... copy the spark_cluster_tag from a spot instance requests over to the instances.
Author: Vida Ha <vida@databricks.com>
Closes#2163 from vidaha/vida/spark-3213 and squashes the following commits:
5070a70 [Vida Ha] Spark-3214 Fix issue with spark-ec2 not detecting slaves created with 'Launch More Like This' and using Spot Requests
RDD.lookup(key)
Return the list of values in the RDD for key `key`. This operation
is done efficiently if the RDD has a known partitioner by only
searching the partition that the key maps to.
>>> l = range(1000)
>>> rdd = sc.parallelize(zip(l, l), 10)
>>> rdd.lookup(42) # slow
[42]
>>> sorted = rdd.sortByKey()
>>> sorted.lookup(42) # fast
[42]
It also clean up the code in RDD.py, and fix several bugs (related to preservesPartitioning).
Author: Davies Liu <davies.liu@gmail.com>
Closes#2093 from davies/lookup and squashes the following commits:
1789cd4 [Davies Liu] `f` in foreach could be generator or not.
2871b80 [Davies Liu] Merge branch 'master' into lookup
c6390ea [Davies Liu] address all comments
0f1bce8 [Davies Liu] add test case for lookup()
be0e8ba [Davies Liu] fix preservesPartitioning
eb1305d [Davies Liu] add RDD.lookup(key)
```if (!fs.getFileStatus(path).isDir) throw Exception``` make no sense after this commit #1370
be careful if someone is working on SPARK-2551, make sure the new change passes test case ```test("Read a parquet file instead of a directory")```
Author: chutium <teng.qiu@gmail.com>
Closes#2044 from chutium/parquet-singlefile and squashes the following commits:
4ae477f [chutium] [SPARK-3138][SQL] sqlContext.parquetFile should be able to take a single file as parameter
As seen with [SI-6502](https://issues.scala-lang.org/browse/SI-6502) of Scala, the _:cp_ command was broken in Scala 2.10.x. As the Spark shell is a friendly wrapper on top of the Scala REPL, it is also affected by this problem.
My solution was to alter the internal classpath and invalidate any new entries. I also had to add the ability to add new entries to the parent classloader of the interpreter (SparkIMain's global).
The advantage of this versus wiping the interpreter and replaying all of the commands is that you don't have to worry about rerunning heavy Spark-related commands (going to the cluster) or potentially reloading data that might have changed. Instead, you get to work from where you left off.
Until this is fixed upstream for 2.10.x, I had to use reflection to alter the internal compiler classpath.
The solution now looks like this:
Author: Chip Senkbeil <rcsenkbe@us.ibm.com>
Closes#1929 from rcsenkbeil/FixReplClasspathSupport and squashes the following commits:
f420cbf [Chip Senkbeil] Added SparkContext.addJar calls to support executing code on remote clusters
a826795 [Chip Senkbeil] Updated AddUrlsToClasspath to use 'new Run' suggestion over hackish compiler error
2ff1d86 [Chip Senkbeil] Added compilation failure on symbols hack to get Scala classes to load correctly
a220639 [Chip Senkbeil] Added support for :cp <jar> that was broken in Scala 2.10.x for REPL
Aggregation function min/max in catalyst will create expression tree for each single row, however, the expression tree creation is quite expensive in a multithreading env currently. Hence we got a very bad performance for the min/max.
Here is the benchmark that I've done in my local.
Master | Previous Result (ms) | Current Result (ms)
------------ | ------------- | -------------
local | 3645 | 3416
local[6] | 3602 | 1002
The Benchmark source code.
