## What changes were proposed in this pull request?
PySpark ML Params setter code clean up.
For examples,
```setInputCol``` can be simplified from
```
self._set(inputCol=value)
return self
```
to:
```
return self._set(inputCol=value)
```
This is a pretty big sweeps, and we cleaned wherever possible.
## How was this patch tested?
Exist unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12749 from yanboliang/spark-14971.
## What changes were proposed in this pull request?
Per discussion on [https://github.com/apache/spark/pull/12604], this removes ML persistence for Python tuning (TrainValidationSplit, CrossValidator, and their Models) since they do not handle nesting easily. This support should be re-designed and added in the next release.
## How was this patch tested?
Removed unit test elements saving and loading the tuning algorithms, but kept tests to save and load their bestModel fields.
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#12782 from jkbradley/remove-python-tuning-saveload.
## What changes were proposed in this pull request?
support avgMetrics in CrossValidatorModel with Python
## How was this patch tested?
Doctest and `test_save_load` in `pyspark/ml/test.py`
[JIRA](https://issues.apache.org/jira/browse/SPARK-12810)
Author: Kai Jiang <jiangkai@gmail.com>
Closes#12464 from vectorijk/spark-12810.
## What changes were proposed in this pull request?
#11663 adds type conversion functionality for parameters in Pyspark. This PR find out the omissive ```Param``` that did not pass corresponding ```TypeConverter``` argument and fix them. After this PR, all params in pyspark/ml/ used ```TypeConverter```.
## How was this patch tested?
Existing tests.
cc jkbradley sethah
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12529 from yanboliang/typeConverter.
## What changes were proposed in this pull request?
This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes:
- ContinuousQuery
- Trigger
- ProcessingTime
in pyspark under `pyspark.sql.streaming`.
In addition, it contains the new methods added under:
- `DataFrameWriter`
a) `startStream`
b) `trigger`
c) `queryName`
- `DataFrameReader`
a) `stream`
- `DataFrame`
a) `isStreaming`
This PR doesn't contain all methods exposed for `ContinuousQuery`, for example:
- `exception`
- `sourceStatuses`
- `sinkStatus`
They may be added in a follow up.
This PR also contains some very minor doc fixes in the Scala side.
## How was this patch tested?
Python doc tests
TODO:
- [ ] verify Python docs look good
Author: Burak Yavuz <brkyvz@gmail.com>
Author: Burak Yavuz <burak@databricks.com>
Closes#12320 from brkyvz/stream-python.
## What changes were proposed in this pull request?
Param setters in python previously accessed the _paramMap directly to update values. The `_set` method now implements type checking, so it should be used to update all parameters. This PR eliminates all direct accesses to `_paramMap` besides the one in the `_set` method to ensure type checking happens.
Additional changes:
* [SPARK-13068](https://github.com/apache/spark/pull/11663) missed adding type converters in evaluation.py so those are done here
* An incorrect `toBoolean` type converter was used for StringIndexer `handleInvalid` param in previous PR. This is fixed here.
## How was this patch tested?
Existing unit tests verify that parameters are still set properly. No new functionality is actually added in this PR.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#11939 from sethah/SPARK-14104.
Currently, JavaWrapper is only a wrapper class for pipeline classes that have Params and JavaCallable is a separate mixin that provides methods to make Java calls. This change simplifies the class structure and to define the Java wrapper in a plain base class along with methods to make Java calls. Also, renames Java wrapper classes to better reflect their purpose.
Ran existing Python ml tests and generated documentation to test this change.
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#12304 from BryanCutler/pyspark-cleanup-JavaWrapper-SPARK-14472.
## What changes were proposed in this pull request?
Cleanups to documentation. No changes to code.
* GBT docs: Move Scala doc for private object GradientBoostedTrees to public docs for GBTClassifier,Regressor
* GLM regParam: needs doc saying it is for L2 only
* TrainValidationSplitModel: add .. versionadded:: 2.0.0
* Rename “_transformer_params_from_java” to “_transfer_params_from_java”
* LogReg Summary classes: “probability” col should not say “calibrated”
* LR summaries: coefficientStandardErrors —> document that intercept stderr comes last. Same for t,p-values
* approxCountDistinct: Document meaning of “rsd" argument.
* LDA: note which params are for online LDA only
## How was this patch tested?
Doc build
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#12266 from jkbradley/ml-doc-cleanups.
## What changes were proposed in this pull request?
https://issues.apache.org/jira/browse/SPARK-13786
Add save/load for Python CrossValidator/Model and TrainValidationSplit/Model.
## How was this patch tested?
Test with Python doctest.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#12020 from yinxusen/SPARK-13786.
## What changes were proposed in this pull request?
This patch adds type conversion functionality for parameters in Pyspark. A `typeConverter` field is added to the constructor of `Param` class. This argument is a function which converts values passed to this param to the appropriate type if possible. This is beneficial so that the params can fail at set time if they are given inappropriate values, but even more so because coherent error messages are now provided when Py4J cannot cast the python type to the appropriate Java type.
