Use SquaredL2Updater in LogisticRegressionWithSGD #2231
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We read the py4j port from the stdout of the `bin/spark-submit` subprocess. If there is interference in stdout (e.g. a random echo in `spark-submit`), we throw an exception with a warning message. We do not, however, distinguish between this case from the case where no stdout is produced at all. I wasted a non-trivial amount of time being baffled by this exception in search of places where I print random whitespace (in vain, of course). A clearer exception message that distinguishes between these cases will prevent similar headaches that I have gone through. Author: Andrew Or <[email protected]> Closes #2067 from andrewor14/python-exception and squashes the following commits: 742f823 [Andrew Or] Further clarify warning messages e96a7a0 [Andrew Or] Distinguish between unexpected output and no output at all
Moved TF-IDF before Word2Vec because the former is more basic. I also added a link for Word2Vec. atalwalkar Author: Xiangrui Meng <[email protected]> Closes #2061 from mengxr/tfidf-doc and squashes the following commits: ca04c70 [Xiangrui Meng] address comments a5ea4b4 [Xiangrui Meng] add tf-idf user guide
atalwalkar srowen Author: Xiangrui Meng <[email protected]> Closes #2064 from mengxr/als-doc and squashes the following commits: b2e20ab [Xiangrui Meng] introduced -> discussed 98abdd7 [Xiangrui Meng] add reference 339bd08 [Xiangrui Meng] add a section about regularization parameter in ALS
Updated DecisionTree documentation, with examples for Java, Python. Added same Java example to code as well. CC: @mengxr @manishamde @atalwalkar Author: Joseph K. Bradley <[email protected]> Closes #2063 from jkbradley/dt-docs and squashes the following commits: 2dd2c19 [Joseph K. Bradley] Last updates based on github review. 9dd1b6b [Joseph K. Bradley] Updated decision tree doc. d802369 [Joseph K. Bradley] Updates based on comments: cache data, corrected doc text. b9bee04 [Joseph K. Bradley] Updated DT examples 57eee9f [Joseph K. Bradley] Created JavaDecisionTree example from example in docs, and corrected doc example as needed. d939a92 [Joseph K. Bradley] Updated DecisionTree documentation. Added Java, Python examples.
Author: XuTingjun <[email protected]> Closes #1614 from XuTingjun/yarn-bug and squashes the following commits: f07096e [XuTingjun] Update ClientArguments.scala
…ume sink Due to maven bug https://jira.codehaus.org/browse/MNG-1378, maven could not resolve spark streaming classes required by the spark-streaming test-jar dependency of external/flume-sink. There is no particular reason that the external/flume-sink has to depend on Spark Streaming at all, so I am eliminating this dependency. Also I have removed the exclusions present in the Flume dependencies, as there is no reason to exclude them (they were excluded in the external/flume module to prevent dependency collisions with Spark). Since Jenkins will test the sbt build and the unit test, I only tested maven compilation locally. Author: Tathagata Das <[email protected]> Closes #2101 from tdas/spark-sink-pom-fix and squashes the following commits: 8f42621 [Tathagata Das] Added Flume sink exclusions back, and added netty to test dependencies 93b559f [Tathagata Das] Removed dependency on spark streaming test from spark flume sink
…g CLI and Thrift JDBC server is absent in proper document - The most important things I mentioned in #1885 is as follows. * People who build Spark is not always programmer. * If a person who build Spark is not a programmer, he/she won't read programmer's guide before building. So, how to build for using CLI and JDBC server is not only in programmer's guide. Author: Kousuke Saruta <[email protected]> Closes #2080 from sarutak/SPARK-2963 and squashes the following commits: ee07c76 [Kousuke Saruta] Modified regression of the description about building for using Thrift JDBC server and CLI ed53329 [Kousuke Saruta] Modified description and notaton of proper noun 07c59fc [Kousuke Saruta] Added a description about how to build to use HiveServer and CLI for SparkSQL to building-with-maven.md 6e6645a [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-2963 c88fa93 [Kousuke Saruta] Added a description about building to use HiveServer and CLI for SparkSQL
In JVM 1.8.0, MaxPermSize is no longer supported.
