This patch adds documentation for Spark configurations that affect off-heap memory and makes some naming and validation improvements for those configs.
- Change `spark.memory.offHeapSize` to `spark.memory.offHeap.size`. This is fine because this configuration has not shipped in any Spark release yet (it's new in Spark 1.6).
- Deprecated `spark.unsafe.offHeap` in favor of a new `spark.memory.offHeap.enabled` configuration. The motivation behind this change is to gather all memory-related configurations under the same prefix.
- Add a check which prevents users from setting `spark.memory.offHeap.enabled=true` when `spark.memory.offHeap.size == 0`. After SPARK-11389 (#9344), which was committed in Spark 1.6, Spark enforces a hard limit on the amount of off-heap memory that it will allocate to tasks. As a result, enabling off-heap execution memory without setting `spark.memory.offHeap.size` will lead to immediate OOMs. The new configuration validation makes this scenario easier to diagnose, helping to avoid user confusion.
- Document these configurations on the configuration page.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#10237 from JoshRosen/SPARK-12251.
This avoids bringing up yet another HTTP server on the driver, and
instead reuses the file server already managed by the driver's
RpcEnv. As a bonus, the repl now inherits the security features of
the network library.
There's also a small change to create the directory for storing classes
under the root temp dir for the application (instead of directly
under java.io.tmpdir).
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#9923 from vanzin/SPARK-11563.
Replaces a number of occurences of `MLlib` in the documentation that were meant to refer to the `spark.mllib` package instead. It should clarify for new users the difference between `spark.mllib` (the package) and MLlib (the umbrella project for ML in spark).
It also removes some files that I forgot to delete with #10207
Author: Timothy Hunter <timhunter@databricks.com>
Closes#10234 from thunterdb/12212.
Documentation regarding the `IndexToString` label transformer with code snippets in Scala/Java/Python.
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#10166 from BenFradet/SPARK-12159.
This reverts PR #10002, commit 78209b0cca.
The original PR wasn't tested on Jenkins before being merged.
Author: Cheng Lian <lian@databricks.com>
Closes#10200 from liancheng/revert-pr-10002.
Add ```SQLTransformer``` user guide, example code and make Scala API doc more clear.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10006 from yanboliang/spark-11958.
Made new patch contaning only markdown examples moved to exmaple/folder.
Ony three java code were not shfted since they were contaning compliation error ,these classes are
1)StandardScale 2)NormalizerExample 3)VectorIndexer
Author: Xusen Yin <yinxusen@gmail.com>
Author: somideshmukh <somilde@us.ibm.com>
Closes#10002 from somideshmukh/SomilBranch1.33.
The existing `spark.memory.fraction` (default 0.75) gives the system 25% of the space to work with. For small heaps, this is not enough: e.g. default 1GB leaves only 250MB system memory. This is especially a problem in local mode, where the driver and executor are crammed in the same JVM. Members of the community have reported driver OOM's in such cases.
**New proposal.** We now reserve 300MB before taking the 75%. For 1GB JVMs, this leaves `(1024 - 300) * 0.75 = 543MB` for execution and storage. This is proposal (1) listed in the [JIRA](https://issues.apache.org/jira/browse/SPARK-12081).
Author: Andrew Or <andrew@databricks.com>
Closes#10081 from andrewor14/unified-memory-small-heaps.
This pull request fixes multiple issues with API doc generation.
- Modify the Jekyll plugin so that the entire doc build fails if API docs cannot be generated. This will make it easy to detect when the doc build breaks, since this will now trigger Jenkins failures.
- Change how we handle the `-target` compiler option flag in order to fix `javadoc` generation.
- Incorporate doc changes from thunterdb (in #10048).
Closes#10048.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Timothy Hunter <timhunter@databricks.com>
Closes#10049 from JoshRosen/fix-doc-build.
jira: https://issues.apache.org/jira/browse/SPARK-11689
Add simple user guide for LDA under spark.ml and example code under examples/. Use include_example to include example code in the user guide markdown. Check SPARK-11606 for instructions.
Original PR is reverted due to document build error. https://github.com/apache/spark/pull/9722
mengxr feynmanliang yinxusen Sorry for the troubling.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#9974 from hhbyyh/ldaMLExample.
The list in ml-ensembles.md wasn't properly formatted and, as a result, was looking like this:
This PR aims to make it look like this:
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#10025 from BenFradet/ml-ensembles-doc.
This change abstracts the code that serves jars / files to executors so that
each RpcEnv can have its own implementation; the akka version uses the existing
HTTP-based file serving mechanism, while the netty versions uses the new
stream support added to the network lib, which makes file transfers benefit
from the easier security configuration of the network library, and should also
reduce overhead overall.
The change includes a small fix to TransportChannelHandler so that it propagates
user events to downstream handlers.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#9530 from vanzin/SPARK-11140.
Add label expression support for AM to restrict it runs on the specific set of nodes. I tested it locally and works fine.
sryza and vanzin please help to review, thanks a lot.