This patch also adds a `TypeConverters` class with factory methods for common type conversions. Most of the changes involve adding these factory type converters to existing params. The previous solution to this issue, `expectedType`, is deprecated and can be removed in 2.1.0 as discussed on the Jira.
## How was this patch tested?
Unit tests were added in python/pyspark/ml/tests.py to test parameter type conversion. These tests check that values that should be convertible are converted correctly, and that the appropriate errors are thrown when invalid values are provided.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#11663 from sethah/SPARK-13068-tc.
## What changes were proposed in this pull request?
The changes proposed were to add train-validation-split to pyspark.ml.tuning.
## How was the this patch tested?
This patch was tested through unit tests located in pyspark/ml/test.py.
This is my original work and I license it to Spark.
Author: JeremyNixon <jnixon2@gmail.com>
Closes#11335 from JeremyNixon/tvs_pyspark.
The current python ml params require cut-and-pasting the param setup and description between the class & ```__init__``` methods. Remove this possible case of errors & simplify use of custom params by adding a ```_copy_new_parent``` method to param so as to avoid cut and pasting (and cut and pasting at different indentation levels urgh).
Author: Holden Karau <holden@us.ibm.com>
Closes#10216 from holdenk/SPARK-10509-excessive-param-boiler-plate-code.
Extend CrossValidator with HasSeed in PySpark.
This PR replaces [https://github.com/apache/spark/pull/7997]
CC: yanboliang thunterdb mmenestret Would one of you mind taking a look? Thanks!
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Martin MENESTRET <mmenestret@ippon.fr>
Closes#10268 from jkbradley/pyspark-cv-seed.
* 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.
The new test uses CV to compare `maxIter=0` and `maxIter=1`, and validate on the evaluation result. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6572 from mengxr/SPARK-7432 and squashes the following commits:
c236bb8 [Xiangrui Meng] fix flacky cv doctest
This PR makes pipeline stages in Python copyable and hence simplifies some implementations. It also includes the following changes:
1. Rename `paramMap` and `defaultParamMap` to `_paramMap` and `_defaultParamMap`, respectively.
2. Accept a list of param maps in `fit`.
3. Use parent uid and name to identify param.
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6088 from mengxr/SPARK-7380 and squashes the following commits:
413c463 [Xiangrui Meng] remove unnecessary doc
4159f35 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380
611c719 [Xiangrui Meng] fix python style
68862b8 [Xiangrui Meng] update _java_obj initialization
927ad19 [Xiangrui Meng] fix ml/tests.py
0138fc3 [Xiangrui Meng] update feature transformers and fix a bug in RegexTokenizer
9ca44fb [Xiangrui Meng] simplify Java wrappers and add tests
c7d84ef [Xiangrui Meng] update ml/tests.py to test copy params
7e0d27f [Xiangrui Meng] merge master
46840fb [Xiangrui Meng] update wrappers
b6db1ed [Xiangrui Meng] update all self.paramMap to self._paramMap
46cb6ed [Xiangrui Meng] merge master
a163413 [Xiangrui Meng] fix style
1042e80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380
9630eae [Xiangrui Meng] fix Identifiable._randomUID
13bd70a [Xiangrui Meng] update ml/tests.py
64a536c [Xiangrui Meng] use _fit/_transform/_evaluate to simplify the impl
02abf13 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into copyable-python
66ce18c [Joseph K. Bradley] some cleanups before sending to Xiangrui
7431272 [Joseph K. Bradley] Rebased with master
Fixes bug with PySpark cvModel not having UID
Also made small PySpark fixes: Evaluator should inherit from Params. MockModel should inherit from Model.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5968 from jkbradley/pyspark-cv-uid and squashes the following commits:
57f13cd [Joseph K. Bradley] Made CrossValidatorModel call parent init in PySpark
Temporarily disable flaky doctest for CrossValidator. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#5962 from mengxr/disable-pyspark-cv-test and squashes the following commits:
5db7e5b [Xiangrui Meng] disable cv doctest
Since CrossValidator is a meta algorithm, we copy the implementation in Python. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#5926 from mengxr/SPARK-6940 and squashes the following commits:
6af181f [Xiangrui Meng] add TODOs
8285134 [Xiangrui Meng] update doc
060f7c3 [Xiangrui Meng] update doctest
acac727 [Xiangrui Meng] add keyword args
cdddecd [Xiangrui Meng] add CrossValidator in Python
as suggested by justinuang on #5601.
Author: Xiangrui Meng <meng@databricks.com>
Closes#5873 from mengxr/SPARK-7329 and squashes the following commits:
d08f9cf [Xiangrui Meng] simplify tests
b7a7b9b [Xiangrui Meng] simplify grid build
Author: Omede Firouz <ofirouz@palantir.com>
Author: Omede <omedefirouz@gmail.com>
Closes#5601 from oefirouz/paramgrid and squashes the following commits:
c9e2481 [Omede Firouz] Make test a doctest
9a8ce22 [Omede] Fix linter issues
8b8a6d2 [Omede Firouz] [SPARK-7022][PySpark][ML] Add ML.Tuning.ParamGridBuilder to PySpark