### What changes were proposed in this pull request?
Use Seq instead of Array in sc.parallelize, with reference types.
Remove usage of WrappedArray.
### Why are the changes needed?
These both enable building on Scala 2.13.
### Does this PR introduce any user-facing change?
None
### How was this patch tested?
Existing tests
Closes#26787 from srowen/SPARK-30158.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
This PR adds some extra documentation for the new Cogrouped map Pandas udfs. Specifically:
- Updated the usage guide for the new `COGROUPED_MAP` Pandas udfs added in https://github.com/apache/spark/pull/24981
- Updated the docstring for pandas_udf to include the COGROUPED_MAP type as suggested by HyukjinKwon in https://github.com/apache/spark/pull/25939Closes#26110 from d80tb7/SPARK-29126-cogroup-udf-usage-guide.
Authored-by: Chris Martin <chris@cmartinit.co.uk>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
To push the built jars to maven release repository, we need to remove the 'SNAPSHOT' tag from the version name.
Made the following changes in this PR:
* Update all the `3.0.0-SNAPSHOT` version name to `3.0.0-preview`
* Update the sparkR version number check logic to allow jvm version like `3.0.0-preview`
**Please note those changes were generated by the release script in the past, but this time since we manually add tags on master branch, we need to manually apply those changes too.**
We shall revert the changes after 3.0.0-preview release passed.
### Why are the changes needed?
To make the maven release repository to accept the built jars.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A
### What changes were proposed in this pull request?
To push the built jars to maven release repository, we need to remove the 'SNAPSHOT' tag from the version name.
Made the following changes in this PR:
* Update all the `3.0.0-SNAPSHOT` version name to `3.0.0-preview`
* Update the PySpark version from `3.0.0.dev0` to `3.0.0`
**Please note those changes were generated by the release script in the past, but this time since we manually add tags on master branch, we need to manually apply those changes too.**
We shall revert the changes after 3.0.0-preview release passed.
### Why are the changes needed?
To make the maven release repository to accept the built jars.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A
Closes#26243 from jiangxb1987/3.0.0-preview-prepare.
Lead-authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Co-authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
This PR proposes a few typos:
1. Sparks => Spark's
2. parallize => parallelize
3. doesnt => doesn't
Closes#26140 from plusplusjiajia/fix-typos.
Authored-by: Jiajia Li <jiajia.li@intel.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
### What changes were proposed in this pull request?
Scala 2.13 emits a deprecation warning for procedure-like declarations:
```
def foo() {
...
```
This is equivalent to the following, so should be changed to avoid a warning:
```
def foo(): Unit = {
...
```
### Why are the changes needed?
It will avoid about a thousand compiler warnings when we start to support Scala 2.13. I wanted to make the change in 3.0 as there are less likely to be back-ports from 3.0 to 2.4 than 3.1 to 3.0, for example, minimizing that downside to touching so many files.
Unfortunately, that makes this quite a big change.
### Does this PR introduce any user-facing change?
No behavior change at all.
### How was this patch tested?
Existing tests.
Closes#25968 from srowen/SPARK-29291.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Update scalatest, scalacheck, scopt, clapper, scala-parser-combinators to latest maintenance release that is also cross-published for Scala 2.13.
### Why are the changes needed?
To build in the future for Scala 2.13
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing tests
Closes#25967 from srowen/SPARK-29289.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
### What changes were proposed in this pull request?
- Remove SQLContext.createExternalTable and Catalog.createExternalTable, deprecated in favor of createTable since 2.2.0, plus tests of deprecated methods
- Remove HiveContext, deprecated in 2.0.0, in favor of `SparkSession.builder.enableHiveSupport`
- Remove deprecated KinesisUtils.createStream methods, plus tests of deprecated methods, deprecate in 2.2.0
- Remove deprecated MLlib (not Spark ML) linear method support, mostly utility constructors and 'train' methods, and associated docs. This includes methods in LinearRegression, LogisticRegression, Lasso, RidgeRegression. These have been deprecated since 2.0.0
- Remove deprecated Pyspark MLlib linear method support, including LogisticRegressionWithSGD, LinearRegressionWithSGD, LassoWithSGD
- Remove 'runs' argument in KMeans.train() method, which has been a no-op since 2.0.0
- Remove deprecated ChiSqSelector isSorted protected method
- Remove deprecated 'yarn-cluster' and 'yarn-client' master argument in favor of 'yarn' and deploy mode 'cluster', etc
Notes:
- I was not able to remove deprecated DataFrameReader.json(RDD) in favor of DataFrameReader.json(Dataset); the former was deprecated in 2.2.0, but, it is still needed to support Pyspark's .json() method, which can't use a Dataset.