In spark `stderr` output, there would be a line of
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
Author: Daoyuan Wang <[email protected]>
Closes #2011 from adrian-wang/maxpermsize and squashes the following commits:
ef1d660 [Daoyuan Wang] direct get java version in runtime
37db9c1 [Daoyuan Wang] code refine
3c1d554 [Daoyuan Wang] remove MaxPermSize option for jvm 1.8
Fix a typo in comment. Author: Liang-Chi Hsieh <[email protected]> Closes #2105 from viirya/fix_typo and squashes the following commits: 6596a80 [Liang-Chi Hsieh] fix typo.
Seems we missed `transient` for the `functionRegistry` in `HiveContext`. cc: marmbrus Author: Yin Huai <[email protected]> Closes #2074 from yhuai/makeFunctionRegistryTransient and squashes the following commits: 6534e7d [Yin Huai] Make functionRegistry transient.
…tion improvements Author: Michael Armbrust <[email protected]> Author: Gregory Owen <[email protected]> Closes #1935 from marmbrus/countDistinctPartial and squashes the following commits: 5c7848d [Michael Armbrust] turn off caching in the constructor 8074a80 [Michael Armbrust] fix tests 32d216f [Michael Armbrust] reynolds comments c122cca [Michael Armbrust] Address comments, add tests b2e8ef3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial fae38f4 [Michael Armbrust] Fix style fdca896 [Michael Armbrust] cleanup 93d0f64 [Michael Armbrust] metastore concurrency fix. db44a30 [Michael Armbrust] JIT hax. 3868f6c [Michael Armbrust] Merge pull request #9 from GregOwen/countDistinctPartial c9e67de [Gregory Owen] Made SpecificRow and types serializable by Kryo 2b46c4b [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial 8ff6402 [Michael Armbrust] Add specific row. 58d15f1 [Michael Armbrust] disable codegen logging 87d101d [Michael Armbrust] Fix isNullAt bug abee26d [Michael Armbrust] WIP 27984d0 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial 57ae3b1 [Michael Armbrust] Fix order dependent test b3d0f64 [Michael Armbrust] Add golden files. c1f7114 [Michael Armbrust] Improve tests / fix serialization. f31b8ad [Michael Armbrust] more fixes 38c7449 [Michael Armbrust] comments and style 9153652 [Michael Armbrust] better toString d494598 [Michael Armbrust] Fix tests now that the planner is better 41fbd1d [Michael Armbrust] Never try and create an empty hash set. 050bb97 [Michael Armbrust] Skip no-arg constructors for kryo, bd08239 [Michael Armbrust] WIP 213ada8 [Michael Armbrust] First draft of partially aggregated and code generated count distinct / max
… shuffle fix. Follow-up to #2066 Author: Michael Armbrust <[email protected]> Closes #2072 from marmbrus/sortShuffle and squashes the following commits: 2ff8114 [Michael Armbrust] Fix bug
RDD.max(key=None)
param key: A function used to generate key for comparing
>>> rdd = sc.parallelize([1.0, 5.0, 43.0, 10.0])
>>> rdd.max()
43.0
>>> rdd.max(key=str)
5.0
RDD.min(key=None)
Find the minimum item in this RDD.
param key: A function used to generate key for comparing
>>> rdd = sc.parallelize([2.0, 5.0, 43.0, 10.0])
>>> rdd.min()
2.0
>>> rdd.min(key=str)
10.0
RDD.top(num, key=None)
Get the top N elements from a RDD.
Note: It returns the list sorted in descending order.