Author: jerryshao <sshao@hortonworks.com>
Closes#9800 from jerryshao/SPARK-7173.
This PR adds a sidebar menu when browsing the user guide of MLlib. It uses a YAML file to describe the structure of the documentation. It should be trivial to adapt this to the other projects.
Author: Timothy Hunter <timhunter@databricks.com>
Closes#9826 from thunterdb/spark-11835.
jira: https://issues.apache.org/jira/browse/SPARK-11689
Add simple user guide for LDA under spark.ml and example code under examples/. Use include_example to include example code in the user guide markdown. Check SPARK-11606 for instructions.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#9722 from hhbyyh/ldaMLExample.
Added tests for function that are reported as masked, to make sure the base:: or stats:: function can be called.
For those we can't call, added them to SparkR programming guide.
It would seem to me `table, sample, subset, filter, cov` not working are not actually expected - I investigated/experimented with them but couldn't get them to work. It looks like as they are defined in base or stats they are missing the S3 generic, eg.
```
> methods("transform")
[1] transform,ANY-method transform.data.frame
[3] transform,DataFrame-method transform.default
see '?methods' for accessing help and source code
> methods("subset")
[1] subset.data.frame subset,DataFrame-method subset.default
[4] subset.matrix
see '?methods' for accessing help and source code
Warning message:
In .S3methods(generic.function, class, parent.frame()) :
function 'subset' appears not to be S3 generic; found functions that look like S3 methods
```
Any idea?
More information on masking:
http://www.ats.ucla.edu/stat/r/faq/referencing_objects.htmhttp://www.sfu.ca/~sweldon/howTo/guide4.pdf
This is what the output doc looks like (minus css):
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9785 from felixcheung/rmasked.
This PR includes:
* Update SparkR:::glm, SparkR:::summary API docs.
* Update SparkR machine learning user guide and example codes to show:
* supporting feature interaction in R formula.
* summary for gaussian GLM model.
* coefficients for binomial GLM model.
mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9727 from yanboliang/spark-11684.
Based on my conversions with people, I believe the consensus is that the coarse-grained mode is more stable and easier to reason about. It is best to use that as the default rather than the more flaky fine-grained mode.
Author: Reynold Xin <rxin@databricks.com>
Closes#9795 from rxin/SPARK-11809.
JIRA issue https://issues.apache.org/jira/browse/SPARK-11728.
The ml-ensembles.md file contains `OneVsRestExample`. Instead of writing new code files of two `OneVsRestExample`s, I use two existing files in the examples directory, they are `OneVsRestExample.scala` and `JavaOneVsRestExample.scala`.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#9716 from yinxusen/SPARK-11728.
This PR adds a new option `spark.sql.hive.thriftServer.singleSession` for disabling multi-session support in the Thrift server.
Note that this option is added as a Spark configuration (retrieved from `SparkConf`) rather than Spark SQL configuration (retrieved from `SQLConf`). This is because all SQL configurations are session-ized. Since multi-session support is by default on, no JDBC connection can modify global configurations like the newly added one.
Author: Cheng Lian <lian@databricks.com>
Closes#9740 from liancheng/spark-11089.single-session-option.
MESOS_NATIVE_LIBRARY was renamed in favor of MESOS_NATIVE_JAVA_LIBRARY. This commit fixes the reference in the documentation.
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#9768 from philipphoffmann/patch-2.
In the **[Task Launching Overheads](http://spark.apache.org/docs/latest/streaming-programming-guide.html#task-launching-overheads)** section,
>Task Serialization: Using Kryo serialization for serializing tasks can reduce the task sizes, and therefore reduce the time taken to send them to the slaves.
as we known **Task Serialization** is configuration by **spark.closure.serializer** parameter, but currently only the Java serializer is supported. If we set **spark.closure.serializer** to **org.apache.spark.serializer.KryoSerializer**, then this will throw a exception.
Author: yangping.wu <wyphao.2007@163.com>
Closes#9734 from 397090770/397090770-patch-1.
`<\code>` end tag missing backslash in
docs/configuration.md{L308-L339}
ref #8795
Author: Kai Jiang <jiangkai@gmail.com>
Closes#9715 from vectorijk/minor-typo-docs.
Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame, include:
* Use libSVM data source for all example codes under examples/ml, and remove unused import.
* Use libSVM data source for user guides under ml-*** which were omitted by #8697.
* Fix bug: We should use ```sqlContext.read().format("libsvm").load(path)``` at Java side, but the API doc and user guides misuse as ```sqlContext.read.format("libsvm").load(path)```.
* Code cleanup.
mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9690 from yanboliang/spark-11723.
I have made the required changes and tested.
Kindly review the changes.
Author: Rishabh Bhardwaj <rbnext29@gmail.com>
Closes#9407 from rishabhbhardwaj/SPARK-11445.
Add Python example code for Multilayer Perceptron Classification, and make example code in user guide document testable. mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9594 from yanboliang/spark-11629.
