Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/685#discussion_r12502576
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/util/NumericParser.scala ---
@@ -0,0 +1,153 @@
+/*
+ * 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.util
+
+import scala.collection.mutable.{ArrayBuffer, ListBuffer}
+
+private[mllib] object NumericTokenizer {
+ val NUMBER = -1
+ val END = -2
+}
+
+import NumericTokenizer._
+
+/**
+ * Simple tokenizer for a numeric structure consisting of three types:
+ *
+ * - number: a double in Java's floating number format
+ * - array: an array of numbers stored as `[v0,v1,...,vn]`
+ * - tuple: a list of numbers, arrays, or tuples stored as `(...)`
+ *
+ * @param s input string
+ * @param start start index
+ * @param end end index
+ */
+private[mllib] class NumericTokenizer(s: String, start: Int, end: Int) {
--- End diff --
Much of the logic here could perhaps be replaced by `new
StringTokenizer(s.substring(start, end), "[]()," true)`. StringTokenizer can be
configured to return the tokens (namely '[', ',', etc) so it should be enough
for parsing these data types.
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