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* SPARK-1786: Reopening PR 724Ankur Dave2014-05-1212-26/+49
| | | | | | | | | | | | | | | Addressing issue in MimaBuild.scala. Author: Ankur Dave <ankurdave@gmail.com> Author: Joseph E. Gonzalez <joseph.e.gonzalez@gmail.com> Closes #742 from jegonzal/edge_partition_serialization and squashes the following commits: 8ba6e0d [Ankur Dave] Add concatenation operators to MimaBuild.scala cb2ed3a [Joseph E. Gonzalez] addressing missing exclusion in MimaBuild.scala 5d27824 [Ankur Dave] Disable reference tracking to fix serialization test c0a9ae5 [Ankur Dave] Add failing test for EdgePartition Kryo serialization a4a3faa [Joseph E. Gonzalez] Making EdgePartition serializable.
* SPARK-1806: Upgrade Mesos dependency to 0.18.1Bernardo Gomez Palacio2014-05-125-5/+14
| | | | | | | | | | | | | | | | | | | | Enabled Mesos (0.18.1) dependency with shaded protobuf Why is this needed? Avoids any protobuf version collision between Mesos and any other dependency in Spark e.g. Hadoop HDFS 2.2+ or 1.0.4. Ticket: https://issues.apache.org/jira/browse/SPARK-1806 * Should close https://issues.apache.org/jira/browse/SPARK-1433 Author berngp Author: Bernardo Gomez Palacio <bernardo.gomezpalacio@gmail.com> Closes #741 from berngp/feature/SPARK-1806 and squashes the following commits: 5d70646 [Bernardo Gomez Palacio] SPARK-1806: Upgrade Mesos dependency to 0.18.1
* SPARK-1772 Stop catching Throwable, let Executors dieAaron Davidson2014-05-1219-140/+127
| | | | | | | | | | | | | | | | | The main issue this patch fixes is [SPARK-1772](https://issues.apache.org/jira/browse/SPARK-1772), in which Executors may not die when fatal exceptions (e.g., OOM) are thrown. This patch causes Executors to delegate to the ExecutorUncaughtExceptionHandler when a fatal exception is thrown. This patch also continues the fight in the neverending war against `case t: Throwable =>`, by only catching Exceptions in many places, and adding a wrapper for Threads and Runnables to make sure any uncaught exceptions are at least printed to the logs. It also turns out that it is unlikely that the IndestructibleActorSystem actually works, given testing ([here](https://gist.github.com/aarondav/ca1f0cdcd50727f89c0d)). The uncaughtExceptionHandler is not called from the places that we expected it would be. [SPARK-1620](https://issues.apache.org/jira/browse/SPARK-1620) deals with part of this issue, but refactoring our Actor Systems to ensure that exceptions are dealt with properly is a much bigger change, outside the scope of this PR. Author: Aaron Davidson <aaron@databricks.com> Closes #715 from aarondav/throwable and squashes the following commits: f9b9bfe [Aaron Davidson] Remove other redundant 'throw e' e937a0a [Aaron Davidson] Address Prashant and Matei's comments 1867867 [Aaron Davidson] [RFC] SPARK-1772 Stop catching Throwable, let Executors die
* Revert "SPARK-1786: Edge Partition Serialization"Patrick Wendell2014-05-1211-44/+23
| | | | This reverts commit a6b02fb7486356493474c7f42bb714c9cce215ca.
* SPARK-1786: Edge Partition SerializationAnkur Dave2014-05-1111-23/+44
| | | | | | | | | | | | | This appears to address the issue with edge partition serialization. The solution appears to be just registering the `PrimitiveKeyOpenHashMap`. However I noticed that we appear to have forked that code in GraphX but retained the same name (which is confusing). I also renamed our local copy to `GraphXPrimitiveKeyOpenHashMap`. We should consider dropping that and using the one in Spark if possible. Author: Ankur Dave <ankurdave@gmail.com> Author: Joseph E. Gonzalez <joseph.e.gonzalez@gmail.com> Closes #724 from jegonzal/edge_partition_serialization and squashes the following commits: b0a525a [Ankur Dave] Disable reference tracking to fix serialization test bb7f548 [Ankur Dave] Add failing test for EdgePartition Kryo serialization 67dac22 [Joseph E. Gonzalez] Making EdgePartition serializable.
* Fix error in 2d Graph PartitionerJoseph E. Gonzalez2014-05-111-2/+2
| | | | | | | | | | Their was a minor bug in which negative partition ids could be generated when constructing a 2D partitioning of a graph. This could lead to an inefficient 2D partition for large vertex id values. Author: Joseph E. Gonzalez <joseph.e.gonzalez@gmail.com> Closes #709 from jegonzal/fix_2d_partitioning and squashes the following commits: 937c562 [Joseph E. Gonzalez] fixing bug in 2d partitioning algorithm where negative partition ids could be generated.
