Author: Zhang, Liye <liye.zhang@intel.com>
Closes#2793 from liyezhang556520/uniformHashMap and squashes the following commits:
5884735 [Zhang, Liye] [CORE]codeStyle: uniform ConcurrentHashMap define in StorageLevel.scala
The driver hangs sometimes when we coalesce RDD partitions. See JIRA for more details and reproduction.
This is because our use of empty string as default preferred location in `CoalescedRDDPartition` causes the `TaskSetManager` to schedule the corresponding task on host `""` (empty string). The intended semantics here, however, is that the partition does not have a preferred location, and the TSM should schedule the corresponding task accordingly.
Author: Andrew Or <andrew@databricks.com>
Closes#3633 from andrewor14/coalesce-preferred-loc and squashes the following commits:
e520d6b [Andrew Or] Oops
3ebf8bd [Andrew Or] A few comments
f370a4e [Andrew Or] Fix tests
2f7dfb6 [Andrew Or] Avoid using empty string as default preferred location
Hi all - I've renamed the unhelpfully named variable and added a comment clarifying what's actually happening.
Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Closes#3666 from ilganeli/SPARK-4569B and squashes the following commits:
1810394 [Ilya Ganelin] [SPARK-4569] Rename 'externalSorting' in Aggregator
e2d2092 [Ilya Ganelin] [SPARK-4569] Rename 'externalSorting' in Aggregator
d7cefec [Ilya Ganelin] [SPARK-4569] Rename 'externalSorting' in Aggregator
5b3f39c [Ilya Ganelin] [SPARK-4569] Rename in Aggregator
Currently this doesn't do anything in other modes, so we might as well just disable it rather than having the user mistakenly rely on it.
Author: Andrew Or <andrew@databricks.com>
Closes#3615 from andrewor14/dynamic-allocation-yarn-only and squashes the following commits:
ce6487a [Andrew Or] Allow requesting / killing executors only in YARN mode
Accumulators keep thread-local copies of themselves. These copies were only cleared at the beginning of a task. This meant that (a) the memory they used was tied up until the next task ran on that thread, and (b) if a thread died, the memory it had used for accumulators was locked up forever on that worker.
This PR clears the thread-local copies of accumulators at the end of each task, in the tasks finally block, to make sure they are cleaned up between tasks. It also stores them in a ThreadLocal object, so that if, for some reason, the thread dies, any memory they are using at the time should be freed up.
Author: Nathan Kronenfeld <nkronenfeld@oculusinfo.com>
Closes#3570 from nkronenfeld/Accumulator-Improvements and squashes the following commits:
a581f3f [Nathan Kronenfeld] Change Accumulators to private[spark] instead of adding mima exclude to get around false positive in mima tests
b6c2180 [Nathan Kronenfeld] Include MiMa exclude as per build error instructions - this version incompatibility should be irrelevent, as it will only surface if a master is talking to a worker running a different version of spark.
537baad [Nathan Kronenfeld] Fuller refactoring as intended, incorporating JR's suggestions for ThreadLocal localAccums, and keeping clear(), but also calling it in tasks' finally block, rather than just at the beginning of the task.
39a82f2 [Nathan Kronenfeld] Clear local copies of accumulators as soon as we're done with them
Author: Sandy Ryza <sandy@cloudera.com>
Closes#3426 from sryza/sandy-spark-4567 and squashes the following commits:
cb4b8d2 [Sandy Ryza] SPARK-4567. Make SparkJobInfo and SparkStageInfo serializable
After synchronizing on the `info` lock in the `removeBlock`/`dropOldBlocks`/`dropFromMemory` methods in BlockManager, the block that `info` represented may have already removed.
The three methods have the same logic to get the `info` lock:
```
info = blockInfo.get(id)
if (info != null) {
info.synchronized {
// do something
}
}
```
So, there is chance that when a thread enters the `info.synchronized` block, `info` has already been removed from the `blockInfo` map by some other thread who entered `info.synchronized` first.
The `removeBlock` and `dropOldBlocks` methods are idempotent, so it's safe for them to run on blocks that have already been removed.
