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## What changes were proposed in this pull request?
Document RDD.pipe semantics; don't execute process for empty input partitions.
Note this includes the fix in https://github.com/apache/spark/pull/14256 because it's necessary to even test this. One or the other will merge the fix.
## How was this patch tested?
Jenkins tests including new test.
Author: Sean Owen <sowen@cloudera.com>
Closes #14260 from srowen/SPARK-16613.
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SparkSubmitSuite
## What changes were proposed in this pull request?
This change moves the include jar test from R to SparkSubmitSuite and uses a dynamically compiled jar. This helps us remove the binary jar from the R package and solves both the CRAN warnings and the lack of source being available for this jar.
## How was this patch tested?
SparkR unit tests, SparkSubmitSuite, check-cran.sh
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes #14243 from shivaram/sparkr-jar-move.
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String)`
## What changes were proposed in this pull request?
Currently `RDD.pipe(command: String)`:
- works only when the command is specified without any options, such as `RDD.pipe("wc")`
- does NOT work when the command is specified with some options, such as `RDD.pipe("wc -l")`
This is a regression from Spark 1.6.
This patch adds back the tokenization process in `RDD.pipe(command: String)` to fix this regression.
## How was this patch tested?
Added a test which:
- would pass in `1.6`
- _[prior to this patch]_ would fail in `master`
- _[after this patch]_ would pass in `master`
Author: Liwei Lin <lwlin7@gmail.com>
Closes #14256 from lw-lin/rdd-pipe.
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minExecutors
## What changes were proposed in this pull request?
Currently if `spark.dynamicAllocation.initialExecutors` is less than `spark.dynamicAllocation.minExecutors`, Spark will automatically pick the minExecutors without any warning. While in 1.6 Spark will throw exception if configured like this. So here propose to add warning log if these parameters are configured invalidly.
## How was this patch tested?
Unit test added to verify the scenario.
Author: jerryshao <sshao@hortonworks.com>
Closes #14149 from jerryshao/SPARK-16435.
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## What changes were proposed in this pull request?
It's possible to also change the callers to not pass in empty chunks, but it seems cleaner to just allow `ChunkedByteBuffer` to handle empty arrays. cc JoshRosen
## How was this patch tested?
Unit tests, also checked that the original reproduction case in https://github.com/apache/spark/pull/11748#issuecomment-230760283 is resolved.
Author: Eric Liang <ekl@databricks.com>
Closes #14099 from ericl/spark-16432.
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in UI
## What changes were proposed in this pull request?
This moves over old PR https://github.com/apache/spark/pull/13664 to target master rather than branch-1.6.
Added links to logs (or an indication that there are no logs) for entries which list an executor in the stage details page of the UI.
This helps streamline the workflow where a user views a stage details page and determines that they would like to see the associated executor log for further examination. Previously, a user would have to cross reference the executor id listed on the stage details page with the corresponding entry on the executors tab.
Link to the JIRA: https://issues.apache.org/jira/browse/SPARK-15885
## How was this patch tested?
Ran existing unit tests.
Ran test queries on a platform which did not record executor logs and again on a platform which did record executor logs and verified that the new table column was empty and links to the logs (which were verified as linking to the appropriate files), respectively.
Attached is a screenshot of the UI page with no links, with the new columns highlighted. Additional screenshot of these columns with the populated links.
Without links:
With links:
This contribution is my original work and I license the work to the project under the Apache Spark project's open source license.
Author: Tom Magrino <tmagrino@fb.com>
Closes #13861 from tmagrino/uilogstweak.
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## What changes were proposed in this pull request?
This patch updates the failure handling logic so Spark executor does not crash when seeing LinkageError.
## How was this patch tested?
Added an end-to-end test in FailureSuite.
Author: petermaxlee <petermaxlee@gmail.com>
Closes #13982 from petermaxlee/SPARK-16304.
