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* [MINOR][BUILD] Fix Java Linter `LineLength` errorsDongjoon Hyun2016-07-192-2/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes four java linter `LineLength` errors. Those are all `LineLength` errors, but we had better remove all java linter errors before release. ## How was this patch tested? After pass the Jenkins, `./dev/lint-java`. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14255 from dongjoon-hyun/minor_java_linter.
* [SPARK-16505][YARN] Optionally propagate error during shuffle service startup.Marcelo Vanzin2016-07-141-32/+43
| | | | | | | | | | | This prevents the NM from starting when something is wrong, which would lead to later errors which are confusing and harder to debug. Added a unit test to verify startup fails if something is wrong. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #14162 from vanzin/SPARK-16505.
* [SPARK-14963][MINOR][YARN] Fix typo in YarnShuffleService recovery file namejerryshao2016-07-141-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Due to the changes of [SPARK-14963](https://issues.apache.org/jira/browse/SPARK-14963), external shuffle recovery file name is changed mistakenly, so here change it back to the previous file name. This only affects the master branch, branch-2.0 is correct [here](https://github.com/apache/spark/blob/branch-2.0/common/network-yarn/src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java#L195). ## How was this patch tested? N/A Author: jerryshao <sshao@hortonworks.com> Closes #14197 from jerryshao/fix-typo-file-name.
* [MINOR] Fix Java style errors and remove unused importsXin Ren2016-07-132-4/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix Java style errors and remove unused imports, which are randomly found ## How was this patch tested? Tested on my local machine. Author: Xin Ren <iamshrek@126.com> Closes #14161 from keypointt/SPARK-16437.
* [SPARK-16405] Add metrics and source for external shuffle serviceYangyang Liu2016-07-124-17/+105
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Since externalShuffleService is essential for spark, better monitoring for shuffle service is necessary. In order to do so, we added various metrics in shuffle service and imported into ExternalShuffleServiceSource for metric system. Metrics added in shuffle service: * registeredExecutorsSize * openBlockRequestLatencyMillis * registerExecutorRequestLatencyMillis * blockTransferRateBytes JIRA Issue: https://issues.apache.org/jira/browse/SPARK-16405 ## How was this patch tested? Some test cases are added to verify metrics as expected in metric system. Those unit test cases are shown in `ExternalShuffleBlockHandlerSuite ` Author: Yangyang Liu <yangyangliu@fb.com> Closes #14080 from lovexi/yangyang-metrics.
* [SPARK-16477] Bump master version to 2.1.0-SNAPSHOTReynold Xin2016-07-116-6/+6
| | | | | | | | | | | | ## What changes were proposed in this pull request? After SPARK-16476 (committed earlier today as #14128), we can finally bump the version number. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #14130 from rxin/SPARK-16477.
* [SPARK-16420] Ensure compression streams are closed.Ryan Blue2016-07-081-0/+23
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This uses the try/finally pattern to ensure streams are closed after use. `UnsafeShuffleWriter` wasn't closing compression streams, causing them to leak resources until garbage collected. This was causing a problem with codecs that use off-heap memory. ## How was this patch tested? Current tests are sufficient. This should not change behavior. Author: Ryan Blue <blue@apache.org> Closes #14093 from rdblue/SPARK-16420-unsafe-shuffle-writer-leak.
* [SPARK-16021] Fill freed memory in test to help catch correctness bugsEric Liang2016-07-066-3/+56
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patches `MemoryAllocator` to fill clean and freed memory with known byte values, similar to https://github.com/jemalloc/jemalloc/wiki/Use-Case:-Find-a-memory-corruption-bug . Memory filling is flag-enabled in test only by default. ## How was this patch tested? Unit test that it's on in test. cc sameeragarwal Author: Eric Liang <ekl@databricks.com> Closes #13983 from ericl/spark-16021.
* [SPARK-16018][SHUFFLE] Shade netty to load shuffle jar in NodemangerDhruve Ashar2016-06-171-0/+7
| | | | | | | | | | | | ## What changes were proposed in this pull request? Shade the netty.io namespace so that we can use it in shuffle independent of the dependencies being pulled by hadoop jars. ## How was this patch tested? Ran a decent job involving shuffle write/read and tested the new spark-x-yarn-shuffle jar. After shading netty.io namespace, the nodemanager loads and shuffle job completes successfully. Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #13739 from dhruve/bug/SPARK-16018.
* [SPARK-15391] [SQL] manage the temporary memory of timsortDavies Liu2016-06-031-1/+1
| | | | | | | | | | | | | | | | | | ## 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.