>>> sc.parallelize([10, 4, 2, 12, 3]).top(1)
[12]
>>> sc.parallelize([2, 3, 4, 5, 6], 2).top(2)
[6, 5]
>>> sc.parallelize([10, 4, 2, 12, 3]).top(3, key=str)
[4, 3, 2]
Author: Davies Liu <[email protected]>
Closes #2094 from davies/cmp and squashes the following commits:
ccbaf25 [Davies Liu] add `key` to top()
ad7e374 [Davies Liu] fix tests
2f63512 [Davies Liu] change `comp` to `key` in min/max
dd91e08 [Davies Liu] add `comp` argument for RDD.max() and RDD.min()
RDD.countApprox(self, timeout, confidence=0.95)
:: Experimental ::
Approximate version of count() that returns a potentially incomplete
result within a timeout, even if not all tasks have finished.
>>> rdd = sc.parallelize(range(1000), 10)
>>> rdd.countApprox(1000, 1.0)
1000
RDD.sumApprox(self, timeout, confidence=0.95)
Approximate operation to return the sum within a timeout
or meet the confidence.
>>> rdd = sc.parallelize(range(1000), 10)
>>> r = sum(xrange(1000))
>>> (rdd.sumApprox(1000) - r) / r < 0.05
RDD.meanApprox(self, timeout, confidence=0.95)
:: Experimental ::
Approximate operation to return the mean within a timeout
or meet the confidence.
>>> rdd = sc.parallelize(range(1000), 10)
>>> r = sum(xrange(1000)) / 1000.0
>>> (rdd.meanApprox(1000) - r) / r < 0.05
True
Author: Davies Liu <[email protected]>
Closes #2095 from davies/approx and squashes the following commits:
e8c252b [Davies Liu] add approx API for RDD
Just clean unused code which have been moved into ExternalSorter. Author: Raymond Liu <[email protected]> Closes #1882 from colorant/sortShuffleWriter and squashes the following commits: e6337be [Raymond Liu] Clean unused code in SortShuffleWriter
…have 4 space indentation. Author: Kousuke Saruta <[email protected]> Closes #2104 from sarutak/SPARK-3192 and squashes the following commits: db78419 [Kousuke Saruta] Modified indentation of spark-shell
Documentation for newly added feature transformations: 1. TF-IDF 2. StandardScaler 3. Normalizer Author: DB Tsai <[email protected]> Closes #2068 from dbtsai/transformer-documentation and squashes the following commits: 109f324 [DB Tsai] address feedback
Update the documentation to reflect the fact we can handle roughly square matrices. Author: Reza Zadeh <[email protected]> Closes #2070 from rezazadeh/svddocs and squashes the following commits: 826b8fe [Reza Zadeh] left singular vectors 3f34fc6 [Reza Zadeh] PCA is still TS 7ffa2aa [Reza Zadeh] better title aeaf39d [Reza Zadeh] More docs 788ed13 [Reza Zadeh] add computational cost explanation 6429c59 [Reza Zadeh] Add link to rowmatrix docs 1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square
RDD.zipWithIndex()
Zips this RDD with its element indices.
The ordering is first based on the partition index and then the
ordering of items within each partition. So the first item in
the first partition gets index 0, and the last item in the last
partition receives the largest index.
This method needs to trigger a spark job when this RDD contains
more than one partitions.
>>> sc.parallelize(range(4), 2).zipWithIndex().collect()
[(0, 0), (1, 1), (2, 2), (3, 3)]
RDD.zipWithUniqueId()
Zips this RDD with generated unique Long ids.
