data/examples/solr-hdp-spark-recommender.ipynb

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   "source": [
    "# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n",
    "# not use this file except in compliance with the License. You may obtain\n",
    "# a copy of the License at\n",
    "#\n",
    "#      http://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n",
    "# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n",
    "# License for the specific language governing permissions and limitations\n",
    "# under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "# Creating a Scalable Recommender with Apache Spark & Apache Solr\n",
    "\n",
    "In this notebook, you will create a recommendation engine using Spark and Solr. Using some movie rating data,\n",
    "you will train a collaborative filtering model in Spark and export the trained model to Solr. Once exported, \n",
    "you can test your recommendations by querying Solr and displaying the results.\n",
    "\n",
    "### _Prerequisites_\n",
    "\n",
    "The notebook assumes you have installed Solr, the Solr vector-scoring plugin, Apache Spark and the Solr Spark connector detailed in the [setup steps](https://github.com/MLnick/elasticsearch-spark-recommender-demo/tree/master#steps).\n",
    "\n",
    "> _Optional:_\n",
    "\n",
    "> In order to display the images in the recommendation demo, you will need to access [The Movie Database (TMdb) API](https://www.themoviedb.org/documentation/api). Please follow the [instructions](https://developers.themoviedb.org/3/getting-started) to get an API key.\n",
    "\n",
    "## Overview\n",
    "\n",
    "You will work through the following steps\n",
    "\n",
    "1. Prepare the data\n",
    "2. Use the Solr Spark connector to save it to Solr\n",
    "3. Load ratings data and train a collaborative filtering recommendation model using Spark MLlib\n",
    "3. Save the model to Solr\n",
    "4. Show recommendations using Solr vector scoring plugin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "## Step 1: Prepare the data\n",
    "\n",
    "* This notebook uses the \"small\" version of the latest MovieLens movie rating dataset, containing about 100,000 ratings, 9,000 movies and 700 users\n",
    "* The latest version of the data can be downloaded at https://grouplens.org/datasets/movielens/latest/\n",
    "* Download the `ml-latest-small.zip` file and unzip it to a suitable location on your system.\n",
    "\n",
    "The folder should contain a number of CSV files. We will be using the following files:\n",
    "* `ratings.csv` - movie rating data\n",
    "* `links.csv` - external database ids for each movie\n",
    "* `movies.csv` - movie title and genres"
   ]
  },
  {
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       "['Requirement already satisfied: simplejson in /user-home/1001/.local/lib/python2.7/site-packages (3.15.0)',\n",
       " \"mxnet 1.1.0 has requirement numpy<=1.13.3, but you'll have numpy 1.14.1 which is incompatible.\"]"
      ]
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     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "!!pip install tmdbsimple --user\n",
    "!!pip install solrcloudpy --user\n",
    "!!pip install simplejson --user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sparkmagic.magics extension is already loaded. To reload it, use:\n",
      "  %reload_ext sparkmagic.magics\n",
      "success configuring sparkmagic livy.\n"
     ]
    }
   ],
   "source": [
    "%load_ext sparkmagic.magics\n",
    "import dsx_core_utils\n",
    "dsx_core_utils.setup_livy_sparkmagic()\n",
    "%reload_ext sparkmagic.magics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%spark delete -s $edgenode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting Spark application\n"
     ]
    },
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       "<table>\n",
       "<tr><th>ID</th><th>YARN Application ID</th><th>Kind</th><th>State</th><th>Spark UI</th><th>Driver log</th><th>Current session?</th></tr><tr><td>68</td><td>application_1528313432729_0007</td><td>pyspark</td><td>idle</td><td><a target=\"_blank\" href=\"http://db-hdp2642.fyre.ibm.com:8088/proxy/application_1528313432729_0007/\">Link</a></td><td><a target=\"_blank\" href=\"http://db-hdp2642.fyre.ibm.com:8042/node/containerlogs/container_e15_1528313432729_0007_01_000001/user1\">Link</a></td><td>✔</td></tr></table>"
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       "<IPython.core.display.HTML object>"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SparkSession available as 'spark'.\n"
     ]
    }
   ],
   "source": [
    "edgenode=\"PROVIDE_HOST_NAME_OF_EDGE_SERVER\"\n",
    "dsxhiURL=\"PROVIDE_DSXHI_URL\"\n",
    "webhdfsURL=dsxhiURL + \"webhdfs/v1/\"\n",
    "livyURL=dsxhiURL + \"livy/v1/\"\n",
    "livy2URL=dsxhiURL + \"livy2/v1/\"\n",
    "\n",
    "%spark add -s $edgenode -l python -u $livy2URL"
   ]
  },
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   "source": [
    "# first import a few utility methods that we'll use later on\n",
    "from IPython.display import Image, HTML, display\n",
    "from urllib2 import *\n",
    "import simplejson as json\n",
    "import requests as requests\n",
    "import sys\n",
    "from solrcloudpy.connection import SolrConnection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pyspark.sql.session.SparkSession object at 0x3062690>"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# first import a few utility methods that we'll use later on\n",
    "from IPython.display import Image, HTML, display\n",
    "from urllib2 import *\n",
    "import simplejson as json\n",
    "import requests as requests\n",
    "import sys\n",
    "import paramiko\n",
    "from solrcloudpy.connection import SolrConnection\n",
    "# check PySpark is running\n",
    "spark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Load rating and movie data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Ratings**\n",
    "\n",
    "The ratings data consists of around 100,000 ratings given by users to movies. Each row of the `DataFrame` consists of a `userId`, `movieId` and `timestamp` for the event, together with the `rating` given by the user to the movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
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   "source": [
    "%%spark\n",
    "# if you unzipped the data to a different location than that specified in the Journey setup steps\n",
    "# you can change the path below to point to the correct location\n",
    "PATH_TO_DATA = \"PATH_TO_YOUR_DATA\"\n",
    "# load ratings data\n",
    "ratings = spark.read.csv(PATH_TO_DATA + \"/ratings.csv\", header=True, inferSchema=True)\n",
    "ratings.cache()\n",
    "print(\"Number of ratings: %i\" % ratings.count())\n",
    "print(\"Sample of ratings:\")\n",
    "ratings.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "You will see that the `timestamp` field is a UNIX timestamp in seconds. In the following cell, a spark built-in function `from_unix_timestap` is called to convert the timestamp to the format solr acccepts. More information on splr date formats can be found in https://lucene.apache.org/solr/guide/6_6/working-with-dates.html "
   ]
  },
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   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------+-------+------+-------------------+\n",
      "|userId|movieId|rating|          timestamp|\n",
      "+------+-------+------+-------------------+\n",
      "|     1|     31|   2.5|2009-12-13 18:52:24|\n",
      "|     1|   1029|   3.0|2009-12-13 18:52:59|\n",
      "|     1|   1061|   3.0|2009-12-13 18:53:02|\n",
      "|     1|   1129|   2.0|2009-12-13 18:53:05|\n",
      "|     1|   1172|   4.0|2009-12-13 18:53:25|\n",
      "+------+-------+------+-------------------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "from pyspark.sql import functions as F\n",
    "ratings = ratings.select(\"userId\", \"movieId\", \"rating\", F.from_unixtime(\"timestamp\").alias(\"timestamp\"))\n",
    "ratings.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Movies**\n",
    "\n",
    "The file `movies.csv` contains the `movieId`, `title` and `genres` for each movie. As you can see, the `genres` field is a bit tricky to use, as the genres are in the form of one string delimited by the `|` character: `Adventure|Animation|Children|Comedy|Fantasy`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Raw movie data:\n",
      "+-------+----------------------------------+-------------------------------------------+\n",
      "|movieId|title                             |genres                                     |\n",
      "+-------+----------------------------------+-------------------------------------------+\n",
      "|1      |Toy Story (1995)                  |Adventure|Animation|Children|Comedy|Fantasy|\n",
      "|2      |Jumanji (1995)                    |Adventure|Children|Fantasy                 |\n",
      "|3      |Grumpier Old Men (1995)           |Comedy|Romance                             |\n",
      "|4      |Waiting to Exhale (1995)          |Comedy|Drama|Romance                       |\n",
      "|5      |Father of the Bride Part II (1995)|Comedy                                     |\n",
      "+-------+----------------------------------+-------------------------------------------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# load raw data from CSV\n",
