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author | Xiangrui Meng <meng@databricks.com> | 2015-02-19 18:06:16 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-02-19 18:06:16 -0800 |
commit | 0cfd2cebde0b7fac3779eda80d6e42223f8a3d9f (patch) | |
tree | 36bdfdec69a205b85f7b85697c36abf2044d9ff5 /docs/mllib-clustering.md | |
parent | 6bddc40353057a562c78e75c5549c79a0d7d5f8b (diff) | |
download | spark-0cfd2cebde0b7fac3779eda80d6e42223f8a3d9f.tar.gz spark-0cfd2cebde0b7fac3779eda80d6e42223f8a3d9f.tar.bz2 spark-0cfd2cebde0b7fac3779eda80d6e42223f8a3d9f.zip |
[SPARK-5900][MLLIB] make PIC and FPGrowth Java-friendly
In the previous version, PIC stores clustering assignments as an `RDD[(Long, Int)]`. This is mapped to `RDD<Tuple2<Object, Object>>` in Java and hence Java users have to cast types manually. We should either create a new method called `javaAssignments` that returns `JavaRDD[(java.lang.Long, java.lang.Int)]` or wrap the result pair in a class. I chose the latter approach in this PR. Now assignments are stored as an `RDD[Assignment]`, where `Assignment` is a class with `id` and `cluster`.
Similarly, in FPGrowth, the frequent itemsets are stored as an `RDD[(Array[Item], Long)]`, which is mapped to `RDD<Tuple2<Object, Object>>`. Though we provide a "Java-friendly" method `javaFreqItemsets` that returns `JavaRDD[(Array[Item], java.lang.Long)]`. It doesn't really work because `Array[Item]` is mapped to `Object` in Java. So in this PR I created a class `FreqItemset` to wrap the results. It has `items` and `freq`, as well as a `javaItems` method that returns `List<Item>` in Java.
I'm not certain that the names I chose are proper: `Assignment`/`id`/`cluster` and `FreqItemset`/`items`/`freq`. Please let me know if there are better suggestions.
CC: jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes #4695 from mengxr/SPARK-5900 and squashes the following commits:
865b5ca [Xiangrui Meng] make Assignment serializable
cffa96e [Xiangrui Meng] fix test
9c0e590 [Xiangrui Meng] remove unused Tuple2
1b9db3d [Xiangrui Meng] make PIC and FPGrowth Java-friendly
Diffstat (limited to 'docs/mllib-clustering.md')
-rw-r--r-- | docs/mllib-clustering.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md index 6e46a47338..0b6db4fcb7 100644 --- a/docs/mllib-clustering.md +++ b/docs/mllib-clustering.md @@ -314,8 +314,8 @@ val pic = new PowerIteartionClustering() .setMaxIterations(20) val model = pic.run(similarities) -model.assignments.foreach { case (vertexId, clusterId) => - println(s"$vertexId -> $clusterId") +model.assignments.foreach { a => + println(s"${a.id} -> ${a.cluster}") } {% endhighlight %} @@ -349,8 +349,8 @@ PowerIterationClustering pic = new PowerIterationClustering() .setMaxIterations(10); PowerIterationClusteringModel model = pic.run(similarities); -for (Tuple2<Object, Object> assignment: model.assignments().toJavaRDD().collect()) { - System.out.println(assignment._1() + " -> " + assignment._2()); +for (PowerIterationClustering.Assignment a: model.assignments().toJavaRDD().collect()) { + System.out.println(a.id() + " -> " + a.cluster()); } {% endhighlight %} </div> |