Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8279#discussion_r37315896
--- Diff: docs/mllib-frequent-pattern-mining.md ---
@@ -41,21 +41,23 @@ MLlib's FP-growth implementation takes the following
(hyper-)parameters:
[`FPGrowth`](api/scala/index.html#org.apache.spark.mllib.fpm.FPGrowth)
implements the
FP-growth algorithm.
-It take a `JavaRDD` of transactions, where each transaction is an
`Iterable` of items of a generic type.
+It take a `RDD` of transactions, where each transaction is an `Array` of
items of a generic type.
Calling `FPGrowth.run` with transactions returns an
[`FPGrowthModel`](api/scala/index.html#org.apache.spark.mllib.fpm.FPGrowthModel)
that stores the frequent itemsets with their frequencies.
{% highlight scala %}
import org.apache.spark.rdd.RDD
-import org.apache.spark.mllib.fpm.{FPGrowth, FPGrowthModel}
+import org.apache.spark.mllib.fpm.FPGrowth
-val transactions: RDD[Array[String]] = ...
+val data = sc.textFile("data/mllib/sample_fpgrowth.txt")
-val fpg = new FPGrowth()
+val transactions: RDD[Array[String]] = data.map(s => s.trim.split(' '))
+
+val fpm = new FPGrowth()
--- End diff --
Should be `fpg` for `FP-growth`.
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