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Process.destroyForcibly() if and only if Process.destroy() fails
## What changes were proposed in this pull request?
Utils.terminateProcess should `destroy()` first and only fall back to `destroyForcibly()` if it fails. It's kind of bad that we're force-killing executors -- and only in Java 8. See JIRA for an example of the impact: no shutdown
While here: `Utils.waitForProcess` should use the Java 8 method if available instead of a custom implementation.
## How was this patch tested?
Existing tests, which cover the force-kill case, and Amplab tests, which will cover both Java 7 and Java 8 eventually. However I tested locally on Java 8 and the PR builder will try Java 7 here.
Author: Sean Owen <sowen@cloudera.com>
Closes #13973 from srowen/SPARK-16182.
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than 4 executors
## What changes were proposed in this pull request?
Before this change, when you turn on blacklisting with `spark.scheduler.executorTaskBlacklistTime`, but you have fewer than `spark.task.maxFailures` executors, you can end with a job "hung" after some task failures.
Whenever a taskset is unable to schedule anything on resourceOfferSingleTaskSet, we check whether the last pending task can be scheduled on *any* known executor. If not, the taskset (and any corresponding jobs) are failed.
* Worst case, this is O(maxTaskFailures + numTasks). But unless many executors are bad, this should be small
* This does not fail as fast as possible -- when a task becomes unschedulable, we keep scheduling other tasks. This is to avoid an O(numPendingTasks * numExecutors) operation
* Also, it is conceivable this fails too quickly. You may be 1 millisecond away from unblacklisting a place for a task to run, or acquiring a new executor.
## How was this patch tested?
Added unit test which failed before the change, ran new test 5k times manually, ran all scheduler tests manually, and the full suite via jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13603 from squito/progress_w_few_execs_and_blacklist.
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Executor ID
## What changes were proposed in this pull request?
Previously, the TaskLocation implementation would not allow for executor ids which include underscores. This tweaks the string split used to get the hostname and executor id, allowing for underscores in the executor id.
This addresses the JIRA found here: https://issues.apache.org/jira/browse/SPARK-16148
This is moved over from a previous PR against branch-1.6: https://github.com/apache/spark/pull/13857
## How was this patch tested?
Ran existing unit tests for core and streaming. Manually ran a simple streaming job with an executor whose id contained underscores and confirmed that the job ran successfully.
This is my original work and I license the work to the project under the project's open source license.
Author: Tom Magrino <tmagrino@fb.com>
Closes #13858 from tmagrino/fixtasklocation.
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to existing hosts
## What changes were proposed in this pull request?
TaskSchedulerImpl used to only set `newExecAvailable` when a new *host* was added, not when a new executor was added to an existing host. It also didn't update some internal state tracking live executors until a task was scheduled on the executor. This patch changes it to properly update as soon as it knows about a new executor.
## How was this patch tested?
added a unit test, ran everything via jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13826 from squito/SPARK-16106_executorByHosts.
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## What changes were proposed in this pull request?
TaskManagerSuite "Kill other task attempts when one attempt belonging to the same task succeeds" was flaky. When checking whether a task is speculatable, at least one millisecond must pass since the task was submitted. Use a manual clock to avoid the problem.
I noticed these tests were leaving lots of threads lying around as well (which prevented me from running the test repeatedly), so I fixed that too.
## How was this patch tested?
Ran the test 1k times on my laptop, passed every time (it failed about 20% of the time before this).
Author: Imran Rashid <irashid@cloudera.com>
Closes #13848 from squito/fix_flaky_taskmanagersuite.
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## The problem
Before this change, if either of the following cases happened to a task , the task would be marked as `FAILED` instead of `KILLED`:
- the task was killed before it was deserialized
- `executor.kill()` marked `taskRunner.killed`, but before calling `task.killed()` the worker thread threw the `TaskKilledException`
The reason is, in the `catch` block of the current [Executor.TaskRunner](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/executor/Executor.scala#L362)'s implementation, we are mistakenly catching:
```scala
case _: TaskKilledException | _: InterruptedException if task.killed => ...
