_doc/notebooks/pig_hive/pig_streaming_cloudera_correction.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# PIG et JSON et streaming avec les donn\u00e9es v\u00e9lib - correction avec cloudera\n",
        "\n",
        "Correction."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<b>Plan</b>\n",
              "<div id=\"my_menu_id\">run previous cell, wait for 2 seconds</div>\n",
              "<script>\n",
              "function repeat_indent_string(n){\n",
              "    var a = \"\" ;\n",
              "    for ( ; n > 0 ; --n) {\n",
              "        a += \"    \";\n",
              "    }\n",
              "    return a;\n",
              "}\n",
              "var update_menu_string = function(begin, lfirst, llast, sformat, send) {\n",
              "    var anchors = document.getElementsByClassName(\"section\");\n",
              "    if (anchors.length == 0) {\n",
              "        anchors = document.getElementsByClassName(\"text_cell_render rendered_html\");\n",
              "    }\n",
              "    var i,t;\n",
              "    var text_menu = begin;\n",
              "    var text_memo = \"<pre>\\nlength:\" + anchors.length + \"\\n\";\n",
              "    var ind = \"\";\n",
              "    var memo_level = 1;\n",
              "    var href;\n",
              "    var tags = [];\n",
              "    for (i = 0; i <= llast; i++) {\n",
              "        tags.push(\"h\" + i);\n",
              "    }\n",
              "\n",
              "    for (i = 0; i < anchors.length; i++) {\n",
              "        text_memo += \"**\" + anchors[i].id + \"--\\n\";\n",
              "\n",
              "        var child = null;\n",
              "        for(t = 0; t < tags.length; t++) {\n",
              "            var r = anchors[i].getElementsByTagName(tags[t]);\n",
              "            if (r.length > 0) {\n",
              "child = r[0];\n",
              "break;\n",
              "            }\n",
              "        }\n",
              "        if (child == null){\n",
              "            text_memo += \"null\\n\";\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        if (anchors[i].hasAttribute(\"id\")) {\n",
              "            // when converted in RST\n",
              "            href = anchors[i].id;\n",
              "            text_memo += \"#1-\" + href;\n",
              "            // passer \u00e0 child suivant (le chercher)\n",
              "        }\n",
              "        else if (child.hasAttribute(\"id\")) {\n",
              "            // in a notebook\n",
              "            href = child.id;\n",
              "            text_memo += \"#2-\" + href;\n",
              "        }\n",
              "        else {\n",
              "            text_memo += \"#3-\" + \"*\" + \"\\n\";\n",
              "            continue;\n",
              "        }\n",
              "        var title = child.textContent;\n",
              "        var level = parseInt(child.tagName.substring(1,2));\n",
              "\n",
              "        text_memo += \"--\" + level + \"?\" + lfirst + \"--\" + title + \"\\n\";\n",
              "\n",
              "        if ((level < lfirst) || (level > llast)) {\n",
              "            continue ;\n",
              "        }\n",
              "        if (title.endsWith('\u00b6')) {\n",
              "            title = title.substring(0,title.length-1).replace(\"<\", \"&lt;\").replace(\">\", \"&gt;\").replace(\"&\", \"&amp;\")\n",
              "        }\n",
              "\n",
              "        if (title.length == 0) {\n",
              "            continue;\n",
              "        }\n",
              "        while (level > memo_level) {\n",
              "            text_menu += \"<ul>\\n\";\n",
              "            memo_level += 1;\n",
              "        }\n",
              "        while (level < memo_level) {\n",
              "            text_menu += \"</ul>\\n\";\n",
              "            memo_level -= 1;\n",
              "        }\n",
              "        text_menu += repeat_indent_string(level-2) + sformat.replace(\"__HREF__\", href).replace(\"__TITLE__\", title);\n",
              "    }\n",
              "    while (1 < memo_level) {\n",
              "        text_menu += \"</ul>\\n\";\n",
              "        memo_level -= 1;\n",
              "    }\n",
              "    text_menu += send;\n",
              "    //text_menu += \"\\n\" + text_memo;\n",
              "    return text_menu;\n",
              "};\n",
              "var update_menu = function() {\n",
              "    var sbegin = \"\";\n",
              "    var sformat = '<li><a href=\"#__HREF__\">__TITLE__</a></li>';\n",
              "    var send = \"\";\n",
              "    var text_menu = update_menu_string(sbegin, 2, 4, sformat, send);\n",
              "    var menu = document.getElementById(\"my_menu_id\");\n",
              "    menu.innerHTML=text_menu;\n",
              "};\n",
              "window.setTimeout(update_menu,2000);\n",
              "            </script>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from jyquickhelper import add_notebook_menu\n",
        "add_notebook_menu()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## R\u00e9cup\u00e9ration des donn\u00e9es\n",
        "\n",
        "Le code suivant t\u00e9l\u00e9charge les donn\u00e9es n\u00e9cessaires [data_velib_paris_2014-11-11_22-23.zip](http://www.xavierdupre.fr/enseignement/complements/data_velib_paris_2014-11-11_22-23.zip)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['velib\\\\paris.2014-11-11_22-00-18.331391.txt',\n",