    "raw_movies = spark.read.csv(PATH_TO_DATA + \"/movies.csv\", header=True, inferSchema=True)\n",
    "print(\"Raw movie data:\")\n",
    "raw_movies.show(5, truncate=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Create a `DataFrame` user-defined function (UDF) to extract this delimited string into a list of genres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------+----------------------------------+-------------------------------------------------+\n",
      "|movieId|title                             |genres                                           |\n",
      "+-------+----------------------------------+-------------------------------------------------+\n",
      "|1      |Toy Story (1995)                  |[adventure, animation, children, comedy, fantasy]|\n",
      "|2      |Jumanji (1995)                    |[adventure, children, fantasy]                   |\n",
      "|3      |Grumpier Old Men (1995)           |[comedy, romance]                                |\n",
      "|4      |Waiting to Exhale (1995)          |[comedy, drama, romance]                         |\n",
      "|5      |Father of the Bride Part II (1995)|[comedy]                                         |\n",
      "+-------+----------------------------------+-------------------------------------------------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "from pyspark.sql.functions import udf\n",
    "from pyspark.sql.types import *\n",
    "# define a UDF to convert the raw genres string to an array of genres and lowercase\n",
    "extract_genres = udf(lambda x: x.lower().split(\"|\"), ArrayType(StringType()))\n",
    "# test it out\n",
    "raw_movies.select(\"movieId\", \"title\", extract_genres(\"genres\").alias(\"genres\")).show(5, False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Ok, that looks better!\n",
    "\n",
    "You may also notice that the movie titles contain the year of release. It would be useful to have that as a field in your search index for filtering results (say you want to filter our recommendations to include only more recent movies).\n",
    "\n",
    "Create a UDF to extract the release year from the title using a Python regular expression."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Jumanji', '1995')"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "import re\n",
    "# define a UDF to extract the release year from the title, and return the new title and year in a struct type\n",
    "def extract_year_fn(title):\n",
    "    result = re.search(\"\\(\\d{4}\\)\", title)\n",
    "    try:\n",
    "        if result:\n",
    "            group = result.group()\n",
    "            year = group[1:-1]\n",
    "            start_pos = result.start()\n",
    "            title = title[:start_pos-1]\n",
    "            return (title, year)\n",
    "        else:\n",
    "            return (title, 1970)\n",
    "    except:\n",
    "        print(title)\n",
    "\n",
    "extract_year = udf(extract_year_fn,\\\n",
    "                   StructType([StructField(\"title\", StringType(), True),\\\n",
    "                               StructField(\"release_date\", StringType(), True)]))\n",
    "    \n",
    "# test out our function\n",
    "s = \"Jumanji (1995)\"\n",
    "extract_year_fn(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Ok the function works! Now create a new `DataFrame` with the cleaned-up titles, release dates and genres of the movies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cleaned movie data:\n",
      "+-------+---------------------------+------------+-------------------------------------------------+\n",
      "|movieId|title                      |release_date|genres                                           |\n",
      "+-------+---------------------------+------------+-------------------------------------------------+\n",
      "|1      |Toy Story                  |1995        |[adventure, animation, children, comedy, fantasy]|\n",
      "|2      |Jumanji                    |1995        |[adventure, children, fantasy]                   |\n",
      "|3      |Grumpier Old Men           |1995        |[comedy, romance]                                |\n",
      "|4      |Waiting to Exhale          |1995        |[comedy, drama, romance]                         |\n",
      "|5      |Father of the Bride Part II|1995        |[comedy]                                         |\n",
      "+-------+---------------------------+------------+-------------------------------------------------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "movies = raw_movies.select(\n",
    "    \"movieId\", extract_year(\"title\").title.alias(\"title\"),\\\n",
    "    extract_year(\"title\").release_date.alias(\"release_date\"),\\\n",
    "    extract_genres(\"genres\").alias(\"genres\"))\n",
    "print(\"Cleaned movie data:\")\n",
    "movies.show(5, truncate=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Next, join the `links.csv` data to `movies` so that there is an id for _The Movie Database_ corresponding to each movie. You can use this id to retrieve movie poster images when displaying your recommendations later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cleaned movie data with tmdbId links:\n",
      "+-------+---------------------------+------------+-------------------------------------------------+------+\n",
      "|movieId|title                      |release_date|genres                                           |tmdbId|\n",
      "+-------+---------------------------+------------+-------------------------------------------------+------+\n",
      "|1      |Toy Story                  |1995        |[adventure, animation, children, comedy, fantasy]|862   |\n",
      "|2      |Jumanji                    |1995        |[adventure, children, fantasy]                   |8844  |\n",
      "|3      |Grumpier Old Men           |1995        |[comedy, romance]                                |15602 |\n",
      "|4      |Waiting to Exhale          |1995        |[comedy, drama, romance]                         |31357 |\n",
      "|5      |Father of the Bride Part II|1995        |[comedy]                                         |11862 |\n",
      "+-------+---------------------------+------------+-------------------------------------------------+------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "link_data = spark.read.csv(PATH_TO_DATA + \"/links.csv\", header=True, inferSchema=True)\n",
    "# join movies with links to get TMDB id\n",
    "movie_data = movies.join(link_data, movies.movieId == link_data.movieId)\\\n",
    "    .select(movies.movieId, movies.title, movies.release_date, movies.genres, link_data.tmdbId)\n",
    "num_movies = movie_data.count()\n",
    "print(\"Cleaned movie data with tmdbId links:\")\n",
    "movie_data.show(5, truncate=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "> **_Optional_**\n",
    "\n",
    "> Run the below cell to test your access to TMDb API. You should see the _Toy Story_ movie poster displayed inline.\n",
    "\n",
    "> To install the Python package run `pip install tmdbsimple`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "hide_input": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully imported tmdbsimple!"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "try:\n",
    "    import tmdbsimple as tmdb\n",
    "    # replace this variable with your actual TMdb API key\n",
    "    tmdb.API_KEY='YOUR_TMDB_API_KEY'\n",
    "    print(\"Successfully imported tmdbsimple!\")\n",
    "    # base URL for TMDB poster images\n",
    "    IMAGE_URL = 'https://image.tmdb.org/t/p/w500'\n",
    "    movie_id = movie_data.first().tmdbId\n",
    "    movie_info = tmdb.Movies(movie_id).info()\n",
    "    movie_poster_url = IMAGE_URL + movie_info['poster_path']\n",
    "    # display(Image(movie_poster_url, width=200))\n",
    "    selectQuery = \"SELECT '%s'\" % (movie_poster_url)\n",
    "    poster_df = spark.sql(selectQuery)\n",
    "    poster_df.registerTempTable('poster')\n",
    "except Exception:\n",
    "    print(\"Cannot import tmdbsimple, no movie posters will be displayed!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%%spark -c sql -o poster_url -q\n",
    "select * from poster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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btXN+xy6Y7HY8He2JrUg2WNVXrpRzhjBjb06iyyg1s1d+GJ/1v0+PYemavexl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\ntcS8jTHDIiVWbDHRHsLclLuegNfHKtxyse+FxnR1aYHCOYVxPsjQTGDstYk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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "width": 200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image(poster_url.iloc[0][0], width=200))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Setting of global variables. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "*** Fill in the following variables \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Host name where solr is installed\n",
    "SOLR_HOST = 'SOLR_HOST_NAME'\n",
    "# The port solr server is listening at.\n",
    "SOLR_PORT = '8983'\n",
    "SOLR_HOST_PORT = SOLR_HOST + ':' + SOLR_PORT\n",
    "SOLR_URL = 'http://' + SOLR_HOST_PORT + '/solr'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%%spark\n",
    "# Install directory needs to be specified to aid in moving solr config files to\n",
    "# zookeeper. This is a requirement in solr cloud setup.\n",
    "SOLR_INSTALL_DIR = 'SOLR_INSTALL_DIR'\n",
