Notebook for Robin Hood hashing (using Julia)

RobinHood.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "setprecision(512);\n",
    "\n",
    "memoize_dist = Dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "distribution_sum (generic function with 1 method)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PRECISION = 5000\n",
    "\n",
    "function displacement_probability(n, a)\n",
    "    a = BigFloat(a)\n",
    "\tp = 1 / a - 1\n",
    "\tq = BigFloat(0)\n",
    "\tn = BigInt(n)\n",
    "\tfor k in BigInt(PRECISION):-1:1\n",
    "\t\tq = e^-a * a / (k + n) * ((1 - k * a / (k + n + 1)) * k^(k + n) + q)\n",
    "\tend\n",
    "\treturn p * q * a^n / factorial(BigInt(n))\n",
    "end\n",
    "\n",
    "function distribution(fn; limit=nothing, load_factor=nothing)\n",
    "    pmap((k) -> begin\n",
    "        key = (fn, k, load_factor)\n",
    "        if !haskey(memoize_dist, key)\n",
    "            memoize_dist[key] = fn(k, load_factor)\n",
    "        end\n",
    "        memoize_dist[key]\n",
    "    end, 0:limit)\n",
    "end\n",
    "\n",
    "function distribution_sum(fn; limit=nothing, load_factor=nothing)\n",
    "    values = distribution(fn, limit=limit, load_factor=load_factor)\n",
    "    map((i) -> sum(values[i:length(values)]), 1:limit)\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#memoize_oflo = Dict()\n",
    "\n",
    "# function overflow(m, a, k)\n",
    "#     if m == 0 && k == 0\n",
    "#         return 1\n",
    "#     elseif m < k\n",
    "#         return 0\n",
    "#     elseif a == 0 && k == 0\n",
    "#         return 1\n",
    "#     elseif a == 0\n",
    "#         return 0\n",
    "#     end\n",
    "#     sum(\n",
    "#         (j) -> e^(a*(j+1)) * (-1)^(k-j) * (a * (j + 1))^(k-1-j) * (k + a * (j + 1) - j) / factorial(k - j),\n",
    "#         0:k\n",
    "#     ) * (1 - a)\n",
    "# end\n",
    "\n",
    "# function overflow_err(m, a, k)\n",
    "#     if m == 0 && k == 0\n",
    "#         return 1\n",
    "#     elseif m < k\n",
    "#         return 0\n",
    "#     elseif a == 0 && k == 0\n",
    "#         return 1\n",
    "#     elseif a == 0\n",
    "#         return 0\n",
    "#     end\n",
    "#     overflow(m, a, k) + a^m\n",
    "# end\n",
    "\n",
    "# function run_length_probability3(k, load_factor; table_size=2^22, ofn=overflow)\n",
    "#     k = BigInt(k)\n",
    "#     load_factor = BigFloat(load_factor)\n",
    "#     table_size = BigInt(table_size)\n",
    "#     if k == 0\n",
    "#         return 1 - load_factor\n",
    "#     end\n",
    "#     sum(\n",
    "#         (o_n) -> begin\n",
    "#             o_n = BigInt(o_n)\n",
    "#             n = BigInt(floor(load_factor * table_size))\n",
    "#             a_n = k - o_n\n",
    "#             r_l = table_size# - k\n",
    "#             r_n = n - a_n\n",
    "#             pr1 = binomial(n, a_n) * (k // table_size)^a_n * ((table_size - k - 1) // table_size)^(n-a_n)# * (1 - (n - a_n) / (table_size - k))\n",
    "#             pr2 = formula_g(k, a_n, 0)\n",
    "#             adjusted_r_n = BigInt(round(r_n * table_size / (table_size - k)))\n",
    "#             key = (adjusted_r_n, o_n)\n",
    "#             if !haskey(memoize_oflo, key)\n",
    "#                 memoize_oflo[key] = overflow(table_size, adjusted_r_n // table_size, o_n)\n",
    "#             end\n",
    "#             pr3 = memoize_oflo[key]\n",
    "#             pr1 * pr2 * pr3\n",
    "#         end,\n",
    "#         1:k\n",
    "#     )\n",
    "# end\n",
    "\n",
    "# function formula_g(n, m, d)\n",
    "#     #sum(\n",
    "#     #    (i) -> binomial(m, i) * (n - m + d) * (n - m + d + i)^(i-1) * (m - d - i)^(m-i),\n",
