Repository: spark Updated Branches: refs/heads/master 7f203a248 -> b5d8d9ba1
[SPARK-20506][DOCS] 2.2 migration guide Update ML guide for migration `2.1` -> `2.2` and the previous version migration guide section. ## How was this patch tested? Build doc locally. Author: Nick Pentreath <ni...@za.ibm.com> Closes #17996 from MLnick/SPARK-20506-2.2-migration-guide. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/b5d8d9ba Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/b5d8d9ba Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/b5d8d9ba Branch: refs/heads/master Commit: b5d8d9ba17d62167cfbacd5f6188a8b4a5b8a2be Parents: 7f203a2 Author: Nick Pentreath <ni...@za.ibm.com> Authored: Fri May 19 20:51:56 2017 +0200 Committer: Nick Pentreath <ni...@za.ibm.com> Committed: Fri May 19 20:51:56 2017 +0200 ---------------------------------------------------------------------- docs/ml-guide.md | 56 ++++++++++++++++++++++++++-------------- docs/ml-migration-guides.md | 29 +++++++++++++++++++++ 2 files changed, 66 insertions(+), 19 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/b5d8d9ba/docs/ml-guide.md ---------------------------------------------------------------------- diff --git a/docs/ml-guide.md b/docs/ml-guide.md index 9717619..362e883 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -26,7 +26,7 @@ The primary Machine Learning API for Spark is now the [DataFrame](sql-programmin * MLlib will still support the RDD-based API in `spark.mllib` with bug fixes. * MLlib will not add new features to the RDD-based API. * In the Spark 2.x releases, MLlib will add features to the DataFrames-based API to reach feature parity with the RDD-based API. -* After reaching feature parity (roughly estimated for Spark 2.2), the RDD-based API will be deprecated. +* After reaching feature parity (roughly estimated for Spark 2.3), the RDD-based API will be deprecated. * The RDD-based API is expected to be removed in Spark 3.0. *Why is MLlib switching to the DataFrame-based API?* @@ -66,41 +66,59 @@ To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 [^1]: To learn more about the benefits and background of system optimised natives, you may wish to watch Sam Halliday's ScalaX talk on [High Performance Linear Algebra in Scala](http://fommil.github.io/scalax14/#/). +# Highlights in 2.2 + +The list below highlights some of the new features and enhancements added to MLlib in the `2.2` +release of Spark: + +* `ALS` methods for _top-k_ recommendations for all users or items, matching the functionality + in `mllib` ([SPARK-19535](https://issues.apache.org/jira/browse/SPARK-19535)). Performance + was also improved for both `ml` and `mllib` + ([SPARK-11968](https://issues.apache.org/jira/browse/SPARK-11968) and + [SPARK-20587](https://issues.apache.org/jira/browse/SPARK-20587)) +* `Correlation` and `ChiSquareTest` stats functions for `DataFrames` + ([SPARK-19636](https://issues.apache.org/jira/browse/SPARK-19636) and + [SPARK-19635](https://issues.apache.org/jira/browse/SPARK-19635)) +* `FPGrowth` algorithm for frequent pattern mining + ([SPARK-14503](https://issues.apache.org/jira/browse/SPARK-14503)) +* `GLM` now supports the full `Tweedie` family + ([SPARK-18929](https://issues.apache.org/jira/browse/SPARK-18929)) +* `Imputer` feature transformer to impute missing values in a dataset + ([SPARK-13568](https://issues.apache.org/jira/browse/SPARK-13568)) +* `LinearSVC` for linear Support Vector Machine classification + ([SPARK-14709](https://issues.apache.org/jira/browse/SPARK-14709)) +* Logistic regression now supports constraints on the coefficients during training + ([SPARK-20047](https://issues.apache.org/jira/browse/SPARK-20047)) + # Migration guide MLlib is under active development. The APIs marked `Experimental`/`DeveloperApi` may change in future releases, and the migration guide below will explain all changes between releases. -## From 2.0 to 2.1 +## From 2.1 to 2.2 ### Breaking changes - -**Deprecated methods removed** -* `setLabelCol` in `feature.ChiSqSelectorModel` -* `numTrees` in `classification.RandomForestClassificationModel` (This now refers to the Param called `numTrees`) -* `numTrees` in `regression.RandomForestRegressionModel` (This