    "# Host name where solr is installed\n",
    "SOLR_HOST = 'SOLR_HOST_NAME'\n",
    "# The port solr server is listening at.\n",
    "SOLR_PORT = '8983'\n",
    "# Host name where zookeeper is installed.\n",
    "ZKHOST = 'ZOOKEPER_HOST'\n",
    "# Zookeeper port.\n",
    "ZKPORT = '2181'\n",
    "# Required in order to ssh to the machine where solr server is installed in order\n",
    "# to copy the solr configuration files into zookeeper. If you don't want to\n",
    "# do this step from the notebook, then you can do this outside the notebook and\n",
    "# do the remaining steps like creating collection and setting up schemas from notebook.\n",
    "SSHUSER = 'SSH_USER'\n",
    "SSHPASSWORD = 'SSH_PASSWORD'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%%spark\n",
    "# Derived variables used in the following cells\n",
    "SOLR_HOST_PORT = SOLR_HOST + ':' + SOLR_PORT\n",
    "SOLR_URL = 'http://' + SOLR_HOST_PORT + '/solr'\n",
    "SOLR_ADMIN_URL = SOLR_URL + '/admin/'\n",
    "SCHEMA_URL = SOLR_URL + '/solr/admin/'\n",
    "ZK_URL = ZKHOST + ':' + ZKPORT + '/solr'\n",
    "json_response = '&wt=json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "### Utility functions that helps in performing admin functions against SOLR."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%%spark\n",
    "def executeSshCommand(command):\n",
    "  ssh = None\n",
    "  try:\n",
    "      ssh = paramiko.SSHClient()\n",
    "      ssh.load_system_host_keys()\n",
    "      ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n",
    "      ssh.connect(SOLR_HOST, username=SSHUSER, password=SSHPASSWORD)\n",
    "      ssh_stdin, ssh_stdout, ssh_stderr = ssh.exec_command(command)\n",
    "      # print(ssh_stdout)\n",
    "      # print(ssh_stderr)\n",
    "  finally:\n",
    "      if ssh:\n",
    "         ssh.close()\n",
    "\n",
    "def createJKConfig(collectionName):\n",
    "  cmd = (SOLR_INSTALL_DIR + '/solr/server/scripts/cloud-scripts' +\n",
    "        '/zkcli.sh -zkhost ' + ZK_URL +\n",
    "        ' -cmd upconfig -confdir ' +\n",
    "        SOLR_INSTALL_DIR + '/' + 'solr/server/solr/configsets/data_driven_schema_configs/conf/ -confname ' + collectionName\n",
    "        )\n",
    "  executeSshCommand(cmd)\n",
    "    \n",
    "def deleteJKConfig(collectionName):\n",
    "  dirToClear = 'configs/collectionName'\n",
    "  cmd = (SOLR_INSTALL_DIR + '/solr/server/scripts/cloud-scripts' +\n",
    "        '/zkcli.sh -zkhost ' + ZK_URL +\n",
    "        ' -cmd clear ' + dirToClear\n",
    "        )\n",
    "  executeSshCommand(cmd)\n",
    "\n",
    "def displayStatus():\n",
    "  request = SOLR_ADMIN_URL + 'info/system?'+ json_response\n",
    "  try:\n",
    "    connection = urlopen(request)\n",
    "    response = json.load(connection)\n",
    "    responseCode = response[\"responseHeader\"][\"status\"]\n",
    "    if responseCode == 0:\n",
    "      print(response)\n",
    "    else:\n",
    "      print(\"Error: \", responseCode)\n",
    "  except URLError, e:\n",
    "    print e.reason\n",
    "\n",
    "def createCollection(collectionName):\n",
    "  time.sleep(2)\n",
    "  action_string = 'collections?action=CREATE&name=' + \\\n",
    "                  collectionName + \\\n",
    "                  '&numShards=1&replicationFactor=1'\n",
    "  request = SOLR_ADMIN_URL + action_string + json_response\n",
    "  try:\n",
    "    connection = urlopen(request)\n",
    "    response = json.load(connection)\n",
    "    responseCode = response[\"responseHeader\"][\"status\"]\n",
    "    if responseCode == 0:\n",
    "      print(\"Successfully created collection: \", collectionName)\n",
    "    else:\n",
    "      print(\"Error: \", responseCode)\n",
    "  except URLError, e:\n",
    "    pass \n",
    "\n",
    "def dropCollection(collectionName):\n",
    "  action_string = 'collections?action=DELETE&name=' + collectionName\n",
    "  request = SOLR_ADMIN_URL + action_string + json_response\n",
    "  try:\n",
    "    connection = urlopen(request)\n",
    "    response = json.load(connection)\n",
    "    responseCode = response[\"responseHeader\"][\"status\"]\n",
    "    if responseCode == 0:\n",
    "      print(\"Successfully removed collection: \", collectionName)\n",
    "    else:\n",
    "      print(\"Error: \", responseCode)\n",
    "  except URLError, e:\n",
    "    print e.reason\n",
    "  deleteJKConfig(collectionName)\n",
    "\n",
    "def setupSchema():\n",
    "  try:\n",
    "    dropCollection('ratings')\n",
    "  except:\n",
    "    pass\n",
    "  try:\n",
    "    dropCollection('users')\n",
    "  except:\n",
    "    pass\n",
    "  try:\n",
    "    dropCollection('movies')\n",
    "  except:\n",
    "    pass\n",
    "  try:\n",
    "    dropCollection('movies_vector')\n",
    "  except:\n",
    "    pass\n",
    "  createCollection('ratings')\n",
    "  createCollection('users')\n",
    "  createCollection('movies')\n",
    "  createCollection('movies_vector')\n",
    "  print(\"Created collections : [ratings, users, movies, movies_vector]\")\n",
    "  ratings_schema = \"\"\"{\n",
    "    \"add-field\":{\n",
    "       \"name\":\"timestamp\",\n",
    "       \"type\":\"date\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"userId\",\n",
    "       \"type\":\"int\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"movieId\",\n",
    "       \"type\":\"int\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"rating\",\n",
    "       \"type\":\"double\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     }\n",
    "  }\"\"\"\n",
    "  users_schema = \"\"\"{\n",
    "    \"add-field\":{\n",
    "       \"name\":\"id\",\n",
    "       \"type\":\"int\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"factor\",\n",
    "       \"type\":\"VectorField\",\n",
    "       \"termOffsets\":\"true\",\n",
    "       \"termPositions\":\"true\",\n",
    "       \"termVectors\":\"true\",\n",
    "       \"multiValued\":\"true\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"version\",\n",
    "       \"type\":\"string\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\",\n",
    "       \"multiValued\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"timestamp\",\n",
    "       \"type\":\"date\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     }\n",
    "  }\"\"\"\n",
    "  movies_schema = \"\"\"{\n",
    "    \"add-field\":{\n",
    "       \"name\":\"movieId\",\n",
    "       \"type\":\"int\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"tmdbId\",\n",
    "       \"type\":\"string\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\",\n",
    "       \"multiValued\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"title\",\n",
    "       \"type\":\"text_general\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"genres\",\n",
    "       \"type\":\"string\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\",\n",
    "       \"multiValued\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"release_date\",\n",
    "       \"type\":\"int\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"factor\",\n",
    "       \"type\":\"VectorField\",\n",
    "       \"termOffsets\":\"true\",\n",
    "       \"termPositions\":\"true\",\n",
    "       \"termVectors\":\"true\",\n",
    "       \"multiValued\":\"true\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"version\",\n",
    "       \"type\":\"string\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\",\n",
    "       \"multiValued\":\"true\"\n",
    "     },\n",
    "    \"add-field\":{\n",
    "       \"name\":\"timestamp\",\n",
    "       \"type\":\"date\",\n",
    "       \"stored\":\"true\",\n",
    "       \"indexed\":\"true\"\n",
    "    }\n",
    "  }\"\"\"\n",
    "  mappings_schema_url = SOLR_URL + '/ratings/schema'\n",
    "  headers = {'content-type': 'application/json'}\n",
    "  ratings_status = requests.post(mappings_schema_url, data=ratings_schema, headers=headers)\n",
    "  if ratings_status.status_code == requests.codes.ok:\n",
    "     print(\"Successfully registered schema for collection ratings\")\n",
    "  else:\n",
    "     ratings_status.raise_for_status()\n",
    "  users_schema_url = SOLR_URL + '/users/schema'\n",
    "  users_status  = requests.post(users_schema_url, data=users_schema, headers=headers)\n",
    "  if users_status.status_code == requests.codes.ok:\n",
    "     print(\"Successfully registered schema for collection users\")\n",
    "  else:\n",
    "     users_status.raise_for_status()\n",
    "  movies_schema_url = SOLR_URL + '/movies/schema'\n",
    "  movies_status = requests.post(movies_schema_url, data=movies_schema, headers=headers)\n",
    "  if movies_status.status_code == requests.codes.ok:\n",
    "     print(\"Successfully registered schema for collection movies\")\n",
    "  else:\n",
    "     movies_status.raise_for_status()\n",
    "  movies_vector_schema_url = SOLR_URL + '/movies_vector/schema'\n",
    "  movies_vector_status = requests.post(movies_vector_schema_url, data=movies_schema, headers=headers)\n",
    "  if movies_vector_status.status_code == requests.codes.ok:\n",
    "     print(\"Successfully registered schema for collection movies_vector\")\n",
    "  else:\n",
    "     movies_vector_status.raise_for_status()     \n",
    "\n",
    "def commit(conn, collection):\n",
    "    conn[collection].commit()\n",
    "\n",
    "def prettyPrint(docs):\n",
    "    for x in docs:\n",
