When we decrease the width of browsers, the header of WebUI wraps and collapses like as following image.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3995 from sarutak/fixed-collapse-webui-layout and squashes the following commits:
3e60b5b [Kousuke Saruta] Modified line-height property in webui.css
7bfb5fb [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fixed-collapse-webui-layout
5d83e18 [Kousuke Saruta] Fixed collapse of WebUI layout
History Server doesn't show collect job submission time.
It's because `JobProgressListener` updates job submission time every time `onJobStart` method is invoked from `ReplayListenerBus`.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#4029 from sarutak/SPARK-5231 and squashes the following commits:
0af9e22 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5231
da8bd14 [Kousuke Saruta] Made submissionTime in SparkListenerJobStartas and completionTime in SparkListenerJobEnd as regular Long
0412a6a [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5231
26b9b99 [Kousuke Saruta] Fixed the test cases
2d47bd3 [Kousuke Saruta] Fixed to record job submission time and completion time collectly
There is an int overflow in the ParallelCollectionRDD.slice method. That's originally reported by SaintBacchus.
```
sc.makeRDD(1 to (Int.MaxValue)).count // result = 0
sc.makeRDD(1 to (Int.MaxValue - 1)).count // result = 2147483646 = Int.MaxValue - 1
sc.makeRDD(1 until (Int.MaxValue)).count // result = 2147483646 = Int.MaxValue - 1
```
see https://github.com/apache/spark/pull/2874 for more details.
This pr try to fix the overflow. However, There's another issue I don't address.
```
val largeRange = Int.MinValue to Int.MaxValue
largeRange.length // throws java.lang.IllegalArgumentException: -2147483648 to 2147483647 by 1: seqs cannot contain more than Int.MaxValue elements.
```
So, the range we feed to sc.makeRDD cannot contain more than Int.MaxValue elements. This is the limitation of Scala. However I think we may want to support that kind of range. But the fix is beyond this pr.
srowen andrewor14 would you mind take a look at this pr?
Author: Ye Xianjin <advancedxy@gmail.com>
Closes#4002 from advancedxy/SPARk-5201 and squashes the following commits:
96265a1 [Ye Xianjin] Update slice method comment and some responding docs.
e143d7a [Ye Xianjin] Update inclusive range check for splitting inclusive range.
b3f5577 [Ye Xianjin] We can include the last element in the last slice in general for inclusive range, hence eliminate the need to check Int.MaxValue or Int.MinValue.
7d39b9e [Ye Xianjin] Convert the two cases pattern matching to one case.
651c959 [Ye Xianjin] rename sign to needsInclusiveRange. add some comments
196f8a8 [Ye Xianjin] Add test cases for ranges end with Int.MaxValue or Int.MinValue
e66e60a [Ye Xianjin] Deal with inclusive and exclusive ranges in one case. If the range is inclusive and the end of the range is (Int.MaxValue or Int.MinValue), we should use inclusive range instead of exclusive
Based on top of changes in https://github.com/apache/spark/pull/3806.
https://issues.apache.org/jira/browse/SPARK-1507
`--driver-cores` and `spark.driver.cores` for all cluster modes and `spark.yarn.am.cores` for yarn client mode.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#4018 from WangTaoTheTonic/SPARK-1507 and squashes the following commits:
01419d3 [WangTaoTheTonic] amend the args name
b255795 [WangTaoTheTonic] indet thing
d86557c [WangTaoTheTonic] some comments amend
43c9392 [WangTao] fix compile error
b39a100 [WangTao] specify # cores for ApplicationMaster
When calculating the input metrics there was an assumption that one task only reads from one block - this is not true for some operations including coalesce. This patch simply increments the task's input metrics if previous ones existed of the same read method.
A limitation to this patch is that if a task reads from two different blocks of different read methods, one will override the other.