              " 'velib\\\\paris.2014-11-11_22-01-17.859194.txt']"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pyensae.datasource\n",
        "import os, datetime\n",
        "if not os.path.exists(\"velib\"):\n",
        "    os.mkdir(\"velib\")\n",
        "files=pyensae.datasource.download_data(\"data_velib_paris_2014-11-11_22-23.zip\", website=\"xdtd\", whereTo=\"velib\")\n",
        "files[:2]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Connexion au cluster\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"background-color:gainsboro; padding:2px; border:0px;\"><b>server + credentials</b>\n",
              "<br />password <input type=\"password\" id=\"paramspassword\" value=\"\" size=\"80\" />\n",
              "<br />server <input type=\"text\" id=\"paramsserver\" value=\"df...fr\" size=\"80\" />\n",
              "<br />username <input type=\"text\" id=\"paramsusername\" value=\"\" size=\"80\" />\n",
              "<br /><button onclick=\"set_valueparams()\">Ok</button></div>\n",
              "<script type=\"text/Javascript\">\n",
              "function paramscallback(msg) {\n",
              "   var ret = msg.content.data['text/plain'];\n",
              "   $('#outparams').text(ret);\n",
              "}\n",
              "function set_valueparams(){\n",
              "   command='params = {' ;\n",
              "   var paramspasswordvar_value = document.getElementById('paramspassword').value;\n",
              "   command += '\"password\":\"' + paramspasswordvar_value + '\",';\n",
              "   var paramsservervar_value = document.getElementById('paramsserver').value;\n",
              "   command += '\"server\":\"' + paramsservervar_value + '\",';\n",
              "   var paramsusernamevar_value = document.getElementById('paramsusername').value;\n",
              "   command += '\"username\":\"' + paramsusernamevar_value + '\",';\n",
              "   command += '}';\n",
              "   var kernel = IPython.notebook.kernel;\n",
              "   kernel.execute(command);\n",
              "}\n",
              "</script>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x5752a90>"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pyensae\n",
        "%load_ext pyensae\n",
        "%load_ext pyenbc\n",
        "from pyquickhelper.ipythonhelper import open_html_form\n",
        "params={\"server\":\"df...fr\", \"username\":\"\", \"password\":\"\"}\n",
        "open_html_form(params=params,title=\"server + credentials\", key_save=\"params\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<pyensae.remote.remote_connection.ASSHClient at 0x5b43bb0>"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pyensae\n",
        "%load_ext pyensae\n",
        "password = params[\"password\"]\n",
        "server = params[\"server\"]\n",
        "username = params[\"username\"]\n",
        "client = %remote_open\n",
        "client"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Exercice 1 : convertir les valeurs num\u00e9riques\n",
        "\n",
        "Le programme suivant prend comme argument les colonnes \u00e0 extraire des fichiers textes qui sont enregistr\u00e9s au format \"python\"."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PYTHON stream_json.py\n",
        "\n",
        "import sys, datetime\n",
        "cols = [ _ for _ in sys.argv if \".py\" not in _ ]\n",
        "for row in sys.stdin:\n",
        "    row = row.strip()\n",
        "    if len(row) == 0 :\n",
        "        continue\n",
        "    js = eval(row)\n",
        "    for station in js:\n",
        "        vals = [ str(station[c]) for c in cols ]\n",
        "        sys.stdout.write(\",\".join(vals))\n",
        "        sys.stdout.write(\"\\n\")\n",
        "        sys.stdout.flush()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "On v\u00e9rifie qu'il fonctionne en lui faisant ing\u00e9rer les deux lignes suivantes :"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "31705 - CHAMPEAUX (BAGNOLET),OPEN\n",
              "31705 - CHAMPEAUX (BAGNOLET),OPEN\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x96b1330>"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%%runpy stream_json.py name status\n",
        "[{'address': 'RUE DES CHAMPEAUX (PRES DE LA GARE ROUTIERE) - 93170 BAGNOLET', 'collect_date': datetime.datetime(2014, 11, 11, 22, 2, 18, 47270), 'lng': 2.416170724425901, 'contract_name': 'Paris', 'name': '31705 - CHAMPEAUX (BAGNOLET)', 'banking': 0, 'lat': 48.8645278209514, 'bonus': 0, 'status': 'OPEN', 'available_bikes': 1, 'last_update': datetime.datetime(2014, 11, 11, 21, 55, 22), 'number': 31705, 'available_bike_stands': 49, 'bike_stands': 50}]\n",
        "[{'address': 'RUE DES CHAMPEAUX (PRES DE LA GARE ROUTIERE) - 93170 BAGNOLET', 'collect_date': datetime.datetime(2014, 11, 11, 22, 2, 18, 47270), 'lng': 2.416170724425901, 'contract_name': 'Paris', 'name': '31705 - CHAMPEAUX (BAGNOLET)', 'banking': 0, 'lat': 48.8645278209514, 'bonus': 0, 'status': 'OPEN', 'available_bikes': 1, 'last_update': datetime.datetime(2014, 11, 11, 21, 55, 22), 'number': 31705, 'available_bike_stands': 49, 'bike_stands': 50}]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "On \u00e9crit le script PIG qui utilise plus de colonnes :"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PIG json_velib.pig\n",
        "\n",
        "DEFINE pystream `python stream_json.py available_bike_stands available_bikes lat lng name status` \n",
        "   SHIP ('stream_json.py') INPUT(stdin USING PigStreaming(',')) OUTPUT (stdout USING PigStreaming(',')) ;\n",
        "\n",
        "jspy = LOAD 'velib_py/*.txt' USING PigStorage('\\t') AS (arow:chararray);\n",