* SPARK-1652: Set driver memory correctly in spark-submit.Patrick Wendell2014-05-111-2/+4
| | | | | | | | | | | | | | | The previous check didn't account for the fact that the default deploy mode is "client" unless otherwise specified. Also, this sets the more narrowly defined SPARK_DRIVER_MEMORY instead of setting SPARK_MEM. Author: Patrick Wendell <pwendell@gmail.com> Closes #730 from pwendell/spark-submit and squashes the following commits: 430b98f [Patrick Wendell] Feedback from Aaron e788edf [Patrick Wendell] Changes based on Aaron's feedback f508146 [Patrick Wendell] SPARK-1652: Set driver memory correctly in spark-submit.
* SPARK-1770: Load balance elements when repartitioning.Patrick Wendell2014-05-112-2/+46
| | | | | | | | | | | | | | | | | | | This patch adds better balancing when performing a repartition of an RDD. Previously the elements in the RDD were hash partitioned, meaning if the RDD was skewed certain partitions would end up being very large. This commit adds load balancing of elements across the repartitioned RDD splits. The load balancing is not perfect: a given output partition can have up to N more elements than the average if there are N input partitions. However, some randomization is used to minimize the probabiliy that this happens. Author: Patrick Wendell <pwendell@gmail.com> Closes #727 from pwendell/load-balance and squashes the following commits: f9da752 [Patrick Wendell] Response to Matei's feedback acfa46a [Patrick Wendell] SPARK-1770: Load balance elements when repartitioning.
* remove outdated runtime Information scala homewitgo2014-05-111-2/+1
| | | | | | | | | Author: witgo <witgo@qq.com> Closes #728 from witgo/scala_home and squashes the following commits: cdfd8be [witgo] Merge branch 'master' of https://github.com/apache/spark into scala_home fac094a [witgo] remove outdated runtime Information scala home
* Enabled incremental build that comes with sbt 0.13.2Prashant Sharma2014-05-101-1/+1
| | | | | | | | | | More info at. https://github.com/sbt/sbt/issues/1010 Author: Prashant Sharma <prashant.s@imaginea.com> Closes #525 from ScrapCodes/sbt-inc-opt and squashes the following commits: ba8fa42 [Prashant Sharma] Enabled incremental build that comes with sbt 0.13.2
* [SPARK-1774] Respect SparkSubmit --jars on YARN (client)Andrew Or2014-05-104-53/+102
| | | | | | | | | | | | | | | | | | | | SparkSubmit ignores `--jars` for YARN client. This is a bug. This PR also automatically adds the application jar to `spark.jar`. Previously, when running as yarn-client, you must specify the jar additionally through `--files` (because `--jars` didn't work). Now you don't have to explicitly specify it through either. Tested on a YARN cluster. Author: Andrew Or <andrewor14@gmail.com> Closes #710 from andrewor14/yarn-jars and squashes the following commits: 35d1928 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-jars c27bf6c [Andrew Or] For yarn-cluster and python, do not add primaryResource to spark.jar c92c5bf [Andrew Or] Minor cleanups 269f9f3 [Andrew Or] Fix format 013d840 [Andrew Or] Fix tests 1407474 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-jars 3bb75e8 [Andrew Or] Allow SparkSubmit --jars to take effect in yarn-client mode
* SPARK-1789. Multiple versions of Netty dependencies cause FlumeStreamSuite ↵Sean Owen2014-05-108-70/+24
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | failure TL;DR is there is a bit of JAR hell trouble with Netty, that can be mostly resolved and will resolve a test failure. I hit the error described at http://apache-spark-user-list.1001560.n3.nabble.com/SparkContext-startup-time-out-td1753.html while running FlumeStreamingSuite, and have for a short while (is it just me?) velvia notes: "I have found a workaround. If you add akka 2.2.4 to your dependencies, then everything works, probably because akka 2.2.4 brings in newer version of Jetty." There are at least 3 versions of Netty in play in the build: - the new Flume 1.4.0 dependency brings in io.netty:netty:3.4.0.Final, and that is the immediate problem - the custom version of akka 2.2.3 depends on io.netty:netty:3.6.6. - but, Spark Core directly uses io.netty:netty-all:4.0.17.Final The POMs try to exclude other versions of netty, but are excluding org.jboss.netty:netty, when in fact older versions of io.netty:netty (not netty-all) are also an issue. The org.jboss.netty:netty excludes are largely unnecessary. I replaced many of them with io.netty:netty exclusions until everything agreed on io.netty:netty-all:4.0.17.Final. But this didn't work, since Akka 2.2.3 doesn't work with Netty 4.x. Down-grading to 3.6.6.Final across the board made some Spark code not compile. If the build *keeps* io.netty:netty:3.6.6.Final as well, everything seems to work. Part of the reason seems to be that Netty 3.x used the old `org.jboss.netty` packages. This is less than ideal, but is no worse than the current situation. So this PR resolves the issue and improves the JAR hell, even if it leaves the existing theoretical Netty 3-vs-4 conflict: - Remove org.jboss.netty excludes where possible, for clarity; they're not needed except with Hadoop artifacts - Add io.netty:netty excludes where needed -- except, let akka keep its io.netty:netty - Change a bit of test code that actually depended on Netty 3.x, to use 4.x equivalent - Update SBT build accordingly A better change would be to update Akka far enough such that it agrees on Netty 4.x, but I don't know if that's feasible. Author: Sean Owen <sowen@cloudera.com> Closes #723 from srowen/SPARK-1789 and squashes the following commits: 43661b7 [Sean Owen] Update and add Netty excludes to prevent some JAR conflicts that cause test issues
