Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7697#discussion_r35619542
--- Diff:
examples/src/main/java/org/apache/spark/examples/ml/JavaKMeansExample.java ---
@@ -0,0 +1,98 @@
+/*
+ * 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;
+
+import java.util.regex.Pattern;
+
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.ml.clustering.KMeansModel;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.VectorUDT;
+import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.sql.DataFrame;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SQLContext;
+import org.apache.spark.sql.catalyst.expressions.GenericRow;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+
+/**
+ * An example demonstrating a k-means clustering.
+ * Run with
+ * <pre>
+ * bin/run-example ml.JavaSimpleParamsExample <file> <k>
+ * </pre>
+ */
+public class JavaKMeansExample {
+
+ private static class ParsePoint implements Function<String, Row> {
+ private static Pattern separater = Pattern.compile(" ");
+
+ @Override
+ public Row call(String line) {
+ String[] tok = separater.split(line);
+ double[] point = new double[tok.length];
+ for (int i = 0; i < tok.length; ++i) {
+ point[i] = Double.parseDouble(tok[i]);
+ }
+ Vector[] points = {Vectors.dense(point)};
+ Row row = new GenericRow(points);
+ return row;
+ }
+ }
+
+ public static void main(String[] args) {
+ if (args.length != 2) {
+ System.err.println("Usage: ml.JavaKMeansExample <file> <k>");
+ System.exit(1);
+ }
+ String inputFile = args[0];
+ int k = Integer.parseInt(args[1]);
+
+ // Parses the arguments
+ SparkConf conf = new SparkConf().setAppName("JavaKMeansExample");
+ JavaSparkContext jsc = new JavaSparkContext(conf);
+ SQLContext sqlContext = new SQLContext(jsc);
+
+ // Loads data
+ JavaRDD<Row> points = jsc.textFile(inputFile).map(new ParsePoint());
+ StructField[] fields = new StructField[1];
+ fields[0] = new StructField("features", new VectorUDT(), false,
Metadata.empty());
--- End diff --
You can use the same `Foo[] = { ... };` declaration as above here?
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