| #!/bin/env python |
| |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| import sys |
| import subprocess |
| import datetime |
| import logging |
| import os |
| import json |
| from multiprocessing import Process |
| from common.utils import Util |
| from common import hive_engine |
| from common import hdfs_client as hdfs |
| from confluent_kafka import KafkaError, KafkaException |
| |
| |
| class Worker(object): |
| |
| def __init__(self, db_name, hdfs_app_path, kafka_consumer, conf_type, processes=None): |
| self._initialize_members(db_name, hdfs_app_path, kafka_consumer, conf_type) |
| |
| def _initialize_members(self, db_name, hdfs_app_path, kafka_consumer, conf_type): |
| |
| # get logger instance. |
| self._logger = Util.get_logger('SPOT.INGEST.WRK.FLOW') |
| |
| self._db_name = db_name |
| self._hdfs_app_path = hdfs_app_path |
| |
| # read proxy configuration. |
| self._script_path = os.path.dirname(os.path.abspath(__file__)) |
| conf_file = "{0}/ingest_conf.json".format(os.path.dirname(os.path.dirname(self._script_path))) |
| conf = json.loads(open(conf_file).read()) |
| self._conf = conf["pipelines"][conf_type] |
| self._id = "spot-{0}-worker".format(conf_type) |
| |
| self._process_opt = self._conf['process_opt'] |
| self._local_staging = self._conf['local_staging'] |
| self.kafka_consumer = kafka_consumer |
| |
| # self._cursor = hive_engine.create_connection() |
| self._cursor = hive_engine |
| |
| def start(self): |
| |
| self._logger.info("Listening topic:{0}".format(self.kafka_consumer.Topic)) |
| consumer = self.kafka_consumer.start() |
| try: |
| while True: |
| message = consumer.poll(timeout=1.0) |
| if message is None: |
| continue |
| if not message.error(): |
| self._new_file(message.value().decode('utf-8')) |
| elif message.error(): |
| if message.error().code() == KafkaError._PARTITION_EOF: |
| continue |
| elif message.error: |
| raise KafkaException(message.error()) |
| |
| except KeyboardInterrupt: |
| sys.stderr.write('%% Aborted by user\n') |
| |
| consumer.close() |
| |
| def _new_file(self, nf): |
| |
| self._logger.info( |
| "-------------------------------------- New File received --------------------------------------" |
| ) |
| self._logger.info("File: {0} ".format(nf)) |
| |
| p = Process(target=self._process_new_file, args=(nf, )) |
| p.start() |
| p.join() |
| |
| def _process_new_file(self, nf): |
| |
| # get file name and date |
| file_name_parts = nf.split('/') |
| file_name = file_name_parts[len(file_name_parts)-1] |
| nf_path = nf.rstrip(file_name) |
| flow_date = file_name.split('.')[1] |
| flow_year = flow_date[0:4] |
| flow_month = flow_date[4:6] |
| flow_day = flow_date[6:8] |
| flow_hour = flow_date[8:10] |
| |
| # get file from hdfs |
| if hdfs.file_exists(nf_path, file_name): |
| self._logger.info("Getting file from hdfs: {0}".format(nf)) |
| hdfs.download_file(nf, self._local_staging) |
| else: |
| self._logger.info("file: {0} not found".format(nf)) |
| # TODO: error handling |
| |
| # build process cmd. |
| sf = "{0}{1}.csv".format(self._local_staging,file_name) |
| process_cmd = "nfdump -o csv -r {0}{1} {2} > {3}".format(self._local_staging, file_name, self._process_opt, sf) |
| self._logger.info("Processing file: {0}".format(process_cmd)) |
| Util.execute_cmd(process_cmd,self._logger) |
| |
| # create hdfs staging. |
| hdfs_path = "{0}/flow".format(self._hdfs_app_path) |
| staging_timestamp = datetime.datetime.now().strftime('%M%S%f')[:-4] |
| hdfs_staging_path = "{0}/stage/{1}".format(hdfs_path,staging_timestamp) |
| self._logger.info("Creating staging: {0}".format(hdfs_staging_path)) |
| hdfs.mkdir(hdfs_staging_path) |
| |
| # move to stage. |
| local_file = "{0}{1}.csv".format(self._local_staging, file_name) |
| self._logger.info("Moving data to staging: {0}".format(hdfs_staging_path)) |
| hdfs.upload_file(hdfs_staging_path, local_file) |
| |
| # load with impyla |
| drop_table = "DROP TABLE IF EXISTS {0}.flow_tmp".format(self._db_name) |
| self._logger.info( "Dropping temp table: {0}".format(drop_table)) |
| self._cursor.execute_query(drop_table) |
| |
| create_external = ("\n" |