* Unify GraphImpl RDDs + other graph load optimizationsAnkur Dave2014-05-1028-851/+1353
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR makes the following changes, primarily in e4fbd329aef85fe2c38b0167255d2a712893d683: 1. *Unify RDDs to avoid zipPartitions.* A graph used to be four RDDs: vertices, edges, routing table, and triplet view. This commit merges them down to two: vertices (with routing table), and edges (with replicated vertices). 2. *Avoid duplicate shuffle in graph building.* We used to do two shuffles when building a graph: one to extract routing information from the edges and move it to the vertices, and another to find nonexistent vertices referred to by edges. With this commit, the latter is done as a side effect of the former. 3. *Avoid no-op shuffle when joins are fully eliminated.* This is a side effect of unifying the edges and the triplet view. 4. *Join elimination for mapTriplets.* 5. *Ship only the needed vertex attributes when upgrading the triplet view.* If the triplet view already contains source attributes, and we now need both attributes, only ship destination attributes rather than re-shipping both. This is done in `ReplicatedVertexView#upgrade`. Author: Ankur Dave <ankurdave@gmail.com> Closes #497 from ankurdave/unify-rdds and squashes the following commits: 332ab43 [Ankur Dave] Merge remote-tracking branch 'apache-spark/master' into unify-rdds 4933e2e [Ankur Dave] Exclude RoutingTable from binary compatibility check 5ba8789 [Ankur Dave] Add GraphX upgrade guide from Spark 0.9.1 13ac845 [Ankur Dave] Merge remote-tracking branch 'apache-spark/master' into unify-rdds a04765c [Ankur Dave] Remove unnecessary toOps call 57202e8 [Ankur Dave] Replace case with pair parameter 75af062 [Ankur Dave] Add explicit return types 04d3ae5 [Ankur Dave] Convert implicit parameter to context bound c88b269 [Ankur Dave] Revert upgradeIterator to if-in-a-loop 0d3584c [Ankur Dave] EdgePartition.size should be val 2a928b2 [Ankur Dave] Set locality wait 10b3596 [Ankur Dave] Clean up public API ae36110 [Ankur Dave] Fix style errors e4fbd32 [Ankur Dave] Unify GraphImpl RDDs + other graph load optimizations d6d60e2 [Ankur Dave] In GraphLoader, coalesce to minEdgePartitions 62c7b78 [Ankur Dave] In Analytics, take PageRank numIter d64e8d4 [Ankur Dave] Log current Pregel iteration
* [SPARK-1690] Tolerating empty elements when saving Python RDD to text filesKan Zhang2014-05-102-2/+11
| | | | | | | | | | | Tolerate empty strings in PythonRDD Author: Kan Zhang <kzhang@apache.org> Closes #644 from kanzhang/SPARK-1690 and squashes the following commits: c62ad33 [Kan Zhang] Adding Python doctest 473ec4b [Kan Zhang] [SPARK-1690] Tolerating empty elements when saving Python RDD to text files
* Add Python includes to path before depickling broadcast valuesBouke van der Bijl2014-05-102-12/+12
| | | | | | | | | | | | This fixes https://issues.apache.org/jira/browse/SPARK-1731 by adding the Python includes to the PYTHONPATH before depickling the broadcast values @airhorns Author: Bouke van der Bijl <boukevanderbijl@gmail.com> Closes #656 from bouk/python-includes-before-broadcast and squashes the following commits: 7b0dfe4 [Bouke van der Bijl] Add Python includes to path before depickling broadcast values
* fix broken in link in python docsAndy Konwinski2014-05-101-1/+1
| | | | | | | | Author: Andy Konwinski <andykonwinski@gmail.com> Closes #650 from andyk/python-docs-link-fix and squashes the following commits: a1f9d51 [Andy Konwinski] fix broken in link in python docs
* SPARK-1708. Add a ClassTag on Serializer and things that depend on itMatei Zaharia2014-05-1022-72/+103
| | | | | | | | | | | | | | | | | This pull request contains a rebased patch from @heathermiller (https://github.com/heathermiller/spark/pull/1) to add ClassTags on Serializer and types that depend on it (Broadcast and AccumulableCollection). Putting these in the public API signatures now will allow us to use Scala Pickling for serialization down the line without breaking binary compatibility. One question remaining is whether we also want them on Accumulator -- Accumulator is passed as part of a bigger Task or TaskResult object via the closure serializer so it doesn't seem super useful to add the ClassTag there. Broadcast and AccumulableCollection in contrast were being serialized directly. CC @rxin, @pwendell, @heathermiller Author: Matei Zaharia <matei@databricks.com> Closes #700 from mateiz/spark-1708 and squashes the following commits: 1a3d8b0 [Matei Zaharia] Use fake ClassTag in Java 3b449ed [Matei Zaharia] test fix 2209a27 [Matei Zaharia] Code style fixes 9d48830 [Matei Zaharia] Add a ClassTag on Serializer and things that depend on it
* [SPARK-1778] [SQL] Add 'limit' transformation to SchemaRDD.Takuya UESHIN2014-05-102-0/+15
| | | | | | | | | | Add `limit` transformation to `SchemaRDD`. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #711 from ueshin/issues/SPARK-1778 and squashes the following commits: 33169df [Takuya UESHIN] Add 'limit' transformation to SchemaRDD.