```
case class Record(key: Int, value: Int)
object TestHive2 extends HiveContext(new SparkContext("local[6]", "TestSQLContext", new SparkConf()))
object DataPrepare extends App {
import TestHive2._
val rdd = sparkContext.parallelize((1 to 10000000).map(i => Record(i % 3000, i)), 12)
runSqlHive("SHOW TABLES")
runSqlHive("DROP TABLE if exists a")
runSqlHive("DROP TABLE if exists result")
rdd.registerAsTable("records")
runSqlHive("""CREATE TABLE a (key INT, value INT)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
runSqlHive("""CREATE TABLE result (key INT, value INT)
| ROW FORMAT SERDE
| 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
| STORED AS RCFILE
""".stripMargin)
hql(s"""from records
| insert into table a
| select key, value
""".stripMargin)
}
object PerformanceTest extends App {
import TestHive2._
hql("SHOW TABLES")
hql("set spark.sql.shuffle.partitions=12")
val cmd = "select min(value), max(value) from a group by key"
val results = ("Result1", benchmark(cmd)) ::
("Result2", benchmark(cmd)) ::
("Result3", benchmark(cmd)) :: Nil
results.foreach { case (prompt, result) => {
println(s"$prompt: took ${result._1} ms (${result._2} records)")
}
}
def benchmark(cmd: String) = {
val begin = System.currentTimeMillis()
val count = hql(cmd).count
val end = System.currentTimeMillis()
((end - begin), count)
}
}
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2113 from chenghao-intel/aggregation_expression_optimization and squashes the following commits:
db40395 [Cheng Hao] remove the transient and add val for the expression property
d56167d [Cheng Hao] Reduce the Expressions creation
JIRA issue: [SPARK-3118] https://issues.apache.org/jira/browse/SPARK-3118
eg:
> SHOW TBLPROPERTIES test;
SHOW TBLPROPERTIES test;
numPartitions 0
numFiles 1
transient_lastDdlTime 1407923642
numRows 0
totalSize 82
rawDataSize 0
eg:
> SHOW COLUMNS in test;
SHOW COLUMNS in test;
OK
Time taken: 0.304 seconds
id
stid
bo
Author: u0jing <u9jing@gmail.com>
Closes#2034 from u0jing/spark-3118 and squashes the following commits:
b231d87 [u0jing] add golden answer files
35f4885 [u0jing] add 'show columns' and 'show tblproperties' support
Author: Allan Douglas R. de Oliveira <allan@chaordicsystems.com>
Closes#2162 from douglaz/user_data_master and squashes the following commits:
10d15f6 [Allan Douglas R. de Oliveira] Give user data also to the master
compeleted stage only need to remove its own partitions that are no longer cached. However, "StorageTab" may lost some rdds which are cached actually. Not only in "StorageTab", "ExectutorTab" may also lose some rdd info which have been overwritten by last rdd in a same task.
1. "StorageTab": when multiple stages run simultaneously, completed stage will remove rdd info which belong to other stages that are still running.
2. "ExectutorTab": taskcontext may lose some "updatedBlocks" info of rdds in a dependency chain. Like the following example:
val r1 = sc.paralize(..).cache()
val r2 = r1.map(...).cache()
val n = r2.count()
When count the r2, r1 and r2 will be cached finally. So in CacheManager.getOrCompute, the taskcontext should contain "updatedBlocks" of r1 and r2. Currently, the "updatedBlocks" only contain the info of r2.
Author: uncleGen <hustyugm@gmail.com>
Closes#2131 from uncleGen/master_ui_fix and squashes the following commits:
a6a8a0b [uncleGen] fix some coding style
3a1bc15 [uncleGen] fix some error in unit test
56ea488 [uncleGen] there's some line too long
c82ba82 [uncleGen] Bug Fix: RDD info loss in "StorageTab" and "ExecutorTab"
This change modifies the Yarn module so that all the logic related
to running the ApplicationMaster is localized. Instead of, previously,
4 different classes with mostly identical code, now we have:
- A single, shared ApplicationMaster class, which can operate both in
client and cluster mode, and substitutes the old ApplicationMaster
(for cluster mode) and ExecutorLauncher (for client mode).
The benefit here is that all different execution modes for all supported
yarn versions use the same shared code for monitoring executor allocation,
setting up configuration, and monitoring the process's lifecycle.
- A new YarnRMClient interface, which defines basic RM functionality needed
by the ApplicationMaster. This interface has concrete implementations for
each supported Yarn version.
- A new YarnAllocator interface, which just abstracts the existing interface
of the YarnAllocationHandler class. This is to avoid having to touch the
allocator code too much in this change, although it might benefit from a
similar effort in the future.
The end result is much easier to understand code, with much less duplication,
making it much easier to fix bugs, add features, and test everything knowing
that all supported versions will behave the same.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#2020 from vanzin/SPARK-2933 and squashes the following commits:
3bbf3e7 [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
ff389ed [Marcelo Vanzin] Do not interrupt reporter thread from within itself.
3a8ed37 [Marcelo Vanzin] Remote stale comment.
