apache / datasketches-java

A software library of stochastic streaming algorithms, a.k.a. sketches.
https://datasketches.apache.org
Apache License 2.0
888 stars 208 forks source link

Theta sketch intersection estimation value is greater than source sketch estimation value #325

Closed phstudy closed 4 years ago

phstudy commented 4 years ago

Sample code:

import org.apache.datasketches.memory.Memory;
import org.apache.datasketches.theta.*;

import java.nio.ByteOrder;
import java.util.Base64;

import static org.apache.datasketches.Util.DEFAULT_UPDATE_SEED;

public class ThetaSketchIntesectionApp {
    public static void main(String[] args) {
        byte[] sketch1Arr = Base64.getDecoder().decode("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");
        final Memory serializedSketch = Memory.wrap(sketch1Arr,
                                                    0,
                                                    sketch1Arr.length,
                                                    ByteOrder.nativeOrder());
        Sketch sketch1 = Sketch.wrap(serializedSketch, DEFAULT_UPDATE_SEED);

        byte[] sketch2Arr = Base64.getDecoder().decode("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");
        final Memory serializedSketch2 = Memory.wrap(sketch2Arr,
                                                    0,
                                                     sketch2Arr.length,
                                                    ByteOrder.nativeOrder());
        Sketch sketch2 = Sketch.wrap(serializedSketch2, DEFAULT_UPDATE_SEED);

        Sketch intSketch = Intersection.builder()
                    .buildIntersection()
                    .intersect(sketch1, sketch2);

        System.out.println("Sketch#1 Estimation: " + sketch1.getEstimate());
        System.out.println("Sketch#2 Estimation: " + sketch2.getEstimate());
        System.out.println("Sketch#1 and Sketch#2 Intersection Estimation: " + intSketch.getEstimate());
    }
}

Result:

Sketch#1 Estimation: 2.6420417306809786E8
Sketch#2 Estimation: 20693.591312562978
Sketch#1 and Sketch#2 Intersection Estimation: 64502.97194045358
jmalkin commented 4 years ago

Which release tag were you using for this example?

leerho commented 4 years ago

@phstudy Thank you for providing sufficient information & code so that we could actually understand and replicate your issue.

Your example is not a bug, in fact, given the two sketches you provided, the results are correct.

The fundamental issue is that you are intersecting two sketches, one estimating 264M uniques and the other 21K uniques, both with lgK = 12 or K=4096, .... but the intersection had only one retained item!

Intersections can produce much larger errors than normal sketching or unioning as is discussed on our website. The fundamental problem is that the intersection operation reduces your sample size and in this case it reduced your sample size down to only one sample! So you cannot expect reasonable accuracy with only one sample. In fact, you were lucky, it could have returned an estimate of zero. Would have been happier with that?

When doing intersections it is always a good idea to print out the upper and lower bounds along with the estimate. If you had done that, you would have discovered that the range of 95% confidence was (LB, Est, UB) = {1484, 65502, 366548}, which is huge!

The sketch is telling you that the true value of the intersection is somewhere between 1484 and 366,548! That is a clue that the sketch is not very confident of the result!

From the sketch you can also print out other information that tells you a great deal about what is going on inside the sketch. I added these extra print statements to your code (PhstudyTest below) so that you can learn to use these tools. The output from the modified test (PhstudyTestResults below) reveals a great deal about what your example is doing. Of course, the first really big clue is the line:

Retained Entries : 1

From both the preamble output as well as the sketch.toString() output, I could see that all of the sketches and the intersection are behaving quite normally. (Note: I did not include the long Base64 strings, since you already have them.)

Cheers, Lee.

    public class PhstudyTest {
      @SuppressWarnings("javadoc")
      @Test
      public void checkPhstudy() {
          byte[] sketch1Arr = Base64.getDecoder().decode("<sketch1Base64>");
          PreambleUtil.preambleToString(sketch1Arr);
          final Memory serializedSketch = Memory.wrap(sketch1Arr);
          Sketch sketch1 = Sketch.wrap(serializedSketch, DEFAULT_UPDATE_SEED);
          println(Sketch.toString(sketch1Arr));
          println(sketch1.toString());

          byte[] sketch2Arr = Base64.getDecoder().decode("<sketch2Base64>");
          final Memory serializedSketch2 = Memory.wrap(sketch2Arr);
          Sketch sketch2 = Sketch.wrap(serializedSketch2, DEFAULT_UPDATE_SEED);
          println(Sketch.toString(sketch2Arr));
          println(sketch2.toString());

