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from apache_beam.options.pipeline_options import PipelineOptions | |
from google.cloud import pubsub_v1 | |
from google.cloud import bigquery | |
import apache_beam as beam | |
import logging | |
import argparse | |
import sys | |
import re | |
PROJECT="user-logs-237110" | |
schema = 'remote_addr:STRING, timelocal:STRING, request_type:STRING, status:STRING, body_bytes_sent:STRING, http_referer:STRING, http_user_agent:STRING' | |
TOPIC = "projects/user-logs-237110/topics/userlogs" | |
def regex_clean(data): | |
PATTERNS = [r'(^\S+\.[\S+\.]+\S+)\s',r'(?<=\[).+?(?=\])', | |
r'\"(\S+)\s(\S+)\s*(\S*)\"',r'\s(\d+)\s',r"(?<=\[).\d+(?=\])", | |
r'\"[A-Z][a-z]+', r'\"(http|https)://[a-z]+.[a-z]+.[a-z]+'] | |
result = [] | |
for match in PATTERNS: | |
try: | |
reg_match = re.search(match, data).group() | |
if reg_match: | |
result.append(reg_match) | |
else: | |
result.append(" ") | |
except: | |
print("There was an error with the regex search") | |
result = [x.strip() for x in result] | |
result = [x.replace('"', "") for x in result] | |
res = ','.join(result) | |
return res | |
class Split(beam.DoFn): | |
def process(self, element): | |
from datetime import datetime | |
element = element.split(",") | |
d = datetime.strptime(element[1], "%d/%b/%Y:%H:%M:%S") | |
date_string = d.strftime("%Y-%m-%d %H:%M:%S") | |
return [{ | |
'remote_addr': element[0], | |
'timelocal': date_string, | |
'request_type': element[2], | |
'body_bytes_sent': element[3], | |
'status': element[4], | |
'http_referer': element[5], | |
'http_user_agent': element[6] | |
}] | |
def main(argv=None): | |
parser = argparse.ArgumentParser() | |
parser.add_argument("--input_topic") | |
parser.add_argument("--output") | |
known_args = parser.parse_known_args(argv) | |
p = beam.Pipeline(options=PipelineOptions()) | |
(p | |
| 'ReadData' >> beam.io.ReadFromPubSub(topic=TOPIC).with_output_types(bytes) | |
| "Decode" >> beam.Map(lambda x: x.decode('utf-8')) | |
| "Clean Data" >> beam.Map(regex_clean) | |
| 'ParseCSV' >> beam.ParDo(Split()) | |
| 'WriteToBigQuery' >> beam.io.WriteToBigQuery('{0}:userlogs.logdata'.format(PROJECT), schema=schema, | |
write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND) | |
) | |
result = p.run() | |
result.wait_until_finish() | |
if __name__ == '__main__': | |
logger = logging.getLogger().setLevel(logging.INFO) | |
main() |
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