* [SQL] Upgrade parquet library.Michael Armbrust2014-05-102-2/+2
| | | | | | | | | | | | I think we are hitting this issue in some perf tests: https://github.com/Parquet/parquet-mr/commit/6aed5288fd4a1398063a5a219b2ae4a9f71b02cf Credit to @aarondav ! Author: Michael Armbrust <michael@databricks.com> Closes #684 from marmbrus/upgradeParquet and squashes the following commits: e10a619 [Michael Armbrust] Upgrade parquet library.
* [SPARK-1644] The org.datanucleus:* should not be packaged into ↵witgo2014-05-102-5/+7
| | | | | | | | | | | | | spark-assembly-*.jar Author: witgo <witgo@qq.com> Closes #688 from witgo/SPARK-1644 and squashes the following commits: 56ad6ac [witgo] review commit 87c03e4 [witgo] Merge branch 'master' of https://github.com/apache/spark into SPARK-1644 6ffa7e4 [witgo] review commit a597414 [witgo] The org.datanucleus:* should not be packaged into spark-assembly-*.jar
* SPARK-1686: keep schedule() calling in the main threadCodingCat2014-05-091-3/+12
| | | | | | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-1686 moved from original JIRA (by @markhamstra): In deploy.master.Master, the completeRecovery method is the last thing to be called when a standalone Master is recovering from failure. It is responsible for resetting some state, relaunching drivers, and eventually resuming its scheduling duties. There are currently four places in Master.scala where completeRecovery is called. Three of them are from within the actor's receive method, and aren't problems. The last starts from within receive when the ElectedLeader message is received, but the actual completeRecovery() call is made from the Akka scheduler. That means that it will execute on a different scheduler thread, and Master itself will end up running (i.e., schedule() ) from that Akka scheduler thread. In this PR, I added a new master message TriggerSchedule to trigger the "local" call of schedule() in the scheduler thread Author: CodingCat <zhunansjtu@gmail.com> Closes #639 from CodingCat/SPARK-1686 and squashes the following commits: 81bb4ca [CodingCat] rename variable 69e0a2a [CodingCat] style fix 36a2ac0 [CodingCat] address Aaron's comments ec9b7bb [CodingCat] address the comments 02b37ca [CodingCat] keep schedule() calling in the main thread
* SPARK-1770: Revert accidental(?) fixAaron Davidson2014-05-091-2/+2
| | | | | | | | | | | | | Looks like this change was accidentally committed here: https://github.com/apache/spark/commit/06b15baab25951d124bbe6b64906f4139e037deb but the change does not show up in the PR itself (#704). Other than not intending to go in with that PR, this also broke the test JavaAPISuite.repartition. Author: Aaron Davidson <aaron@databricks.com> Closes #716 from aarondav/shufflerand and squashes the following commits: b1cf70b [Aaron Davidson] SPARK-1770: Revert accidental(?) fix
* [SPARK-1760]: fix building spark with maven documentationwitgo2014-05-091-1/+1
| | | | | | | | Author: witgo <witgo@qq.com> Closes #712 from witgo/building-with-maven and squashes the following commits: 215523b [witgo] fix building spark with maven documentation
* Converted bang to ask to avoid scary warning when a block is removedTathagata Das2014-05-081-1/+1
| | | | | | | | | | | | | | | | | | Removing a block through the blockmanager gave a scary warning messages in the driver. ``` 2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true 2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true 2014-05-08 20:16:19,172 WARN BlockManagerMasterActor: Got unknown message: true ``` This is because the [BlockManagerSlaveActor](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala#L44) would send back an acknowledgement ("true"). But the BlockManagerMasterActor would have sent the RemoveBlock message as a send, not as ask(), so would reject the receiver "true" as a unknown message. @pwendell Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #708 from tdas/bm-fix and squashes the following commits: ed4ef15 [Tathagata Das] Converted bang to ask to avoid scary warning when a block is removed.
