started from 'x' time and finished before 'y' time.
For backward compatibility, we can keep existing minDate and maxDate query parameters as they are and they can continue support filtering based on start time range.
## How was this patch tested?
Existing unit tests and 4 new unit tests.
Author: Parag Chaudhari <paragpc@amazon.com>
Closes#11867 from paragpc/master-SHS-query-by-endtime_2.
## What changes were proposed in this pull request?
Fix typo in docs
## How was this patch tested?
Author: uncleGen <hustyugm@gmail.com>
Closes#16658 from uncleGen/typo-issue.
## What changes were proposed in this pull request?
Drop more elements when `stageData.taskData.size > retainedTasks` to reduce the number of times on call drop function.
## How was this patch tested?
Jenkins
Author: Yuming Wang <wgyumg@gmail.com>
Closes#16527 from wangyum/SPARK-19146.
## What changes were proposed in this pull request?
In docs/security.md, there is a description as follows.
```
steps to configure the key-stores and the trust-store for the standalone deployment mode is as
follows:
* Generate a keys pair for each node
* Export the public key of the key pair to a file on each node
* Import all exported public keys into a single trust-store
```
According to markdown format, the first item should follow a blank line.
## How was this patch tested?
Manually tested.
Following captures are rendered web page before and after fix.
* before
* after
Author: sarutak <sarutak@oss.nttdata.co.jp>
Closes#16653 from sarutak/SPARK-19302.
## What changes were proposed in this pull request?
`spark.yarn.access.namenodes` configuration cannot actually reflects the usage of it, inside the code it is the Hadoop filesystems we get tokens, not NNs. So here propose to update the name of this configuration, also change the related code and doc.
## How was this patch tested?
Local verification.
Author: jerryshao <sshao@hortonworks.com>
Closes#16560 from jerryshao/SPARK-19179.
## What changes were proposed in this pull request?
core/src/main/scala/org/apache/spark/SparkContext.scala contains LOCAL_N_FAILURES_REGEX master mode, but this was never documented, so do so.
## How was this patch tested?
By using the Github Markdown preview feature.
Author: Maurus Cuelenaere <mcuelenaere@gmail.com>
Closes#16562 from mcuelenaere/patch-1.
## What changes were proposed in this pull request?
Adding option in spark-submit to allow overriding the default IvySettings used to resolve artifacts as part of the Spark Packages functionality. This will allow all artifact resolution to go through a central managed repository, such as Nexus or Artifactory, where site admins can better approve and control what is used with Spark apps.
This change restructures the creation of the IvySettings object in two distinct ways. First, if the `spark.ivy.settings` option is not defined then `buildIvySettings` will create a default settings instance, as before, with defined repositories (Maven Central) included. Second, if the option is defined, the ivy settings file will be loaded from the given path and only repositories defined within will be used for artifact resolution.
## How was this patch tested?
Existing tests for default behaviour, Manual tests that load a ivysettings.xml file with local and Nexus repositories defined. Added new test to load a simple Ivy settings file with a local filesystem resolver.
Author: Bryan Cutler <cutlerb@gmail.com>
Author: Ian Hummel <ian@themodernlife.net>
Closes#15119 from BryanCutler/spark-custom-IvySettings.
Currently Spark can only get token renewal interval from security HDFS (hdfs://), if Spark runs with other security file systems like webHDFS (webhdfs://), wasb (wasb://), ADLS, it will ignore these tokens and not get token renewal intervals from these tokens. These will make Spark unable to work with these security clusters. So instead of only checking HDFS token, we should generalize to support different DelegationTokenIdentifier.
## How was this patch tested?
Manually verified in security cluster.
Author: jerryshao <sshao@hortonworks.com>
Closes#16432 from jerryshao/SPARK-19021.
## What changes were proposed in this pull request?
This PR allow update mode for non-aggregation streaming queries. It will be same as the append mode if a query has no aggregations.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16520 from zsxwing/update-without-agg.
## What changes were proposed in this pull request?
Add FDR test case in ml/feature/ChiSqSelectorSuite.
Improve some comments in the code.
This is a follow-up pr for #15212.
## How was this patch tested?
ut
Author: Peng, Meng <peng.meng@intel.com>
Closes#16434 from mpjlu/fdr_fwe_update.
## What changes were proposed in this pull request?
This PR adds a new behavior change description on `CREATE TABLE ... LOCATION` at `sql-programming-guide.md` clearly under `Upgrading From Spark SQL 1.6 to 2.0`. This change is introduced at Apache Spark 2.0.0 as [SPARK-15276](https://issues.apache.org/jira/browse/SPARK-15276).
## How was this patch tested?
```
SKIP_API=1 jekyll build
```
**Newly Added Description**
<img width="913" alt="new" src="https://cloud.githubusercontent.com/assets/9700541/21743606/7efe2b12-d4ba-11e6-8a0d-551222718ea2.png">
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#16400 from dongjoon-hyun/SPARK-18941.
## What changes were proposed in this pull request?
configuration.html section headings were not specified correctly in markdown and weren't rendering, being recognized correctly. Removed extra p tags and pulled level 4 titles up to level 3, since level 3 had been skipped. This improves the TOC.
## How was this patch tested?
Doc build, manual check.
Author: Sean Owen <sowen@cloudera.com>
Closes#16490 from srowen/SPARK-19106.
## What changes were proposed in this pull request?
Current HistoryServer's ACLs is derived from application event-log, which means the newly changed ACLs cannot be applied to the old data, this will become a problem where newly added admin cannot access the old application history UI, only the new application can be affected.
So here propose to add admin ACLs for history server, any configured user/group could have the view access to all the applications, while the view ACLs derived from application run-time still take effect.
## How was this patch tested?
Unit test added.
Author: jerryshao <sshao@hortonworks.com>
Closes#16470 from jerryshao/SPARK-19033.
## What changes were proposed in this pull request?
Today we have different syntax to create data source or hive serde tables, we should unify them to not confuse users and step forward to make hive a data source.
Please read https://issues.apache.org/jira/secure/attachment/12843835/CREATE-TABLE.pdf for details.
TODO(for follow-up PRs):
1. TBLPROPERTIES is not added to the new syntax, we should decide if we wanna add it later.
2. `SHOW CREATE TABLE` should be updated to use the new syntax.
3. we should decide if we wanna change the behavior of `SET LOCATION`.
## How was this patch tested?
new tests
Author: Wenchen Fan <wenchen@databricks.com>
Closes#16296 from cloud-fan/create-table.
## What changes were proposed in this pull request?
add streaming rest api doc
related to pr #16253
cc saturday-shi srowen
## How was this patch tested?
Author: uncleGen <hustyugm@gmail.com>
Closes#16414 from uncleGen/SPARK-19009.
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.
## How was this patch tested?
N/A since only docs or comments were updated.
Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>
Closes#16455 from neurons/np.structure_streaming_doc.
## What changes were proposed in this pull request?
The configuration `spark.yarn.security.tokens.{service}.enabled` is deprecated. Now we should use `spark.yarn.security.credentials.{service}.enabled`. Some places in the doc is not updated yet.
## How was this patch tested?
N/A. Just doc change.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#16444 from viirya/minor-credential-provider-doc.
## What changes were proposed in this pull request?
Currently some code snippets in the programming guide just do not compile. We should fix them.
## How was this patch tested?
```
SKIP_API=1 jekyll build
```
## Screenshot from part of the change:
Author: Liwei Lin <lwlin7@gmail.com>
Closes#16442 from lw-lin/ss-pro-guide-.
## What changes were proposed in this pull request?
This PR documents the scalable partition handling feature in the body of the programming guide.
Before this PR, we only mention it in the migration guide. It's not super clear that external datasource tables require an extra `MSCK REPAIR TABLE` command is to have per-partition information persisted since 2.1.
## How was this patch tested?
N/A.
Author: Cheng Lian <lian@databricks.com>
Closes#16424 from liancheng/scalable-partition-handling-doc.
## What changes were proposed in this pull request?
Added missing Java example under section "Design Patterns for using foreachRDD". Now this section has examples in all 3 languages, improving consistency of documentation.
## How was this patch tested?
Manual.
Generated docs using command "SKIP_API=1 jekyll build" and verified generated HTML page manually.
The syntax of example has been tested for correctness using sample code on Java1.7 and Spark 2.2.0-SNAPSHOT.
Author: adesharatushar <tushar_adeshara@persistent.com>
Closes#16408 from adesharatushar/streaming-doc-fix.
## What changes were proposed in this pull request?
Univariate feature selection works by selecting the best features based on univariate statistical tests.
FDR and FWE are a popular univariate statistical test for feature selection.
In 2005, the Benjamini and Hochberg paper on FDR was identified as one of the 25 most-cited statistical papers. The FDR uses the Benjamini-Hochberg procedure in this PR. https://en.wikipedia.org/wiki/False_discovery_rate.
In statistics, FWE is the probability of making one or more false discoveries, or type I errors, among all the hypotheses when performing multiple hypotheses tests.
https://en.wikipedia.org/wiki/Family-wise_error_rate
We add FDR and FWE methods for ChiSqSelector in this PR, like it is implemented in scikit-learn.
http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection
## How was this patch tested?
ut will be added soon
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: Peng <peng.meng@intel.com>
Author: Peng, Meng <peng.meng@intel.com>
Closes#15212 from mpjlu/fdr_fwe.
## What changes were proposed in this pull request?
add example with `--pip` and `--r` switch as it is actually done in create-release
## How was this patch tested?
Doc only
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16364 from felixcheung/buildguide.
## What changes were proposed in this pull request?
On configuration doc page:https://spark.apache.org/docs/latest/configuration.html
We mentioned spark.kryoserializer.buffer.max : Maximum allowable size of Kryo serialization buffer. This must be larger than any object you attempt to serialize. Increase this if you get a "buffer limit exceeded" exception inside Kryo.
from source code, it has hard coded upper limit :
```
val maxBufferSizeMb = conf.getSizeAsMb("spark.kryoserializer.buffer.max", "64m").toInt
if (maxBufferSizeMb >= ByteUnit.GiB.toMiB(2))
{ throw new IllegalArgumentException("spark.kryoserializer.buffer.max must be less than " + s"2048 mb, got: + $maxBufferSizeMb mb.") }
```
We should mention "this value must be less than 2048 mb" on the configuration doc page as well.
## How was this patch tested?
None. Since it's minor doc change.
Author: Yuexin Zhang <yxzhang@cloudera.com>
Closes#16412 from cnZach/SPARK-19006.
## What changes were proposed in this pull request?
We can build Python API docs by `cd ./python/docs && make html for Python` and R API docs by `cd ./R && sh create-docs.sh for R` separately. However, `jekyll` fails in some environments.
This PR aims to support `SKIP_PYTHONDOC` and `SKIP_RDOC` for documentation build in `docs` folder. Currently, we can use `SKIP_SCALADOC` or `SKIP_API`. The reason providing additional options is that the Spark documentation build uses a number of tools to build HTML docs and API docs in Scala, Python and R. Specifically, for Python and R,
- Python API docs requires `sphinx`.
- R API docs requires `R` installation and `knitr` (and more others libraries).