```
the semantics of which is:
- **(**`TaskKilledException` **OR** `InterruptedException`**)** **AND** `task.killed`
Then when `TaskKilledException` is thrown but `task.killed` is not marked, we would mark the task as `FAILED` (which should really be `KILLED`).
## What changes were proposed in this pull request?
This patch alters the catch condition's semantics from:
- **(**`TaskKilledException` **OR** `InterruptedException`**)** **AND** `task.killed`
to
- `TaskKilledException` **OR** **(**`InterruptedException` **AND** `task.killed`**)**
so that we can catch `TaskKilledException` correctly and mark the task as `KILLED` correctly.
## How was this patch tested?
Added unit test which failed before the change, ran new test 1000 times manually
Author: Liwei Lin <lwlin7@gmail.com>
Closes #13685 from lw-lin/fix-task-killed.
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## What changes were proposed in this pull request?
Since SPARK-13220(Deprecate "yarn-client" and "yarn-cluster"), YarnClusterSuite doesn't test "yarn cluster" mode correctly.
This pull request fixes it.
## How was this patch tested?
Unit test
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: peng.zhang <peng.zhang@xiaomi.com>
Closes #13836 from renozhang/SPARK-16125-test-yarn-cluster-mode.
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## 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.
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popVariance/popStdev
## What changes were proposed in this pull request?
In Spark-11490, `variance/stdev` are redefined as the **sample** `variance/stdev` instead of population ones. This PR updates the other old documentations to prevent users from misunderstanding. This will update the following Scala/Java API docs.
- http://spark.apache.org/docs/2.0.0-preview/api/scala/index.html#org.apache.spark.api.java.JavaDoubleRDD
- http://spark.apache.org/docs/2.0.0-preview/api/scala/index.html#org.apache.spark.rdd.DoubleRDDFunctions
- http://spark.apache.org/docs/2.0.0-preview/api/scala/index.html#org.apache.spark.util.StatCounter
- http://spark.apache.org/docs/2.0.0-preview/api/java/org/apache/spark/api/java/JavaDoubleRDD.html
- http://spark.apache.org/docs/2.0.0-preview/api/java/org/apache/spark/rdd/DoubleRDDFunctions.html
- http://spark.apache.org/docs/2.0.0-preview/api/java/org/apache/spark/util/StatCounter.html
Also, this PR adds them `popVariance` and `popStdev` functions clearly.
## How was this patch tested?
Pass the updated Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #13403 from dongjoon-hyun/SPARK-15660.
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## What changes were proposed in this pull request?
This fixes SerializationDebugger to not recurse forever when `writeReplace` returns an object of the same class, which is the case for at least the `SQLMetrics` class.
See also the OpenJDK unit tests on the behavior of recursive `writeReplace()`:
https://github.com/openjdk-mirror/jdk7u-jdk/blob/f4d80957e89a19a29bb9f9807d2a28351ed7f7df/test/java/io/Serializable/nestedReplace/NestedReplace.java
cc davies cloud-fan
## How was this patch tested?
Unit tests for SerializationDebugger.
Author: Eric Liang <ekl@databricks.com>
Closes #13814 from ericl/spark-16003.
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## What changes were proposed in this pull request?
Three changes here -- first two were causing failures w/ BlacklistIntegrationSuite
1. The testing framework didn't include the reviveOffers thread, so the test which involved delay scheduling might never submit offers late enough for the delay scheduling to kick in. So added in the periodic revive offers, just like the real scheduler.
2. `assertEmptyDataStructures` would occasionally fail, because it appeared there was still an active job. This is because in DAGScheduler, the jobWaiter is notified of the job completion before the data structures are cleaned up. Most of the time the test code that is waiting on the jobWaiter won't become active until after the data structures are cleared, but occasionally the race goes the other way, and the assertions fail.
3. `DAGSchedulerSuite` was not stopping all the inner parts it was setting up, so each test was leaking a number of threads. So we stop those parts too.
4. Turns out that `assertMapOutputAvailable` is not terribly useful in this framework -- most of the places I was trying to use it suffer from some race.
