- Nov 04, 2014
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Michael Armbrust authored
Author: Michael Armbrust <michael@databricks.com> Closes #3097 from marmbrus/asString and squashes the following commits: 6430520 [Michael Armbrust] Add String option for DSL AS
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Aaron Davidson authored
Also lays the groundwork for supporting it inside the external shuffle service. Author: Aaron Davidson <aaron@databricks.com> Closes #3087 from aarondav/sasl and squashes the following commits: 3481718 [Aaron Davidson] Delete rogue println 44f8410 [Aaron Davidson] Delete documentation - muahaha! eb9f065 [Aaron Davidson] Improve documentation and add end-to-end test at Spark-level a6b95f1 [Aaron Davidson] Address comments 785bbde [Aaron Davidson] Cleanup 79973cb [Aaron Davidson] Remove unused file 151b3c5 [Aaron Davidson] Add docs, timeout config, better failure handling f6177d7 [Aaron Davidson] Cleanup SASL state upon connection termination 7b42adb [Aaron Davidson] Add unit tests 8191bcb [Aaron Davidson] [SPARK-2938] Support SASL authentication in NettyBlockTransferService
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Niklas Wilcke authored
Author: Niklas Wilcke <1wilcke@informatik.uni-hamburg.de> Closes #2907 from numbnut/master and squashes the following commits: 7f7c767 [Niklas Wilcke] [Spark-4060] [MLlib] exposing special rdd functions to the public, #2907
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Dariusz Kobylarz authored
the filter tests Double objects by references whereas it should test their values Author: Dariusz Kobylarz <darek.kobylarz@gmail.com> Closes #3081 from dkobylarz/master and squashes the following commits: 5d43a39 [Dariusz Kobylarz] naive bayes example update a304b93 [Dariusz Kobylarz] fixed MLlib Naive-Bayes java example bug
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Davies Liu authored
This PR simplify serializer, always use batched serializer (AutoBatchedSerializer as default), even batch size is 1. Author: Davies Liu <davies@databricks.com> This patch had conflicts when merged, resolved by Committer: Josh Rosen <joshrosen@databricks.com> Closes #2920 from davies/fix_autobatch and squashes the following commits: e544ef9 [Davies Liu] revert unrelated change 6880b14 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 1d557fc [Davies Liu] fix tests 8180907 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 76abdce [Davies Liu] clean up 53fa60b [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch d7ac751 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 2cc2497 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch b4292ce [Davies Liu] fix bug in master d79744c [Davies Liu] recover hive tests be37ece [Davies Liu] refactor eb3938d [Davies Liu] refactor serializer in scala 8d77ef2 [Davies Liu] simplify serializer, use AutoBatchedSerializer by default.
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zsxwing authored
Author: zsxwing <zsxwing@gmail.com> Closes #3085 from zsxwing/SPARK-4166-back-comp and squashes the following commits: 89329f4 [zsxwing] Add a backward compatibility test for ExecutorLostFailure
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zsxwing authored
/cc aarondav Author: zsxwing <zsxwing@gmail.com> Closes #3086 from zsxwing/SPARK-4163-back-comp and squashes the following commits: 21cb2a8 [zsxwing] Add a backward compatibility test for FetchFailed
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Xiangrui Meng authored
Register MLlib's Vector as a SQL user-defined type (UDT) in both Scala and Python. With this PR, we can easily map a RDD[LabeledPoint] to a SchemaRDD, and then select columns or save to a Parquet file. Examples in Scala/Python are attached. The Scala code was copied from jkbradley. ~~This PR contains the changes from #3068 . I will rebase after #3068 is merged.~~ marmbrus jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #3070 from mengxr/SPARK-3573 and squashes the following commits: 3a0b6e5 [Xiangrui Meng] organize imports 236f0a0 [Xiangrui Meng] register vector as UDT and provide dataset examples
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- Nov 03, 2014