In other words, we cannot generate Python API docs without R installation. Also, we cannot generate R API docs without Python `sphinx` installation. If Spark provides `SKIP_PYTHONDOC` and `SKIP_RDOC` like `SKIP_SCALADOC`, it would be more convenient.
## How was this patch tested?
Manual.
**Skipping Scala/Java/Python API Doc Build**
```bash
$ cd docs
$ SKIP_SCALADOC=1 SKIP_PYTHONDOC=1 jekyll build
$ ls api
DESCRIPTION R
```
**Skipping Scala/Java/R API Doc Build**
```bash
$ cd docs
$ SKIP_SCALADOC=1 SKIP_RDOC=1 jekyll build
$ ls api
python
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#16336 from dongjoon-hyun/SPARK-18923.
## What changes were proposed in this pull request?
Spark's current task cancellation / task killing mechanism is "best effort" because some tasks may not be interruptible or may not respond to their "killed" flags being set. If a significant fraction of a cluster's task slots are occupied by tasks that have been marked as killed but remain running then this can lead to a situation where new jobs and tasks are starved of resources that are being used by these zombie tasks.
This patch aims to address this problem by adding a "task reaper" mechanism to executors. At a high-level, task killing now launches a new thread which attempts to kill the task and then watches the task and periodically checks whether it has been killed. The TaskReaper will periodically re-attempt to call `TaskRunner.kill()` and will log warnings if the task keeps running. I modified TaskRunner to rename its thread at the start of the task, allowing TaskReaper to take a thread dump and filter it in order to log stacktraces from the exact task thread that we are waiting to finish. If the task has not stopped after a configurable timeout then the TaskReaper will throw an exception to trigger executor JVM death, thereby forcibly freeing any resources consumed by the zombie tasks.
This feature is flagged off by default and is controlled by four new configurations under the `spark.task.reaper.*` namespace. See the updated `configuration.md` doc for details.
## How was this patch tested?
Tested via a new test case in `JobCancellationSuite`, plus manual testing.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#16189 from JoshRosen/cancellation.
## What changes were proposed in this pull request?
Add additional information to wholeTextFiles in the Programming Guide. Also explain partitioning policy difference in relation to textFile and its impact on performance.
Also added reference to the underlying CombineFileInputFormat
## How was this patch tested?
Manual build of documentation and inspection in browser
```
cd docs
jekyll serve --watch
```
Author: Michal Senkyr <mike.senkyr@gmail.com>
Closes#16157 from michalsenkyr/wholeTextFilesExpandedDocs.
## What changes were proposed in this pull request?
This builds upon the blacklisting introduced in SPARK-17675 to add blacklisting of executors and nodes for an entire Spark application. Resources are blacklisted based on tasks that fail, in tasksets that eventually complete successfully; they are automatically returned to the pool of active resources based on a timeout. Full details are available in a design doc attached to the jira.
## How was this patch tested?
Added unit tests, ran them via Jenkins, also ran a handful of them in a loop to check for flakiness.
The added tests include:
- verifying BlacklistTracker works correctly
- verifying TaskSchedulerImpl interacts with BlacklistTracker correctly (via a mock BlacklistTracker)
- an integration test for the entire scheduler with blacklisting in a few different scenarios
Author: Imran Rashid <irashid@cloudera.com>
Author: mwws <wei.mao@intel.com>
Closes#14079 from squito/blacklist-SPARK-8425.
## What changes were proposed in this pull request?
Since Apache Spark 1.4.0, R API document page has a broken link on `DESCRIPTION file` because Jekyll plugin script doesn't copy the file. This PR aims to fix that.
- Official Latest Website: http://spark.apache.org/docs/latest/api/R/index.html
- Apache Spark 2.1.0-rc2: http://people.apache.org/~pwendell/spark-releases/spark-2.1.0-rc2-docs/api/R/index.html
## How was this patch tested?
Manual.
```bash
cd docs
SKIP_SCALADOC=1 jekyll build
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#16292 from dongjoon-hyun/SPARK-18875.
This change moves the logic that translates Spark configuration to
commons-crypto configuration to the network-common module. It also
extends TransportConf and ConfigProvider to provide the necessary
interfaces for the translation to work.
As part of the change, I removed SystemPropertyConfigProvider, which
was mostly used as an "empty config" in unit tests, and adjusted the
very few tests that required a specific config.
I also changed the config keys for AES encryption to live under the
"spark.network." namespace, which is more correct than their previous
names under "spark.authenticate.".
Tested via existing unit test.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16200 from vanzin/SPARK-18773.
## What changes were proposed in this pull request?
This PR clarifies where accumulators will be displayed.
## How was this patch tested?
No testing.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Bill Chambers <bill@databricks.com>
Author: anabranch <wac.chambers@gmail.com>
Author: Bill Chambers <wchambers@ischool.berkeley.edu>
Closes#16180 from anabranch/improve-acc-docs.
## What changes were proposed in this pull request?
According to the notice of the following Wiki front page, we can remove the obsolete wiki pointer safely in `README.md` and `docs/index.md`, too. These two lines are the last occurrence of that links.
```
All current wiki content has been merged into pages at http://spark.apache.org as of November 2016.
Each page links to the new location of its information on the Spark web site.
Obsolete wiki content is still hosted here, but carries a notice that it is no longer current.
```
## How was this patch tested?
Manual.
- `README.md`: https://github.com/dongjoon-hyun/spark/tree/remove_wiki_from_readme
- `docs/index.md`:
```
cd docs
SKIP_API=1 jekyll build
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#16239 from dongjoon-hyun/remove_wiki_from_readme.
## What changes were proposed in this pull request?
There has been some confusion around "Spark ML" vs. "MLlib". This PR adds some FAQ-like entries to the MLlib user guide to explain "Spark ML" and reduce the confusion.
I check the [Spark FAQ page](http://spark.apache.org/faq.html), which seems too high-level for the content here. So I added it to the MLlib user guide instead.
cc: mateiz
Author: Xiangrui Meng <meng@databricks.com>
Closes#16241 from mengxr/SPARK-18812.
## What changes were proposed in this pull request?
Typo fixes
## How was this patch tested?
Local build. Awaiting the official build.
Author: Jacek Laskowski <jacek@japila.pl>
Closes#16144 from jaceklaskowski/typo-fixes.
## What changes were proposed in this pull request?
* Add all R examples for ML wrappers which were added during 2.1 release cycle.
* Split the whole ```ml.R``` example file into individual example for each algorithm, which will be convenient for users to rerun them.
* Add corresponding examples to ML user guide.
* Update ML section of SparkR user guide.
Note: MLlib Scala/Java/Python examples will be consistent, however, SparkR examples may different from them, since R users may use the algorithms in a different way, for example, using R ```formula``` to specify ```featuresCol``` and ```labelCol```.
## How was this patch tested?
Run all examples manually.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#16148 from yanboliang/spark-18325.
## What changes were proposed in this pull request?
WeightedLeastSquares now supports L1 and elastic net penalties and has an additional solver option: QuasiNewton. The docs are updated to reflect this change.
## How was this patch tested?
Docs only. Generated documentation to make sure Latex looks ok.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#16139 from sethah/SPARK-18705.
## What changes were proposed in this pull request?
Logistic Regression summary is added in Python API. We need to add example and document for summary.
The newly added example is consistent with Scala and Java examples.
## How was this patch tested?
Manually tests: Run the example with spark-submit; copy & paste code into pyspark; build document and check the document.
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes#16064 from wangmiao1981/py.
## What changes were proposed in this pull request?
Although, currently, the saveAsTable does not provide an API to save the table as an external table from a DataFrame, we can achieve this functionality by using options on DataFrameWriter where the key for the map is the String: "path" and the value is another String which is the location of the external table itself. This can be provided before the call to saveAsTable is performed.
## How was this patch tested?
Documentation was reviewed for formatting and content after the push was performed on the branch.
Author: c-sahuja <sahuja@cloudera.com>
Closes#16185 from c-sahuja/createExternalTable.
This PR adds `spark.ui.showConsoleProgress` to the configuration docs.
I tested this PR by building the docs locally and confirming that this change shows up as expected.
Relates to #3029.
Author: Nicholas Chammas <nicholas.chammas@gmail.com>
Closes#16151 from nchammas/ui-progressbar-doc.
Looking at the distributions provided on spark.apache.org, I see that the Spark YARN shuffle jar is under `yarn/` and not `lib/`.
This change is so minor I'm not sure it needs a JIRA. But let me know if so and I'll create one.
Author: Nicholas Chammas <nicholas.chammas@gmail.com>
Closes#16130 from nchammas/yarn-doc-fix.
## What changes were proposed in this pull request?
Add R examples to ML programming guide for the following algorithms as POC:
* spark.glm
* spark.survreg
* spark.naiveBayes
* spark.kmeans
The four algorithms were added to SparkR since 2.0.0, more docs for algorithms added during 2.1 release cycle will be addressed in a separate follow-up PR.
## How was this patch tested?
This is the screenshots of generated ML programming guide for ```GeneralizedLinearRegression```:
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#16136 from yanboliang/spark-18279.
## What changes were proposed in this pull request?
If SparkR is running as a package and it has previously downloaded Spark Jar it should be able to run as before without having to set SPARK_HOME. Basically with this bug the auto install Spark will only work in the first session.
This seems to be a regression on the earlier behavior.
Fix is to always try to install or check for the cached Spark if running in an interactive session.
As discussed before, we should probably only install Spark iff running in an interactive session (R shell, RStudio etc)
## How was this patch tested?
Manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16077 from felixcheung/rsessioninteractive.
## What changes were proposed in this pull request?
The user guide for LSH is added to ml-features.md, with several scala/java examples in spark-examples.
## How was this patch tested?
Doc has been generated through Jekyll, and checked through manual inspection.
Author: Yunni <Euler57721@gmail.com>
Author: Yun Ni <yunn@uber.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Yun Ni <Euler57721@gmail.com>
Closes#15795 from Yunni/SPARK-18081-lsh-guide.
## What changes were proposed in this pull request?
This patch bumps master branch version to 2.2.0-SNAPSHOT.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#16126 from rxin/SPARK-18695.
## What changes were proposed in this pull request?
Update ML programming and migration guide for 2.1 release.
## How was this patch tested?
Doc change, no test.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#16076 from yanboliang/spark-18324.
## What changes were proposed in this pull request?
API review for 2.1, except ```LSH``` related classes which are still under development.
## How was this patch tested?
Only doc changes, no new tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#16009 from yanboliang/spark-18318.
## What changes were proposed in this pull request?
Added missing semicolon in quick-start-guide java example code which wasn't compiling before.
## How was this patch tested?
Locally by running and generating site for docs. You can see the last line contains ";" in the below snapshot.
Author: manishAtGit <manish@knoldus.com>
Closes#16081 from manishatGit/fixed-quick-start-guide.
## What changes were proposed in this pull request?
This documents the partition handling changes for Spark 2.1 and how to migrate existing tables.
## How was this patch tested?
Built docs locally.
rxin
Author: Eric Liang <ekl@databricks.com>
Closes#16074 from ericl/spark-18145.
## What changes were proposed in this pull request?
This pull request contains updates to Scala and Java Accumulator code snippets in the programming guide.
