add libSVMFile to MLContext

mllib/src/main/scala/org/apache/spark/mllib/MLContext.scala

@@ -0,0 +1,61 @@
+/*
+ * 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.mllib
+
+import org.apache.spark.SparkContext
+
+import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.rdd.RDD
+
+class MLContext(self: SparkContext) {
+  /**
+   * Reads labeled data in the LIBSVM format into an RDD[LabeledPoint].
+   * The LIBSVM format is a text-based format used by LIBSVM (http://www.csie.ntu.edu.tw/~cjlin/libsvm/).
+   * Each line represents a labeled sparse feature vector using the following format:
+   * {{{label index1:value1 index2:value2 ...}}}
+   * where the indices are one-based and in ascending order.
+   * This method parses each line into a [[org.apache.spark.mllib.regression.LabeledPoint]] instance,
+   * where the feature indices are converted to zero-based.
+   *
+   * @param path file or directory path in any Hadoop-supported file system URI
+   * @param numFeatures number of features
+   * @param labelParser parser for labels, default: _.toDouble
+   * @return labeled data stored as an RDD[LabeledPoint]
+   */
+  def libSVMFile(
+      path: String,
+      numFeatures: Int,
+      labelParser: String => Double = _.toDouble): RDD[LabeledPoint] = {
+    self.textFile(path).map(_.trim).filter(!_.isEmpty).map { line =>
+      val items = line.split(' ')
+      val label = labelParser(items.head)
+      val features = Vectors.sparse(numFeatures, items.tail.map { item =>
+        val indexAndValue = item.split(':')
+        val index = indexAndValue(0).toInt - 1
+        val value = indexAndValue(1).toDouble
+        (index, value)
+      })
+      LabeledPoint(label, features)
+    }
+  }
+}
+
+object MLContext {
+  implicit def sparkContextToMLContext(sc: SparkContext): MLContext = new MLContext(sc)
+}

mllib/src/test/scala/org/apache/spark/mllib/MLContextSuite.scala

@@ -0,0 +1,51 @@
+/*
+ * 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.mllib
+
+import org.apache.spark.mllib.MLContext._
+import org.apache.spark.mllib.util.LocalSparkContext
+import org.scalatest.FunSuite
+import com.google.common.io.Files
+import java.io.File
+import com.google.common.base.Charsets
+import org.apache.spark.mllib.linalg.Vectors
+
+class MLContextSuite extends FunSuite with LocalSparkContext {
+  test("libSVMFile") {
+    val lines =
+      """
+        |1 1:1.0 3:2.0 5:3.0
+        |0 2:4.0 4:5.0 6:6.0
+      """.stripMargin
+    val tempDir = Files.createTempDir()
+    val file = new File(tempDir.getPath, "part-00000")
+    Files.write(lines, file, Charsets.US_ASCII)
+    val points = sc.libSVMFile(tempDir.toURI.toString, 6).collect()
+    assert(points.length === 2)
+    assert(points(0).label === 1.0)
+    assert(points(0).features === Vectors.sparse(6, Seq((0, 1.0), (2, 2.0), (4, 3.0))))
+    assert(points(1).label === 0.0)
+    assert(points(1).features === Vectors.sparse(6, Seq((1, 4.0), (3, 5.0), (5, 6.0))))
+    try {
+      file.delete()
+      tempDir.delete()
+    } catch {
+      case t: Throwable =>
+    }
+  }
+}