| "CREATE EXTERNAL TABLE {0}.flow_tmp (\n" |
| " treceived STRING,\n" |
| " tryear INT,\n" |
| " trmonth INT,\n" |
| " trday INT,\n" |
| " trhour INT,\n" |
| " trminute INT,\n" |
| " trsec INT,\n" |
| " tdur FLOAT,\n" |
| " sip STRING,\n" |
| " dip STRING,\n" |
| " sport INT,\n" |
| " dport INT,\n" |
| " proto STRING,\n" |
| " flag STRING,\n" |
| " fwd INT,\n" |
| " stos INT,\n" |
| " ipkt BIGINT,\n" |
| " ibyt BIGINT,\n" |
| " opkt BIGINT,\n" |
| " obyt BIGINT,\n" |
| " input INT,\n" |
| " output INT,\n" |
| " sas INT,\n" |
| " das INT,\n" |
| " dtos INT,\n" |
| " dir INT,\n" |
| " rip STRING\n" |
| " )\n" |
| " ROW FORMAT DELIMITED FIELDS TERMINATED BY ','\n" |
| " STORED AS TEXTFILE\n" |
| " LOCATION '{1}'\n" |
| " TBLPROPERTIES ('avro.schema.literal'='{{\n" |
| " \"type\": \"record\"\n" |
| " , \"name\": \"RawFlowRecord\"\n" |
| " , \"namespace\" : \"com.cloudera.accelerators.flows.avro\"\n" |
| " , \"fields\": [\n" |
| " {{\"name\": \"treceived\", \"type\":[\"string\", \"null\"]}}\n" |
| " , {{\"name\": \"tryear\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"trmonth\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"trday\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"trhour\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"trminute\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"trsec\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"tdur\", \"type\":[\"float\", \"null\"]}}\n" |
| " , {{\"name\": \"sip\", \"type\":[\"string\", \"null\"]}}\n" |
| " , {{\"name\": \"sport\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"dip\", \"type\":[\"string\", \"null\"]}}\n" |
| " , {{\"name\": \"dport\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"proto\", \"type\":[\"string\", \"null\"]}}\n" |
| " , {{\"name\": \"flag\", \"type\":[\"string\", \"null\"]}}\n" |
| " , {{\"name\": \"fwd\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"stos\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"ipkt\", \"type\":[\"bigint\", \"null\"]}}\n" |
| " , {{\"name\": \"ibyt\", \"type\":[\"bigint\", \"null\"]}}\n" |
| " , {{\"name\": \"opkt\", \"type\":[\"bigint\", \"null\"]}}\n" |
| " , {{\"name\": \"obyt\", \"type\":[\"bigint\", \"null\"]}}\n" |
| " , {{\"name\": \"input\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"output\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"sas\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"das\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"dtos\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"dir\", \"type\":[\"int\", \"null\"]}}\n" |
| " , {{\"name\": \"rip\", \"type\":[\"string\", \"null\"]}}\n" |
| " ]\n" |
| "}}')\n" |
| ).format(self._db_name, hdfs_staging_path) |
| self._logger.info( "Creating external table: {0}".format(create_external)) |
| self._cursor.execute_query(create_external) |
| |
| insert_into_table = """ |
| INSERT INTO TABLE {0}.flow |
| PARTITION (y={1}, m={2}, d={3}, h={4}) |
| SELECT treceived, unix_timestamp(treceived) AS unix_tstamp, tryear, trmonth, trday, trhour, trminute, trsec, |
| tdur, sip, dip, sport, dport, proto, flag, fwd, stos, ipkt, ibyt, opkt, obyt, input, output, |
| sas, das, dtos, dir, rip |
| FROM {0}.flow_tmp |
| """.format(self._db_name, flow_year, flow_month, flow_day, flow_hour) |
| self._logger.info( "Loading data to {0}: {1}" |
| .format(self._db_name, insert_into_table) |
| ) |
| self._cursor.execute_query(insert_into_table) |
| |
| # remove from hdfs staging |
| self._logger.info("Removing staging path: {0}".format(hdfs_staging_path)) |
| hdfs.delete_folder(hdfs_staging_path) |
| |
| # remove from local staging. |
| rm_local_staging = "rm {0}{1}".format(self._local_staging,file_name) |
| self._logger.info("Removing files from local staging: {0}".format(rm_local_staging)) |
| Util.execute_cmd(rm_local_staging,self._logger) |
| |
| rm_local_staging = "rm {0}".format(sf) |
| self._logger.info("Removing files from local staging: {0}".format(rm_local_staging)) |
| Util.execute_cmd(rm_local_staging,self._logger) |
| |
| self._logger.info("File {0} was successfully processed.".format(file_name)) |
