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The following commit(s) were added to refs/heads/branch-4.3 by this push:
new e8969b4ecff5 [SPARK-58758][DOC] Remove the stale Highlights in 3.0
section from the ML guide
e8969b4ecff5 is described below
commit e8969b4ecff52f31defb0f22b3d686fe7379bc54
Author: Uros Bojanic <[email protected]>
AuthorDate: Thu Aug 13 15:22:58 2026 +0000
[SPARK-58758][DOC] Remove the stale Highlights in 3.0 section from the ML
guide
### What changes were proposed in this pull request?
Removes the `Highlights in 3.0` section from `docs/ml-guide.md`, and
rewrites a sentence that still described DataFrame-based API feature parity as
future work in the Spark 2.x releases.
### Why are the changes needed?
Both are stale on the current codebase. The guide keeps no equivalent
`Highlights` section for 1.x or 2.x, so dropping superseded highlights is the
established practice: SPARK-30934 replaced the 2.3 highlights with the 3.0 ones
rather than accumulating them. The `Migration Guide` section immediately below
already points readers to the archived migration guide, and the 3.0 features
remain documented on their own pages, so no user-facing information is lost.
Feature parity between the D [...]
### Does this PR introduce _any_ user-facing change?
No, other than the updated documentation.
### How was this patch tested?
Documentation only. No internal doc links point at the removed section's
anchor, and the surrounding sections remain well-formed after the deletion.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code (Opus 4.8)
Closes #57987 from uros-b/doc-mlguide-stale-highlights.
Authored-by: Uros Bojanic <[email protected]>
Signed-off-by: Uros Bojanic <[email protected]>
(cherry picked from commit 99b57f97330411f32de527ca37e161574274ad43)
Signed-off-by: Uros Bojanic <[email protected]>
---
docs/ml-guide.md | 28 +---------------------------
1 file changed, 1 insertion(+), 27 deletions(-)
diff --git a/docs/ml-guide.md b/docs/ml-guide.md
index 64c469d906e3..34c7e7d72491 100644
--- a/docs/ml-guide.md
+++ b/docs/ml-guide.md
@@ -40,7 +40,7 @@ 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.
+* MLlib added features to the DataFrame-based API in the Spark 2.x releases,
reaching feature parity with the RDD-based API.
*Why is MLlib switching to the DataFrame-based API?*
@@ -74,32 +74,6 @@ To use MLlib in Python, you will need
[NumPy](http://www.numpy.org) version 1.23
[^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 3.0
-
-The list below highlights some of the new features and enhancements added to
MLlib in the `3.0`
-release of Spark:
-
-* Multiple columns support was added to `Binarizer`
([SPARK-23578](https://issues.apache.org/jira/browse/SPARK-23578)),
`StringIndexer`
([SPARK-11215](https://issues.apache.org/jira/browse/SPARK-11215)),
`StopWordsRemover`
([SPARK-29808](https://issues.apache.org/jira/browse/SPARK-29808)) and PySpark
`QuantileDiscretizer`
([SPARK-22796](https://issues.apache.org/jira/browse/SPARK-22796)).
-* Tree-Based Feature Transformation was added
-([SPARK-13677](https://issues.apache.org/jira/browse/SPARK-13677)).
-* Two new evaluators `MultilabelClassificationEvaluator`
([SPARK-16692](https://issues.apache.org/jira/browse/SPARK-16692)) and
`RankingEvaluator`
([SPARK-28045](https://issues.apache.org/jira/browse/SPARK-28045)) were added.
-* Sample weights support was added in `DecisionTreeClassifier/Regressor`
([SPARK-19591](https://issues.apache.org/jira/browse/SPARK-19591)),
`RandomForestClassifier/Regressor`
([SPARK-9478](https://issues.apache.org/jira/browse/SPARK-9478)),
`GBTClassifier/Regressor`
([SPARK-9612](https://issues.apache.org/jira/browse/SPARK-9612)),
`MulticlassClassificationEvaluator`
([SPARK-24101](https://issues.apache.org/jira/browse/SPARK-24101)),
`RegressionEvaluator` ([SPARK-24102](https://issues.a [...]
-* R API for `PowerIterationClustering` was added
-([SPARK-19827](https://issues.apache.org/jira/browse/SPARK-19827)).
-* Added Spark ML listener for tracking ML pipeline status
-([SPARK-23674](https://issues.apache.org/jira/browse/SPARK-23674)).
-* Fit with validation set was added to Gradient Boosted Trees in Python
-([SPARK-24333](https://issues.apache.org/jira/browse/SPARK-24333)).
-* [`RobustScaler`](ml-features.html#robustscaler) transformer was added
-([SPARK-28399](https://issues.apache.org/jira/browse/SPARK-28399)).
-* [`Factorization
Machines`](ml-classification-regression.html#factorization-machines) classifier
and regressor were added
-([SPARK-29224](https://issues.apache.org/jira/browse/SPARK-29224)).
-* Gaussian Naive Bayes Classifier
([SPARK-16872](https://issues.apache.org/jira/browse/SPARK-16872)) and
Complement Naive Bayes Classifier
([SPARK-29942](https://issues.apache.org/jira/browse/SPARK-29942)) were added.
-* ML function parity between Scala and Python
-([SPARK-28958](https://issues.apache.org/jira/browse/SPARK-28958)).
-* `predictRaw` is made public in all the Classification models.
`predictProbability` is made public in all the Classification models except
`LinearSVCModel`
-([SPARK-30358](https://issues.apache.org/jira/browse/SPARK-30358)).
-
# Migration Guide
The migration guide is now archived [on this page](ml-migration-guide.html).
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