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* [DOC] add config option spark.ui.enabled into documentWeichenXu2016-08-121-0/+7
| | | | | | | | | | | | | | | | ## 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.
* [SPARK-13081][PYSPARK][SPARK_SUBMIT] Allow set pythonExec of driver and ↵Jeff Zhang2016-08-111-2/+19
| | | | | | | | | | | | executor through conf… 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.
* Correct example value for spark.ssl.YYY.XXX settingsAndrew Ash2016-08-111-2/+4
| | | | | | | | | | 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.
* Update docs to include SASL support for RPCMichael Gummelt2016-08-081-3/+4
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Update docs to include SASL support for RPC Evidence: https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rpc/netty/NettyRpcEnv.scala#L63 ## How was this patch tested? Docs change only Author: Michael Gummelt <mgummelt@mesosphere.io> Closes #14549 from mgummelt/sasl.
* [SPARK-15074][SHUFFLE] Cache shuffle index file to speedup shuffle fetchSital Kedia2016-08-041-0/+7
| | | | | | | | | | | | | | ## 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.
* Fix description of spark.speculation.quantileNicholas Brown2016-07-251-1/+1
| | | | | | | | | | | | | | | | | | ## 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.
* [SPARK-16650] Improve documentation of spark.task.maxFailuresTom Graves2016-07-221-1/+3
| | | | | | | | | | 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.
* [DOC][SQL] update out-of-date code snippets using SQLContext in all documents.WeichenXu2016-07-061-2/+2
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? I search the whole documents directory using SQLContext, and update the following places: - docs/configuration.md, sparkR code snippets. - docs/streaming-programming-guide.md, several example code. ## How was this patch tested? N/A Author: WeichenXu <WeichenXu123@outlook.com> Closes #14025 from WeichenXu123/WIP_SQLContext_update.
* [SPARK-13723][YARN] Change behavior of --num-executors with dynamic allocation.Ryan Blue2016-06-231-0/+3
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This changes the behavior of --num-executors and spark.executor.instances when using dynamic allocation. Instead of turning dynamic allocation off, it uses the value for the initial number of executors. This changes was discussed on [SPARK-13723](https://issues.apache.org/jira/browse/SPARK-13723). I highly recommend using it while we can change the behavior for 2.0.0. In practice, the 1.x behavior causes unexpected behavior for users (it is not clear that it disables dynamic allocation) and wastes cluster resources because users rarely notice the log message. ## How was this patch tested? This patch updates tests and adds a test for Utils.getDynamicAllocationInitialExecutors. Author: Ryan Blue <blue@apache.org> Closes #13338 from rdblue/SPARK-13723-num-executors-with-dynamic-allocation.
* [SPARK-15796][CORE] Reduce spark.memory.fraction default to avoid ↵Sean Owen2016-06-161-3/+4
| | | | | | | | | | | | | | | | overrunning old gen in JVM default config ## What changes were proposed in this pull request? Reduce `spark.memory.fraction` default to 0.6 in order to make it fit within default JVM old generation size (2/3 heap). See JIRA discussion. This means a full cache doesn't spill into the new gen. CC andrewor14 ## How was this patch tested? Jenkins tests. Author: Sean Owen <sowen@cloudera.com> Closes #13618 from srowen/SPARK-15796.
* [SPARK-15760][DOCS] Add documentation for package-related configs.Marcelo Vanzin2016-06-071-0/+47
| | | | | | | | | While there, also document spark.files and spark.jars. Text is the same as the spark-submit help text with some minor adjustments. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #13502 from vanzin/SPARK-15760.
* [SPARK-15485][SQL][DOCS] Spark SQL Configurationgatorsmile2016-05-231-0/+42
| | | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? So far, the page Configuration in the official documentation does not have a section for Spark SQL. http://spark.apache.org/docs/latest/configuration.html For Spark users, the information and default values of these public configuration parameters are very useful. This PR is to add this missing section to the configuration.html. rxin yhuai marmbrus #### How was this patch tested? Below is the generated webpage. <img width="924" alt="screenshot 2016-05-23 11 35 57" src="https://cloud.githubusercontent.com/assets/11567269/15480492/b08fefc4-20da-11e6-9fa2-7cd5b699ed35.png"> <img width="914" alt="screenshot 2016-05-23 11 37 38" src="https://cloud.githubusercontent.com/assets/11567269/15480499/c5f9482e-20da-11e6-95ff-10821add1af4.png"> <img width="923" alt="screenshot 2016-05-23 11 36 11" src="https://cloud.githubusercontent.com/assets/11567269/15480506/cbd81644-20da-11e6-9d27-effb716b2fac.png"> <img width="920" alt="screenshot 2016-05-23 11 36 18" src="https://cloud.githubusercontent.com/assets/11567269/15480511/d013e332-20da-11e6-854a-cf8813c46f36.png"> Author: gatorsmile <gatorsmile@gmail.com> Closes #13263 from gatorsmile/configurationSQL.
