HackerNews Challenge.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# HackerNews data analysis challenge with Spark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, you will analyse a dataset of (almost) all submitted HackerNews posts with Spark. Let's start by importing some of the libraries you will need."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
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   "outputs": [
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       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import json\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime as dt\n",
    "\n",
    "# use line of code below when running the code locally. In Databricks, the following line is replaced by display() function\n",
    "# %matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "    word-wrap: break-word;\n",
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       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">&lt;SparkContext master=local[8] appName=Databricks Shell&gt;\n",
       "Ready to go!\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyspark import SparkContext\n",
    "sc = SparkContext.getOrCreate()\n",
    "print(sc)\n",
    "print(\"Ready to go!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file has one JSON entry per line. In order to make accessing it easier, first turn each entry as a dictionary and use `persist()` to cache the resulting RDD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">13</span><span class=\"ansired\">]: </span>PythonRDD[20] at RDD at PythonRDD.scala:56\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset_json = sc.textFile(\"/FileStore/tables/HNStories.json\")\n",
    "\n",
    "# use line of code below if code was run locally\n",
    "# dataset_json = sc.textFile(\"HNStories.json\")\n",
    "\n",
    "dataset = dataset_json.map(lambda x: json.loads(x))\n",
    "dataset.persist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, Spark has many helper functions on top of the ones we have studied which you will find useful. You can view them at [http://spark.apache.org/docs/latest/api/python/pyspark.html#pyspark.RDD](http://spark.apache.org/docs/latest/api/python/pyspark.html#pyspark.RDD)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets start with some initial analysis. \n",
    "* How many elements are in your datasets?\n",
    "* What does the first element look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">Number of elements in datasets 1333789\n",
       "First element: \n",
       " {&apos;author&apos;: &apos;TuxLyn&apos;, &apos;url&apos;: &apos;https://duckduckgo.com/settings&apos;, &apos;objectID&apos;: &apos;7815290&apos;, &apos;created_at&apos;: &apos;2014-05-29T08:25:40Z&apos;, &apos;points&apos;: 1, &apos;title&apos;: &apos;DuckDuckGo Settings&apos;, &apos;num_comments&apos;: 0, &apos;created_at_i&apos;: 1401351940}\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Number of elements in datasets', dataset.count()\n",
    "print('First element: \\n', dataset.first())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each element is a dictionary of attributes and their values for a post. Can you find the set of all attributes used throughout the RDD? The function `dictionary.keys()` gives you the list of attributes of a dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[&apos;created_at_i&apos;, &apos;points&apos;, &apos;story_text&apos;, &apos;objectID&apos;, &apos;title&apos;, &apos;created_at&apos;, &apos;author&apos;, &apos;num_comments&apos;, &apos;story_id&apos;, &apos;url&apos;]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "elements = dataset.flatMap(lambda x: x.keys()).distinct().collect()\n",
    "print(elements)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that there are more attributes than just the one used in the first element. the function `compare_elems` below returns `True` if two elements have exactly the same set of attributes. Can you use it to count the number of elements which have the same set of attributes as the first element?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
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   "outputs": [
    {
     "data": {
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   "source": [
    "# Returns true if two elements have the same schema\n",
    "# first, second is a list\n",
    "\n",
