Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8537#discussion_r38362299
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/source/libsvm/LibSVMRelation.scala ---
@@ -0,0 +1,104 @@
+/*
+ * 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.ml.source.libsvm
+
+import com.google.common.base.Objects
+import org.apache.spark.Logging
+import org.apache.spark.mllib.linalg.Vector
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.util.MLUtils
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.types._
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{DataSourceRegister, PrunedScan,
BaseRelation, RelationProvider}
+
+
+class LibSVMRelation(val path: String, val numFeatures: Int, val
featuresType: String)
+ (@transient val sqlContext: SQLContext)
+ extends BaseRelation with PrunedScan with Logging {
+
+ private final val vectorType: DataType
+ =
classOf[Vector].getAnnotation(classOf[SQLUserDefinedType]).udt().newInstance()
+
+
+ override def schema: StructType = StructType(
+ StructField("label", DoubleType, nullable = false) ::
+ StructField("features", vectorType, nullable = false) :: Nil
+ )
+
+ override def buildScan(requiredColumns: Array[String]): RDD[Row] = {
+ val sc = sqlContext.sparkContext
+ val baseRdd = MLUtils.loadLibSVMFile(sc, path, numFeatures)
+
+ val rowBuilders = requiredColumns.map {
+ case "label" => (pt: LabeledPoint) => Seq(pt.label)
+ case "features" if featuresType == "sparse" => (pt: LabeledPoint) =>
Seq(pt.features.toSparse)
+ case "features" if featuresType == "dense" => (pt: LabeledPoint) =>
Seq(pt.features.toDense)
+ }
+
+ baseRdd.map(pt => {
+ Row.fromSeq(rowBuilders.map(_(pt)).reduceOption(_ ++
_).getOrElse(Seq.empty))
+ })
+ }
+
+ override def hashCode(): Int = {
+ Objects.hashCode(path, schema)
+ }
+
+ override def equals(other: Any): Boolean = other match {
+ case that: LibSVMRelation => (this.path == that.path) &&
this.schema.equals(that.schema)
+ case _ => false
+ }
+
+}
+
+class DefaultSource extends RelationProvider with DataSourceRegister {
--- End diff --
ditto, does it need to be public?
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