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Removed mrjob hadoop mapreduce section, it was moved to its own notebook.

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Donne Martin 2015-04-16 06:57:46 -04:00
parent 30e48368e6
commit 815accffa0
1 changed files with 1 additions and 331 deletions
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aws/aws.ipynb
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@ -4,13 +4,12 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# AWS Command Lines\n",
"# Amazon Web Services (AWS)\n",
"\n",
"* SSH to EC2\n",
"* S3cmd\n",
"* s3-parallel-put\n",
"* S3DistCp\n",
"* mrjob\n",
"* Redshift\n",
"* Kinesis\n",
"* Lambda"
@ -348,335 +347,6 @@
"--outputCodec,lzo"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h2 id=\"mrjob\">mrjob</h2>\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": [
"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-script.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 mrjob_script.py input_data.txt > output_data.txt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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": [
"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": [
"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": {},