{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hadoop MapReduce: Python Streaming with mrjob\n",
    "\n",
    "* Introduction\n",
    "* Setup\n",
    "* Processing S3 Logs\n",
    "* Running Amazon Elastic MapReduce (EMR) Jobs\n",
    "* Unit Testing S3 Logs\n",
    "* Running S3 Logs Unit Test\n",
    "* Sample .mrjob.conf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "[mrjob](https://pythonhosted.org/mrjob/) lets you write MapReduce jobs in Python 2.5+ and run them on several platforms. You can:\n",
    "\n",
    "* Write multi-step MapReduce jobs in pure Python\n",
    "* Test on your local machine\n",
    "* Run on a Hadoop cluster\n",
    "* Run in the cloud using Amazon Elastic MapReduce (EMR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "From PyPI:\n",
    "\n",
    "``pip install mrjob``\n",
    "\n",
    "From source:\n",
    "\n",
    "``python setup.py install``\n",
    "\n",
    "See \"Sample .mrjob.conf\" section for additional config details."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Processing S3 Logs\n",
    "\n",
    "Sample mrjob code that processes log files on Amazon S3 based on the [S3 logging format](http://docs.aws.amazon.com/AmazonS3/latest/dev/LogFormat.html):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%file mr_s3_log_parser.py\n",
    "\n",
    "import time\n",
    "from mrjob.job import MRJob\n",
    "from mrjob.protocol import RawValueProtocol, ReprProtocol\n",
    "import re\n",
    "\n",
    "\n",
    "class MrS3LogParser(MRJob):\n",
    "    \"\"\"Parses the logs from S3 based on the S3 logging format:\n",
    "    http://docs.aws.amazon.com/AmazonS3/latest/dev/LogFormat.html\n",
    "    \n",
    "    Aggregates a user's daily requests by user agent and operation\n",
    "    \n",
    "    Outputs date_time, requester, user_agent, operation, count\n",
    "    \"\"\"\n",
    "\n",
    "    LOGPATS  = r'(\\S+) (\\S+) \\[(.*?)\\] (\\S+) (\\S+) ' \\\n",
    "               r'(\\S+) (\\S+) (\\S+) (\"([^\"]+)\"|-) ' \\\n",
    "               r'(\\S+) (\\S+) (\\S+) (\\S+) (\\S+) (\\S+) ' \\\n",
    "               r'(\"([^\"]+)\"|-) (\"([^\"]+)\"|-)'\n",
    "    NUM_ENTRIES_PER_LINE = 17\n",
    "    logpat = re.compile(LOGPATS)\n",
    "\n",
    "    (S3_LOG_BUCKET_OWNER, \n",
    "     S3_LOG_BUCKET, \n",
    "     S3_LOG_DATE_TIME,\n",
    "     S3_LOG_IP, \n",
    "     S3_LOG_REQUESTER_ID, \n",
    "     S3_LOG_REQUEST_ID,\n",
    "     S3_LOG_OPERATION, \n",
    "     S3_LOG_KEY, \n",
    "     S3_LOG_HTTP_METHOD,\n",
    "     S3_LOG_HTTP_STATUS, \n",
    "     S3_LOG_S3_ERROR, \n",
    "     S3_LOG_BYTES_SENT,\n",
    "     S3_LOG_OBJECT_SIZE, \n",
    "     S3_LOG_TOTAL_TIME, \n",
    "     S3_LOG_TURN_AROUND_TIME,\n",
    "     S3_LOG_REFERER, \n",
    "     S3_LOG_USER_AGENT) = range(NUM_ENTRIES_PER_LINE)\n",
    "\n",
    "    DELIMITER = '\\t'\n",
    "\n",
    "    # We use RawValueProtocol for input to be format agnostic\n",
    "    # and avoid any type of parsing errors\n",
    "    INPUT_PROTOCOL = RawValueProtocol\n",
    "\n",
    "    # We use RawValueProtocol for output so we can output raw lines\n",
    "    # instead of (k, v) pairs\n",
    "    OUTPUT_PROTOCOL = RawValueProtocol\n",
    "\n",
    "    # Encode the intermediate records using repr() instead of JSON, so the\n",
    "    # record doesn't get Unicode-encoded\n",
    "    INTERNAL_PROTOCOL = ReprProtocol\n",
    "\n",
    "    def clean_date_time_zone(self, raw_date_time_zone):\n",
    "        \"\"\"Converts entry 22/Jul/2013:21:04:17 +0000 to the format\n",
    "        'YYYY-MM-DD HH:MM:SS' which is more suitable for loading into\n",
    "        a database such as Redshift or RDS\n",
    "\n",
    "        Note: requires the chars \"[ ]\" to be stripped prior to input\n",
    "        Returns the converted datetime annd timezone\n",
    "        or None for both values if failed\n",
    "\n",
    "        TODO: Needs to combine timezone with date as one field\n",
    "        \"\"\"\n",
    "        date_time = None\n",
    "        time_zone_parsed = None\n",
    "\n",
    "        # TODO: Probably cleaner to parse this with a regex\n",
    "        date_parsed = raw_date_time_zone[:raw_date_time_zone.find(\":\")]\n",
    "        time_parsed = raw_date_time_zone[raw_date_time_zone.find(\":\") + 1:\n",