Items in the kth partition will get ids k, n+k, 2*n+k, ..., where
n is the number of partitions. So there may exist gaps, but this
method won't trigger a spark job, which is different from
L{zipWithIndex}
>>> sc.parallelize(range(4), 2).zipWithUniqueId().collect()
[(0, 0), (2, 1), (1, 2), (3, 3)]
Author: Davies Liu <[email protected]>
Closes #2092 from davies/zipWith and squashes the following commits:
cebe5bf [Davies Liu] improve test cases, reverse the order of index
0d2a128 [Davies Liu] add zipWithIndex() and zipWithUniqueId()
to re-construct k-means models freeman-lab Author: Xiangrui Meng <[email protected]> Closes #2112 from mengxr/public-constructors and squashes the following commits: 18d53a9 [Xiangrui Meng] make KMeans constructor public
…ml files (EDIT) Since the scalatest issue was since resolved, this is now about a few small problems in the Flume Sink `pom.xml` - `scalatest` is not declared as a test-scope dependency - Its Avro version doesn't match the rest of the build - Its Flume version is not synced with the other Flume module - The other Flume module declares its dependency on Flume Sink slightly incorrectly, hard-coding the Scala 2.10 version - It depends on Scala Lang directly, which it shouldn't Author: Sean Owen <[email protected]> Closes #1726 from srowen/SPARK-2798 and squashes the following commits: a46e2c6 [Sean Owen] scalatest to test scope, harmonize Avro and Flume versions, remove direct Scala dependency, fix '2.10' in Flume dependency
Adds the --authorized-address and --additional-security-group options as explained in the issue. Author: Allan Douglas R. de Oliveira <[email protected]> Closes #2088 from douglaz/configurable_sg and squashes the following commits: e3e48ca [Allan Douglas R. de Oliveira] Adds the option to specify the address authorized to access the SG and another option to provide an additional existing SG
rxin Author: Xiangrui Meng <[email protected]> Closes #2120 from mengxr/sendMessageReliably and squashes the following commits: b14400c [Xiangrui Meng] fix error message in sendMessageReliably
It should be `spark-env.sh` rather than `spark.env.sh`. Author: Cheng Lian <[email protected]> Closes #2119 from liancheng/fix-mesos-doc and squashes the following commits: f360548 [Cheng Lian] Fixed a typo in docs/running-on-mesos.md
…foldable. Author: Takuya UESHIN <[email protected]> Closes #2116 from ueshin/issues/SPARK-3204 and squashes the following commits: 7d9b107 [Takuya UESHIN] Make MaxOf foldable if both left and right are foldable.
Removed most hard coded timeout, timing assumptions and all `Thread.sleep`. Simplified IPC and synchronization with `scala.sys.process` and future/promise so that the test suites can run more robustly and faster. Author: Cheng Lian <[email protected]> Closes #1856 from liancheng/thriftserver-tests and squashes the following commits: 2d914ca [Cheng Lian] Minor refactoring 0e12e71 [Cheng Lian] Cleaned up test output 0ee921d [Cheng Lian] Refactored Thrift server and CLI suites
Provide `extended` keyword support for `explain` command in SQL. e.g.
```
explain extended select key as a1, value as a2 from src where key=1;
== Parsed Logical Plan ==
Project ['key AS a1#3,'value AS a2#4]
Filter ('key = 1)
UnresolvedRelation None, src, None
== Analyzed Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = CAST(1, DoubleType))
MetastoreRelation default, src, None
== Optimized Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = 1.0)
MetastoreRelation default, src, None
== Physical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
Filter (CAST(key#8, DoubleType) = 1.0)
HiveTableScan [key#8,value#9], (MetastoreRelation default, src, None), None
Code Generation: false
== RDD ==
(2) MappedRDD[14] at map at HiveContext.scala:350
MapPartitionsRDD[13] at mapPartitions at basicOperators.scala:42
MapPartitionsRDD[12] at mapPartitions at basicOperators.scala:57
MapPartitionsRDD[11] at mapPartitions at TableReader.scala:112
MappedRDD[10] at map at TableReader.scala:240
HadoopRDD[9] at HadoopRDD at TableReader.scala:230
```
It's the sub task of #1847. But can go without any dependency.