* [SPARK-15223][DOCS] fix wrongly named config referencePhilipp Hoffmann2016-05-091-2/+2
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The configuration setting `spark.executor.logs.rolling.size.maxBytes` was changed to `spark.executor.logs.rolling.maxSize` in 1.4 or so. This commit fixes a remaining reference to the old name in the documentation. Also the description for `spark.executor.logs.rolling.maxSize` was edited to clearly state that the unit for the size is bytes. ## How was this patch tested? no tests Author: Philipp Hoffmann <mail@philipphoffmann.de> Closes #13001 from philipphoffmann/patch-3.
* [SPARK-4224][CORE][YARN] Support group aclsDhruve Ashar2016-05-041-3/+52
| | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently only a list of users can be specified for view and modify acls. This change enables a group of admins/devs/users to be provisioned for viewing and modifying Spark jobs. **Changes Proposed in the fix** Three new corresponding config entries have been added where the user can specify the groups to be given access. ``` spark.admin.acls.groups spark.modify.acls.groups spark.ui.view.acls.groups ``` New config entries were added because specifying the users and groups explicitly is a better and cleaner way compared to specifying them in the existing config entry using a delimiter. A generic trait has been introduced to provide the user to group mapping which makes it pluggable to support a variety of mapping protocols - similar to the one used in hadoop. A default unix shell based implementation has been provided. Custom user to group mapping protocol can be specified and configured by the entry ```spark.user.groups.mapping``` **How the patch was Tested** We ran different spark jobs setting the config entries in combinations of admin, modify and ui acls. For modify acls we tried killing the job stages from the ui and using yarn commands. For view acls we tried accessing the UI tabs and the logs. Headless accounts were used to launch these jobs and different users tried to modify and view the jobs to ensure that the groups mapping applied correctly. Additional Unit tests have been added without modifying the existing ones. These test for different ways of setting the acls through configuration and/or API and validate the expected behavior. Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #12760 from dhruve/impr/SPARK-4224.
* [SPARK-14667] Remove HashShuffleManagerReynold Xin2016-04-181-9/+0
| | | | | | | | | | | | ## What changes were proposed in this pull request? The sort shuffle manager has been the default since Spark 1.2. It is time to remove the old hash shuffle manager. ## How was this patch tested? Removed some tests related to the old manager. Author: Reynold Xin <rxin@databricks.com> Closes #12423 from rxin/SPARK-14667.
* [SPARK-14572][DOC] Update config docs to allow -Xms in extraJavaOptionsDhruve Ashar2016-04-141-4/+7
| | | | | | | | | | | | ## What changes were proposed in this pull request? The configuration docs are updated to reflect the changes introduced with [SPARK-12384](https://issues.apache.org/jira/browse/SPARK-12384). This allows the user to specify initial heap memory settings through the extraJavaOptions for executor, driver and am. ## How was this patch tested? The changes are tested in [SPARK-12384](https://issues.apache.org/jira/browse/SPARK-12384). This is just documenting the changes made. Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #12333 from dhruve/doc/SPARK-14572.
* [MINOR][DOC] improve the doc for "spark.memory.offHeap.size"CodingCat2016-03-071-1/+1
| | | | | | | | | | | | The description of "spark.memory.offHeap.size" in the current document does not clearly state that memory is counted with bytes.... This PR contains a small fix for this tiny issue document fix Author: CodingCat <zhunansjtu@gmail.com> Closes #11561 from CodingCat/master.
* [SPARK-13521][BUILD] Remove reference to Tachyon in cluster & release scriptsReynold Xin2016-02-261-24/+0
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? We provide a very limited set of cluster management script in Spark for Tachyon, although Tachyon itself provides a much better version of it. Given now Spark users can simply use Tachyon as a normal file system and does not require extensive configurations, we can remove this management capabilities to simplify Spark bash scripts. Note that this also reduces coupling between a 3rd party external system and Spark's release scripts, and would eliminate possibility for failures such as Tachyon being renamed or the tar balls being relocated. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #11400 from rxin/release-script.