5. When there is an exception in the backend, try to improve the error msg a little bit. Before the exception was printed to the console, but the test would fail w/ a timeout, and the logs wouldn't show anything.
## How was this patch tested?
I ran all the tests in `BlacklistIntegrationSuite` 5k times and everything in `DAGSchedulerSuite` 1k times on my laptop. Also I ran a full jenkins build with `BlacklistIntegrationSuite` 500 times and `DAGSchedulerSuite` 50 times, see https://github.com/apache/spark/pull/13548. (I tried more times but jenkins timed out.)
To check for more leaked threads, I added some code to dump the list of all threads at the end of each test in DAGSchedulerSuite, which is how I discovered the mapOutputTracker and eventLoop were leaking threads. (I removed that code from the final pr, just part of the testing.)
And I'll run Jenkins on this a couple of times to do one more check.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13565 from squito/blacklist_extra_tests.
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## What changes were proposed in this pull request?
[SPARK-15395](https://issues.apache.org/jira/browse/SPARK-15395) changes the behavior that how the driver gets the executor host and the driver will get the executor IP address instead of the host name. This PR just sends the hostname from executors to driver so that driver can pass it to TaskScheduler.
## How was this patch tested?
Existing unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes #13741 from zsxwing/SPARK-16017.
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## What changes were proposed in this pull request?
This pull request refactors parts of the DAGScheduler to improve readability, focusing on the code around stage creation. One goal of this change it to make it clearer which functions may create new stages (as opposed to looking up stages that already exist). There are no functionality changes in this pull request. In more detail:
* shuffleToMapStage was renamed to shuffleIdToMapStage (when reading the existing code I have sometimes struggled to remember what the key is -- is it a stage? A stage id? This change is intended to avoid that confusion)
* Cleaned up the code to create shuffle map stages. Previously, creating a shuffle map stage involved 3 different functions (newOrUsedShuffleStage, newShuffleMapStage, and getShuffleMapStage), and it wasn't clear what the purpose of each function was. With the new code, a single function (getOrCreateShuffleMapStage) is responsible for getting a stage (if it already exists) or creating new shuffle map stages and any missing ancestor stages, and it delegates to createShuffleMapStage when new stages need to be created. There's some remaining confusion here because the getOrCreateParentStages call in createShuffleMapStage may recursively create ancestor stages; this is an issue I plan to fix in a future pull request, because it's trickier to fix and involves a slight functionality change.
* newResultStage was renamed to createResultStage, for consistency with naming around shuffle map stages.
* getParentStages has been renamed to getOrCreateParentStages, to make it clear that this function will sometimes create missing ancestor stages.
* The only *slight* functionality change is that on line 478, updateJobIdStageIdMaps now uses a stage's parents instance variable rather than re-calculating them (I couldn't see any reason why they'd need to be re-calculated, and suspect this is just leftover from older code).
* getAncestorShuffleDependencies was renamed to getMissingAncestorShuffleDependencies, to make it clear that this only returns dependencies that have not yet been run.
cc squito markhamstra JoshRosen (who requested more DAG scheduler commenting long ago -- an issue this pull request tries, in part, to address)
FYI rxin
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes #13677 from kayousterhout/SPARK-15926.
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When `--packages` is specified with spark-shell the classes from those packages cannot be found, which I think is due to some of the changes in SPARK-12343.
Tested manually with both scala 2.10 and 2.11 repls.
vanzin davies can you guys please review?
Author: Marcelo Vanzin <vanzin@cloudera.com>
Author: Nezih Yigitbasi <nyigitbasi@netflix.com>
Closes #13709 from nezihyigitbasi/SPARK-15782.
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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.
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This reverts commit 4df8df5c2e68f5a5d231c401b04d762d7a648159.
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## What changes were proposed in this pull request?
SPARK-15927 exacerbated a race in BasicSchedulerIntegrationTest, so it went from very unlikely to fairly frequent. The issue is that stage numbering is not completely deterministic, but these tests treated it like it was. So turn off the tests.