Author: Cheng Hao <[email protected]>
Closes #1962 from chenghao-intel/explain_extended and squashes the following commits:
295db74 [Cheng Hao] Fix bug in printing the simple execution plan
48bc989 [Cheng Hao] Support EXTENDED for EXPLAIN
Author: wangfei <[email protected]> Closes #1939 from scwf/patch-5 and squashes the following commits: f952d10 [wangfei] [SQL] logWarning should be logInfo in getResultSetSchema
…ontext.parquetFile fix compile error on hadoop 0.23 for the pull request #1924. Author: Chia-Yung Su <[email protected]> Closes #1959 from joesu/bugfix-spark3011 and squashes the following commits: be30793 [Chia-Yung Su] remove .* and _* except _metadata 8fe2398 [Chia-Yung Su] add note to explain 40ea9bd [Chia-Yung Su] fix hadoop-0.23 compile error c7e44f2 [Chia-Yung Su] match syntax f8fc32a [Chia-Yung Su] filter out tmp dir
Put original YARN queue spark-submit arg description in running-on-yarn html table and example command line Author: Mark G. Whitney <[email protected]> Closes #2218 from kramimus/2258-yarndoc and squashes the following commits: 4b5d808 [Mark G. Whitney] remove yarn queue config f8cda0d [Mark G. Whitney] [SPARK-2558][DOCS] Add spark.yarn.queue description to YARN doc
Contributor
|
@BigCrunsh Just saw that the target is |
…orrectly Author: RJ Nowling <[email protected]> Closes #2370 from rnowling/python_rdd_docstrings and squashes the following commits: 5230574 [RJ Nowling] Add blank line so that Python RDD.top() docstring renders correctly
Logically, we should remove the Hive Table/Database first and then reset the Hive configuration, repoint to the new data warehouse directory etc. Otherwise it raised exceptions like "Database doesn't not exists: default" in the local testing. Author: Cheng Hao <[email protected]> Closes #2352 from chenghao-intel/test_hive and squashes the following commits: 74fd76b [Cheng Hao] eliminate the error log
This commit exists to close the following pull requests on Github: Closes #930 (close requested by 'andrewor14') Closes #867 (close requested by 'marmbrus') Closes #1829 (close requested by 'marmbrus') Closes #1131 (close requested by 'JoshRosen') Closes #1571 (close requested by 'andrewor14') Closes #2359 (close requested by 'andrewor14')
GraphX's current implementation of static (fixed iteration count) PageRank uses the Pregel API. This unnecessarily tracks active vertices, even though in static PageRank all vertices are always active. Active vertex tracking incurs the following costs: 1. A shuffle per iteration to ship the active sets to the edge partitions. 2. A hash table creation per iteration at each partition to index the active sets for lookup. 3. A hash lookup per edge to check whether the source vertex is active. I reimplemented static PageRank using the lower-level GraphX API instead of the Pregel API. In benchmarks on a 16-node m2.4xlarge cluster, this provided a 23% speedup (from 514 s to 397 s, mean over 3 trials) for 10 iterations of PageRank on a synthetic graph with 10M vertices and 1.27B edges. Author: Ankur Dave <[email protected]> Closes #2308 from ankurdave/SPARK-3427 and squashes the following commits: 449996a [Ankur Dave] Avoid unnecessary active vertex tracking in static PageRank
…rio... ...s Author: Sandy Ryza <[email protected]> Closes #1934 from sryza/sandy-spark-3014 and squashes the following commits: ae19cc1 [Sandy Ryza] SPARK-3014. Log a more informative messages in a couple failure scenarios
When that option is used, the compiled classes from the build directory are prepended to the classpath. Now that we avoid packaging Guava, that means we have classes referencing the original Guava location in the app's classpath, so errors happen. For that case, add Guava manually to the classpath. Note: if Spark is compiled with "-Phadoop-provided", it's tricky to make things work with SPARK_PREPEND_CLASSES, because you need to add the Hadoop classpath using SPARK_CLASSPATH and that means the older Hadoop Guava overrides the newer one Spark needs. So someone using SPARK_PREPEND_CLASSES needs to remember to not use that profile. Author: Marcelo Vanzin <[email protected]> Closes #2141 from vanzin/SPARK-3217 and squashes the following commits: b967324 [Marcelo Vanzin] [SPARK-3217] Add Guava to classpath when SPARK_PREPEND_CLASSES is set.