* [MINOR] Resolve a number of miscellaneous build warningsSean Owen2016-05-291-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This change resolves a number of build warnings that have accumulated, before 2.x. It does not address a large number of deprecation warnings, especially related to the Accumulator API. That will happen separately. ## How was this patch tested? Jenkins Author: Sean Owen <sowen@cloudera.com> Closes #13377 from srowen/BuildWarnings.
* [SPARK-15386][CORE] Master doesn't compile against Java 1.7 / Process.isAliveSean Owen2016-05-181-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Remove call to Process.isAlive -- Java 8 only. Introduced in https://github.com/apache/spark/pull/13042 / SPARK-15263 ## How was this patch tested? Jenkins tests Author: Sean Owen <sowen@cloudera.com> Closes #13174 from srowen/SPARK-15386.
* [SPARK-15263][CORE] Make shuffle service dir cleanup faster by using `rm -rf`Tejas Patil2016-05-183-16/+61
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Jira: https://issues.apache.org/jira/browse/SPARK-15263 The current logic for directory cleanup is slow because it does directory listing, recurses over child directories, checks for symbolic links, deletes leaf files and finally deletes the dirs when they are empty. There is back-and-forth switching from kernel space to user space while doing this. Since most of the deployment backends would be Unix systems, we could essentially just do `rm -rf` so that entire deletion logic runs in kernel space. The current Java based impl in Spark seems to be similar to what standard libraries like guava and commons IO do (eg. http://svn.apache.org/viewvc/commons/proper/io/trunk/src/main/java/org/apache/commons/io/FileUtils.java?view=markup#l1540). However, guava removed this method in favour of shelling out to an operating system command (like in this PR). See the `Deprecated` note in older javadocs for guava for details : http://google.github.io/guava/releases/10.0.1/api/docs/com/google/common/io/Files.html#deleteRecursively(java.io.File) Ideally, Java should be providing such APIs so that users won't have to do such things to get platform specific code. Also, its not just about speed, but also handling race conditions while doing at FS deletions is tricky. I could find this bug for Java in similar context : http://bugs.java.com/bugdatabase/view_bug.do?bug_id=7148952 ## How was this patch tested? I am relying on existing test cases to test the method. If there are suggestions about testing it, welcome to hear about it. ## Performance gains *Input setup* : Created a nested directory structure of depth 3 and each entry having 50 sub-dirs. The input being cleaned up had total ~125k dirs. Ran both approaches (in isolation) for 6 times to get average numbers: Native Java cleanup | `rm -rf` as a separate process ------------ | ------------- 10.04 sec | 4.11 sec This change made deletion 2.4 times faster for the given test input. Author: Tejas Patil <tejasp@fb.com> Closes #13042 from tejasapatil/delete_recursive.
* [SPARK-15290][BUILD] Move annotations, like @Since / @DeveloperApi, into ↵Sean Owen2016-05-1713-11/+234
| | | | | | | | | | | | | | | | | | spark-tags ## What changes were proposed in this pull request? (See https://github.com/apache/spark/pull/12416 where most of this was already reviewed and committed; this is just the module structure and move part. This change does not move the annotations into test scope, which was the apparently problem last time.) Rename `spark-test-tags` -> `spark-tags`; move common annotations like `Since` to `spark-tags` ## How was this patch tested? Jenkins tests. Author: Sean Owen <sowen@cloudera.com> Closes #13074 from srowen/SPARK-15290.
* [SPARK-14963][YARN] Using recoveryPath if NM recovery is enabledjerryshao2016-05-101-11/+53
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? From Hadoop 2.5+, Yarn NM supports NM recovery which using recovery path for auxiliary services such as spark_shuffle, mapreduce_shuffle. So here change to use this path install of NM local dir if NM recovery is enabled. ## How was this patch tested? Unit test + local test. Author: jerryshao <sshao@hortonworks.com> Closes #12994 from jerryshao/SPARK-14963.
* [SPARK-15178][CORE] Remove LazyFileRegion instead use netty's DefaultFileRegionSandeep Singh2016-05-072-112/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? Remove LazyFileRegion instead use netty's DefaultFileRegion, since It was created so that we didn't create a file descriptor before having to send the file. ## How was this patch tested? Existing tests Author: Sandeep Singh <sandeep@techaddict.me> Closes #12977 from techaddict/SPARK-15178.