        "\n",
        "matrice = STREAM jspy THROUGH pystream AS \n",
        "                (   available_bike_stands:int, \n",
        "                    available_bikes:int, \n",
        "                    lat:double, \n",
        "                    lng:double, \n",
        "                    name:chararray, \n",
        "                    status:chararray) ;\n",
        "\n",
        "STORE matrice INTO 'velib_py_results/firstjob' USING PigStorage('\\t') ;"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "On supprime la pr\u00e9c\u00e9dente ex\u00e9cution si besoin puis on v\u00e9rifie que le r\u00e9pertoire contenant les r\u00e9sultats est vide :"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(\"Moved: 'hdfs://nameservice1/user/xavierdupre/velib_py_results/firstjob' to trash at: hdfs://nameservice1/user/xavierdupre/.Trash/Current\\n\",\n",
              " '14/11/23 20:35:18 INFO fs.TrashPolicyDefault: Namenode trash configuration: Deletion interval = 1440 minutes, Emptier interval = 0 minutes.\\n')"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if client.dfs_exists(\"velib_py_results/firstjob\"):\n",
        "    client.dfs_rm(\"velib_py_results/firstjob\", recursive=True)\n",
        "%dfs_mkdir velib_py_results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>attributes</th>\n",
              "      <th>code</th>\n",
              "      <th>alias</th>\n",
              "      <th>folder</th>\n",
              "      <th>size</th>\n",
              "      <th>date</th>\n",
              "      <th>time</th>\n",
              "      <th>name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [attributes, code, alias, folder, size, date, time, name]\n",
              "Index: []"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%dfs_ls velib_py_results/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x888ddb0>"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%pig_submit json_velib.pig stream_json.py -r redirection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "Total bytes written : 4611956\n",
              "Spillable Memory Manager spill count : 0\n",
              "Total bags proactively spilled: 0\n",
              "Total records proactively spilled: 0\n",
              "\n",
              "Job DAG:\n",
              "job_1414491244634_0119\n",
              "\n",
              "\n",
              "2014-11-23 20:36:50,180 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x888de50>"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%remote_cmd tail redirection.pig.err"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "On r\u00e9cup\u00e8re les informations qu'on affiche sous forme de dataframe :"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'velib_py_results/firstjob'"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if os.path.exists(\"velib_exo1.txt\") : os.remove(\"velib_exo1.txt\")\n",
        "client.download_cluster(\"velib_py_results/firstjob\",\"velib_exo1.txt\", merge=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>available_bike_stands</th>\n",
              "      <th>available_bikes</th>\n",
              "      <th>lat</th>\n",
              "      <th>lng</th>\n",
              "      <th>name</th>\n",
              "      <th>status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td> 47</td>\n",
              "      <td>  3</td>\n",
              "      <td> 48.864528</td>\n",
              "      <td> 2.416171</td>\n",
              "      <td>   31705 - CHAMPEAUX (BAGNOLET)</td>\n",
              "      <td> OPEN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>  5</td>\n",
              "      <td> 28</td>\n",
              "      <td> 48.872420</td>\n",
              "      <td> 2.348395</td>\n",
              "      <td> 10042 - POISSONNI\u00c8RE - ENGHIEN</td>\n",
              "      <td> OPEN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td> 42</td>\n",
              "      <td>  1</td>\n",
              "      <td> 48.882149</td>\n",
              "      <td> 2.319860</td>\n",
              "      <td>             08020 - METRO ROME</td>\n",
              "      <td> OPEN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>  5</td>\n",
              "      <td> 31</td>\n",
              "      <td> 48.868217</td>\n",
              "      <td> 2.330494</td>\n",
              "      <td>         01022 - RUE DE LA PAIX</td>\n",
              "      <td> OPEN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td> 20</td>\n",
              "      <td>  5</td>\n",
              "      <td> 48.893269</td>\n",
              "      <td> 2.412716</td>\n",
              "      <td>     35014 - DE GAULLE (PANTIN)</td>\n",
              "      <td> OPEN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   available_bike_stands  available_bikes        lat       lng  \\\n",
              "0                     47                3  48.864528  2.416171   \n",
              "1                      5               28  48.872420  2.348395   \n",
              "2                     42                1  48.882149  2.319860   \n",
              "3                      5               31  48.868217  2.330494   \n",
              "4                     20                5  48.893269  2.412716   \n",
              "\n",
              "                             name status  \n",
              "0    31705 - CHAMPEAUX (BAGNOLET)   OPEN  \n",
              "1  10042 - POISSONNI\u00c8RE - ENGHIEN   OPEN  \n",
              "2              08020 - METRO ROME   OPEN  \n",
              "3          01022 - RUE DE LA PAIX   OPEN  \n",
              "4      35014 - DE GAULLE (PANTIN)   OPEN  "