But in `dropFromMemory` it may be problematic since it may drop block data which already removed into the diskstore, and this calls data store operations that are not designed to handle missing blocks.
This patch fixes this issue by adding a check to `dropFromMemory` to test whether blocks have been removed by a racing thread.
Author: hushan[胡珊] <hushan@xiaomi.com>
Closes#3574 from suyanNone/refine-block-concurrency and squashes the following commits:
edb989d [hushan[胡珊]] Refine code style and comments position
55fa4ba [hushan[胡珊]] refine code
e57e270 [hushan[胡珊]] add check info is already remove or not while having gotten info.syn
This commit removes the GC time for each task from the set of
optional, additional metrics, and instead always shows it for
each task.
cc pwendell
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#3622 from kayousterhout/gc_time and squashes the following commits:
15ac242 [Kay Ousterhout] Make TaskDetailsClassNames private[spark]
e71d893 [Kay Ousterhout] [SPARK-4765] Make GC time always shown in UI.
In HashShuffleReader.scala and HashShuffleWriter.scala, no need to judge "dep.aggregator.isEmpty" again as this is judged by "dep.aggregator.isDefined"
In SortShuffleWriter.scala, "dep.aggregator.isEmpty" is better than "!dep.aggregator.isDefined" ?
Author: maji2014 <maji3@asiainfo.com>
Closes#3553 from maji2014/spark-4691 and squashes the following commits:
bf7b14d [maji2014] change a elegant way for SortShuffleWriter.scala
10d0cf0 [maji2014] change a elegant way
d8f52dc [maji2014] code optimization for judgement
My original 'fix' didn't fix at all. Now, there's a unit test to check whether it works. Of the two options to really fix it -- copy the `Map` to a `java.util.HashMap`, or copy and modify Scala's implementation in `Wrappers.MapWrapper`, I went with the latter.
Author: Sean Owen <sowen@cloudera.com>
Closes#3587 from srowen/SPARK-3926 and squashes the following commits:
8586bb9 [Sean Owen] Remove unneeded no-arg constructor, and add additional note about copied code in LICENSE
7bb0e66 [Sean Owen] Make SerializableMapWrapper actually serialize, and add unit test
Simple omission on my part.
Author: Andrew Or <andrew@databricks.com>
Closes#3612 from andrewor14/dynamic-allocation-synchronization and squashes the following commits:
1f03b60 [Andrew Or] Synchronize kills
tempFile is created in the same directory than targetFile, so that the
move from tempFile to targetFile is always atomic
Author: Christophe Préaud <christophe.preaud@kelkoo.com>
Closes#2855 from preaudc/master and squashes the following commits:
9ba89ca [Christophe Préaud] Ensure that files are fetched atomically
54419ae [Christophe Préaud] Merge remote-tracking branch 'upstream/master'
c6a5590 [Christophe Préaud] Revert commit 8ea871f8130b2490f1bad7374a819bf56f0ccbbd
7456a33 [Christophe Préaud] Merge remote-tracking branch 'upstream/master'
8ea871f [Christophe Préaud] Ensure that files are fetched atomically
In BlockManagermasterActor, when handling message type UpdateBlockInfo, the message replies is in handled in individual private methods, should handle it in receive of Akka.
Author: Zhang, Liye <liye.zhang@intel.com>
Closes#2853 from liyezhang556520/akkaRecv and squashes the following commits:
9b06f0a [Zhang, Liye] remove the unreachable code
bf518cd [Zhang, Liye] change the indent
242166b [Zhang, Liye] modified accroding to the comments
d4b929b [Zhang, Liye] [SPARK-4005][CORE] handle message replies in receive instead of in the individual private methods
I ran into multiple cases that SBT/Scala compiler was confused by the implicits in continuous compilation mode. Adding explicit return types fixes the problem.
Author: Reynold Xin <rxin@databricks.com>
Closes#3580 from rxin/rdd-implicit and squashes the following commits:
ee32fcd [Reynold Xin] Move object RDD to the end of the file.
b8562c9 [Reynold Xin] Merge branch 'master' of github.com:apache/spark into rdd-implicit
d4e9f85 [Reynold Xin] Code review.
a836a37 [Reynold Xin] Move object RDD to the front of RDD.scala.
