Author: Sandy Ryza <sandy@cloudera.com>
Closes#789 from sryza/sandy-spark-1813 and squashes the following commits:
48b05e9 [Sandy Ryza] Simplify
b824932 [Sandy Ryza] Allow both spark.kryo.classesToRegister and spark.kryo.registrator at the same time
6a15bb7 [Sandy Ryza] Small fix
a2278c0 [Sandy Ryza] Respond to review comments
6ef592e [Sandy Ryza] SPARK-1813. Add a utility to SparkConf that makes using Kryo really easy
This patch attempts to fix SPARK-2546 in `branch-1.0` and `branch-1.1`. The underlying problem is that thread-safety issues in Hadoop Configuration objects may cause Spark tasks to get stuck in infinite loops. The approach taken here is to clone a new copy of the JobConf for each task rather than sharing a single copy between tasks. Note that there are still Configuration thread-safety issues that may affect the driver, but these seem much less likely to occur in practice and will be more complex to fix (see discussion on the SPARK-2546 ticket).
This cloning is guarded by a new configuration option (`spark.hadoop.cloneConf`) and is disabled by default in order to avoid unexpected performance regressions for workloads that are unaffected by the Configuration thread-safety issues.
Author: Josh Rosen <joshrosen@apache.org>
Closes#2684 from JoshRosen/jobconf-fix-backport and squashes the following commits:
f14f259 [Josh Rosen] Add configuration option to control cloning of Hadoop JobConf.
b562451 [Josh Rosen] Remove unused jobConfCacheKey field.
dd25697 [Josh Rosen] [SPARK-2546] [1.0 / 1.1 backport] Clone JobConf for each task.
(cherry picked from commit 2cd40db2b3)
Signed-off-by: Josh Rosen <joshrosen@databricks.com>
Conflicts:
core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
Introduced in f7e79bc42c, I'm not sure why we need two spark.executor.memory here.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#2745 from WangTaoTheTonic/redundantconfig and squashes the following commits:
e7564dc [WangTao] too long line
fdbdb1f [WangTaoTheTonic] trivial workaround
d06b6e5 [WangTaoTheTonic] remove redundant spark.executor.memory in doc
Something about the 2.3.4 upgrade seems to have made the issue manifest where all the services disconnect from each other after exactly 1000 seconds (which is the heartbeat interval). [This post](https://groups.google.com/forum/#!topic/akka-user/X3xzpTCbEFs) suggests that heartbeat pause should be greater than heartbeat interval, and increasing the pause from 600s to 6000s seems to have rectified the issue. My current cluster has now exceeded 1400s of uptime without failure!
I do not know why this fixed it, because the threshold we have set for the failure detector is the exponent of a timeout, and 300 is extremely large. Perhaps the default failure detector changed in 2.3.4 and now ignores threshold.
Author: Aaron Davidson <aaron@databricks.com>
Closes#2784 from aarondav/fix-timeout and squashes the following commits:
bd1151a [Aaron Davidson] Increase pause, don't decrease interval
9cb0372 [Aaron Davidson] [SPARK-3923] Decrease Akka heartbeat interval below heartbeat pause
It took me a minute to track this down, so I thought it could be useful to have it in the docs.
I'm unsure if 512mb is the default for spark.driver.memory? Also - there could be a better value for the 'description' to differentiate it from spark.executor.memory.
Author: nartz <nartzpod@gmail.com>
Author: Nathan Artz <nathanartz@Nathans-MacBook-Pro.local>
Closes#2410 from nartz/docs/add-spark-driver-memory-to-config-docs and squashes the following commits:
a2f6c62 [nartz] Update configuration.md
74521b8 [Nathan Artz] add spark.driver.memory to config docs
Author: Brenden Matthews <brenden@diddyinc.com>
Closes#2401 from brndnmtthws/master and squashes the following commits:
4abaa5d [Brenden Matthews] [SPARK-3535][Mesos] Fix resource handling.
Update of PR #997.
With this PR, setting SPARK_CONF_DIR overrides SPARK_HOME/conf (not only spark-defaults.conf and spark-env).
Author: EugenCepoi <cepoi.eugen@gmail.com>
Closes#2481 from EugenCepoi/SPARK-2058 and squashes the following commits:
0bb32c2 [EugenCepoi] use orElse orNull and fixing trailing percent in compute-classpath.cmd
77f35d7 [EugenCepoi] SPARK-2058: Overriding SPARK_HOME/conf with SPARK_CONF_DIR
Author: scwf <wangfei1@huawei.com>
Closes#2632 from scwf/compress-doc and squashes the following commits:
7983a1a [scwf] snappy is the default compression codec for broadcast
https://issues.apache.org/jira/browse/SPARK-3565
"spark.ports.maxRetries" should be "spark.port.maxRetries". Make the configuration keys in document and code consistent.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Closes#2427 from WangTaoTheTonic/fixPortRetries and squashes the following commits:
c178813 [WangTaoTheTonic] Use blank lines trigger Jenkins
646f3fe [WangTaoTheTonic] also in SparkBuild.scala
3700dba [WangTaoTheTonic] Fix configuration item not consistent with document
change the value of spark.files.fetchTimeout
Author: viper-kun <xukun.xu@huawei.com>
Closes#2406 from viper-kun/master and squashes the following commits:
ecb0d46 [viper-kun] [Docs] Correct spark.files.fetchTimeout default value
7cf4c7a [viper-kun] Update configuration.md
Reuse Python worker to avoid the overhead of fork() Python process for each tasks. It also tracks the broadcasts for each worker, avoid sending repeated broadcasts.