Author: Kostas Sakellis <kostas@cloudera.com>
Closes#3120 from ksakellis/kostas-spark-4092 and squashes the following commits:
54e6658 [Kostas Sakellis] Drops metrics if conflicting read methods exist
f0e0cc5 [Kostas Sakellis] Add bytesReadCallback to InputMetrics
a2a36d4 [Kostas Sakellis] CR feedback
5a0c770 [Kostas Sakellis] [SPARK-4092] [CORE] Fix InputMetrics for coalesce'd Rdds
Adds onExecutorAdded and onExecutorRemoved events to the SparkListener. This will allow a client to get notified when an executor has been added/removed and provide additional information such as how many vcores it is consuming.
In addition, this commit adds a SparkListenerAdapter to the Java API that provides default implementations to the SparkListener. This is to get around the fact that default implementations for traits don't work in Java. Having Java clients extend SparkListenerAdapter moving forward will prevent breakage in java when we add new events to SparkListener.
Author: Kostas Sakellis <kostas@cloudera.com>
Closes#3711 from ksakellis/kostas-spark-4857 and squashes the following commits:
946d2c5 [Kostas Sakellis] Added executorAdded/Removed events to MesosSchedulerBackend
b1d054a [Kostas Sakellis] Remove executorInfo from ExecutorRemoved event
1727b38 [Kostas Sakellis] Renamed ExecutorDetails back to ExecutorInfo and other CR feedback
14fe78d [Kostas Sakellis] Added executor added/removed events to json protocol
93d087b [Kostas Sakellis] [SPARK-4857] [CORE] Adds Executor membership events to SparkListener
In BlockManager, there is a word `BlockTranserService` but I think it's typo for `BlockTransferService`.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#4046 from sarutak/fix-tiny-typo and squashes the following commits:
a3e2a2f [Kousuke Saruta] Fixed tiny typo in BlockManager
As part of SPARK-5193:
1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf").
2. For Java UDFs, renamed dataType to returnType.
3. For Scala UDFs, added type tags.
4. Added all Java UDF registration methods to Scala's UDFRegistration.
5. Documentation
Author: Reynold Xin <rxin@databricks.com>
Closes#4056 from rxin/udf-registration and squashes the following commits:
ae9c556 [Reynold Xin] Updated example.
675a3c9 [Reynold Xin] Style fix
47c24ff [Reynold Xin] Python fix.
5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags.
032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.
After the default batchSize changed to 0 (batched based on the size of object), but parallelize() still use BatchedSerializer with batchSize=1, this PR will use batchSize=1024 for parallelize by default.
Also, BatchedSerializer did not work well with list and numpy.ndarray, this improve BatchedSerializer by using __len__ and __getslice__.
Here is the benchmark for parallelize 1 millions int with list or ndarray:
| before | after | improvements
------- | ------------ | ------------- | -------
list | 11.7 s | 0.8 s | 14x
numpy.ndarray | 32 s | 0.7 s | 40x
Author: Davies Liu <davies@databricks.com>
Closes#4024 from davies/opt_numpy and squashes the following commits:
7618c7c [Davies Liu] improve performance of parallelize list/ndarray
1. Removed the deprecated LocalHiveContext
2. Made private[sql] fields protected[sql] so they don't show up in javadoc.
3. Added javadoc to refreshTable.
4. Added Experimental tag to analyze command.
Author: Reynold Xin <rxin@databricks.com>
Closes#4054 from rxin/hivecontext-api and squashes the following commits:
25cc00a [Reynold Xin] Add implicit conversion back.
cbca886 [Reynold Xin] [SPARK-5193][SQL] Tighten up HiveContext API
Forgot to remove this section in #4052.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4053 from mengxr/SPARK-5254-update and squashes the following commits:
f295bde [Xiangrui Meng] remove developers section from spark.ml guide
1. Removed 2 implicits (logicalPlanToSparkQuery and baseRelationToSchemaRDD)
2. Moved extraStrategies into ExperimentalMethods.
3. Made private methods protected[sql] so they don't show up in javadocs.
4. Removed createParquetFile.
5. Added Java version of applySchema to SQLContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#4049 from rxin/sqlContext-refactor and squashes the following commits:
a326a1a [Reynold Xin] Remove createParquetFile and add applySchema for Java to SQLContext.
ecd6685 [Reynold Xin] Added baseRelationToSchemaRDD back.