    "       print(json.dumps(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Step 2: Load data into Solr\n",
    "\n",
    "Now that you have your dataset processed and prepared, you will load it into Solr.\n",
    "\n",
    "_Note:_ for the purposes of this demo notebook you have started with an existing example dataset and will load that into Solr. In practice you may write your event data as well as user and item metadata from your application directly into Solr.\n",
    "\n",
    "First test that your Solr instance is running and you can connect to it using the Solr Admin API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%%spark\n",
    "displayStatus()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Create an Solr collections with schema mappings for users, movies and rating events\n",
    "\n",
    "Creates the solr collections and explicitly author their schema. While solr supports dynamic mapping, it's advisable to specify the schema mapping explicitly if you know what your data looks like.\n",
    "\n",
    "For the purposes of your recommendation engine, this is also necessary so that you can specify a custom analyzer for the field that will hold the recommendation \"model\" (that is, the factor vectors). This will ensure the vector-scoring plugin will work correctly.\n",
    "\n",
    "> _Note_ This notebook does not go into detail about the underlying scoring mechanism or the relevant Solr internals. See the talks and slides in the [Journey Links section](https://github.com/MLnick/elasticsearch-spark-recommender-demo/blob/master/README.md#links) for more detail.\n",
    "\n",
    "__References:__\n",
    "* [Create index request](https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-create-index.html)\n",
    "* [Delimited payload filter](https://www.elastic.co/guide/en/elasticsearch/reference/2.4/analysis-delimited-payload-tokenfilter.html)\n",
    "* [Term vectors](https://www.elastic.co/guide/en/elasticsearch/reference/2.4/docs-termvectors.html#_term_information)\n",
    "* [Mapping](https://www.elastic.co/guide/en/elasticsearch/reference/2.4/mapping.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "> **Note**\n",
    "\n",
    "> Please note that, the following cell drops the collections first and then recreates them with appropriate schema. Please make sure you don't have existing collections with the same name. You may inadvertently delete the collections with the following step."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Now you're ready to create the collections and author their respective schema definitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Successfully removed collection: ', 'ratings')\n",
      "('Successfully removed collection: ', 'users')\n",
      "('Successfully removed collection: ', 'movies')\n",
      "('Successfully removed collection: ', 'movies_vector')\n",
      "('Successfully created collection: ', 'ratings')\n",
      "('Successfully created collection: ', 'users')\n",
      "('Successfully created collection: ', 'movies')\n",
      "('Successfully created collection: ', 'movies_vector')\n",
      "Created collections : [ratings, users, movies, movies_vector]\n",
      "Successfully registered schema for collection ratings\n",
      "Successfully registered schema for collection users\n",
      "Successfully registered schema for collection movies\n",
      "Successfully registered schema for collection movies_vector"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "setupSchema()\n",
    "conn = SolrConnection(SOLR_HOST_PORT, version=\"6.6.0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "conn = SolrConnection(SOLR_HOST_PORT, version=\"6.6.0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Load Ratings and Movies DataFrames into Solr\n",
    "\n",
    "First you will write the ratings data to Solr. Notice that you can simply use the Spark Solr connector to write a `DataFrame` with the native Spark datasource API by specifying `format(\"solr\")`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataframe count: 100004\n",
      "Solr index count:  100004"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# write ratings data\n",
    "ratings.write.format(\"solr\").option(\"zkhost\", ZK_URL).option(\"collection\", \"ratings\").save(\"ratings\")\n",
    "commit(conn, \"ratings\")\n",
    "# check write went ok\n",
    "print(\"Dataframe count: %d\" % ratings.count())\n",
    "res = conn[\"ratings\"].search({'q':'*:*'})\n",
    "print(\"Solr index count:  %d\" % res.result.response.numFound)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"rating\": 2.5, \"movieId\": 31, \"timestamp\": \"2009-12-13T18:52:24Z\", \"userId\": 1, \"_version_\": 1602571901399465984, \"id\": \"aba4cbb1-c87c-4fb0-b45e-9b903ed73ad3\"}\n",
      "{\"rating\": 3.0, \"movieId\": 1029, \"timestamp\": \"2009-12-13T18:52:59Z\", \"userId\": 1, \"_version_\": 1602571901411000320, \"id\": \"3c156a93-2130-476f-a6db-919f4b3786ce\"}\n",
      "{\"rating\": 3.0, \"movieId\": 1061, \"timestamp\": \"2009-12-13T18:53:02Z\", \"userId\": 1, \"_version_\": 1602571901411000321, \"id\": \"33efb74d-589e-4653-b482-f8cceea8d1d3\"}\n",
      "Number of documents returned from Query 3"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# test things out by retrieving a few rating event documents from Solr\n",
    "from solrcloudpy.parameters import SearchOptions\n",
    "se = SearchOptions()\n",
    "se.commonparams.q(\"*\").rows(3)\n",
    "res = conn[\"ratings\"].search(se)\n",
    "prettyPrint(res.result.response.docs)\n",
    "print(\"Number of documents returned from Query %d\" % len(res.result.response.docs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Since you've indexed the rating event data into Solr, you can use all the capabilities of a search engine to query the data. For example, you could count the number of ratings events in a given date range using Solr's date math in a query string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"rating\": 4.0, \"movieId\": 111, \"timestamp\": \"2016-01-01T20:25:54Z\", \"userId\": 62, \"_version_\": 1602571903162122244, \"id\": \"421630a1-a456-43a6-9a66-e8d5384ce598\"}\n",
      "{\"rating\": 4.0, \"movieId\": 6016, \"timestamp\": \"2016-01-01T20:21:32Z\", \"userId\": 62, \"_version_\": 1602571903164219394, \"id\": \"6e92b470-12a4-4d8c-989c-47a465e10ee0\"}\n",
      "{\"rating\": 4.0, \"movieId\": 48774, \"timestamp\": \"2016-01-20T11:29:34Z\", \"userId\": 62, \"_version_\": 1602571903164219396, \"id\": \"f34e7528-4d2d-4317-870f-79c4bcfed956\"}\n",
      "{\"rating\": 3.5, \"movieId\": 49530, \"timestamp\": \"2016-01-15T20:03:09Z\", \"userId\": 62, \"_version_\": 1602571903165267968, \"id\": \"8a768472-a5a0-411b-98e4-430f4a41bd39\"}\n",
      "{\"rating\": 4.5, \"movieId\": 68157, \"timestamp\": \"2016-01-01T20:25:22Z\", \"userId\": 62, \"_version_\": 1602571903165267971, \"id\": \"767717e9-9b75-4060-a558-9569cf099f0d\"}\n",
      "{\"rating\": 4.5, \"movieId\": 68237, \"timestamp\": \"2016-01-01T20:17:08Z\", \"userId\": 62, \"_version_\": 1602571903165267972, \"id\": \"0c3333ec-d60e-4432-b0a1-bb7e9b47ad5c\"}\n",
      "{\"rating\": 3.5, \"movieId\": 69481, \"timestamp\": \"2016-01-01T20:11:26Z\", \"userId\": 62, \"_version_\": 1602571903165267973, \"id\": \"aa707772-4ee9-47aa-bbf2-a4fe7fb465d1\"}\n",
      "{\"rating\": 4.0, \"movieId\": 70286, \"timestamp\": \"2016-01-01T20:14:24Z\", \"userId\": 62, \"_version_\": 1602571903166316544, \"id\": \"088e85da-79ca-43e9-ab51-273277f62ce2\"}\n",
      "{\"rating\": 4.0, \"movieId\": 70862, \"timestamp\": \"2016-01-01T20:27:11Z\", \"userId\": 62, \"_version_\": 1602571903166316545, \"id\": \"17f96db8-50e7-424e-bfe7-803ad00585ab\"}\n",
      "{\"rating\": 5.0, \"movieId\": 79132, \"timestamp\": \"2016-01-01T20:21:41Z\", \"userId\": 62, \"_version_\": 1602571903166316546, \"id\": \"8fe37cf5-0424-4075-9e20-2056d595b066\"}\n",
      "Number of documents returned from Query 10"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "se = SearchOptions()\n",
    "se.commonparams.q(\"timestamp:[2016-01-01T00:00:00Z  TO 2016-02-01T23:59:59Z]\")\n",
    "res = conn[\"ratings\"].search(se)\n",
    "prettyPrint(res.result.response.docs)\n",
    "print(\"Number of documents returned from Query %d\" % len(res.result.response.docs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Next write the movie metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movie DF count: 9125\n",
      "Solr index count:  9125"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# write movie data\n",
    "movie_data.write.format(\"solr\").option(\"zkhost\", ZK_URL).option(\"collection\", \"movies\").save(\"movies\")\n",
    "commit(conn, \"movies\")\n",
    "# check load went ok\n",
    "print(\"Movie DF count: %d\" % movie_data.count())\n",
    "res = conn[\"movies\"].search({'q':'*:*'})\n",
    "print(\"Solr index count:  %d\" % res.result.response.numFound)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Again you can harness the power of search to query the movie metadata:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"genres\": [\"action\", \"sci-fi\", \"thriller\"], \"movieId\": 2571, \"title\": [\"Matrix, The\"], \"release_date\": 1999, \"tmdbId\": [\"603\"], \"_version_\": 1602571924008861704, \"id\": \"57c1eb87-2b09-49cb-b084-7b1268349d86\"}\n",