- For Scala, the pull request fixes the signature of the 'add()' method in the custom Accumulator, which contained two params (as the old AccumulatorParam) instead of one (as in AccumulatorV2).
- The Java example was updated to use the AccumulatorV2 class since AccumulatorParam is marked as deprecated.
- Scala and Java examples are more consistent now.
## How was this patch tested?
This patch was tested manually by building the docs locally.
Author: aokolnychyi <okolnychyyanton@gmail.com>
Closes#16024 from aokolnychyi/fixed_accumulator_example.
This change modifies the method used to propagate encryption keys used during
shuffle. Instead of relying on YARN's UserGroupInformation credential propagation,
this change explicitly distributes the key using the messages exchanged between
driver and executor during registration. When RPC encryption is enabled, this means
key propagation is also secure.
This allows shuffle encryption to work in non-YARN mode, which means that it's
easier to write unit tests for areas of the code that are affected by the feature.
The key is stored in the SecurityManager; because there are many instances of
that class used in the code, the key is only guaranteed to exist in the instance
managed by the SparkEnv. This path was chosen to avoid storing the key in the
SparkConf, which would risk having the key being written to disk as part of the
configuration (as, for example, is done when starting YARN applications).
Tested by new and existing unit tests (which were moved from the YARN module to
core), and by running apps with shuffle encryption enabled.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#15981 from vanzin/SPARK-18547.
## What changes were proposed in this pull request?
This patch adds a new property called `spark.secret.redactionPattern` that
allows users to specify a scala regex to decide which Spark configuration
properties and environment variables in driver and executor environments
contain sensitive information. When this regex matches the property or
environment variable name, its value is redacted from the environment UI and
various logs like YARN and event logs.
This change uses this property to redact information from event logs and YARN
logs. It also, updates the UI code to adhere to this property instead of
hardcoding the logic to decipher which properties are sensitive.
Here's an image of the UI post-redaction:
Here's the text in the YARN logs, post-redaction:
``HADOOP_CREDSTORE_PASSWORD -> *********(redacted)``
Here's the text in the event logs, post-redaction:
``...,"spark.executorEnv.HADOOP_CREDSTORE_PASSWORD":"*********(redacted)","spark.yarn.appMasterEnv.HADOOP_CREDSTORE_PASSWORD":"*********(redacted)",...``
## How was this patch tested?
1. Unit tests are added to ensure that redaction works.
2. A YARN job reading data off of S3 with confidential information
(hadoop credential provider password) being provided in the environment
variables of driver and executor. And, afterwards, logs were grepped to make
sure that no mention of secret password was present. It was also ensure that
the job was able to read the data off of S3 correctly, thereby ensuring that
the sensitive information was being trickled down to the right places to read
the data.
3. The event logs were checked to make sure no mention of secret password was
present.
4. UI environment tab was checked to make sure there was no secret information
being displayed.
Author: Mark Grover <mark@apache.org>
Closes#15971 from markgrover/master_redaction.
## What changes were proposed in this pull request?
This PR is to fix incorrect `code` tag in `sql-programming-guide.md`
## How was this patch tested?
Manually.
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes#15941 from weiqingy/fixtag.
## What changes were proposed in this pull request?
This is a follow-up PR of #15868 to merge `maxConnections` option into `numPartitions` options.
## How was this patch tested?
Pass the existing tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#15966 from dongjoon-hyun/SPARK-18413-2.
## What changes were proposed in this pull request?
Updates links to the wiki to links to the new location of content on spark.apache.org.
## How was this patch tested?
Doc builds
Author: Sean Owen <sowen@cloudera.com>
Closes#15967 from srowen/SPARK-18073.1.
## What changes were proposed in this pull request?
This PR adds a new JDBCOption `maxConnections` which means the maximum number of simultaneous JDBC connections allowed. This option applies only to writing with coalesce operation if needed. It defaults to the number of partitions of RDD. Previously, SQL users cannot cannot control this while Scala/Java/Python users can use `coalesce` (or `repartition`) API.
**Reported Scenario**
For the following cases, the number of connections becomes 200 and database cannot handle all of them.
```sql
CREATE OR REPLACE TEMPORARY VIEW resultview
USING org.apache.spark.sql.jdbc
OPTIONS (
url "jdbc:oracle:thin:10.129.10.111:1521:BKDB",
dbtable "result",
user "HIVE",
password "HIVE"
);
-- set spark.sql.shuffle.partitions=200
INSERT OVERWRITE TABLE resultview SELECT g, count(1) AS COUNT FROM tnet.DT_LIVE_INFO GROUP BY g
```
## How was this patch tested?
Manual. Do the followings and see Spark UI.
**Step 1 (MySQL)**
```
CREATE TABLE t1 (a INT);
CREATE TABLE data (a INT);
INSERT INTO data VALUES (1);
INSERT INTO data VALUES (2);
INSERT INTO data VALUES (3);
```
**Step 2 (Spark)**
```scala
SPARK_HOME=$PWD bin/spark-shell --driver-memory 4G --driver-class-path mysql-connector-java-5.1.40-bin.jar
scala> sql("SET spark.sql.shuffle.partitions=3")
scala> sql("CREATE OR REPLACE TEMPORARY VIEW data USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:mysql://localhost:3306/t', dbtable 'data', user 'root', password '')")
scala> sql("CREATE OR REPLACE TEMPORARY VIEW t1 USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:mysql://localhost:3306/t', dbtable 't1', user 'root', password '', maxConnections '1')")
scala> sql("INSERT OVERWRITE TABLE t1 SELECT a FROM data GROUP BY a")
scala> sql("CREATE OR REPLACE TEMPORARY VIEW t1 USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:mysql://localhost:3306/t', dbtable 't1', user 'root', password '', maxConnections '2')")
scala> sql("INSERT OVERWRITE TABLE t1 SELECT a FROM data GROUP BY a")
scala> sql("CREATE OR REPLACE TEMPORARY VIEW t1 USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:mysql://localhost:3306/t', dbtable 't1', user 'root', password '', maxConnections '3')")
scala> sql("INSERT OVERWRITE TABLE t1 SELECT a FROM data GROUP BY a")
scala> sql("CREATE OR REPLACE TEMPORARY VIEW t1 USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:mysql://localhost:3306/t', dbtable 't1', user 'root', password '', maxConnections '4')")
scala> sql("INSERT OVERWRITE TABLE t1 SELECT a FROM data GROUP BY a")
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#15868 from dongjoon-hyun/SPARK-18413.
## What changes were proposed in this pull request?
Avoid hard-coding spark.rpc.askTimeout to non-default in Client; fix doc about spark.rpc.askTimeout default
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#15833 from srowen/SPARK-18353.
## What changes were proposed in this pull request?
1, There are two `[Graph.partitionBy]` in `graphx-programming-guide.md`, the first one had no effert.
2, `DataFrame`, `Transformer`, `Pipeline` and `Parameter` in `ml-pipeline.md` were linked to `ml-guide.html` by mistake.
3, `PythonMLLibAPI` in `mllib-linear-methods.md` was not accessable, because class `PythonMLLibAPI` is private.
4, Other link updates.
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#15912 from zhengruifeng/md_fix.
## What changes were proposed in this pull request?
Remove `spark.driver.memory`, `spark.executor.memory`, `spark.driver.cores`, and `spark.executor.cores` from `running-on-yarn.md` as they are not Yarn-specific, and they are also defined in`configuration.md`.
## How was this patch tested?
Build passed & Manually check.
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes#15869 from weiqingy/yarnDoc.
## What changes were proposed in this pull request?
Suggest users to increase `NodeManager's` heap size if `External Shuffle Service` is enabled as
`NM` can spend a lot of time doing GC resulting in shuffle operations being a bottleneck due to `Shuffle Read blocked time` bumped up.
Also because of GC `NodeManager` can use an enormous amount of CPU and cluster performance will suffer.
I have seen NodeManager using 5-13G RAM and up to 2700% CPU with `spark_shuffle` service on.
## How was this patch tested?
#### Added step 5:
Author: Artur Sukhenko <artur.sukhenko@gmail.com>
Closes#15906 from Devian-ua/nmHeapSize.
## What changes were proposed in this pull request?
This PR aims to provide a pip installable PySpark package. This does a bunch of work to copy the jars over and package them with the Python code (to prevent challenges from trying to use different versions of the Python code with different versions of the JAR). It does not currently publish to PyPI but that is the natural follow up (SPARK-18129).
Done:
- pip installable on conda [manual tested]
- setup.py installed on a non-pip managed system (RHEL) with YARN [manual tested]
- Automated testing of this (virtualenv)
- packaging and signing with release-build*
Possible follow up work:
- release-build update to publish to PyPI (SPARK-18128)
- figure out who owns the pyspark package name on prod PyPI (is it someone with in the project or should we ask PyPI or should we choose a different name to publish with like ApachePySpark?)
- Windows support and or testing ( SPARK-18136 )
- investigate details of wheel caching and see if we can avoid cleaning the wheel cache during our test
- consider how we want to number our dev/snapshot versions
Explicitly out of scope:
- Using pip installed PySpark to start a standalone cluster
- Using pip installed PySpark for non-Python Spark programs
*I've done some work to test release-build locally but as a non-committer I've just done local testing.
## How was this patch tested?
Automated testing with virtualenv, manual testing with conda, a system wide install, and YARN integration.
release-build changes tested locally as a non-committer (no testing of upload artifacts to Apache staging websites)
Author: Holden Karau <holden@us.ibm.com>
Author: Juliet Hougland <juliet@cloudera.com>
Author: Juliet Hougland <not@myemail.com>
Closes#15659 from holdenk/SPARK-1267-pip-install-pyspark.
## What changes were proposed in this pull request?
Add links to API docs for ML algos
## How was this patch tested?
Manual checking for the API links
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#15890 from zhengruifeng/algo_link.
## What changes were proposed in this pull request?
Fix typos in the 'configuration', 'monitoring' and 'sql-programming-guide' documentation.
## How was this patch tested?
Manually.
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes#15886 from weiqingy/fixTypo.
## What changes were proposed in this pull request?
1,Remove `runs` from docs of mllib.KMeans
2,Add notes for `k` according to comments in sources
## How was this patch tested?
existing tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#15873 from zhengruifeng/update_doc_mllib_kmeans.
## What changes were proposed in this pull request?
Adds support for CNI-isolated containers
## How was this patch tested?
I launched SparkPi both with and without `spark.mesos.network.name`, and verified the job completed successfully.
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#15740 from mgummelt/spark-342-cni.
## What changes were proposed in this pull request?
1, Add link of `VertexRDD` and `EdgeRDD`
2, Notify in `Vertex and Edge RDDs` that not all methods are listed
3, `VertexID` -> `VertexId`
## How was this patch tested?
No tests, only docs is modified
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#15875 from zhengruifeng/update_graphop_doc.
## What changes were proposed in this pull request?
Update the python section of the Structured Streaming Guide from .builder() to .builder
## How was this patch tested?
Validated documentation and successfully running the test example.
Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark before opening a pull request.
'Builder' object is not callable object hence changed .builder() to
.builder
Author: Denny Lee <dennylee@gallifrey.local>
Closes#15872 from dennyglee/master.