Author: Thomas Graves <[email protected]> Closes #2373 from tgravescs/SPARK-3456 and squashes the following commits: 77e9532 [Thomas Graves] [SPARK-3456] YarnAllocator on alpha can lose container requests to RM
After this patch, we can run PySpark in PyPy (testing with PyPy 2.3.1 in Mac 10.9), for example:
```
PYSPARK_PYTHON=pypy ./bin/spark-submit wordcount.py
```
The performance speed up will depend on work load (from 20% to 3000%). Here are some benchmarks:
Job | CPython 2.7 | PyPy 2.3.1 | Speed up
------- | ------------ | ------------- | -------
Word Count | 41s | 15s | 2.7x
Sort | 46s | 44s | 1.05x
Stats | 174s | 3.6s | 48x
Here is the code used for benchmark:
```python
rdd = sc.textFile("text")
def wordcount():
rdd.flatMap(lambda x:x.split('/'))\
.map(lambda x:(x,1)).reduceByKey(lambda x,y:x+y).collectAsMap()
def sort():
rdd.sortBy(lambda x:x, 1).count()
def stats():
sc.parallelize(range(1024), 20).flatMap(lambda x: xrange(5024)).stats()
```
Author: Davies Liu <[email protected]>
Closes #2144 from davies/pypy and squashes the following commits:
9aed6c5 [Davies Liu] use protocol 2 in CloudPickle
4bc1f04 [Davies Liu] refactor
b20ab3a [Davies Liu] pickle sys.stdout and stderr in portable way
3ca2351 [Davies Liu] Merge branch 'master' into pypy
fae8b19 [Davies Liu] improve attrgetter, add tests
591f830 [Davies Liu] try to run tests with PyPy in run-tests
c8d62ba [Davies Liu] cleanup
f651fd0 [Davies Liu] fix tests using array with PyPy
1b98fb3 [Davies Liu] serialize itemgetter/attrgetter in portable ways
3c1dbfe [Davies Liu] Merge branch 'master' into pypy
42fb5fa [Davies Liu] Merge branch 'master' into pypy
cb2d724 [Davies Liu] fix tests
9986692 [Davies Liu] Merge branch 'master' into pypy
25b4ca7 [Davies Liu] support PyPy
Currently, SchemaRDD._jschema_rdd is SchemaRDD, the Scala API (coalesce(), repartition()) can not been called in Python easily, there is no way to specify the implicit parameter `ord`. The _jrdd is an JavaRDD, so _jschema_rdd should also be JavaSchemaRDD. In this patch, change _schema_rdd to JavaSchemaRDD, also added an assert for it. If some methods are missing from JavaSchemaRDD, then it's called by _schema_rdd.baseSchemaRDD().xxx(). BTW, Do we need JavaSQLContext? Author: Davies Liu <[email protected]> Closes #2369 from davies/fix_schemardd and squashes the following commits: abee159 [Davies Liu] use JavaSchemaRDD as SchemaRDD._jschema_rdd
…n in constructor Please refer to the JIRA ticket for details. **NOTE** We should check all test suites that do similar initialization-like side effects in their constructors. This PR only fixes `ParquetMetastoreSuite` because it breaks our Jenkins Maven build. Author: Cheng Lian <[email protected]> Closes #2375 from liancheng/say-no-to-constructor and squashes the following commits: 0ceb75b [Cheng Lian] Moves test suite setup code to beforeAll rather than in constructor
…h failures This is necessary because we rely on this callback interface to clean resources up. The old behavior would lead to resource leaks. Note that this also changes the fault semantics of TaskCompletionListener. Previously failures in TaskCompletionListeners would result in the task being reported immediately. With this change, we report the exception at the end, and the reported exception is a TaskCompletionListenerException that contains all the exception messages. Author: Reynold Xin <[email protected]> Closes #2343 from rxin/taskcontext-callback and squashes the following commits: a3845b2 [Reynold Xin] Mark TaskCompletionListenerException as private[spark]. ac5baea [Reynold Xin] Removed obsolete comment. aa68ea4 [Reynold Xin] Throw an exception if task completion callback fails. 29b6162 [Reynold Xin] oops compilation failed. 1cb444d [Reynold Xin] [SPARK-3469] Call all TaskCompletionListeners even if some fail.