Please see https://issues.apache.org/jira/browse/SPARK-4459
Author: Saldanha <saldaal1@phusca-l24858.wlan.na.novartis.net>
Closes#3327 from alokito/master and squashes the following commits:
54b1095 [Saldanha] [SPARK-4459] changed type parameter for keyBy from K to U
d5f73c3 [Saldanha] [SPARK-4459] added keyBy test
316ad77 [Saldanha] SPARK-4459 changed type parameter for groupBy from K to U.
62ddd4b [Saldanha] SPARK-4459 added failing unit test
In yarn-cluster and standalone-cluster modes, we don't know where driver will run until it is launched. If the `spark.driver.host` property is set on the submitting machine and propagated to the driver through SparkConf then this will lead to errors when the driver launches.
This patch fixes this issue by dropping the `spark.driver.host` property in SparkSubmit when running in a cluster deploy mode.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#3112 from WangTaoTheTonic/SPARK4253 and squashes the following commits:
ed1a25c [WangTaoTheTonic] revert unrelated formatting issue
02c4e49 [WangTao] add comment
32a3f3f [WangTaoTheTonic] ingore it in SparkSubmit instead of SparkContext
667cf24 [WangTaoTheTonic] document fix
ff8d5f7 [WangTaoTheTonic] also ignore it in standalone cluster mode
2286e6b [WangTao] ignore spark.driver.host in yarn-cluster mode
MappedRDD, MappedValuesRDD, FlatMappedValuesRDD, FilteredRDD, GlommedRDD, FlatMappedRDD are not necessary. They can be implemented trivially using MapPartitionsRDD.
Author: Reynold Xin <rxin@databricks.com>
Closes#3578 from rxin/SPARK-4719 and squashes the following commits:
eed9853 [Reynold Xin] Preserve partitioning for filter.
eb1a89b [Reynold Xin] [SPARK-4719][API] Consolidate various narrow dep RDD classes with MapPartitionsRDD.
cc aarondav kayousterhout pwendell
This should go into 1.2?
Author: Reynold Xin <rxin@databricks.com>
Closes#3579 from rxin/SPARK-4085 and squashes the following commits:
255b4fd [Reynold Xin] Updated test.
f9814d9 [Reynold Xin] Code review feedback.
2afaf35 [Reynold Xin] [SPARK-4085] Propagate FetchFailedException when Spark fails to read local shuffle file.
The ExecutorInfo only reaches the RUNNING state if the Driver is alive to send the ExecutorStateChanged message to master. Else, appInfo.resetRetryCount() is never called and failing Executors will eventually exceed ApplicationState.MAX_NUM_RETRY, resulting in the application being removed from the master's accounting.
JoshRosen
Author: Mark Hamstra <markhamstra@gmail.com>
Closes#3550 from markhamstra/SPARK-4498 and squashes the following commits:
8f543b1 [Mark Hamstra] Don't transition ExecutorInfo to RUNNING until Executor is added by Driver
ShuffleMemoryManager.tryToAcquire may return a negative value. The unit test demonstrates this bug. It will output `0 did not equal -200 granted is negative`.
Author: zsxwing <zsxwing@gmail.com>
Closes#3575 from zsxwing/SPARK-4715 and squashes the following commits:
a193ae6 [zsxwing] Make sure tryToAcquire won't return a negative value
As #3262 wasn't merged to branch 1.2, the `since` value of `deprecated` should be '1.3.0'.
Author: zsxwing <zsxwing@gmail.com>
Closes#3573 from zsxwing/SPARK-4397-version and squashes the following commits:
1daa03c [zsxwing] Change the 'since' value to '1.3.0'
The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672
The f closure of `PartitionsRDD(ZippedPartitionsRDD2)` contains a `$outer` that references EdgeRDD/VertexRDD, which causes task's serialization chain become very long in iterative GraphX applications. As a result, StackOverflow error will occur. If we set "f = null" in `clearDependencies()`, checkpoint() can cut off the long serialization chain. More details and explanation can be found in the JIRA.