This can reduce the time for dummy task from 22ms to 13ms (-40%). It can help to reduce the latency for Spark Streaming.
For a job with broadcast (43M after compress):
```
b = sc.broadcast(set(range(30000000)))
print sc.parallelize(range(24000), 100).filter(lambda x: x in b.value).count()
```
It will finish in 281s without reused worker, and it will finish in 65s with reused worker(4 CPUs). After reusing the worker, it can save about 9 seconds for transfer and deserialize the broadcast for each tasks.
It's enabled by default, could be disabled by `spark.python.worker.reuse = false`.
Author: Davies Liu <davies.liu@gmail.com>
Closes#2259 from davies/reuse-worker and squashes the following commits:
f11f617 [Davies Liu] Merge branch 'master' into reuse-worker
3939f20 [Davies Liu] fix bug in serializer in mllib
cf1c55e [Davies Liu] address comments
3133a60 [Davies Liu] fix accumulator with reused worker
760ab1f [Davies Liu] do not reuse worker if there are any exceptions
7abb224 [Davies Liu] refactor: sychronized with itself
ac3206e [Davies Liu] renaming
8911f44 [Davies Liu] synchronized getWorkerBroadcasts()
6325fc1 [Davies Liu] bugfix: bid >= 0
e0131a2 [Davies Liu] fix name of config
583716e [Davies Liu] only reuse completed and not interrupted worker
ace2917 [Davies Liu] kill python worker after timeout
6123d0f [Davies Liu] track broadcasts for each worker
8d2f08c [Davies Liu] reuse python worker
Sort-based shuffle has lower memory usage and seems to outperform hash-based in almost all of our testing.
Author: Reynold Xin <rxin@apache.org>
Closes#2178 from rxin/sort-shuffle and squashes the following commits:
713d341 [Reynold Xin] Fixed test failures by setting spark.shuffle.compress to the same value as spark.shuffle.spill.compress.
85165e6 [Reynold Xin] Fixed a comment typo.
aa0d372 [Reynold Xin] [SPARK-3280] Made sort-based shuffle the default implementation
The executors and the driver may not share the same Spark home. There is currently one way to set the executor side Spark home in Mesos, through setting `spark.home`. However, this is neither documented nor intuitive. This PR adds a more specific config `spark.mesos.executor.home` and exposes this to the user.
liancheng tnachen
Author: Andrew Or <andrewor14@gmail.com>
Closes#2166 from andrewor14/mesos-spark-home and squashes the following commits:
b87965e [Andrew Or] Merge branch 'master' of github.com:apache/spark into mesos-spark-home
f6abb2e [Andrew Or] Document spark.mesos.executor.home
ca7846d [Andrew Or] Add more specific configuration for executor Spark home in Mesos
Currently, local execution of Spark jobs is only used by take(), and it can be problematic as it can load a significant amount of data onto the driver. The worst case scenarios occur if the RDD is cached (guaranteed to load whole partition), has very large elements, or the partition is just large and we apply a filter with high selectivity or computational overhead.
Additionally, jobs that run locally in this manner do not show up in the web UI, and are thus harder to track or understand what is occurring.
This PR adds a flag to disable local execution, which is turned OFF by default, with the intention of perhaps eventually removing this functionality altogether. Removing it now is a tougher proposition since it is part of the public runJob API. An alternative solution would be to limit the flag to take()/first() to avoid impacting any external users of this API, but such usage (or, at least, reliance upon the feature) is hopefully minimal.
Author: Aaron Davidson <aaron@databricks.com>
Closes#1321 from aarondav/allowlocal and squashes the following commits:
136b253 [Aaron Davidson] Fix DAGSchedulerSuite
5599d55 [Aaron Davidson] [RFC] Disable local execution of Spark jobs by default
These configs looked inconsistent from the rest.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1936 from andrewor14/docs-code and squashes the following commits:
15f578a [Andrew Or] Add <code> tag
Instead of requiring "org.apache.spark.io.LZ4CompressionCodec", it is easier for users if Spark just accepts "lz4", "lzf", "snappy".
Author: Reynold Xin <rxin@apache.org>
Closes#1873 from rxin/compressionCodecShortForm and squashes the following commits:
9f50962 [Reynold Xin] Specify short-form compression codec names first.
63f78ee [Reynold Xin] Updated configuration documentation.
47b3848 [Reynold Xin] [SPARK-2953] Allow using short names for io compression codecs
In SPARK-1946(PR #900), configuration <code>spark.scheduler.minRegisteredExecutorsRatio</code> was introduced. However, in standalone mode, there is a race condition where isReady() can return true because totalExpectedExecutors has not been correctly set.
Because expected executors is uncertain in standalone mode, the PR try to use CPU cores(<code>--total-executor-cores</code>) as expected resources to judge whether SchedulerBackend is ready.
Author: li-zhihui <zhihui.li@intel.com>
Author: Li Zhihui <zhihui.li@intel.com>
Closes#1525 from li-zhihui/fixre4s and squashes the following commits:
e9a630b [Li Zhihui] Rename variable totalExecutors and clean codes
abf4860 [Li Zhihui] Push down variable totalExpectedResources to children classes
ca54bd9 [li-zhihui] Format log with String interpolation
88c7dc6 [li-zhihui] Few codes and docs refactor
41cf47e [li-zhihui] Fix race condition at SchedulerBackend.isReady in standalone mode
As described in https://issues.apache.org/jira/browse/SPARK-2787, right now sort-based shuffle is more expensive than hash-based for map operations that do no partial aggregation or sorting, such as groupByKey. This is because it has to serialize each data item twice (once when spilling to intermediate files, and then again when merging these files object-by-object). This patch adds a code path to just write separate files directly if the # of output partitions is small, and concatenate them at the end to produce a sorted file.