    "def compare_elems(first, second):\n",
    "    if len(first) != len(second):\n",
    "        return False\n",
    "    for key in first:\n",
    "        if key not in second:\n",
    "            return False    \n",
    "    return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">Number of elements which have the same set of attributes as the first element is:  1145245\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "first = dataset.take(1)\n",
    "num_sameElement = (dataset\n",
    "                  .map(lambda x: compare_elems(first[0].keys(), x.keys()))\n",
    "                  .filter(lambda x: x == True)\n",
    "                  .count())\n",
    "\n",
    "print('Number of total elemtn')\n",
    "print('Number of elements which have the same set of attributes as the first element is: ', num_sameElement)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the vast majority of elements hold the same structure. In order to make this analysis easier, redefine `dataset` to only have elements which hold this structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<div class=\"ansiout\">The number of elements in new dataset:  1145245\n",
       "[{&apos;author&apos;: &apos;TuxLyn&apos;, &apos;url&apos;: &apos;https://duckduckgo.com/settings&apos;, &apos;objectID&apos;: &apos;7815290&apos;, &apos;created_at&apos;: &apos;2014-05-29T08:25:40Z&apos;, &apos;points&apos;: 1, &apos;title&apos;: &apos;DuckDuckGo Settings&apos;, &apos;num_comments&apos;: 0, &apos;created_at_i&apos;: 1401351940}, {&apos;author&apos;: &apos;Leynos&apos;, &apos;url&apos;: &apos;http://bits.blogs.nytimes.com/2014/05/28/making-twitter-easier-to-use/&apos;, &apos;objectID&apos;: &apos;7815285&apos;, &apos;created_at&apos;: &apos;2014-05-29T08:23:46Z&apos;, &apos;points&apos;: 1, &apos;title&apos;: &apos;Making Twitter Easier to Use&apos;, &apos;num_comments&apos;: 0, &apos;created_at_i&apos;: 1401351826}, {&apos;author&apos;: &apos;darrhiggs&apos;, &apos;url&apos;: &apos;http://www.bbc.co.uk/news/technology-27617079&apos;, &apos;objectID&apos;: &apos;7815279&apos;, &apos;created_at&apos;: &apos;2014-05-29T08:21:56Z&apos;, &apos;points&apos;: 2, &apos;title&apos;: &apos;London refers Uber app row to High Court&apos;, &apos;num_comments&apos;: 0, &apos;created_at_i&apos;: 1401351716}]\n",
       "<span class=\"ansired\">Out[</span><span class=\"ansired\">178</span><span class=\"ansired\">]: </span>PythonRDD[20] at RDD at PythonRDD.scala:56\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_dataset = dataset.filter(lambda x: compare_elems(first[0].keys(), x.keys())).persist()\n",
    "print('The number of elements in new dataset: ', new_dataset.count())\n",
    "print(new_dataset.take(3))\n",
    "\n",
    "# to avoid RDD overflow to the disk, unpersist unused RDD\n",
    "dataset.unpersist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All of the following tasks are optional, if you want to analyse the dataset in your own way using Spark feel free to do so! The tasks are there as a guide."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 2: How many posts through time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The field `created_at_i` is very useful, it gives you a UNIX timestamp of the time at which the file was created. The following function lets you extract a time from a timestamp."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
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   ],
   "source": [
    "def extract_time(timestamp):\n",
    "    return dt.fromtimestamp(timestamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find the minimum and maximum timestamps in the RDD and call them `min_time` and `max_time`. These correspond to the first and last post, when did they occur?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<div class=\"ansiout\">[datetime.datetime(2014, 5, 29, 8, 25, 40), datetime.datetime(2014, 5, 29, 8, 23, 46), datetime.datetime(2014, 5, 29, 8, 21, 56), datetime.datetime(2014, 5, 29, 8, 18, 42), datetime.datetime(2014, 5, 29, 8, 17, 30)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_RDD = new_dataset.map(lambda x: extract_time(x['created_at_i']))\n",
    "min_time = time_RDD.min()\n",
    "max_time = time_RDD.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true,
    "scrolled": true
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   "outputs": [
    {