Author: JerryLead <JerryLead@163.com>
Author: Lijie Xu <csxulijie@gmail.com>
Closes#3545 from JerryLead/my_core and squashes the following commits:
f7faea5 [JerryLead] checkpoint() should clear the f to avoid StackOverflow error
c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark
52799e3 [Lijie Xu] Merge pull request #1 from apache/master
This PR cleans up `import SparkContext._` in core for SPARK-4397(#3262) to prove it really works well.
Author: zsxwing <zsxwing@gmail.com>
Closes#3530 from zsxwing/SPARK-4397-cleanup and squashes the following commits:
04e2273 [zsxwing] Cleanup 'import SparkContext._' in core
Author: zsxwing <zsxwing@gmail.com>
Closes#3521 from zsxwing/SPARK-4661 and squashes the following commits:
03cbe3f [zsxwing] Minor code and docs cleanup
If `spark.akka.frameSize` > 2047, it will overflow and become negative. Should have some assertion in `maxFrameSizeBytes` to warn people.
Author: zsxwing <zsxwing@gmail.com>
Closes#3527 from zsxwing/SPARK-4664 and squashes the following commits:
0089c7a [zsxwing] Throw an exception when spark.akka.frameSize > 2047
If using spark-sql in yarn-cluster mode, print an error infomation just as the spark shell in yarn-cluster mode.
Author: carlmartin <carlmartinmax@gmail.com>
Author: huangzhaowei <carlmartinmax@gmail.com>
Closes#3479 from SaintBacchus/sparkSqlShell and squashes the following commits:
35829a9 [carlmartin] improve the description of comment
e6c1eb7 [carlmartin] add a comment in bin/spark-sql to remind user who wants to change the class
f1c5c8d [carlmartin] Merge branch 'master' into sparkSqlShell
8e112c5 [huangzhaowei] singular form
ec957bc [carlmartin] Add the some error infomation if using spark-sql in yarn-cluster mode
7bcecc2 [carlmartin] Merge branch 'master' of https://github.com/apache/spark into codereview
4fad75a [carlmartin] Add the Error infomation using spark-sql in yarn-cluster mode
Added a ClassTag parameter to CompactBuffer. So CompactBuffer[T] can create primitive arrays for primitive types. It will reduce the memory usage for primitive types significantly and only pay minor performance lost.
Here is my test code:
```Scala
// Call org.apache.spark.util.SizeEstimator.estimate
def estimateSize(obj: AnyRef): Long = {
val c = Class.forName("org.apache.spark.util.SizeEstimator$")
val f = c.getField("MODULE$")
val o = f.get(c)
val m = c.getMethod("estimate", classOf[Object])
m.setAccessible(true)
m.invoke(o, obj).asInstanceOf[Long]
}
sc.parallelize(1 to 10000).groupBy(_ => 1).foreach {
case (k, v) =>
println(v.getClass() + " size: " + estimateSize(v))
}
```
Using the previous CompactBuffer outputed
```
class org.apache.spark.util.collection.CompactBuffer size: 313358
```
Using the new CompactBuffer outputed
```
class org.apache.spark.util.collection.CompactBuffer size: 65712
```
In this case, the new `CompactBuffer` only used 20% memory of the previous one. It's really helpful for `groupByKey` when using a primitive value.
Author: zsxwing <zsxwing@gmail.com>
Closes#3378 from zsxwing/SPARK-4505 and squashes the following commits:
4abdbba [zsxwing] Add a ClassTag parameter to reduce the memory usage of CompactBuffer[T] when T is a primitive type
Admittedly a really small tweak.
Author: Stephen Haberman <stephen@exigencecorp.com>
Closes#3514 from stephenh/include-key-name-in-npe and squashes the following commits:
937740a [Stephen Haberman] Include the key name when failing on an invalid value.
`File.exists()` and `File.mkdirs()` only throw `SecurityException` instead of `IOException`. Then, when an exception is thrown, `dir` should be reset too.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#3449 from viirya/fix_createtempdir and squashes the following commits:
36cacbd [Liang-Chi Hsieh] Use proper exception and reset variable.