* [SPARK-7729][UI] Executor which has been killed should also be displayed on ↵Lianhui Wang2016-02-231-0/+7
| | | | | | | | | | | | | | | Executor Tab andrewor14 squito Dead Executors should also be displayed on Executor Tab. as following: ![image](https://cloud.githubusercontent.com/assets/545478/11492707/ae55d7f6-982b-11e5-919a-b62cd84684b2.png) Author: Lianhui Wang <lianhuiwang09@gmail.com> This patch had conflicts when merged, resolved by Committer: Andrew Or <andrew@databricks.com> Closes #10058 from lianhuiwang/SPARK-7729.
* [MINOR][DOCS] Fix typos in `configuration.md` and `hardware-provisioning.md`Dongjoon Hyun2016-02-211-5/+5
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes some typos in the following documentation files. * `NOTICE`, `configuration.md`, and `hardware-provisioning.md`. ## How was the this patch tested? manual tests Author: Dongjoon Hyun <dongjoonapache.org> Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11289 from dongjoon-hyun/minor_fix_typos_notice_and_confdoc.
* [SPARK-13350][DOCS] Config doc updated to state that PYSPARK_PYTHON's ↵Christopher C. Aycock2016-02-171-1/+1
| | | | | | | | default is "python2.7" Author: Christopher C. Aycock <chris@chrisaycock.com> Closes #11239 from chrisaycock/master.
* [SPARK-11627] Add initial input rate limit for spark streaming backpressure ↵junhao2016-02-161-0/+8
| | | | | | | | | | | | | mechanism. https://issues.apache.org/jira/browse/SPARK-11627 Spark Streaming backpressure mechanism has no initial input rate limit, it might cause OOM exception. In the firest batch task ,receivers receive data at the maximum speed they can reach,it might exhaust executors memory resources. Add a initial input rate limit value can make sure the Streaming job execute success in the first batch,then the backpressure mechanism can adjust receiving rate adaptively. Author: junhao <junhao@mogujie.com> Closes #9593 from junhaoMg/junhao-dev.
* [SPARK-6166] Limit number of in flight outbound requestsSanket2016-02-111-0/+10
| | | | | | | | | | | This JIRA is related to https://github.com/apache/spark/pull/5852 Had to do some minor rework and test to make sure it works with current version of spark. Author: Sanket <schintap@untilservice-lm> Closes #10838 from redsanket/limit-outbound-connections.
* [SPARK-12414][CORE] Remove closure serializerSean Owen2016-02-101-7/+0
| | | | | | | | | | Remove spark.closure.serializer option and use JavaSerializer always CC andrewor14 rxin I see there's a discussion in the JIRA but just thought I'd offer this for a look at what the change would be. Author: Sean Owen <sowen@cloudera.com> Closes #11150 from srowen/SPARK-12414.
* [SPARK-5095][MESOS] Support launching multiple mesos executors in coarse ↵Michael Gummelt2016-02-101-5/+10
| | | | | | | | | | | | | | | | | | | | grained mesos mode. This is the next iteration of tnachen's previous PR: https://github.com/apache/spark/pull/4027 In that PR, we resolved with andrewor14 and pwendell to implement the Mesos scheduler's support of `spark.executor.cores` to be consistent with YARN and Standalone. This PR implements that resolution. This PR implements two high-level features. These two features are co-dependent, so they're implemented both here: - Mesos support for spark.executor.cores - Multiple executors per slave We at Mesosphere have been working with Typesafe on a Spark/Mesos integration test suite: https://github.com/typesafehub/mesos-spark-integration-tests, which passes for this PR. The contribution is my original work and I license the work to the project under the project's open source license. Author: Michael Gummelt <mgummelt@mesosphere.io> Closes #10993 from mgummelt/executor_sizing.
* [SPARK-13214][DOCS] update dynamicAllocation documentationBill Chambers2016-02-051-2/+2
| | | | | | Author: Bill Chambers <bill@databricks.com> Closes #11094 from anabranch/dynamic-docs.
* [SPARK-12463][SPARK-12464][SPARK-12465][SPARK-10647][MESOS] Fix zookeeper ↵Timothy Chen2016-02-011-0/+23
| | | | | | | | | | dir with mesos conf and add docs. Fix zookeeper dir configuration used in cluster mode, and also add documentation around these settings. Author: Timothy Chen <tnachen@gmail.com> Closes #10057 from tnachen/fix_mesos_dir.
* [SPARK-1680][DOCS] Explain environment variables for running on YARN in ↵Andrew2016-01-271-0/+2
| | | | | | | | | | cluster mode JIRA 1680 added a property called spark.yarn.appMasterEnv. This PR draws users' attention to this special case by adding an explanation in configuration.html#environment-variables Author: Andrew <weiner.andrew.j@gmail.com> Closes #10869 from weineran/branch-yarn-docs.
