[
https://issues.apache.org/jira/browse/FLINK-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14701440#comment-14701440
]
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_r37313995
--- Diff:
flink-core/src/main/java/org/apache/flink/api/common/operators/util/PoissonSampler.java
---
@@ -0,0 +1,109 @@
+/*
+ * 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 com.google.common.base.Preconditions;
+import org.apache.commons.math3.distribution.PoissonDistribution;
+
+import java.util.Iterator;
+
+/**
+ * A sampler implementation based on Poisson Distribution. While sampling
elements with fraction and replacement,
+ * the selected number of each element follows a given poisson
distribution, so we could use poisson
+ * distribution to generate random variables for sample.
+ *
+ * @param <T> The type of sample.
+ * @see <a
href="https://en.wikipedia.org/wiki/Poisson_distribution";>https://en.wikipedia.org/wiki/Poisson_distribution</a>
+ */
+public class PoissonSampler<T> extends RandomSampler<T> {
+
+ private PoissonDistribution poissonDistribution;
+ private final double fraction;
+
+ /**
+ * Create a poisson sampler which would sample elements with
replacement.
+ *
+ * @param fraction The expected count of each element.
+ * @param seed Random number generator seed for internal
PoissonDistribution.
+ */
+ public PoissonSampler(double fraction, long seed) {
+ Preconditions.checkArgument(fraction >= 0, "fraction should be
positive.");
+ this.fraction = fraction;
+ if (this.fraction > 0) {
+ this.poissonDistribution = new
PoissonDistribution(fraction);
+ this.poissonDistribution.reseedRandomGenerator(seed);
+ }
+ }
+
+ /**
+ * Create a poisson sampler which would sample elements with
replacement.
+ *
+ * @param fraction The expected count of each element.
+ */
+ public PoissonSampler(double fraction) {
+ Preconditions.checkArgument(fraction >= 0, "fraction should be
non-negative.");
+ this.fraction = fraction;
+ if (this.fraction > 0) {
+ this.poissonDistribution = new
PoissonDistribution(fraction);
+ }
+ }
+
+ /**
+ * Sample the input elements, for each input element, generate its
count with poisson distribution random variables generation.
+ *
+ * @param input Elements to be sampled.
+ * @return The sampled result which is lazy computed upon input
elements.
+ */
+ @Override
+ public Iterator<T> sample(final Iterator<T> input) {
+ if (fraction == 0) {
+ return EMPTY_ITERABLE;
+ }
+
+ return new SampledIterator<T>() {
+ T currentElement;
+ int currentCount = 0;
+
+ @Override
+ public boolean hasNext() {
+ if (currentElement == null || currentCount ==
0) {
+ while (input.hasNext()) {
+ currentElement = input.next();
+ currentCount =
poissonDistribution.sample();
+ if (currentCount > 0) {
+ return true;
+ }
+ }
+ return false;
+ }
+ return true;
+ }
+
+ @Override
+ public T next() {
+ T result = currentElement;
+ if (currentCount == 0) {
+ currentElement = null;
+ return null;
+ }
--- End diff --
Can we put the following statements in an else branch and remove the `T
result = currentElement;`? I think this makes the control flow slightly more
explicit.
> 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 or exact size of the sample, set a seed for
> reproducibility, and support sampling within iterations.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
