COMPSs_Manuals/source/Sections/09_PyCOMPSs_Notebooks/hands-on/11_Wordcount_Solution-with-reduce.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Wordcount Solution (With reduce)\n",
    "\n",
    "## Complete version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pycompss.interactive as ipycompss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pycompss.api.task import task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pycompss.api.parameter import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********************************************************\n",
      "**************** PyCOMPSs Interactive ******************\n",
      "********************************************************\n",
      "*          .-~~-.--.           ______         ____     *\n",
      "*         :         )         |____  \\       |__  \\    *\n",
      "*   .~ ~ -.\\       /.- ~~ .      __) |          ) |    *\n",
      "*   >       `.   .'       <     |__  |         / /     *\n",
      "*  (         .- -.         )   ____) |   _    / /__    *\n",
      "*   `- -.-~  `- -'  ~-.- -'   |______/  |_|  |_____|   *\n",
      "*     (        :        )           _ _ .-:            *\n",
      "*      ~--.    :    .--~        .-~  .-~  }            *\n",
      "*          ~-.-^-.-~ \\_      .~  .-~   .~              *\n",
      "*                   \\ \\ '     \\ '_ _ -~                *\n",
      "*                    \\`.\\`.    //                      *\n",
      "*           . - ~ ~-.__\\`.\\`-.//                       *\n",
      "*       .-~   . - ~  }~ ~ ~-.~-.                       *\n",
      "*     .' .-~      .-~       :/~-.~-./:                 *\n",
      "*    /_~_ _ . - ~                 ~-.~-._              *\n",
      "*                                     ~-.<             *\n",
      "********************************************************\n",
      "* - Starting COMPSs runtime...                         *\n",
      "* - Log path : /home/user/.COMPSs/Interactive_20/\n",
      "* - PyCOMPSs Runtime started... Have fun!              *\n",
      "********************************************************\n"
     ]
    }
   ],
   "source": [
    "if 'BINDER_SERVICE_HOST' in os.environ:\n",
    "    ipycompss.start(graph=True, trace=True, debug=False,\n",
    "                    project_xml='../xml/project.xml',\n",
    "                    resources_xml='../xml/resources.xml')\n",
    "else:\n",
    "    ipycompss.start(graph=True, monitor=1000, trace=True, debug=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "@task(returns=list)\n",
    "def read_file(file_path):\n",
    "    \"\"\" Read a file and return a list of words.\n",
    "    :param file_path: file's path\n",
    "    :return: list of words\n",
    "    \"\"\"\n",
    "    data = []\n",
    "    with open(file_path, 'r') as f:\n",
    "        for line in f:\n",
    "            data += line.split()\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "@task(returns=dict)\n",
    "def wordCount(data):\n",
    "    \"\"\" Construct a frequency word dictorionary from a list of words.\n",
    "    :param data: a list of words\n",
    "    :return: a dictionary where key=word and value=#appearances\n",
    "    \"\"\"\n",
    "    partialResult = {}\n",
    "    for entry in data:\n",
    "        if entry in partialResult:\n",
    "            partialResult[entry] += 1\n",
    "        else:\n",
    "            partialResult[entry] = 1\n",
    "    return partialResult"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "@task(returns=dict, priority=True)\n",
    "def merge_dicts(*dictionaries):\n",
    "    import queue\n",
    "    q = queue.Queue()\n",
    "    for i in dictionaries:\n",
    "        q.put(i)\n",
    "    while not q.empty():\n",
    "        x = q.get()\n",
    "        if not q.empty():\n",
    "            y = q.get()\n",
    "            for k in y:\n",
    "                if k in x:\n",
    "                    x[k] += y[k]\n",
    "                else:\n",
    "                    x[k] = y[k]\n",
    "            q.put(x)\n",
    "    return(x)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found task: read_file\n",
      "Found task: wordCount\n",
      "Found task: merge_dicts\n"
     ]
    }
   ],
   "source": [
    "from pycompss.api.api import compss_wait_on\n",
    "\n",
    "# Get the dataset path\n",
    "pathDataset = os.getcwd() + '/dataset'\n",
    "\n",
    "# Construct a list with the file's paths from the dataset\n",
    "partialResult = []\n",
    "for fileName in os.listdir(pathDataset):\n",
    "    p = os.path.join(pathDataset, fileName)\n",
    "    data=read_file(p)\n",
    "    partialResult.append(wordCount(data))\n",
    "    \n",
    "# Accumulate the partial results to get the final result.\n",
    "result=merge_dicts(*partialResult)\n",
    "\n",
    "# Wait for result\n",
    "result = compss_wait_on(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result:\n",
      "{'Adipisci': 227,\n",
      " 'Aliquam': 233,\n",
      " 'Amet': 207,\n",
      " 'Consectetur': 201,\n",
      " 'Dolor': 198,\n",
      " 'Dolore': 236,\n",
      " 'Dolorem': 232,\n",
      " 'Eius': 251,\n",
      " 'Est': 197,\n",
      " 'Etincidunt': 232,\n",
      " 'Ipsum': 228,\n",
      " 'Labore': 229,\n",
      " 'Magnam': 195,\n",
      " 'Modi': 201,\n",
      " 'Neque': 205,\n",
      " 'Non': 226,\n",
      " 'Numquam': 253,\n",
      " 'Porro': 205,\n",
      " 'Quaerat': 217,\n",
      " 'Quiquia': 212,\n",
      " 'Quisquam': 214,\n",
      " 'Sed': 225,\n",
      " 'Sit': 220,\n",
      " 'Tempora': 189,\n",
      " 'Ut': 217,\n",
      " 'Velit': 218,\n",
      " 'Voluptatem': 235,\n",
      " 'adipisci': 1078,\n",
      " 'aliquam': 1107,\n",
      " 'amet': 1044,\n",
      " 'consectetur': 1073,\n",
      " 'dolor': 1120,\n",
      " 'dolore': 1065,\n",
      " 'dolorem': 1107,\n",
      " 'eius': 1048,\n",
      " 'est': 1101,\n",
      " 'etincidunt': 1114,\n",
      " 'ipsum': 1061,\n",
      " 'labore': 1070,\n",
      " 'magnam': 1096,\n",
      " 'modi': 1127,\n",
      " 'neque': 1093,\n",
      " 'non': 1099,\n",
      " 'numquam': 1094,\n",
      " 'porro': 1101,\n",
      " 'quaerat': 1086,\n",
      " 'quiquia': 1079,\n",
      " 'quisquam': 1144,\n",
      " 'sed': 1109,\n",
      " 'sit': 1130,\n",
      " 'tempora': 1064,\n",
      " 'ut': 1070,\n",
      " 'velit': 1105,\n",
      " 'voluptatem': 1121}\n",
      "Words: 35409\n"
     ]
    }
   ],
   "source": [
    "print(\"Result:\")\n",
    "from pprint import pprint\n",
    "pprint(result)\n",
    "print(\"Words: {}\".format(sum(result.values())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********************************************************\n",
      "***************** STOPPING PyCOMPSs ********************\n",
      "********************************************************\n",
      "Checking if any issue happened.\n",
      "Warning: some of the variables used with PyCOMPSs may\n",
      "         have not been brought to the master.\n",
      "********************************************************\n"
     ]
    }
   ],
   "source": [
    "ipycompss.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipycompss.complete_task_graph(fit=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.2"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}