## How was this patch tested?
on my laptop the test failed abotu 10% of the time before this change, and didn't fail in 500 runs after the change.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13688 from squito/hotfix_basic_scheduler.
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## What changes were proposed in this pull request?
When `--packages` is specified with `spark-shell` the classes from those packages cannot be found, which I think is due to some of the changes in `SPARK-12343`. In particular `SPARK-12343` removes a line that sets the `spark.jars` system property in client mode, which is used by the repl main class to set the classpath.
## How was this patch tested?
Tested manually.
This system property is used by the repl to populate its classpath. If
this is not set properly the classes for external packages cannot be
found.
tgravescs vanzin as you may be familiar with this part of the code.
Author: Nezih Yigitbasi <nyigitbasi@netflix.com>
Closes #13527 from nezihyigitbasi/repl-fix.
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## What changes were proposed in this pull request?
Link to jira which describes the problem: https://issues.apache.org/jira/browse/SPARK-15826
The fix in this PR is to allow users specify encoding in the pipe() operation. For backward compatibility,
keeping the default value to be system default.
## How was this patch tested?
Ran existing unit tests
Author: Tejas Patil <tejasp@fb.com>
Closes #13563 from tejasapatil/pipedrdd_utf8.
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LocalSchedulerBackend
## What changes were proposed in this pull request?
This patch is a follow-up to https://github.com/apache/spark/pull/13288 completing the renaming:
- LocalScheduler -> LocalSchedulerBackend~~Endpoint~~
## How was this patch tested?
Updated test cases to reflect the name change.
Author: Liwei Lin <lwlin7@gmail.com>
Closes #13683 from lw-lin/rename-backend.
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To try to eliminate redundant code to traverse the RDD dependency graph,
this PR creates a new function getShuffleDependencies that returns
shuffle dependencies that are immediate parents of a given RDD. This
new function is used by getParentStages and
getAncestorShuffleDependencies.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes #13646 from kayousterhout/SPARK-15927.
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accumulators
## What changes were proposed in this pull request?
Another PR to clean up recent build warnings. This particularly cleans up several instances of the old accumulator API usage in tests that are straightforward to update. I think this qualifies as "minor".
## How was this patch tested?
Jenkins
Author: Sean Owen <sowen@cloudera.com>
Closes #13642 from srowen/BuildWarnings.
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## What changes were proposed in this pull request?
Remove deprecated support for `zk://` master (`mesos://zk//` remains supported)
## How was this patch tested?
Jenkins
Author: Sean Owen <sowen@cloudera.com>
Closes #13625 from srowen/SPARK-15876.
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ReplayListenerSuite
## What changes were proposed in this pull request?
These tests weren't properly using `LocalSparkContext` so weren't cleaning up correctly when tests failed.
## How was this patch tested?
Jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13602 from squito/SPARK-15878_cleanup_replaylistener.
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## What changes were proposed in this pull request?
Adds codahale metrics for the codegen source text size and how long it takes to compile. The size is particularly interesting, since the JVM does have hard limits on how large methods can get.
To simplify, I added the metrics under a statically-initialized source that is always registered with SparkEnv.
## How was this patch tested?
Unit tests
Author: Eric Liang <ekl@databricks.com>
Closes #13586 from ericl/spark-15860.
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## What changes were proposed in this pull request?
This adds support for radix sort of nullable long fields. When a sort field is null and radix sort is enabled, we keep nulls in a separate region of the sort buffer so that radix sort does not need to deal with them. This also has performance benefits when sorting smaller integer types, since the current representation of nulls in two's complement (Long.MIN_VALUE) otherwise forces a full-width radix sort.
This strategy for nulls does mean the sort is no longer stable. cc davies
## How was this patch tested?
Existing randomized sort tests for correctness. I also tested some TPCDS queries and there does not seem to be any significant regression for non-null sorts.
Some test queries (best of 5 runs each).