## What changes were proposed in this pull request?
Many applications take Spark as a computing engine and run on it. This PR adds a configuration property `spark.log.callerContext` that can be used by Spark's upstream applications (e.g. Oozie) to set up their caller contexts into Spark. In the end, Spark will combine its own caller context with the caller contexts of its upstream applications, and write them into Yarn RM log and HDFS audit log.
The audit log has a config to truncate the caller contexts passed in (default 128). The caller contexts will be sent over rpc, so it should be concise. The call context written into HDFS log and Yarn log consists of two parts: the information `A` specified by Spark itself and the value `B` of `spark.log.callerContext` property. Currently `A` typically takes 64 to 74 characters, so `B` can have up to 50 characters (mentioned in the doc `running-on-yarn.md`)
## How was this patch tested?
Manual tests. I have run some Spark applications with `spark.log.callerContext` configuration in Yarn client/cluster mode, and verified that the caller contexts were written into Yarn RM log and HDFS audit log correctly.
The ways to configure `spark.log.callerContext` property:
- In spark-defaults.conf:
```
spark.log.callerContext infoSpecifiedByUpstreamApp
```
- In app's source code:
```
val spark = SparkSession
.builder
.appName("SparkKMeans")
.config("spark.log.callerContext", "infoSpecifiedByUpstreamApp")
.getOrCreate()
```
When running on Spark Yarn cluster mode, the driver is unable to pass 'spark.log.callerContext' to Yarn client and AM since Yarn client and AM have already started before the driver performs `.config("spark.log.callerContext", "infoSpecifiedByUpstreamApp")`.
The following example shows the command line used to submit a SparkKMeans application and the corresponding records in Yarn RM log and HDFS audit log.
Command:
```
./bin/spark-submit --verbose --executor-cores 3 --num-executors 1 --master yarn --deploy-mode client --class org.apache.spark.examples.SparkKMeans examples/target/original-spark-examples_2.11-2.1.0-SNAPSHOT.jar hdfs://localhost:9000/lr_big.txt 2 5
```
Yarn RM log:
<img width="1440" alt="screen shot 2016-10-19 at 9 12 03 pm" src="https://cloud.githubusercontent.com/assets/8546874/19547050/7d2f278c-9649-11e6-9df8-8d5ff12609f0.png">
HDFS audit log:
<img width="1400" alt="screen shot 2016-10-19 at 10 18 14 pm" src="https://cloud.githubusercontent.com/assets/8546874/19547102/096060ae-964a-11e6-981a-cb28efd5a058.png">
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes#15563 from weiqingy/SPARK-16759.
## What changes were proposed in this pull request?
DIGEST-MD5 mechanism is used for SASL authentication and secure communication. DIGEST-MD5 mechanism supports 3DES, DES, and RC4 ciphers. However, 3DES, DES and RC4 are slow relatively.
AES provide better performance and security by design and is a replacement for 3DES according to NIST. Apache Common Crypto is a cryptographic library optimized with AES-NI, this patch employ Apache Common Crypto as enc/dec backend for SASL authentication and secure channel to improve spark RPC.
## How was this patch tested?
Unit tests and Integration test.
Author: Junjie Chen <junjie.j.chen@intel.com>
Closes#15172 from cjjnjust/shuffle_rpc_encrypt.
## What changes were proposed in this pull request?
1, `**Example**` => `**Examples**`, because more algos use `**Examples**`.
2, delete `### Examples` in `Isotonic regression`, because it's not that special in http://spark.apache.org/docs/latest/ml-classification-regression.html
3, add missing marks for `LDA` and other algos.
## How was this patch tested?
No tests for it only modify doc
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#15783 from zhengruifeng/doc_fix.
## What changes were proposed in this pull request?
This Pull request comprises of the critical bug SPARK-16575 changes. This change rectifies the issue with BinaryFileRDD partition calculations as upon creating an RDD with sc.binaryFiles, the resulting RDD always just consisted of two partitions only.
## How was this patch tested?
The original issue ie. getNumPartitions on binary Files RDD (always having two partitions) was first replicated and then tested upon the changes. Also the unit tests have been checked and passed.
This contribution is my original work and I licence the work to the project under the project's open source license
srowen hvanhovell rxin vanzin skyluc kmader zsxwing datafarmer Please have a look .
Author: fidato <fidato.july13@gmail.com>
Closes#15327 from fidato13/SPARK-16575.
## What changes were proposed in this pull request?
Document that Java 7, Python 2.6, Scala 2.10, Hadoop < 2.6 are deprecated in Spark 2.1.0. This does not actually implement any of the change in SPARK-18138, just peppers the documentation with notices about it.
## How was this patch tested?
Doc build
Author: Sean Owen <sowen@cloudera.com>
Closes#15733 from srowen/SPARK-18138.
## What changes were proposed in this pull request?
This patch uses `{% highlight lang %}...{% endhighlight %}` to highlight code snippets in the `Structured Streaming Kafka010 integration doc` and the `Spark Streaming Kafka010 integration doc`.
This patch consists of two commits:
- the first commit fixes only the leading spaces -- this is large
- the second commit adds the highlight instructions -- this is much simpler and easier to review
## How was this patch tested?
SKIP_API=1 jekyll build
## Screenshots
**Before**
**After**
Author: Liwei Lin <lwlin7@gmail.com>
Closes#15715 from lw-lin/doc-highlight-code-snippet.
## What changes were proposed in this pull request?
- Renamed kbest to numTopFeatures
- Renamed alpha to fpr
- Added missing Since annotations
- Doc cleanups
## How was this patch tested?
Added new standardized unit tests for spark.ml.
Improved existing unit test coverage a bit.
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#15647 from jkbradley/chisqselector-follow-ups.
In SPARK-4761 / #3621 (December 2014) we enabled Kryo serialization by default in the Spark Thrift Server. However, I don't think that the original rationale for doing this still holds now that most Spark SQL serialization is now performed via encoders and our UnsafeRow format.
In addition, the use of Kryo as the default serializer can introduce performance problems because the creation of new KryoSerializer instances is expensive and we haven't performed instance-reuse optimizations in several code paths (including DirectTaskResult deserialization).
Given all of this, I propose to revert back to using JavaSerializer as the default serializer in the Thrift Server.
/cc liancheng
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14906 from JoshRosen/disable-kryo-in-thriftserver.
Mesos 0.23.0 introduces a Fetch Cache feature http://mesos.apache.org/documentation/latest/fetcher/ which allows caching of resources specified in command URIs.
This patch:
- Updates the Mesos shaded protobuf dependency to 0.23.0
- Allows setting `spark.mesos.fetcherCache.enable` to enable the fetch cache for all specified URIs. (URIs must be specified for the setting to have any affect)
- Updates documentation for Mesos configuration with the new setting.
This patch does NOT:
- Allow for per-URI caching configuration. The cache setting is global to ALL URIs for the command.
Author: Charles Allen <charles@allen-net.com>
Closes#13713 from drcrallen/SPARK15994.
## What changes were proposed in this pull request?
This PR merges multiple lines enumerating items in order to remove the redundant spaces following slashes in [Structured Streaming Programming Guide in 2.0.2-rc1](http://people.apache.org/~pwendell/spark-releases/spark-2.0.2-rc1-docs/structured-streaming-programming-guide.html).
- Before: `Scala/ Java/ Python`
- After: `Scala/Java/Python`
## How was this patch tested?
Manual by the followings because this is documentation update.
```
cd docs
SKIP_API=1 jekyll build
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#15686 from dongjoon-hyun/minor_doc_space.
## What changes were proposed in this pull request?
This patch makes RBackend connection timeout configurable by user.
## How was this patch tested?
N/A
Author: Hossein <hossein@databricks.com>
Closes#15471 from falaki/SPARK-17919.
## What changes were proposed in this pull request?
This PR is an enhancement of PR with commit ID:57dc326bd00cf0a49da971e9c573c48ae28acaa2.
NaN is a special type of value which is commonly seen as invalid. But We find that there are certain cases where NaN are also valuable, thus need special handling. We provided user when dealing NaN values with 3 options, to either reserve an extra bucket for NaN values, or remove the NaN values, or report an error, by setting handleNaN "keep", "skip", or "error"(default) respectively.
'''Before:
val bucketizer: Bucketizer = new Bucketizer()
.setInputCol("feature")
.setOutputCol("result")
.setSplits(splits)
'''After:
val bucketizer: Bucketizer = new Bucketizer()
.setInputCol("feature")
.setOutputCol("result")
.setSplits(splits)
.setHandleNaN("keep")
## How was this patch tested?
Tests added in QuantileDiscretizerSuite, BucketizerSuite and DataFrameStatSuite
Signed-off-by: VinceShieh <vincent.xieintel.com>
Author: VinceShieh <vincent.xie@intel.com>
Author: Vincent Xie <vincent.xie@intel.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#15428 from VinceShieh/spark-17219_followup.
## What changes were proposed in this pull request?
maxOffsetsPerTrigger option for rate limiting, proportionally based on volume of different topicpartitions.
## How was this patch tested?
Added unit test
Author: cody koeninger <cody@koeninger.org>
Closes#15527 from koeninger/SPARK-17813.
## What changes were proposed in this pull request?
API and programming guide doc changes for Scala, Python and R.
## How was this patch tested?
manual test
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#15629 from felixcheung/jsondoc.
## What changes were proposed in this pull request?
Currently users can kill stages via the web ui but not jobs directly (jobs are killed if one of their stages is). I've added the ability to kill jobs via the web ui. This code change is based on #4823 by lianhuiwang and updated to work with the latest code matching how stages are currently killed. In general I've copied the kill stage code warning and note comments and all. I also updated applicable tests and documentation.
## How was this patch tested?
Manually tested and dev/run-tests
Author: Alex Bozarth <ajbozart@us.ibm.com>
Author: Lianhui Wang <lianhuiwang09@gmail.com>
Closes#15441 from ajbozarth/spark4411.
## What changes were proposed in this pull request?
Always resolve spark.sql.warehouse.dir as a local path, and as relative to working dir not home dir
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#15382 from srowen/SPARK-17810.
## What changes were proposed in this pull request?
Document `user:password` syntax as possible means of specifying credentials for password-protected `--repositories`
## How was this patch tested?
Doc build
Author: Sean Owen <sowen@cloudera.com>
Closes#15584 from srowen/SPARK-17898.
## What changes were proposed in this pull request?
Minor doc change to mention kafka configuration for larger spark batches.
## How was this patch tested?
Doc change only, confirmed via jekyll.
The configuration issue was discussed / confirmed with users on the mailing list.
Author: cody koeninger <cody@koeninger.org>
Closes#15570 from koeninger/kafka-doc-heartbeat.
## What changes were proposed in this pull request?
startingOffsets takes specific per-topicpartition offsets as a json argument, usable with any consumer strategy
assign with specific topicpartitions as a consumer strategy
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#15504 from koeninger/SPARK-17812.
## What changes were proposed in this pull request?
Add crossJoin and do not default to cross join if joinExpr is left out
## How was this patch tested?
unit test
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#15559 from felixcheung/rcrossjoin.
## What changes were proposed in this pull request?
Update docs to not suggest to package Spark before running tests.
## How was this patch tested?
Not creating a JIRA since this pretty small. We haven't had the need to run mvn package before mvn test since 1.6 at least, or so I am told. So, updating the docs to not be misguiding.