* MINOR: Removing dead code.Patrick Wendell2014-05-081-1/+0
| | | | Meant to do this when patching up the last merge.
* SPARK-1775: Unneeded lock in ShuffleMapTask.deserializeInfoSandeep2014-05-081-9/+7
| | | | | | | | | | This was used in the past to have a cache of deserialized ShuffleMapTasks, but that's been removed, so there's no need for a lock. It slows down Spark when task descriptions are large, e.g. due to large lineage graphs or local variables. Author: Sandeep <sandeep@techaddict.me> Closes #707 from techaddict/SPARK-1775 and squashes the following commits: 18d8ebf [Sandeep] SPARK-1775: Unneeded lock in ShuffleMapTask.deserializeInfo This was used in the past to have a cache of deserialized ShuffleMapTasks, but that's been removed, so there's no need for a lock. It slows down Spark when task descriptions are large, e.g. due to large lineage graphs or local variables.
* SPARK-1565 (Addendum): Replace `run-example` with `spark-submit`.Patrick Wendell2014-05-087-65/+37
| | | | | | | | | | | | | Gives a nicely formatted message to the user when `run-example` is run to tell them to use `spark-submit`. Author: Patrick Wendell <pwendell@gmail.com> Closes #704 from pwendell/examples and squashes the following commits: 1996ee8 [Patrick Wendell] Feedback form Andrew 3eb7803 [Patrick Wendell] Suggestions from TD 2474668 [Patrick Wendell] SPARK-1565 (Addendum): Replace `run-example` with `spark-submit`.
* [SPARK-1631] Correctly set the Yarn app name when launching the AM.Marcelo Vanzin2014-05-081-3/+3
| | | | | | | | Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #539 from vanzin/yarn-app-name and squashes the following commits: 7d1ca4f [Marcelo Vanzin] [SPARK-1631] Correctly set the Yarn app name when launching the AM.
* [SPARK-1755] Respect SparkSubmit --name on YARNAndrew Or2014-05-082-8/+11
| | | | | | | | | | | | | | | | | | | | Right now, SparkSubmit ignores the `--name` flag for both yarn-client and yarn-cluster. This is a bug. In client mode, SparkSubmit treats `--name` as a [cluster config](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L170) and does not propagate this to SparkContext. In cluster mode, SparkSubmit passes this flag to `org.apache.spark.deploy.yarn.Client`, which only uses it for the [YARN ResourceManager](https://github.com/apache/spark/blob/master/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/Client.scala#L80), but does not propagate this to SparkContext. This PR ensures that `spark.app.name` is always set if SparkSubmit receives the `--name` flag, which is what the usage promises. This makes it possible for applications to start a SparkContext with an empty conf `val sc = new SparkContext(new SparkConf)`, and inherit the app name from SparkSubmit. Tested both modes on a YARN cluster. Author: Andrew Or <andrewor14@gmail.com> Closes #699 from andrewor14/yarn-app-name and squashes the following commits: 98f6a79 [Andrew Or] Fix tests dea932f [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-app-name c86d9ca [Andrew Or] Respect SparkSubmit --name on YARN
* Include the sbin/spark-config.sh in spark-executorBouke van der Bijl2014-05-081-0/+3
| | | | | | | | | | | | | This is needed because broadcast values are broken on pyspark on Mesos, it tries to import pyspark but can't, as the PYTHONPATH is not set due to changes in ff5be9a4 https://issues.apache.org/jira/browse/SPARK-1725 Author: Bouke van der Bijl <boukevanderbijl@gmail.com> Closes #651 from bouk/include-spark-config-in-mesos-executor and squashes the following commits: b2f1295 [Bouke van der Bijl] Inline PYTHONPATH in spark-executor eedbbcc [Bouke van der Bijl] Include the sbin/spark-config.sh in spark-executor
* Bug fix of sparse vector conversionFunes2014-05-082-1/+14
| | | | | | | | | | | | | | | Fixed a small bug caused by the inconsistency of index/data array size and vector length. Author: Funes <tianshaocun@gmail.com> Author: funes <tianshaocun@gmail.com> Closes #661 from funes/bugfix and squashes the following commits: edb2b9d [funes] remove unused import 75dced3 [Funes] update test case d129a66 [Funes] Add test for sparse breeze by vector builder 64e7198 [Funes] Copy data only when necessary b85806c [Funes] Bug fix of sparse vector conversion
* [SPARK-1157][MLlib] Bug fix: lossHistory should exclude rejection steps, and ↵DB Tsai2014-05-082-48/+30
| | | | | | | | | | | | | | remove miniBatch Getting the lossHistory from Breeze's API which already excludes the rejection steps in line search. Also, remove the miniBatch in LBFGS since those quasi-Newton methods approximate the inverse of Hessian. It doesn't make sense if the gradients are computed from a varying objective. Author: DB Tsai <dbtsai@alpinenow.com> Closes #582 from dbtsai/dbtsai-lbfgs-bug and squashes the following commits: 9cc6cf9 [DB Tsai] Removed the miniBatch in LBFGS. 1ba6a33 [DB Tsai] Formatting the code. d72c679 [DB Tsai] Using Breeze's states to get the loss.