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       "<style scoped>\n",
       "  .ansiout {\n",
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       "<div class=\"ansiout\">2006-10-09 18:21:51\n",
       "2014-05-29 08:25:40\n",
       "</div>"
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(min_time)\n",
    "print(max_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets analyse how many elements through time. The following function assigns a record to one of 200 \"buckets\" of time. Use it to count the number of elements that fall within each bucket and call the result `bucket_rdd`. The result should be such that `buckets` below generates the corresponding output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  .ansiout {\n",
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       "<div class=\"ansiout\"></div>"
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_time = dt.timestamp(min_time)\n",
    "max_time = dt.timestamp(max_time)\n",
    "interval = (max_time - min_time + 1) / 200.0\n",
    "\n",
    "def get_bucket(rec):\n",
    "    return int((rec['created_at_i'] - min_time) / interval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
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   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
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       "    word-wrap: break-word;\n",
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       "<div class=\"ansiout\"></div>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from operator import add\n",
    "\n",
    "buckets_rdd = new_dataset.map(lambda x: (get_bucket(x), 1)).reduceByKey(add)\n",
    "# print(buckets_rdd.take(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
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       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(0, 46), (4, 1), (9, 265), (10, 703), (11, 696), (12, 183), (13, 870), (14, 940), (15, 865), (16, 657), (17, 653), (18, 610), (19, 545), (20, 594), (21, 755), (22, 879), (23, 979), (24, 936), (25, 996), (26, 470), (33, 1022), (34, 1712), (35, 1818), (36, 1691), (37, 2069), (38, 2258), (39, 2161), (40, 2210), (41, 2220), (42, 2210), (43, 2374), (44, 2377), (45, 2464), (46, 2536), (47, 2504), (48, 2427), (49, 2427), (50, 2379), (51, 2677), (52, 2511), (53, 2716), (54, 2555), (55, 2504), (56, 2645), (57, 2199), (58, 2437), (59, 2955), (60, 3155), (61, 3089), (62, 3031), (63, 3229), (64, 3066), (65, 2988), (66, 3399), (67, 3206), (68, 2995), (69, 3073), (70, 3083), (71, 652), (83, 2170), (84, 3339), (85, 4708), (86, 5191), (87, 5396), (88, 5436), (89, 5185), (90, 4880), (91, 4883), (92, 5623), (93, 5723), (94, 5784), (95, 5299), (96, 5176), (97, 5096), (98, 5403), (99, 5393), (100, 5486), (101, 5741), (102, 5639), (103, 6206), (104, 6508), (105, 6412), (106, 6716), (107, 7249), (108, 6922), (109, 7446), (110, 5895), (111, 7619), (112, 7921), (113, 8014), (114, 7983), (115, 8304), (116, 8758), (117, 8504), (118, 8013), (119, 7879), (120, 7861), (121, 7970), (122, 7972), (123, 8105), (124, 8102), (125, 8896), (126, 9315), (127, 9454), (128, 10048), (129, 11161), (130, 11793), (131, 10767), (132, 12017), (133, 12504), (134, 11844), (135, 10189), (136, 8336), (137, 10165), (138, 10673), (139, 10306), (140, 9982), (141, 10420), (142, 11184), (143, 11302), (144, 11360), (145, 10999), (146, 10807), (147, 10756), (148, 10256), (149, 10028), (150, 10177), (151, 10379), (152, 10402), (153, 9540), (154, 9241), (155, 9603), (156, 9446), (157, 9282), (158, 9265), (159, 9830), (160, 9660), (161, 10526), (162, 8091), (163, 9642), (164, 10683), (165, 11483), (166, 11196), (167, 11400), (168, 11453), (169, 10947), (170, 10823), (171, 10627), (172, 10505), (173, 10372), (174, 11366), (175, 10962), (176, 10369), (177, 10444), (178, 10419), (179, 10608), (180, 10215), (181, 10703), (182, 10879), (183, 10574), (184, 10992), (185, 11592), (186, 10287), (187, 9729), (188, 8305), (189, 7708), (190, 9714), (191, 9643), (192, 9428), (193, 9522), (194, 9356), (195, 10491), (196, 9157), (197, 8873), (198, 8903), (199, 8294)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use this to test your result\n",
    "buckets = sorted(buckets_rdd.collect())\n",
    "print(buckets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then use this to plot the number of submitted posts over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bs = [dt.fromtimestamp(x[0]*interval + min_time) for x in buckets]\n",
