It does not make much sense to set `spark.shuffle.spill` or `spark.sql.planner.externalSort` to false: I believe that these configurations were initially added as "escape hatches" to guard against bugs in the external operators, but these operators are now mature and well-tested. In addition, these configurations are not handled in a consistent way anymore: SQL's Tungsten codepath ignores these configurations and will continue to use spilling operators. Similarly, Spark Core's `tungsten-sort` shuffle manager does not respect `spark.shuffle.spill=false`.
This pull request removes these configurations, adds warnings at the appropriate places, and deletes a large amount of code which was only used in code paths that did not support spilling.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#8831 from JoshRosen/remove-ability-to-disable-spilling.
In Spark 1.5.0, Spark SQL is compatible with Hive 0.12.0 through 1.2.1 but the documentation is wrong.
/CC yhuai
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#8776 from sarutak/SPARK-10584-2.
The [published docs for 1.5.0](http://spark.apache.org/docs/1.5.0/api/java/org/apache/spark/streaming/) have a bunch of test classes in them. The only way I can reproduce this is to `test:compile` before running `unidoc`. To prevent this from happening again, I've added a clean before doc generation.
Author: Michael Armbrust <michael@databricks.com>
Closes#8787 from marmbrus/testsInDocs.
In the Configuration section, the **spark.yarn.driver.memoryOverhead** and **spark.yarn.am.memoryOverhead**‘s default value should be "driverMemory * 0.10, with minimum of 384" and "AM memory * 0.10, with minimum of 384" respectively. Because from Spark 1.4.0, the **MEMORY_OVERHEAD_FACTOR** is set to 0.1.0, not 0.07.
Author: yangping.wu <wyphao.2007@163.com>
Closes#8797 from 397090770/SparkOnYarnDocError.
Various ML guide cleanups.
* ml-guide.md: Make it easier to access the algorithm-specific guides.
* LDA user guide: EM often begins with useless topics, but running longer generally improves them dramatically. E.g., 10 iterations on a Wikipedia dataset produces useless topics, but 50 iterations produces very meaningful topics.
* mllib-feature-extraction.html#elementwiseproduct: “w” parameter should be “scalingVec”
* Clean up Binarizer user guide a little.
* Document in Pipeline that users should not put an instance into the Pipeline in more than 1 place.
* spark.ml Word2Vec user guide: clean up grammar/writing
* Chi Sq Feature Selector docs: Improve text in doc.
CC: mengxr feynmanliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8752 from jkbradley/mlguide-fixes-1.5.
* a follow-up to 16b6d18613 as `--num-executors` flag is not suppported.
* links + formatting
Author: Jacek Laskowski <jacek.laskowski@deepsense.io>
Closes#8762 from jaceklaskowski/docs-spark-on-yarn.
Links work now properly + consistent use of *Spark standalone cluster* (Spark uppercase + lowercase the rest -- seems agreed in the other places in the docs).
Author: Jacek Laskowski <jacek.laskowski@deepsense.io>
Closes#8759 from jaceklaskowski/docs-submitting-apps.
The default value of hive metastore version is 1.2.1 but the documentation says the value of `spark.sql.hive.metastore.version` is 0.13.1.
Also, we cannot get the default value by `sqlContext.getConf("spark.sql.hive.metastore.version")`.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#8739 from sarutak/SPARK-10584.
I fixed to use LIBSVM data source in the example code in spark.ml instead of MLUtils
Author: y-shimizu <y.shimizu0429@gmail.com>
Closes#8697 from y-shimizu/SPARK-10518.
spark.scheduler.minRegisteredResourcesRatio configuration parameter works for YARN mode but not for Mesos Coarse grained mode.
If the parameter specified default value of 0 will be set for spark.scheduler.minRegisteredResourcesRatio in base class and this method will always return true.
There are no existing test for YARN mode too. Hence not added test for the same.
Author: Akash Mishra <akash.mishra20@gmail.com>
Closes#8672 from SleepyThread/master.
Small typo in the example for `LabelledPoint` in the MLLib docs.
Author: Sean Paradiso <seanparadiso@gmail.com>
Closes#8680 from sparadiso/docs_mllib_smalltypo.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#8656 from tdas/SPARK-10492 and squashes the following commits:
986cdd6 [Tathagata Das] Added information on backpressure
We introduced the Netty network module for shuffle in Spark 1.2, and has turned it on by default for 3 releases. The old ConnectionManager is difficult to maintain. If we merge the patch now, by the time it is released, it would be 1 yr for which ConnectionManager is off by default. It's time to remove it.
Author: Reynold Xin <rxin@databricks.com>
Closes#8161 from rxin/SPARK-9767.