Time suffix exists in Utils.getUsedTimeMs(startTime), no need to append again, delete that
Author: maji2014 <maji3@asiainfo.com>
Closes#3475 from maji2014/SPARK-4619 and squashes the following commits:
df0da4e [maji2014] delete redundant time suffix
This PR introduces a set of Java APIs for using `JdbcRDD`:
1. Trait (interface) `JdbcRDD.ConnectionFactory`: equivalent to the `getConnection: () => Connection` parameter in `JdbcRDD` constructor.
2. Two overloaded versions of `Jdbc.create`: used to create `JavaRDD` that wraps a `JdbcRDD`.
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Author: Cheng Lian <lian@databricks.com>
Closes#3478 from liancheng/japi-jdbc-rdd and squashes the following commits:
9a54625 [Cheng Lian] Only shutdowns a single DB rather than the whole Derby driver
d4cedc5 [Cheng Lian] Moves Java JdbcRDD test case to a separate test suite
ffcdf2e [Cheng Lian] Java API for JdbcRDD
Author: roxchkplusony <roxchkplusony@gmail.com>
Closes#3483 from roxchkplusony/bugfix/4626 and squashes the following commits:
aba9184 [roxchkplusony] replace warning message per review
5e7fdea [roxchkplusony] [SPARK-4626] Kill a task only if the executorId is (still) registered with the scheduler
Warn against subclassing scala.App, and remove one instance of this in examples
Author: Sean Owen <sowen@cloudera.com>
Closes#3497 from srowen/SPARK-4170 and squashes the following commits:
4a6131f [Sean Owen] Restore multiline string formatting
a8ca895 [Sean Owen] Warn against subclassing scala.App, and remove one instance of this in examples
https://issues.apache.org/jira/browse/SPARK-3628
In current implementation, the accumulator will be updated for every successfully finished task, even the task is from a resubmitted stage, which makes the accumulator counter-intuitive
In this patch, I changed the way for the DAGScheduler to update the accumulator,
DAGScheduler maintains a HashTable, mapping the stage id to the received <accumulator_id , value> pairs. Only when the stage becomes independent, (no job needs it any more), we accumulate the values of the <accumulator_id , value> pairs, when a task finished, we check if the HashTable has contained such stageId, it saves the accumulator_id, value only when the task is the first finished task of a new stage or the stage is running for the first attempt...
Author: CodingCat <zhunansjtu@gmail.com>
Closes#2524 from CodingCat/SPARK-732-1 and squashes the following commits:
701a1e8 [CodingCat] roll back change on Accumulator.scala
1433e6f [CodingCat] make MIMA happy
b233737 [CodingCat] address Matei's comments
02261b8 [CodingCat] rollback some changes
6b0aff9 [CodingCat] update document
2b2e8cf [CodingCat] updateAccumulator
83b75f8 [CodingCat] style fix
84570d2 [CodingCat] re-enable the bad accumulator guard
1e9e14d [CodingCat] add NPE guard
21b6840 [CodingCat] simplify the patch
88d1f03 [CodingCat] fix rebase error
f74266b [CodingCat] add test case for resubmitted result stage
5cf586f [CodingCat] de-duplicate on task level
138f9b3 [CodingCat] make MIMA happy
67593d2 [CodingCat] make if allowing duplicate update as an option of accumulator
https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/executor/Executor.scala#L337 creates a configuration object for every task that is launched, even if there is no new dependent file/JAR to update. This is a heavy-weight creation that should be avoided if there is no new file/JAR to update. This PR makes that creation lazy. Quick local test in spark-perf scheduling throughput tests gives the following numbers in a local standalone scheduler mode.
1 job with 10000 tasks: before 7.8395 seconds, after 2.6415 seconds = 3x increase in task scheduling throughput
pwendell JoshRosen
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#3463 from tdas/lazy-config and squashes the following commits:
c791c1e [Tathagata Das] Reduce task latency by making configuration initialization lazy
In practice, only 2-4 cores should be required to transfer roughly 10 Gb/s, and each core that we use will have an initial overhead of roughly 32 MB of off-heap memory, which comes at a premium.
Thus, this value should still retain maximum throughput and reduce wasted off-heap memory allocation. It can be overridden by setting the number of serverThreads and clientThreads manually in Spark's configuration.