0f5142c [Marcelo Vanzin] Review feedback.
41f8c8a [Marcelo Vanzin] Fix app status reporting.
c0794be [Marcelo Vanzin] Correctly clean up staging directory.
92770cc [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
ecaf332 [Marcelo Vanzin] Small fix to shutdown code.
f02d3f8 [Marcelo Vanzin] Merge branch 'master' into SPARK-2933
f581122 [Marcelo Vanzin] Review feedback.
557fdeb [Marcelo Vanzin] Cleanup a couple more constants.
be6068d [Marcelo Vanzin] Restore shutdown hook to clean up staging dir.
5150993 [Marcelo Vanzin] Some more cleanup.
b6289ab [Marcelo Vanzin] Move cluster/client code to separate methods.
ecb23cd [Marcelo Vanzin] More trivial cleanup.
34f1e63 [Marcelo Vanzin] Fix some questionable error handling.
5657c7d [Marcelo Vanzin] Finish app if SparkContext initialization times out.
0e4be3d [Marcelo Vanzin] Keep "ExecutorLauncher" as the main class for client-mode AM.
91beabb [Marcelo Vanzin] Fix UI filter registration.
8c72239 [Marcelo Vanzin] Trivial cleanups.
99a52d5 [Marcelo Vanzin] Changes to the yarn-alpha project to use common AM code.
848ca6d [Marcelo Vanzin] [SPARK-2933] [yarn] Refactor and cleanup Yarn AM code.
Currently lot of errors get thrown from Avro IPC layer when the dstream
or sink is shutdown. This PR cleans it up. Some refactoring is done in the
receiver code to put all of the RPC code into a single Try and just recover
from that. The sink code has also been cleaned up.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#2065 from harishreedharan/clean-flume-shutdown and squashes the following commits:
f93a07c [Hari Shreedharan] Formatting fixes.
d7427cc [Hari Shreedharan] More fixes!
a0a8852 [Hari Shreedharan] Fix race condition, hopefully! Minor other changes.
4c9ed02 [Hari Shreedharan] Remove unneeded list in Callback handler. Other misc changes.
8fee36f [Hari Shreedharan] Scala-library is required, else maven build fails. Also catch InterruptedException in TxnProcessor.
445e700 [Hari Shreedharan] Merge remote-tracking branch 'asf/master' into clean-flume-shutdown
87232e0 [Hari Shreedharan] Refactor Flume Input Stream. Clean up code, better error handling.
9001d26 [Hari Shreedharan] Change log level to debug in TransactionProcessor#shutdown method
e7b8d82 [Hari Shreedharan] Incorporate review feedback
598efa7 [Hari Shreedharan] Clean up some exception handling code
e1027c6 [Hari Shreedharan] Merge remote-tracking branch 'asf/master' into clean-flume-shutdown
ed608c8 [Hari Shreedharan] [SPARK-3154][STREAMING] Make FlumePollingInputDStream shutdown cleaner.
The only updates are in DecisionTree.
CC: mengxr
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes#2146 from jkbradley/mllib-migration and squashes the following commits:
5a1f487 [Joseph K. Bradley] small edit to doc
411d6d9 [Joseph K. Bradley] Added migration guide for v1.0 to v1.1. The only updates are in DecisionTree.
1. renamed mllib-basics to mllib-data-types
1. renamed mllib-stats to mllib-statistics
1. moved random data generation to the bottom of mllib-stats
1. updated toc accordingly
atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes#2151 from mengxr/mllib-doc-1.1 and squashes the following commits:
0bd79f3 [Xiangrui Meng] add mllib-data-types
b64a5d7 [Xiangrui Meng] update the content list of basis statistics in mllib-guide
f625cc2 [Xiangrui Meng] move mllib-basics to mllib-data-types
4d69250 [Xiangrui Meng] move random data generation to the bottom of statistics
e64f3ce [Xiangrui Meng] move mllib-stats.md to mllib-statistics.md
Author: Michael Armbrust <michael@databricks.com>
Closes#2153 from marmbrus/parquetFilters and squashes the following commits:
712731a [Michael Armbrust] Use closure serializer for sending filters.
1e83f80 [Michael Armbrust] Clean udf functions.