On the unit test side, I added some tests that force or don't force this bypass path to be used, and checked that our tests for other features (e.g. all the operations) cover both cases.
Author: Matei Zaharia <matei@databricks.com>
Closes#1799 from mateiz/SPARK-2787 and squashes the following commits:
88cf26a [Matei Zaharia] Fix rebase
10233af [Matei Zaharia] Review comments
398cb95 [Matei Zaharia] Fix looking up shuffle manager in conf
ca3efd9 [Matei Zaharia] Add docs for shuffle manager properties, and allow short names for them
d0ae3c5 [Matei Zaharia] Fix some comments
90d084f [Matei Zaharia] Add code path to bypass merge-sort in ExternalSorter, and tests
31e5d7c [Matei Zaharia] Move existing logic for writing partitioned files into ExternalSorter
The goal of this PR is to allow users of Spark to write tight firewall rules for their clusters. This is currently not possible because Spark uses random ports in many places, notably the communication between executors and drivers. The changes in this PR are based on top of ash211's changes in #1107.
The list covered here may or may not be the complete set of port needed for Spark to operate perfectly. However, as of the latest commit there are no known sources of random ports (except in tests). I have not documented a few of the more obscure configs.
My spark-env.sh looks like this:
```
export SPARK_MASTER_PORT=6060
export SPARK_WORKER_PORT=7070
export SPARK_MASTER_WEBUI_PORT=9090
export SPARK_WORKER_WEBUI_PORT=9091
```
and my spark-defaults.conf looks like this:
```
spark.master spark://andrews-mbp:6060
spark.driver.port 5001
spark.fileserver.port 5011
spark.broadcast.port 5021
spark.replClassServer.port 5031
spark.blockManager.port 5041
spark.executor.port 5051
```
Author: Andrew Or <andrewor14@gmail.com>
Author: Andrew Ash <andrew@andrewash.com>
Closes#1777 from andrewor14/configure-ports and squashes the following commits:
621267b [Andrew Or] Merge branch 'master' of github.com:apache/spark into configure-ports
8a6b820 [Andrew Or] Use a random UI port during tests
7da0493 [Andrew Or] Fix tests
523c30e [Andrew Or] Add test for isBindCollision
b97b02a [Andrew Or] Minor fixes
c22ad00 [Andrew Or] Merge branch 'master' of github.com:apache/spark into configure-ports
93d359f [Andrew Or] Executors connect to wrong port when collision occurs
d502e5f [Andrew Or] Handle port collisions when creating Akka systems
a2dd05c [Andrew Or] Patrick's comment nit
86461e2 [Andrew Or] Remove spark.executor.env.port and spark.standalone.client.port
1d2d5c6 [Andrew Or] Fix ports for standalone cluster mode
cb3be88 [Andrew Or] Various doc fixes (broken link, format etc.)
e837cde [Andrew Or] Remove outdated TODOs
bfbab28 [Andrew Or] Merge branch 'master' of github.com:apache/spark into configure-ports
de1b207 [Andrew Or] Update docs to reflect new ports
b565079 [Andrew Or] Add spark.ports.maxRetries
2551eb2 [Andrew Or] Remove spark.worker.watcher.port
151327a [Andrew Or] Merge branch 'master' of github.com:apache/spark into configure-ports
9868358 [Andrew Or] Add a few miscellaneous ports
6016e77 [Andrew Or] Add spark.executor.port
8d836e6 [Andrew Or] Also document SPARK_{MASTER/WORKER}_WEBUI_PORT
4d9e6f3 [Andrew Or] Fix super subtle bug
3f8e51b [Andrew Or] Correct erroneous docs...
e111d08 [Andrew Or] Add names for UI services
470f38c [Andrew Or] Special case non-"Address already in use" exceptions
1d7e408 [Andrew Or] Treat 0 ports specially + return correct ConnectionManager port
ba32280 [Andrew Or] Minor fixes
6b550b0 [Andrew Or] Assorted fixes
73fbe89 [Andrew Or] Move start service logic to Utils
ec676f4 [Andrew Or] Merge branch 'SPARK-2157' of github.com:ash211/spark into configure-ports
038a579 [Andrew Ash] Trust the server start function to report the port the service started on
7c5bdc4 [Andrew Ash] Fix style issue
0347aef [Andrew Ash] Unify port fallback logic to a single place
24a4c32 [Andrew Ash] Remove type on val to match surrounding style
9e4ad96 [Andrew Ash] Reformat for style checker
5d84e0e [Andrew Ash] Document new port configuration options
066dc7a [Andrew Ash] Fix up HttpServer port increments
cad16da [Andrew Ash] Add fallover increment logic for HttpServer
c5a0568 [Andrew Ash] Fix ConnectionManager to retry with increment
b80d2fd [Andrew Ash] Make Spark's block manager port configurable
17c79bb [Andrew Ash] Add a configuration option for spark-shell's class server
f34115d [Andrew Ash] SPARK-1176 Add port configuration for HttpBroadcast
49ee29b [Andrew Ash] SPARK-1174 Add port configuration for HttpFileServer
1c0981a [Andrew Ash] Make port in HttpServer configurable
This can substantially reduce memory usage during shuffle.