* [SPARK-15134][EXAMPLE] Indent SparkSession builder patterns and update ↵Dongjoon Hyun2016-05-051-2/+5
| | | | | | | | | | | | | | | | | | | binary_classification_metrics_example.py ## What changes were proposed in this pull request? This issue addresses the comments in SPARK-15031 and also fix java-linter errors. - Use multiline format in SparkSession builder patterns. - Update `binary_classification_metrics_example.py` to use `SparkSession`. - Fix Java Linter errors (in SPARK-13745, SPARK-15031, and so far) ## How was this patch tested? After passing the Jenkins tests and run `dev/lint-java` manually. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12911 from dongjoon-hyun/SPARK-15134.
* [SPARK-15121] Improve logging of external shuffle handlerThomas Graves2016-05-041-1/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add more informative logging in the external shuffle service to aid in debugging who is connecting to the YARN Nodemanager when the external shuffle service runs under it. ## How was this patch tested? Ran and saw logs coming out in log file. Author: Thomas Graves <tgraves@staydecay.corp.gq1.yahoo.com> Closes #12900 from tgravescs/SPARK-15121.
* Revert "[SPARK-14613][ML] Add @Since into the matrix and vector classes in ↵Yin Huai2016-04-2812-86/+8
| | | | | | spark-mllib-local" This reverts commit dae538a4d7c36191c1feb02ba87ffc624ab960dc.
* [SPARK-14613][ML] Add @Since into the matrix and vector classes in ↵Pravin Gadakh2016-04-2812-8/+86
| | | | | | | | | | | | | | | | spark-mllib-local ## What changes were proposed in this pull request? This PR adds `since` tag into the matrix and vector classes in spark-mllib-local. ## How was this patch tested? Scala-style checks passed. Author: Pravin Gadakh <prgadakh@in.ibm.com> Closes #12416 from pravingadakh/SPARK-14613.
* [SPARK-14756][CORE] Use parseLong instead of valueOfAzeem Jiva2016-04-261-4/+4
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Use Long.parseLong which returns a primative. Use a series of appends() reduces the creation of an extra StringBuilder type ## How was this patch tested? Unit tests Author: Azeem Jiva <azeemj@gmail.com> Closes #12520 from javawithjiva/minor.
* [SPARK-14731][shuffle]Revert SPARK-12130 to make 2.0 shuffle service ↵Lianhui Wang2016-04-256-27/+31
| | | | | | | | | | | | | | | compatible with 1.x ## What changes were proposed in this pull request? SPARK-12130 make 2.0 shuffle service incompatible with 1.x. So from discussion: [http://apache-spark-developers-list.1001551.n3.nabble.com/YARN-Shuffle-service-and-its-compatibility-td17222.html](url) we should maintain compatibility between Spark 1.x and Spark 2.x's shuffle service. I put string comparison into executor's register at first avoid string comparison in getBlockData every time. ## How was this patch tested? N/A Author: Lianhui Wang <lianhuiwang09@gmail.com> Closes #12568 from lianhuiwang/SPARK-14731.
* [SPARK-14667] Remove HashShuffleManagerReynold Xin2016-04-186-90/+10
| | | | | | | | | | | | ## What changes were proposed in this pull request? The sort shuffle manager has been the default since Spark 1.2. It is time to remove the old hash shuffle manager. ## How was this patch tested? Removed some tests related to the old manager. Author: Reynold Xin <rxin@databricks.com> Closes #12423 from rxin/SPARK-14667.
* [SPARK-14547] Avoid DNS resolution for reusing connectionsReynold Xin2016-04-121-11/+20
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch changes the connection creation logic in the network client module to avoid DNS resolution when reusing connections. ## How was this patch tested? Testing in production. This is too difficult to test in isolation (for high fidelity unit tests, we'd need to change the DNS resolution behavior in the JVM). Author: Reynold Xin <rxin@databricks.com> Closes #12315 from rxin/SPARK-14547.
* [SPARK-14134][CORE] Change the package name used for shading classes.Marcelo Vanzin2016-04-061-2/+2
| | | | | | | | | | | | | | | The current package name uses a dash, which is a little weird but seemed to work. That is, until a new test tried to mock a class that references one of those shaded types, and then things started failing. Most changes are just noise to fix the logging configs. For reference, SPARK-8815 also raised this issue, although at the time it did not cause any issues in Spark, so it was not addressed. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11941 from vanzin/SPARK-14134.