      "{\"genres\": [\"action\", \"adventure\", \"sci-fi\", \"thriller\", \"imax\"], \"movieId\": 6365, \"title\": [\"Matrix Reloaded, The\"], \"release_date\": 2003, \"tmdbId\": [\"604\"], \"_version_\": 1602571924188168193, \"id\": \"c2878d05-cc53-4dc7-853c-18c06eb81e59\"}\n",
      "{\"genres\": [\"action\", \"adventure\", \"sci-fi\", \"thriller\", \"imax\"], \"movieId\": 6934, \"title\": [\"Matrix Revolutions, The\"], \"release_date\": 2003, \"tmdbId\": [\"605\"], \"_version_\": 1602571924200751120, \"id\": \"6793a7df-3a8d-41d3-a9e9-69bdad5fb8c6\"}\n",
      "Number of documents returned from Query 3"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# test things out by searching for movies containing \"matrix\" in the title\n",
    "se = SearchOptions()\n",
    "se.commonparams.q(\"title:matrix\").rows(3)\n",
    "res = conn[\"movies\"].search(se)\n",
    "prettyPrint(res.result.response.docs)\n",
    "print(\"Number of documents returned from Query %d\" % len(res.result.response.docs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Step 3: Train a recommmender model on the ratings data\n",
    "\n",
    "Your data is now stored in Solr and you will use the ratings data to build a collaborative filtering recommendation model.\n",
    "\n",
    "[Collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering) is a recommendation approach that is effectively based on the \"wisdom of the crowd\". It makes the assumption that, if two people share similar preferences, then the things that one of them prefers could be good recommendations to make to the other. In other words, if user A tends to like certain movies, and user B shares some of these preferences with user A, then the movies that user A likes, that user B _has not yet seen_, may well be movies that user B will also like.\n",
    "\n",
    "In a similar manner, we can think about _items_ as being similar if they tend to be rated highly by the same people, on average. \n",
    "\n",
    "Hence these models are based on the combined, collaborative preferences and behavior of all users in aggregate. They tend to be very effective in practice (provided you have enough preference data to train the model). The ratings data you have is a form of _explicit preference data_, perfect for training collaborative filtering models.\n",
    "\n",
    "### Alternating Least Squares\n",
    "\n",
    "Alternating Least Squares (ALS) is a specific algorithm for solving a type of collaborative filtering model known as [matrix factorization (MF)](https://en.wikipedia.org/wiki/Matrix_decomposition). The core idea of MF is to represent the ratings as a _user-item ratings matrix_. In the diagram below you will see this matrix on the left (with users as _rows_ and movies as _columns_). The entries in this matrix are the ratings given by users to movies.\n",
    "\n",
    "You may also notice that the matrix has _missing entries_ because not all users have rated all movies. In this situation we refer to the data as _sparse_.\n",
    "\n",
    "![als-diagram.png](../doc/source/images/als-diagram.png)\n",
    "\n",
    "MF methods aim to find two much smaller matrices (one representing the _users_ and the other the _items_) that, when multiplied together, re-construct the original ratings matrix as closely as possible. This is know as _factorizing_ the original matrix, hence the name of the technique.\n",
    "\n",
    "The two smaller matrices are called _factor matrices_ (or _latent features_). The user and movie factor matrices are illustrated on the right in the diagram above. The idea is that each user factor vector is a compressed representation of the user's preferences and behavior. Likewise, each item factor vector is a compressed representation of the item. Once the model is trained, the factor vectors can be used to make recommendations, which is what you will do in the following sections.\n",
    "\n",
    "__Further reading:__\n",
    "\n",
    "* [Spark MLlib Collaborative Filtering](http://spark.apache.org/docs/latest/ml-collaborative-filtering.html)\n",
    "* [Alternating Least Squares and collaborative filtering](https://datasciencemadesimpler.wordpress.com/tag/alternating-least-squares/)\n",
    "* [Quora question on Alternating Least Squares](https://www.quora.com/What-is-the-Alternating-Least-Squares-method-in-recommendation-systems-And-why-does-this-algorithm-work-intuition-behind-this)\n",
    "\n",
    "Fortunately, Spark's MLlib machine learning library has a scalable, efficient implementation of matrix factorization built in, which we can use to train our recommendation model. Next, you will use Spark's ALS to train a model on your ratings data from Solr."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-------+------+-------------------+------+\n",
      "|                  id|movieId|rating|          timestamp|userId|\n",
      "+--------------------+-------+------+-------------------+------+\n",
      "|0000b99e-73e3-4f9...|    230|   4.0|1996-09-19 21:19:16|   496|\n",
      "|0000d190-f6d5-46d...|   1278|   5.0|2006-08-21 10:05:16|    83|\n",
      "|000167b2-e363-427...|   2502|   3.5|2005-04-03 13:58:06|   417|\n",
      "|000284ba-899e-42f...|   2916|   3.5|2005-03-23 05:11:30|   282|\n",
      "|00046417-f6f8-430...|     16|   5.0|1996-03-30 03:12:30|   224|\n",
      "+--------------------+-------+------+-------------------+------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "ratings_from_solr = spark.read.format(\"solr\").option(\"zkhost\", ZK_URL).option(\"collection\", \"ratings\").load(\"ratings\")\n",
    "ratings_from_solr.show(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---+--------------------+\n",
      "| id|            features|\n",
      "+---+--------------------+\n",
      "| 10|[0.3674726, 0.118...|\n",
      "| 20|[-0.60201323, 0.8...|\n",
      "| 30|[0.45107082, 0.01...|\n",
      "| 40|[-0.23864046, -0....|\n",
      "| 50|[0.44629014, 0.42...|\n",
      "+---+--------------------+\n",
      "only showing top 5 rows\n",
      "\n",
      "+---+--------------------+\n",
      "| id|            features|\n",
      "+---+--------------------+\n",
      "| 10|[0.43729877, -0.3...|\n",
      "| 20|[0.99712294, 1.34...|\n",
      "| 30|[0.36094037, 0.10...|\n",
      "| 40|[1.3377725, -0.00...|\n",
      "| 50|[0.28212664, -0.2...|\n",
      "+---+--------------------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "from pyspark.ml.recommendation import ALS\n",
    "from pyspark.sql.functions import col\n",
    "als = ALS(userCol=\"userId\", itemCol=\"movieId\", ratingCol=\"rating\", regParam=0.01, rank=20, seed=12)\n",
    "model = als.fit(ratings_from_solr)\n",
    "model.userFactors.show(5)\n",
    "model.itemFactors.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Step 4: Export ALS user and item factor vectors to Solr\n",
    "\n",
    "Congratulations, you've trained a recommendation model! The next step is to export the model factors (shown in the `DataFrames` above) to Solr.\n",
    "\n",
    "In order to store the model in the correct format for the index mappings set up earlier, you will need to create some utility functions. These functions will allow you to convert the raw vectors (which are equivalent to a Python list in the factor `DataFrames` above) to the correct _delimited string format_. This ensures Solr will parse the vector field in the model correctly using the delimited token filter custom analyzer you configured earlier.\n",
    "\n",
    "You will also create a function to convert a vector and related metadata (such as the Spark model id and a timestamp) into a `DataFrame` field that matches the `model` field in the Solr index mapping."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Utility functions for converting factor vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%%spark\n",
    "from pyspark.sql.types import *\n",
    "from pyspark.sql.functions import udf, lit, current_timestamp, unix_timestamp\n",
    "\n",
    "def convert_vector(x):\n",
    "    '''Convert a list or numpy array to delimited token filter format'''\n",
    "    return \" \".join([\"%s|%s\" % (i, v) for i, v in enumerate(x)])\n",
    "\n",
    "def reverse_convert(s):\n",
    "    '''Convert a delimited token filter format string back to list format'''\n",
    "    return  [float(f.split(\"|\")[1]) for f in s.split(\" \")]\n",
    "\n",
    "def vector_to_struct(x, version, ts):\n",
    "    '''Convert a vector to a SparkSQL Struct with string-format vector and version fields'''\n",
    "    return (convert_vector(x), version, ts)\n",
    "\n",
    "vector_struct = udf(vector_to_struct, \\\n",
    "                    StructType([StructField(\"factor\", StringType(), True), \\\n",
    "                                StructField(\"version\", StringType(), True),\\\n",
    "                                StructField(\"timestamp\", LongType(), True)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.3674725890159607, 0.11864374577999115, 0.3943413197994232, 0.627119779586792, 0.1258048564195633, -0.43264928460121155, 0.607657253742218, -0.002352567855268717, -0.0375259667634964, -0.07540702074766159, 0.1594085991382599, -0.8177066445350647, 0.5343821048736572, -0.6135174632072449, 0.5194279551506042, 0.28479066491127014, -0.14081591367721558, -0.007298605982214212, -0.26084643602371216, -0.5528038144111633]\n",
      "()\n",