Author: Reynold Xin <rxin@apache.org>
Closes#1781 from rxin/SPARK-2503-spark.shuffle.file.buffer.kb and squashes the following commits:
104b8d8 [Reynold Xin] [SPARK-2503] Lower shuffle output buffer (spark.shuffle.file.buffer.kb) to 32KB.
Note that this also documents spark.executorEnv.* which to me means its public. If we don't want that please speak up.
Author: Thomas Graves <tgraves@apache.org>
Closes#1512 from tgravescs/SPARK-1680 and squashes the following commits:
11525df [Thomas Graves] more doc changes
553bad0 [Thomas Graves] fix documentation
152bf7c [Thomas Graves] fix docs
5382326 [Thomas Graves] try fix docs
32f86a4 [Thomas Graves] use configs for specifying environment variables on YARN
It was easier to combine these 2 jira since they touch many of the same places. This pr adds the following:
- adds modify acls
- adds admin acls (list of admins/users that get added to both view and modify acls)
- modify Kill button on UI to take modify acls into account
- changes config name of spark.ui.acls.enable to spark.acls.enable since I choose poorly in original name. We keep backwards compatibility so people can still use spark.ui.acls.enable. The acls should apply to any web ui as well as any CLI interfaces.
- send view and modify acls information on to YARN so that YARN interfaces can use (yarn cli for killing applications for example).
Author: Thomas Graves <tgraves@apache.org>
Closes#1196 from tgravescs/SPARK-1890 and squashes the following commits:
8292eb1 [Thomas Graves] review comments
b92ec89 [Thomas Graves] remove unneeded variable from applistener
4c765f4 [Thomas Graves] Add in admin acls
72eb0ac [Thomas Graves] Add modify acls
Author: Reynold Xin <rxin@apache.org>
Closes#1780 from rxin/kryo-init-size and squashes the following commits:
551b935 [Reynold Xin] [SPARK-2856] Decrease initial buffer size for Kryo to 64KB.
All these changes are from mridulm's work in #1609, but extracted here to fix this specific issue and make it easier to merge not 1.1. This particular set of changes is to make sure that we read exactly the right range of bytes from each spill file in EAOM: some serializers can write bytes after the last object (e.g. the TC_RESET flag in Java serialization) and that would confuse the previous code into reading it as part of the next batch. There are also improvements to cleanup to make sure files are closed.
In addition to bringing in the changes to ExternalAppendOnlyMap, I also copied them to the corresponding code in ExternalSorter and updated its test suite to test for the same issues.
Author: Matei Zaharia <matei@databricks.com>
Closes#1722 from mateiz/spark-2792 and squashes the following commits:
5d4bfb5 [Matei Zaharia] Make objectStreamReset counter count the last object written too
18fe865 [Matei Zaharia] Update docs on objectStreamReset
576ee83 [Matei Zaharia] Allow objectStreamReset to be 0
0374217 [Matei Zaharia] Remove super paranoid code to close file handles
bda37bb [Matei Zaharia] Implement Mridul's ExternalAppendOnlyMap fixes in ExternalSorter too
0d6dad7 [Matei Zaharia] Added Mridul's test changes for ExternalAppendOnlyMap
9a78e4b [Matei Zaharia] Add @mridulm's fixes to ExternalAppendOnlyMap for batch sizes
This is a sketch of a patch that allows the UI to show metrics for tasks that have not yet completed. It adds a heartbeat every 2 seconds from the executors to the driver, reporting metrics for all of the executor's tasks.
It still needs unit tests, polish, and cluster testing, but I wanted to put it up to get feedback on the approach.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#1056 from sryza/sandy-spark-2099 and squashes the following commits:
93b9fdb [Sandy Ryza] Up heartbeat interval to 10 seconds and other tidying
132aec7 [Sandy Ryza] Heartbeat and HeartbeatResponse are already Serializable as case classes
38dffde [Sandy Ryza] Additional review feedback and restore test that was removed in BlockManagerSuite
51fa396 [Sandy Ryza] Remove hostname race, add better comments about threading, and some stylistic improvements
3084f10 [Sandy Ryza] Make TaskUIData a case class again
3bda974 [Sandy Ryza] Stylistic fixes
0dae734 [Sandy Ryza] SPARK-2099. Report progress while task is running.
Author: Koert Kuipers <koert@tresata.com>
Closes#735 from koertkuipers/feat-kryo-max-buffersize and squashes the following commits:
15f6d81 [Koert Kuipers] change default for spark.kryoserializer.buffer.max.mb to 64mb and add some documentation
1bcc22c [Koert Kuipers] Merge branch 'master' into feat-kryo-max-buffersize
0c9f8eb [Koert Kuipers] make default for kryo max buffer size 16MB
143ec4d [Koert Kuipers] test resizable buffer in kryo Output
0732445 [Koert Kuipers] support setting maxCapacity to something different than capacity in kryo Output
**Problem.** When caching, we currently unroll the entire RDD partition before making sure we have enough free memory. This is a common cause for OOMs especially when (1) the BlockManager has little free space left in memory, and (2) the partition is large.
**Solution.** We maintain a global memory pool of `M` bytes shared across all threads, similar to the way we currently manage memory for shuffle aggregation. Then, while we unroll each partition, periodically check if there is enough space to continue. If not, drop enough RDD blocks to ensure we have at least `M` bytes to work with, then try again. If we still don't have enough space to unroll the partition, give up and drop the block to disk directly if applicable.