As a workaround for SPARK-3015, the ContextCleaner was made "blocking", that is, it cleaned items one-by-one. But shuffles can take a long time to be deleted. Given that the RC for 1.1 is imminent, this PR makes a narrow change in the context cleaner - not wait for shuffle cleanups to complete. Also it changes the error messages on failure to delete to be milder warnings, as exceptions in the delete code path for one item does not really stop the actual functioning of the system.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#2143 from tdas/cleaner-shuffle-fix and squashes the following commits:
9c84202 [Tathagata Das] Restoring default blocking behavior in ContextCleanerSuite, and added docs to identify that spark.cleaner.referenceTracking.blocking does not control shuffle.
2181329 [Tathagata Das] Mark shuffle cleanup as non-blocking.
e337cc2 [Tathagata Das] Changed semantics based on PR comments.
387b578 [Tathagata Das] Made ContextCleaner to not block on shuffles
This is an effort to bring the Windows scripts up to speed after recent splashing changes in #1845.
Author: Andrew Or <andrewor14@gmail.com>
Closes#2129 from andrewor14/windows-config and squashes the following commits:
881a8f0 [Andrew Or] Add reference to Windows taskkill
92e6047 [Andrew Or] Update a few comments (minor)
22b1acd [Andrew Or] Fix style again (minor)
afcffea [Andrew Or] Fix style (minor)
72004c2 [Andrew Or] Actually respect --driver-java-options
803218b [Andrew Or] Actually respect SPARK_*_CLASSPATH
eeb34a0 [Andrew Or] Update outdated comment (minor)
35caecc [Andrew Or] In Windows, actually kill Java processes on exit
f97daa2 [Andrew Or] Fix Windows spark shell stdin issue
83ebe60 [Andrew Or] Parse special driver configs in Windows (broken)
This is a HOTFIX for 1.1.
Author: Reynold Xin <rxin@apache.org>
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#2127 from rxin/SPARK-3224 and squashes the following commits:
effb1ce [Reynold Xin] Move log message.
49282b3 [Reynold Xin] Kay's feedback.
3f01847 [Reynold Xin] Merge pull request #2 from kayousterhout/SPARK-3224
796d282 [Kay Ousterhout] Added unit test for SPARK-3224
3d3d356 [Reynold Xin] Remove map output loc even for repeated FetchFaileds.
1dd3eb5 [Reynold Xin] [SPARK-3224] FetchFailed reduce stages should only show up once in the failed stages UI.
When using Mesos with the fine-grained mode, a Spark job can run into a dead lock on low allocatable memory on Mesos slaves. As a work-around 32 MB (= Mesos MIN_MEM) are allocated for each task, to ensure Mesos making new offers after task completion.
From my perspective, it would be better to fix this problem in Mesos by dropping the constraint on memory for offers, but as temporary solution this patch helps to avoid the dead lock on current Mesos versions.
See [[MESOS-1688] No offers if no memory is allocatable](https://issues.apache.org/jira/browse/MESOS-1688) for details for this problem.
Author: Martin Weindel <martin.weindel@gmail.com>
Closes#1860 from MartinWeindel/master and squashes the following commits:
5762030 [Martin Weindel] reverting work-around
a6bf837 [Martin Weindel] added known issue for issue MESOS-1688
d9d2ca6 [Martin Weindel] work around for problem with Mesos offering semantic (see [https://issues.apache.org/jira/browse/MESOS-1688])
JIRA:
- https://issues.apache.org/jira/browse/SPARK-3036
- https://issues.apache.org/jira/browse/SPARK-3037
Currently this uses the following Parquet schema for `MapType` when `valueContainsNull` is `true`:
```
message root {
optional group a (MAP) {
repeated group map (MAP_KEY_VALUE) {
required int32 key;
optional int32 value;
}
}
}
```
for `ArrayType` when `containsNull` is `true`:
```
message root {
optional group a (LIST) {
repeated group bag {
optional int32 array;
}
}
}
```
We have to think about compatibilities with older version of Spark or Hive or others I mentioned in the JIRA issues.
Notice:
This PR is based on #1963 and #1889.
Please check them first.
/cc marmbrus, yhuai
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2032 from ueshin/issues/SPARK-3036_3037 and squashes the following commits:
4e8e9e7 [Takuya UESHIN] Add ArrayType containing null value support to Parquet.