Author: Aaron Davidson <aaron@databricks.com>
Closes#3469 from aarondav/fewer-pools2 and squashes the following commits:
087c59f [Aaron Davidson] [SPARK-4516] Cap default number of Netty threads at 8
Fix [SPARK-4471](https://issues.apache.org/jira/browse/SPARK-4471): blockManagerIdFromJson function throws exception while BlockManagerId be null in MetadataFetchFailedException
Author: hushan[胡珊] <hushan@xiaomi.com>
Closes#3340 from suyanNone/fix-blockmanagerId-jnothing-2 and squashes the following commits:
159f9a3 [hushan[胡珊]] Refine test code for blockmanager is null
4380d73 [hushan[胡珊]] remove useless blank line
3ccf651 [hushan[胡珊]] Fix SPARK-4471: blockManagerIdFromJson function throws exception while metadata fetch failed
The documentation points the user to run the following
```
sbin/start-history-server.sh
```
The first thing this does is throw an exception that complains a log directory is not specified. The exception message itself does not say anything about what to set. Instead we should have a default and a landing page with a better message. The new default log directory is `file:/tmp/spark-events`.
This is what it looks like as of this PR:
Author: Andrew Or <andrew@databricks.com>
Closes#3411 from andrewor14/minor-history-improvements and squashes the following commits:
f33d6b3 [Andrew Or] Point user to set config if default log dir does not exist
fc4c17a [Andrew Or] Improve HistoryServer UX
**Summary.** On failover, the Master may receive duplicate registrations from the same worker, causing the worker to exit. This is caused by this commit 4afe9a4852, which adds logic for the worker to re-register with the master in case of failures. However, the following race condition may occur:
(1) Master A fails and Worker attempts to reconnect to all masters
(2) Master B takes over and notifies Worker
(3) Worker responds by registering with Master B
(4) Meanwhile, Worker's previous reconnection attempt reaches Master B, causing the same Worker to register with Master B twice
**Fix.** Instead of attempting to register with all known masters, the worker should re-register with only the one that it has been communicating with. This is safe because the fact that a failover has occurred means the old master must have died. Then, when the worker is finally notified of a new master, it gives up on the old one in favor of the new one.
**Caveat.** Even this fix is subject to more obscure race conditions. For instance, if Master B fails and Master A recovers immediately, then Master A may still observe duplicate worker registrations. However, this and other potential race conditions summarized in [SPARK-4592](https://issues.apache.org/jira/browse/SPARK-4592), are much, much less likely than the one described above, which is deterministically reproducible.
Author: Andrew Or <andrew@databricks.com>
Closes#3447 from andrewor14/standalone-failover and squashes the following commits:
0d9716c [Andrew Or] Move re-registration logic to actor for thread-safety
79286dc [Andrew Or] Preserve old behavior for initial retries
83b321c [Andrew Or] Tweak wording
1fce6a9 [Andrew Or] Active master actor could be null in the beginning
b6f269e [Andrew Or] Avoid duplicate worker registrations
Functionally, this is just a small change on top of #3393 (by jongyoul). The issue being addressed is discussed in the comments there. I have not yet added a test for the bug there. I will add one shortly.
I've also done some minor renaming/clean-up of variables in this class and tests.
Author: Patrick Wendell <pwendell@gmail.com>
Author: Jongyoul Lee <jongyoul@gmail.com>
Closes#3436 from pwendell/mesos-issue and squashes the following commits:
58c35b5 [Patrick Wendell] Adding unit test for this situation
c4f0697 [Patrick Wendell] Additional clean-up and fixes on top of existing fix
f20f1b3 [Jongyoul Lee] [SPARK-4525] MesosSchedulerBackend.resourceOffers cannot decline unused offers from acceptedOffers - Added code for declining unused offers among acceptedOffers - Edited testCase for checking declining unused offers
This reverts commit b043c27424.
I accidentally committed this using my own authorship credential. However,
I should have given authoriship to the original author: Jongyoul Lee.
Functionally, this is just a small change on top of #3393 (by jongyoul). The issue being addressed is discussed in the comments there. I have not yet added a test for the bug there. I will add one shortly.