    "                                         raw_date_time_zone.find(\"+\") - 1]\n",
    "        time_zone_parsed = raw_date_time_zone[raw_date_time_zone.find(\"+\"):]\n",
    "\n",
    "        try:\n",
    "            date_struct = time.strptime(date_parsed, \"%d/%b/%Y\")\n",
    "            converted_date = time.strftime(\"%Y-%m-%d\", date_struct)\n",
    "            date_time = converted_date + \" \" + time_parsed\n",
    "\n",
    "        # Throws a ValueError exception if the operation fails that is\n",
    "        # caught by the calling function and is handled appropriately\n",
    "        except ValueError as error:\n",
    "            raise ValueError(error)\n",
    "        else:\n",
    "            return converted_date, date_time, time_zone_parsed\n",
    "\n",
    "    def mapper(self, _, line):\n",
    "        line = line.strip()\n",
    "        match = self.logpat.search(line)\n",
    "\n",
    "        date_time = None\n",
    "        requester = None\n",
    "        user_agent = None\n",
    "        operation = None\n",
    "\n",
    "        try:\n",
    "            for n in range(self.NUM_ENTRIES_PER_LINE):\n",
    "                group = match.group(1 + n)\n",
    "\n",
    "                if n == self.S3_LOG_DATE_TIME:\n",
    "                    date, date_time, time_zone_parsed = \\\n",
    "                        self.clean_date_time_zone(group)\n",
    "                    # Leave the following line of code if \n",
    "                    # you want to aggregate by date\n",
    "                    date_time = date + \" 00:00:00\"\n",
    "                elif n == self.S3_LOG_REQUESTER_ID:\n",
    "                    requester = group\n",
    "                elif n == self.S3_LOG_USER_AGENT:\n",
    "                    user_agent = group\n",
    "                elif n == self.S3_LOG_OPERATION:\n",
    "                    operation = group\n",
    "                else:\n",
    "                    pass\n",
    "\n",
    "        except Exception:\n",
    "            yield ((\"Error while parsing line: %s\", line), 1)\n",
    "        else:\n",
    "            yield ((date_time, requester, user_agent, operation), 1)\n",
    "\n",
    "    def reducer(self, key, values):\n",
    "        output = list(key)\n",
    "        output = self.DELIMITER.join(output) + \\\n",
    "                 self.DELIMITER + \\\n",
    "                 str(sum(values))\n",
    "\n",
    "        yield None, output\n",
    "\n",
    "    def steps(self):\n",
    "        return [\n",
    "            self.mr(mapper=self.mapper,\n",
    "                    reducer=self.reducer)\n",
    "        ]\n",
    "\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    MrS3LogParser.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running Amazon Elastic MapReduce (EMR) Jobs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run an Amazon EMR job on the given input (must be a flat file hierarchy), placing the results in the output (output directory must not exist):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "!python mr-mr_s3_log_parser.py -r emr s3://bucket-source/ --output-dir=s3://bucket-dest/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run a MapReduce job locally on the specified input file, sending the results to the specified output file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "!python mr_s3_log_parser.py input_data.txt > output_data.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit Testing S3 Logs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accompanying unit test:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%file test_mr_s3_log_parser.py\n",
    "\n",
    "from StringIO import StringIO\n",
    "import unittest2 as unittest\n",
    "from mr_s3_log_parser import MrS3LogParser\n",
    "\n",
    "\n",
    "class MrTestsUtil:\n",
    "\n",
    "    def run_mr_sandbox(self, mr_job, stdin):\n",
    "        # inline runs the job in the same process so small jobs tend to\n",
    "        # run faster and stack traces are simpler\n",
    "        # --no-conf prevents options from local mrjob.conf from polluting\n",
    "        # the testing environment\n",
    "        # \"-\" reads from standard in\n",
    "        mr_job.sandbox(stdin=stdin)\n",
    "\n",
    "        # make_runner ensures job cleanup is performed regardless of\n",