    "ts = [x[1] for x in buckets]\n",
    "plt.plot(bs, ts)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "The following function gets the hour of the day at which a post was submitted. Use it to find the number of posts submitted at each hour of the day. The value of `hours_buckets` should match the one printed below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_hour(rec):\n",
    "    t = dt.fromtimestamp(rec['created_at_i'])\n",
    "    return t.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hours_buckets_rdd = new_dataset.map(lambda x: (get_hour(x), 1)).reduceByKey(add)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(0, 38636), (1, 36761), (2, 34940), (3, 33531), (4, 31730), (5, 30435), (6, 30320), (7, 29856), (8, 29910), (9, 30453), (10, 32045), (11, 37158), (12, 46490), (13, 58537), (14, 68421), (15, 73554), (16, 75936), (17, 75641), (18, 72235), (19, 66127), (20, 62096), (21, 57582), (22, 49808), (23, 43043)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hours_buckets = sorted(hours_buckets_rdd.collect())\n",
    "print(hours_buckets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hrs = [x[0] for x in hours_buckets]\n",
    "sz = [x[1] for x in hours_buckets]\n",
    "\n",
    "# used for clearing the previous plot so it does not overlapped (in Databricks )\n",
    "plt.close()\n",
    "plt.plot(hrs, sz)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of points scored by a post is under the attribute `points`. Use it to compute the average score received by submissions for each hour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">114</span><span class=\"ansired\">]: </span>\n",
       "[{&apos;author&apos;: &apos;TuxLyn&apos;,\n",
       "  &apos;url&apos;: &apos;https://duckduckgo.com/settings&apos;,\n",
       "  &apos;objectID&apos;: &apos;7815290&apos;,\n",
       "  &apos;created_at&apos;: &apos;2014-05-29T08:25:40Z&apos;,\n",
       "  &apos;points&apos;: 1,\n",
       "  &apos;title&apos;: &apos;DuckDuckGo Settings&apos;,\n",
       "  &apos;num_comments&apos;: 0,\n",
       "  &apos;created_at_i&apos;: 1401351940}]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#what the data looks like\n",
    "new_dataset.take(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_per_hour_rdd = (new_dataset\n",
    "                   .map(lambda x: (get_hour(x), x['points']))\n",
    "                   .reduceByKey(add)\n",
    "                   .join(hours_buckets_rdd)\n",
    "                   .mapValues(lambda x: x[0]/x[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(0, 10.864426959312558), (1, 10.510350643344848), (2, 10.087779049799657), (3, 10.037338582207509), (4, 9.748975732745036), (5, 9.629209791358633), (6, 8.586378627968339), (7, 8.980807877813504), (8, 9.199197592778335), (9, 9.49666699504154), (10, 10.108878140115463), (11, 10.891355831853167), (12, 10.954140675414067), (13, 11.131557818132121), (14, 10.737668259744815), (15, 10.277877477771433), (16, 10.42850558364939), (17, 10.822318583836807), (18, 10.833930919914168), (19, 10.958867028596488), (20, 10.396080262818861), (21, 10.65820916258553), (22, 10.575108416318663), (23, 10.677880259275607)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_per_hour = sorted(scores_per_hour_rdd.collect())\n",
    "print(scores_per_hour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hrs = [x[0] for x in scores_per_hour]\n",
    "sz = [x[1] for x in scores_per_hour]\n",
    "plt.close()\n",
    "plt.plot(hrs, sz)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It may be more useful to look at sucessful posts that get over 200 points. Find the proportion of posts that get above 200 points per hour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prop_per_hour_rdd = (new_dataset\n",
    "                   .filter(lambda x: x['points'] > 200)\n",
    "                   .map(lambda x: (get_hour(x), 1))\n",
    "                   .reduceByKey(add)\n",
    "                   .join(hours_buckets_rdd)\n",