* [SPARK-14290][CORE][NETWORK] avoid significant memory copy in netty's transferToZhang, Liye2016-04-061-1/+29
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When netty transfer data that is not `FileRegion`, data will be in format of `ByteBuf`, If the data is large, there will occur significant performance issue because there is memory copy underlying in `sun.nio.ch.IOUtil.write`, the CPU is 100% used, and network is very low. In this PR, if data size is large, we will split it into small chunks to call `WritableByteChannel.write()`, so that avoid wasting of memory copy. Because the data can't be written within a single write, and it will call `transferTo` multiple times. ## How was this patch tested? Spark unit test and manual test. Manual test: `sc.parallelize(Array(1,2,3),3).mapPartitions(a=>Array(new Array[Double](1024 * 1024 * 50)).iterator).reduce((a,b)=> a).length` For more details, please refer to [SPARK-14290](https://issues.apache.org/jira/browse/SPARK-14290) Author: Zhang, Liye <liye.zhang@intel.com> Closes #12083 from liyezhang556520/spark-14290.
* [SPARK-14355][BUILD] Fix typos in Exception/Testcase/Comments and static ↵Dongjoon Hyun2016-04-034-6/+6
| | | | | | | | | | | | | | | | | | | | | analysis results ## What changes were proposed in this pull request? This PR contains the following 5 types of maintenance fix over 59 files (+94 lines, -93 lines). - Fix typos(exception/log strings, testcase name, comments) in 44 lines. - Fix lint-java errors (MaxLineLength) in 6 lines. (New codes after SPARK-14011) - Use diamond operators in 40 lines. (New codes after SPARK-13702) - Fix redundant semicolon in 5 lines. - Rename class `InferSchemaSuite` to `CSVInferSchemaSuite` in CSVInferSchemaSuite.scala. ## How was this patch tested? Manual and pass the Jenkins tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12139 from dongjoon-hyun/SPARK-14355.
* [SPARK-13992] Add support for off-heap cachingJosh Rosen2016-04-011-0/+32
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch adds support for caching blocks in the executor processes using direct / off-heap memory. ## User-facing changes **Updated semantics of `OFF_HEAP` storage level**: In Spark 1.x, the `OFF_HEAP` storage level indicated that an RDD should be cached in Tachyon. Spark 2.x removed the external block store API that Tachyon caching was based on (see #10752 / SPARK-12667), so `OFF_HEAP` became an alias for `MEMORY_ONLY_SER`. As of this patch, `OFF_HEAP` means "serialized and cached in off-heap memory or on disk". Via the `StorageLevel` constructor, `useOffHeap` can be set if `serialized == true` and can be used to construct custom storage levels which support replication. **Storage UI reporting**: the storage UI will now report whether in-memory blocks are stored on- or off-heap. **Only supported by UnifiedMemoryManager**: for simplicity, this feature is only supported when the default UnifiedMemoryManager is used; applications which use the legacy memory manager (`spark.memory.useLegacyMode=true`) are not currently able to allocate off-heap storage memory, so using off-heap caching will fail with an error when legacy memory management is enabled. Given that we plan to eventually remove the legacy memory manager, this is not a significant restriction. **Memory management policies:** the policies for dividing available memory between execution and storage are the same for both on- and off-heap memory. For off-heap memory, the total amount of memory available for use by Spark is controlled by `spark.memory.offHeap.size`, which is an absolute size. Off-heap storage memory obeys `spark.memory.storageFraction` in order to control the amount of unevictable storage memory. For example, if `spark.memory.offHeap.size` is 1 gigabyte and Spark uses the default `storageFraction` of 0.5, then up to 500 megabytes of off-heap cached blocks will be protected from eviction due to execution memory pressure. If necessary, we can split `spark.memory.storageFraction` into separate on- and off-heap configurations, but this doesn't seem necessary now and can be done later without any breaking changes. **Use of off-heap memory does not imply use of off-heap execution (or vice-versa)**: for now, the settings controlling the use of off-heap execution memory (`spark.memory.offHeap.enabled`) and off-heap caching are completely independent, so Spark SQL can be configured to use off-heap memory for execution while continuing to cache blocks on-heap. If desired, we can change this in a followup patch so that `spark.memory.offHeap.enabled` affect the default storage level for cached SQL tables. ## Internal changes - Rename `ByteArrayChunkOutputStream` to `ChunkedByteBufferOutputStream` - It now returns a `ChunkedByteBuffer` instead of an array of byte arrays. - Its constructor now accept an `allocator` function which is called to allocate `ByteBuffer`s. This allows us to control whether it allocates regular ByteBuffers or off-heap DirectByteBuffers. - Because block serialization is now performed during the unroll process, a `ChunkedByteBufferOutputStream` which is configured with a `DirectByteBuffer` allocator will use off-heap memory for both unroll and storage memory. - The `MemoryStore`'s MemoryEntries now tracks whether blocks are stored on- or off-heap. - `evictBlocksToFreeSpace()` now accepts a `MemoryMode` parameter so that we don't try to evict off-heap blocks in response to on-heap memory pressure (or vice-versa). - Make sure that off-heap buffers are properly de-allocated during MemoryStore eviction. - The JVM limits the total size of allocated direct byte buffers using the `-XX:MaxDirectMemorySize` flag and the default tends to be fairly low (< 512 megabytes in some JVMs). To work around this limitation, this patch adds a custom DirectByteBuffer allocator which ignores this memory limit. Author: Josh Rosen <joshrosen@databricks.com> Closes #11805 from JoshRosen/off-heap-caching.