4a38c9b [Reynold Xin] [SPARK-5193][SQL] Tighten up SQLContext API
The current statement in the user guide may deliver confusing messages to users. spark.ml contains high-level APIs for building ML pipelines. But it doesn't mean that spark.mllib is being deprecated.
First of all, the pipeline API is in its alpha stage and we need to see more use cases from the community to stabilizes it, which may take several releases. Secondly, the components in spark.ml are simple wrappers over spark.mllib implementations. Neither the APIs or the implementations from spark.mllib are being deprecated. We expect users use spark.ml pipeline APIs to build their ML pipelines, but we will keep supporting and adding features to spark.mllib. For example, there are many features in review at https://spark-prs.appspot.com/#mllib. So users should be comfortable with using spark.mllib features and expect more coming. The user guide needs to be updated to make the message clear.
Author: Xiangrui Meng <meng@databricks.com>
Closes#4052 from mengxr/SPARK-5254 and squashes the following commits:
6d5f1d3 [Xiangrui Meng] typo
0cc935b [Xiangrui Meng] update user guide to position spark.ml better
JIRA issue: https://issues.apache.org/jira/browse/SPARK-5234
simply add the call.
Author: Yuhao Yang <yuhao@yuhaodevbox.sh.intel.com>
Closes#4044 from hhbyyh/addscStop and squashes the following commits:
c1f75ac [Yuhao Yang] add SparkContext.stop to 3 ml examples
Declare SQLConf to be serializable to fix "Task not serializable" exceptions in SparkSQL
Author: Alex Baretta <alexbaretta@gmail.com>
Closes#4031 from alexbaretta/SPARK-5235-SQLConf and squashes the following commits:
c2103f5 [Alex Baretta] [SPARK-5235] Make SQLConf Serializable
`TaskContext.attemptId` is misleadingly-named, since it currently returns a taskId, which uniquely identifies a particular task attempt within a particular SparkContext, instead of an attempt number, which conveys how many times a task has been attempted.
This patch deprecates `TaskContext.attemptId` and add `TaskContext.taskId` and `TaskContext.attemptNumber` fields. Prior to this change, it was impossible to determine whether a task was being re-attempted (or was a speculative copy), which made it difficult to write unit tests for tasks that fail on early attempts or speculative tasks that complete faster than original tasks.
Earlier versions of the TaskContext docs suggest that `attemptId` behaves like `attemptNumber`, so there's an argument to be made in favor of changing this method's implementation. Since we've decided against making that change in maintenance branches, I think it's simpler to add better-named methods and retain the old behavior for `attemptId`; if `attemptId` behaved differently in different branches, then this would cause confusing build-breaks when backporting regression tests that rely on the new `attemptId` behavior.
Most of this patch is fairly straightforward, but there is a bit of trickiness related to Mesos tasks: since there's no field in MesosTaskInfo to encode the attemptId, I packed it into the `data` field alongside the task binary.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3849 from JoshRosen/SPARK-4014 and squashes the following commits:
89d03e0 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
5cfff05 [Josh Rosen] Introduce wrapper for serializing Mesos task launch data.
38574d4 [Josh Rosen] attemptId -> taskAttemptId in PairRDDFunctions
a180b88 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
1d43aa6 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
eee6a45 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014
0b10526 [Josh Rosen] Use putInt instead of putLong (silly mistake)
8c387ce [Josh Rosen] Use local with maxRetries instead of local-cluster.
cbe4d76 [Josh Rosen] Preserve attemptId behavior and deprecate it:
b2dffa3 [Josh Rosen] Address some of Reynold's minor comments
9d8d4d1 [Josh Rosen] Doc typo
1e7a933 [Josh Rosen] [SPARK-4014] Change TaskContext.attemptId to return attempt number instead of task ID.
fd515a5 [Josh Rosen] Add failing test for SPARK-4014
In current WebUI, tables for Active Stages, Completed Stages, Skipped Stages and Failed Stages are hidden when they are empty while tables for Active Jobs, Completed Jobs and Failed Jobs are not hidden though they are empty.