* [SPARK-7997][CORE] Remove Akka from Spark Core and StreamingShixiong Zhu2016-01-221-61/+4
| | | | | | | | | | | | - Remove Akka dependency from core. Note: the streaming-akka project still uses Akka. - Remove HttpFileServer - Remove Akka configs from SparkConf and SSLOptions - Rename `spark.akka.frameSize` to `spark.rpc.message.maxSize`. I think it's still worth to keep this config because using `DirectTaskResult` or `IndirectTaskResult` depends on it. - Update comments and docs Author: Shixiong Zhu <shixiong@databricks.com> Closes #10854 from zsxwing/remove-akka.
* [SPARK-12534][DOC] update documentation to list command line equivalent to ↵felixcheung2016-01-211-5/+5
| | | | | | | | | | properties Several Spark properties equivalent to Spark submit command line options are missing. Author: felixcheung <felixcheung_m@hotmail.com> Closes #10491 from felixcheung/sparksubmitdoc.
* [SPARK-2750][WEB UI] Add https support to the Web UIscwf2016-01-191-0/+22
| | | | | | | | | Author: scwf <wangfei1@huawei.com> Author: Marcelo Vanzin <vanzin@cloudera.com> Author: WangTaoTheTonic <wangtao111@huawei.com> Author: w00228970 <wangfei1@huawei.com> Closes #10238 from vanzin/SPARK-2750.
* [SPARK-12507][STREAMING][DOCUMENT] Expose closeFileAfterWrite and ↵Shixiong Zhu2016-01-071-0/+18
| | | | | | | | | | allowBatching configurations for Streaming /cc tdas brkyvz Author: Shixiong Zhu <shixiong@databricks.com> Closes #10453 from zsxwing/streaming-conf.
* [DOC] fix 'spark.memory.offHeap.enabled' default value to falsezzcclp2016-01-061-1/+1
| | | | | | | | modify 'spark.memory.offHeap.enabled' default value to false Author: zzcclp <xm_zzc@sina.com> Closes #10633 from zzcclp/fix_spark.memory.offHeap.enabled_default_value.
* [SPARK-7689] Remove TTL-based metadata cleaning in Spark 2.0Josh Rosen2016-01-061-11/+0
| | | | | | | | | | | | This PR removes `spark.cleaner.ttl` and the associated TTL-based metadata cleaning code. Now that we have the `ContextCleaner` and a timer to trigger periodic GCs, I don't think that `spark.cleaner.ttl` is necessary anymore. The TTL-based cleaning isn't enabled by default, isn't included in our end-to-end tests, and has been a source of user confusion when it is misconfigured. If the TTL is set too low, data which is still being used may be evicted / deleted, leading to hard to diagnose bugs. For all of these reasons, I think that we should remove this functionality in Spark 2.0. Additional benefits of doing this include marginally reduced memory usage, since we no longer need to store timetsamps in hashmaps, and a handful fewer threads. Author: Josh Rosen <joshrosen@databricks.com> Closes #10534 from JoshRosen/remove-ttl-based-cleaning.
* [SPARK-12588] Remove HttpBroadcast in Spark 2.0.Reynold Xin2015-12-301-17/+2
| | | | | | | | We switched to TorrentBroadcast in Spark 1.1, and HttpBroadcast has been undocumented since then. It's time to remove it in Spark 2.0. Author: Reynold Xin <rxin@databricks.com> Closes #10531 from rxin/SPARK-12588.
* [SPARK-12388] change default compression to lz4Davies Liu2015-12-211-1/+1
| | | | | | | | | | | | | | According the benchmark [1], LZ4-java could be 80% (or 30%) faster than Snappy. After changing the compressor to LZ4, I saw 20% improvement on end-to-end time for a TPCDS query (Q4). [1] https://github.com/ning/jvm-compressor-benchmark/wiki cc rxin Author: Davies Liu <davies@databricks.com> Closes #10342 from davies/lz4.
* [SPARK-12091] [PYSPARK] Deprecate the JAVA-specific deserialized storage levelsgatorsmile2015-12-181-3/+4
| | | | | | | | | | | | | | The current default storage level of Python persist API is MEMORY_ONLY_SER. This is different from the default level MEMORY_ONLY in the official document and RDD APIs. davies Is this inconsistency intentional? Thanks! Updates: Since the data is always serialized on the Python side, the storage levels of JAVA-specific deserialization are not removed, such as MEMORY_ONLY. Updates: Based on the reviewers' feedback. In Python, stored objects will always be serialized with the [Pickle](https://docs.python.org/2/library/pickle.html) library, so it does not matter whether you choose a serialized level. The available storage levels in Python include `MEMORY_ONLY`, `MEMORY_ONLY_2`, `MEMORY_AND_DISK`, `MEMORY_AND_DISK_2`, `DISK_ONLY`, `DISK_ONLY_2` and `OFF_HEAP`. Author: gatorsmile <gatorsmile@gmail.com> Closes #10092 from gatorsmile/persistStorageLevel.