    "#     #    0:(m - d)\n",
    "#     #)\n",
    "#     n = BigInt(n)\n",
    "#     m = BigInt(m)\n",
    "#     d = BigInt(d)\n",
    "#     if n == 0 && d == 0\n",
    "#         return 1\n",
    "#     elseif n < d\n",
    "#         return 0\n",
    "#     elseif m == 0 && d == 0\n",
    "#         return 1\n",
    "#     elseif m == 0\n",
    "#         return 0\n",
    "#     elseif d >= m\n",
    "#         return 0\n",
    "#     end\n",
    "#     (\n",
    "#         sum(\n",
    "#             (i) -> begin\n",
    "#                 binomial(m, i) * (\n",
    "#                     (n - m + d) * (n - m + d + i)^float(i-1) * (m - d - i)^(m-i)\n",
    "#                     -\n",
    "#                     (n - m + d + 1) * (n - m + d + 1 + i)^float(i-1) * (m - d - 1 - i)^(m-i)\n",
    "#                 )\n",
    "#             end,\n",
    "#             0:(m - d - 1)\n",
    "#         ) +\n",
    "#             binomial(m, m - d) * (n - m + d) * (n - m + d + m - d)^(m - d -1) * 0^d\n",
    "#     ) / n^m\n",
    "# end\n",
    "\n",
    "# for k in keys(memoize_dist)\n",
    "#     if k[1] == run_length_probability3 || k[1] == run_length_probability3_err\n",
    "#         delete!(memoize_dist, k)\n",
    "#     end\n",
    "# end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "References:\n",
    "\n",
    "* Alfredo Viola (2005), Distributional analysis of Robin Hood linear probing hashing with buckets.\n",
    "* Uri Zwick, Hash Tables: Linear Probing. http://www.cs.tau.ac.il/~zwick/Adv-Alg-2015/Linear-Probing.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "calc = [\n",
    "    Dict(\n",
    "        :fn => displacement_probability,\n",
    "        :title => \"Distribution of Pr{lookup cost >= k}\",\n",
    "        :params => [\n",
    "            Dict(:load_factor => 0.9, :limit => 300, :show => 250),\n",
    "            Dict(:load_factor => 0.833, :limit => 300, :show => 250),\n",
    "            Dict(:load_factor => 0.8, :limit => 300, :show => 250),\n",
    "            Dict(:load_factor => 0.4, :limit => 300, :show => 250),\n",
    "            Dict(:load_factor => 0.2, :limit => 300, :show => 250),\n",
    "        ]\n",
    "    )\n",
    "]\n",
    "\n",
    "calc = map(\n",
    "  item -> merge(item, Dict(\n",
    "    :params_list => map(\n",
    "      params -> merge(params, Dict(\n",
    "        :distribution => distribution_sum(item[:fn], load_factor = params[:load_factor], limit = params[:limit])\n",
    "      )),\n",
    "      item[:params]\n",
    "    )\n",
    "  )),\n",
    "  calc\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pr_0.9 sum = 9.99999999999737688742258142496845087662392196247881119349447317128615380035736767851496220687326080593646815669054278338550298678370908536532791010956316331e-01\n",
      "Pr_0.833 sum = 9.99999999999999999999999999999999994850899466427952904323675334063644085666886802301967722701650621089256906837050595626600020792494573088235743139211981319e-01\n",
      "Pr_0.8 sum = 9.99999999999999999999999999999999999999999999999999667004804318735591698669284858774116523655875232085983687200304611441682325342173468513423003171242797777e-01\n",
      "Pr_0.4 sum = 1.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000\n",
      "Pr_0.2 sum = 1.0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000003\n"
     ]
    }
   ],
   "source": [
    "for chart in calc\n",
    "    for line in chart[:params_list]\n",
    "        println(\"Pr_$(line[:load_factor]) sum = \", line[:distribution][1])\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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",