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Xiangrui Meng authored
Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python. marmbrus jkbradley davies Author: Xiangrui Meng <meng@databricks.com> Closes #3068 from mengxr/SPARK-4192-sql and squashes the following commits: acff637 [Xiangrui Meng] merge master dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well 2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion 7c4a6a9 [Xiangrui Meng] address comments 75223db [Xiangrui Meng] minor update f740379 [Xiangrui Meng] remove UDT from default imports e98d9d0 [Xiangrui Meng] fix py style 4e84fce [Xiangrui Meng] remove local hive tests and add more tests 39f19e0 [Xiangrui Meng] add tests b7f666d [Xiangrui Meng] add Python UDT
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Xiangrui Meng authored
Saw Jenkins test failures due to random seeds. jkbradley manishamde Author: Xiangrui Meng <meng@databricks.com> Closes #3084 from mengxr/fix-baggedpoint-suite and squashes the following commits: f735a43 [Xiangrui Meng] fix seed in BaggedPointSuite
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Josh Rosen authored
This patch allows executor thread dumps to be collected on-demand and viewed in the Spark web UI. The thread dumps are collected using Thread.getAllStackTraces(). To allow remote thread dumps to be triggered from the web UI, I added a new `ExecutorActor` that runs inside of the Executor actor system and responds to RPCs from the driver. The driver's mechanism for obtaining a reference to this actor is a little bit hacky: it uses the block manager master actor to determine the host/port of the executor actor systems in order to construct ActorRefs to ExecutorActor. Unfortunately, I couldn't find a much cleaner way to do this without a big refactoring of the executor -> driver communication. Screenshots:    Author: Josh Rosen <joshrosen@databricks.com> Closes #2944 from JoshRosen/jstack-in-web-ui and squashes the following commits: 3c21a5d [Josh Rosen] Address review comments: 880f7f7 [Josh Rosen] Merge remote-tracking branch 'origin/master' into jstack-in-web-ui f719266 [Josh Rosen] Merge remote-tracking branch 'origin/master' into jstack-in-web-ui 19707b0 [Josh Rosen] Add one comment. 127a130 [Josh Rosen] Update to use SparkContext.DRIVER_IDENTIFIER b8e69aa [Josh Rosen] Merge remote-tracking branch 'origin/master' into jstack-in-web-ui 3dfc2d4 [Josh Rosen] Add missing file. bc1e675 [Josh Rosen] Undo some leftover changes from the earlier approach. f4ac1c1 [Josh Rosen] Switch to on-demand collection of thread dumps dfec08b [Josh Rosen] Add option to disable thread dumps in UI. 4c87d7f [Josh Rosen] Use separate RPC for sending thread dumps. 2b8bdf3 [Josh Rosen] Enable thread dumps from the driver when running in non-local mode. cc3e6b3 [Josh Rosen] Fix test code in DAGSchedulerSuite. 87b8b65 [Josh Rosen] Add new listener event for thread dumps. 8c10216 [Josh Rosen] Add missing file. 0f198ac [Josh Rosen] [SPARK-611] Display executor thread dumps in web UI
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Zhang, Liye authored
The number of completed stages and failed stages showed on webUI will always be less than 1000. This is really misleading when there are already thousands of stages completed or failed. The number should be correct even when only partial stages listed on the webUI (stage info will be removed if the number is too large). Author: Zhang, Liye <liye.zhang@intel.com> Closes #3035 from liyezhang556520/webStageNum and squashes the following commits: d9e29fb [Zhang, Liye] add detailed comments for variables 4ea8fd1 [Zhang, Liye] change variable name accroding to comments f4c404d [Zhang, Liye] [SPARK-4168][WebUI] web statges number should show correctly when stages are more than 1000
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Michael Armbrust authored
Author: Michael Armbrust <michael@databricks.com> Closes #3077 from marmbrus/udfsWithUdts and squashes the following commits: 34b5f27 [Michael Armbrust] style 504adef [Michael Armbrust] Convert arguments to Scala UDFs
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Sandy Ryza authored