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas\n",
        "df = pandas.read_csv(\"velib_hd.txt\", sep=\"\\t\",names=[\"available_bike_stands\",\"available_bikes\",\"lat\",\"lng\",\"name\",\"status\"])\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Exercice 2 : stations ferm\u00e9es\n",
        "    \n",
        "Les stations ferm\u00e9es ne le sont pas tout le temps. On veut calculer le ratio minutes/stations ferm\u00e9es / total des minutes/stations. Le script python permettant de lire les donn\u00e9es ne change pas, il suffit juste de d\u00e9clarer les sorties num\u00e9riques comme telles. Quelques d\u00e9tails sur les tables :\n",
        "\n",
        "* ``jspy`` : contient les donn\u00e9es brutes dans une liste de fichiers\n",
        "* ``matrice`` : d'apr\u00e8s le job qui pr\u00e9c\u00e8de, la table contient une ligne par stations et par minute, chaque ligne d\u00e9crit le status de la station\n",
        "* ``grstation`` : table ``matrice`` group\u00e9e par status\n",
        "* ``fermees`` : pour chaque groupe, on aggr\u00e9g\u00e9 le nombre de minutes multipli\u00e9s par le nombre de v\u00e9los\n",
        "* ``gr*,dist*`` : distribution du nombre de stations (Y) en fonction du nombre de v\u00e9los ou places disponibles"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "En cas d'ex\u00e9cution pr\u00e9c\u00e9dentes :"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(\"Moved: 'hdfs://nameservice1/user/xavierdupre/velib_py_results/distribution_stands.txt' to trash at: hdfs://nameservice1/user/xavierdupre/.Trash/Current\\n\",\n",
              " '14/11/23 21:33:49 INFO fs.TrashPolicyDefault: Namenode trash configuration: Deletion interval = 1440 minutes, Emptier interval = 0 minutes.\\n')"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%dfs_rmr velib_py_results/fermees.txt\n",
        "%dfs_rmr velib_py_results/distribution_bikes.txt\n",
        "%dfs_rmr velib_py_results/distribution_stands.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PIG json_fermee.pig\n",
        "\n",
        "DEFINE pystream `python stream_json.py available_bike_stands available_bikes lat lng name status` \n",
        "   SHIP ('stream_json.py') INPUT(stdin USING PigStreaming(',')) OUTPUT (stdout USING PigStreaming(',')) ;\n",
        "\n",
        "jspy = LOAD 'velib_py/*.txt' USING PigStorage('\\t') AS (arow:chararray);\n",
        "\n",
        "matrice = STREAM jspy THROUGH pystream AS \n",
        "                (   available_bike_stands:int, \n",
        "                    available_bikes:int, \n",
        "                    lat:double, \n",
        "                    lng:double, \n",
        "                    name:chararray, \n",
        "                    status:chararray) ;\n",
        "                \n",
        "grstation = GROUP matrice BY status ;  \n",
        "\n",
        "fermees = FOREACH grstation GENERATE\n",
        "                 group\n",
        "                ,SUM(matrice.available_bikes) AS available_bikes\n",
        "                ,SUM(matrice.available_bike_stands) AS available_bike_stands \n",
        "                ;\n",
        "\n",
        "gr_av   = GROUP matrice BY available_bikes ;\n",
        "dist_av = FOREACH gr_av GENERATE group, COUNT(matrice) ;\n",
        "gr_pl   = GROUP matrice BY available_bike_stands ;\n",
        "dist_pl = FOREACH gr_pl GENERATE group, COUNT(matrice) ;\n",
        "\n",
        "STORE fermees INTO 'velib_py_results/fermees.txt' USING PigStorage('\\t') ;\n",
        "STORE dist_av INTO 'velib_py_results/distribution_bikes.txt' USING PigStorage('\\t') ;\n",
        "STORE dist_pl INTO 'velib_py_results/distribution_stands.txt' USING PigStorage('\\t') ;"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x9f62710>"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%pig_submit json_fermee.pig stream_json.py -r redirection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "Total bytes written : 1009\n",
              "Spillable Memory Manager spill count : 0\n",
              "Total bags proactively spilled: 0\n",
              "Total records proactively spilled: 0\n",
              "\n",
              "Job DAG:\n",
              "job_1414491244634_0124\n",
              "\n",
              "\n",
              "2014-11-23 21:35:28,238 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0x8975df0>"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%remote_cmd tail redirection.pig.err "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>attributes</th>\n",
              "      <th>code</th>\n",
              "      <th>alias</th>\n",
              "      <th>folder</th>\n",
              "      <th>size</th>\n",
              "      <th>date</th>\n",
              "      <th>time</th>\n",
              "      <th>name</th>\n",
              "      <th>isdir</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 20:54</td>\n",
              "      <td>  velib_py_results/distribution_bikes.txt</td>\n",
              "      <td> True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 20:54</td>\n",
              "      <td> velib_py_results/distribution_stands.txt</td>\n",
              "      <td> True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 20:36</td>\n",
              "      <td>                velib_py_results/firstjob</td>\n",
              "      <td> True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   attributes code        alias       folder size        date   time  \\\n",
              "0  drwxr-xr-x    -  xavierdupre  xavierdupre    0  2014-11-23  20:54   \n",
              "1  drwxr-xr-x    -  xavierdupre  xavierdupre    0  2014-11-23  20:54   \n",