      "0|0.367472589016 1|0.11864374578 2|0.394341319799 3|0.627119779587 4|0.12580485642 5|-0.432649284601 6|0.607657253742 7|-0.00235256785527 8|-0.0375259667635 9|-0.0754070207477 10|0.159408599138 11|-0.817706644535 12|0.534382104874 13|-0.613517463207 14|0.519427955151 15|0.284790664911 16|-0.140815913677 17|-0.00729860598221 18|-0.260846436024 19|-0.552803814411"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# test out the vector conversion function\n",
    "test_vec = model.userFactors.select(\"features\").first().features\n",
    "print(test_vec)\n",
    "print()\n",
    "print(convert_vector(test_vec))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Convert factor vectors to [factor, version, timestamp] form and write to Solr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---+--------------------+--------------------+----------+\n",
      "| id|              factor|             version| timestamp|\n",
      "+---+--------------------+--------------------+----------+\n",
      "| 10|0|0.437298774719 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 20|0|0.997122943401 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 30|0|0.360940366983 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 40|0|1.33777248859 1...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 50|0|0.282126635313 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "+---+--------------------+--------------------+----------+\n",
      "only showing top 5 rows\n",
      "\n",
      "+---+--------------------+--------------------+----------+\n",
      "| id|              factor|             version| timestamp|\n",
      "+---+--------------------+--------------------+----------+\n",
      "| 10|0|0.367472589016 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 20|0|-0.602013230324...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 30|0|0.451070815325 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 40|0|-0.238640457392...|ALS_4d6198252d2f6...|1528331697|\n",
      "| 50|0|0.446290135384 ...|ALS_4d6198252d2f6...|1528331697|\n",
      "+---+--------------------+--------------------+----------+\n",
      "only showing top 5 rows"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "ver = model.uid\n",
    "ts = unix_timestamp(current_timestamp())\n",
    "movie_vectors = model.itemFactors.select(\"id\", vector_struct(\"features\", lit(ver), ts).alias(\"@model\"))\n",
    "movie_vectors.select(\"id\", \"@model.factor\", \"@model.version\", \"@model.timestamp\").show(5)\n",
    "user_vectors = model.userFactors.select(\"id\", vector_struct(\"features\", lit(ver), ts).alias(\"@model\"))\n",
    "user_vectors.select(\"id\", \"@model.factor\", \"@model.version\", \"@model.timestamp\").show(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movie DF count: 9066\n",
      "Solr index count:  9066"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "movie_vectors.registerTempTable(\"movie_vector\")\n",
    "movie_data.registerTempTable(\"movie_data\")\n",
    "\n",
    "# Inner join to fill in the extra info from movie vector\n",
    "movie_vector_data = spark.sql(\"select * from movie_data, movie_vector where movieId = id\").drop(\"id\")\n",
    "movie_vector_data.registerTempTable(\"movie_vector_data\")\n",
    "movie_vector_data = \\\n",
    "    movie_vector_data.select( \\\n",
    "      \"movieId\", \"tmdbId\", \"title\", \"release_date\", \\\n",
    "      \"genres\", \"@model.factor\", \"@model.version\", \\\n",
    "       F.from_unixtime(\"@model.timestamp\").alias(\"timestamp\"))\n",
    "# Now write to solr\n",
    "movie_vector_data.write.format(\"solr\").option(\"zkhost\", ZK_URL).option(\"collection\", \"movies_vector\").save(\"movies_vector\")\n",
    "commit(conn, \"movies_vector\")\n",
    "# check load went ok\n",
    "print(\"Movie DF count: %d\" % movie_vector_data.count())\n",
    "res = conn[\"movies_vector\"].search({'q':'*:*'})\n",
    "print(\"Solr index count:  %d\" % res.result.response.numFound)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Users DF count: 671\n",
      "Solr index count:  671"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# write data to SOLR.\n",
    "users_vector = \\\n",
    "    user_vectors.select(\"id\", \"@model.factor\", \"@model.version\", \\\n",
    "                         F.from_unixtime(\"@model.timestamp\").alias(\"timestamp\"))\n",
    "users_vector.write.format(\"solr\").option(\"zkhost\", ZK_URL).option(\"collection\", \"users\").save(\"users\")\n",
    "commit(conn, \"users\")\n",
    "print(\"Users DF count: %d\" % users_vector.count())\n",
    "res = conn[\"users\"].search({'q':'*:*'})\n",
    "print(\"Solr index count:  %d\" % res.result.response.numFound)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Check the data  was written correctly\n",
    "\n",
    "You can search for a movie to see if the model factor vector was written correctly. You should see a `'@model': {'factor': '0|...` field in the returned movie document."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solr index count:  54\n",
      "{\"genres\": [\"action\", \"adventure\", \"sci-fi\"], \"movieId\": 2628, \"title\": [\"Star Wars: Episode I - The Phantom Menace\"], \"timestamp\": \"2018-06-06T17:34:57Z\", \"release_date\": 1999, \"version\": [\"ALS_4d6198252d2f65bc0b99\"], \"tmdbId\": [\"1893\"], \"factor\": [\"0|0.0669704005122 1|0.531547248363 2|0.601375579834 3|0.079128973186 4|1.03414511681 5|-1.11473667622 6|0.386077940464 7|-1.98664963245 8|0.851461529732 9|0.0678836777806 10|0.527850389481 11|-0.850936353207 12|0.526257097721 13|0.369143038988 14|-0.121699631214 15|2.79477190971 16|0.179985553026 17|-1.0284113884 18|-0.41951623559 19|-1.22518694401\"], \"_version_\": 1602571942515179521, \"id\": \"c24ff97c-1068-4254-afa5-dd48f679e0a9\"}"
     ]
    }
   ],
   "source": [
    "%%spark\n",
    "# search for a particular sci-fi movie\n",
    "se = SearchOptions()\n",
    "se.commonparams.q(\"star wars phantom menace\").rows(1)\n",
    "res = conn[\"movies_vector\"].search(se)\n",
    "print(\"Solr index count:  %d\" % res.result.response.numFound)\n",
    "prettyPrint(res.result.response.docs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Step 5: Recommend using Solr!\n",
    "\n",
    "Now that you have loaded your recommendation model into Solr, you will generate some recommendations.\n",
    "First, you will need to create a few utility functions for:\n",
    "\n",
    "* Fetching movie posters from TMdb API (optional)\n",
    "* Constructing the Solr query to generate recommendations from your factor model\n",
    "* Given a movie, use this query to find the movies most similar to it\n",
    "* Given a user, use this query to find the movies with the highest predicted rating, to recommend to the user\n",
    "* Display the results as an HTML table in Jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image, HTML, display\n",
    "from solrcloudpy.parameters import SearchOptions\n",
    "\n",
    "def reverse_convert(s):\n",
    "    '''Convert a delimited token filter format string back to list format'''\n",
    "    return  [float(f.split(\"|\")[1]) for f in s.split(\" \")]\n",
    "\n",
    "def get_poster_url(id):\n",
    "    \"\"\"Fetch movie poster image URL from TMDb API given a tmdbId\"\"\"\n",
    "    IMAGE_URL = 'https://image.tmdb.org/t/p/w500'\n",
    "    \n",
    "    try:\n",
    "        import tmdbsimple as tmdb\n",
    "        from tmdbsimple import APIKeyError\n",
    "        tmdb.API_KEY = 'f9d0653765943704849a02c66b5f73ba'\n",
    "        try:\n",
    "            movie = tmdb.Movies(id).info()\n",
    "            poster_url = IMAGE_URL + movie['poster_path'] if 'poster_path' in movie and movie['poster_path'] is not None else \"\"\n",
    "            return poster_url\n",
    "        except APIKeyError as ae:\n",
    "            return \"KEY_ERR\"\n",
    "    except Exception as me:\n",
    "        print(str(me))\n",
    "        return \"NA\"\n",
    "    \n",
    "    \n",
    "def fn_query(query_vec, q=\"\", cosine=False):\n",
    "    \"\"\"\n",
    "    Construct a Solr query that produces score for each document based on training model data.\n",
    "    \n",
    "    The query takes as parameters:\n",
    "        - the field in the candidate document that contains the factor vector\n",
    "        - the query vector\n",
    "        - a flag indicating whether to use dot product or cosine similarity (normalized dot product) for scores\n",
    "        \n",
    "    The query vector passed in will be the user factor vector (if generating recommended movies for a user)\n",
    "    or movie factor vector (if generating similar movies for a given movie)\n",
    "    \"\"\"\n",
    "    query_vec_str = \",\".join(map(str, query_vec))\n",
    "    query = '{!vp f=factor vector = \"' + query_vec_str + '\"' + ' cosine = ' + str(cosine).lower() + '}'\n",
    "    return query\n",
    "\n",
    "def get_similar(the_id, q=\"\", num=10, index=\"demo\", dt=\"movies_vector\"):\n",
    "    \"\"\"\n",
    "    Given a movie id, execute the recommendation function score query to find similar movies, ranked by cosine similarity\n",
    "    \"\"\"\n",
    "    se = SearchOptions()           \n",
    "    query = 'movieId : %s' % the_id \n",
    "    se.commonparams.q(query) \n",
    "    res = conn[dt].search(se)\n",
    "    src = res.result.response.docs[0]\n",
    "    if 'factor' in src:\n",
    "        raw_vec = src['factor']\n",
    "        # our script actually uses the list form for the query vector and handles conversion internally\n",
    "        query_vec = reverse_convert(raw_vec[0])\n",