...ntiation Author: Sandy Ryza <sandy@cloudera.com> Closes #3045 from sryza/sandy-spark-4178 and squashes the following commits: 8d2e70e [Sandy Ryza] Kostas's review feedback e5b27c0 [Sandy Ryza] SPARK-4178. Hadoop input metrics ignore bytes read in RecordReader instantiation
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Michael Armbrust authored
- Turns on compression for in-memory cached data by default - Changes the default parquet compression format back to gzip (we have seen more OOMs with production workloads due to the way Snappy allocates memory) - Ups the batch size to 10,000 rows - Increases the broadcast threshold to 10mb. - Uses our parquet implementation instead of the hive one by default. - Cache parquet metadata by default. Author: Michael Armbrust <michael@databricks.com> Closes #3064 from marmbrus/fasterDefaults and squashes the following commits: 97ee9f8 [Michael Armbrust] parquet codec docs e641694 [Michael Armbrust] Remote also a12866a [Michael Armbrust] Cache metadata. 2d73acc [Michael Armbrust] Update docs defaults. d63d2d5 [Michael Armbrust] document parquet option da373f9 [Michael Armbrust] More aggressive defaults
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Cheng Hao authored
CREATE TABLE t1 (a String); CREATE TABLE t1 AS SELECT key FROM src; – throw exception CREATE TABLE if not exists t1 AS SELECT key FROM src; – expect do nothing, currently it will overwrite the t1, which is incorrect. Author: Cheng Hao <hao.cheng@intel.com> Closes #3013 from chenghao-intel/ctas_unittest and squashes the following commits: 194113e [Cheng Hao] fix bug in CTAS when table already existed
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Cheng Lian authored
This feature is based on an offline discussion with mengxr, hopefully can be useful for the new MLlib pipeline API. For the following test snippet ```scala case class KeyValue(key: Int, value: String) val testData = sc.parallelize(1 to 10).map(i => KeyValue(i, i.toString)).toSchemaRDD def foo(a: Int, b: String) => a.toString + b ``` the newly introduced DSL enables the following syntax ```scala import org.apache.spark.sql.catalyst.dsl._ testData.select(Star(None), foo.call('key, 'value) as 'result) ``` which is equivalent to ```scala testData.registerTempTable("testData") sqlContext.registerFunction("foo", foo) sql("SELECT *, foo(key, value) AS result FROM testData") ``` Author: Cheng Lian <lian@databricks.com> Closes #3067 from liancheng/udf-dsl and squashes the following commits: f132818 [Cheng Lian] Adds DSL support for Scala UDF -
Davies Liu authored
This patch will try to infer schema for RDD which has empty value (None, [], {}) in the first row. It will try first 100 rows and merge the types into schema, also merge fields of StructType together. If there is still NullType in schema, then it will show an warning, tell user to try with sampling. If sampling is presented, it will infer schema from all the rows after sampling. Also, add samplingRatio for jsonFile() and jsonRDD() Author: Davies Liu <davies.liu@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #2716 from davies/infer and squashes the following commits: e678f6d [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 34b5c63 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 567dc60 [Davies Liu] update docs 9767b27 [Davies Liu] Merge branch 'master' into infer e48d7fb [Davies Liu] fix tests 29e94d5 [Davies Liu] let NullType inherit from PrimitiveType ee5d524 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 540d1d5 [Davies Liu] merge fields for StructType f93fd84 [Davies Liu] add more tests 3603e00 [Davies Liu] take more rows to infer schema, or infer the schema by sampling the RDD -
ravipesala authored
Queries which has 'not like' is not working spark sql. sql("SELECT * FROM records where value not like 'val%'") same query works in Spark HiveQL Author: ravipesala <ravindra.pesala@huawei.com> Closes #3075 from ravipesala/SPARK-4207 and squashes the following commits: 35c11e7 [ravipesala] Supported 'not like' syntax in sql -
fi authored