              "2  drwxr-xr-x    -  xavierdupre  xavierdupre    0  2014-11-23  20:36   \n",
              "\n",
              "                                       name isdir  \n",
              "0   velib_py_results/distribution_bikes.txt  True  \n",
              "1  velib_py_results/distribution_stands.txt  True  \n",
              "2                 velib_py_results/firstjob  True  "
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%dfs_ls velib_py_results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'distribution_bikes.txt'"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if os.path.exists(\"distribution_bikes.txt\") : os.remove(\"distribution_bikes.txt\")\n",
        "%remote_down_cluster_merge velib_py_results/distribution_bikes.txt distribution_bikes.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>nb_velos</th>\n",
              "      <th>nb_stations_minutes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td> 0</td>\n",
              "      <td> 8445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td> 1</td>\n",
              "      <td> 6589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td> 2</td>\n",
              "      <td> 4825</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td> 3</td>\n",
              "      <td> 3793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td> 4</td>\n",
              "      <td> 2839</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   nb_velos  nb_stations_minutes\n",
              "0         0                 8445\n",
              "1         1                 6589\n",
              "2         2                 4825\n",
              "3         3                 3793\n",
              "4         4                 2839"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas\n",
        "df = pandas.read_csv(\"distribution_bikes.txt\", sep=\"\\t\", names=[\"nb_velos\", \"nb_stations_minutes\"])\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes.AxesSubplot at 0x9f3c4d0>"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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FMll71cpk7RXJZO0VyWTtFclk7RXJZO0VyWTtFclk7RXJZO0VyWTtFclk7RXJZO0FIzU5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\nEZFl978AcC4XmRnbM2QAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x9f7b0b0>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df.plot(x=\"nb_velos\",y=\"nb_stations_minutes\",kind=\"bar\",figsize=(16,4))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'distribution_stands.txt'"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if os.path.exists(\"distribution_stands.txt\") : os.remove(\"distribution_stands.txt\")\n",
        "%remote_down_cluster_merge velib_py_results/distribution_stands.txt distribution_stands.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes.AxesSubplot at 0xa04d390>"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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V+jo4mHWzPnhxcNqeWT03G1/fcX/0mec/+EiSJK3rgkizY7EwN32mcv52X9b8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\nJGnLOTiVJEmSJG25/x/G58B0ReXiEQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0xa094850>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df = pandas.read_csv(\"distribution_stands.txt\", sep=\"\\t\", names=[\"nb_places\", \"nb_stations_minutes\"])\n",
        "df.plot(x=\"nb_places\",y=\"nb_stations_minutes\",kind=\"bar\",figsize=(16,4))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'fermees.txt'"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if os.path.exists(\"fermees.txt\") : os.remove(\"fermees.txt\")\n",
        "%remote_down_cluster_merge velib_py_results/fermees.txt fermees.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>status</th>\n",
              "      <th>OPEN</th>\n",
              "      <th>CLOSED</th>\n",
              "      <th>%close</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>nb_velos_stations_minutes</th>\n",
              "      <td> 1048654</td>\n",
              "      <td> 3060</td>\n",
              "      <td> 0.002910</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>nb_places_stations_minutes</th>\n",
              "      <td> 1255146</td>\n",
              "      <td>  120</td>\n",
              "      <td> 0.000096</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "status                         OPEN  CLOSED    %close\n",
              "nb_velos_stations_minutes   1048654    3060  0.002910\n",
              "nb_places_stations_minutes  1255146     120  0.000096"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = pandas.read_csv(\"fermees.txt\", sep=\"\\t\", names=[\"status\", \"nb_velos_stations_minutes\", \"nb_places_stations_minutes\"])\n",
        "df=df.set_index(\"status\")\n",
        "df = df.T\n",
        "df[\"%close\"] = df.CLOSED / (df.CLOSED + df.OPEN)\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Ce dernier tableau n'est vrai que dans la mesure o\u00f9 les nombres report\u00e9es sont fiables lorsque les stations sont ferm\u00e9es."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Exercice 3 : stations ferm\u00e9es, journ\u00e9e compl\u00e8te\n",
        "    \n",
        "Appliquer cela \u00e0 une journ\u00e9e compl\u00e8te revient \u00e0 lancer le m\u00eame job sur des donn\u00e9es plus grandes. On verra bient\u00f4t commencer \u00e9viter de recopier le job une seconde fois (introduisant une source potentielle d'erreur)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>attributes</th>\n",
              "      <th>code</th>\n",
              "      <th>alias</th>\n",
              "      <th>folder</th>\n",
              "      <th>size</th>\n",