    "        qry = fn_query(query_vec, q=q, cosine=True)\n",
    "        se = SearchOptions()\n",
    "        se.commonparams.q(qry).fl(\"* score\").fq(q)\n",
    "        results = conn[dt].search(se)\n",
    "        hits = results.result.response.docs\n",
    "        return src, hits[1:num+1]\n",
    "    \n",
    "def get_user_recs(the_id, q=\"\", num=10, index=\"demo\"):\n",
    "    \"\"\"\n",
    "    Given a user id, execute the recommendation function score query to find top movies, ranked by predicted rating\n",
    "    \"\"\"\n",
    "    se = SearchOptions()           \n",
    "    query = 'id : %s' % the_id \n",
    "    se.commonparams.q(query)                           \n",
    "    res = conn[\"users\"].search(se)  \n",
    "    src = res.result.response.docs[0]\n",
    "    if 'factor' in src:\n",
    "        raw_vec = src['factor']\n",
    "        # our script actually uses the list form for the query vector and handles conversion internally\n",
    "        query_vec = reverse_convert(raw_vec[0])\n",
    "        qry = fn_query(query_vec, q=q, cosine=False)\n",
    "        se = SearchOptions()\n",
    "        se.commonparams.q(qry).fl(\"* score\").fq(q)      \n",
    "        results = conn[\"movies_vector\"].search(se)                        \n",
    "        hits = results.result.response.docs\n",
    "        return src, hits[:num]\n",
    "\n",
    "def get_movies_for_user(the_id, num=10, index=\"demo\"):\n",
    "    \"\"\"\n",
    "    Given a user id, get the movies rated by that user, from highest- to lowest-rated.\n",
    "    \"\"\"\n",
    "    se = SearchOptions()\n",
    "    se.commonparams.q(\"userId:%s\" % the_id).rows(num).sort(\"rating desc\")\n",
    "    res = conn[\"ratings\"].search(se) \n",
    "    hits = res.result.response.docs\n",
    "    ids = [h['movieId'] for h in hits]\n",
    "    \n",
    "    ids_disjunction_str = \" OR movieId:\".join(map(str, ids))\n",
    "    query = 'movieId : %s' % ids_disjunction_str\n",
    "    se = SearchOptions()\n",
    "    se.commonparams.q(query).fl('tmdbId, title')\n",
    "    res = conn[\"movies_vector\"].search(se)\n",
    "    tmdbids = res.result.response.docs\n",
    "    return tmdbids\n",
    "\n",
    "            \n",
    "def display_user_recs(the_id, q=\"*\", num=10, num_last=10, index=\"demo\"):\n",
    "    user, recs = get_user_recs(the_id, q, num, index)\n",
    "    user_movies = get_movies_for_user(the_id, num_last, index)\n",
    "    # check that posters can be displayed\n",
    "    first_movie = user_movies[0]\n",
    "    first_im_url = get_poster_url(int(first_movie['tmdbId'][0]))\n",
    "    if first_im_url == \"NA\":\n",
    "        display(HTML(\"<i>Cannot import tmdbsimple. No movie posters will be displayed!</i>\"))\n",
    "    if first_im_url == \"KEY_ERR\":\n",
    "        display(HTML(\"<i>Key error accessing TMDb API. Check your API key. No movie posters will be displayed!</i>\"))\n",
    "        \n",
    "    # display the movies that this user has rated highly\n",
    "    display(HTML(\"<h2>Get recommended movies for user id %s</h2>\" % the_id))\n",
    "    display(HTML(\"<h4>The user has rated the following movies highly:</h4>\"))\n",
    "    user_html = \"<table border=0>\"\n",
    "    i = 0\n",
    "    for movie in user_movies:\n",
    "        movie_im_url = get_poster_url(int(movie['tmdbId'][0]))\n",
    "        movie_title = movie['title']\n",
    "        user_html += \"<td><h5>%s</h5><img src=%s width=150></img></td>\" % (movie_title, movie_im_url)\n",
    "        i += 1\n",
    "        if i % 5 == 0:\n",
    "            user_html += \"</tr><tr>\"\n",
    "    user_html += \"</tr></table>\"\n",
    "    display(HTML(user_html))\n",
    "    # now display the recommended movies for the user\n",
    "    display(HTML(\"<br>\"))\n",
    "    display(HTML(\"<h2>Recommended movies:</h2>\"))\n",
    "    rec_html = \"<table border=0>\"\n",
    "    i = 0\n",
    "    for rec in recs:\n",
    "        r_im_url = get_poster_url(int(rec['tmdbId'][0]))\n",
    "        r_score = rec['score']\n",
    "        r_title = rec['title']\n",
    "        rec_html += \"<td><h5>%s</h5><img src=%s width=150></img></td><td><h5>%2.3f</h5></td>\" % (r_title, r_im_url, r_score)\n",
    "        i += 1\n",
    "        if i % 5 == 0:\n",
    "            rec_html += \"</tr><tr>\"\n",
    "    rec_html += \"</tr></table>\"\n",
    "    display(HTML(rec_html))\n",
    "\n",
    "    \n",
    "def display_similar(the_id, q=\"*\", num=10, index=\"demo\", dt=\"movies_vector\"):\n",
    "    \"\"\"\n",
    "    Display query movie, together with similar movies and similarity scores, in a table\n",
    "    \"\"\"\n",
    "    movie, recs = get_similar(the_id, q, num, index, dt)\n",
    "    q_im_url = get_poster_url(int(movie['tmdbId'][0]))\n",
    "    if q_im_url == \"NA\":\n",
    "        display(HTML(\"<i>Cannot import tmdbsimple. No movie posters will be displayed!</i>\"))\n",
    "    if q_im_url == \"KEY_ERR\":\n",
    "        display(HTML(\"<i>Key error accessing TMDb API. Check your API key. No movie posters will be displayed!</i>\"))\n",
    "        \n",
    "    display(HTML(\"<h2>Get similar movies for:</h2>\"))\n",
    "    display(HTML(\"<h4>%s</h4>\" % movie['title']))\n",
    "    if q_im_url != \"NA\":\n",
    "        display(Image(q_im_url, width=200))\n",
    "    display(HTML(\"<br>\"))\n",
    "    display(HTML(\"<h2>People who liked this movie also liked these:</h2>\"))\n",
    "    sim_html = \"<table border=0>\"\n",
    "    i = 0\n",
    "    for rec in recs:\n",
    "        r_im_url = get_poster_url(int(rec['tmdbId'][0]))\n",
    "        r_score = rec['score']\n",
    "        r_title = rec['title']\n",
    "        sim_html += \"<td><h5>%s</h5><img src=%s width=150></img></td><td><h5>%2.3f</h5></td>\" % (r_title, r_im_url, r_score)\n",
    "        i += 1\n",
    "        if i % 5 == 0:\n",
    "            sim_html += \"</tr><tr>\"\n",
    "    sim_html += \"</tr></table>\"\n",
    "    display(HTML(sim_html))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Now, you're ready to generate some recommendations.\n",
    "\n",
    "### 5(a) Find similar movies for a given movie\n",
    "\n",
    "To start, you can find movies that are _similar_ to a given movie. This similarity score is computed from the model factor vectors for each movie. Recall that the ALS model you trained earlier is a collaborative filtering model, so the similarity between movie vectors will be based on the _rating co-occurrence_ of the movies. In other words, two movies that tend to be rated highly by a user will tend to be more similar. It is common to use the [cosine similarity](https://en.wikipedia.org/wiki/Cosine_similarity) of the movie factor vectors as a measure of the similarity between two movies.\n",
    "\n",
    "Using this similarity you can show recommendations along the lines of _people who liked this movie also liked these_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Get similar movies for:</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h4>[u'Star Wars: Episode I - The Phantom Menace']</h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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m9Nk7sqxSN7MrBeyuvSGvlYq9sD+GX7wDKoplc3oZNhSdVuLwZDqP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Hf1O9zDdaGRpIcPez8YYrCUoRFZxDy9/bNXHrlF2R9J9ug1muigvaa+SHQfKYrHRSGggQ3C6T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\n0P05GEPp+2YARjIpigo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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<br>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h2>People who liked this movie also liked these:</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=0><td><h5>[u'Star Wars: Episode II - Attack of the Clones']</h5><img src=https://image.tmdb.org/t/p/w500/2vcNFtrZXNwIcBgH5e2xXCmVR8t.jpg width=150></img></td><td><h5>0.943</h5></td><td><h5>[u'X-Files: Fight the Future, The']</h5><img src=https://image.tmdb.org/t/p/w500/cpvwMPMkvsZLzThJTcnh8wcNPMH.jpg width=150></img></td><td><h5>0.932</h5></td><td><h5>[u'Matrix Reloaded, The']</h5><img src=https://image.tmdb.org/t/p/w500/ezIurBz2fdUc68d98Fp9dRf5ihv.jpg width=150></img></td><td><h5>0.914</h5></td><td><h5>[u'Kiss the Girls']</h5><img src=https://image.tmdb.org/t/p/w500/m9CyzlwbXhfUPooRIAcBoE63Frg.jpg width=150></img></td><td><h5>0.911</h5></td><td><h5>[u'World Is Not Enough, The']</h5><img src=https://image.tmdb.org/t/p/w500/aPfALBxfgx2tsbTwRMR1MbNHSvn.jpg width=150></img></td><td><h5>0.901</h5></td></tr><tr></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_similar(2628, num=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "So we see that people who like Star Wars tend like other sci-fi movies (including other Star Wars films), as well as some action and drama.\n",
    "\n",
    "> _Note_ since we are using a very small dataset, results may not be as good as those for the same model trained on a larger dataset.\n",
    "\n",
    "Now you will see the power and flexibility that comes from using a search engine to generate recommendations. Solr allows you to tweak the results returned by the recommendation query using any standard search query or filter - from free text search through to filters based on time and geo-location (or any other piece of metadata you can think of).\n",
    "\n",