Before change:
scala> val start = System.nanoTime; spark.range(5000000).selectExpr("if(id > 5, cast(hash(id) as long), NULL) as h").coalesce(1).orderBy("h").collect(); (System.nanoTime - start) / 1e6
start: Long = 3190437233227987
res3: Double = 4716.471091
After change:
scala> val start = System.nanoTime; spark.range(5000000).selectExpr("if(id > 5, cast(hash(id) as long), NULL) as h").coalesce(1).orderBy("h").collect(); (System.nanoTime - start) / 1e6
start: Long = 3190367870952791
res4: Double = 2981.143045
Author: Eric Liang <ekl@databricks.com>
Closes #13161 from ericl/sc-2998.
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## What changes were proposed in this pull request?
SparkContext.listAccumulator, by Spark's convention, makes it sound like "list" is a verb and the method should return a list of accumulators. This patch renames the method and the class collection accumulator.
## How was this patch tested?
Updated test case to reflect the names.
Author: Reynold Xin <rxin@databricks.com>
Closes #13594 from rxin/SPARK-15866.
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## What changes were proposed in this pull request?
With very wide tables, e.g. thousands of fields, the plan output is unreadable and often causes OOMs due to inefficient string processing. This truncates all struct and operator field lists to a user configurable threshold to limit performance impact.
It would also be nice to optimize string generation to avoid these sort of O(n^2) slowdowns entirely (i.e. use StringBuilder everywhere including expressions), but this is probably too large of a change for 2.0 at this point, and truncation has other benefits for usability.
## How was this patch tested?
Added a microbenchmark that covers this case particularly well. I also ran the microbenchmark while varying the truncation threshold.
```
numFields = 5
wide shallowly nested struct field r/w: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
2000 wide x 50 rows (write in-mem) 2336 / 2558 0.0 23364.4 0.1X
numFields = 25
wide shallowly nested struct field r/w: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
2000 wide x 50 rows (write in-mem) 4237 / 4465 0.0 42367.9 0.1X
numFields = 100
wide shallowly nested struct field r/w: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
2000 wide x 50 rows (write in-mem) 10458 / 11223 0.0 104582.0 0.0X
numFields = Infinity
wide shallowly nested struct field r/w: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
[info] java.lang.OutOfMemoryError: Java heap space
```
Author: Eric Liang <ekl@databricks.com>
Author: Eric Liang <ekhliang@gmail.com>
Closes #13537 from ericl/truncated-string.
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for now
## What changes were proposed in this pull request?
There is still some flakiness in BlacklistIntegrationSuite, so turning it off for the moment to avoid breaking more builds -- will turn it back with more fixes.
## How was this patch tested?
jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13528 from squito/ignore_blacklist.
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## What changes were proposed in this pull request?
`an -> a`
Use cmds like `find . -name '*.R' | xargs -i sh -c "grep -in ' an [^aeiou]' {} && echo {}"` to generate candidates, and review them one by one.
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #13515 from zhengruifeng/an_a.
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"EST" is …
## What changes were proposed in this pull request?
Stop using the abbreviated and ambiguous timezone "EST" in a test, since it is machine-local default timezone dependent, and fails in different timezones. Fixed [SPARK-15723](https://issues.apache.org/jira/browse/SPARK-15723).
## How was this patch tested?
Note that to reproduce this problem in any locale/timezone, you can modify the scalatest-maven-plugin argLine to add a timezone:
<argLine>-ea -Xmx3g -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=${CodeCacheSize} -Duser.timezone="Australia/Sydney"</argLine>
and run
$ mvn test -DwildcardSuites=org.apache.spark.status.api.v1.SimpleDateParamSuite -Dtest=none. Equally this will fix it in an effected timezone:
<argLine>-ea -Xmx3g -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=${CodeCacheSize} -Duser.timezone="America/New_York"</argLine>
To test the fix, apply the above change to `pom.xml` to set test TZ to `Australia/Sydney`, and confirm the test now passes.
Author: Brett Randall <javabrett@gmail.com>
Closes #13462 from javabrett/SPARK-15723-SimpleDateParamSuite.
