python消费kafka数据批量插入到es的方法

Python  /  管理员 发布于 7年前   198

1、es的批量插入

这是为了方便后期配置的更改，把配置信息放在logging.conf中

用elasticsearch来实现批量操作，先安装依赖包，sudo pip install Elasticsearch2

from elasticsearch import Elasticsearch class ImportEsData:  logging.config.fileConfig("logging.conf")  logger = logging.getLogger("msg")  def __init__(self,hosts,index,type):    self.es = Elasticsearch(hosts=hosts.strip(',').split(','), timeout=5000)    self.index = index    self.type = type  def set_date(self,data):     # 批量处理     # es.index(index="test-index",doc_type="test-type",id=42,body={"any":"data","timestamp":datetime.now()})    self.es.index(index=self.index,doc_type=self.index,body=data)

2、使用pykafka消费kafka

1.因为kafka是0.8，pykafka不支持zk，只能用get_simple_consumer来实现

2.为了实现多个应用同时消费而且不重消费，所以一个应用消费一个partition

3. 为是确保消费数据量在不满足10000这个批量值，能在一个时间范围内插入到es中，这里设置consumer_timeout_ms一个超时等待时间，退出等待消费阻塞。

4.退出等待消费阻塞后导致无法再消费数据，因此在获取self.consumer 的外层加入了while True 一个死循环

#!/usr/bin/python# -*- coding: UTF-8 -*-from pykafka import KafkaClientimport loggingimport logging.configfrom ConfigUtil import ConfigUtilimport datetimeclass KafkaPython:  logging.config.fileConfig("logging.conf")  logger = logging.getLogger("msg")  logger_data = logging.getLogger("data")  def __init__(self):    self.server = ConfigUtil().get("kafka","kafka_server")    self.topic = ConfigUtil().get("kafka","topic")    self.group = ConfigUtil().get("kafka","group")    self.partition_id = int(ConfigUtil().get("kafka","partition"))    self.consumer_timeout_ms = int(ConfigUtil().get("kafka","consumer_timeout_ms"))    self.consumer = None    self.hosts = ConfigUtil().get("es","hosts")    self.index_name = ConfigUtil().get("es","index_name")    self.type_name = ConfigUtil().get("es","type_name")  def getConnect(self):    client = KafkaClient(self.server)    topic = client.topics[self.topic]    p = topic.partitions    ps={p.get(self.partition_id)}    self.consumer = topic.get_simple_consumer(      consumer_group=self.group,      auto_commit_enable=True,      consumer_timeout_ms=self.consumer_timeout_ms,      # num_consumer_fetchers=1,      # consumer_id='test1',      partitions=ps      )    self.starttime = datetime.datetime.now()  def beginConsumer(self):    print("beginConsumer kafka-python")    imprtEsData = ImportEsData(self.hosts,self.index_name,self.type_name)    #创建ACTIONS     count = 0    ACTIONS = []     while True:      endtime = datetime.datetime.now()      print (endtime - self.starttime).seconds      for message in self.consumer:        if message is not None:          try:count = count + 1# print(str(message.partition.id)+","+str(message.offset)+","+str(count))# self.logger.info(str(message.partition.id)+","+str(message.offset)+","+str(count))action = {   "_index": self.index_name,   "_type": self.type_name,   "_source": message.value}ACTIONS.append(action)if len(ACTIONS) >= 10000:  imprtEsData.set_date(ACTIONS)  ACTIONS = []  self.consumer.commit_offsets()  endtime = datetime.datetime.now()  print (endtime - self.starttime).seconds  #break          except (Exception) as e:# self.consumer.commit_offsets()print(e)self.logger.error(e)self.logger.error(str(message.partition.id)+","+str(message.offset)+","+message.value+"\n")# self.logger_data.error(message.value+"\n")          # self.consumer.commit_offsets()      if len(ACTIONS) > 0:        self.logger.info("等待时间超过，consumer_timeout_ms，把集合数据插入es")        imprtEsData.set_date(ACTIONS)        ACTIONS = []        self.consumer.commit_offsets()  def disConnect(self):    self.consumer.close()from elasticsearch import Elasticsearch from elasticsearch.helpers import bulkclass ImportEsData:  logging.config.fileConfig("logging.conf")  logger = logging.getLogger("msg")  def __init__(self,hosts,index,type):    self.es = Elasticsearch(hosts=hosts.strip(',').split(','), timeout=5000)    self.index = index    self.type = type  def set_date(self,data):     # 批量处理     success = bulk(self.es, data, index=self.index, raise_on_error=True)     self.logger.info(success) 

3、运行

if __name__ == '__main__':  kp = KafkaPython()  kp.getConnect()  kp.beginConsumer()  # kp.disConnect()

注：简单的写了一个从kafka中读取数据到一个list里，当数据达到一个阈值时，在批量插入到 es的插件

现在还在批量的压测中。。。

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