* MLlib documentation fixDB Tsai2014-05-082-5/+5
| | | | | | | | | | Fixed the documentation for that `loadLibSVMData` is changed to `loadLibSVMFile`. Author: DB Tsai <dbtsai@alpinenow.com> Closes #703 from dbtsai/dbtsai-docfix and squashes the following commits: 71dd508 [DB Tsai] loadLibSVMData is changed to loadLibSVMFile
* [SPARK-1754] [SQL] Add missing arithmetic DSL operations.Takuya UESHIN2014-05-082-1/+19
| | | | | | | | | | | | | Add missing arithmetic DSL operations: `unary_-`, `%`. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #689 from ueshin/issues/SPARK-1754 and squashes the following commits: a09ef69 [Takuya UESHIN] Add also missing ! (not) operation. f73ae2c [Takuya UESHIN] Remove redundant tests. 5b3f087 [Takuya UESHIN] Add tests relating DSL operations. e09c5b8 [Takuya UESHIN] Add missing arithmetic DSL operations.
* Fixing typo in als.pyEvan Sparks2014-05-081-1/+1
| | | | | | | | | | XtY should be Xty. Author: Evan Sparks <evan.sparks@gmail.com> Closes #696 from etrain/patch-2 and squashes the following commits: 634cb8d [Evan Sparks] Fixing typo in als.py
* [SPARK-1745] Move interrupted flag from TaskContext constructor (minor)Andrew Or2014-05-085-22/+17
| | | | | | | | | | | | | | | It makes little sense to start a TaskContext that is interrupted. Indeed, I searched for all use cases of it and didn't find a single instance in which `interrupted` is true on construction. This was inspired by reviewing #640, which adds an additional `@volatile var completed` that is similar. These are not the most urgent changes, but I wanted to push them out before I forget. Author: Andrew Or <andrewor14@gmail.com> Closes #675 from andrewor14/task-context and squashes the following commits: 9575e02 [Andrew Or] Add space 69455d1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into task-context c471490 [Andrew Or] Oops, removed one flag too many. Adding it back. 85311f8 [Andrew Or] Move interrupted flag from TaskContext constructor
* SPARK-1565, update examples to be used with spark-submit script.Prashant Sharma2014-05-0856-480/+405
| | | | | | | | | | | | | | | | Commit for initial feedback, basically I am curious if we should prompt user for providing args esp. when its mandatory. And can we skip if they are not ? Also few other things that did not work like `bin/spark-submit examples/target/scala-2.10/spark-examples-1.0.0-SNAPSHOT-hadoop1.0.4.jar --class org.apache.spark.examples.SparkALS --arg 100 500 10 5 2` Not all the args get passed properly, may be I have messed up something will try to sort it out hopefully. Author: Prashant Sharma <prashant.s@imaginea.com> Closes #552 from ScrapCodes/SPARK-1565/update-examples and squashes the following commits: 669dd23 [Prashant Sharma] Review comments 2727e70 [Prashant Sharma] SPARK-1565, update examples to be used with spark-submit script.
* [SQL] Improve SparkSQL AggregatesMichael Armbrust2014-05-084-10/+96
| | | | | | | | | | | * Add native min/max (was using hive before). * Handle nulls correctly in Avg and Sum. Author: Michael Armbrust <michael@databricks.com> Closes #683 from marmbrus/aggFixes and squashes the following commits: 64fe30b [Michael Armbrust] Improve SparkSQL Aggregates * Add native min/max (was using hive before). * Handle nulls correctly in Avg and Sum.
* Use numpy directly for matrix multiply.Evan Sparks2014-05-081-8/+7
| | | | | | | | | | | | | | Using matrix multiply to compute XtX and XtY yields a 5-20x speedup depending on problem size. For example - the following takes 19s locally after this change vs. 5m21s before the change. (16x speedup). bin/pyspark examples/src/main/python/als.py local[8] 1000 1000 50 10 10 Author: Evan Sparks <evan.sparks@gmail.com> Closes #687 from etrain/patch-1 and squashes the following commits: e094dbc [Evan Sparks] Touching only diaganols on update. d1ab9b6 [Evan Sparks] Use numpy directly for matrix multiply.