- Looks like SQLContext.createExternalTable was not actually deprecated in Pyspark, but, almost certainly was meant to be? Catalog.createExternalTable was.
- I afterwards noted that the toDegrees, toRadians functions were almost removed fully in SPARK-25908, but Felix suggested keeping just the R version as they hadn't been technically deprecated. I'd like to revisit that. Do we really want the inconsistency? I'm not against reverting it again, but then that implies leaving SQLContext.createExternalTable just in Pyspark too, which seems weird.
- I *kept* LogisticRegressionWithSGD, LinearRegressionWithSGD, LassoWithSGD, RidgeRegressionWithSGD in Pyspark, though deprecated, as it is hard to remove them (still used by StreamingLogisticRegressionWithSGD?) and they are not fully removed in Scala. Maybe should not have been deprecated.
### Why are the changes needed?
Deprecated items are easiest to remove in a major release, so we should do so as much as possible for Spark 3. This does not target items deprecated 'recently' as of Spark 2.3, which is still 18 months old.
### Does this PR introduce any user-facing change?
Yes, in that deprecated items are removed from some public APIs.
### How was this patch tested?
Existing tests.
Closes#25684 from srowen/SPARK-28980.
Lead-authored-by: Sean Owen <sean.owen@databricks.com>
Co-authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
since method `labels` is already deprecated, we should update the examples and suites to turn off warings when compiling spark:
```
[warn] /Users/zrf/Dev/OpenSource/spark/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala:65: method labels in class StringIndexerModel is deprecated (since 3.0.0): `labels` is deprecated and will be removed in 3.1.0. Use `labelsArray` instead.
[warn] .setLabels(labelIndexer.labels)
[warn] ^
[warn] /Users/zrf/Dev/OpenSource/spark/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala:68: method labels in class StringIndexerModel is deprecated (since 3.0.0): `labels` is deprecated and will be removed in 3.1.0. Use `labelsArray` instead.
[warn] .setLabels(labelIndexer.labels)
[warn] ^
```
## How was this patch tested?
existing suites
Closes#25428 from zhengruifeng/del_stringindexer_labels_usage.
Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Now, DirectKafkaWordCount example is not support to visit kafka using kerberos authentication. Add Java/Scala DirectKerberizedKafkaWordCount.
## How was this patch tested?
Use cmd to visit kafka using kerberos authentication.
```
$ bin/run-example --files ${path}/kafka_jaas.conf \
--driver-java-options "-Djava.security.auth.login.config=${path}/kafka_jaas.conf" \
--conf "spark.executor.extraJavaOptions=-Djava.security.auth.login.config=./kafka_jaas.conf" \
streaming.DirectKerberizedKafkaWordCount broker1-host:port,broker2-host:port \
consumer-group topic1,topic2
```
Closes#25412 from hddong/example-streaming-support-kafka-kerberos.
Lead-authored-by: hongdd <jn_hdd@163.com>
Co-authored-by: hongdongdong <hongdongdong@cmss.chinamobile.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
This PR fixed typos in comments and replace the explicit type with '<>' for Java 8+.
## How was this patch tested?
Manually tested.
Closes#25338 from younggyuchun/younggyu.
Authored-by: younggyu chun <younggyuchun@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Implement `RobustScaler`
Since the transformation is quite similar to `StandardScaler`, I refactor the transform function so that it can be reused in both scalers.
## How was this patch tested?
existing and added tests
Closes#25160 from zhengruifeng/robust_scaler.
Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add docs for `SCALAR_ITER` Pandas UDF.
cc: WeichenXu123 HyukjinKwon
## How was this patch tested?
Tested example code manually.
Closes#24897 from mengxr/SPARK-28056.
Authored-by: Xiangrui Meng <meng@databricks.com>
Signed-off-by: Xiangrui Meng <meng@databricks.com>
## What changes were proposed in this pull request?
Usage: DirectKafkaWordCount <brokers> <topics>
--
<brokers> is a list of one or more Kafka brokers
<groupId> is a consumer group name to consume from topics
<topics> is a list of one or more kafka topics to consume from
## How was this patch tested?
N/A.
Please review https://spark.apache.org/contributing.html before opening a pull request.
Closes#24819 from cnZach/minor_DirectKafkaWordCount_UsageWithGroupId.