Author: Mark Grover <mark@apache.org>
Closes#15572 from markgrover/doc_update.
## What changes were proposed in this pull request?
`SerializationUtils.clone()` of commons-lang3 (<3.5) has a bug that breaks thread safety, which gets stack sometimes caused by race condition of initializing hash map.
See https://issues.apache.org/jira/browse/LANG-1251.
## How was this patch tested?
Existing tests.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#15548 from ueshin/issues/SPARK-17985.
## What changes were proposed in this pull request?
In http://spark.apache.org/docs/latest/sql-programming-guide.html, Section "Untyped Dataset Operations (aka DataFrame Operations)"
Link to R DataFrame doesn't work that return
The requested URL /docs/latest/api/R/DataFrame.html was not found on this server.
Correct link is SparkDataFrame.html for spark 2.0
## How was this patch tested?
Manual checked.
Author: Tommy YU <tummyyu@163.com>
Closes#15543 from Wenpei/spark-18001.
This reverts commit bfe7885aee.
The commit caused build failures on Hadoop 2.2 profile:
```
[error] /scratch/rxin/spark/core/src/main/scala/org/apache/spark/util/Utils.scala:1489: value read is not a member of object org.apache.commons.io.IOUtils
[error] var numBytes = IOUtils.read(gzInputStream, buf)
[error] ^
[error] /scratch/rxin/spark/core/src/main/scala/org/apache/spark/util/Utils.scala:1492: value read is not a member of object org.apache.commons.io.IOUtils
[error] numBytes = IOUtils.read(gzInputStream, buf)
[error] ^
```
## What changes were proposed in this pull request?
Add more built-in sources in sql-programming-guide.md.
## How was this patch tested?
Manually.
Author: Weiqing Yang <yangweiqing001@gmail.com>
Closes#15522 from weiqingy/dsDoc.
## What changes were proposed in this pull request?
`SerializationUtils.clone()` of commons-lang3 (<3.5) has a bug that breaks thread safety, which gets stack sometimes caused by race condition of initializing hash map.
See https://issues.apache.org/jira/browse/LANG-1251.
## How was this patch tested?
Existing tests.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#15525 from ueshin/issues/SPARK-17985.
## What changes were proposed in this pull request?
This PR adds support for executor log compression.
## How was this patch tested?
Unit tests
cc: yhuai tdas mengxr
Author: Yu Peng <loneknightpy@gmail.com>
Closes#15285 from loneknightpy/compress-executor-log.
This reverts commit ed14633414.
The patch merged had obvious quality and documentation issue. The idea is useful, and we should work towards improving its quality and merging it in again.
## What changes were proposed in this pull request?
Restructure the code and implement two new task assigner.
PackedAssigner: try to allocate tasks to the executors with least available cores, so that spark can release reserved executors when dynamic allocation is enabled.
BalancedAssigner: try to allocate tasks to the executors with more available cores in order to balance the workload across all executors.
By default, the original round robin assigner is used.
We test a pipeline, and new PackedAssigner save around 45% regarding the reserved cpu and memory with dynamic allocation enabled.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Both unit test in TaskSchedulerImplSuite and manual tests in production pipeline.
Author: Zhan Zhang <zhanzhang@fb.com>
Closes#15218 from zhzhan/packed-scheduler.
## What changes were proposed in this pull request?
This is a step along the way to SPARK-8425.
To enable incremental review, the first step proposed here is to expand the blacklisting within tasksets. In particular, this will enable blacklisting for
* (task, executor) pairs (this already exists via an undocumented config)
* (task, node)
* (taskset, executor)
* (taskset, node)
Adding (task, node) is critical to making spark fault-tolerant of one-bad disk in a cluster, without requiring careful tuning of "spark.task.maxFailures". The other additions are also important to avoid many misleading task failures and long scheduling delays when there is one bad node on a large cluster.
Note that some of the code changes here aren't really required for just this -- they put pieces in place for SPARK-8425 even though they are not used yet (eg. the `BlacklistTracker` helper is a little out of place, `TaskSetBlacklist` holds onto a little more info than it needs to for just this change, and `ExecutorFailuresInTaskSet` is more complex than it needs to be).
## How was this patch tested?
Added unit tests, run tests via jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Author: mwws <wei.mao@intel.com>
Closes#15249 from squito/taskset_blacklist_only.
## What changes were proposed in this pull request?
Documentation fix to make it clear that reusing group id for different streams is super duper bad, just like it is with the underlying Kafka consumer.
## How was this patch tested?
I built jekyll doc and made sure it looked ok.
Author: cody koeninger <cody@koeninger.org>
Closes#15442 from koeninger/SPARK-17853.
## What changes were proposed in this pull request?
In `programming-guide.md`, the url which links to `AccumulatorV2` says `api/scala/index.html#org.apache.spark.AccumulatorV2` but `api/scala/index.html#org.apache.spark.util.AccumulatorV2` is correct.
## How was this patch tested?
manual test.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#15439 from sarutak/SPARK-17880.
Couple of mvn build examples use `-Dhadoop.version=VERSION` instead of actual version number
Author: Alexander Pivovarov <apivovarov@gmail.com>
Closes#15440 from apivovarov/patch-1.
## What changes were proposed in this pull request?
This PR proposes to fix arbitrary usages among `Map[String, String]`, `Properties` and `JDBCOptions` instances for options in `execution/jdbc` package and make the connection properties exclude Spark-only options.
This PR includes some changes as below:
- Unify `Map[String, String]`, `Properties` and `JDBCOptions` in `execution/jdbc` package to `JDBCOptions`.
- Move `batchsize`, `fetchszie`, `driver` and `isolationlevel` options into `JDBCOptions` instance.
- Document `batchSize` and `isolationlevel` with marking both read-only options and write-only options. Also, this includes minor types and detailed explanation for some statements such as url.
- Throw exceptions fast by checking arguments first rather than in execution time (e.g. for `fetchsize`).
- Exclude Spark-only options in connection properties.
## How was this patch tested?
Existing tests should cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#15292 from HyukjinKwon/SPARK-17719.
## What changes were proposed in this pull request?
Enable GPU resources to be used when running coarse grain mode with Mesos.
## How was this patch tested?
Manual test with GPU.
Author: Timothy Chen <tnachen@gmail.com>
Closes#14644 from tnachen/gpu_mesos.
## What changes were proposed in this pull request?
Global temporary view is a cross-session temporary view, which means it's shared among all sessions. Its lifetime is the lifetime of the Spark application, i.e. it will be automatically dropped when the application terminates. It's tied to a system preserved database `global_temp`(configurable via SparkConf), and we must use the qualified name to refer a global temp view, e.g. SELECT * FROM global_temp.view1.
changes for `SessionCatalog`:
1. add a new field `gloabalTempViews: GlobalTempViewManager`, to access the shared global temp views, and the global temp db name.
2. `createDatabase` will fail if users wanna create `global_temp`, which is system preserved.
3. `setCurrentDatabase` will fail if users wanna set `global_temp`, which is system preserved.
4. add `createGlobalTempView`, which is used in `CreateViewCommand` to create global temp views.
5. add `dropGlobalTempView`, which is used in `CatalogImpl` to drop global temp view.
6. add `alterTempViewDefinition`, which is used in `AlterViewAsCommand` to update the view definition for local/global temp views.
7. `renameTable`/`dropTable`/`isTemporaryTable`/`lookupRelation`/`getTempViewOrPermanentTableMetadata`/`refreshTable` will handle global temp views.
changes for SQL commands:
1. `CreateViewCommand`/`AlterViewAsCommand` is updated to support global temp views
2. `ShowTablesCommand` outputs a new column `database`, which is used to distinguish global and local temp views.
3. other commands can also handle global temp views if they call `SessionCatalog` APIs which accepts global temp views, e.g. `DropTableCommand`, `AlterTableRenameCommand`, `ShowColumnsCommand`, etc.
changes for other public API
1. add a new method `dropGlobalTempView` in `Catalog`
2. `Catalog.findTable` can find global temp view
3. add a new method `createGlobalTempView` in `Dataset`
## How was this patch tested?
new tests in `SQLViewSuite`
Author: Wenchen Fan <wenchen@databricks.com>
Closes#14897 from cloud-fan/global-temp-view.
## What changes were proposed in this pull request?
This expands calls to Jetty's simple `ServerConnector` constructor to explicitly specify a `ScheduledExecutorScheduler` that makes daemon threads. It should otherwise result in exactly the same configuration, because the other args are copied from the constructor that is currently called.
(I'm not sure we should change the Hive Thriftserver impl, but I did anyway.)
This also adds `sc.stop()` to the quick start guide example.
## How was this patch tested?
Existing tests; _pending_ at least manual verification of the fix.
Author: Sean Owen <sowen@cloudera.com>
Closes#15381 from srowen/SPARK-17707.
## What changes were proposed in this pull request?
This PR adds a new project ` external/kafka-0-10-sql` for Structured Streaming Kafka source.
It's based on the design doc: https://docs.google.com/document/d/19t2rWe51x7tq2e5AOfrsM9qb8_m7BRuv9fel9i0PqR8/edit?usp=sharing
tdas did most of work and part of them was inspired by koeninger's work.
### Introduction
The Kafka source is a structured streaming data source to poll data from Kafka. The schema of reading data is as follows:
Column | Type
---- | ----
key | binary
value | binary
topic | string
partition | int
offset | long
timestamp | long
timestampType | int
The source can deal with deleting topics. However, the user should make sure there is no Spark job processing the data when deleting a topic.
### Configuration
The user can use `DataStreamReader.option` to set the following configurations.
Kafka Source's options | value | default | meaning
------ | ------- | ------ | -----
startingOffset | ["earliest", "latest"] | "latest" | The start point when a query is started, either "earliest" which is from the earliest offset, or "latest" which is just from the latest offset. Note: This only applies when a new Streaming query is started, and that resuming will always pick up from where the query left off.
failOnDataLost | [true, false] | true | Whether to fail the query when it's possible that data is lost (e.g., topics are deleted, or offsets are out of range). This may be a false alarm. You can disable it when it doesn't work as you expected.
subscribe | A comma-separated list of topics | (none) | The topic list to subscribe. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
subscribePattern | Java regex string | (none) | The pattern used to subscribe the topic. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
kafka.consumer.poll.timeoutMs | long | 512 | The timeout in milliseconds to poll data from Kafka in executors
fetchOffset.numRetries | int | 3 | Number of times to retry before giving up fatch Kafka latest offsets.
fetchOffset.retryIntervalMs | long | 10 | milliseconds to wait before retrying to fetch Kafka offsets
Kafka's own configurations can be set via `DataStreamReader.option` with `kafka.` prefix, e.g, `stream.option("kafka.bootstrap.servers", "host:port")`
### Usage
* Subscribe to 1 topic
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1")
.load()
```
* Subscribe to multiple topics
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1,topic2")
.load()
```
* Subscribe to a pattern
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribePattern", "topic.*")
.load()
```
## How was this patch tested?
The new unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Shixiong Zhu <zsxwing@gmail.com>
Author: cody koeninger <cody@koeninger.org>
Closes#15102 from zsxwing/kafka-source.