* SPARK-1668: Add implicit preference as an option to examples/MovieLensALSSandeep2014-05-081-9/+46
| | | | | | | | | | | | | | | | Add --implicitPrefs as an command-line option to the example app MovieLensALS under examples/ Author: Sandeep <sandeep@techaddict.me> Closes #597 from techaddict/SPARK-1668 and squashes the following commits: 8b371dc [Sandeep] Second Pass on reviews by mengxr eca9d37 [Sandeep] based on mengxr's suggestions 937e54c [Sandeep] Changes 5149d40 [Sandeep] Changes based on review 1dd7657 [Sandeep] use mean() 42444d7 [Sandeep] Based on Suggestions by mengxr e3082fa [Sandeep] SPARK-1668: Add implicit preference as an option to examples/MovieLensALS Add --implicitPrefs as an command-line option to the example app MovieLensALS under examples/
* SPARK-1544 Add support for deep decision trees.Manish Amde2014-05-075-33/+177
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | @etrain and I came with a PR for arbitrarily deep decision trees at the cost of multiple passes over the data at deep tree levels. To summarize: 1) We take a parameter that indicates the amount of memory users want to reserve for computation on each worker (and 2x that at the driver). 2) Using that information, we calculate two things - the maximum depth to which we train as usual (which is, implicitly, the maximum number of nodes we want to train in parallel), and the size of the groups we should use in the case where we exceed this depth. cc: @atalwalkar, @hirakendu, @mengxr Author: Manish Amde <manish9ue@gmail.com> Author: manishamde <manish9ue@gmail.com> Author: Evan Sparks <sparks@cs.berkeley.edu> Closes #475 from manishamde/deep_tree and squashes the following commits: 968ca9d [Manish Amde] merged master 7fc9545 [Manish Amde] added docs ce004a1 [Manish Amde] minor formatting b27ad2c [Manish Amde] formatting 426bb28 [Manish Amde] programming guide blurb 8053fed [Manish Amde] more formatting 5eca9e4 [Manish Amde] grammar 4731cda [Manish Amde] formatting 5e82202 [Manish Amde] added documentation, fixed off by 1 error in max level calculation cbd9f14 [Manish Amde] modified scala.math to math dad9652 [Manish Amde] removed unused imports e0426ee [Manish Amde] renamed parameter 718506b [Manish Amde] added unit test 1517155 [Manish Amde] updated documentation 9dbdabe [Manish Amde] merge from master 719d009 [Manish Amde] updating user documentation fecf89a [manishamde] Merge pull request #6 from etrain/deep_tree 0287772 [Evan Sparks] Fixing scalastyle issue. 2f1e093 [Manish Amde] minor: added doc for maxMemory parameter 2f6072c [manishamde] Merge pull request #5 from etrain/deep_tree abc5a23 [Evan Sparks] Parameterizing max memory. 50b143a [Manish Amde] adding support for very deep trees
* Update GradientDescentSuite.scalabaishuo(白硕)2014-05-071-3/+3
| | | | | | | | | | | | use more faster way to construct an array Author: baishuo(白硕) <vc_java@hotmail.com> Closes #588 from baishuo/master and squashes the following commits: 45b95fb [baishuo(白硕)] Update GradientDescentSuite.scala c03b61c [baishuo(白硕)] Update GradientDescentSuite.scala b666d27 [baishuo(白硕)] Update GradientDescentSuite.scala
* [SPARK-1743][MLLIB] add loadLibSVMFile and saveAsLibSVMFile to pysparkXiangrui Meng2014-05-072-2/+178
| | | | | | | | | | | | | Make loading/saving labeled data easier for pyspark users. Also changed type check in `SparseVector` to allow numpy integers. Author: Xiangrui Meng <meng@databricks.com> Closes #672 from mengxr/pyspark-mllib-util and squashes the following commits: 2943fa7 [Xiangrui Meng] format docs d61668d [Xiangrui Meng] add loadLibSVMFile and saveAsLibSVMFile to pyspark
* SPARK-1569 Spark on Yarn, authentication broken by pr299Thomas Graves2014-05-071-19/+30
| | | | | | | | | | | | | | Pass the configs as java options since the executor needs to know before it registers whether to create the connection using authentication or not. We could see about passing only the authentication configs but for now I just had it pass them all. I also updating it to use a list to construct the command to make it the same as ClientBase and avoid any issues with spaces. Author: Thomas Graves <tgraves@apache.org> Closes #649 from tgravescs/SPARK-1569 and squashes the following commits: 0178ab8 [Thomas Graves] add akka settings 22a8735 [Thomas Graves] Change to only path spark.auth* configs 8ccc1d4 [Thomas Graves] SPARK-1569 Spark on Yarn, authentication broken
* [SPARK-1688] Propagate PySpark worker stderr to driverAndrew Or2014-05-074-101/+123