Authored-by: Yuexin Zhang <zach.yx.zhang@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
`spark.sql.execution.arrow.enabled` was added when we add PySpark arrow optimization.
Later, in the current master, SparkR arrow optimization was added and it's controlled by the same configuration `spark.sql.execution.arrow.enabled`.
There look two issues about this:
1. `spark.sql.execution.arrow.enabled` in PySpark was added from 2.3.0 whereas SparkR optimization was added 3.0.0. The stability is different so it's problematic when we change the default value for one of both optimization first.
2. Suppose users want to share some JVM by PySpark and SparkR. They are currently forced to use the optimization for all or none if the configuration is set globally.
This PR proposes two separate configuration groups for PySpark and SparkR about Arrow optimization:
- Deprecate `spark.sql.execution.arrow.enabled`
- Add `spark.sql.execution.arrow.pyspark.enabled` (fallback to `spark.sql.execution.arrow.enabled`)
- Add `spark.sql.execution.arrow.sparkr.enabled`
- Deprecate `spark.sql.execution.arrow.fallback.enabled`
- Add `spark.sql.execution.arrow.pyspark.fallback.enabled ` (fallback to `spark.sql.execution.arrow.fallback.enabled`)
Note that `spark.sql.execution.arrow.maxRecordsPerBatch` is used within JVM side for both.
Note that `spark.sql.execution.arrow.fallback.enabled` was added due to behaviour change. We don't need it in SparkR - SparkR side has the automatic fallback.
## How was this patch tested?
Manually tested and some unittests were added.
Closes#24700 from HyukjinKwon/separate-sparkr-arrow.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
move the script to a scripts directory based on discussion on https://github.com/apache/spark/pull/24731
## How was this patch tested?
ran script
Closes#24754 from tgravescs/SPARK-27897.
Authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Example GPU resource discovery script that can be used with Nvidia GPUs and passed into SPARK via spark.{driver/executor}.resource.gpu.discoveryScript
For example:
./bin/spark-shell --master yarn --deploy-mode client --driver-memory 1g --conf spark.yarn.am.memory=3g --num-executors 1 --executor-memory 1g --conf spark.driver.resource.gpu.count=2 --executor-cores 1 --conf spark.driver.resource.gpu.discoveryScript=/home/tgraves/workspace/tgravescs-spark/examples/src/main/resources/getGpusResources.sh --conf spark.executor.resource.gpu.count=1 --conf spark.task.resource.gpu.count=1 --conf spark.executor.resource.gpu.discoveryScript=/home/tgraves/workspace/tgravescs-spark/examples/src/main/resources/getGpusResources.sh
## How was this patch tested?
Manually tested local cluster mode and yarn mode. Tested on a node with 8 GPUs and one with 2 GPUs.
Closes#24731 from tgravescs/SPARK-27725.
Authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Don't use internal Spark logging in user examples, because users shouldn't / can't use it directly anyway. These examples already use println in some cases. Note that the usage in StreamingExamples is on purpose.
## How was this patch tested?
N/A
Closes#24649 from srowen/ExampleLog.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
`StructuredSessionization` comment contains duplicate 'add', I think it should be changed.
## How was this patch tested?
Exists UT.
Closes#24589 from beliefer/remove-duplicate-add-in-comment.
Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: Jiaan Geng <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Added method 'meanAveragePrecisionAt' k to RankingMetrics.
This branch is rebased with squashed commits from https://github.com/apache/spark/pull/24458
## How was this patch tested?
Added code in the existing test RankingMetricsSuite.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Closes#24543 from qb-tarushg/SPARK-27540-REBASE.
Authored-by: qb-tarushg <tarush.grover@quantumblack.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
### Background:
The data source option `pathGlobFilter` is introduced for Binary file format: https://github.com/apache/spark/pull/24354 , which can be used for filtering file names, e.g. reading `.png` files only while there is `.json` files in the same directory.
### Proposal:
Make the option `pathGlobFilter` as a general option for all file sources. The path filtering should happen in the path globbing on Driver.
### Motivation:
Filtering the file path names in file scan tasks on executors is kind of ugly.
### Impact:
1. The splitting of file partitions will be more balanced.
2. The metrics of file scan will be more accurate.
3. Users can use the option for reading other file sources.
## How was this patch tested?
Unit tests
Closes#24518 from gengliangwang/globFilter.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
This PR avoids usage of reflective calls in Scala. It removes the import that suppresses the warnings and rewrites code in small ways to avoid accessing methods that aren't technically accessible.
## How was this patch tested?
Existing tests.