    "                   .mapValues(lambda x: x[0]/x[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(0, 0.008411843876177659), (1, 0.007127118413536085), (2, 0.007412707498568975), (3, 0.007038263099818079), (4, 0.006586826347305389), (5, 0.006735666173813044), (6, 0.006299472295514512), (7, 0.0070002679528403), (8, 0.007154797726512872), (9, 0.007125734738777789), (10, 0.007489467935715401), (11, 0.008477313095430325), (12, 0.00905571090557109), (13, 0.009395766779985309), (14, 0.008915391473378057), (15, 0.008415585828099084), (16, 0.008652022756005058), (17, 0.008910511495088643), (18, 0.009081470201425901), (19, 0.008967592662603777), (20, 0.007891007472300954), (21, 0.008058073703587926), (22, 0.007709604882749759), (23, 0.007806147341031062)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prop_per_hour = sorted(prop_per_hour_rdd.collect())\n",
    "print(prop_per_hour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hrs = [x[0] for x in prop_per_hour]\n",
    "sz = [x[1] for x in prop_per_hour]\n",
    "plt.close()\n",
    "plt.plot(hrs, sz)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function lists the word in the title. Use it to count the number of words in the title of each post, and look at the proportion of successful posts for each title length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import re\n",
    "def get_words(line):\n",
    "    return re.compile('\\w+').findall(line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_success = new_dataset.filter(lambda x: x['points'] > 200).count()\n",
    "\n",
    "prop_per_title_length_rdd = (new_dataset\n",
    "                             .filter(lambda x: x['points'] > 200)\n",
    "                             .map(lambda x: (len(get_words(x['title'])), 1))\n",
    "                             .reduceByKey(add)\n",
    "                             .mapValues(lambda x: x / num_success))                         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(1, 0.014781491002570694), (2, 0.03963153384747215), (3, 0.06694515852613539), (4, 0.09393744644387318), (5, 0.11300342759211654), (6, 0.1063624678663239), (7, 0.10839760068551842), (8, 0.10143530419880034), (9, 0.0921165381319623), (10, 0.07722793487574979), (11, 0.06276778063410454), (12, 0.04937874892887746), (13, 0.037917737789203085), (14, 0.017673521850899744), (15, 0.011568123393316195), (16, 0.005141388174807198), (17, 0.0012853470437017994), (18, 0.00032133676092544985), (19, 0.00010711225364181663)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prop_per_title_length = sorted(prop_per_title_length_rdd.collect())\n",
    "print(prop_per_title_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hrs = [x[0] for x in prop_per_title_length]\n",
    "sz = [x[1] for x in prop_per_title_length]\n",
    "plt.close()\n",
    "plt.plot(hrs, sz)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets compare this with the distribution of number of words. Count for each title length the number of submissions with that length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "submissions_per_length_rdd = (new_dataset\n",
    "                              .map(lambda x: (len(get_words(x['title'])), 1))\n",
    "                              .reduceByKey(add))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(0, 1872), (1, 8286), (2, 27724), (3, 60100), (4, 87779), (5, 116065), (6, 135970), (7, 144269), (8, 139418), (9, 123801), (10, 102534), (11, 78129), (12, 54170), (13, 34005), (14, 17604), (15, 8289), (16, 3329), (17, 1195), (18, 387), (19, 164), (20, 65), (21, 33), (22, 8), (23, 13), (24, 12), (25, 7), (26, 7), (27, 2), (28, 1), (29, 3), (30, 2), (36, 1), (38, 1)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "submissions_per_length = sorted(submissions_per_length_rdd.collect())\n",
    "print(submissions_per_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hrs = [x[0] for x in submissions_per_length]\n",
    "sz = [x[1] for x in submissions_per_length]\n",
    "plt.close()\n",
    "plt.plot(hrs, sz)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like most people are getting it wrong!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "For this task, you will need a new function: `takeOrdered()`. Like `take()` it collects elements from an RDD. However, it can be applied the smalles elements. For example, `takeOrdered(10)` returns the 10 smallest elements. Furthermore, you can pass it a function to specify the way in which the elements should be ordered. For example, `takeOrdered(10, lambda x: -x)` will return the 10 largest elements.\n",
    "\n",
    "The function below extracts the url domain out of a record. Use it to count the number of distinct domains posted to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">duckduckgo.com\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from urllib.parse import urlparse\n",