013c2ca [Takuya UESHIN] Add MapType containing null value support to Parquet.
62989de [Takuya UESHIN] Merge branch 'issues/SPARK-2969' into issues/SPARK-3036_3037
8e38b53 [Takuya UESHIN] Merge branch 'issues/SPARK-3063' into issues/SPARK-3036_3037
The Contributing to Spark guide [recommends](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark#ContributingtoSpark-AutomatedTesting) running tests by calling `./dev/run-tests`. The README should, too.
`./sbt/sbt test` does not cover Python tests or style tests.
Author: nchammas <nicholas.chammas@gmail.com>
Closes#2149 from nchammas/patch-2 and squashes the following commits:
2b3b132 [nchammas] [Docs] Run tests like in contributing guide
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#1886 from sarutak/SPARK-2964 and squashes the following commits:
8ef8751 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-2964
26e7c95 [Kousuke Saruta] Revert "Shorten timeout to more reasonable value"
ffb68fa [Kousuke Saruta] Modified spark-sql and start-thriftserver.sh to use bin/utils.sh
8c6f658 [Kousuke Saruta] Merge branch 'spark-3026' of https://github.com/liancheng/spark into SPARK-2964
81b43a8 [Cheng Lian] Shorten timeout to more reasonable value
a89e66d [Cheng Lian] Fixed command line options quotation in scripts
9c894d3 [Cheng Lian] Fixed bin/spark-sql -S option typo
be4736b [Cheng Lian] Report better error message when running JDBC/CLI without hive-thriftserver profile enabled
use_conf_dir => user_conf_dir in load-spark-env.sh.
Author: WangTao <barneystinson@aliyun.com>
Closes#1926 from WangTaoTheTonic/TypoInScript and squashes the following commits:
0c104ad [WangTao] Typo in script
Using external sort to support sort large datasets in reduce stage.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1978 from davies/sort and squashes the following commits:
bbcd9ba [Davies Liu] check spilled bytes in tests
b125d2f [Davies Liu] add test for external sort in rdd
eae0176 [Davies Liu] choose different disks from different processes and instances
1f075ed [Davies Liu] Merge branch 'master' into sort
eb53ca6 [Davies Liu] Merge branch 'master' into sort
644abaf [Davies Liu] add license in LICENSE
19f7873 [Davies Liu] improve tests
55602ee [Davies Liu] use external sort in sortBy() and sortByKey()
It is common to want to describe sets of attributes that are in various parts of a query plan. However, the semantics of putting `AttributeReference` objects into a standard Scala `Set` result in subtle bugs when references differ cosmetically. For example, with case insensitive resolution it is possible to have two references to the same attribute whose names are not equal.
In this PR I introduce a new abstraction, an `AttributeSet`, which performs all comparisons using the globally unique `ExpressionId` instead of case class equality. (There is already a related class, [`AttributeMap`](https://github.com/marmbrus/spark/blob/inMemStats/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeMap.scala#L32)) This new type of set is used to fix a bug in the optimizer where needed attributes were getting projected away underneath join operators.
I also took this opportunity to refactor the expression and query plan base classes. In all but one instance the logic for computing the `references` of an `Expression` were the same. Thus, I moved this logic into the base class.
For query plans the semantics of the `references` method were ill defined (is it the references output? or is it those used by expression evaluation? or what?). As a result, this method wasn't really used very much. So, I removed it.
TODO:
- [x] Finish scala doc for `AttributeSet`
- [x] Scan the code for other instances of `Set[Attribute]` and refactor them.
- [x] Finish removing `references` from `QueryPlan`
Author: Michael Armbrust <michael@databricks.com>
Closes#2109 from marmbrus/attributeSets and squashes the following commits:
1c0dae5 [Michael Armbrust] work on serialization bug.
9ba868d [Michael Armbrust] Merge remote-tracking branch 'origin/master' into attributeSets
3ae5288 [Michael Armbrust] review comments
40ce7f6 [Michael Armbrust] style
d577cc7 [Michael Armbrust] Scaladoc
cae5d22 [Michael Armbrust] remove more references implementations
d6e16be [Michael Armbrust] Remove more instances of "def references" and normal sets of attributes.
fc26b49 [Michael Armbrust] Add AttributeSet class, remove references from Expression.