## What changes were proposed in this pull request?
Updates user guide to reflect that LogisticRegression now supports multiclass. Also adds new examples to show multiclass training.
## How was this patch tested?
Ran locally using spark-submit, run-example, and copy/paste from user guide into shells. Generated docs and verified correct output.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#15349 from sethah/SPARK-17239.
## What changes were proposed in this pull request?
Move note about labels being +1/-1 in formulation only to be just under the table of formulations.
## How was this patch tested?
Doc build
Author: Sean Owen <sowen@cloudera.com>
Closes#15330 from srowen/SPARK-17718.
## What changes were proposed in this pull request?
To build R docs (which are built when R tests are run), users need to install pandoc and rmarkdown. This was done for Jenkins in ~~[SPARK-17420](https://issues.apache.org/jira/browse/SPARK-17420)~~
… pandoc]
Author: Jagadeesan <as2@us.ibm.com>
Closes#15309 from jagadeesanas2/SPARK-17736.
## What changes were proposed in this pull request?
This PR aims to make the doc up-to-date. The documentation is generally correct, but after https://issues.apache.org/jira/browse/SPARK-13926, Spark starts to choose Kyro as a default serialization library during shuffling of simple types, arrays of simple types, or string type.
## How was this patch tested?
This is a documentation update.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#15315 from dongjoon-hyun/SPARK-DOC-SERIALIZER.
## What changes were proposed in this pull request?
`FsHistoryProviderSuite` fails if `root` user runs it. The test case **SPARK-3697: ignore directories that cannot be read** depends on `setReadable(false, false)` to make test data files and expects the number of accessible files is 1. But, `root` can access all files, so it returns 2.
This PR adds the assumption explicitly on doc. `building-spark.md`.
## How was this patch tested?
This is a documentation change.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#15291 from dongjoon-hyun/SPARK-17412.
## What changes were proposed in this pull request?
The discussion of the interaction of Accumulators and Broadcast Variables should logically follow the discussion on Checkpointing. As currently written, this section discusses Checkpointing before it is formally introduced. To remedy this:
- Rename this section to "Accumulators, Broadcast Variables, and Checkpoints", and
- Move this section after "Checkpointing".
## How was this patch tested?
Testing: ran
$ SKIP_API=1 jekyll build
, and verified changes in a Web browser pointed at docs/_site/index.html.
Author: José Hiram Soltren <jose@cloudera.com>
Closes#15281 from jsoltren/doc-changes.
## What changes were proposed in this pull request?
This pr is just to fix the document of `spark-kinesis-integration`.
Since `SPARK-17418` prevented all the kinesis stuffs (including kinesis example code)
from publishing, `bin/run-example streaming.KinesisWordCountASL` and `bin/run-example streaming.JavaKinesisWordCountASL` does not work.
Instead, it fetches the kinesis jar from the Spark Package.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#15260 from maropu/DocFixKinesis.
Corrected a link to the configuration.html page, it was pointing to a page that does not exist (configurations.html).
Documentation change, verified in preview.
Author: Andrew Mills <ammills01@users.noreply.github.com>
Closes#15244 from ammills01/master.
## What changes were proposed in this pull request?
When reading file stream with non-globbing path, the results return data with all `null`s for the
partitioned columns. E.g.,
case class A(id: Int, value: Int)
val data = spark.createDataset(Seq(
A(1, 1),
A(2, 2),
A(2, 3))
)
val url = "/tmp/test"
data.write.partitionBy("id").parquet(url)
spark.read.parquet(url).show
+-----+---+
|value| id|
+-----+---+
| 2| 2|
| 3| 2|
| 1| 1|
+-----+---+
val s = spark.readStream.schema(spark.read.load(url).schema).parquet(url)
s.writeStream.queryName("test").format("memory").start()
sql("SELECT * FROM test").show
+-----+----+
|value| id|
+-----+----+
| 2|null|
| 3|null|
| 1|null|
+-----+----+
## How was this patch tested?
Jenkins tests.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#14803 from viirya/filestreamsource-option.
## What changes were proposed in this pull request?
This change modifies the implementation of DataFrameWriter.save such that it works with jdbc, and the call to jdbc merely delegates to save.
## How was this patch tested?
This was tested via unit tests in the JDBCWriteSuite, of which I added one new test to cover this scenario.
## Additional details
rxin This seems to have been most recently touched by you and was also commented on in the JIRA.
This contribution is my original work and I license the work to the project under the project's open source license.
Author: Justin Pihony <justin.pihony@gmail.com>
Author: Justin Pihony <justin.pihony@typesafe.com>
Closes#12601 from JustinPihony/jdbc_reconciliation.
## What changes were proposed in this pull request?
Spark will add sparkr.zip to archive only when it is yarn mode (SparkSubmit.scala).
```
if (args.isR && clusterManager == YARN) {
val sparkRPackagePath = RUtils.localSparkRPackagePath
if (sparkRPackagePath.isEmpty) {
printErrorAndExit("SPARK_HOME does not exist for R application in YARN mode.")
}
val sparkRPackageFile = new File(sparkRPackagePath.get, SPARKR_PACKAGE_ARCHIVE)
if (!sparkRPackageFile.exists()) {
printErrorAndExit(s"$SPARKR_PACKAGE_ARCHIVE does not exist for R application in YARN mode.")
}
val sparkRPackageURI = Utils.resolveURI(sparkRPackageFile.getAbsolutePath).toString
// Distribute the SparkR package.
// Assigns a symbol link name "sparkr" to the shipped package.
args.archives = mergeFileLists(args.archives, sparkRPackageURI + "#sparkr")
// Distribute the R package archive containing all the built R packages.
if (!RUtils.rPackages.isEmpty) {
val rPackageFile =
RPackageUtils.zipRLibraries(new File(RUtils.rPackages.get), R_PACKAGE_ARCHIVE)
if (!rPackageFile.exists()) {
printErrorAndExit("Failed to zip all the built R packages.")
}
val rPackageURI = Utils.resolveURI(rPackageFile.getAbsolutePath).toString
// Assigns a symbol link name "rpkg" to the shipped package.
args.archives = mergeFileLists(args.archives, rPackageURI + "#rpkg")
}
}
```
So it is necessary to pass spark.master from R process to JVM. Otherwise sparkr.zip won't be distributed to executor. Besides that I also pass spark.yarn.keytab/spark.yarn.principal to spark side, because JVM process need them to access secured cluster.
## How was this patch tested?
Verify it manually in R Studio using the following code.
```
Sys.setenv(SPARK_HOME="/Users/jzhang/github/spark")
.libPaths(c(file.path(Sys.getenv(), "R", "lib"), .libPaths()))
library(SparkR)
sparkR.session(master="yarn-client", sparkConfig = list(spark.executor.instances="1"))
df <- as.DataFrame(mtcars)
head(df)
```
…
Author: Jeff Zhang <zjffdu@apache.org>
Closes#14784 from zjffdu/SPARK-17210.
## What changes were proposed in this pull request?
Modified the documentation to clarify that `build/mvn` and `pom.xml` always add Java 7-specific parameters to `MAVEN_OPTS`, and that developers can safely ignore warnings about `-XX:MaxPermSize` that may result from compiling or running tests with Java 8.
## How was this patch tested?
Rebuilt HTML documentation, made sure that building-spark.html displays correctly in a browser.
Author: frreiss <frreiss@us.ibm.com>
Closes#15005 from frreiss/fred-17421a.
The goal of this feature is to allow the Spark driver to run in an
isolated environment, such as a docker container, and be able to use
the host's port forwarding mechanism to be able to accept connections
from the outside world.
The change is restricted to the driver: there is no support for achieving
the same thing on executors (or the YARN AM for that matter). Those still
need full access to the outside world so that, for example, connections
can be made to an executor's block manager.
The core of the change is simple: add a new configuration that tells what's
the address the driver should bind to, which can be different than the address
it advertises to executors (spark.driver.host). Everything else is plumbing
the new configuration where it's needed.
To use the feature, the host starting the container needs to set up the
driver's port range to fall into a range that is being forwarded; this
required the block manager port to need a special configuration just for
the driver, which falls back to the existing spark.blockManager.port when
not set. This way, users can modify the driver settings without affecting
the executors; it would theoretically be nice to also have different
retry counts for driver and executors, but given that docker (at least)
allows forwarding port ranges, we can probably live without that for now.
Because of the nature of the feature it's kinda hard to add unit tests;
I just added a simple one to make sure the configuration works.
This was tested with a docker image running spark-shell with the following
command:
docker blah blah blah \
-p 38000-38100:38000-38100 \
[image] \
spark-shell \
--num-executors 3 \
--conf spark.shuffle.service.enabled=false \
--conf spark.dynamicAllocation.enabled=false \
--conf spark.driver.host=[host's address] \
--conf spark.driver.port=38000 \
--conf spark.driver.blockManager.port=38020 \
--conf spark.ui.port=38040
Running on YARN; verified the driver works, executors start up and listen
on ephemeral ports (instead of using the driver's config), and that caching
and shuffling (without the shuffle service) works. Clicked through the UI
to make sure all pages (including executor thread dumps) worked. Also tested
apps without docker, and ran unit tests.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#15120 from vanzin/SPARK-4563.
## What changes were proposed in this pull request?
This PR fixes an issue when Bucketizer is called to handle a dataset containing NaN value.
Sometimes, null value might also be useful to users, so in these cases, Bucketizer should
reserve one extra bucket for NaN values, instead of throwing an illegal exception.
Before:
```
Bucketizer.transform on NaN value threw an illegal exception.
```
After:
```
NaN values will be grouped in an extra bucket.
```
## How was this patch tested?
New test cases added in `BucketizerSuite`.
Signed-off-by: VinceShieh <vincent.xieintel.com>
Author: VinceShieh <vincent.xie@intel.com>
Closes#14858 from VinceShieh/spark-17219.
## What changes were proposed in this pull request?
Point references to spark-packages.org to https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects
This will be accompanied by a parallel change to the spark-website repo, and additional changes to this wiki.
## How was this patch tested?
Jenkins tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#15075 from srowen/SPARK-17445.
## What changes were proposed in this pull request?
The relation between spark.network.timeout and spark.executor.heartbeatInterval should be mentioned in the document.
… network timeout]
Author: Jagadeesan <as2@us.ibm.com>
Closes#15042 from jagadeesanas2/SPARK-17449.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
Streaming doc correction.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: Satendra Kumar <satendra@knoldus.com>
Closes#14996 from satendrakumar06/patch-1.
## What changes were proposed in this pull request?
This pull request adds the functionality to enable accessing worker and application UI through master UI itself. Thus helps in accessing SparkUI when running spark cluster in closed networks e.g. Kubernetes. Cluster admin needs to expose only spark master UI and rest of the UIs can be in the private network, master UI will reverse proxy the connection request to corresponding resource. It adds the path for workers/application UIs as
WorkerUI: <http/https>://master-publicIP:<port>/target/workerID/
ApplicationUI: <http/https>://master-publicIP:<port>/target/appID/
This makes it easy for users to easily protect the Spark master cluster access by putting some reverse proxy e.g. https://github.com/bitly/oauth2_proxy
## How was this patch tested?
The functionality has been tested manually and there is a unit test too for testing access to worker UI with reverse proxy address.
pwendell bomeng BryanCutler can you please review it, thanks.