              "      <th>date</th>\n",
              "      <th>time</th>\n",
              "      <th>name</th>\n",
              "      <th>isdir</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0 </th>\n",
              "      <td> drwx------</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 17:55</td>\n",
              "      <td>                          /user/xavierdupre/.Trash</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1 </th>\n",
              "      <td> drwx------</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:41</td>\n",
              "      <td>                        /user/xavierdupre/.staging</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 132727</td>\n",
              "      <td> 2014-11-16</td>\n",
              "      <td> 02:37</td>\n",
              "      <td> /user/xavierdupre/ConfLongDemo_JSI.small.examp...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-16</td>\n",
              "      <td> 02:38</td>\n",
              "      <td> /user/xavierdupre/ConfLongDemo_JSI.small.examp...</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 461444</td>\n",
              "      <td> 2014-11-20</td>\n",
              "      <td> 01:33</td>\n",
              "      <td> /user/xavierdupre/paris.2014-11-11_22-00-18.33...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-20</td>\n",
              "      <td> 23:43</td>\n",
              "      <td>                        /user/xavierdupre/unitest2</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:42</td>\n",
              "      <td>                        /user/xavierdupre/unittest</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:41</td>\n",
              "      <td>                       /user/xavierdupre/unittest2</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-20</td>\n",
              "      <td> 01:53</td>\n",
              "      <td>                      /user/xavierdupre/velib_1hjs</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9 </th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-21</td>\n",
              "      <td> 01:17</td>\n",
              "      <td>                        /user/xavierdupre/velib_py</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:34</td>\n",
              "      <td>                /user/xavierdupre/velib_py_results</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td> drwxr-xr-x</td>\n",
              "      <td> -</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>      0</td>\n",
              "      <td> 2014-11-21</td>\n",
              "      <td> 11:08</td>\n",
              "      <td>              /user/xavierdupre/velib_several_days</td>\n",
              "      <td>  True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    attributes code        alias       folder    size        date   time  \\\n",
              "0   drwx------    -  xavierdupre  xavierdupre       0  2014-11-23  17:55   \n",
              "1   drwx------    -  xavierdupre  xavierdupre       0  2014-11-23  21:41   \n",
              "2   -rw-r--r--    3  xavierdupre  xavierdupre  132727  2014-11-16  02:37   \n",
              "3   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-16  02:38   \n",
              "4   -rw-r--r--    3  xavierdupre  xavierdupre  461444  2014-11-20  01:33   \n",
              "5   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-20  23:43   \n",
              "6   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-23  21:42   \n",
              "7   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-23  21:41   \n",
              "8   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-20  01:53   \n",
              "9   drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-21  01:17   \n",
              "10  drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-23  21:34   \n",
              "11  drwxr-xr-x    -  xavierdupre  xavierdupre       0  2014-11-21  11:08   \n",
              "\n",
              "                                                 name  isdir  \n",
              "0                            /user/xavierdupre/.Trash   True  \n",
              "1                          /user/xavierdupre/.staging   True  \n",
              "2   /user/xavierdupre/ConfLongDemo_JSI.small.examp...  False  \n",
              "3   /user/xavierdupre/ConfLongDemo_JSI.small.examp...   True  \n",
              "4   /user/xavierdupre/paris.2014-11-11_22-00-18.33...  False  \n",
              "5                          /user/xavierdupre/unitest2   True  \n",
              "6                          /user/xavierdupre/unittest   True  \n",
              "7                         /user/xavierdupre/unittest2   True  \n",
              "8                        /user/xavierdupre/velib_1hjs   True  \n",
              "9                          /user/xavierdupre/velib_py   True  \n",
              "10                 /user/xavierdupre/velib_py_results   True  \n",
              "11               /user/xavierdupre/velib_several_days   True  "
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%dfs_ls /user/xavierdupre/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PIG json_fermee.pig\n",
        "\n",
        "DEFINE pystream `python stream_json.py available_bike_stands available_bikes lat lng name status` \n",
        "   SHIP ('stream_json.py') INPUT(stdin USING PigStreaming(',')) OUTPUT (stdout USING PigStreaming(',')) ;\n",
        "\n",
        "jspy = LOAD '/user/xavierdupre/velib_several_days/*.txt' USING PigStorage('\\t') AS (arow:chararray);\n",
        "\n",
        "matrice = STREAM jspy THROUGH pystream AS \n",
        "                (   available_bike_stands:int, \n",