* [SPARK-14242][CORE][NETWORK] avoid copy in compositeBuffer for frame decoderZhang, Liye2016-03-311-1/+1
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In this patch, we set the initial `maxNumComponents` to `Integer.MAX_VALUE` instead of the default size ( which is 16) when allocating `compositeBuffer` in `TransportFrameDecoder` because `compositeBuffer` will introduce too many memory copies underlying if `compositeBuffer` is with default `maxNumComponents` when the frame size is large (which result in many transport messages). For details, please refer to [SPARK-14242](https://issues.apache.org/jira/browse/SPARK-14242). ## How was this patch tested? spark unit tests and manual tests. For manual tests, we can reproduce the performance issue with following code: `sc.parallelize(Array(1,2,3),3).mapPartitions(a=>Array(new Array[Double](1024 * 1024 * 50)).iterator).reduce((a,b)=> a).length` It's easy to see the performance gain, both from the running time and CPU usage. Author: Zhang, Liye <liye.zhang@intel.com> Closes #12038 from liyezhang556520/spark-14242.
* [SPARK-14254][CORE] Add logs to help investigate the network performanceShixiong Zhu2016-03-291-1/+4
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? It would be very helpful for network performance investigation if we log the time spent on connecting and resolving host. ## How was this patch tested? Jenkins unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #12046 from zsxwing/connection-time.
* [SPARK-12181] Check Cached unaligned-access capability before using Unsafetedyu2016-03-291-0/+28
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? For MemoryMode.OFF_HEAP, Unsafe.getInt etc. are used with no restriction. However, the Oracle implementation uses these methods only if the class variable unaligned (commented as "Cached unaligned-access capability") is true, which seems to be calculated whether the architecture is i386, x86, amd64, or x86_64. I think we should perform similar check for the use of Unsafe. Reference: https://github.com/netty/netty/blob/4.1/common/src/main/java/io/netty/util/internal/PlatformDependent0.java#L112 ## How was this patch tested? Unit test suite Author: tedyu <yuzhihong@gmail.com> Closes #11943 from tedyu/master.
* [SPARK-13622][YARN] Issue creating level db for YARN shuffle servicenfraison2016-03-281-3/+4
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch will ensure that we trim all path set in yarn.nodemanager.local-dirs and that the the scheme is well removed so the level db can be created. ## How was this patch tested? manual tests. Author: nfraison <nfraison@yahoo.fr> Closes #11475 from ashangit/level_db_creation_issue.
* [SPARK-14011][CORE][SQL] Enable `LineLength` Java checkstyle ruleDongjoon Hyun2016-03-2121-31/+31
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? [Spark Coding Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide) has 100-character limit on lines, but it's disabled for Java since 11/09/15. This PR enables **LineLength** checkstyle again. To help that, this also introduces **RedundantImport** and **RedundantModifier**, too. The following is the diff on `checkstyle.xml`. ```xml - <!-- TODO: 11/09/15 disabled - the lengths are currently > 100 in many places --> - <!-- <module name="LineLength"> <property name="max" value="100"/> <property name="ignorePattern" value="^package.*|^import.*|a href|href|http://|https://|ftp://"/> </module> - --> <module name="NoLineWrap"/> <module name="EmptyBlock"> <property name="option" value="TEXT"/> -167,5 +164,7 </module> <module name="CommentsIndentation"/> <module name="UnusedImports"/> + <module name="RedundantImport"/> + <module name="RedundantModifier"/> ``` ## How was this patch tested? Currently, `lint-java` is disabled in Jenkins. It needs a manual test. After passing the Jenkins tests, `dev/lint-java` should passes locally. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11831 from dongjoon-hyun/SPARK-14011.