…value of containsNull in an ArrayType After #1889, the default value of `containsNull` in an `ArrayType` is `true`. Author: Yin Huai <[email protected]> Closes #2374 from yhuai/containsNull and squashes the following commits: dc609a3 [Yin Huai] Update the SQL programming guide to show the correct default value of containsNull in an ArrayType (the default value is true instead of false).
… objects ... that expose a stop() lifecycle method. This doesn't add `AutoCloseable`, which is Java 7+ only. But it should be possible to use try-with-resources on a `Closeable` in Java 7, as long as the `close()` does not throw a checked exception, and these don't. Q.E.D. Author: Sean Owen <[email protected]> Closes #2346 from srowen/SPARK-3470 and squashes the following commits: 612c21d [Sean Owen] Add Closeable / close() to Java context objects that expose a stop() lifecycle method
* Fixed random typo * Added in missing description for DecimalType Author: Nicholas Chammas <[email protected]> Closes #2367 from nchammas/patch-1 and squashes the following commits: aa528be [Nicholas Chammas] doc fix for SQL DecimalType 3247ac1 [Nicholas Chammas] [SQL] [Docs] typo fixes
This is a follow up of #2352. Now we can finally remove the evil "MINOR HACK", which covered up the eldest bug in the history of Spark SQL (see details [here](#2352 (comment))). Author: Cheng Lian <[email protected]> Closes #2377 from liancheng/remove-evil-minor-hack and squashes the following commits: 0869c78 [Cheng Lian] Removes the evil MINOR HACK
…rage This is a major refactoring of the in-memory columnar storage implementation, aims to eliminate boxing costs from critical paths (building/accessing column buffers) as much as possible. The basic idea is to refactor all major interfaces into a row-based form and use them together with `SpecificMutableRow`. The difficult part is how to adapt all compression schemes, esp. `RunLengthEncoding` and `DictionaryEncoding`, to this design. Since in-memory compression is disabled by default for now, and this PR should be strictly better than before no matter in-memory compression is enabled or not, maybe I'll finish that part in another PR. **UPDATE** This PR also took the chance to optimize `HiveTableScan` by 1. leveraging `SpecificMutableRow` to avoid boxing cost, and 1. building specific `Writable` unwrapper functions a head of time to avoid per row pattern matching and branching costs. TODO - [x] Benchmark - [ ] ~~Eliminate boxing costs in `RunLengthEncoding`~~ (left to future PRs) - [ ] ~~Eliminate boxing costs in `DictionaryEncoding` (seems not easy to do without specializing `DictionaryEncoding` for every supported column type)~~ (left to future PRs) ## Micro benchmark The benchmark uses a 10 million line CSV table consists of bytes, shorts, integers, longs, floats and doubles, measures the time to build the in-memory version of this table, and the time to scan the whole in-memory table. Benchmark code can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-hivetablescanbenchmark-scala). Script used to generate the input table can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-tablegen-scala). Speedup: - Hive table scanning + column buffer building: **18.74%** The original benchmark uses 1K as in-memory batch size, when increased to 10K, it can be 28.32% faster. - In-memory table scanning: **7.95%** Before: | Building | Scanning ------- | -------- | -------- 1 | 16472 | 525 2 | 16168 | 530 3 | 16386 | 529 4 | 16184 | 538 5 | 16209 | 521 Average | 16283.8 | 528.6 After: | Building | Scanning ------- | -------- | -------- 1 | 13124 | 458 2 | 13260 | 529 3 | 12981 | 463 4 | 13214 | 483 5 | 13583 | 500 Average | 13232.4 | 486.6 Author: Cheng Lian <[email protected]> Closes #2327 from liancheng/prevent-boxing/unboxing and squashes the following commits: 4419fe4 [Cheng