**New configurations.**
- `spark.storage.bufferFraction` - the value of `M` as a fraction of the storage memory. (default: 0.2)
- `spark.storage.safetyFraction` - a margin of safety in case size estimation is slightly off. This is the equivalent of the existing `spark.shuffle.safetyFraction`. (default 0.9)
For more detail, see the [design document](https://issues.apache.org/jira/secure/attachment/12651793/spark-1777-design-doc.pdf). Tests pending for performance and memory usage patterns.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1165 from andrewor14/them-rdd-memories and squashes the following commits:
e77f451 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
c7c8832 [Andrew Or] Simplify logic + update a few comments
269d07b [Andrew Or] Very minor changes to tests
6645a8a [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
b7e165c [Andrew Or] Add new tests for unrolling blocks
f12916d [Andrew Or] Slightly clean up tests
71672a7 [Andrew Or] Update unrollSafely tests
369ad07 [Andrew Or] Correct ensureFreeSpace and requestMemory behavior
f4d035c [Andrew Or] Allow one thread to unroll multiple blocks
a66fbd2 [Andrew Or] Rename a few things + update comments
68730b3 [Andrew Or] Fix weird scalatest behavior
e40c60d [Andrew Or] Fix MIMA excludes
ff77aa1 [Andrew Or] Fix tests
1a43c06 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
b9a6eee [Andrew Or] Simplify locking behavior on unrollMemoryMap
ed6cda4 [Andrew Or] Formatting fix (super minor)
f9ff82e [Andrew Or] putValues -> putIterator + putArray
beb368f [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
8448c9b [Andrew Or] Fix tests
a49ba4d [Andrew Or] Do not expose unroll memory check period
69bc0a5 [Andrew Or] Always synchronize on putLock before unrollMemoryMap
3f5a083 [Andrew Or] Simplify signature of ensureFreeSpace
dce55c8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
8288228 [Andrew Or] Synchronize put and unroll properly
4f18a3d [Andrew Or] bufferFraction -> unrollFraction
28edfa3 [Andrew Or] Update a few comments / log messages
728323b [Andrew Or] Do not synchronize every 1000 elements
5ab2329 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
129c441 [Andrew Or] Fix bug: Use toArray rather than array
9a65245 [Andrew Or] Update a few comments + minor control flow changes
57f8d85 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
abeae4f [Andrew Or] Add comment clarifying the MEMORY_AND_DISK case
3dd96aa [Andrew Or] AppendOnlyBuffer -> Vector (+ a few small changes)
f920531 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
0871835 [Andrew Or] Add an effective storage level interface to BlockManager
64e7d4c [Andrew Or] Add/modify a few comments (minor)
8af2f35 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
4f4834e [Andrew Or] Use original storage level for blocks dropped to disk
ecc8c2d [Andrew Or] Fix binary incompatibility
24185ea [Andrew Or] Avoid dropping a block back to disk if reading from disk
2b7ee66 [Andrew Or] Fix bug in SizeTracking*
9b9a273 [Andrew Or] Fix tests
20eb3e5 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
649bdb3 [Andrew Or] Document spark.storage.bufferFraction
a10b0e7 [Andrew Or] Add initial memory request threshold + rename a few things
e9c3cb0 [Andrew Or] cacheMemoryMap -> unrollMemoryMap
198e374 [Andrew Or] Unfold -> unroll
0d50155 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
d9d02a8 [Andrew Or] Remove unused param in unfoldSafely
ec728d8 [Andrew Or] Add tests for safe unfolding of blocks
22b2209 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
078eb83 [Andrew Or] Add check for hasNext in PrimitiveVector.iterator
0871535 [Andrew Or] Fix tests in BlockManagerSuite
d68f31e [Andrew Or] Safely unfold blocks for all memory puts
5961f50 [Andrew Or] Fix tests
195abd7 [Andrew Or] Refactor: move unfold logic to MemoryStore
1e82d00 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
3ce413e [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
d5dd3b4 [Andrew Or] Free buffer memory in finally
ea02eec [Andrew Or] Fix tests
b8e1d9c [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
a8704c1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
e1b8b25 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
87aa75c [Andrew Or] Fix mima excludes again (typo)
11eb921 [Andrew Or] Clarify comment (minor)
50cae44 [Andrew Or] Remove now duplicate mima exclude
7de5ef9 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
df47265 [Andrew Or] Fix binary incompatibility
6d05a81 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories
f94f5af [Andrew Or] Update a few comments (minor)
776aec9 [Andrew Or] Prevent OOM if a single RDD partition is too large
bbd3eea [Andrew Or] Fix CacheManagerSuite to use Array
97ea499 [Andrew Or] Change BlockManager interface to use Arrays
c12f093 [Andrew Or] Add SizeTrackingAppendOnlyBuffer and tests
Author: Matei Zaharia <matei@databricks.com>
Closes#1593 from mateiz/spark-2680 and squashes the following commits:
3c949c4 [Matei Zaharia] Lower spark.shuffle.memoryFraction to 0.2 by default
The current default value of spark.serializer.objectStreamReset is 10,000.
When trying to re-partition (e.g., to 64 partitions) a large file (e.g., 500MB), containing 1MB records, the serializer will cache 10000 x 1MB x 64 ~= 640 GB which will cause out of memory errors.
This patch sets the default value to a more reasonable default value (100).
