Created
May 2, 2016 05:32
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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3j6FDhxITE0NiYiIvv/yy/3T1r776ikGDBrFz506aNGlC3759mThxon/dxx57\njOHDh+OcIykpiaeeeoqzzz67WvdFSexQNCeVuGGzO4BBwAHgGyDNObe32DJu2rTgxFeeJbN6MHdo\n7/IXDILpGRmMvO++YIfBmDHTSUw8+NoQtUFGxnTuu692xlYb1OZjp89e+XxdBdV+lTczc8H6zRCp\niNI+A0Hp3jKzRGAEcKJz7gS8FqfLgxGLiIiIhIZgdW9lA3uBhmaWD0QCNXghcxEREQl1QWnpcc5l\nAQ8D64FNwE7n3H/LXktERESk8oLS0mNmrYEbgURgF/CSmQ1wzs0pvuyCBeP8z9u1S+XYY1MPUZQi\nIn8OS5cuZenSpcEOQ6TWC1b31snAR865HQBmNh84Ezgo6enVa9yhjUxE5E8mNTWV1NRU//T48eOD\nF4xILRas6/SsAk43s/rmnc93HvB9kGIRERGREBCsMT3pwGzgCyAdMGB6MGIRERGR0BC0ixM65/4J\n/DNY2xcREZHQottQiIiIlCIjI4OwsLAy7xtVmWUDMWvWrBq5SnFSUhKLFy8OePm77rqLI488kviK\nXB47AB9++CHHHXdctdZZHt2GQkREKm3O1KnkZtbcZdai4uMZMGpUQMu2atWKLVu2kJmZSWxsrH/+\niSeeSHp6Oj///HOl7mpekVtPVOdNSmuivorasGEDkydPZsOGDf5bTFRWWFgYP/30E61btwbgrLPO\n4vvvD+1wXiU9IiJSabmZmYxMTKyx+qdX4MZeZkZSUhJz585llC9R+vbbb/ntt9+CnjyU58CBA4SH\nhwc7jINkZGTQtGnTKic8EPwEDtS9JSIih5HBgwcza9Ys//SsWbMYOnRokWWys7MZMmQIzZo1Iykp\nifsK3S8tPz+fW265hSOPPJK2bduycOHCIusW7xoaP348gwcPLjGWZ555hg4dOhAdHU3btm2ZPv2P\n83WWLVtGQkICkyZNokWLFlx55ZUl1uGc49ZbbyU2NpY2bdrw1ltvBVT/9u3b6dWrFzExMTRp0oRz\nzz23SL1fffUVKSkpxMTE0L9/f/buLXLrSwDee+89unXrRmZmJtHR0Vx55ZX+uEvbJ/n5+dx///20\nbduW6OhoTjnlFDZu3Mi5556Lc44TTjiB6OhoXnzxxYPq+uGHH+jSpQsxMTEcf/zxLFiwwF+WlpbG\nNddcQ8+ePYmOjuaMM85g3bp1Je6zsijpERGRw8bpp59OTk4Oq1atIj8/nxdeeIFBgwZR+Eap11xz\nDTk5OfyyI/bhAAAgAElEQVT8888sXbqU2bNnM3PmTACmT5/Om2++SXp6OsuXL+ell14qd5ultWDE\nxcXx5ptvkp2dzcyZM7nxxhtZsWKFv3zLli3s3LmT9evXF0lYCvvss8847rjj2L59O7feeivDhg0L\nqP6HH36YhIQEtm/fztatW7n//vuL1Pviiy/yzjvvsG7dOtLT03nmmWcO2vZ5553HokWLiI+PJzs7\nm6effrrM11uw3RdeeIG33nrLv07Dhg1ZtmwZAN988w3Z2dn069evSF379++nV69eXHTRRfz6669M\nmTKFgQMHsnr1an/dL7zwAuPHj2fnzp20adOGMWPGlBpHaZT0iIjIYaWgtefdd9/luOOOKzIAtyAR\nevDBB4mMjCQxMZGbb76ZZ599FvCSgRtuuIH4+HiOOOII7rjjjkrH0b17d1q1agXA2WefTbdu3fjg\ngw/85eHh4YwfP56IiAjq1atXYh2tWrXiyiuvxMwYOnQoW7ZsYevWreXWHxERwebNm1m3bh3h4eF0\n7ty5SL3XX389cXFxHHHEEfTq1atIMlYVM2bM4L777qNt27YAHH/88cTExPjLCyefhX3yySfs3r2b\n0aNHU6dOHbp06ULPnj2ZO3euf5k+ffpw0kknERYWxsCBAysVs5IeERE5rAwaNIg5c+bwzDPPMGTI\nkCJl27ZtY//+/UUGNCcmJrJp0yYAMjMzi3S5JFZhvNKiRYs444wzaNKkCTExMSxatIht27b5y488\n8kgiIiLKrKN58+b+5w0aNMA5R25ubrn133rrrbRp04Zu3brRtm1b/vGPfxSpNy4uzv88MjLSX2dV\nbdiwwT9QuSI2b958ULdZ4eMCRfdFZWNW0iMiIoeVo48+mqSkJBYtWkTfvn2LlDVt2pSIiAgyCg2Q\nzsjIoGXLlgC0aNGCDRs2FCkrrGHDhuzZs8c