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  {
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   "source": [
    "# Simple Query Demo\n",
    "\n",
    "![pdbj](https://pdbj.org/content/default.svg)\n",
    "\n",
    "PDBj Mine 2 RDB keyword search query and MMTF filtering using pdbid.\n",
    "\n",
    "[PDBj Mine Search Website](https://pdbj.org/mine)\n",
    "\n",
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "from mmtfPyspark.webfilters import PdbjMineSearch\n",
    "from mmtfPyspark.datasets import pdbjMineDataset\n",
    "from mmtfPyspark.io import mmtfReader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configure Spark Context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "conf = SparkConf().setMaster(\"local[*]\") \\\n",
    "                  .setAppName(\"SimpleQuerySearch\")\n",
    "    \n",
    "sc = SparkContext(conf = conf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read in MMTF files from local directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"../../resources/mmtf_full_sample/\"\n",
    "\n",
    "pdb = mmtfReader.read_sequence_file(path, sc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Apply a SQL search on PDBj using a filter\n",
    "\n",
    "Very simple query; this gets the pdbids for all entries modified since 2016-06-28 with a resulution better than 1.5 A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of entries using sql to filter: 11\n"
     ]
    }
   ],
   "source": [
    "sql = \"select pdbid from brief_summary where modification_date >= '2016-06-28' and resolution < 1.5\"\n",
    "\n",
    "search = PdbjMineSearch(sql)\n",
    "count = pdb.filter(search).keys().count()\n",
    "print(f\"Number of entries using sql to filter: {count}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply a SQL search on PDBj and get a dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----------+\n",
      "|structureId|\n",
      "+-----------+\n",
      "|       5U8P|\n",
      "|       5U8U|\n",
      "|       5U8V|\n",
      "|       5U9D|\n",
      "|       5UAM|\n",
      "+-----------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dataset = pdbjMineDataset.get_dataset(sql)\n",
    "dataset.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Terminate Spark Context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  }
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