This is before my patch is applied.
And this is after my patch is applied.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#4028 from sarutak/SPARK-5228 and squashes the following commits:
b1e6e8b [Kousuke Saruta] Fixed a small typo
daab563 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5228
9493a1d [Kousuke Saruta] Modified AllJobPage.scala so that hide Active Jobs/Completed Jobs/Failed Jobs when they are empty
Slightly different than the scala code which converts the sparsevector into a densevector and then checks the index.
I also hope I've added tests in the right place.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#4025 from MechCoder/spark-2909 and squashes the following commits:
07d0f26 [MechCoder] STY: Rename item to index
f02148b [MechCoder] [SPARK-2909] [Mlib] SparseVector in pyspark now supports indexing
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4000 from adrian-wang/comment and squashes the following commits:
9c24fc4 [Daoyuan Wang] some comments
jira: https://issues.apache.org/jira/browse/SPARK-5211
Author: Yin Huai <yhuai@databricks.com>
Closes#4026 from yhuai/SPARK-5211 and squashes the following commits:
15ee32b [Yin Huai] Remove extra line.
c6c1651 [Yin Huai] Get back HiveMetastoreTypes.toDataType.
rxin follow up of #3732
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4041 from adrian-wang/decimal and squashes the following commits:
aa3d738 [Daoyuan Wang] fix auto refactor
7777a58 [Daoyuan Wang] move sql.types.decimal.Decimal to sql.types.Decimal
Mostly just moving stuff around. This should still be source compatible since we type aliased Row previously in org.apache.spark.sql.Row.
Added the following APIs to Row:
```scala
def getMap[K, V](i: Int): scala.collection.Map[K, V]
def getJavaMap[K, V](i: Int): java.util.Map[K, V]
def getSeq[T](i: Int): Seq[T]
def getList[T](i: Int): java.util.List[T]
def getStruct(i: Int): StructType
```
Author: Reynold Xin <rxin@databricks.com>
Closes#4030 from rxin/sql-row and squashes the following commits:
6c85c29 [Reynold Xin] Fixed style violation by adding a new line to Row.scala.
82b064a [Reynold Xin] [SPARK-5167][SQL] Move Row into sql package and make it usable for Java.
Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box.
As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code.
This subsumes https://github.com/apache/spark/pull/3925
Author: Reynold Xin <rxin@databricks.com>
Closes#3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits:
66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
This change should be binary and source backward compatible since we didn't change any user facing APIs.
Author: Reynold Xin <rxin@databricks.com>
Closes#3965 from rxin/SPARK-5168-sqlconf and squashes the following commits:
42eec09 [Reynold Xin] Fix default conf value.
0ef86cc [Reynold Xin] Fix constructor ordering.
4d7f910 [Reynold Xin] Properly override config.
ccc8e6a [Reynold Xin] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext
With changes in this PR, users can persist metadata of tables created based on the data source API in metastore through DDLs.
Author: Yin Huai <yhuai@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3960 from yhuai/persistantTablesWithSchema2 and squashes the following commits:
069c235 [Yin Huai] Make exception messages user friendly.
c07cbc6 [Yin Huai] Get the location of test file in a correct way.
4456e98 [Yin Huai] Test data.
5315dfc [Yin Huai] rxin's comments.
7fc4b56 [Yin Huai] Add DDLStrategy and HiveDDLStrategy to plan DDLs based on the data source API.
aeaf4b3 [Yin Huai] Add comments.
06f9b0c [Yin Huai] Revert unnecessary changes.
feb88aa [Yin Huai] Merge remote-tracking branch 'apache/master' into persistantTablesWithSchema2
172db80 [Yin Huai] Fix unit test.
49bf1ac [Yin Huai] Unit tests.