Author: Hossein <hossein@databricks.com>
Closes#1595 from falaki/objectStreamReset and squashes the following commits:
650a935 [Hossein] Updated documentation
1aa0df8 [Hossein] Reduce default value of spark.serializer.objectStreamReset
During aggregation in Python worker, if the memory usage is above spark.executor.memory, it will do disk spilling aggregation.
It will split the aggregation into multiple stage, in each stage, it will partition the aggregated data by hash and dump them into disks. After all the data are aggregated, it will merge all the stages together (partition by partition).
Author: Davies Liu <davies.liu@gmail.com>
Closes#1460 from davies/spill and squashes the following commits:
cad91bf [Davies Liu] call gc.collect() after data.clear() to release memory as much as possible.
37d71f7 [Davies Liu] balance the partitions
902f036 [Davies Liu] add shuffle.py into run-tests
dcf03a9 [Davies Liu] fix memory_info() of psutil
67e6eba [Davies Liu] comment for MAX_TOTAL_PARTITIONS
f6bd5d6 [Davies Liu] rollback next_limit() again, the performance difference is huge:
e74b785 [Davies Liu] fix code style and change next_limit to memory_limit
400be01 [Davies Liu] address all the comments
6178844 [Davies Liu] refactor and improve docs
fdd0a49 [Davies Liu] add long doc string for ExternalMerger
1a97ce4 [Davies Liu] limit used memory and size of objects in partitionBy()
e6cc7f9 [Davies Liu] Merge branch 'master' into spill
3652583 [Davies Liu] address comments
e78a0a0 [Davies Liu] fix style
24cec6a [Davies Liu] get local directory by SPARK_LOCAL_DIR
57ee7ef [Davies Liu] update docs
286aaff [Davies Liu] let spilled aggregation in Python configurable
e9a40f6 [Davies Liu] recursive merger
6edbd1f [Davies Liu] Hash based disk spilling aggregation
...spark-submit
The PR allows invocations like
spark-submit --class org.MyClass --spark.shuffle.spill false myjar.jar
Author: Sandy Ryza <sandy@cloudera.com>
Closes#1253 from sryza/sandy-spark-2310 and squashes the following commits:
1dc9855 [Sandy Ryza] More doc and cleanup
00edfb9 [Sandy Ryza] Review comments
91b244a [Sandy Ryza] Change format to --conf PROP=VALUE
8fabe77 [Sandy Ryza] SPARK-2310. Support arbitrary Spark properties on the command line with spark-submit
Author: Ian O Connell <ioconnell@twitter.com>
Closes#1377 from ianoc/feature/SPARK-2102 and squashes the following commits:
5498566 [Ian O Connell] Docs update suggested by Patrick
20e8555 [Ian O Connell] Slight style change
f92c294 [Ian O Connell] Add docs for new KryoSerializer option
f3735c8 [Ian O Connell] Add using a kryo resource pool for the SqlSerializer
4e5c342 [Ian O Connell] Register the SparkConf for kryo, it gets swept into serialization
665805a [Ian O Connell] Add a spark.kryo.registrationRequired option for configuring the Kryo Serializer
HttpBroadcastFactory is the current default broadcast factory. It sends the broadcast data to each worker one by one, which is slow when the cluster is big. TorrentBroadcastFactory scales much better than http. Maybe we should make torrent the default broadcast method.
Author: Xiangrui Meng <meng@databricks.com>
Closes#1437 from mengxr/bt-broadcast and squashes the following commits:
ed492fe [Xiangrui Meng] set default broadcast factory to torrent
Author: Reynold Xin <rxin@apache.org>
Closes#1417 from rxin/lz4 and squashes the following commits:
472f6a1 [Reynold Xin] Set the proper default.
9cf0b2f [Reynold Xin] Added LZ4 to compression codec in configuration page.
Based on Greg Bowyer's patch from JIRA https://issues.apache.org/jira/browse/SPARK-2399
Author: Reynold Xin <rxin@apache.org>
Closes#1416 from rxin/lz4 and squashes the following commits:
6c8fefe [Reynold Xin] Fixed typo.
8a14d38 [Reynold Xin] [SPARK-2399] Add support for LZ4 compression.
Because submitting tasks and registering executors are asynchronous, in most situation, early stages' tasks run without preferred locality.
A simple solution is sleeping few seconds in application, so that executors have enough time to register.
The PR add 2 configuration properties to make TaskScheduler submit tasks after a few of executors have been registered.
\# Submit tasks only after (registered executors / total executors) arrived the ratio, default value is 0
spark.scheduler.minRegisteredExecutorsRatio = 0.8
\# Whatever minRegisteredExecutorsRatio is arrived, submit tasks after the maxRegisteredWaitingTime(millisecond), default value is 30000
spark.scheduler.maxRegisteredExecutorsWaitingTime = 5000
Author: li-zhihui <zhihui.li@intel.com>
Closes#900 from li-zhihui/master and squashes the following commits:
b9f8326 [li-zhihui] Add logs & edit docs
1ac08b1 [li-zhihui] Add new configs to user docs
22ead12 [li-zhihui] Move waitBackendReady to postStartHook
c6f0522 [li-zhihui] Bug fix: numExecutors wasn't set & use constant DEFAULT_NUMBER_EXECUTORS
4d6d847 [li-zhihui] Move waitBackendReady to TaskSchedulerImpl.start & some code refactor
0ecee9a [li-zhihui] Move waitBackendReady from DAGScheduler.submitStage to TaskSchedulerImpl.submitTasks
4261454 [li-zhihui] Add docs for new configs & code style
ce0868a [li-zhihui] Code style, rename configuration property name of minRegisteredRatio & maxRegisteredWaitingTime
6cfb9ec [li-zhihui] Code style, revert default minRegisteredRatio of yarn to 0, driver get --num-executors in yarn/alpha
812c33c [li-zhihui] Fix driver lost --num-executors option in yarn-cluster mode
e7b6272 [li-zhihui] support yarn-cluster
37f7dc2 [li-zhihui] support yarn mode(percentage style)
3f8c941 [li-zhihui] submit stage after (configured ratio of) executors have been registered
Author: Issac Buenrostro <buenrostro@ooyala.com>
Closes#945 from ibuenros/SPARK-1341-throttle and squashes the following commits:
5514916 [Issac Buenrostro] Formatting changes, added documentation for streaming throttling, stricter unit tests for throttling.