Documentation updated for the Statistics Toolkit of MLlib. mengxr atalwalkar
https://issues.apache.org/jira/browse/SPARK-2839
P.S. Accidentally closed#2123. New commits didn't show up after I reopened the PR. I've opened this instead and closed the old one.
Author: Burak <brkyvz@gmail.com>
Closes#2130 from brkyvz/StatsLib-Docs and squashes the following commits:
a54a855 [Burak] [SPARK-2839][MLlib] Addressed comments
bfc6896 [Burak] [SPARK-2839][MLlib] Added a more specific link to colStats() for pyspark
213fe3f [Burak] [SPARK-2839][MLlib] Modifications made according to review
fec4d9d [Burak] [SPARK-2830][MLlib] Stats Toolkit documentation updated
to mention `-Pnetlib-lgpl` option. atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes#2128 from mengxr/mllib-native and squashes the following commits:
4cbba57 [Xiangrui Meng] update mllib dependencies
Currently `ExistingRdd.convertToCatalyst` doesn't convert `Map` value.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1963 from ueshin/issues/SPARK-3063 and squashes the following commits:
3ba41f2 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
4d7bae2 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
9321379 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-3063
d8a900a [Takuya UESHIN] Make ExistingRdd.convertToCatalyst be able to convert Map value.
Make `ScalaReflection` be able to handle like:
- `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)`
- `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)`
- `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)`
- `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1889 from ueshin/issues/SPARK-2969 and squashes the following commits:
24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API.
79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API.
7cd1a7a [Takuya UESHIN] Fix json test failures.
2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true.
2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull.
9fa02f5 [Takuya UESHIN] Fix a test failure.
1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.
RDD.histogram(buckets)
Compute a histogram using the provided buckets. The buckets
are all open to the right except for the last which is closed.
e.g. [1,10,20,50] means the buckets are [1,10) [10,20) [20,50],
which means 1<=x<10, 10<=x<20, 20<=x<=50. And on the input of 1
and 50 we would have a histogram of 1,0,1.
If your histogram is evenly spaced (e.g. [0, 10, 20, 30]),
this can be switched from an O(log n) inseration to O(1) per
element(where n = # buckets).
Buckets must be sorted and not contain any duplicates, must be
at least two elements.
If `buckets` is a number, it will generates buckets which is
evenly spaced between the minimum and maximum of the RDD. For
example, if the min value is 0 and the max is 100, given buckets
as 2, the resulting buckets will be [0,50) [50,100]. buckets must
be at least 1 If the RDD contains infinity, NaN throws an exception
If the elements in RDD do not vary (max == min) always returns
a single bucket.
It will return an tuple of buckets and histogram.
>>> rdd = sc.parallelize(range(51))
>>> rdd.histogram(2)
([0, 25, 50], [25, 26])
>>> rdd.histogram([0, 5, 25, 50])
([0, 5, 25, 50], [5, 20, 26])
>>> rdd.histogram([0, 15, 30, 45, 60], True)
([0, 15, 30, 45, 60], [15, 15, 15, 6])
>>> rdd = sc.parallelize(["ab", "ac", "b", "bd", "ef"])
>>> rdd.histogram(("a", "b", "c"))
(('a', 'b', 'c'), [2, 2])
closes#122, it's duplicated.
Author: Davies Liu <davies.liu@gmail.com>
Closes#2091 from davies/histgram and squashes the following commits:
a322f8a [Davies Liu] fix deprecation of e.message
84e85fa [Davies Liu] remove evenBuckets, add more tests (including str)
d9a0722 [Davies Liu] address comments
0e18a2d [Davies Liu] add histgram() API
There are 4 different compression codec available for ```ParquetOutputFormat```
in Spark SQL, it was set as a hard-coded value in ```ParquetRelation.defaultCompression```
original discuss:
https://github.com/apache/spark/pull/195#discussion-diff-11002083
i added a new config property in SQLConf to allow user to change this compression codec, and i used similar short names syntax as described in SPARK-2953 #1873 (https://github.com/apache/spark/pull/1873/files#diff-0)
btw, which codec should we use as default? it was set to GZIP (https://github.com/apache/spark/pull/195/files#diff-4), but i think maybe we should change this to SNAPPY, since SNAPPY is already the default codec for shuffling in spark-core (SPARK-2469, #1415), and parquet-mr supports Snappy codec natively (e440108de5).