I've also done some minor renaming/clean-up of variables in this class and tests.
Author: Patrick Wendell <pwendell@gmail.com>
Author: Jongyoul Lee <jongyoul@gmail.com>
Closes#3436 from pwendell/mesos-issue and squashes the following commits:
58c35b5 [Patrick Wendell] Adding unit test for this situation
c4f0697 [Patrick Wendell] Additional clean-up and fixes on top of existing fix
f20f1b3 [Jongyoul Lee] [SPARK-4525] MesosSchedulerBackend.resourceOffers cannot decline unused offers from acceptedOffers - Added code for declining unused offers among acceptedOffers - Edited testCase for checking declining unused offers
The commit changes the java script used to show/hide additional
metrics in order to reduce page load time. SPARK-4016 significantly
increased page load time for the stage page when stages had a lot
(thousands or tens of thousands) of tasks, due to the additional
Javascript to hide some metrics by default and stripe the tables.
This commit reduces page load time in two ways:
(1) Now, all of the metrics that are hidden by default are
hidden by setting "display: none;" using CSS for the page,
rather than hiding them using javascript after the page loads.
Without this change, for stages with thousands of tasks, there
was a few second delay after page load, where first the additional
metrics were shown, and then after a delay were hidden once the
relevant JS finished running.
(2) CSS is used to stripe all of the tables except for the summary
table. The summary table needs javascript to do the striping because
some rows are hidden, but the javascript striping is slower, which
again resulted in a delay when it was used for the task table (where
for a few seconds after page load, all of the rows in the task table
would be white, while the browser finished running the JS to stripe
the table).
cc pwendell
This change is intended to be backported to 1.2 to avoid a regression in
UI performance when users run large jobs.
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#3328 from kayousterhout/SPARK-4266 and squashes the following commits:
f964091 [Kay Ousterhout] [SPARK-4266] [Web-UI] Reduce stage page load time.
Re-implement the Python broadcast using file:
1) serialize the python object using cPickle, write into disks.
2) Create a wrapper in JVM (for the dumped file), it read data from during serialization
3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors
4) During deserialization, writing the data into disk.
5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access.
It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor).
Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% |
python-broadcast-w-set | 4.13 | 4.50 | -8.35% |
Testing with 100 tasks (16 CPUs):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 38.16 | 8.40 | 353.98%
python-broadcast-w-set | 23.29 | 9.59 | 142.80%
Author: Davies Liu <davies@databricks.com>
Closes#3417 from davies/pybroadcast and squashes the following commits:
50a58e0 [Davies Liu] address comments
b98de1d [Davies Liu] disable gc while unpickle
e5ee6b9 [Davies Liu] support large string
09303b8 [Davies Liu] read all data into memory
dde02dd [Davies Liu] improve performance of python broadcast
This PR adds two new pages to the Spark Web UI:
- A jobs overview page, which shows details on running / completed / failed jobs.
- A job details page, which displays information on an individual job's stages.
The jobs overview page is now the default UI homepage; the old homepage is still accessible at `/stages`.
### Screenshots
#### New UI homepage
#### Job details page
(This is effectively a per-job version of the stages page that can be extended later with other things, such as DAG visualizations)
### Key changes in this PR
- Rename `JobProgressPage` to `AllStagesPage`
- Expose `StageInfo` objects in the ``SparkListenerJobStart` event; add backwards-compatibility tests to JsonProtocol.
- Add additional data structures to `JobProgressListener` to map from stages to jobs.
- Add several fields to `JobUIData`.
I also added ~150 lines of Selenium tests as I uncovered UI issues while developing this patch.
### Limitations
If a job contains stages that aren't run, then its overall job progress bar may be an underestimate of the total job progress; in other words, a completed job may appear to have a progress bar that's not at 100%.
If stages or tasks fail, then the progress bar will not go backwards to reflect the true amount of remaining work.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3009 from JoshRosen/job-page and squashes the following commits:
eb05e90 [Josh Rosen] Disable kill button in completed stages tables.
f00c851 [Josh Rosen] Fix JsonProtocol compatibility
b89c258 [Josh Rosen] More JSON protocol backwards-compatibility fixes.
ff804cd [Josh Rosen] Don't write "Stage Ids" field in JobStartEvent JSON.