Closes#24463 from srowen/SPARK-27571.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Adds the Spark ML Interaction transformer to PySpark
## How was this patch tested?
- Added Python doctest
- Ran the newly added example code
- Manually confirmed that a PipelineModel that contains an Interaction transformer can now be loaded in PySpark
Closes#24426 from Andrew-Crosby/pyspark-interaction-transformer.
Lead-authored-by: Andrew-Crosby <37139900+Andrew-Crosby@users.noreply.github.com>
Co-authored-by: Andrew-Crosby <andrew.crosby@autotrader.co.uk>
Signed-off-by: Bryan Cutler <cutlerb@gmail.com>
## What changes were proposed in this pull request?
- Adds persistent volume integration tests
- Adds a custom tag to the test to exclude it if it is run against a cloud backend.
- Assumes default fs type for the host, AFAIK that is ext4.
## How was this patch tested?
Manually run the tests against minikube as usual:
```
[INFO] --- scalatest-maven-plugin:1.0:test (integration-test) spark-kubernetes-integration-tests_2.12 ---
Discovery starting.
Discovery completed in 192 milliseconds.
Run starting. Expected test count is: 16
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark with Python2 to test a pyfiles example
- Run PySpark with Python3 to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- Test PVs with local storage
```
Closes#23514 from skonto/pvctests.
Authored-by: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Signed-off-by: shane knapp <incomplete@gmail.com>
This is a very low level error.
Closes#24153 from jiangruocheng/master.
Authored-by: Ruocheng Jiang <jiangruocheng@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This pr adds 2 maven properties to help us upgrade the built-in Hive.
| Property Name | Default | In future |
| ------ | ------ | ------ |
| hive.classifier | (none) | core |
| hive.parquet.group | com.twitter | org.apache.parquet |
## How was this patch tested?
existing tests
Closes#23996 from wangyum/add_2_maven_properties.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add 'Recall_at_k' metric to RankingMetrics
## How was this patch tested?
Add test to RankingMetricsSuite.
Closes#23881 from masa3141/SPARK-26981.
Authored-by: masa3141 <masahiro@kazama.tv>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
These builtin typed aggregate functions are not very useful:
1. users can just call the untyped ones and turn the resulting dataframe to a dataset. It has better performance.
2. the typed aggregate functions have subtle different behaviors regarding empty input.
I think we should get rid of these builtin typed agg functions and suggest users to use the untyped ones.
However, these functions are still useful as a demo of the `Aggregator` API, so I copied them to the example module.
## How was this patch tested?
N/A
Closes#23763 from cloud-fan/example.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
In the PR, I propose to use `System.nanoTime()` instead of `System.currentTimeMillis()` in measurements of time intervals.
`System.currentTimeMillis()` returns current wallclock time and will follow changes to the system clock. Thus, negative wallclock adjustments can cause timeouts to "hang" for a long time (until wallclock time has caught up to its previous value again). This can happen when ntpd does a "step" after the network has been disconnected for some time. The most canonical example is during system bootup when DHCP takes longer than usual. This can lead to failures that are really hard to understand/reproduce. `System.nanoTime()` is guaranteed to be monotonically increasing irrespective of wallclock changes.
## How was this patch tested?
By existing test suites.
Closes#23727 from MaxGekk/system-nanotime.
Lead-authored-by: Maxim Gekk <max.gekk@gmail.com>
Co-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Make .unpersist(), .destroy() non-blocking by default and adjust callers to request blocking only where important.
This also adds an optional blocking argument to Pyspark's RDD.unpersist(), which never had one.
## How was this patch tested?
Existing tests.
Closes#23685 from srowen/SPARK-26771.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add python example for Power Iteration Clustering in spark.ml
## How was this patch tested?
Manually tested
Closes#22996 from huaxingao/spark-25997.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Misc code cleanup from lgtm.com analysis. See comments below for details.
## How was this patch tested?
Existing tests.
Closes#23571 from srowen/SPARK-26640.
Lead-authored-by: Sean Owen <sean.owen@databricks.com>
Co-authored-by: Hyukjin Kwon <gurwls223@apache.org>
Co-authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR addresses warning messages in Java files reported at [lgtm.com](https://lgtm.com).
[lgtm.com](https://lgtm.com) provides automated code review of Java/Python/JavaScript files for OSS projects. [Here](https://lgtm.com/projects/g/apache/spark/alerts/?mode=list&severity=warning) are warning messages regarding Apache Spark project.