8f8f1a1 [Yin Huai] [SPARK-4574][SQL] Adding support for defining schema in foreign DDL commands. #3431
f47fda1 [Yin Huai] Unit tests.
2b59723 [Michael Armbrust] Set external when creating tables
c00bb1b [Michael Armbrust] Don't use reflection to read options
1ea6e7b [Michael Armbrust] Don't fail when trying to uncache a table that doesn't exist
6edc710 [Michael Armbrust] Add tests.
d7da491 [Michael Armbrust] First draft of persistent tables.
It will introduce problems if the object in dict/list/tuple can not support by py4j, such as Vector.
Also, pickle may have better performance for larger object (less RPC).
In some cases that the object in dict/list can not be pickled (such as JavaObject), we should still use MapConvert/ListConvert.
This PR should be ported into branch-1.2
Author: Davies Liu <davies@databricks.com>
Closes#4023 from davies/listconvert and squashes the following commits:
55d4ab2 [Davies Liu] fix MapConverter and ListConverter in MLlib
There is a discrepancy in WAL implementation and configuration doc.
Author: uncleGen <hustyugm@gmail.com>
Closes#3930 from uncleGen/master-clean-doc and squashes the following commits:
3a4245f [uncleGen] doc typo
8e407d3 [uncleGen] doc typo
I found some arguments in yarn module take environment variables before system properties while the latter override the former in core module.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#3557 from WangTaoTheTonic/SPARK4697 and squashes the following commits:
836b9ef [WangTaoTheTonic] fix type mismatch
e3e486a [WangTaoTheTonic] remove the comma
1262d57 [WangTaoTheTonic] handle spark.app.name and SPARK_YARN_APP_NAME in SparkSubmitArguments
bee9447 [WangTaoTheTonic] wrong brace
81833bb [WangTaoTheTonic] rebase
40934b4 [WangTaoTheTonic] just switch blocks
5f43f45 [WangTao] System property can override environment variable
https://issues.apache.org/jira/browse/SPARK-5006
I think the issue is produced in https://github.com/apache/spark/pull/1777.
Not digging mesos's backend yet. Maybe should add same logic either.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#3841 from WangTaoTheTonic/SPARK-5006 and squashes the following commits:
8cdf96d [WangTao] indent thing
2d86d65 [WangTaoTheTonic] fix line length
7cdfd98 [WangTaoTheTonic] fit for new HttpServer constructor
61a370d [WangTaoTheTonic] some minor fixes
bc6e1ec [WangTaoTheTonic] rebase
67bcb46 [WangTaoTheTonic] put conf at 3rd position, modify suite class, add comments
f450cd1 [WangTaoTheTonic] startServiceOnPort will use a SparkConf arg
29b751b [WangTaoTheTonic] rebase as ExecutorRunnableUtil changed to ExecutorRunnable
396c226 [WangTaoTheTonic] make the grammar more like scala
191face [WangTaoTheTonic] invalid value name
62ec336 [WangTaoTheTonic] spark.port.maxRetries doesn't work
When attempting to infer the schema of an RDD that contains namedtuples, pyspark fails to identify the records as namedtuples, resulting in it raising an error.
Example:
```python
from pyspark import SparkContext
from pyspark.sql import SQLContext
from collections import namedtuple
import os
sc = SparkContext()
rdd = sc.textFile(os.path.join(os.getenv('SPARK_HOME'), 'README.md'))
TextLine = namedtuple('TextLine', 'line length')
tuple_rdd = rdd.map(lambda l: TextLine(line=l, length=len(l)))
tuple_rdd.take(5) # This works
sqlc = SQLContext(sc)
# The following line raises an error
schema_rdd = sqlc.inferSchema(tuple_rdd)
```
The error raised is:
```
File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 107, in main
process()
File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 98, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/serializers.py", line 227, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/rdd.py", line 1107, in takeUpToNumLeft
yield next(iterator)
File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/sql.py", line 816, in convert_struct
raise ValueError("unexpected tuple: %s" % obj)
TypeError: not all arguments converted during string formatting
```
Author: Gabe Mulley <gabe@edx.org>
Closes#3978 from mulby/inferschema-namedtuple and squashes the following commits:
98c61cc [Gabe Mulley] Ensure exception message is populated correctly
375d96b [Gabe Mulley] Ensure schema can be inferred from a namedtuple
Followup to #3870. Props to rahulaggarwalguavus for identifying the issue.