          Intersection inter = SetOperation.builder().buildIntersection();
          Sketch intSketch = inter.intersect(sketch1, sketch2);
          println(intSketch.toString());
      }
      static void println(Object o) { System.out.println(o.toString()); }
    }
PhstudyTest Results:

### SKETCH PREAMBLE SUMMARY:
Byte  0: Preamble Longs       : 3
Byte  0: ResizeFactor         : X1
Byte  1: Serialization Version: 3
Byte  2: Family               : COMPACT
Byte  3: LgNomLongs           : 0
Byte  4: LgArrLongs           : 0
Byte  5: Flags Field          : 00011010, 26
  (Native Byte Order)         : LITTLE_ENDIAN
  BIG_ENDIAN_STORAGE          : false
  READ_ONLY                   : true
  EMPTY                       : false
  COMPACT                     : true
  ORDERED                     : true
  SINGLEITEM  (derived)       : false
Bytes 6-7  : Seed Hash        : 93cc
Bytes 8-11 : CurrentCount     : 4096
Bytes 12-15: P                : 0.0
Bytes 16-23: Theta (double)   : 1.5503161636074036E-5
             Theta (long)     : 142991427517005
             Theta (long,hex) : 0000820cc93e3a4d
Preamble Bytes                : 24
Data Bytes                    : 32768
TOTAL Sketch Bytes            : 32792
### END SKETCH PREAMBLE SUMMARY

### DirectCompactOrderedSketch SUMMARY: 
   Estimate                : 2.6420417306809786E8
   Upper Bound, 95% conf   : 2.726232570287611E8
   Lower Bound, 95% conf   : 2.5604410472331813E8
   Theta (double)          : 1.5503161636074036E-5
   Theta (long)            : 142991427517005
   Theta (long) hex        : 0000820cc93e3a4d
   EstMode?                : true
   Empty?                  : false
   Retained Entries        : 4096
   Seed Hash               : 93cc | 37836
### END SKETCH SUMMARY

### SKETCH PREAMBLE SUMMARY:
Byte  0: Preamble Longs       : 3
Byte  0: ResizeFactor         : X1
Byte  1: Serialization Version: 3
Byte  2: Family               : COMPACT
Byte  3: LgNomLongs           : 0
Byte  4: LgArrLongs           : 0
Byte  5: Flags Field          : 00011010, 26
  (Native Byte Order)         : LITTLE_ENDIAN
  BIG_ENDIAN_STORAGE          : false
  READ_ONLY                   : true
  EMPTY                       : false
  COMPACT                     : true
  ORDERED                     : true
  SINGLEITEM  (derived)       : false
Bytes 6-7  : Seed Hash        : 93cc
Bytes 8-11 : CurrentCount     : 4096
Bytes 12-15: P                : 1.0
Bytes 16-23: Theta (double)   : 0.19793567670940415
             Theta (long)     : 1825634385657445494
             Theta (long,hex) : 1955f4cd16d9bc76
Preamble Bytes                : 24
Data Bytes                    : 32768
TOTAL Sketch Bytes            : 32792
### END SKETCH PREAMBLE SUMMARY

### DirectCompactOrderedSketch SUMMARY: 
   Estimate                : 20693.591312562978
   Upper Bound, 95% conf   : 21283.962960450415
   Lower Bound, 95% conf   : 20119.498939949455
   Theta (double)          : 0.19793567670940415
   Theta (long)            : 1825634385657445494
   Theta (long) hex        : 1955f4cd16d9bc76
   EstMode?                : true
   Empty?                  : false
   Retained Entries        : 4096
   Seed Hash               : 93cc | 37836
### END SKETCH SUMMARY

### HeapCompactOrderedSketch SUMMARY: 
   Estimate                : 64502.97194045358
   Upper Bound, 95% conf   : 366548.2818845309
   Lower Bound, 95% conf   : 1484.0
   Theta (double)          : 1.5503161636074036E-5
   Theta (long)            : 142991427517005
   Theta (long) hex        : 0000820cc93e3a4d
   EstMode?                : true
   Empty?                  : false
   Retained Entries        : 1
   Seed Hash               : 93cc | 37836
### END SKETCH SUMMARY
phstudy commented 4 years ago

@jmalkin I use 1.3.0-incubating

phstudy commented 4 years ago

@leerho Thanks for your detailed explanation and point out the documentation. I will try to improve the result by increasing K and using LB & UB.