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | When at least one of the following conditions is true, PySpark cannot be loaded: 1. PYTHONPATH is not set 2. PYTHONPATH does not contain the python directory (or jar, in the case of YARN) 3. The jar does not contain pyspark files (YARN) 4. The jar does not contain py4j files (YARN) However, we currently throw the same random `java.io.EOFException` for all of the above cases, when trying to read from the python daemon's output. This message is super unhelpful. This PR includes the python stderr and the PYTHONPATH in the exception propagated to the driver. Now, the exception message looks something like: ``` Error from python worker: : No module named pyspark PYTHONPATH was: /path/to/spark/python:/path/to/some/jar java.io.EOFException <stack trace> ``` whereas before it was just ``` java.io.EOFException <stack trace> ``` Author: Andrew Or <andrewor14@gmail.com> Closes #603 from andrewor14/pyspark-exception and squashes the following commits: 10d65d3 [Andrew Or] Throwable -> Exception, worker -> daemon 862d1d7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception a5ed798 [Andrew Or] Use block string and interpolation instead of var (minor) cc09c45 [Andrew Or] Account for the fact that the python daemon may not have terminated yet 444f019 [Andrew Or] Use the new RedirectThread + include system PYTHONPATH aab00ae [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception 0cc2402 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception 783efe2 [Andrew Or] Make python daemon stderr indentation consistent 9524172 [Andrew Or] Avoid potential NPE / error stream contention + Move things around 29f9688 [Andrew Or] Add back original exception type e92d36b [Andrew Or] Include python worker stderr in the exception propagated to the driver 7c69360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception cdbc185 [Andrew Or] Fix python attribute not found exception when PYTHONPATH is not set dcc0353 [Andrew Or] Check both python and system environment variables for PYTHONPATH 6c09c21 [Andrew Or] Validate PYTHONPATH and PySpark modules before starting python workers
* Typo fix: fetchting -> fetchingAndrew Ash2014-05-071-1/+1
| | | | | | | | Author: Andrew Ash <andrew@andrewash.com> Closes #680 from ash211/patch-3 and squashes the following commits: 9ce3746 [Andrew Ash] Typo fix: fetchting -> fetching
* Nicer logging for SecurityManager startupAndrew Ash2014-05-071-2/+3
| | | | | | | | | | Happy to open a jira ticket if you'd like to track one there. Author: Andrew Ash <andrew@andrewash.com> Closes #678 from ash211/SecurityManagerLogging and squashes the following commits: 2aa0b7a [Andrew Ash] Nicer logging for SecurityManager startup
* [SQL] Fix Performance Issue in data type castingCheng Hao2014-05-071-1/+1
| | | | | | | | | | Using lazy val object instead of function in the class Cast, which improved the performance nearly by 2X in my local micro-benchmark. Author: Cheng Hao <hao.cheng@intel.com> Closes #679 from chenghao-intel/fix_type_casting and squashes the following commits: 71b0902 [Cheng Hao] using lazy val object instead of function for data type casting
* SPARK-1579: Clean up PythonRDD and avoid swallowing IOExceptionsAaron Davidson2014-05-075-107/+141
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch includes several cleanups to PythonRDD, focused around fixing [SPARK-1579](https://issues.apache.org/jira/browse/SPARK-1579) cleanly. Listed in order of approximate importance: - The Python daemon waits for Spark to close the socket before exiting, in order to avoid causing spurious IOExceptions in Spark's `PythonRDD::WriterThread`. - Removes the Python Monitor Thread, which polled for task cancellations in order to kill the Python worker. Instead, we do this in the onCompleteCallback, since this is guaranteed to be called during cancellation. - Adds a "completed" variable to TaskContext to avoid the issue noted in [SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), where onCompleteCallbacks may be execution-order dependent. Along with this, I removed the "context.interrupted = true" flag in the onCompleteCallback. - Extracts PythonRDD::WriterThread to its own class. Since this patch provides an alternative solution to [SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), I did test it with ``` sc.textFile("latlon.tsv").take(5) ``` many times without error. Additionally, in order to test the unswallowed exceptions, I performed ``` sc.textFile("s3n://<big file>").count() ``` and cut my internet during execution. Prior to this patch, we got the "stdin writer exited early" message, which was unhelpful. Now, we get the SocketExceptions propagated through Spark to the user and get proper (though unsuccessful) task retries. Author: Aaron Davidson <aaron@databricks.com> Closes #640 from aarondav/pyspark-io and squashes the following commits: b391ff8 [Aaron Davidson] Detect "clean socket shutdowns" and stop waiting on the socket c0c49da [Aaron Davidson] SPARK-1579: Clean up PythonRDD and avoid swallowing IOExceptions
* [SPARK-1460] Returning SchemaRDD instead of normal RDD on Set operations...Kan Zhang2014-05-077-22/+246
| | | | | | | | | | | | ... that do not change schema Author: Kan Zhang <kzhang@apache.org> Closes #448 from kanzhang/SPARK-1460 and squashes the following commits: 111e388 [Kan Zhang] silence MiMa errors in EdgeRDD and VertexRDD 91dc787 [Kan Zhang] Taking into account newly added Ordering param 79ed52a [Kan Zhang] [SPARK-1460] Returning SchemaRDD on Set operations that do not change schema
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