This is just some small glue code to actually make use of the
AMPLAB_JENKINS_BUILD_TOOL switch. As far as I can tell, we actually
don't currently use the Maven support in the tool even though it exists.
This patch switches to Maven when the PR title contains "test-maven".
There are a few small other pieces of cleanup in the patch as well.
Author: Patrick Wendell <patrick@databricks.com>
Closes#7878 from pwendell/maven-tests.
JIRA Issue: https://issues.apache.org/jira/browse/SPARK-10184
Change `cumWeight > target` to `cumWeight >= target` in `RangePartitioner.determineBounds` method to make the output partitions more balanced.
Author: ihainan <ihainan72@gmail.com>
Closes#8397 from ihainan/opt_for_rangepartitioner.
* The example code was added in 1.2, before `createDataFrame`. This PR switches to `createDataFrame`. Java code still uses JavaBean.
* assume `sqlContext` is available
* fix some minor issues from previous code review
jkbradley srowen feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8518 from mengxr/SPARK-10331.
* replace `ML Dataset` by `DataFrame` to unify the abstraction
* ML algorithms -> pipeline components to describe the main concept
* remove Scala API doc links from the main guide
* `Section Title` -> `Section tile` to be consistent with other section titles in MLlib guide
* modified lines break at 100 chars or periods
jkbradley feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8517 from mengxr/SPARK-10348.
This PR includes the following changes:
- Add `LocalNodeTest` for local operator tests and add unit tests for FilterNode and ProjectNode.
- Add `LimitNode` and `UnionNode` and their unit tests to show how to use `LocalNodeTest`. (SPARK-9991, SPARK-9993)
Author: zsxwing <zsxwing@gmail.com>
Closes#8464 from zsxwing/local-execution.
This fixes the problem that scanning partitioned table causes driver have a high memory pressure and takes down the cluster. Also, with this fix, we will be able to correctly show the query plan of a query consuming partitioned tables.
https://issues.apache.org/jira/browse/SPARK-10339https://issues.apache.org/jira/browse/SPARK-10334
Finally, this PR squeeze in a "quick fix" for SPARK-10301. It is not a real fix, but it just throw a better error message to let user know what to do.
Author: Yin Huai <yhuai@databricks.com>
Closes#8515 from yhuai/partitionedTableScan.
SparkHadoopUtil contains methods that use reflection to work around TaskAttemptContext binary incompatibilities between Hadoop 1.x and 2.x. We should use these methods in more places.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#8499 from JoshRosen/use-hadoop-reflection-in-more-places.
When I tested the latest version of spark with exclamation mark, I got some errors. Then I reseted the spark version and found that commit id "a2409d1c8e8ddec04b529ac6f6a12b5993f0eeda" brought the bug. With jline version changing from 0.9.94 to 2.12 after this commit, exclamation mark would be treated as a special character in ConsoleReader.
Author: wangwei <wangwei82@huawei.com>
Closes#8420 from small-wang/jline-SPARK-10226.
Actually using this API requires access to a lot of classes that we might make private by accident. I've added some tests to prevent this.
Author: Michael Armbrust <michael@databricks.com>
Closes#8516 from marmbrus/extraStrategiesTests.
This PR introduces a direct write API for testing Parquet. It's a DSL flavored version of the [`writeDirect` method] [1] comes with parquet-avro testing code. With this API, it's much easier to construct arbitrary Parquet structures. It's especially useful when adding regression tests for various compatibility corner cases.
Sample usage of this API can be found in the new test case added in `ParquetThriftCompatibilitySuite`.
[1]: https://github.com/apache/parquet-mr/blob/apache-parquet-1.8.1/parquet-avro/src/test/java/org/apache/parquet/avro/TestArrayCompatibility.java#L945-L972
Author: Cheng Lian <lian@databricks.com>
Closes#8454 from liancheng/spark-10289/parquet-testing-direct-write-api.
Add subset and transform
Also reorganize `[` & `[[` to subset instead of select
Note: for transform, transform is very similar to mutate. Spark doesn't seem to replace existing column with the name in mutate (ie. `mutate(df, age = df$age + 2)` - returned DataFrame has 2 columns with the same name 'age'), so therefore not doing that for now in transform.
Though it is clearly stated it should replace column with matching name (should I open a JIRA for mutate/transform?)
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#8503 from felixcheung/rsubset_transform.
After this PR, In/InSet/ArrayContain will return null if value is null, instead of false. They also will return null even if there is a null in the set/array.