62f395f [Issac Buenrostro] Add comments and license to streaming RateLimiter.scala
7066438 [Issac Buenrostro] Moved throttle code to RateLimiter class, smoother pushing when throttling active
ccafe09 [Issac Buenrostro] Throttle BlockGenerator to limit rate of data consumption.
Currently, in the default log4j configuration, all the executor logs get sent to the file <code>[executor-working-dir]/stderr</code>. This does not all log files to be rolled, so old logs cannot be removed.
Using log4j RollingFileAppender allows log4j logs to be rolled, but all the logs get sent to a different set of files, other than the files <code>stdout</code> and <code>stderr</code> . So the logs are not visible in the Spark web UI any more as Spark web UI only reads the files <code>stdout</code> and <code>stderr</code>. Furthermore, it still does not allow the stdout and stderr to be cleared periodically in case a large amount of stuff gets written to them (e.g. by explicit `println` inside map function).
This PR solves this by implementing a simple `RollingFileAppender` within Spark (disabled by default). When enabled (using configuration parameter `spark.executor.rollingLogs.enabled`), the logs can get rolled over either by time interval (set with `spark.executor.rollingLogs.interval`, set to daily by default), or by size of logs (set with `spark.executor.rollingLogs.size`). Finally, old logs can be automatically deleted by specifying how many of the latest log files to keep (set with `spark.executor.rollingLogs.keepLastN`). The web UI has also been modified to show the logs across the rolled-over files.
You can test this locally (without waiting a whole day) by setting configuration `spark.executor.rollingLogs.enabled=true` and `spark.executor.rollingLogs.interval=minutely`. Continuously generate logs by running spark jobs and the generated logs files would look like this (`stderr` and `stdout` are the most current log file that are being written to).
```
stderr
stderr--2014-05-27--14-37
stderr--2014-05-27--14-47
stderr--2014-05-27--15-05
stdout
stdout--2014-05-27--14-47
```
The web ui should show logs across these files.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#895 from tdas/rolling-logs and squashes the following commits:
fd8f87f [Tathagata Das] Minor change.
d326aee [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into rolling-logs
ad956c1 [Tathagata Das] Scala style fix.
1f0a6ec [Tathagata Das] Some more changes based on Patrick's PR comments.
c8bfe4e [Tathagata Das] Refactore FileAppender to a package spark.util.logging and broke up the file into multiple files. Changed configuration parameter names.
4224409 [Tathagata Das] Style fix.
108a9f8 [Tathagata Das] Added better constraint handling for rolling policies.
f7da977 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into rolling-logs
9134495 [Tathagata Das] Simplified rolling logs by removing Daily/Hourly/MinutelyRollingFileAppender, and removing the setting rollingLogs.enabled
312d874 [Tathagata Das] Minor fixes based on PR comments.
8a67d83 [Tathagata Das] Fixed comments.
b36cfd6 [Tathagata Das] Implemented RollingPolicy, TimeBasedRollingPolicy and SizeBasedRollingPolicy, and changed RollingFileAppender accordingly.
b7e8272 [Tathagata Das] Style fix,
374c9a9 [Tathagata Das] Added missing license.
24354ea [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into rolling-logs
6cc09c7 [Tathagata Das] Fixed bugs in rolling logs, and added more debug statements.
adf4910 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into rolling-logs
931f8fb [Tathagata Das] Changed log viewer in Spark web UI to handle rolling log files.
cb4fb6d [Tathagata Das] Added FileAppender and RollingFileAppender to generate rolling executor logs.
https://issues.apache.org/jira/browse/SPARK-1677
For compatibility with older versions of Spark it would be nice to have an option `spark.hadoop.validateOutputSpecs` (default true) for the user to disable the output directory existence checking
Author: CodingCat <zhunansjtu@gmail.com>
Closes#947 from CodingCat/SPARK-1677 and squashes the following commits:
7930f83 [CodingCat] miao
c0c0e03 [CodingCat] bug fix and doc update
5318562 [CodingCat] bug fix
13219b5 [CodingCat] allow user to disable output dir existence checking
This is a fairly large PR to clean up and update the docs for 1.0. The major changes are:
* A unified programming guide for all languages replaces language-specific ones and shows language-specific info in tabs
* New programming guide sections on key-value pairs, unit testing, input formats beyond text, migrating from 0.9, and passing functions to Spark
* Spark-submit guide moved to a separate page and expanded slightly
* Various cleanups of the menu system, security docs, and others
* Updated look of title bar to differentiate the docs from previous Spark versions
You can find the updated docs at http://people.apache.org/~matei/1.0-docs/_site/ and in particular http://people.apache.org/~matei/1.0-docs/_site/programming-guide.html.