/vWXLlhJj2Lt3L3/729+47bbb+PXXX8nKyqJ79+5F\nWjqqMrC3vPqjoqJ46KGHWLNmDa+//jqTJ09myZIlld5egeKv/8CBA/z666/+6YSEBNasWVPheuPj\n44vsd4D169f7j0t1UdIjIiKHnaeffprFixfToEGDIvPDwsK49NJLGTNmDLm5uWRkZPDII4/4ByNf\neumlTJkyhU2bNpGVlXVQC0mnTp2YN28e+/fvL3HMT0HSsXfvXvbu3UvTpk0JCwtj0aJFvPPOO9X2\n+sqrf+HChf7ko1GjRtSpU6dazg5r164dv//+O4sWLWL//v1MnDixyCDo4cOHc/fdd/PTTz8B3hie\nrKwswGupWbt2bYn1nnbaaURGRjJp0iT279/P0qVLeeONN+jfv3+VYy5Mp6yLiEilRcXHV+i08srU\nH6jCLSdJSUkkJSWVWDZlyhSuvfZaWrduTYMGDRg5ciRpaWkAjBgxgtWrV5OSkkLjxo255ZZbirSQ\n3HvvvfTv35/Y2FjOPfdcBg4cyI4dOw7aTlRUFFOmTKFfv37s3buXXr16cfHFF1d8B5TyGsurf/Xq\n1VxzzTVs27aNmJgYRo0axTnnnHPQvqio6OhoHn/8cYYNG0Z+fj633XYbRx11lL/8pptuYu/evXTr\n1o3t27fTvn17XnnlFWJiYrjnnnsYMmQIv//+O9OnT+fII4/0rxcREcGCBQu4+uqruf/++znqqKN4\n9tlnOeaYY6occ2FW2qCi2sDM3LRptTO+JbN6MHdo72CHUaLpGRmMLHQKZrCMGTOdxMSRwQ6jRBkZ\n07nvvtoZW21Qm4+dPnvlMzOcc9V+URQzc7X5N0OkQGmfAXVviYiISEhQ0iMiIiIhQUmPiIiIhAQl\nPSIiIhISlPSIiIhISFDSIyIiIiFBSY+IiIiEBF2cUELSmuVLmD6m5i6oVhVR8fEMGDUq2GGIiBx2\nlPRISLLcXYyswo0Ea1JNXt1WRKqmY8eOPP744/6rG8ufi5IeERGpvKlTITOz5uqPj4cgtXympaWR\nkJDAhAkT/PO+/fbboMRSEaNHj2bGjBmYGcOGDePBBx8sddn33nuPa665hg0bNnDaaacxc+ZM/x3o\nly5dyoQJE/jyyy+JjY096L5ZXbt25dtvvyUvL4+WLVty4403MmLECH/59OnTmTRpEtu2baNdu3Y8\n8sgjdO7cuUgdWVlZtGvXjuOOO47333+/GvdCyZT0iIhI5WVmQk22mlay5fPAgQPVcoPNP5tp06bx\n+uuv88033wBw/vnn07p1a0aOPPi2Mtu3b+eSSy7h6aefpmfPntx1111cdtllfPLJJ4B3R/Vhw4Yx\nYMAA7r///oPWf+yxx2jfvj0RERF8/vnnnHPOOZxzzjkce+yxrFixgptvvpkPPviATp068cQTT9Cn\nTx9++eWXIvfRGj16NMnJyeTn59fQHilKA5lFROSwkJSUxKRJk0hJSSEqKooDBw4QFhZWpIUiLS2N\nsWPHArBs2TISEhKYPHkycXFxtGzZkmeeeQaAJ598kueff55JkyYRHR3tv5lnUlISixcvBmD8+PFc\neumlDB48mOjoaFJSUli9ejUPPvggcXFxtGrViv/+97/+bWdnZzN8+HDi4+NJSEjg7rvvprrvZTZ7\n9mxuvvlmWrRoQYsWLbjlllv8r6m4+fPn07FjR/r27UvdunUZN24c6enp/PjjjwCccsopDBw4sMiN\nWws7/vjjiYiI8E9HRUURHR0NwPfff09ycjKdOnUCYMiQIWzfvp2tW7f6l//4449ZuXKl/2avh0K5\nSY+ZHfRqS5onIiISbPPmzWPRokXs3LmT8PDwcu/OvWXLFnJycsjMzOSpp55i1KhR7Nq1ixEjRjBw\n4EBuu+02srOzee2110pc/4033mDo0KHs3LmTTp06ccEFF+CcIzMzk7vuuqtIC8vQoUOpW7cua9eu\n5auvvuLdd9/lqaeeKrHeuXPnEhMTQ2xsLDExMUWex8bGsnHjxhLXW7lyJSkpKf7plJQUVq5cGdCy\nkZGRtG3bttTlS9KrVy8aNGhAly5dePrpp2nRogUAZ511FuvWrePzzz8nPz+fGTNm0KlTJ+Li4gDI\nz8/n2muv5d///nfA26oOgbT0vFzCvJeqOxAREZGquv7664mPj6devXoA5bak1K1bl7vvvpvw8HC6\nd+9OVFQUq1atCnh7Z599Nueffz5hYWH069ePHTt2cPvttxMeHs7ll19ORkYG2dnZ/PLLLyxatIhH\nHnmE+vXr07RpU2644Qbmzp1bYr39+/cnKyuLHTt2kJWVVeT5jh07OOqoo0pcLzc3l8aNG/uno6Oj\nyc3NDWjZguVzcnICfv0LFiwgNzeXWbNmccUVV7BhwwYAEhISmDhxIp07d6Z+/frce++9TJ8+3b/e\nlClTOOOMMzjxxBMD3lZ1KHVMj5m1B5KBxmbWt1BRNFC/pgMTERGpqNKSgdI0adKEsLA//v+PjIws\nNUkoSUHLBUCDBg1o2rSpv3WpQYMGOOfIzc1l06ZN7Nu3z98S4pzDOecfNFxdoqKiyM7O9k/v2rWL\nqKiogJYtWL5Ro0YV2mZ4eDh/+9vfmDFjBq+88grXXXcdr7/+Og8//DA//PADbdq04e233+avf/0r\nK1aswDnHlClT+PLLL4HyE9P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8UY3bfgS4Fe/aPyIiIiI1KpCkZwLwNvCTc+7/mVlrYHVV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\nQxB6AIAhfALmB6Y/Khc+hwAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10b567390>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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//kj79u1xzjF9+nR27NgBwKeffsrUqVO57LLLKr6Bg6RL1kVEpMISEyt+WXmw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\nQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10b08bc50>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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Snp7Om2++6e0jNHDgQDIzM1m0aBEFBQUsX76cPXv20L17dwAKCgrIy8vj6NGj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\nqout+FwAAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10b558048>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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eeolBgwYxbdo0brnlFnr06OFzHYMHD6ZXr16Eh4eTkJDAwoULS9z64z393Llz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\nC/530QTEmHDJAAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10b77f2e8>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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OxTAI+g+pYV09ce2PLCKiVVWHoMpIv3tKqYqgCVAZhdR1ex9P9QcREXF5VYegyki/e0qp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\nQJIkqTsGIEmS1B0DkCRJ6o4BSJIkdedjDBpgZJDw1xMAAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10b97bcf8>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"%matplotlib inline\n", | |
"\n", | |
"import matplotlib.pyplot as plt\n", | |
"import matplotlib.patches as mpatches\n", | |
"import numpy as np\n", | |
"import time\n", | |
"\n", | |
"from sympy.ntheory import isprime\n", | |
"import random\n", | |
"\n", | |
"def simple_hash(key, m):\n", | |
" return key % m\n", | |
"\n", | |
"def modular_hash(key, m, p):\n", | |
" random.seed(m)\n", | |
" a = random.randint(1, p - 1)\n", | |
" b = random.randint(0, p - 1)\n", | |
" return ( (a*key + b) % p ) % m\n", | |
"\n", | |
"def compute_distribution(p, m):\n", | |
" p_prime = p\n", | |
" while True:\n", | |