Author: Gurvinder Singh <gurvinder.singh@uninett.no>
Closes#13950 from gurvindersingh/rproxy.
After change [SPARK-16405](https://github.com/apache/spark/pull/14080), we need to update docs by adding shuffle service metrics entry in currently supporting metrics list.
Author: Yangyang Liu <yangyangliu@fb.com>
Closes#14254 from lovexi/yangyang-monitoring-doc.
## What changes were proposed in this pull request?
Avoid allocating some 0-length arrays, esp. in UTF8String, and by using Array.empty in Scala over Array[T]()
## How was this patch tested?
Jenkins
Author: Sean Owen <sowen@cloudera.com>
Closes#14895 from srowen/SPARK-17331.
## What changes were proposed in this pull request?
Allow user to set sparkr shell command through --conf spark.r.shell.command
## How was this patch tested?
Unit test is added and also verify it manually through
```
bin/sparkr --master yarn-client --conf spark.r.shell.command=/usr/local/bin/R
```
Author: Jeff Zhang <zjffdu@apache.org>
Closes#14744 from zjffdu/SPARK-17178.
## What changes were proposed in this pull request?
With the new History Server the summary page loads the application list via the the REST API, this makes it very slow to impossible to load with large (10K+) application history. This pr fixes this by adding the `spark.history.ui.maxApplications` conf to limit the number of applications the History Server displays. This is accomplished using a new optional `limit` param for the `applications` api. (Note this only applies to what the summary page displays, all the Application UI's are still accessible if the user knows the App ID and goes to the Application UI directly.)
I've also added a new test for the `limit` param in `HistoryServerSuite.scala`
## How was this patch tested?
Manual testing and dev/run-tests
Author: Alex Bozarth <ajbozart@us.ibm.com>
Closes#14835 from ajbozarth/spark17243.
This patch is using Apache Commons Crypto library to enable shuffle encryption support.
Author: Ferdinand Xu <cheng.a.xu@intel.com>
Author: kellyzly <kellyzly@126.com>
Closes#8880 from winningsix/SPARK-10771.
## What changes were proposed in this pull request?
Fix minor typos python example code in streaming programming guide
## How was this patch tested?
N/A
Author: Dmitriy Sokolov <silentsokolov@gmail.com>
Closes#14805 from silentsokolov/fix-typos.
## What changes were proposed in this pull request?
Allow centering / mean scaling of sparse vectors in StandardScaler, if requested. This is for compatibility with `VectorAssembler` in common usages.
## How was this patch tested?
Jenkins tests, including new caes to reflect the new behavior.
Author: Sean Owen <sowen@cloudera.com>
Closes#14663 from srowen/SPARK-17001.
## What changes were proposed in this pull request?
Move Mesos code into a mvn module
## How was this patch tested?
unit tests
manually submitting a client mode and cluster mode job
spark/mesos integration test suite
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14637 from mgummelt/mesos-module.
## What changes were proposed in this pull request?
Updated links of external dstream projects.
## How was this patch tested?
Just document changes.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#14814 from zsxwing/dstream-link.
## What changes were proposed in this pull request?
Based on #12990 by tankkyo
Since the History Server currently loads all application's data it can OOM if too many applications have a significant task count. `spark.ui.trimTasks` (default: false) can be set to true to trim tasks by `spark.ui.retainedTasks` (default: 10000)
(This is a "quick fix" to help those running into the problem until a update of how the history server loads app data can be done)
## How was this patch tested?
Manual testing and dev/run-tests
Author: Alex Bozarth <ajbozart@us.ibm.com>
Closes#14673 from ajbozarth/spark15083.
## What changes were proposed in this pull request?
Collect GC discussion in one section, and documenting findings about G1 GC heap region size.
## How was this patch tested?
Jekyll doc build
Author: Sean Owen <sowen@cloudera.com>
Closes#14732 from srowen/SPARK-16320.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
This is the document for previous JDBC Writer options.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Unit test has been added in previous PR.
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: GraceH <jhuang1@paypal.com>
Closes#14683 from GraceH/jdbc_options.
## What changes were proposed in this pull request?
`spark.ssl.enabled`=true, but failing to set `spark.ssl.protocol` will fail and throw meaningless exception. `spark.ssl.protocol` is required when `spark.ssl.enabled`.
Improvement: require `spark.ssl.protocol` when initializing SSLContext, otherwise throws an exception to indicate that.
Remove the OrElse("default").
Document this requirement in configure.md
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Manual tests:
Build document and check document
Configure `spark.ssl.enabled` only, it throws exception below:
6/08/16 16:04:37 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(mwang); groups with view permissions: Set(); users with modify permissions: Set(mwang); groups with modify permissions: Set()
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: spark.ssl.protocol is required when enabling SSL connections.
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:285)
at org.apache.spark.deploy.master.Master$.startRpcEnvAndEndpoint(Master.scala:1026)
at org.apache.spark.deploy.master.Master$.main(Master.scala:1011)
at org.apache.spark.deploy.master.Master.main(Master.scala)
Configure `spark.ssl.protocol` and `spark.ssl.protocol`
It works fine.
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes#14674 from wangmiao1981/ssl.
## What changes were proposed in this pull request?
- adds documentation for https://issues.apache.org/jira/browse/SPARK-11714
## How was this patch tested?
Doc no test needed.
Author: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Closes#14667 from skonto/add_doc.
## What changes were proposed in this pull request?
Remove the api doc link for mapReduceTriplets operator because in latest api they are remove so when user link to that api they will not get mapReduceTriplets there so its more good to remove than confuse the user.
## How was this patch tested?
Run all the test cases
Author: sandy <phalodi@gmail.com>
Closes#14669 from phalodi/SPARK-17089.
## What changes were proposed in this pull request?
As README.md file is updated over time. Some code snippet outputs are not correct based on new README.md file. For example:
```
scala> textFile.count()
res0: Long = 126
```
should be
```
scala> textFile.count()
res0: Long = 99
```
This pr is to add comments to point out this problem so that new spark learners have a correct reference.
Also, fixed a samll bug, inside current documentation, the outputs of linesWithSpark.count() without and with cache are different (one is 15 and the other is 19)
```
scala> val linesWithSpark = textFile.filter(line => line.contains("Spark"))
linesWithSpark: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[2] at filter at <console>:27
scala> textFile.filter(line => line.contains("Spark")).count() // How many lines contain "Spark"?
res3: Long = 15
...
scala> linesWithSpark.cache()
res7: linesWithSpark.type = MapPartitionsRDD[2] at filter at <console>:27
scala> linesWithSpark.count()
res8: Long = 19
```
## How was this patch tested?
manual test: run `$ SKIP_API=1 jekyll serve --watch`
Author: linbojin <linbojin203@gmail.com>
Closes#14645 from linbojin/quick-start-documentation.
## What changes were proposed in this pull request?
When documentation is built is should reference examples from the same build. There are times when the docs have links that point to files in the GitHub head which may not be valid on the current release. Changed that in URLs to make them point to the right tag in git using ```SPARK_VERSION_SHORT```
…from its own release version] [Streaming programming guide]
Author: Jagadeesan <as2@us.ibm.com>
Closes#14596 from jagadeesanas2/SPARK-12370.
## What changes were proposed in this pull request?
The configuration doc lost the config option `spark.ui.enabled` (default value is `true`)
I think this option is important because many cases we would like to turn it off.
so I add it.
## How was this patch tested?
N/A
Author: WeichenXu <WeichenXu123@outlook.com>
Closes#14604 from WeichenXu123/add_doc_param_spark_ui_enabled.
Before this PR, user have to export environment variable to specify the python of driver & executor which is not so convenient for users. This PR is trying to allow user to specify python through configuration "--pyspark-driver-python" & "--pyspark-executor-python"
Manually test in local & yarn mode for pyspark-shell and pyspark batch mode.
Author: Jeff Zhang <zjffdu@apache.org>
Closes#13146 from zjffdu/SPARK-13081.
## What changes were proposed in this pull request?
Originally this PR was based on #14491 but I realised that fixing examples are more sensible rather than comments.
This PR fixes three things below:
- Fix two wrong examples in `structured-streaming-programming-guide.md`. Loading via `read.load(..)` without `as` will be `Dataset<Row>` not `Dataset<String>` in Java.
- Fix indentation across `structured-streaming-programming-guide.md`. Python has 4 spaces and Scala and Java have double spaces. These are inconsistent across the examples.
- Fix `StructuredNetworkWordCountWindowed` and `StructuredNetworkWordCount` in Java and Scala to initially load `DataFrame` and `Dataset<Row>` to be consistent with the comments and some examples in `structured-streaming-programming-guide.md` and to match Scala and Java to Python one (Python one loads it as `DataFrame` initially).
## How was this patch tested?
N/A
Closes https://github.com/apache/spark/pull/14491
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Ganesh Chand <ganeshchand@Ganeshs-MacBook-Pro-2.local>
Closes#14564 from HyukjinKwon/SPARK-16886.
Docs adjustment to:
- link to other relevant section of docs
- correct statement about the only value when actually other values are supported
Author: Andrew Ash <andrew@andrewash.com>
Closes#14581 from ash211/patch-10.
## What changes were proposed in this pull request?
change the remain percent to right one.
## How was this patch tested?
Manual review
Author: Tao Wang <wangtao111@huawei.com>
Closes#14591 from WangTaoTheTonic/patch-1.
## What changes were proposed in this pull request?
Add a configurable token manager for Spark on running on yarn.
### Current Problems ###
1. Supported token provider is hard-coded, currently only hdfs, hbase and hive are supported and it is impossible for user to add new token provider without code changes.
2. Also this problem exits in timely token renewer and updater.
### Changes In This Proposal ###
In this proposal, to address the problems mentioned above and make the current code more cleaner and easier to understand, mainly has 3 changes:
1. Abstract a `ServiceTokenProvider` as well as `ServiceTokenRenewable` interface for token provider. Each service wants to communicate with Spark through token way needs to implement this interface.
2. Provide a `ConfigurableTokenManager` to manage all the register token providers, also token renewer and updater. Also this class offers the API for other modules to obtain tokens, get renewal interval and so on.
3. Implement 3 built-in token providers `HDFSTokenProvider`, `HiveTokenProvider` and `HBaseTokenProvider` to keep the same semantics as supported today. Whether to load in these built-in token providers is controlled by configuration "spark.yarn.security.tokens.${service}.enabled", by default for all the built-in token providers are loaded.
### Behavior Changes ###
For the end user there's no behavior change, we still use the same configuration `spark.yarn.security.tokens.${service}.enabled` to decide which token provider is enabled (hbase or hive).
For user implemented token provider (assume the name of token provider is "test") needs to add into this class should have two configurations:
1. `spark.yarn.security.tokens.test.enabled` to true
2. `spark.yarn.security.tokens.test.class` to the full qualified class name.
So we still keep the same semantics as current code while add one new configuration.
### Current Status ###
- [x] token provider interface and management framework.
- [x] implement built-in token providers (hdfs, hbase, hive).
- [x] Coverage of unit test.
- [x] Integrated test with security cluster.