Author: Michael Armbrust <michael@databricks.com>
Closes#3990 from marmbrus/SPARK-5049 and squashes the following commits:
dd03e4e [Michael Armbrust] Fill in the partition values of parquet scans instead of using JoinedRow
Currently WAL-backed block is read out from HDFS and put into BlockManger with storage level MEMORY_ONLY_SER by default, since WAL-backed block is already materialized in HDFS with fault-tolerance, no need to put into BlockManger again by default.
Author: jerryshao <saisai.shao@intel.com>
Closes#3906 from jerryshao/SPARK-4999 and squashes the following commits:
b95f95e [jerryshao] Change storeInBlockManager to false by default
In addition to the `hadoop-2.x` profiles in the parent POM, there is actually another set of profiles in `examples` that has to be activated differently to get the right Hadoop 1 vs 2 flavor of HBase. This wasn't actually used in making Hadoop 2 distributions, hence the problem.
To reduce complexity, I suggest merging them with the parent POM profiles, which is possible now.
You'll see this changes appears to update the HBase version, but actually, the default 0.94 version was not being used. HBase is only used in examples, and the examples POM always chose one profile or the other that updated the version to 0.98.x anyway.
Author: Sean Owen <sowen@cloudera.com>
Closes#3992 from srowen/SPARK-5172 and squashes the following commits:
17830d9 [Sean Owen] Control hbase hadoop1/2 flavor in the parent POM with existing hadoop-2.x profiles
Current spark lets you set the ip address using SPARK_LOCAL_IP, but then this is given to akka after doing a reverse DNS lookup. This makes it difficult to run spark in Docker. You can already change the hostname that is used programmatically, but it would be nice to be able to do this with an environment variable as well.
Author: Michael Armbrust <michael@databricks.com>
Closes#3893 from marmbrus/localHostnameEnv and squashes the following commits:
85045b6 [Michael Armbrust] Optionally read from SPARK_LOCAL_HOSTNAME
https://issues.apache.org/jira/browse/SPARK-4159 was resolved but as Sandy points out, the guidance in https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools under "Running Individual Tests" no longer quite works, not optimally.
This minor change is not really the important change, which is an update to the wiki text. The correct way to run one Scala test suite in Maven is now:
```
mvn test -DwildcardSuites=org.apache.spark.io.CompressionCodecSuite -Dtests=none
```
The correct way to run one Java test is
```
mvn test -DwildcardSuites=none -Dtests=org.apache.spark.streaming.JavaAPISuite
```
Basically, you have to set two properties in order to suppress all of one type of test (with a non-existent test name like 'none') and all but one test of the other type.
The change in the PR just prevents Surefire from barfing when it finds no "none" test.
Author: Sean Owen <sowen@cloudera.com>
Closes#3993 from srowen/SPARK-4159 and squashes the following commits:
83106d7 [Sean Owen] Default failIfNoTests to false to enable the -DwildcardSuites=... -Dtests=... syntax for running one test to work
CompressedMapStatus and HighlyCompressedMapStatus needs to be registered with Kryo, because they are subclass of MapStatus.
Author: lianhuiwang <lianhuiwang09@gmail.com>
Closes#4007 from lianhuiwang/SPARK-5102 and squashes the following commits:
9d2238a [lianhuiwang] remove register of MapStatus
05a285d [lianhuiwang] subclass of MapStatus needs to be registered with Kryo
Disables the Spark web UI in HiveThriftServer2Suite in order to prevent Jenkins test failures due to port contention.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3998 from JoshRosen/SPARK-5200 and squashes the following commits:
a384416 [Josh Rosen] [SPARK-5200] Disable web UI in Hive Thriftserver tests.