Author: Matei Zaharia <matei@databricks.com>
Closes#896 from mateiz/1.0-docs and squashes the following commits:
03e6853 [Matei Zaharia] Some tweaks to configuration and YARN docs
0779508 [Matei Zaharia] tweak
ef671d4 [Matei Zaharia] Keep frames in JavaDoc links, and other small tweaks
1bf4112 [Matei Zaharia] Review comments
4414f88 [Matei Zaharia] tweaks
d04e979 [Matei Zaharia] Fix some old links to Java guide
a34ed33 [Matei Zaharia] tweak
541bb3b [Matei Zaharia] miscellaneous changes
fcefdec [Matei Zaharia] Moved submitting apps to separate doc
61d72b4 [Matei Zaharia] stuff
181f217 [Matei Zaharia] migration guide, remove old language guides
e11a0da [Matei Zaharia] Add more API functions
6a030a9 [Matei Zaharia] tweaks
8db0ae3 [Matei Zaharia] Added key-value pairs section
318d2c9 [Matei Zaharia] tweaks
1c81477 [Matei Zaharia] New section on basics and function syntax
e38f559 [Matei Zaharia] Actually added programming guide to Git
a33d6fe [Matei Zaharia] First pass at updating programming guide to support all languages, plus other tweaks throughout
3b6a876 [Matei Zaharia] More CSS tweaks
01ec8bf [Matei Zaharia] More CSS tweaks
e6d252e [Matei Zaharia] Change color of doc title bar to differentiate from 0.9.0
This PR improves and organizes the config option page
and makes a few other changes to config docs. See a preview here:
http://people.apache.org/~pwendell/config-improvements/configuration.html
The biggest changes are:
1. The configs for the standalone master/workers were moved to the
standalone page and out of the general config doc.
2. SPARK_LOCAL_DIRS was missing from the standalone docs.
3. Expanded discussion of injecting configs with spark-submit, including an
example.
4. Config options were organized into the following categories:
- Runtime Environment
- Shuffle Behavior
- Spark UI
- Compression and Serialization
- Execution Behavior
- Networking
- Scheduling
- Security
- Spark Streaming
Author: Patrick Wendell <pwendell@gmail.com>
Closes#880 from pwendell/config-cleanup and squashes the following commits:
93f56c3 [Patrick Wendell] Feedback from Matei
6f66efc [Patrick Wendell] More feedback
16ae776 [Patrick Wendell] Adding back header section
d9c264f [Patrick Wendell] Small fix
e0c1728 [Patrick Wendell] Response to Matei's review
27d57db [Patrick Wendell] Reverting changes to index.html (covered in #896)
e230ef9 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into config-cleanup
a374369 [Patrick Wendell] Line wrapping fixes
fdff7fc [Patrick Wendell] Merge remote-tracking branch 'apache/master' into config-cleanup
3289ea4 [Patrick Wendell] Pulling in changes from #856
106ee31 [Patrick Wendell] Small link fix
f7e79bc [Patrick Wendell] Re-organizing config options.
54b184d [Patrick Wendell] Adding standalone configs to the standalone page
592e94a [Patrick Wendell] Stash
29b5446 [Patrick Wendell] Better discussion of spark-submit in configuration docs
2d719ef [Patrick Wendell] Small fix
4af9e07 [Patrick Wendell] Adding SPARK_LOCAL_DIRS docs
204b248 [Patrick Wendell] Small fixes
https://issues.apache.org/jira/browse/SPARK-1903
Author: Andrew Ash <andrew@andrewash.com>
Closes#856 from ash211/SPARK-1903 and squashes the following commits:
6e7782a [Andrew Ash] Add the technology used on each port
1d9b5d3 [Andrew Ash] Document port for history server
56193ee [Andrew Ash] spark.ui.port becomes worker.ui.port and master.ui.port
a774c07 [Andrew Ash] Wording in network section
90e8237 [Andrew Ash] Use real :toc instead of the hand-written one
edaa337 [Andrew Ash] Master -> Standalone Cluster Master
57e8869 [Andrew Ash] Port -> Default Port
3d4d289 [Andrew Ash] Title to title case
c7d42d9 [Andrew Ash] [WIP] SPARK-1903 Add initial port listing for documentation
a416ae9 [Andrew Ash] Word wrap to 100 lines
1. Add < code > to configuration options
2. List env variables in tabular format to be consistent with other pages.
3. Moved Viewing Spark Properties section up.
This is against branch-1.0, but should be cherry picked into master as well.
Author: Reynold Xin <rxin@apache.org>
Closes#851 from rxin/doc-config and squashes the following commits:
28ac0d3 [Reynold Xin] Add <code> to configuration options, and list env variables in a table.
(cherry picked from commit 75af8bd333)
Signed-off-by: Reynold Xin <rxin@apache.org>
The example code on the configuration page currently does not compile.
Author: Andrew Or <andrewor14@gmail.com>
Closes#842 from andrewor14/conf-docs and squashes the following commits:
aabff57 [Andrew Or] Correct example of creating a new SparkConf
This causes an unrecoverable error for applications that are running for longer
than 7 days that have jars added to the SparkContext, as the jars are cleaned up
even though the application is still running.
Author: Aaron Davidson <aaron@databricks.com>
Closes#800 from aarondav/shitty-defaults and squashes the following commits:
a573fbb [Aaron Davidson] SPARK-1860: Do not cleanup application work/ directories by default
