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ASF GitHub Bot commented on FLINK-1901: --------------------------------------- Github user tillrohrmann commented on a diff in the pull request: https://github.com/apache/flink/pull/949#discussion_r35984950 --- Diff: flink-core/src/main/java/org/apache/flink/api/common/operators/util/RandomSampler.java --- @@ -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.flink.api.common.operators.util; + +import java.util.Iterator; + +public abstract class RandomSampler<T> { + + protected final Iterator<T> EMPTY_ITERABLE = new SampledIterator<T>() { + @Override + public boolean hasNext() { + return false; + } + + @Override + public T next() { + return null; + } + }; + + /** + * Randomly sample the elements from input, and return the result iterator. + * + * @param input source data + * @return the sample result. + */ + public abstract Iterator<T> sample(Iterator<T> input); +} + +abstract class SampledIterator<T> implements Iterator<T> { --- End diff -- JavaDocs are missing > Create sample operator for Dataset > ---------------------------------- > > Key: FLINK-1901 > URL: https://issues.apache.org/jira/browse/FLINK-1901 > Project: Flink > Issue Type: Improvement > Components: Core > Reporter: Theodore Vasiloudis > Assignee: Chengxiang Li > > In order to be able to implement Stochastic Gradient Descent and a number of > other machine learning algorithms we need to have a way to take a random > sample from a Dataset. > We need to be able to sample with or without replacement from the Dataset, > choose the relative size of the sample, and set a seed for reproducibility. -- This message was sent by Atlassian JIRA (v6.3.4#6332)