" if isprime(p_prime):\n", | |
" break\n", | |
" p_prime += 1\n", | |
" points1 = np.zeros(m)\n", | |
" points2 = np.zeros(m)\n", | |
" t1_start = time.time()\n", | |
" for key in range(p):\n", | |
" points1[simple_hash(key, m)] += 1\n", | |
" t1_end = round(time.time() - t1_start, 5)\n", | |
"\n", | |
" t2_start = time.time()\n", | |
" for key in range(p):\n", | |
" points2[modular_hash(key, m, p_prime)] += 1\n", | |
" t2_end = round(time.time() - t2_start, 5)\n", | |
"\n", | |
" return (points1, points2, t1_end, t2_end)\n", | |
"\n", | |
"def plot_chart(distributions, p, m):\n", | |
" fig, ax = plt.subplots()\n", | |
" index = np.arange(3)\n", | |
" bar_width = 0.35\n", | |
" opacity = 0.4\n", | |
" hash1_vals = [distributions[0].mean(), distributions[0].min(), distributions[0].max()]\n", | |
" hash2_vals = [distributions[1].mean(), distributions[1].min(), distributions[0].max()]\n", | |
" rects1 = plt.bar(index, hash1_vals, bar_width,\n", | |
" alpha=opacity,\n", | |
" color='b',\n", | |
" label='Naive hash fuction'\n", | |
" )\n", | |
" rects2 = plt.bar(index + bar_width, hash2_vals, bar_width,\n", | |
" alpha=opacity,\n", | |
" color='r',\n", | |
" label='Modular hash fuction'\n", | |
" )\n", | |
" \n", | |
" # add some text for labels, title and axes ticks\n", | |
" ax.set_ylabel('Keys per bucket')\n", | |
" ax.set_title('Comparison of key distribution between 2 hash function')\n", | |
" ax.set_xticks(index + bar_width)\n", | |
" ax.set_xticklabels(('Aver', 'Min', 'Max'))\n", | |
"\n", | |
" add_p = mpatches.Patch(color='none', label='m = {}'.format(p))\n", | |
" add_m = mpatches.Patch(color='none', label='p = {}'.format(m))\n", | |
" time1 = mpatches.Patch(alpha=opacity, color='b', label='runtime = {}'.format(distributions[2]))\n", | |
" time2 = mpatches.Patch(alpha=opacity, color='r', label='runtime = {}'.format(distributions[3]))\n", | |
"\n", | |
" plt.legend(handles=[rects1, time1, rects2, time2, add_p, add_m], bbox_to_anchor=(1.05, 1), loc=2)\n", | |
"# plt.legend()\n", | |
"\n", | |
"\n", | |
"\n", | |
"for p,m in [(10**i, 10**(i - 1)) for i in range(3, 8)]:\n", | |
" plot_chart(compute_distribution(p, m), p, m)\n", | |
"# plot_chart(compute_distribution(10**4, 10**3), 10**4, 10000)\n", | |
"\n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.5.0" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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