instead of `hive.version=0.13.1`. e.g. mvn -Phive -Phive=0.13.1 Note: `hive.version=0.13.1a` is the default property value. However, when explicitly specifying the `hive-0.13.1` maven profile, the wrong one would be selected. References: PR #2685, which resolved a package incompatibility issue with Hive-0.13.1 by introducing a special version Hive-0.13.1a Author: fi <coderfi@gmail.com> Closes #3072 from coderfi/master and squashes the following commits: 7ca4b1e [fi] Fixes the `hive-0.13.1` maven profile referencing `hive.version=0.13.1` instead of the Spark compatible `hive.version=0.13.1a` Note: `hive.version=0.13.1a` is the default version. However, when explicitly specifying the `hive-0.13.1` maven profile, the wrong one would be selected. e.g. mvn -Phive -Phive=0.13.1 See PR #2685
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Xiangrui Meng authored
The current way of seed distribution makes the random sequences from partition i and i+1 offset by 1. ~~~ In [14]: import random In [15]: r1 = random.Random(10) In [16]: r1.randint(0, 1) Out[16]: 1 In [17]: r1.random() Out[17]: 0.4288890546751146 In [18]: r1.random() Out[18]: 0.5780913011344704 In [19]: r2 = random.Random(10) In [20]: r2.randint(0, 1) Out[20]: 1 In [21]: r2.randint(0, 1) Out[21]: 0 In [22]: r2.random() Out[22]: 0.5780913011344704 ~~~ Note: The new tests are not for this bug fix. Author: Xiangrui Meng <meng@databricks.com> Closes #3010 from mengxr/SPARK-4148 and squashes the following commits: 869ae4b [Xiangrui Meng] move tests tests.py c1bacd9 [Xiangrui Meng] fix seed distribution and add some tests for rdd.sample
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Nicholas Chammas authored
We reference a specific branch in two places. This patch makes it one place. Author: Nicholas Chammas <nicholas.chammas@gmail.com> Closes #3008 from nchammas/mesos-spark-ec2-branch and squashes the following commits: 10a6089 [Nicholas Chammas] factor out mess spark-ec2 branch
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zsxwing authored
This is a PR to send the fetch failure message back to Web UI. Before:   After (Please ignore the meaning of exception, I threw it in the code directly because it's hard to simulate a fetch failure):   Author: zsxwing <zsxwing@gmail.com> Closes #3032 from zsxwing/SPARK-4163 and squashes the following commits: f7e1faf [zsxwing] Discard changes for FetchFailedException and minor modification 4e946f7 [zsxwing] Add e as the cause of SparkException 316767d [zsxwing] Add private[storage] to FetchResult d51b0b6 [zsxwing] Set e as the cause of FetchFailedException b88c919 [zsxwing] Use 'private[storage]' for case classes instead of 'sealed' 62103fd [zsxwing] Update as per review 0c07d1f [zsxwing] Backward-compatible support a3bca65 [zsxwing] Send the fetch failure message back to Web UI
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wangfei authored
Author: wangfei <wangfei1@huawei.com> Closes #3042 from scwf/patch-9 and squashes the following commits: 3784ed1 [wangfei] remove 'TODO' 1891553 [wangfei] update build doc since JDBC/CLI support hive 13
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- Nov 02, 2014
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Reynold Xin authored
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Aaron Davidson authored
Note that we're turning this on for at least the first part of the QA period as a trial. We want to enable this (and deprecate the NioBlockTransferService) as soon as possible in the hopes that NettyBlockTransferService will be more stable and easier to maintain. We will turn it off if we run into major issues. Author: Aaron Davidson <aaron@databricks.com> Closes #3049 from aarondav/enable-netty and squashes the following commits: bb981cc [Aaron Davidson] [SPARK-4183] Enable NettyBlockTransferService by default
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Joseph K. Bradley authored