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## What changes were proposed in this pull request?
Currently, the memory for temporary buffer used by TimSort is always allocated as on-heap without bookkeeping, it could cause OOM both in on-heap and off-heap mode.
This PR will try to manage that by preallocate it together with the pointer array, same with RadixSort. It both works for on-heap and off-heap mode.
This PR also change the loadFactor of BytesToBytesMap to 0.5 (it was 0.70), it enables use to radix sort also makes sure that we have enough memory for timsort.
## How was this patch tested?
Existing tests.
Author: Davies Liu <davies@databricks.com>
Closes #13318 from davies/fix_timsort.
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calling sc.setLogLevel
## What changes were proposed in this pull request?
Currently `SparkContext API setLogLevel(level: String) `can not handle lower case or mixed case input string. But `org.apache.log4j.Level.toLevel` can take lowercase or mixed case.
This PR is to allow case-insensitive user input for the log level.
## How was this patch tested?
A unit testcase is added.
Author: Xin Wu <xinwu@us.ibm.com>
Closes #13422 from xwu0226/reset_loglevel.
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## What changes were proposed in this pull request?
BlacklistIntegrationSuite (introduced by SPARK-10372) is a bit flaky because of some race conditions:
1. Failed jobs might have non-empty results, because the resultHandler will be invoked for successful tasks (if there are task successes before failures)
2. taskScheduler.taskIdToTaskSetManager must be protected by a lock on taskScheduler
(1) has failed a handful of jenkins builds recently. I don't think I've seen (2) in jenkins, but I've run into with some uncommitted tests I'm working on where there are lots more tasks.
While I was in there, I also made an unrelated fix to `runningTasks`in the test framework -- there was a pointless `O(n)` operation to remove completed tasks, could be `O(1)`.
## How was this patch tested?
I modified the o.a.s.scheduler.BlacklistIntegrationSuite to have it run the tests 1k times on my laptop. It failed 11 times before this change, and none with it. (Pretty sure all the failures were problem (1), though I didn't check all of them).
Also the full suite of tests via jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes #13454 from squito/SPARK-15714.
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If an RDD partition is cached on disk and the DiskStore file is lost, then reads of that cached partition will fail and the missing partition is supposed to be recomputed by a new task attempt. In the current BlockManager implementation, however, the missing file does not trigger any metadata updates / does not invalidate the cache, so subsequent task attempts will be scheduled on the same executor and the doomed read will be repeatedly retried, leading to repeated task failures and eventually a total job failure.
In order to fix this problem, the executor with the missing file needs to properly mark the corresponding block as missing so that it stops advertising itself as a cache location for that block.
This patch fixes this bug and adds an end-to-end regression test (in `FailureSuite`) and a set of unit tests (`in BlockManagerSuite`).
Author: Josh Rosen <joshrosen@databricks.com>
Closes #13473 from JoshRosen/handle-missing-cache-files.
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accumulators.
## What changes were proposed in this pull request?
This PR corrects the remaining cases for using old accumulators.
This does not change some old accumulator usages below:
- `ImplicitSuite.scala` - Tests dedicated to old accumulator, for implicits with `AccumulatorParam`
- `AccumulatorSuite.scala` - Tests dedicated to old accumulator
- `JavaSparkContext.scala` - For supporting old accumulators for Java API.
- `debug.package.scala` - Usage with `HashSet[String]`. Currently, it seems no implementation for this. I might be able to write an anonymous class for this but I didn't because I think it is not worth writing a lot of codes only for this.
- `SQLMetricsSuite.scala` - This uses the old accumulator for checking type boxing. It seems new accumulator does not require type boxing for this case whereas the old one requires (due to the use of generic).
## How was this patch tested?
Existing tests cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #13434 from HyukjinKwon/accum.