Author: Davies Liu <davies@databricks.com>
Closes#8492 from davies/fix_in.
This PR updates the MLlib user guide and adds migration guide for 1.4->1.5.
* merge migration guide for `spark.mllib` and `spark.ml` packages
* remove dependency section from `spark.ml` guide
* move the paragraph about `spark.mllib` and `spark.ml` to the top and recommend `spark.ml`
* move Sam's talk to footnote to make the section focus on dependencies
Minor changes to code examples and other wording will be in a separate PR.
jkbradley srowen feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#8498 from mengxr/SPARK-9671.
`fitIntercept` is a command line option but not set in the main program.
dbtsai
Author: Shuo Xiang <sxiang@pinterest.com>
Closes#8510 from coderxiang/intercept and squashes the following commits:
57c9b7d [Shuo Xiang] fix not being able to set intercept in LR example
This change aims at speeding up the dev cycle a little bit, by making
sure that all tests behave the same w.r.t. where the code to be tested
is loaded from. Namely, that means that tests don't rely on the assembly
anymore, rather loading all needed classes from the build directories.
The main change is to make sure all build directories (classes and test-classes)
are added to the classpath of child processes when running tests.
YarnClusterSuite required some custom code since the executors are run
differently (i.e. not through the launcher library, like standalone and
Mesos do).
I also found a couple of tests that could leak a SparkContext on failure,
and added code to handle those.
With this patch, it's possible to run the following command from a clean
source directory and have all tests pass:
mvn -Pyarn -Phadoop-2.4 -Phive-thriftserver install
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#7629 from vanzin/SPARK-9284.
This commit fixes an issue where the public SQL `Row` class did not override `hashCode`, causing it to violate the hashCode() + equals() contract. To fix this, I simply ported the `hashCode` implementation from the 1.4.x version of `Row`.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#8500 from JoshRosen/SPARK-10325 and squashes the following commits:
51ffea1 [Josh Rosen] Override hashCode() for public Row.
This is based on davies comment on SPARK-8952 which suggests to only call normalizePath() when path starts with '~'
Author: Luciano Resende <lresende@apache.org>
Closes#8343 from lresende/SPARK-8952.
Current port number is fixed as default (7337) in test, this will introduce port contention exception, better to change to a random number in unit test.
squito , seems you're author of this unit test, mind taking a look at this fix? Thanks a lot.
```
[info] - executor state kept across NM restart *** FAILED *** (597 milliseconds)
[info] org.apache.hadoop.service.ServiceStateException: java.net.BindException: Address already in use
[info] at org.apache.hadoop.service.ServiceStateException.convert(ServiceStateException.java:59)
[info] at org.apache.hadoop.service.AbstractService.init(AbstractService.java:172)
[info] at org.apache.spark.network.yarn.YarnShuffleServiceSuite$$anonfun$1.apply$mcV$sp(YarnShuffleServiceSuite.scala:72)
[info] at org.apache.spark.network.yarn.YarnShuffleServiceSuite$$anonfun$1.apply(YarnShuffleServiceSuite.scala:70)
[info] at org.apache.spark.network.yarn.YarnShuffleServiceSuite$$anonfun$1.apply(YarnShuffleServiceSuite.scala:70)
[info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
[info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
[info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
[info] at org.scalatest.Transformer.apply(Transformer.scala:22)
[info] at org.scalatest.Transformer.apply(Transformer.scala:20)
[info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
[info] at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:42)
...
```
Author: jerryshao <sshao@hortonworks.com>
Closes#8502 from jerryshao/avoid-hardcode-port.
Remove obsolete warning about dynamic allocation not working with cached RDDs
See discussion in https://issues.apache.org/jira/browse/SPARK-10295
Author: Sean Owen <sowen@cloudera.com>
Closes#8489 from srowen/SPARK-10295.
* Added isLargerBetter() method to Pyspark Evaluator to match the Scala version.
* JavaEvaluator delegates isLargerBetter() to underlying Scala object.
* Added check for isLargerBetter() in CrossValidator to determine whether to use argmin or argmax.
* Added test cases for where smaller is better (RMSE) and larger is better (R-Squared).
(This contribution is my original work and that I license the work to the project under Sparks' open source license)
Author: noelsmith <mail@noelsmith.com>
Closes#8399 from noel-smith/pyspark-rmse-xval-fix.
