Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/296#discussion_r11366080
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/rdd/CoordinateRDDMatrix.scala
---
@@ -0,0 +1,73 @@
+/*
+ * 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.linalg.rdd
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.SparkContext._
+import org.apache.spark.mllib.linalg.Vectors
+
+/**
+ * Represents a matrix in coordinate list format.
+ *
+ * @param entries matrix entries
+ * @param m number of rows (default: -1L, which means unknown)
+ * @param n number of column (default: -1L, which means unknown)
+ */
+class CoordinateRDDMatrix(
+ val entries: RDD[RDDMatrixEntry],
+ m: Long = -1L,
+ n: Long = -1L) extends RDDMatrix {
+
+ private var _m = m
+ private var _n = n
+
+ /** Gets or computes the number of columns. */
+ override def numCols(): Long = {
+ if (_n < 0) {
+ computeSize()
+ }
+ _n
+ }
+
+ /** Gets or computes the number of rows. */
+ override def numRows(): Long = {
+ if (_m < 0) {
+ computeSize()
+ }
+ _m
+ }
+
+ private def computeSize() {
+ val (m1, n1) = entries.map(entry => (entry.i, entry.j)).reduce { case
((i1, j1), (i2, j2)) =>
+ (math.max(i1, i2), math.max(j1, j2))
+ }
+ // There may be empty columns at the very right and empty rows at the
very bottom.
+ _m = math.max(_m, m1 + 1L)
+ _n = math.max(_n, n1 + 1L)
+ }
+
+ def toIndexedRowRDDMatrix(): IndexedRowRDDMatrix = {
+ val n = numCols().toInt
+ val indexedRows = entries.map(entry => (entry.i, (entry.j.toInt,
entry.value)))
+ .groupByKey()
+ .map { case (i, vectorEntries) =>
+ IndexedRDDMatrixRow(i, Vectors.sparse(n, vectorEntries))
+ }
+ new IndexedRowRDDMatrix(indexedRows, numRows(), numCols())
+ }
--- End diff --
This should also have a toRowMatrix.
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