This PR adds User-Defined Types (UDTs) to SQL. It is a precursor to using SchemaRDD as a Dataset for the new MLlib API. Currently, the UDT API is private since there is incomplete support (e.g., no Java or Python support yet). Author: Joseph K. Bradley <joseph@databricks.com> Author: Michael Armbrust <michael@databricks.com> Author: Xiangrui Meng <meng@databricks.com> Closes #3063 from marmbrus/udts and squashes the following commits: 7ccfc0d [Michael Armbrust] remove println 46a3aee [Michael Armbrust] Slightly easier to read test output. 6cc434d [Michael Armbrust] Recursively convert rows. e369b91 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udts 15c10a6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into sql-udt2 f3c72fe [Joseph K. Bradley] Fixing merge e13cd8a [Joseph K. Bradley] Removed Vector UDTs 5817b2b [Joseph K. Bradley] style edits 30ce5b2 [Joseph K. Bradley] updates based on code review d063380 [Joseph K. Bradley] Cleaned up Java UDT Suite, and added warning about element ordering when creating schema from Java Bean a571bb6 [Joseph K. Bradley] Removed old UDT code (registry and Java UDTs). Cleaned up other code. Extended JavaUserDefinedTypeSuite 6fddc1c [Joseph K. Bradley] Made MyLabeledPoint into a Java Bean 20630bc [Joseph K. Bradley] fixed scalastyle fa86b20 [Joseph K. Bradley] Removed Java UserDefinedType, and made UDTs private[spark] for now 8de957c [Joseph K. Bradley] Modified UserDefinedType to store Java class of user type so that registerUDT takes only the udt argument. 8b242ea [Joseph K. Bradley] Fixed merge error after last merge. Note: Last merge commit also removed SQL UDT examples from mllib. 7f29656 [Joseph K. Bradley] Moved udt case to top of all matches. Small cleanups b028675 [Xiangrui Meng] allow any type in UDT 4500d8a [Xiangrui Meng] update example code 87264a5 [Xiangrui Meng] remove debug code 3143ac3 [Xiangrui Meng] remove unnecessary changes cfbc321 [Xiangrui Meng] support UDT in parquet db16139 [Joseph K. Bradley] Added more doc for UserDefinedType. Removed unused code in Suite 759af7a [Joseph K. Bradley] Added more doc to UserDefineType 63626a4 [Joseph K. Bradley] Updated ScalaReflectionsSuite per @marmbrus suggestions 51e5282 [Joseph K. Bradley] fixed 1 test f025035 [Joseph K. Bradley] Cleanups before PR. Added new tests 85872f6 [Michael Armbrust] Allow schema calculation to be lazy, but ensure its available on executors. dff99d6 [Joseph K. Bradley] Added UDTs for Vectors in MLlib, plus DatasetExample using the UDTs cd60cb4 [Joseph K. Bradley] Trying to get other SQL tests to run 34a5831 [Joseph K. Bradley] Added MLlib dependency on SQL. e1f7b9c [Joseph K. Bradley] blah 2f40c02 [Joseph K. Bradley] renamed UDT types 3579035 [Joseph K. Bradley] udt annotation now working b226b9e [Joseph K. Bradley] Changing UDT to annotation fea04af [Joseph K. Bradley] more cleanups 964b32e [Joseph K. Bradley] some cleanups 893ee4c [Joseph K. Bradley] udt finallly working 50f9726 [Joseph K. Bradley] udts 04303c9 [Joseph K. Bradley] udts 39f8707 [Joseph K. Bradley] removed old udt suite 273ac96 [Joseph K. Bradley] basic UDT is working, but deserialization has yet to be done 8bebf24 [Joseph K. Bradley] commented out convertRowToScala for debugging 53de70f [Joseph K. Bradley] more udts... 982c035 [Joseph K. Bradley] still working on UDTs 19b2f60 [Joseph K. Bradley] still working on UDTs 0eaeb81 [Joseph K. Bradley] Still working on UDTs 105c5a3 [Joseph K. Bradley] Adding UserDefinedType to SQL, not done yet.
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Aaron Davidson authored
A leak of event loops may be causing test failures. Author: Aaron Davidson <aaron@databricks.com> Closes #3053 from aarondav/leak and squashes the following commits: e676d18 [Aaron Davidson] Typo! 8f96475 [Aaron Davidson] Keep original ssc semantics 7e49f10 [Aaron Davidson] A leak of event loops may be causing test failures.
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Cheng Lian authored
This PR adds an API for unregistering temporary tables. If a temporary table has been cached before, it's unpersisted as well. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #3039 from liancheng/unregister-temp-table and squashes the following commits: 54ae99f [Cheng Lian] Fixes Scala styling issue 1948c14 [Cheng Lian] Removes the unpersist argument aca41d3 [Cheng Lian] Ensures thread safety 7d4fb2b [Cheng Lian] Adds unregisterTempTable API
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Yin Huai authored
JIRA: https://issues.apache.org/jira/browse/SPARK-4185. This PR also has the fix of #3052. Author: Yin Huai <huai@cse.ohio-state.edu> Closes #3056 from yhuai/SPARK-4185 and squashes the following commits: ed3a5a8 [Yin Huai] Correctly handle type conflicts between structs and primitive types in an array.
