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ASF GitHub Bot commented on APEXMALHAR2094:

Github user sandeepn commented on a diff in the pull request:
https://github.com/apache/apexmalhar/pull/301#discussion_r66496208
 Diff: sketches/src/main/java/org/apache/apex/malhar/sketches/QuantilesEstimator.java

@@ 0,0 +1,188 @@
+/**
+ * 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/LICENSE2.0
+ *
+ * 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.apex.malhar.sketches;
+
+import com.yahoo.sketches.quantiles.QuantilesSketch;
+
+import com.datatorrent.api.DefaultInputPort;
+import com.datatorrent.api.DefaultOutputPort;
+import com.datatorrent.api.annotation.OperatorAnnotation;
+import com.datatorrent.common.util.BaseOperator;
+
+/**
+ * An implementation of BaseOperator that computes a "sketch" (a representation of the
probability distribution using
+ * a low memory footprint) of the incoming numeric data, and evaluates/outputs the cumulative
distribution function and
+ * quantiles of the probability distribution. Leverages the quantiles sketch implementation
from the Yahoo Datasketches
+ * Library.
+ * <p/>
+ * <b>Input Port(s) : </b><br>
+ * <b>data : </b> Data values input port. <br>
+ * <br>
+ * <b>Output Port(s) : </b> <br>
+ * <b>cdfOutput : </b>cumulative distribution function output port. <br>
+ * <b>quantilesOutput : </b>quantiles output port. <br>
+ * <br>
+ * <b>Partitions : </b> No unifier. Merging these sketches is nontrivial.
<br>
+ * <br>+
+ */
+@OperatorAnnotation(partitionable = false)
+public class QuantilesEstimator extends BaseOperator
+{
+ /**
+ * Constructor that allows nondefault initialization of the quantile sketch object
+ *
+ * @param k: Parameter that determines accuracy and memory usage of quantile sketch.
See QuantilesSketch
+ * documentation for details
+ * @param seed: The quantile sketch algorithm is inherently random. Set seed to 0 for
reproducibility in testing, but
+ * do not set otherwise.
+ */
+ public QuantilesEstimator(int k, short seed)
+ {
+ quantilesSketch = QuantilesSketch.builder().setSeed(seed).build(k);
+ }
+
+ private transient QuantilesSketch quantilesSketch = QuantilesSketch.builder().build();
+
+ /**
+ * This field determines the specific quantiles to be calculated. For a stream of numbers,
the quantile at a value
+ * 0 <= p <= 1 is the number x such that a fraction p of the numbers in the sorted
stream are less than x. E.g., the
+ * quantile at p = 0.5 is the median (half the numbers in the stream are less than
the median).
+ * The default is set to compute the standard quartiles (4quantiles).
+ */
+ private double[] fractions = {0.0, 0.25, 0.50, 0.75, 1.00};
+ /**
+ * This field determines the intervals on which the probability mass function is computed.
+ */
+ private double[] pmfIntervals = {};
+
+ /**
+ * This operator computes three different quantities which are output on separate output
ports. If not using any of
+ * these quantities, these variables can be set to avoid unnecessary computation.
+ */
+ private boolean computeCdf = true;
 End diff 
That would be cleaner. Thanks for the suggestion.
> Quantiles sketch operator
> 
>
> Key: APEXMALHAR2094
> URL: https://issues.apache.org/jira/browse/APEXMALHAR2094
> Project: Apache Apex Malhar
> Issue Type: New Feature
> Reporter: Sandeep Narayanaswami
> Assignee: Sandeep Narayanaswami
> Priority: Minor
>
> An operator that "sketches" in an online fashion the probability distribution of an input
(numeric) data stream, enabling computation of quantiles and cumulative distribution functions.

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