Github user BryanCutler commented on a diff in the pull request:

    https://github.com/apache/spark/pull/17130#discussion_r104009419
  
    --- Diff: 
examples/src/main/scala/org/apache/spark/examples/ml/FPGrowthExample.scala ---
    @@ -0,0 +1,71 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.examples.ml
    +
    +// scalastyle:off println
    +
    +// $example on$
    +import org.apache.spark.ml.fpm.FPGrowth
    +// $example off$
    +import org.apache.spark.sql.SparkSession
    +
    +/**
    + * An example demonstrating FP-Growth.
    + * Run with
    + * {{{
    + * bin/run-example ml.FPGrowthExample
    + * }}}
    + */
    +object FPGrowthExample {
    +
    +  def main(args: Array[String]): Unit = {
    +
    +    val spark = SparkSession
    +      .builder
    +      .appName(s"${this.getClass.getSimpleName}")
    +      .getOrCreate()
    +    import spark.implicits._
    +
    +    // $example on$
    +    // Loads data.
    +    val dataset = spark.createDataset(Seq(
    +      "1 2 5",
    +      "1 2 3 5",
    +      "1 2")
    +    ).map(t => t.split(" ")).toDF("features")
    +
    +    // Trains a FPGrowth model.
    --- End diff --
    
    nit: technically it is just the line below calling `fit` that trains the 
model, I would move this comment down or just take it out


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