now refers to the Param called `numTrees`) -* `model` in `regression.LinearRegressionSummary` -* `validateParams` in `PipelineStage` -* `validateParams` in `Evaluator` +There are no breaking changes. ### Deprecations and changes of behavior **Deprecations** -* [SPARK-18592](https://issues.apache.org/jira/browse/SPARK-18592): - Deprecate all Param setter methods except for input/output column Params for `DecisionTreeClassificationModel`, `GBTClassificationModel`, `RandomForestClassificationModel`, `DecisionTreeRegressionModel`, `GBTRegressionModel` and `RandomForestRegressionModel` +There are no deprecations. **Changes of behavior** -* [SPARK-17870](https://issues.apache.org/jira/browse/SPARK-17870): - Fix a bug of `ChiSqSelector` which will likely change its result. Now `ChiSquareSelector` use pValue rather than raw statistic to select a fixed number of top features. -* [SPARK-3261](https://issues.apache.org/jira/browse/SPARK-3261): - `KMeans` returns potentially fewer than k cluster centers in cases where k distinct centroids aren't available or aren't selected. -* [SPARK-17389](https://issues.apache.org/jira/browse/SPARK-17389): - `KMeans` reduces the default number of steps from 5 to 2 for the k-means|| initialization mode. - +* [SPARK-19787](https://issues.apache.org/jira/browse/SPARK-19787): + Default value of `regParam` changed from `1.0` to `0.1` for `ALS.train` method (marked `DeveloperApi`). + **Note** this does _not affect_ the `ALS` Estimator or Model, nor MLlib's `ALS` class. +* [SPARK-14772](https://issues.apache.org/jira/browse/SPARK-14772): + Fixed inconsistency between Python and Scala APIs for `Param.copy` method. +* [SPARK-11569](https://issues.apache.org/jira/browse/SPARK-11569): + `StringIndexer` now handles `NULL` values in the same way as unseen values. Previously an exception + would always be thrown regardless of the setting of the `handleInvalid` parameter. + ## Previous Spark versions Earlier migration guides are archived [on this page](ml-migration-guides.html). http://git-wip-us.apache.org/repos/asf/spark/blob/b5d8d9ba/docs/ml-migration-guides.md ---------------------------------------------------------------------- diff --git a/docs/ml-migration-guides.md b/docs/ml-migration-guides.md index 58c3747..687d7c8 100644 --- a/docs/ml-migration-guides.md +++ b/docs/ml-migration-guides.md @@ -7,6 +7,35 @@ description: MLlib migration guides from before Spark SPARK_VERSION_SHORT The migration guide for the current Spark version is kept on the [MLlib Guide main page](ml-guide.html#migration-guide). +## From 2.0 to 2.1 + +### Breaking changes + +**Deprecated methods removed** + +* `setLabelCol` in `feature.ChiSqSelectorModel` +* `numTrees` in `classification.RandomForestClassificationModel` (This now refers to the Param called `numTrees`) +* `numTrees` in `regression.RandomForestRegressionModel` (This now refers to the Param called `numTrees`) +* `model` in `regression.LinearRegressionSummary` +* `validateParams` in `PipelineStage` +* `validateParams` in `Evaluator` + +### Deprecations and changes of behavior + +**Deprecations** + +* [SPARK-18592](https://issues.apache.org/jira/browse/SPARK-18592): + Deprecate all Param setter methods except for input/output column Params for `DecisionTreeClassificationModel`, `GBTClassificationModel`, `RandomForestClassificationModel`, `DecisionTreeRegressionModel`, `GBTRegressionModel` and `RandomForestRegressionModel` + +**Changes of behavior** + +* [SPARK-17870](https://issues.apache.org/jira/browse/SPARK-17870): + Fix a bug of `ChiSqSelector` which will likely change its result. Now `ChiSquareSelector` use pValue rather than raw statistic to select a fixed number of top features. +* [SPARK-3261](https://issues.apache.org/jira/browse/SPARK-3261): + `KMeans` returns potentially fewer than k cluster centers in cases where k distinct centroids aren't available or aren't selected. +* [SPARK-17389](https://issues.apache.org/jira/browse/SPARK-17389): + `KMeans` reduces the default number of steps from 5 to 2 for the k-means|| initialization mode. + ## From 1.6 to 2.0 ### Breaking changes --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