* [SPARK-10680][TESTS] Increase 'connectionTimeout' to make ↵Shixiong Zhu2016-03-191-5/+5
| | | | | | | | | | | | | | | | RequestTimeoutIntegrationSuite more stable ## What changes were proposed in this pull request? Increase 'connectionTimeout' to make RequestTimeoutIntegrationSuite more stable ## How was this patch tested? Existing unit tests Author: Shixiong Zhu <shixiong@databricks.com> Closes #11833 from zsxwing/SPARK-10680.
* [SPARK-13921] Store serialized blocks as multiple chunks in MemoryStoreJosh Rosen2016-03-171-1/+1
| | | | | | | | | | | | This patch modifies the BlockManager, MemoryStore, and several other storage components so that serialized cached blocks are stored as multiple small chunks rather than as a single contiguous ByteBuffer. This change will help to improve the efficiency of memory allocation and the accuracy of memory accounting when serializing blocks. Our current serialization code uses a ByteBufferOutputStream, which doubles and re-allocates its backing byte array; this increases the peak memory requirements during serialization (since we need to hold extra memory while expanding the array). In addition, we currently don't account for the extra wasted space at the end of the ByteBuffer's backing array, so a 129 megabyte serialized block may actually consume 256 megabytes of memory. After switching to storing blocks in multiple chunks, we'll be able to efficiently trim the backing buffers so that no space is wasted. This change is also a prerequisite to being able to cache blocks which are larger than 2GB (although full support for that depends on several other changes which have not bee implemented yet). Author: Josh Rosen <joshrosen@databricks.com> Closes #11748 from JoshRosen/chunked-block-serialization.
* [SPARK-13823][SPARK-13397][SPARK-13395][CORE] More warnings, StandardCharset ↵Sean Owen2016-03-168-104/+93
| | | | | | | | | | | | | | | | | | | | follow up ## What changes were proposed in this pull request? Follow up to https://github.com/apache/spark/pull/11657 - Also update `String.getBytes("UTF-8")` to use `StandardCharsets.UTF_8` - And fix one last new Coverity warning that turned up (use of unguarded `wait()` replaced by simpler/more robust `java.util.concurrent` classes in tests) - And while we're here cleaning up Coverity warnings, just fix about 15 more build warnings ## How was this patch tested? Jenkins tests Author: Sean Owen <sowen@cloudera.com> Closes #11725 from srowen/SPARK-13823.2.
* [MINOR][COMMON] Fix copy-paste oversight in variable namingBjorn Jonsson2016-03-141-2/+2
| | | | | | | | | | ## What changes were proposed in this pull request? JavaUtils.java has methods to convert time and byte strings for internal use, this change renames a variable used in byteStringAs(), from timeError to byteError. Author: Bjorn Jonsson <bjornjon@gmail.com> Closes #11695 from bjornjon/master.
* [SPARK-12583][MESOS] Mesos shuffle service: Don't delete shuffle files ↵Bertrand Bossy2016-03-144-18/+130
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | before application has stopped ## Problem description: Mesos shuffle service is completely unusable since Spark 1.6.0 . The problem seems to occur since the move from akka to netty in the networking layer. Until now, a connection from the driver to each shuffle service was used as a signal for the shuffle service to determine, whether the driver is still running. Since 1.6.0, this connection is closed after spark.shuffle.io.connectionTimeout (or spark.network.timeout if the former is not set) due to it being idle. The shuffle service interprets this as a signal that the driver has stopped, despite the driver still being alive. Thus, shuffle files are deleted before the application has stopped. ### Context and analysis: spark shuffle fails with mesos after 2mins: https://issues.apache.org/jira/browse/SPARK-12583 External shuffle service broken w/ Mesos: https://issues.apache.org/jira/browse/SPARK-13159 This is a follow up on #11207 . ## What changes were proposed in this pull request? This PR adds a heartbeat signal from the Driver (in MesosExternalShuffleClient) to all registered external mesos shuffle service instances. In MesosExternalShuffleBlockHandler, a thread periodically checks whether a driver has timed out and cleans an application's shuffle files if this is the case. ## How was the this patch tested? This patch has been tested on a small mesos test cluster using the spark-shell. Log output from mesos shuffle service: ``` 16/02/19 15:13:45 INFO mesos.MesosExternalShuffleBlockHandler: Received registration request from app 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 (remote address /xxx.xxx.xxx.xxx:52391, heartbeat timeout 120000 ms). 16/02/19 15:13:47 INFO shuffle.ExternalShuffleBlockResolver: Registered executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=3} with ExecutorShuffleInfo{localDirs=[/foo/blockmgr-c84c0697-a3f9-4f61-9c64-4d3ee227c047], subDirsPerLocalDir=64, shuffleManager=sort} 16/02/19 15:13:47 INFO shuffle.ExternalShuffleBlockResolver: Registered executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=7} with ExecutorShuffleInfo{localDirs=[/foo/blockmgr-bf46497a-de80-47b9-88f9-563123b59e03], subDirsPerLocalDir=64, shuffleManager=sort} 16/02/19 15:16:02 INFO mesos.MesosExternalShuffleBlockHandler: Application 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 timed out. Removing shuffle files. 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Application 294def07-3249-4e0f-8d71-bf8c83c58a50-0018 removed, cleanupLocalDirs = true 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Cleaning up executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=3}'s 1 local dirs 16/02/19 15:16:02 INFO shuffle.ExternalShuffleBlockResolver: Cleaning up executor AppExecId{appId=294def07-3249-4e0f-8d71-bf8c83c58a50-0018, execId=7}'s 1 local dirs ``` Note: there are 2 executors running on this slave. Author: Bertrand Bossy <bertrand.bossy@teralytics.net> Closes #11272 from bbossy/SPARK-12583-mesos-shuffle-service-heartbeat.