        "                    available_bikes:int, \n",
        "                    lat:double, \n",
        "                    lng:double, \n",
        "                    name:chararray, \n",
        "                    status:chararray) ;\n",
        "                \n",
        "grstation = GROUP matrice BY status ;  \n",
        "\n",
        "fermees = FOREACH grstation GENERATE\n",
        "                 group\n",
        "                ,SUM(matrice.available_bikes) AS available_bikes\n",
        "                ,SUM(matrice.available_bike_stands) AS available_bike_stands \n",
        "                ;\n",
        "\n",
        "gr_av   = GROUP matrice BY available_bikes ;\n",
        "dist_av = FOREACH gr_av GENERATE group, COUNT(matrice) ;\n",
        "gr_pl   = GROUP matrice BY available_bike_stands ;\n",
        "dist_pl = FOREACH gr_pl GENERATE group, COUNT(matrice) ;\n",
        "\n",
        "STORE fermees INTO 'velib_py_results_3days/fermees.txt' USING PigStorage('\\t') ;\n",
        "STORE dist_av INTO 'velib_py_results_3days/distribution_bikes.txt' USING PigStorage('\\t') ;\n",
        "STORE dist_pl INTO 'velib_py_results_3days/distribution_stands.txt' USING PigStorage('\\t') ;"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xad1ce70>"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%pigsubmit json_fermee.pig stream_json.py redirection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "Total bytes written : 1306\n",
              "Spillable Memory Manager spill count : 0\n",
              "Total bags proactively spilled: 0\n",
              "Total records proactively spilled: 0\n",
              "\n",
              "Job DAG:\n",
              "job_1414491244634_0128\n",
              "\n",
              "\n",
              "2014-11-23 21:55:06,336 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xaaa3490>"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%remote_cmd tail redirection.err"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>attributes</th>\n",
              "      <th>code</th>\n",
              "      <th>alias</th>\n",
              "      <th>folder</th>\n",
              "      <th>size</th>\n",
              "      <th>date</th>\n",
              "      <th>time</th>\n",
              "      <th>name</th>\n",
              "      <th>isdir</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>   0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_bikes.txt/...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 210</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_bikes.txt/...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 208</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_bikes.txt/...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 216</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_bikes.txt/...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>   0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_stands.txt...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 210</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_stands.txt...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 208</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_stands.txt...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> 210</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td> velib_py_results_3days/distribution_stands.txt...</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>   0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td>       velib_py_results_3days/fermees.txt/_SUCCESS</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9 </th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>  20</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td>   velib_py_results_3days/fermees.txt/part-r-00000</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>   0</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td>   velib_py_results_3days/fermees.txt/part-r-00001</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td> -rw-r--r--</td>\n",
              "      <td> 3</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td> xavierdupre</td>\n",
              "      <td>  24</td>\n",
              "      <td> 2014-11-23</td>\n",
              "      <td> 21:54</td>\n",
              "      <td>   velib_py_results_3days/fermees.txt/part-r-00002</td>\n",
              "      <td> False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    attributes code        alias       folder size        date   time  \\\n",
              "0   -rw-r--r--    3  xavierdupre  xavierdupre    0  2014-11-23  21:54   \n",
              "1   -rw-r--r--    3  xavierdupre  xavierdupre  210  2014-11-23  21:54   \n",
              "2   -rw-r--r--    3  xavierdupre  xavierdupre  208  2014-11-23  21:54   \n",
              "3   -rw-r--r--    3  xavierdupre  xavierdupre  216  2014-11-23  21:54   \n",
              "4   -rw-r--r--    3  xavierdupre  xavierdupre    0  2014-11-23  21:54   \n",
              "5   -rw-r--r--    3  xavierdupre  xavierdupre  210  2014-11-23  21:54   \n",
              "6   -rw-r--r--    3  xavierdupre  xavierdupre  208  2014-11-23  21:54   \n",
              "7   -rw-r--r--    3  xavierdupre  xavierdupre  210  2014-11-23  21:54   \n",
              "8   -rw-r--r--    3  xavierdupre  xavierdupre    0  2014-11-23  21:54   \n",
              "9   -rw-r--r--    3  xavierdupre  xavierdupre   20  2014-11-23  21:54   \n",
              "10  -rw-r--r--    3  xavierdupre  xavierdupre    0  2014-11-23  21:54   \n",
              "11  -rw-r--r--    3  xavierdupre  xavierdupre   24  2014-11-23  21:54   \n",
              "\n",