Lian] Addressing comments e5d2cf2 [Cheng Lian] Bug fix: should call setNullAt when field value is null to avoid NPE 8b8552b [Cheng Lian] Only checks for partition batch pruning flag once 489f97b [Cheng Lian] Bug fix: TableReader.fillObject uses wrong ordinals 97bbc4e [Cheng Lian] Optimizes hive.TableReader by by providing specific Writable unwrappers a head of time 3dc1f94 [Cheng Lian] Minor changes to eliminate row object creation 5b39cb9 [Cheng Lian] Lowers log level of compression scheme details f2a7890 [Cheng Lian] Use SpecificMutableRow in InMemoryColumnarTableScan to avoid boxing 9cf30b0 [Cheng Lian] Added row based ColumnType.append/extract 456c366 [Cheng Lian] Made compression decoder row based edac3cd [Cheng Lian] Makes ColumnAccessor.extractSingle row based 8216936 [Cheng Lian] Removes boxing cost in IntDelta and LongDelta by providing specialized implementations b70d519 [Cheng Lian] Made some in-memory columnar storage interfaces row-based
Author: Michael Armbrust <[email protected]> Closes #2164 from marmbrus/shufflePartitions and squashes the following commits: 0da1e8c [Michael Armbrust] test hax ef2d985 [Michael Armbrust] more test hacks. 2dabae3 [Michael Armbrust] more test fixes 0bdbf21 [Michael Armbrust] Make parquet tests less order dependent b42eeab [Michael Armbrust] increase test parallelism 80453d5 [Michael Armbrust] Decrease partitions when testing
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 <[email protected]>
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
Aggregate the number of bytes spilled into disks during aggregation or sorting, show them in Web UI.  This patch is blocked by SPARK-3465. (It includes a fix for that). Author: Davies Liu <[email protected]> Closes #2336 from davies/metrics and squashes the following commits: e37df38 [Davies Liu] remove outdated comments 1245eb7 [Davies Liu] remove the temporary fix ebd2f43 [Davies Liu] Merge branch 'master' into metrics 7e4ad04 [Davies Liu] Merge branch 'master' into metrics fbe9029 [Davies Liu] show spilled bytes in Python in web ui
SPARK-3039: Adds the maven property "avro.mapred.classifier" to build spark-assembly with avro-mapred with support for the new Hadoop API. Sets this property to hadoop2 for Hadoop 2 profiles. I am not very familiar with maven, nor do I know whether this potentially breaks something in the hive part of spark. There might be a more elegant way of doing this. Author: Bertrand Bossy <[email protected]> Closes #1945 from bbossy/SPARK-3039 and squashes the following commits: c32ce59 [Bertrand Bossy] SPARK-3039: Allow spark to be built using avro-mapred for hadoop2
…ldn... ...'t depend on Publish local in maven term is `install` and publish otherwise is `deploy` So disabled both for following projects. Author: Prashant Sharma <[email protected]> Closes #2329 from ScrapCodes/SPARK-3452/maven-skip-install and squashes the following commits: 257b79a [Prashant Sharma] [SPARK-3452] Maven build should skip publishing artifacts people shouldn't depend on
SimpleUpdater ignores the regularizer, which leads to an unregularized LogReg. To enable the common L2 regularizer (and the corresponding regularization parameter) for logistic regression the SquaredL2Updater has to be used in SGD (see, e.g., [SVMWithSGD])
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QA tests have started for PR 2231 at commit
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BigCrunsh
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QA tests have finished for PR 2231 at commit
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SimpleUpdater ignores the regularizer, which leads to an unregularized LogReg. To enable the common L2 regularizer (and the corresponding regularization parameter) for logistic regression the SquaredL2Updater has to be used in SGD (see, e.g., [SVMWithSGD])