## How was this patch tested?
Unit test and integrated test.
Please suggest and review, any comment is greatly appreciated.
Author: jerryshao <sshao@hortonworks.com>
Closes#14065 from jerryshao/SPARK-16342.
## What changes were proposed in this pull request?
- enable setting default properties for all jobs submitted through the dispatcher [SPARK-16927]
- remove duplication of conf vars on cluster submitted jobs [SPARK-16923] (this is a small fix, so I'm including in the same PR)
## How was this patch tested?
mesos/spark integration test suite
manual testing
Author: Timothy Chen <tnachen@gmail.com>
Closes#14511 from mgummelt/override-props.
## What changes were proposed in this pull request?
This patch introduces a new configuration, `spark.deploy.maxExecutorRetries`, to let users configure an obscure behavior in the standalone master where the master will kill Spark applications which have experienced too many back-to-back executor failures. The current setting is a hardcoded constant (10); this patch replaces that with a new cluster-wide configuration.
**Background:** This application-killing was added in 6b5980da79 (from September 2012) and I believe that it was designed to prevent a faulty application whose executors could never launch from DOS'ing the Spark cluster via an infinite series of executor launch attempts. In a subsequent patch (#1360), this feature was refined to prevent applications which have running executors from being killed by this code path.
**Motivation for making this configurable:** Previously, if a Spark Standalone application experienced more than `ApplicationState.MAX_NUM_RETRY` executor failures and was left with no executors running then the Spark master would kill that application, but this behavior is problematic in environments where the Spark executors run on unstable infrastructure and can all simultaneously die. For instance, if your Spark driver runs on an on-demand EC2 instance while all workers run on ephemeral spot instances then it's possible for all executors to die at the same time while the driver stays alive. In this case, it may be desirable to keep the Spark application alive so that it can recover once new workers and executors are available. In order to accommodate this use-case, this patch modifies the Master to never kill faulty applications if `spark.deploy.maxExecutorRetries` is negative.
I'd like to merge this patch into master, branch-2.0, and branch-1.6.
## How was this patch tested?
I tested this manually using `spark-shell` and `local-cluster` mode. This is a tricky feature to unit test and historically this code has not changed very often, so I'd prefer to skip the additional effort of adding a testing framework and would rather rely on manual tests and review for now.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14544 from JoshRosen/add-setting-for-max-executor-failures.
## What changes were proposed in this pull request?
Links the Spark Mesos Dispatcher UI to the history server UI
- adds spark.mesos.dispatcher.historyServer.url
- explicitly generates frameworkIDs for the launched drivers, so the dispatcher knows how to correlate drivers and frameworkIDs
## How was this patch tested?
manual testing
Author: Michael Gummelt <mgummelt@mesosphere.io>
Author: Sergiusz Urbaniak <sur@mesosphere.io>
Closes#14414 from mgummelt/history-server.
## What changes were proposed in this pull request?
Fix the broken links in the programming guide of the Graphx Migration and understanding closures
## How was this patch tested?
By running the test cases and checking the links.
Author: Shivansh <shiv4nsh@gmail.com>
Closes#14503 from shiv4nsh/SPARK-16911.
## What changes were proposed in this pull request?
default value for spark.sql.broadcastTimeout is 300s. and this property do not show in any docs of spark. so add "spark.sql.broadcastTimeout" into docs/sql-programming-guide.md to help people to how to fix this timeout error when it happenned
## How was this patch tested?
not need
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
…ide.md
JIRA_ID:SPARK-16870
Description:default value for spark.sql.broadcastTimeout is 300s. and this property do not show in any docs of spark. so add "spark.sql.broadcastTimeout" into docs/sql-programming-guide.md to help people to how to fix this timeout error when it happenned
Test:done
Author: keliang <keliang@cmss.chinamobile.com>
Closes#14477 from biglobster/keliang.
## What changes were proposed in this pull request?
In the programming guide, the accumulator section mixes up both the old and new APIs causing it to be confusing. This is not necessary for Scala, so all references to the old API are removed. For Java, it is somewhat fixed up except for the example of a custom accumulator because I don't think an API exists yet. Python has not currently implemented the new API.
## How was this patch tested?
built doc locally
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#14516 from BryanCutler/fixup-accumulator-programming-guide-SPARK-15702.
## What changes were proposed in this pull request?
Doc for the Kafka 0.10 integration
## How was this patch tested?
Scala code examples were taken from my example repo, so hopefully they compile.
Author: cody koeninger <cody@koeninger.org>
Closes#14385 from koeninger/SPARK-16312.
## What changes were proposed in this pull request?
Shuffle fetch on large intermediate dataset is slow because the shuffle service open/close the index file for each shuffle fetch. This change introduces a cache for the index information so that we can avoid accessing the index files for each block fetch
## How was this patch tested?
Tested by running a job on the cluster and the shuffle read time was reduced by 50%.
Author: Sital Kedia <skedia@fb.com>
Closes#12944 from sitalkedia/shuffle_service.
## What changes were proposed in this pull request?
This PR makes various minor updates to examples of all language bindings to make sure they are consistent with each other. Some typos and missing parts (JDBC example in Scala/Java/Python) are also fixed.
## How was this patch tested?
Manually tested.
Author: Cheng Lian <lian@databricks.com>
Closes#14368 from liancheng/revise-examples.
## What changes were proposed in this pull request?
Fix the link at http://spark.apache.org/docs/latest/ml-guide.html.
## How was this patch tested?
None
Author: Sun Dapeng <sdp@apache.org>
Closes#14386 from sundapeng/doclink.
## What changes were proposed in this pull request?
New config var: spark.mesos.docker.containerizer={"mesos","docker" (default)}
This adds support for running docker containers via the Mesos unified containerizer: http://mesos.apache.org/documentation/latest/container-image/
The benefit is losing the dependency on `dockerd`, and all the costs which it incurs.
I've also updated the supported Mesos version to 0.28.2 for support of the required protobufs.
This is blocked on: https://github.com/apache/spark/pull/14167
## How was this patch tested?
- manually testing jobs submitted with both "mesos" and "docker" settings for the new config var.
- spark/mesos integration test suite
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14275 from mgummelt/unified-containerizer.
## What changes were proposed in this pull request?
added missing keyword for java example
## How was this patch tested?
wasn't
Author: Bartek Wiśniewski <wedi@Ava.local>
Closes#14381 from wedi-dev/quickfix/missing_keyword.
## What changes were proposed in this pull request?
Adding a new property to SparkConf called spark.metrics.namespace that allows users to
set a custom namespace for executor and driver metrics in the metrics systems.
By default, the root namespace used for driver or executor metrics is
the value of `spark.app.id`. However, often times, users want to be able to track the metrics
across apps for driver and executor metrics, which is hard to do with application ID
(i.e. `spark.app.id`) since it changes with every invocation of the app. For such use cases,
users can set the `spark.metrics.namespace` property to another spark configuration key like
`spark.app.name` which is then used to populate the root namespace of the metrics system
(with the app name in our example). `spark.metrics.namespace` property can be set to any
arbitrary spark property key, whose value would be used to set the root namespace of the
metrics system. Non driver and executor metrics are never prefixed with `spark.app.id`, nor
does the `spark.metrics.namespace` property have any such affect on such metrics.
## How was this patch tested?
Added new unit tests, modified existing unit tests.
Author: Mark Grover <mark@apache.org>
Closes#14270 from markgrover/spark-5847.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
(`spark.mesos.executor.docker.forcePullImage`). Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#14348 from philipphoffmann/force-pull-image.
## What changes were proposed in this pull request?
Minor doc fix regarding the spark.speculation.quantile configuration parameter. It incorrectly states it should be a percentage, when it should be a fraction.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
I tried building the documentation but got some unidoc errors. I also got them when building off origin/master, so I don't think I caused that problem. I did run the web app and saw the changes reflected as expected.
Author: Nicholas Brown <nbrown@adroitdigital.com>
Closes#14352 from nwbvt/master.
## What changes were proposed in this pull request?
This pr is to fix a wrong description for parquet default compression.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#14351 from maropu/FixParquetDoc.
## What changes were proposed in this pull request?
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
`spark.mesos.executor.docker.forcePullImage`. Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
## How was this patch tested?
I ran a sample application including this change on a Mesos cluster and verified the correct behaviour for both, with and without, force pulling the executor image. As expected the image is being force pulled if the flag is set.
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#13051 from philipphoffmann/force-pull-image.
This PR is based on PR #14098 authored by wangmiao1981.
## What changes were proposed in this pull request?
This PR replaces the original Python Spark SQL example file with the following three files:
- `sql/basic.py`
Demonstrates basic Spark SQL features.
- `sql/datasource.py`
Demonstrates various Spark SQL data sources.
- `sql/hive.py`
Demonstrates Spark SQL Hive interaction.
This PR also removes hard-coded Python example snippets in the SQL programming guide by extracting snippets from the above files using the `include_example` Liquid template tag.
## How was this patch tested?
Manually tested.
Author: wm624@hotmail.com <wm624@hotmail.com>
Author: Cheng Lian <lian@databricks.com>
Closes#14317 from liancheng/py-examples-update.
Clarify documentation on spark.task.maxFailures
No tests run as its documentation
Author: Tom Graves <tgraves@yahoo-inc.com>
Closes#14287 from tgravescs/SPARK-16650.
## What changes were proposed in this pull request?
Added new configuration namespace: spark.mesos.env.*
This allows a user submitting a job in cluster mode to set arbitrary environment variables on the driver.
spark.mesos.driverEnv.KEY=VAL will result in the env var "KEY" being set to "VAL"
I've also refactored the tests a bit so we can re-use code in MesosClusterScheduler.
And I've refactored the command building logic in `buildDriverCommand`. Command builder values were very intertwined before, and now it's easier to determine exactly how each variable is set.
## How was this patch tested?
unit tests
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14167 from mgummelt/driver-env-vars.
## What changes were proposed in this pull request?
Fix parquet to csv in a comment to match the input format being read.
## How was this patch tested?
N/A (doc change only)
Author: Holden Karau <holden@us.ibm.com>
Closes#14274 from holdenk/minor-docfix-schema-of-csv-rather-than-parquet.
1. Create the executorspage-template.html for displaying application information in datables.
2. Added REST API endpoint "allexecutors" to be able to see all executors created for particular job.
3. The executorspage.js uses jQuery to access the data from /api/v1/applications/appid/allexecutors REST API, and use DataTable to display executors for the application. It also, generates summary of dead/live and total executors created during life of the application.
4. Similar changes applicable to Executors Page on history server for a given application.
Snapshots for how it looks like now:
<img width="938" alt="screen shot 2016-06-14 at 2 45 44 pm" src="https://cloud.githubusercontent.com/assets/6090397/16060092/ad1de03a-324b-11e6-8469-9eaa3f2548b5.png">
New Executors Page screenshot looks like this:
<img width="1436" alt="screen shot 2016-06-15 at 10 12 01 am" src="https://cloud.githubusercontent.com/assets/6090397/16085514/ee7004f0-32e1-11e6-9340-33d91e407f2b.png">
Author: Kishor Patil <kpatil@yahoo-inc.com>
Closes#13670 from kishorvpatil/execTemplates.