This PR addresses the following warnings:
- Result of multiplication cast to wider type
- Implicit narrowing conversion in compound assignment
- Boxed variable is never null
- Useless null check
NOTE: `Potential input resource leak` looks false positive for now.
## How was this patch tested?
Existing UTs
Closes#23420 from kiszk/SPARK-26508.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
…leAccumulator
## What changes were proposed in this pull request?
This PR implements metric sources for LongAccumulator and DoubleAccumulator, such that a user can register these accumulators easily and have their values be reported by the driver's metric namespace.
## How was this patch tested?
Unit tests, and manual tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Closes#23242 from abellina/SPARK-26285_accumulator_source.
Lead-authored-by: Alessandro Bellina <abellina@yahoo-inc.com>
Co-authored-by: Alessandro Bellina <abellina@oath.com>
Co-authored-by: Alessandro Bellina <abellina@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
## What changes were proposed in this pull request?
Print `import org.apache.spark.sql.Row` of `SparkSQLExample.scala` on the `programmatic_schema` example to fix the `not found: value Row` error on it.
```
scala> val rowRDD = peopleRDD.map(_.split(",")).map(attributes => Row(attributes(0), attributes(1).trim))
<console>:28: error: not found: value Row
val rowRDD = peopleRDD.map(_.split(",")).map(attributes => Row(attributes(0), attributes(1).trim))
```
## How was this patch tested?
NA
Closes#23326 from kjmrknsn/fix-sql-getting-started.
Authored-by: Keiji Yoshida <kjmrknsn@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Follow up style fixes to PIC in R; see #23072
## How was this patch tested?
Existing tests.
Closes#23292 from srowen/SPARK-19827.2.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add PowerIterationCluster (PIC) in R
## How was this patch tested?
Add test case
Closes#23072 from huaxingao/spark-19827.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
follow-up PR for SPARK-24207 to fix code style problems
Closes#23256 from huaxingao/spark-24207-cnt.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
We have deprecated `OneHotEncoder` at Spark 2.3.0 and introduced `OneHotEncoderEstimator`. At 3.0.0, we remove deprecated `OneHotEncoder` and rename `OneHotEncoderEstimator` to `OneHotEncoder`.
TODO: According to ML migration guide, we need to keep `OneHotEncoderEstimator` as an alias after renaming. This is not done at this patch in order to facilitate review.
## How was this patch tested?
Existing tests.
Closes#23100 from viirya/remove_one_hot_encoder.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
## What changes were proposed in this pull request?
This PR makes Spark's default Scala version as 2.12, and Scala 2.11 will be the alternative version. This implies that Scala 2.12 will be used by our CI builds including pull request builds.
We'll update the Jenkins to include a new compile-only jobs for Scala 2.11 to ensure the code can be still compiled with Scala 2.11.
## How was this patch tested?
existing tests
Closes#22967 from dbtsai/scala2.12.
Authored-by: DB Tsai <d_tsai@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
…. Other related changes to get JDK 11 working, to test
## What changes were proposed in this pull request?
- Access `sun.misc.Cleaner` (Java 8) and `jdk.internal.ref.Cleaner` (JDK 9+) by reflection (note: the latter only works if illegal reflective access is allowed)
- Access `sun.misc.Unsafe.invokeCleaner` in Java 9+ instead of `sun.misc.Cleaner` (Java 8)
In order to test anything on JDK 11, I also fixed a few small things, which I include here:
- Fix minor JDK 11 compile issues
- Update scala plugin, Jetty for JDK 11, to facilitate tests too
This doesn't mean JDK 11 tests all pass now, but lots do. Note also that the JDK 9+ solution for the Cleaner has a big caveat.
## How was this patch tested?
Existing tests. Manually tested JDK 11 build and tests, and tests covering this change appear to pass. All Java 8 tests should still pass, but this change alone does not achieve full JDK 11 compatibility.
Closes#22993 from srowen/SPARK-24421.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Using `computeCost` for evaluating a model is a very poor approach. We should advice the users to a better approach which is available, ie. using the `ClusteringEvaluator` to evaluate their models. The PR updates the examples for `BisectingKMeans` in order to do that.
## How was this patch tested?
running examples
Closes#22786 from mgaido91/SPARK-25764.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
## What changes were proposed in this pull request?
Our current doc does not explain how we are passing the data source specific options to the underlying data source. According to [the review comment](https://github.com/apache/spark/pull/22622#discussion_r222911529), this PR aims to add more detailed information and examples
## How was this patch tested?
Manual.
Closes#22801 from dongjoon-hyun/SPARK-25656.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