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written if buffer isn't full
## What changes were proposed in this pull request?
1. The class allocated 4x space than needed as it was using `Int` to store the `Byte` values
2. If CircularBuffer isn't full, currently toString() will print some garbage chars along with the content written as is tries to print the entire array allocated for the buffer. The fix is to keep track of buffer getting full and don't print the tail of the buffer if it isn't full (suggestion by sameeragarwal over https://github.com/apache/spark/pull/12194#discussion_r64495331)
3. Simplified `toString()`
## How was this patch tested?
Added new test case
Author: Tejas Patil <tejasp@fb.com>
Closes #13351 from tejasapatil/circular_buffer.
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the same task is succeeded in speculation
## What changes were proposed in this pull request?
With this patch, TaskSetManager kills other running attempts when any one of the attempt succeeds for the same task. Also killed tasks will not be considered as failed tasks and they get listed separately in the UI and also shows the task state as KILLED instead of FAILED.
## How was this patch tested?
core\src\test\scala\org\apache\spark\ui\jobs\JobProgressListenerSuite.scala
core\src\test\scala\org\apache\spark\util\JsonProtocolSuite.scala
I have verified this patch manually by enabling spark.speculation as true, when any attempt gets succeeded then other running attempts are getting killed for the same task and other pending tasks are getting assigned in those. And also when any attempt gets killed then they are considered as KILLED tasks and not considered as FAILED tasks. Please find the attached screen shots for the reference.
Ref : https://github.com/apache/spark/pull/11916
Author: Devaraj K <devaraj@apache.org>
Closes #11996 from devaraj-kavali/SPARK-10530.
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## What changes were proposed in this pull request?
This is a simple patch that makes package names for Java 8 test suites consistent. I moved everything to test.org.apache.spark to we can test package private APIs properly. Also added "java8" as the package name so we can easily run all the tests related to Java 8.
## How was this patch tested?
This is a test only change.
Author: Reynold Xin <rxin@databricks.com>
Closes #13364 from rxin/SPARK-15633.
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## What changes were proposed in this pull request?
Temp directory used to save records is not deleted after program exit in DataFrameExample. Although it called deleteOnExit, it doesn't work as the directory is not empty. Similar things happend in ContextCleanerSuite. Update the code to make sure temp directory is deleted after program exit.
## How was this patch tested?
unit tests and local build.
Author: dding3 <ding.ding@intel.com>
Closes #13328 from dding3/master.
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## What changes were proposed in this pull request?
Profiling a Spark job spilling large amount of intermediate data we found that significant portion of time is being spent in DiskObjectWriter.updateBytesWritten function. Looking at the code, we see that the function is being called too frequently to update the number of bytes written to disk. We should reduce the frequency to avoid this.
## How was this patch tested?
Tested by running the job on cluster and saw 20% CPU gain by this change.
Author: Sital Kedia <skedia@fb.com>
Closes #13332 from sitalkedia/DiskObjectWriter.
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## What changes were proposed in this pull request?
This patch fixes a few integer overflows in `UnsafeSortDataFormat.copyRange()` and `ShuffleSortDataFormat copyRange()` that seems to be the most likely cause behind a number of `TimSort` contract violation errors seen in Spark 2.0 and Spark 1.6 while sorting large datasets.
## How was this patch tested?
Added a test in `ExternalSorterSuite` that instantiates a large array of the form of [150000000, 150000001, 150000002, ...., 300000000, 0, 1, 2, ..., 149999999] that triggers a `copyRange` in `TimSort.mergeLo` or `TimSort.mergeHi`. Note that the input dataset should contain at least 268.43 million rows with a certain data distribution for an overflow to occur.
Author: Sameer Agarwal <sameer@databricks.com>
Closes #13336 from sameeragarwal/timsort-bug.
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This is a basic framework for testing the entire scheduler. The tests this adds aren't very interesting -- the point of this PR is just to setup the framework, to keep the initial change small, but it can be built upon to test more features (eg., speculation, killing tasks, blacklisting, etc.).
Author: Imran Rashid <irashid@cloudera.com>
Closes #8559 from squito/SPARK-10372-scheduler-integs.
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