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wangfei authored
Move wrapperFor in InsertIntoHiveTable to HiveInspectors to reuse them, this method can be reused when writing date with ObjectInspector(such as orc support) Author: wangfei <wangfei1@huawei.com> Author: scwf <wangfei1@huawei.com> Closes #3057 from scwf/reuse-wraperfor and squashes the following commits: 7ccf932 [scwf] fix conflicts d44f4da [wangfei] fix imports 9bf1b50 [wangfei] revert no related change 9a5276a [wangfei] move wrapfor to hiveinspector to reuse them
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Cheng Lian authored
This PR overrides the `GetInfo` Hive Thrift API to provide correct version information. Another property `spark.sql.hive.version` is added to reveal the underlying Hive version. These are generally useful for Spark SQL ODBC driver providers. The Spark version information is extracted from the jar manifest. Also took the chance to remove the `SET -v` hack, which was a workaround for Simba ODBC driver connectivity. TODO - [x] Find a general way to figure out Hive (or even any dependency) version. This [blog post](http://blog.soebes.de/blog/2014/01/02/version-information-into-your-appas-with-maven/) suggests several methods to inspect application version. In the case of Spark, this can be tricky because the chosen method: 1. must applies to both Maven build and SBT build For Maven builds, we can retrieve the version information from the META-INF/maven directory within the assembly jar. But this doesn't work for SBT builds. 2. must not rely on the original jars of dependencies to extract specific dependency version, because Spark uses assembly jar. This implies we can't read Hive version from Hive jar files since standard Spark distribution doesn't include them. 3. should play well with `SPARK_PREPEND_CLASSES` to ease local testing during development. `SPARK_PREPEND_CLASSES` prevents classes to be loaded from the assembly jar, thus we can't locate the jar file and read its manifest. Given these, maybe the only reliable method is to generate a source file containing version information at build time. pwendell Do you have any suggestions from the perspective of the build process? **Update** Hive version is now retrieved from the newly introduced `HiveShim` object. Author: Cheng Lian <lian.cs.zju@gmail.com> Author: Cheng Lian <lian@databricks.com> Closes #2843 from liancheng/get-info and squashes the following commits: a873d0f [Cheng Lian] Updates test case 53f43cd [Cheng Lian] Retrieves underlying Hive verson via HiveShim 1d282b8 [Cheng Lian] Removes the Simba ODBC "SET -v" hack f857fce [Cheng Lian] Overrides Hive GetInfo Thrift API and adds Hive version property
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Cheng Lian authored
`CliSuite` has been flaky for a while, this PR tries to improve this situation by fixing a race condition in `CliSuite`. The `captureOutput` function is used to capture both stdout and stderr output of the forked external process in two background threads and search for expected strings, but wasn't been properly synchronized before. Author: Cheng Lian <lian@databricks.com> Closes #3060 from liancheng/fix-cli-suite and squashes the following commits: a70569c [Cheng Lian] Fixes race condition in CliSuite
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Cheng Lian authored
`NoopColumnStats` was once used for binary, boolean and complex data types. This `ColumnStats` doesn't return properly shaped column statistics and causes caching failure if a table contains columns of the aforementioned types. This PR adds `BooleanColumnStats`, `BinaryColumnStats` and `GenericColumnStats`, used for boolean, binary and all complex data types respectively. In addition, `NoopColumnStats` returns properly shaped column statistics containing null count and row count, but this class is now used for testing purpose only. Author: Cheng Lian <lian@databricks.com> Closes #3059 from liancheng/spark-4182 and squashes the following commits: b398cfd [Cheng Lian] Fixes failed test case fb3ee85 [Cheng Lian] Fixes SPARK-4182
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Michael Armbrust authored
This PR introduces a new set of APIs to Spark SQL to allow other developers to add support for reading data from new sources in `org.apache.spark.sql.sources`. New sources must implement the interface `BaseRelation`, which is responsible for describing the schema of the data. BaseRelations have three `Scan` subclasses, which are responsible for producing an RDD containing row objects. The [various Scan interfaces](https://github.com/marmbrus/spark/blob/foreign/sql/core/src/main/scala/org/apache/spark/sql/sources/package.scala#L50) allow for optimizations such as column pruning and filter push down, when the underlying data source can handle these operations. By implementing a class that inherits from RelationProvider these data