- Fixed information around Python API tags in streaming programming guides
- Added missing stuff in python docs
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#8595 from tdas/SPARK-10440.
Support running pyspark with cluster mode on Mesos!
This doesn't upload any scripts, so if running in a remote Mesos requires the user to specify the script from a available URI.
Author: Timothy Chen <tnachen@gmail.com>
Closes#8349 from tnachen/mesos_python.
SPARK-4223.
Currently we support setting view and modify acls but you have to specify a list of users. It would be nice to support * meaning all users have access.
Manual tests to verify that: "*" works for any user in:
a. Spark ui: view and kill stage. Done.
b. Spark history server. Done.
c. Yarn application killing. Done.
Author: zhuol <zhuol@yahoo-inc.com>
Closes#8398 from zhuoliu/4223.
Migrate Apache download closer.cgi refs to new closer.lua
This is the bit of the change that affects the project docs; I'm implementing the changes to the Apache site separately.
Author: Sean Owen <sowen@cloudera.com>
Closes#8557 from srowen/SPARK-10398.
* The example code was added in 1.2, before `createDataFrame`. This PR switches to `createDataFrame`. Java code still uses JavaBean.
* assume `sqlContext` is available
* fix some minor issues from previous code review
jkbradley srowen feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8518 from mengxr/SPARK-10331.
* replace `ML Dataset` by `DataFrame` to unify the abstraction
* ML algorithms -> pipeline components to describe the main concept
* remove Scala API doc links from the main guide
* `Section Title` -> `Section tile` to be consistent with other section titles in MLlib guide
* modified lines break at 100 chars or periods
jkbradley feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8517 from mengxr/SPARK-10348.
This PR updates the MLlib user guide and adds migration guide for 1.4->1.5.
* merge migration guide for `spark.mllib` and `spark.ml` packages
* remove dependency section from `spark.ml` guide
* move the paragraph about `spark.mllib` and `spark.ml` to the top and recommend `spark.ml`
* move Sam's talk to footnote to make the section focus on dependencies
Minor changes to code examples and other wording will be in a separate PR.
jkbradley srowen feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8498 from mengxr/SPARK-9671.
* Adds user guide for `LinearRegressionSummary`
* Fixes unresolved issues in #8197
CC jkbradley mengxr
Author: Feynman Liang <fliang@databricks.com>
Closes#8491 from feynmanliang/SPARK-9905.
I added a small note about the different types of evaluator and the metrics used.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#8304 from MechCoder/multiclass_evaluator.
https://issues.apache.org/jira/browse/SPARK-10287
After porting json to HadoopFsRelation, it seems hard to keep the behavior of picking up new files automatically for JSON. This PR removes this behavior, so JSON is consistent with others (ORC and Parquet).
Author: Yin Huai <yhuai@databricks.com>
Closes#8469 from yhuai/jsonRefresh.
* Adds user guide for ml.feature.StopWordsRemovers, ran code examples on my machine
* Cleans up scaladocs for public methods
* Adds test for Java compatibility
* Follow up Python user guide code example is tracked by SPARK-10249
Author: Feynman Liang <fliang@databricks.com>
Closes#8436 from feynmanliang/SPARK-10230.
jira: https://issues.apache.org/jira/browse/SPARK-9901
The jira covers only the document update. I can further provide example code for QR (like the ones for SVD and PCA) in a separate PR.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#8462 from hhbyyh/qrDoc.
https://issues.apache.org/jira/browse/SPARK-10315
this parameter is not used any longer and there is some mistake in the current document , should be 'akka.remote.watch-failure-detector.threshold'
Author: CodingCat <zhunansjtu@gmail.com>
Closes#8483 from CodingCat/SPARK_10315.
* Adds two new sections to LDA's user guide; one for each optimizer/model
* Documents new features added to LDA (e.g. topXXXperXXX, asymmetric priors, hyperpam optimization)
* Cleans up a TODO and sets a default parameter in LDA code
jkbradley hhbyyh
Author: Feynman Liang <fliang@databricks.com>
Closes#8254 from feynmanliang/SPARK-9888.
jira: https://issues.apache.org/jira/browse/SPARK-8531
Update ML user guide for MinMaxScaler
Author: Yuhao Yang <hhbyyh@gmail.com>
Author: unknown <yuhaoyan@yuhaoyan-MOBL1.ccr.corp.intel.com>
Closes#7211 from hhbyyh/minmaxdoc.
User guide for spark.ml GBTs and Random Forests.
The examples are copied from the decision tree guide and modified to run.
I caught some issues I had somehow missed in the tree guide as well.
I have run all examples, including Java ones. (Of course, I thought I had previously as well...)
CC: mengxr manishamde yanboliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8369 from jkbradley/ml-ensemble-docs.