* [SPARK-10123][DEPLOY] Support specifying deploy mode from configurationjerryshao2015-12-151-3/+12
| | | | | | | | Please help to review, thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #10195 from jerryshao/SPARK-10123.
* [SPARK-12251] Document and improve off-heap memory configurationsJosh Rosen2015-12-101-0/+16
| | | | | | | | | | | | | 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.
* [SPARK-11563][CORE][REPL] Use RpcEnv to transfer REPL-generated classes.Marcelo Vanzin2015-12-101-8/+0
| | | | | | | | | | | | | | | 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.
* [SPARK-12080][CORE] Kryo - Support multiple user registratorsrotems2015-12-041-2/+2
| | | | | | Author: rotems <roter> Closes #10078 from Botnaim/KryoMultipleCustomRegistrators.
* [SPARK-12081] Make unified memory manager work with small heapsAndrew Or2015-12-011-2/+2
| | | | | | | | | | 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.
* [DOCUMENTATION] Fix minor doc errorJeff Zhang2015-11-251-1/+1
| | | | | | Author: Jeff Zhang <zjffdu@apache.org> Closes #9956 from zjffdu/dev_typo.
* [SPARK-11140][CORE] Transfer files using network lib when using NettyRpcEnv.Marcelo Vanzin2015-11-231-0/+2
| | | | | | | | | | | | | | | | 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.
* [SPARK-11710] Document new memory management modelAndrew Or2015-11-161-5/+8
| | | | | | Author: Andrew Or <andrew@databricks.com> Closes #9676 from andrewor14/memory-management-docs.
* [MINOR][DOCS] typo in docs/configuration.mdKai Jiang2015-11-141-5/+5
| | | | | | | | | | | `<\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.
* [SPARK-11305][DOCS] Remove Third-Party Hadoop Distributions Doc PageSean Owen2015-11-011-0/+15
| | | | | | | | | | Remove Hadoop third party distro page, and move Hadoop cluster config info to configuration page CC pwendell Author: Sean Owen <sowen@cloudera.com> Closes #9298 from srowen/SPARK-11305.
* [SPARK-10971][SPARKR] RRunner should allow setting path to Rscript.Sun Rui2015-10-231-0/+18
| | | | | | | | | | | | | | | | | Add a new spark conf option "spark.sparkr.r.driver.command" to specify the executable for an R script in client modes. The existing spark conf option "spark.sparkr.r.command" is used to specify the executable for an R script in cluster modes for both driver and workers. See also [launch R worker script](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/r/RRDD.scala#L395). BTW, [envrionment variable "SPARKR_DRIVER_R"](https://github.com/apache/spark/blob/master/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java#L275) is used to locate R shell on the local host. For your information, PYSPARK has two environment variables serving simliar purpose: PYSPARK_PYTHON Python binary executable to use for PySpark in both driver and workers (default is `python`). PYSPARK_DRIVER_PYTHON Python binary executable to use for PySpark in driver only (default is PYSPARK_PYTHON). pySpark use the code [here](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala#L41) to determine the python executable for a python script. Author: Sun Rui <rui.sun@intel.com> Closes #9179 from sun-rui/SPARK-10971.
* [SPARK-10708] Consolidate sort shuffle implementationsJosh Rosen2015-10-221-5/+2
| | | | | | | | There's a lot of duplication between SortShuffleManager and UnsafeShuffleManager. Given that these now provide the same set of functionality, now that UnsafeShuffleManager supports large records, I think that we should replace SortShuffleManager's serialized shuffle implementation with UnsafeShuffleManager's and should merge the two managers together. Author: Josh Rosen <joshrosen@databricks.com> Closes #8829 from JoshRosen/consolidate-sort-shuffle-implementations.
* [SPARK-11039][Documentation][Web UI] Document additional ui configurationsNick Pritchard2015-10-151-0/+14
| | | | | | | | | | Add documentation for configuration: - spark.sql.ui.retainedExecutions - spark.streaming.ui.retainedBatches Author: Nick Pritchard <nicholas.pritchard@falkonry.com> Closes #9052 from pnpritchard/SPARK-11039.
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