* [SPARK-13823][CORE][STREAMING][SQL] Always specify Charset in String <-> ↵Sean Owen2016-03-138-51/+55
| | | | | | | | | | | | | | | | | | | | byte[] conversions (and remaining Coverity items) ## What changes were proposed in this pull request? - Fixes calls to `new String(byte[])` or `String.getBytes()` that rely on platform default encoding, to use UTF-8 - Same for `InputStreamReader` and `OutputStreamWriter` constructors - Standardizes on UTF-8 everywhere - Standardizes specifying the encoding with `StandardCharsets.UTF-8`, not the Guava constant or "UTF-8" (which means handling `UnuspportedEncodingException`) - (also addresses the other remaining Coverity scan issues, which are pretty trivial; these are separated into commit https://github.com/srowen/spark/commit/1deecd8d9ca986d8adb1a42d315890ce5349d29c ) ## How was this patch tested? Jenkins tests Author: Sean Owen <sowen@cloudera.com> Closes #11657 from srowen/SPARK-13823.
* [SPARK-13702][CORE][SQL][MLLIB] Use diamond operator for generic instance ↵Dongjoon Hyun2016-03-091-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | creation in Java code. ## What changes were proposed in this pull request? In order to make `docs/examples` (and other related code) more simple/readable/user-friendly, this PR replaces existing codes like the followings by using `diamond` operator. ``` - final ArrayList<Product2<Object, Object>> dataToWrite = - new ArrayList<Product2<Object, Object>>(); + final ArrayList<Product2<Object, Object>> dataToWrite = new ArrayList<>(); ``` Java 7 or higher supports **diamond** operator which replaces the type arguments required to invoke the constructor of a generic class with an empty set of type parameters (<>). Currently, Spark Java code use mixed usage of this. ## How was this patch tested? Manual. Pass the existing tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11541 from dongjoon-hyun/SPARK-13702.
* [SPARK-13692][CORE][SQL] Fix trivial Coverity/Checkstyle defectsDongjoon Hyun2016-03-094-4/+5
| | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This issue fixes the following potential bugs and Java coding style detected by Coverity and Checkstyle. - Implement both null and type checking in equals functions. - Fix wrong type casting logic in SimpleJavaBean2.equals. - Add `implement Cloneable` to `UTF8String` and `SortedIterator`. - Remove dereferencing before null check in `AbstractBytesToBytesMapSuite`. - Fix coding style: Add '{}' to single `for` statement in mllib examples. - Remove unused imports in `ColumnarBatch` and `JavaKinesisStreamSuite`. - Remove unused fields in `ChunkFetchIntegrationSuite`. - Add `stop()` to prevent resource leak. Please note that the last two checkstyle errors exist on newly added commits after [SPARK-13583](https://issues.apache.org/jira/browse/SPARK-13583). ## How was this patch tested? manual via `./dev/lint-java` and Coverity site. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11530 from dongjoon-hyun/SPARK-13692.