    "def get_domain(rec):\n",
    "    url = urlparse(rec['url']).netloc\n",
    "    if url[0:4] == 'www.':\n",
    "        return url[4:]\n",
    "    else:\n",
    "        return url\n",
    "print(get_domain(new_dataset.take(1)[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">Number of distinct domain 90\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distinct_domain = (new_dataset\n",
    "                   .flatMap(lambda x: get_domain(x))\n",
    "                   .distinct()\n",
    "                   .count())\n",
    "\n",
    "print('Number of distinct domain', distinct_domain)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using `takeOrdered()` find the 25 most popular domains posted to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top25 = (new_dataset\n",
    "         .map(lambda x: (get_domain(x), 1))\n",
    "         .reduceByKey(add)\n",
    "         .takeOrdered(25, key= lambda x: -x[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(&apos;techcrunch.com&apos;, 22483), (&apos;youtube.com&apos;, 16783), (&apos;github.com&apos;, 16084), (&apos;nytimes.com&apos;, 14091), (&apos;arstechnica.com&apos;, 10654), (&apos;wired.com&apos;, 8332), (&apos;bbc.co.uk&apos;, 6914), (&apos;medium.com&apos;, 6291), (&apos;mashable.com&apos;, 5937), (&apos;businessinsider.com&apos;, 5495), (&apos;thenextweb.com&apos;, 5447), (&apos;online.wsj.com&apos;, 5374), (&apos;venturebeat.com&apos;, 5306), (&apos;en.wikipedia.org&apos;, 5247), (&apos;readwriteweb.com&apos;, 5223), (&apos;forbes.com&apos;, 5050), (&apos;gigaom.com&apos;, 4931), (&apos;theverge.com&apos;, 4358), (&apos;news.cnet.com&apos;, 4202), (&apos;theatlantic.com&apos;, 3966), (&apos;guardian.co.uk&apos;, 3945), (&apos;economist.com&apos;, 3827), (&apos;washingtonpost.com&apos;, 3402), (&apos;engadget.com&apos;, 3287), (&apos;technologyreview.com&apos;, 2994)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(top25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "index = np.arange(25)\n",
    "labels = [x[0] for x in top25]\n",
    "counts = np.array([x[1] for x in top25]) * 100.0/dataset.count()\n",
    "plt.close()\n",
    "plt.xticks(index,labels, rotation='vertical')\n",
    "plt.bar(index, counts, 0.5)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create an pair RDD with 26 elements mapping each of these 25 popular domains with the average score received by the corresponding submissions as well as an `other` field for all submissions to other domains."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def map_to_domain(rec):\n",
    "    domain = get_domain(rec)\n",
    "    if domain in dict(top25):\n",
    "        return domain\n",
    "    else:\n",
    "        return 'other'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domain_count = (new_dataset\n",
    "                .map(lambda x: (map_to_domain(x), 1))\n",
    "                .reduceByKey(add)\n",
    "                .cache())\n",
    "\n",
    "domain_av_score_rdd = (new_dataset\n",
    "                       .map(lambda x: (map_to_domain(x), x['points']))\n",
    "                       .reduceByKey(add)\n",
    "                       .join(domain_count)\n",
    "                       .mapValues(lambda x: x[0] / x[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(&apos;other&apos;, 10.436019477600967), (&apos;nytimes.com&apos;, 14.112696047122277), (&apos;theverge.com&apos;, 4.373106929784305), (&apos;en.wikipedia.org&apos;, 10.312750142938823), (&apos;technologyreview.com&apos;, 8.105878423513694), (&apos;news.cnet.com&apos;, 9.018086625416469), (&apos;venturebeat.com&apos;, 7.508480964945345), (&apos;washingtonpost.com&apos;, 17.386831275720166), (&apos;economist.com&apos;, 11.029004442121767), (&apos;youtube.com&apos;, 3.738127867484955), (&apos;thenextweb.com&apos;, 11.297411419129796), (&apos;bbc.co.uk&apos;, 11.377928840034713), (&apos;medium.com&apos;, 8.341281195358448), (&apos;mashable.com&apos;, 5.164392790971871), (&apos;readwriteweb.com&apos;, 6.566724104920544), (&apos;gigaom.com&apos;, 8.187385925775704), (&apos;arstechnica.com&apos;, 14.169326074713723), (&apos;guardian.co.uk&apos;, 5.3776932826362485), (&apos;theatlantic.com&apos;, 15.751386787695411), (&apos;techcrunch.com&apos;, 12.69706000088956), (&apos;wired.com&apos;, 13.367618819011042), (&apos;github.com&apos;, 14.577095249937827), (&apos;online.wsj.com&apos;, 10.287309266840342), (&apos;forbes.com&apos;, 9.52990099009901), (&apos;engadget.com&apos;, 8.233951931852753), (&apos;businessinsider.com&apos;, 4.3887170154686075)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domain_av_score = domain_av_score_rdd.collect()\n",