              "                                                 name  isdir  \n",
              "0   velib_py_results_3days/distribution_bikes.txt/...  False  \n",
              "1   velib_py_results_3days/distribution_bikes.txt/...  False  \n",
              "2   velib_py_results_3days/distribution_bikes.txt/...  False  \n",
              "3   velib_py_results_3days/distribution_bikes.txt/...  False  \n",
              "4   velib_py_results_3days/distribution_stands.txt...  False  \n",
              "5   velib_py_results_3days/distribution_stands.txt...  False  \n",
              "6   velib_py_results_3days/distribution_stands.txt...  False  \n",
              "7   velib_py_results_3days/distribution_stands.txt...  False  \n",
              "8         velib_py_results_3days/fermees.txt/_SUCCESS  False  \n",
              "9     velib_py_results_3days/fermees.txt/part-r-00000  False  \n",
              "10    velib_py_results_3days/fermees.txt/part-r-00001  False  \n",
              "11    velib_py_results_3days/fermees.txt/part-r-00002  False  "
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%dfs_ls velib_py_results_3days/*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "On voit que le job a \u00e9t\u00e9 distribu\u00e9 sur trois machines."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Exercice 4 : astuces\n",
        "\n",
        "Les erreurs de PIG ne sont pas tr\u00e8s explicite surtout si elles se produisent dans le script python. Un moyen simple de d\u00e9bugger est d'attraper les exceptions produites par python et de les r\u00e9cup\u00e9rer sous PIG (le reste du job est enlev\u00e9). On peut tout-\u00e0-fait imaginer ajouter la version de python install\u00e9e sur le cluster ainsi que la liste de modules"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PYTHON stream_json_err.py\n",
        "\n",
        "import sys, os\n",
        "for row in sys.stdin:\n",
        "    sys.stdout.write(sys.executable + \"\\n\")\n",
        "    sys.stdout.write(str(sys.version) + \"\\n\")\n",
        "    sys.stdout.write(row + \"\\n\")\n",
        "    # pour obtenir les variables d'environnement\n",
        "    #for k in os.environ:\n",
        "    #    sys.stdout.write(\"%s=%s\\n\" % (k,os.environ[k]))\n",
        "    sys.stdout.flush()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "C:\\Python34\\python.exe\n",
              "3.4.1 (v3.4.1:c0e311e010fc, May 18 2014, 10:38:22) [MSC v.1600 32 bit (Intel)]\n",
              "n'importe quoi\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xaaa5210>"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%%runpy stream_json_err.py\n",
        "n'importe quoi"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%PIG test.pig\n",
        "\n",
        "DEFINE pystream `python stream_json_err.py` \n",
        "   SHIP ('stream_json_err.py') INPUT(stdin USING PigStreaming(',')) OUTPUT (stdout USING PigStreaming(',')) ;\n",
        "\n",
        "jspy = LOAD 'velib_py/*.txt' USING PigStorage('\\t') AS (arow:chararray);\n",
        "one = LIMIT jspy 1 ;\n",
        "info = STREAM one THROUGH pystream AS (row:chararray) ;\n",
        "STORE info INTO 'python_info2.txt' ;"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xaaa5630>"
            ]
          },
          "execution_count": 35,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%pig_submit test.pig stream_json_err.py -r redirection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "2014-11-23 22:07:20,132 [main] INFO  org.apache.hadoop.ipc.Client - Retrying connect to server: dn05.dzr323.dza.datazoomr.com/10.58.223.25:59338. Already tried 1 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=3, sleepTime=1000 MILLISECONDS)\n",
              "2014-11-23 22:07:21,134 [main] INFO  org.apache.hadoop.ipc.Client - Retrying connect to server: dn05.dzr323.dza.datazoomr.com/10.58.223.25:59338. Already tried 2 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=3, sleepTime=1000 MILLISECONDS)\n",
              "2014-11-23 22:07:21,251 [main] INFO  org.apache.hadoop.mapred.ClientServiceDelegate - Application state is completed. FinalApplicationStatus=SUCCEEDED. Redirecting to job history server\n",
              "2014-11-23 22:07:21,471 [main] INFO  org.apache.hadoop.mapred.ClientServiceDelegate - Application state is completed. FinalApplicationStatus=SUCCEEDED. Redirecting to job history server\n",
              "2014-11-23 22:07:21,574 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xaaa5890>"
            ]
          },
          "execution_count": 36,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%remote_cmd tail redirection.pig.err -n 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'python_info2.txt'"
            ]
          },
          "execution_count": 37,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "if os.path.exists(\"python_info2.txt\") : os.remove(\"python_info2.txt\")\n",
        "%remote_down_cluster_merge python_info2.txt python_info2.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<pre>\n",
              "/usr/bin/python\n",
              "2.6.6 (r266:84292\n",
              "[GCC 4.4.7 20120313 (Red Hat 4.4.7-3)]\n",
              "[{'address': 'RUE DES CHAMPEAUX (PRES DE LA GARE ROUTIERE) - 93170 BAGNOLET'\n",
              "\n",
              "\n",
              "</pre>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML at 0xaaa5cf0>"
            ]
          },
          "execution_count": 38,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%head python_info2.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {},
      "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": "3.6.4"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 1
}