* [SPARK-529][CORE][YARN] Add type-safe config keys to SparkConf.Marcelo Vanzin2016-03-071-13/+12
| | | | | | | | | | | | | | | | This is, in a way, the basics to enable SPARK-529 (which was closed as won't fix but I think is still valuable). In fact, Spark SQL created something for that, and this change basically factors out that code and inserts it into SparkConf, with some extra bells and whistles. To showcase the usage of this pattern, I modified the YARN backend to use the new config keys (defined in the new `config` package object under `o.a.s.deploy.yarn`). Most of the changes are mechanic, although logic had to be slightly modified in a handful of places. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #10205 from vanzin/conf-opts.
* [SPARK-13652][CORE] Copy ByteBuffer in sendRpcSync as it will be recycledShixiong Zhu2016-03-032-2/+11
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? `sendRpcSync` should copy the response content because the underlying buffer will be recycled and reused. ## How was this patch tested? Jenkins unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #11499 from zsxwing/SPARK-13652.
* [SPARK-13583][CORE][STREAMING] Remove unused imports and add checkstyle ruleDongjoon Hyun2016-03-0312-17/+0
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? After SPARK-6990, `dev/lint-java` keeps Java code healthy and helps PR review by saving much time. This issue aims remove unused imports from Java/Scala code and add `UnusedImports` checkstyle rule to help developers. ## How was this patch tested? ``` ./dev/lint-java ./build/sbt compile ``` Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11438 from dongjoon-hyun/SPARK-13583.
* [SPARK-13423][WIP][CORE][SQL][STREAMING] Static analysis fixes for 2.xSean Owen2016-03-039-17/+26
| | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Make some cross-cutting code improvements according to static analysis. These are individually up for discussion since they exist in separate commits that can be reverted. The changes are broadly: - Inner class should be static - Mismatched hashCode/equals - Overflow in compareTo - Unchecked warnings - Misuse of assert, vs junit.assert - get(a) + getOrElse(b) -> getOrElse(a,b) - Array/String .size -> .length (occasionally, -> .isEmpty / .nonEmpty) to avoid implicit conversions - Dead code - tailrec - exists(_ == ) -> contains find + nonEmpty -> exists filter + size -> count - reduce(_+_) -> sum map + flatten -> map The most controversial may be .size -> .length simply because of its size. It is intended to avoid implicits that might be expensive in some places. ## How was the this patch tested? Existing Jenkins unit tests. Author: Sean Owen <sowen@cloudera.com> Closes #11292 from srowen/SPARK-13423.
* [SPARK-13548][BUILD] Move tags and unsafe modules into commonReynold Xin2016-03-0126-0/+3771
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch moves tags and unsafe modules into common directory to remove 2 top level non-user-facing directories. ## How was this patch tested? Jenkins should suffice. Author: Reynold Xin <rxin@databricks.com> Closes #11426 from rxin/SPARK-13548.
* [SPARK-13529][BUILD] Move network/* modules into common/network-*Reynold Xin2016-02-28110-0/+13702
| | | | | | | | | | | | ## What changes were proposed in this pull request? As the title says, this moves the three modules currently in network/ into common/network-*. This removes one top level, non-user-facing folder. ## How was this patch tested? Compilation and existing tests. We should run both SBT and Maven. Author: Reynold Xin <rxin@databricks.com> Closes #11409 from rxin/SPARK-13529.
* [MINOR][SQL] Fix modifier order.Dongjoon Hyun2016-02-261-1/+1
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes the order of modifier from `abstract public` into `public abstract`. Currently, when we run `./dev/lint-java`, it shows the error. ``` Checkstyle checks failed at following occurrences: [ERROR] src/main/java/org/apache/spark/util/sketch/CountMinSketch.java:[53,10] (modifier) ModifierOrder: 'public' modifier out of order with the JLS suggestions. ``` ## How was this patch tested? ``` $ ./dev/lint-java Checkstyle checks passed. ``` Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11390 from dongjoon-hyun/fix_modifier_order.
* [MINOR][DOCS] Fix all typos in markdown files of `doc` and similar patterns ↵Dongjoon Hyun2016-02-221-1/+1
| | | | | | | | | | | | | | | | | in other comments ## What changes were proposed in this pull request? This PR tries to fix all typos in all markdown files under `docs` module, and fixes similar typos in other comments, too. ## How was the this patch tested? manual tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11300 from dongjoon-hyun/minor_fix_typos.
* [SPARK-6363][BUILD] Make Scala 2.11 the default Scala versionJosh Rosen2016-01-301-2/+2
| | | | | | | | | | | | This patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the "Building Spark" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds). The Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance). After this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break. Author: Josh Rosen <joshrosen@databricks.com> Closes #10608 from JoshRosen/SPARK-6363.
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