## 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.
![image](https://cloud.githubusercontent.com/assets/6235869/21292915/04d9d084-c515-11e6-811a-999d598dffba.png)
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
![before](https://cloud.githubusercontent.com/assets/4736016/22136731/b358115c-df19-11e6-8f6c-2f7b65766265.png)
* after
![after](https://cloud.githubusercontent.com/assets/4736016/22136745/c6366ff8-df19-11e6-840d-e7e894218f9c.png)
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:
![snip20161231_37](https://cloud.githubusercontent.com/assets/15843379/21576864/cc52fcd8-cf7b-11e6-8bd6-f935d9ff4a6b.png)
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.