* Adds user guide for `LinearRegressionSummary`
* Fixes unresolved issues in #8197
CC jkbradley mengxr
Author: Feynman Liang <fliang@databricks.com>
Closes#8491 from feynmanliang/SPARK-9905.
I added a small note about the different types of evaluator and the metrics used.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#8304 from MechCoder/multiclass_evaluator.
JoshRosen we'd like to check the SparkR source code with the `dev/lint-r` script on the Jenkins. I tried to incorporate the script into `dev/run-test.py`. Could you review it when you have time?
shivaram I modified `dev/lint-r` and `dev/lint-r.R` to install lintr package into a local directory(`R/lib/`) and to exit with a lint status. Could you review it?
- [[SPARK-8505] Add settings to kick `lint-r` from `./dev/run-test.py` - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-8505)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#7883 from yu-iskw/SPARK-8505.
Having sizeInBytes in HadoopFsRelation to enable broadcast join.
cc marmbrus
Author: Davies Liu <davies@databricks.com>
Closes#8490 from davies/sizeInByte.
https://issues.apache.org/jira/browse/SPARK-10287
After porting json to HadoopFsRelation, it seems hard to keep the behavior of picking up new files automatically for JSON. This PR removes this behavior, so JSON is consistent with others (ORC and Parquet).
Author: Yin Huai <yhuai@databricks.com>
Closes#8469 from yhuai/jsonRefresh.
* Adds user guide for ml.feature.StopWordsRemovers, ran code examples on my machine
* Cleans up scaladocs for public methods
* Adds test for Java compatibility
* Follow up Python user guide code example is tracked by SPARK-10249
Author: Feynman Liang <fliang@databricks.com>
Closes#8436 from feynmanliang/SPARK-10230.
jira: https://issues.apache.org/jira/browse/SPARK-9901
The jira covers only the document update. I can further provide example code for QR (like the ones for SVD and PCA) in a separate PR.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#8462 from hhbyyh/qrDoc.
https://issues.apache.org/jira/browse/SPARK-10315
this parameter is not used any longer and there is some mistake in the current document , should be 'akka.remote.watch-failure-detector.threshold'
Author: CodingCat <zhunansjtu@gmail.com>
Closes#8483 from CodingCat/SPARK_10315.
`GeneralizedLinearModel` creates a cached RDD when building a model. It's inconvenient, since these RDDs flood the memory when building several models in a row, so useful data might get evicted from the cache.
The proposed solution is to always cache the dataset & remove the warning. There's a caveat though: input dataset gets evaluated twice, in line 270 when fitting `StandardScaler` for the first time, and when running optimizer for the second time. So, it might worth to return removed warning.
Another possible solution is to disable caching entirely & return removed warning. I don't really know what approach is better.
Author: Vyacheslav Baranov <slavik.baranov@gmail.com>
Closes#8395 from SlavikBaranov/SPARK-10182.
* Replaces instances of `Lists.newArrayList` with `Arrays.asList`
* Replaces `commons.lang.StringUtils` over `com.google.collections.Strings`
* Replaces `List` interface over `ArrayList` implementations
This PR along with #8445#8446#8447 completely removes all `com.google.collections.Lists` dependencies within mllib's Java tests.
Author: Feynman Liang <fliang@databricks.com>
Closes#8451 from feynmanliang/SPARK-10257.
Fix for [JavaConverters.asJavaListConverter](http://www.scala-lang.org/api/2.10.5/index.html#scala.collection.JavaConverters$) being removed in 2.11.7 and hence the build fails with the 2.11 profile enabled. Tested with the default 2.10 and 2.11 profiles. BUILD SUCCESS in both cases.
Build for 2.10:
./build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.7.1 -DskipTests clean install
and 2.11:
./dev/change-scala-version.sh 2.11
./build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.7.1 -Dscala-2.11 -DskipTests clean install
Author: Jacek Laskowski <jacek@japila.pl>
Closes#8479 from jaceklaskowski/SPARK-9613-hotfix.
* Replaces `com.google.common` dependencies with `java.util.Arrays`
* Small clean up in `JavaNormalizerSuite`
Author: Feynman Liang <fliang@databricks.com>
Closes#8445 from feynmanliang/SPARK-10254.
PySpark DataFrameReader should could accept an RDD of Strings (like the Scala version does) for JSON, rather than only taking a path.
If this PR is merged, it should be duplicated to cover the other input types (not just JSON).
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8444 from yanboliang/spark-9964.