    "print(domain_av_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "index26 = np.arange(26)\n",
    "labels = [x[0] for x in top25]\n",
    "labels.append('other')\n",
    "vals = np.array([dict(domain_av_score)[x] for x in labels])\n",
    "plt.close()\n",
    "plt.xticks(index26, labels, rotation='vertical')\n",
    "plt.bar(index26, vals, 0.5)\n",
    "display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now compute the proportion of successes for each domain (over 200 points)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">180</span><span class=\"ansired\">]: </span>\n",
       "{&apos;author&apos;: &apos;TuxLyn&apos;,\n",
       " &apos;url&apos;: &apos;https://duckduckgo.com/settings&apos;,\n",
       " &apos;objectID&apos;: &apos;7815290&apos;,\n",
       " &apos;created_at&apos;: &apos;2014-05-29T08:25:40Z&apos;,\n",
       " &apos;points&apos;: 1,\n",
       " &apos;title&apos;: &apos;DuckDuckGo Settings&apos;,\n",
       " &apos;num_comments&apos;: 0,\n",
       " &apos;created_at_i&apos;: 1401351940}\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_dataset.first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\"></div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domain_prop_rdd = (new_dataset\n",
    "                  .filter(lambda x: x['points'] > 200)\n",
    "                  .map(lambda x: (map_to_domain(x), 1))\n",
    "                  .reduceByKey(add)\n",
    "                  .join(domain_count)\n",
    "                  .mapValues(lambda x: x[0] / x[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "  .ansiout {\n",
       "    display: block;\n",
       "    unicode-bidi: embed;\n",
       "    white-space: pre-wrap;\n",
       "    word-wrap: break-word;\n",
       "    word-break: break-all;\n",
       "    font-family: \"Source Code Pro\", \"Menlo\", monospace;;\n",
       "    font-size: 13px;\n",
       "    color: #555;\n",
       "    margin-left: 4px;\n",
       "    line-height: 19px;\n",
       "  }\n",
       "</style>\n",
       "<div class=\"ansiout\">[(&apos;other&apos;, 0.008386304371689957), (&apos;nytimes.com&apos;, 0.009793485203321269), (&apos;theverge.com&apos;, 0.0016062413951353832), (&apos;en.wikipedia.org&apos;, 0.00952925481227368), (&apos;technologyreview.com&apos;, 0.003006012024048096), (&apos;news.cnet.com&apos;, 0.005235602094240838), (&apos;venturebeat.com&apos;, 0.00395778364116095), (&apos;washingtonpost.com&apos;, 0.018224573780129337), (&apos;economist.com&apos;, 0.004180820486020381), (&apos;youtube.com&apos;, 0.0019066912947625573), (&apos;thenextweb.com&apos;, 0.008077841013401872), (&apos;bbc.co.uk&apos;, 0.007810240092565809), (&apos;medium.com&apos;, 0.008583690987124463), (&apos;mashable.com&apos;, 0.0016843523665150749), (&apos;readwriteweb.com&apos;, 0.002106069308826345), (&apos;gigaom.com&apos;, 0.0038531737984181707), (&apos;arstechnica.com&apos;, 0.011169513797634692), (&apos;guardian.co.uk&apos;, 0.0017743979721166034), (&apos;theatlantic.com&apos;, 0.014120020171457387), (&apos;techcrunch.com&apos;, 0.00587110261086154), (&apos;wired.com&apos;, 0.00972155544887182), (&apos;github.com&apos;, 0.01255906490922656), (&apos;online.wsj.com&apos;, 0.005582433941198363), (&apos;forbes.com&apos;, 0.007722772277227723), (&apos;engadget.com&apos;, 0.003954974140553696), (&apos;businessinsider.com&apos;, 0.0018198362147406734)]\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domain_prop = domain_prop_rdd.collect()\n",
    "print(domain_prop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "index26 = np.arange(26)\n",
    "labels = [x[0] for x in top25]\n",
    "labels.append('other')\n",
    "vals = np.array([dict(domain_prop)[x] for x in labels])\n",
    "plt.close()\n",
    "plt.xticks(index26, labels, rotation='vertical')\n",
    "plt.bar(index26, vals, 0.5)\n",
    "display()"
   ]
  }
 ],
 "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": "3.6.8"
  },
  "name": "HackerNews Challenge",
  "notebookId": 4251968096026468
 },
 "nbformat": 4,
 "nbformat_minor": 1
}