docs/KLL/KLLCppExample.md

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# KLL Sketch C++ Example

    #include <iostream>
    #include <fstream>
    #include <random>
    #include <chrono>

    #include <kll_sketch.hpp>

    //simplified file operations and no error handling for clarity
    int main(int argc, char **argv) {
      // this section generates two sketches from random data and serializes them into files
      {
        std::default_random_engine generator(std::chrono::system_clock::now().time_since_epoch().count());
        std::normal_distribution<float> nd(0, 1); // mean=0, stddev=1

        datasketches::kll_sketch<float> sketch1; // default k=200
        for (int i = 0; i < 10000; i++) {
          sketch1.update(nd(generator)); // mean=0, stddev=1
        }
        std::ofstream os1("kll_sketch_float1.bin");
        sketch1.serialize(os1);

        datasketches::kll_sketch<float> sketch2; // default k=200
        for (int i = 0; i < 10000; i++) {
          sketch2.update(nd(generator) + 1); // shift the mean for the second sketch
        }
        std::ofstream os2("kll_sketch_float2.bin");
        sketch2.serialize(os2);
      }

      // this section deserializes the sketches, produces a union and prints some results
      {
        std::ifstream is1("kll_sketch_float1.bin");
        auto sketch1 = datasketches::kll_sketch<float>::deserialize(is1);

        std::ifstream is2("kll_sketch_float2.bin");
        auto sketch2 = datasketches::kll_sketch<float>::deserialize(is2);

        // we could merge sketch2 into sketch1 or the other way around
        // this is an example of using a new sketch as a union and keeping the original sketches intact
        datasketches::kll_sketch<float> u; // default k=200
        u.merge(sketch1);
        u.merge(sketch2);

        // Debug output
        std::cout << u.to_string();

        std::cout << "Min: " << u.get_min_item() << std::endl;
        std::cout << "Max: " << u.get_max_item() << std::endl;
        auto quantiles = u.get_quantiles((double[3]){0.5, 0.75, 0.9}, 3);
        std::cout << "Quantiles: 0.5 (median), 0.75, 0.9:\n";
        std::cout << quantiles[0] << ", " << quantiles[1] << ", " << quantiles[2] << std::endl;

        std::cout << "Probability Histogram: estimated probability mass in 4 bins: (-inf, -2), [-2, 0), [0, 2), [2, +inf)" << std::endl;
        const float split_points[] {-2, 0, 2};
        const int num_split_points = 3;
        auto pmf = u.get_PMF(split_points, num_split_points);
        std::cout << pmf[0] << ", " << pmf[1] << ", " << pmf[2] << ", " << pmf[3] << std::endl;

        std::cout << "Frequency Histogram: estimated number of original values in the same bins" << std::endl;
        const int num_bins = num_split_points + 1;
        int histogram[num_bins];
        for (int i = 0; i < num_bins; i++) {
          histogram[i] = pmf[i] * u.get_n(); // scale the fractions by the total count of values
        }
        std::cout << histogram[0] << ", " << histogram[1] << ", " << histogram[2] << ", " << histogram[3] << std::endl;
      }

      return 0;
    }

    Output (will be slightly different every time due to random input):
    ### KLL sketch summary:
       K              : 200
       min K          : 200
       M              : 8
       N              : 20000
       Epsilon        : 1.33%
       Epsilon PMF    : 1.65%
       Empty          : false
       Estimation mode: true
       Levels         : 7
       Sorted         : false
       Capacity items : 565
       Retained items : 394
       Min item      : -3.75
       Max item      : 4.6
    ### End sketch summary
    Min: -3.75359
    Max: 4.60465
    Quantiles: 0.5 (median), 0.75, 0.9:
    0.508168, 1.25914, 1.938
    Probability Histogram: estimated probability mass in 4 bins: (-inf, -2), [-2, 0), [0, 2), [2, +inf)
    0.0118, 0.3134, 0.58475, 0.09005
    Frequency Histogram: estimated number of original values in the same bins
    236, 6268, 11695, 1800