Author: chutium <teng.qiu@gmail.com>
Closes#2039 from chutium/parquet-compression and squashes the following commits:
2f44964 [chutium] [SPARK-3131][SQL] parquet compression default codec set to snappy, also in test suite
e578e21 [chutium] [SPARK-3131][SQL] compression codec config property name and default codec set to snappy
21235dc [chutium] [SPARK-3131][SQL] Allow user to set parquet compression codec for writing ParquetFile in SQLContext
As of #1777 we log the name of the actor system when it binds to a port. The current name "spark" is super general and does not convey any meaning. For instance, the following line is taken from my driver log after setting `spark.driver.port` to 5001.
```
14/08/13 19:33:29 INFO Remoting: Remoting started; listening on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/13 19:33:29 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/06 13:40:05 INFO Utils: Successfully started service 'spark' on port 5001.
```
This commit renames this to "sparkDriver" and "sparkExecutor". The goal of this unambitious PR is simply to make the logged information more explicit without introducing any change in functionality.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1810 from andrewor14/service-name and squashes the following commits:
8c459ed [Andrew Or] Use a common variable for driver/executor actor system names
3a92843 [Andrew Or] Change actor name to sparkDriver and sparkExecutor
921363e [Andrew Or] Merge branch 'master' of github.com:apache/spark into service-name
c8c6a62 [Andrew Or] Do not include hyphens in actor name
1c1b42e [Andrew Or] Avoid spaces in akka system name
f644b55 [Andrew Or] Use more specific service name
We can simple treat cross join as inner join without join conditions.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: adrian-wang <daoyuanwong@gmail.com>
Closes#2124 from adrian-wang/crossjoin and squashes the following commits:
8c9b7c5 [Daoyuan Wang] add a test
7d47bbb [adrian-wang] add cross join support for hql
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#1895 from sarutak/SPARK-2976 and squashes the following commits:
1cf7e69 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-2976
d1e0666 [Kousuke Saruta] Modified styles
c5e80a4 [Kousuke Saruta] Remove tab from JavaPageRank.java and JavaKinesisWordCountASL.java
c003b36 [Kousuke Saruta] Removed tab from sorttable.js
Author: witgo <witgo@qq.com>
Author: GuoQiang Li <witgo@qq.com>
Closes#1341 from witgo/history_env and squashes the following commits:
b4fd9f8 [GuoQiang Li] review commit
0ebe401 [witgo] *-history-server.sh load spark-config.sh
fix compile error on hadoop 0.23 for the pull request #1924.
Author: Chia-Yung Su <chiayung@appier.com>
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
Author: wangfei <wangfei_hello@126.com>
Closes#1939 from scwf/patch-5 and squashes the following commits:
f952d10 [wangfei] [SQL] logWarning should be logInfo in getResultSetSchema
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 <hao.cheng@intel.com>
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
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 <lian.cs.zju@gmail.com>
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
Author: Takuya UESHIN <ueshin@happy-camper.st>
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.
It should be `spark-env.sh` rather than `spark.env.sh`.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#2119 from liancheng/fix-mesos-doc and squashes the following commits:
f360548 [Cheng Lian] Fixed a typo in docs/running-on-mesos.md
rxin
Author: Xiangrui Meng <meng@databricks.com>
Closes#2120 from mengxr/sendMessageReliably and squashes the following commits:
b14400c [Xiangrui Meng] fix error message in sendMessageReliably
Adds the --authorized-address and --additional-security-group options as explained in the issue.
Author: Allan Douglas R. de Oliveira <allan@chaordicsystems.com>
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
(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 <sowen@cloudera.com>
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
to re-construct k-means models freeman-lab
Author: Xiangrui Meng <meng@databricks.com>
Closes#2112 from mengxr/public-constructors and squashes the following commits:
18d53a9 [Xiangrui Meng] make KMeans constructor public
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 <davies.liu@gmail.com>
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()
Update the documentation to reflect the fact we can handle roughly square matrices.
Author: Reza Zadeh <rizlar@gmail.com>
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
Documentation for newly added feature transformations:
1. TF-IDF
2. StandardScaler
3. Normalizer
Author: DB Tsai <dbtsai@alpinenow.com>
Closes#2068 from dbtsai/transformer-documentation and squashes the following commits:
109f324 [DB Tsai] address feedback