6f17f3f [Josh Rosen] Only store StageInfos in SparkListenerJobStart event.
2bbf41a [Josh Rosen] Update job progress bar to reflect skipped tasks/stages.
61c265a [Josh Rosen] Add “skipped stages” table; only display non-empty tables.
1f45d44 [Josh Rosen] Incorporate a bunch of minor review feedback.
0b77e3e [Josh Rosen] More bug fixes for phantom stages.
034aa8d [Josh Rosen] Use `.max()` to find result stage for job.
eebdc2c [Josh Rosen] Don’t display pending stages for completed jobs.
67080ba [Josh Rosen] Ensure that "phantom stages" don't cause memory leaks.
7d10b97 [Josh Rosen] Merge remote-tracking branch 'apache/master' into job-page
d69c775 [Josh Rosen] Fix table sorting on all jobs page.
5eb39dc [Josh Rosen] Add pending stages table to job page.
f2a15da [Josh Rosen] Add status field to job details page.
171b53c [Josh Rosen] Move `startTime` to the start of SparkContext.
e2f2c43 [Josh Rosen] Fix sorting of stages in job details page.
8955f4c [Josh Rosen] Display information for pending stages on jobs page.
8ab6c28 [Josh Rosen] Compute numTasks from job start stage infos.
5884f91 [Josh Rosen] Add StageInfos to SparkListenerJobStart event.
79793cd [Josh Rosen] Track indices of completed stage to avoid overcounting when failures occur.
d62ea7b [Josh Rosen] Add failing Selenium test for stage overcounting issue.
1145c60 [Josh Rosen] Display text instead of progress bar for stages.
3d0a007 [Josh Rosen] Merge remote-tracking branch 'origin/master' into job-page
8a2351b [Josh Rosen] Add help tooltip to Spark Jobs page.
b7bf30e [Josh Rosen] Add stages progress bar; fix bug where active stages show as completed.
4846ce4 [Josh Rosen] Hide "(Job Group") if no jobs were submitted in job groups.
4d58e55 [Josh Rosen] Change label to "Tasks (for all stages)"
85e9c85 [Josh Rosen] Extract startTime into separate variable.
1cf4987 [Josh Rosen] Fix broken kill links; add Selenium test to avoid future regressions.
56701fa [Josh Rosen] Move last stage name / description logic out of markup.
a475ea1 [Josh Rosen] Add progress bars to jobs page.
45343b8 [Josh Rosen] More comments
4b206fb [Josh Rosen] Merge remote-tracking branch 'origin/master' into job-page
bfce2b9 [Josh Rosen] Address review comments, except for progress bar.
4487dcb [Josh Rosen] [SPARK-4145] Web UI job pages
2568a6c [Josh Rosen] Rename JobProgressPage to AllStagesPage:
This PR is a workaround for SPARK-4479. Two changes are introduced: when merge sort is bypassed in `ExternalSorter`,
1. also bypass RDD elements buffering as buffering is the reason that `MutableRow` backed row objects must be copied, and
2. avoids defensive copies in `Exchange` operator
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Author: Cheng Lian <lian@databricks.com>
Closes#3422 from liancheng/avoids-defensive-copies and squashes the following commits:
591f2e9 [Cheng Lian] Passes all shuffle suites
0c3c91e [Cheng Lian] Fixes shuffle write metrics when merge sort is bypassed
ed5df3c [Cheng Lian] Fixes styling changes
f75089b [Cheng Lian] Avoids unnecessary defensive copies when sort based shuffle is on
... - there is no way around this for deserializing actorRef(s).
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#3402 from ScrapCodes/SPARK-4377/troubleDeserializing and squashes the following commits:
77233fd [Prashant Sharma] Style fixes
9b35c6e [Prashant Sharma] Scalastyle fixes
29880da [Prashant Sharma] [SPARK-4377] Fixed serialization issue by switching to akka provided serializer - there is no way around this for deserializing actorRef(s).