      "text/plain": [
       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7ff6b8449f60>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "using PyPlot\n",
    "for (index, fig) in enumerate(calc)\n",
    "    figure(index)\n",
    "    for line in fig[:params_list]\n",
    "        plot(line[:distribution][1:line[:show]], linewidth=1.5, linestyle=\"-\", label=\"Load factor is $(line[:load_factor])\")\n",
    "    end\n",
    "    semilogy()\n",
    "    title(fig[:title])\n",
    "    legend(loc=\"lower right\")\n",
    "    xlabel(\"k\")\n",
    "    ylabel(\"probability\")\n",
    "    grid(true)\n",
    "    (x1, x2, y1, y2) = axis()\n",
    "    axis((x1, x2, max(y1, 10e-40), min(y2, 1)))\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for (i, pr) in enumerate(calc[1][:params_list][3][:distribution][1:20])\n",
    "    println(\"Pr{k >= $(i-1)} = \", @sprintf(\"%.3f\", pr))\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000-element Array{Array{Int64,1},1}:\n",
       " [9107378223,9107390323]\n",
       " [7527677405,3272628825]\n",
       " [5454701093,2216049385]\n",
       " [3839208995,1705923248]\n",
       " [2692218269,1394195848]\n",
       " [1887541269,1180105357]\n",
       " [1323604768,1022368402]\n",
       " [928122424,900534919]  \n",
       " [650777472,803169179]  \n",
       " [456330600,723359419]  \n",
       " [319973777,656622072]  \n",
       " [224388517,599917134]  \n",
       " [157349213,551086261]  \n",
       " ⋮                      \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  \n",
       " [0,0]                  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
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   "outputs": [
    {
     "data": {
      "text/plain": [
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     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats_buckets = sum(map(x -> x[2], stats[1:1000]))"
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  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
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      "text/plain": [
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     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "stats_buckets = floor(20_000 * 2^21 * 0.833)"
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   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7ff6b86104a8>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-90.0,1890.0,3.090564395228728e-17,6.112117403414738)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats_dist_without_sum = map(x -> x[2], stats[1:1000])\n",
    "stats_distribution = map(idx -> sum(stats_dist_without_sum[idx:1000]) / stats_buckets, 1:1000)\n",
    "p1_x = 300\n",
    "p_dx = 300\n",
    "p2_x = p1_x + p_dx\n",
    "extrapolate_dx = 1500\n",
    "extrapolate_x = p1_x + extrapolate_dx\n",
    "p1 = stats_distribution[p1_x]\n",
    "p2 = stats_distribution[p1_x + p_dx]\n",
    "extrapolated = [p2, p1 * (p2 / p1)^(extrapolate_dx / p_dx)]\n",
    "\n",
    "using PyPlot\n",
    "figure(0)\n",
    "plot(stats_distribution, linewidth=1.5, linestyle=\"-\", label=\"Real insertion cost\")\n",
    "plot([p2_x, extrapolate_x], extrapolated, linewidth=1.5, linestyle=\"--\", label=\"Extrapolated\")\n",
    "semilogy()\n",
    "title(\"Probability distribution of insertion forward shift cost higher than k at load factor=0.833\")\n",
    "legend(loc=\"lower right\")\n",
    "xlabel(\"k\")\n",
    "ylabel(\"probability\")\n",
    "grid(true)\n",
    "(x1, x2, y1, y2) = axis()\n",
    "axis((x1, x2, max(y1, 10e-40), y2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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