    "        # success or failure\n",
    "        with mr_job.make_runner() as runner:\n",
    "            runner.run()\n",
    "            for line in runner.stream_output():\n",
    "                key, value = mr_job.parse_output_line(line)\n",
    "                yield value\n",
    "\n",
    "                \n",
    "class TestMrS3LogParser(unittest.TestCase):\n",
    "\n",
    "    mr_job = None\n",
    "    mr_tests_util = None\n",
    "\n",
    "    RAW_LOG_LINE_INVALID = \\\n",
    "        '00000fe9688b6e57f75bd2b7f7c1610689e8f01000000' \\\n",
    "        '00000388225bcc00000 ' \\\n",
    "        's3-storage [22/Jul/2013:21:03:27 +0000] ' \\\n",
    "        '00.111.222.33 ' \\\n",
    "\n",
    "    RAW_LOG_LINE_VALID = \\\n",
    "        '00000fe9688b6e57f75bd2b7f7c1610689e8f01000000' \\\n",
    "        '00000388225bcc00000 ' \\\n",
    "        's3-storage [22/Jul/2013:21:03:27 +0000] ' \\\n",
    "        '00.111.222.33 ' \\\n",
    "        'arn:aws:sts::000005646931:federated-user/user 00000AB825500000 ' \\\n",
    "        'REST.HEAD.OBJECT user/file.pdf ' \\\n",
    "        '\"HEAD /user/file.pdf?versionId=00000XMHZJp6DjM9x500000' \\\n",
    "        '00000SDZk ' \\\n",
    "        'HTTP/1.1\" 200 - - 4000272 18 - \"-\" ' \\\n",
    "        '\"Boto/2.5.1 (darwin) USER-AGENT/1.0.14.0\" ' \\\n",
    "        '00000XMHZJp6DjM9x5JVEAMo8MG00000'\n",
    "\n",
    "    DATE_TIME_ZONE_INVALID = \"AB/Jul/2013:21:04:17 +0000\"\n",
    "    DATE_TIME_ZONE_VALID = \"22/Jul/2013:21:04:17 +0000\"\n",
    "    DATE_VALID = \"2013-07-22\"\n",
    "    DATE_TIME_VALID = \"2013-07-22 21:04:17\"\n",
    "    TIME_ZONE_VALID = \"+0000\"\n",
    "\n",
    "    def __init__(self, *args, **kwargs):\n",
    "        super(TestMrS3LogParser, self).__init__(*args, **kwargs)\n",
    "        self.mr_job = MrS3LogParser(['-r', 'inline', '--no-conf', '-'])\n",
    "        self.mr_tests_util = MrTestsUtil()\n",
    "\n",
    "    def test_invalid_log_lines(self):\n",
    "        stdin = StringIO(self.RAW_LOG_LINE_INVALID)\n",
    "\n",
    "        for result in self.mr_tests_util.run_mr_sandbox(self.mr_job, stdin):\n",
    "            self.assertEqual(result.find(\"Error\"), 0)\n",
    "\n",
    "    def test_valid_log_lines(self):\n",
    "        stdin = StringIO(self.RAW_LOG_LINE_VALID)\n",
    "\n",
    "        for result in self.mr_tests_util.run_mr_sandbox(self.mr_job, stdin):\n",
    "            self.assertEqual(result.find(\"Error\"), -1)\n",
    "\n",
    "    def test_clean_date_time_zone(self):\n",
    "        date, date_time, time_zone_parsed = \\\n",
    "            self.mr_job.clean_date_time_zone(self.DATE_TIME_ZONE_VALID)\n",
    "        self.assertEqual(date, self.DATE_VALID)\n",
    "        self.assertEqual(date_time, self.DATE_TIME_VALID)\n",
    "        self.assertEqual(time_zone_parsed, self.TIME_ZONE_VALID)\n",
    "\n",
    "        # Use a lambda to delay the calling of clean_date_time_zone so that\n",
    "        # assertRaises has enough time to handle it properly\n",
    "        self.assertRaises(ValueError,\n",
    "            lambda: self.mr_job.clean_date_time_zone(\n",
    "                self.DATE_TIME_ZONE_INVALID))\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    unittest.main()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running S3 Logs Unit Test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the mrjob test:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "!python test_mr_s3_log_parser.py -v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample .mrjob.conf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "runners:\n",
    "  emr:\n",
    "    aws_access_key_id: __ACCESS_KEY__\n",
    "    aws_secret_access_key: __SECRET_ACCESS_KEY__\n",
    "    aws_region: us-east-1\n",
    "    ec2_key_pair: EMR\n",
    "    ec2_key_pair_file: ~/.ssh/EMR.pem\n",
    "    ssh_tunnel_to_job_tracker: true\n",
    "    ec2_master_instance_type: m3.xlarge\n",
    "    ec2_instance_type: m3.xlarge\n",
    "    num_ec2_instances: 5\n",
    "    s3_scratch_uri: s3://bucket/tmp/\n",
    "    s3_log_uri: s3://bucket/tmp/logs/\n",
    "    enable_emr_debugging: True\n",
    "    bootstrap:\n",
    "    - sudo apt-get install -y python-pip\n",
    "    - sudo pip install --upgrade simplejson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}