Moving MutlivariateGaussian from private[mllib] to public. The class uses Breeze vectors internally, so this involves creating a public interface using MLlib vectors and matrices.
This initial commit provides public construction, accessors for mean/covariance, density and log-density.
Other potential methods include entropy and sample generation.
Author: Travis Galoppo <tjg2107@columbia.edu>
Closes#3923 from tgaloppo/spark-5018 and squashes the following commits:
2b15587 [Travis Galoppo] Style correction
b4121b4 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' into spark-5018
e30a100 [Travis Galoppo] Made mu, sigma private[mllib] members of MultivariateGaussian Moved MultivariateGaussian (and test suite) from stat.impl to stat.distribution (required updates in GaussianMixture{EM,Model}.scala) Marked MultivariateGaussian as @DeveloperApi Fixed style error
9fa3bb7 [Travis Galoppo] Style improvements
91a5fae [Travis Galoppo] Rearranged equation for part of density function
8c35381 [Travis Galoppo] Fixed accessor methods to match member variable names. Modified calculations to avoid log(pow(x,y)) calculations
0943dc4 [Travis Galoppo] SPARK-5018
4dee9e1 [Travis Galoppo] SPARK-5018
If input of the SparkPi args is larger than the 25000, the integer 'n' inside the code will be overflow, and may be a negative number.
And it causes the (0 until n) Seq as an empty seq, then doing the action 'reduce' will throw the UnsupportedOperationException("empty collection").
The max size of the input of sc.parallelize is Int.MaxValue - 1, not the Int.MaxValue.
Author: huangzhaowei <carlmartinmax@gmail.com>
Closes#2874 from SaintBacchus/SparkPi and squashes the following commits:
62d7cd7 [huangzhaowei] Add a commit to explain the modify
4cdc388 [huangzhaowei] Update SparkPi.scala
9a2fb7b [huangzhaowei] Input of the SparkPi is too big
A few changes to fix this issue:
1. Handle the case that receiving `SparkListenerTaskStart` before `SparkListenerBlockManagerAdded`.
2. Don't add `executorId` to `removeTimes` when the executor is busy.
3. Use `HashMap.retain` to safely traverse the HashMap and remove items.
4. Use the same lock in ExecutorAllocationManager and ExecutorAllocationListener to fix the race condition in `totalPendingTasks`.
5. Move the blocking codes out of the message processing code in YarnSchedulerActor.
Author: zsxwing <zsxwing@gmail.com>
Closes#3783 from zsxwing/SPARK-4951 and squashes the following commits:
d51fa0d [zsxwing] Add comments
2e365ce [zsxwing] Remove expired executors from 'removeTimes' and add idle executors back when a new executor joins
49f61a9 [zsxwing] Eliminate duplicate executor registered warnings
d4c4e9a [zsxwing] Minor fixes for the code style
05f6238 [zsxwing] Move the blocking codes out of the message processing code
105ba3a [zsxwing] Fix the race condition in totalPendingTasks
d5c615d [zsxwing] Fix the issue that a busy executor may be killed
Because major OS page sizes is about 4KB, the default value of spark.storage.memoryMapThreshold is integrated to 2 * 4096
Author: lewuathe <lewuathe@me.com>
Closes#3900 from Lewuathe/integrate-memoryMapThreshold and squashes the following commits:
e417acd [lewuathe] [SPARK-5073] Update docs/configuration
834aba4 [lewuathe] [SPARK-5073] Fix style
adcea33 [lewuathe] [SPARK-5073] Integrate memory map threshold to 2MB
fcce2e5 [lewuathe] [SPARK-5073] spark.storage.memoryMapThreshold have two default value
Since GraphX is no longer alpha as of 1.2, MimaExcludes should not exclude GraphX for 1.3
Here are the individual excludes I had to add + the associated commits:
```
// SPARK-4444
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.graphx.EdgeRDD.fromEdges"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.EdgeRDD.filter"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.graphx.impl.EdgeRDDImpl.filter"),
```
[9ac2bb18ed]
```
// SPARK-3623
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.Graph.checkpoint")
```
[e895e0cbec]
```
// SPARK-4620
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.Graph.unpersist"),
```
[8817fc7fe8]
CC: rxin
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#3856 from jkbradley/graphx-mima and squashes the following commits:
1eea2f6 [Joseph K. Bradley] moved cleanup to run-tests
527ccd9 [Joseph K. Bradley] fixed jenkins script to remove ivy2 cache
802e252 [Joseph K. Bradley] Removed GraphX MIMA excludes and added line to clear spark from .m2 dir before Jenkins tests. This may not work yet...