sources can be accessed using using pure SQL. I've used the functionality to update the JSON support so it can now be used in this way as follows: ```sql CREATE TEMPORARY TABLE jsonTableSQL USING org.apache.spark.sql.json OPTIONS ( path '/home/michael/data.json' ) ``` Further example usage can be found in the test cases: https://github.com/marmbrus/spark/tree/foreign/sql/core/src/test/scala/org/apache/spark/sql/sources There is also a library that uses this new API to read avro data available here: https://github.com/marmbrus/sql-avro Author: Michael Armbrust <michael@databricks.com> Closes #2475 from marmbrus/foreign and squashes the following commits: 1ed6010 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign ab2c31f [Michael Armbrust] fix test 1d41bb5 [Michael Armbrust] unify argument names 5b47901 [Michael Armbrust] Remove sealed, more filter types fab154a [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign e3e690e [Michael Armbrust] Add hook for extraStrategies a70d602 [Michael Armbrust] Fix style, more tests, FilteredSuite => PrunedFilteredSuite 70da6d9 [Michael Armbrust] Modify API to ease binary compatibility and interop with Java 7d948ae [Michael Armbrust] Fix equality of AttributeReference. 5545491 [Michael Armbrust] Address comments 5031ac3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign 22963ef [Michael Armbrust] package objects compile wierdly... b069146 [Michael Armbrust] traits => abstract classes 34f836a [Michael Armbrust] Make @DeveloperApi 0d74bcf [Michael Armbrust] Add documention on object life cycle 3e06776 [Michael Armbrust] remove line wraps de3b68c [Michael Armbrust] Remove empty file 360cb30 [Michael Armbrust] style and java api 2957875 [Michael Armbrust] add override 0fd3a07 [Michael Armbrust] Draft of data sources API
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wangfei authored
cc marmbrus Author: wangfei <wangfei1@huawei.com> Closes #3055 from scwf/hotfix and squashes the following commits: d881bd7 [wangfei] miss golden files
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zsxwing authored
Now when ExecutorLostFailure happens, it only displays `ExecutorLostFailure (executor lost)`. Adding the executor id will help locate the faulted executor. Author: zsxwing <zsxwing@gmail.com> Closes #3033 from zsxwing/SPARK-4166 and squashes the following commits: ff4664c [zsxwing] Backward-compatible support c5c4cf2 [zsxwing] Display the executor ID in the Web UI when ExecutorLostFailure happens
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Davies Liu authored
Right now, operations like collect() and take() can crash the driver with an OOM if they bring back too many data. This PR will introduce spark.driver.maxResultSize, after setting it, the driver will abort a job if its result is bigger than it. By default, it's 1g (for backward compatibility for most the cases). In local mode, the driver and executor share the same JVM, the default setting can not protect JVM from OOM. cc mateiz Author: Davies Liu <davies@databricks.com> Closes #3003 from davies/collect and squashes the following commits: 248ed5e [Davies Liu] fix compile 272522e [Davies Liu] address comments 2c35773 [Davies Liu] add sizes in message of abort() 5d62303 [Davies Liu] address comments bc3c077 [Davies Liu] Merge branch 'master' of github.com:apache/spark into collect 11f97c5 [Davies Liu] address comments 47b144f [Davies Liu] check the size of result before send and fetch 3d81af2 [Davies Liu] address comments ca8267d [Davies Liu] limit the size of data by collect
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- Nov 01, 2014
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Matei Zaharia authored
- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf) - Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs This is still marked WIP because there are a few TODOs, but I'll remove that tag when done. Author: Matei Zaharia <matei@databricks.com> Closes #2983 from mateiz/decimal-1 and squashes the following commits: 35e6b02 [Matei Zaharia] Fix issues after merge 227f24a [Matei Zaharia] Review comments 31f915e [Matei Zaharia] Implement Davies's suggestions in Python eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet 4dc6bae [Matei Zaharia] Fix decimal support in PySpark d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore 2118c0d [Matei Zaharia] Some test and bug fixes 81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions 7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double
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Sung Chung authored
...sion trees. jkbradley mengxr chouqin Please review this. Author: Sung Chung <schung@alpinenow.com> Closes #2868 from codedeft/SPARK-3161 and squashes the following commits: 5f5a156 [Sung Chung] [SPARK-3161][MLLIB] Adding a node Id caching mechanism for training decision trees.
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