spark JavaFPGrowthExample 源码
spark JavaFPGrowthExample 代码
文件路径：/examples/src/main/java/org/apache/spark/examples/ml/JavaFPGrowthExample.java
/*
* 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;
// $example on$
import java.util.Arrays;
import java.util.List;
import org.apache.spark.ml.fpm.FPGrowth;
import org.apache.spark.ml.fpm.FPGrowthModel;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.*;
// $example off$
/**
* An example demonstrating FPGrowth.
* Run with
* <pre>
* bin/run-example ml.JavaFPGrowthExample
* </pre>
*/
public class JavaFPGrowthExample {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("JavaFPGrowthExample")
.getOrCreate();
// $example on$
List<Row> data = Arrays.asList(
RowFactory.create(Arrays.asList("1 2 5".split(" "))),
RowFactory.create(Arrays.asList("1 2 3 5".split(" "))),
RowFactory.create(Arrays.asList("1 2".split(" ")))
);
StructType schema = new StructType(new StructField[]{ new StructField(
"items", new ArrayType(DataTypes.StringType, true), false, Metadata.empty())
});
Dataset<Row> itemsDF = spark.createDataFrame(data, schema);
FPGrowthModel model = new FPGrowth()
.setItemsCol("items")
.setMinSupport(0.5)
.setMinConfidence(0.6)
.fit(itemsDF);
// Display frequent itemsets.
model.freqItemsets().show();
// Display generated association rules.
model.associationRules().show();
// transform examines the input items against all the association rules and summarize the
// consequents as prediction
model.transform(itemsDF).show();
// $example off$
spark.stop();
}
}
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