30f8bb4 [Joseph K. Bradley] added individual mima excludes for graphx
a3fea42 [Joseph K. Bradley] removed graphx mima exclude for 1.3
Enable from follow multiple brackets:
```
select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1
```
Author: scwf <wangfei1@huawei.com>
Closes#3853 from scwf/from and squashes the following commits:
14f110a [scwf] enable from follow multiple brackets
Author: wangfei <wangfei1@huawei.com>
Closes#3718 from scwf/sparksqlui and squashes the following commits:
e0d6b5d [wangfei] format fix
383b505 [wangfei] fix conflicts
4d2038a [wangfei] using setJobDescription
df79837 [wangfei] fix compile error
92ce834 [wangfei] show sql statement in spark ui when run sql use spark-sql
cc andrewor14
Author: GuoQiang Li <witgo@qq.com>
Closes#3989 from witgo/MQTTStreamSuite and squashes the following commits:
a6e967e [GuoQiang Li] Resolve sbt warnings during build (MQTTStreamSuite.scala).
https://issues.apache.org/jira/browse/SPARK-5181
Currently, even the logManager is not created, we still see the log entry
s"Writing to log $record"
a simple fix to make log more accurate
Author: CodingCat <zhunansjtu@gmail.com>
Closes#3985 from CodingCat/SPARK-5181 and squashes the following commits:
0e27dc5 [CodingCat] do not print writing WAL log when WAL is disabled
Author: Michael Armbrust <michael@databricks.com>
Closes#3987 from marmbrus/hiveUdfCaching and squashes the following commits:
8bca2fa [Michael Armbrust] [SPARK-5187][SQL] Fix caching of tables with HiveUDFs in the WHERE clause
https://issues.apache.org/jira/browse/SPARK-4963
SchemaRDD.sample() return wrong results due to GapSamplingIterator operating on mutable row.
HiveTableScan make RDD with SpecificMutableRow and SchemaRDD.sample() will return GapSamplingIterator for iterating.
override def next(): T = {
val r = data.next()
advance
r
}
GapSamplingIterator.next() return the current underlying element and assigned it to r.
However if the underlying iterator is mutable row just like what HiveTableScan returned, underlying iterator and r will point to the same object.
After advance operation, we drop some underlying elments and it also changed r which is not expected. Then we return the wrong value different from initial r.
To fix this issue, the most direct way is to make HiveTableScan return mutable row with copy just like the initial commit that I have made. This solution will make HiveTableScan can not get the full advantage of reusable MutableRow, but it can make sample operation return correct result.
Further more, we need to investigate GapSamplingIterator.next() and make it can implement copy operation inside it. To achieve this, we should define every elements that RDD can store implement the function like cloneable and it will make huge change.
Author: Yanbo Liang <yanbohappy@gmail.com>
Closes#3827 from yanbohappy/spark-4963 and squashes the following commits:
0912ca0 [Yanbo Liang] code format keep
65c4e7c [Yanbo Liang] import file and clear annotation
55c7c56 [Yanbo Liang] better output of test case
cea7e2e [Yanbo Liang] SchemaRDD add copy operation before Sample operator
e840829 [Yanbo Liang] HiveTableScan return mutable row with copy
