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VarOpt Sampling Java Example

This example was run using word counts from Shakespeare plays, namely Romeo and Juliet and Hamlet. The scripts, available from various sources including http://shakespeare.mit.edu/, were converted to (word, count) files with the following Perl command:

perl -lane 's/^\s+//; s/[;\.,!?:\x27\[\]&]//g; s/--//g; s/\s+/\n/g; print lc if length > 0' input.txt | sort | uniq -c | awk '{print $1 "\t" $2}' > output.txt

These were then used in the following example, slightly modified to remove error handling for clarity. Serialization and deserialization are completely parallel to the Reservoir Sampling sketch, and example code for that may be found in those Java examples.

import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.FileReader;

import org.apache.datasketches.memory.Memory;
import org.apache.datasketches.ArrayOfLongsSerDe;
import org.apache.datasketches.sampling.SampleSubsetSummary;
import org.apache.datasketches.sampling.VarOptItemsSamples;
import org.apache.datasketches.sampling.VarOptItemsSketch;
import org.apache.datasketches.sampling.VarOptItemsUnion;

// load (token, count) data from file, build sketch of size k
private static VarOptItemsSketch<String> loadFile(final String filename,
                                                  final int k) {
  try (BufferedReader br = new BufferedReader(new FileReader(filename))) {
    VarOptItemsSketch<String> vis = VarOptItemsSketch.newInstance(k);
    String line;
    while ((line = br.readLine()) != null) {
      String[] tokens = line.split("\\s+");
      if (tokens.length == 2) {
        vis.update(tokens[1], Double.parseDouble(tokens[0]));
    return vis;

// this section loads two sketches from prepared text files, unions them
// and demonstrates how to estimate subset sums for VarOpt sketches
  final int k = 100;
  VarOptItemsSketch<String> sketch1 = loadFile("/path/to/romeo_juliet.tsv", k);
  VarOptItemsSketch<String> sketch2 = loadFile("/path/to/hamlet.tsv", k);
  VarOptItemsUnion<String> union = VarOptItemsUnion.newInstance(k);

  // get and iterate over samples
  VarOptItemsSamples<String> samples = union.getResult().getSketchSamples();
  for (VarOptItemsSamples<String>.WeightedSample ws : samples) {
    System.out.println(ws.getItem() + "\t" + ws.getWeight());

  // apply predicate to estimate subset sums, here words of > 7 chars
  SampleSubsetSummary summary = union.getResult().estimateSubsetSum(s -> s.length() > 7);
  System.out.printf("[%f, %f, %f]\n",
        summary.getLowerBound(), summary.getEstimate(), summary.getUpperBound());

Sample Output:

i	567.0
i	580.0
to	737.0
of	667.0
and	716.0
and	964.0
the	1141.0
the	681.0
you	560.5978260869568
message	560.5978260869568
yon	560.5978260869568
thy	560.5978260869568
a	560.5978260869568

Lower bound, estimate, upper bound:

[594.395954, 2242.391304, 5611.681344]