    "For example, perhaps you want to remove any movies with \"matrix\" in the title from the recommendations. You can do this by simply passing a valid Solr query string to the recommendation function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Get similar movies for:</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h4>[u'Star Wars: Episode I - The Phantom Menace']</h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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m9Nk7sqxSN7MrBeyuvSGvlYq9sD+GX7wDKoplc3oZNhSdVuLwZDqP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Hf1O9zDdaGRpIcPez8YYrCUoRFZxDy9/bNXHrlF2R9J9ug1muigvaa+SHQfKYrHRSGggQ3C6T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\n0P05GEPp+2YARjIpigo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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<br>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h2>People who liked this movie also liked these:</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=0><td><h5>[u'Star Wars: Episode II - Attack of the Clones']</h5><img src=https://image.tmdb.org/t/p/w500/2vcNFtrZXNwIcBgH5e2xXCmVR8t.jpg width=150></img></td><td><h5>0.943</h5></td><td><h5>[u'X-Files: Fight the Future, The']</h5><img src=https://image.tmdb.org/t/p/w500/cpvwMPMkvsZLzThJTcnh8wcNPMH.jpg width=150></img></td><td><h5>0.932</h5></td><td><h5>[u'Kiss the Girls']</h5><img src=https://image.tmdb.org/t/p/w500/m9CyzlwbXhfUPooRIAcBoE63Frg.jpg width=150></img></td><td><h5>0.911</h5></td><td><h5>[u'World Is Not Enough, The']</h5><img src=https://image.tmdb.org/t/p/w500/aPfALBxfgx2tsbTwRMR1MbNHSvn.jpg width=150></img></td><td><h5>0.901</h5></td><td><h5>[u'Star Wars: Episode III - Revenge of the Sith']</h5><img src=https://image.tmdb.org/t/p/w500/tgr5Pdy7ehZYBqBkN2K7Q02xgOb.jpg width=150></img></td><td><h5>0.899</h5></td></tr><tr></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_similar(2628, num=5, q='NOT(title:matrix)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Or you may want to ensure that only valid children's movies are shown to young viewers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Get similar movies for:</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h4>[u'Toy Story']</h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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btXN+xy6Y7HY8He2JrUg2WNVXrpRzhjBjb06iyyg1s1d+GJ/1v0+PYemavexl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\ntcS8jTHDIiVWbDHRHsLclLuegNfHKtxyse+FxnR1aYHCOYVxPsjQTGDstYk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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
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       "<h2>People who liked this movie also liked these:</h2>"
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       "<table border=0><td><h5>[u'Finding Nemo']</h5><img src=https://image.tmdb.org/t/p/w500/syPWyeeqzTQIxjIUaIFI7d0TyEY.jpg width=150></img></td><td><h5>0.969</h5></td><td><h5>[u'Beauty and the Beast']</h5><img src=https://image.tmdb.org/t/p/w500/b9QJr2oblOu1grgOMUZF1xkUJdh.jpg width=150></img></td><td><h5>0.969</h5></td><td><h5>[u'Toy Story 2']</h5><img src=https://image.tmdb.org/t/p/w500/3CmK3XurcLeUyMifCR28ibzupbB.jpg width=150></img></td><td><h5>0.967</h5></td><td><h5>[u'Lion King, The']</h5><img src=https://image.tmdb.org/t/p/w500/bKPtXn9n4M4s8vvZrbw40mYsefB.jpg width=150></img></td><td><h5>0.962</h5></td><td><h5>[u'Shrek']</h5><img src=https://image.tmdb.org/t/p/w500/140ewbWv8qHStD3mlBDvvGd0Zvu.jpg width=150></img></td><td><h5>0.957</h5></td></tr><tr></tr></table>"
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   "source": [
    "display_similar(1, num=5, q=\"genres:children\")"
   ]
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    "Feel free to check out the documentation for the Solr [query string query](https://lucene.apache.org/solr/guide/6_6/searching.html) and play around with the various queries you can construct by passing in a query string as `q` in the recommendation function above!"
   ]
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    "### 5(b) Find movies to recommend to a user\n",
    "\n",
    "Now, you're ready to generate some movie recommendations, personalized for a specific user.\n",
    "\n",
    "Given a user, you can recommend movies to that user based on the predicted ratings from your model. In a similar manner to the similar movie recommendations, this predicted rating score is computed from the model factor vector for the user and the factor vectors for each movie. Recall that the collaborative filtering model means that, at a high level, we will recommend movies _liked by other users who liked the same movies as the given user_."
   ]
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       "<h2>Get recommended movies for user id 12</h2>"
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       "<table border=0><td><h5>[u'Harold and Maude']</h5><img src=https://image.tmdb.org/t/p/w500/xqay68babjK46U9WBFD2TmtnGcx.jpg width=150></img></td><td><h5>[u'Army of Darkness']</h5><img src=https://image.tmdb.org/t/p/w500/2eZKDIwLNnySbwqQtAaUz0kYDIL.jpg width=150></img></td><td><h5>[u'X-Men']</h5><img src=https://image.tmdb.org/t/p/w500/hJ09SIDACUvRg3RLQRT2jUfDy7W.jpg width=150></img></td><td><h5>[u'Blues Brothers, The']</h5><img src=https://image.tmdb.org/t/p/w500/6hesUNBkpVRqBTBw2HlTg0h8b56.jpg width=150></img></td><td><h5>[u'Coyote Ugly']</h5><img src=https://image.tmdb.org/t/p/w500/15A92dWMP4anntYpAQ0Mzq7wtru.jpg width=150></img></td></tr><tr></tr></table>"
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       "<h2>Recommended movies:</h2>"
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       "<table border=0><td><h5>[u\"Weekend at Bernie's\"]</h5><img src=https://image.tmdb.org/t/p/w500/h3hjMREZEUPtDkZBiYDzLq0THk0.jpg width=150></img></td><td><h5>7.576</h5></td><td><h5>[u'Pretty in Pink']</h5><img src=https://image.tmdb.org/t/p/w500/6CajvGupHEuWoxkvDHtYGSIHNgx.jpg width=150></img></td><td><h5>7.010</h5></td><td><h5>[u'Underworld']</h5><img src=https://image.tmdb.org/t/p/w500/rdkxl5iXdpVU188cL1LLG3sy6z4.jpg width=150></img></td><td><h5>6.898</h5></td><td><h5>[u'Guardians of the Galaxy']</h5><img src=https://image.tmdb.org/t/p/w500/y31QB9kn3XSudA15tV7UWQ9XLuW.jpg width=150></img></td><td><h5>6.628</h5></td><td><h5>[u'Arachnophobia']</h5><img src=https://image.tmdb.org/t/p/w500/pz4TWF3r6xqXN41Iqsjbf06rAQs.jpg width=150></img></td><td><h5>6.375</h5></td></tr><tr></tr></table>"
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   "source": [
    "display_user_recs(12, num=5, num_last=5)"
   ]
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    "Again, note that since we are using a very small dataset, the results may not be too good. However, we can see that this user seems to like some sci-fi, some horror and some comedy films. The recommended movies fall broadly into these categories and seem to be somewhat reasonable.\n",
    "\n",
    "Next, you can again apply the power of Solr's filtering capabilities to your recommendation engine. Let's say you only want to recommend more recent movies (say, from the past 5 years). This can be done by adding a date math query to the recommendation function query."
   ]
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       "<table border=0><td><h5>[u'Harold and Maude']</h5><img src=https://image.tmdb.org/t/p/w500/xqay68babjK46U9WBFD2TmtnGcx.jpg width=150></img></td><td><h5>[u'Army of Darkness']</h5><img src=https://image.tmdb.org/t/p/w500/2eZKDIwLNnySbwqQtAaUz0kYDIL.jpg width=150></img></td><td><h5>[u'X-Men']</h5><img src=https://image.tmdb.org/t/p/w500/hJ09SIDACUvRg3RLQRT2jUfDy7W.jpg width=150></img></td><td><h5>[u'Blues Brothers, The']</h5><img src=https://image.tmdb.org/t/p/w500/6hesUNBkpVRqBTBw2HlTg0h8b56.jpg width=150></img></td><td><h5>[u'Coyote Ugly']</h5><img src=https://image.tmdb.org/t/p/w500/15A92dWMP4anntYpAQ0Mzq7wtru.jpg width=150></img></td></tr><tr></tr></table>"
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       "<h2>Recommended movies:</h2>"
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       "<table border=0><td><h5>[u'Guardians of the Galaxy']</h5><img src=https://image.tmdb.org/t/p/w500/y31QB9kn3XSudA15tV7UWQ9XLuW.jpg width=150></img></td><td><h5>6.628</h5></td><td><h5>[u'Hobbit: An Unexpected Journey, The']</h5><img src=https://image.tmdb.org/t/p/w500/ysX7vDmSh5O19vFjAi56WL7l4nk.jpg width=150></img></td><td><h5>6.275</h5></td><td><h5>[u'Star Trek Into Darkness']</h5><img src=https://image.tmdb.org/t/p/w500/41mhrXASAW3sdn7LBWF49uCX0xi.jpg width=150></img></td><td><h5>5.771</h5></td><td><h5>[u'Divergent']</h5><img src=https://image.tmdb.org/t/p/w500/yTtx2ciqk4XdN1oKhMMDy3f5ue3.jpg width=150></img></td><td><h5>5.488</h5></td><td><h5>[u'The Hunger Games']</h5><img src=https://image.tmdb.org/t/p/w500/iLJdwmzrHFjFwI5lvYAT1gcpRuA.jpg width=150></img></td><td><h5>5.414</h5></td></tr><tr></tr></table>"
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   "source": [
    "display_user_recs(12, num=5, num_last=5, q=\"release_date:[2012 TO *]\")"
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    "You can see that the recommendation include only recent movies, and this time they seem to be heavily tilted to sci-fi and fantasy genres.\n",
    "\n",
    "As you did with the similar movies recommendations, feel free to play around with the various queries you could pass into the user recommendation query."
   ]
  }
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