python 算子demo

# -*- coding: gbk -*-
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.datastream.functions import RuntimeContext, FlatMapFunction, MapFunction
import json
import re
import logging
import sys
from pyflink.datastream.state import ValueStateDescriptor, MapStateDescriptor
from pyflink.datastream.connectors.kafka import FlinkKafkaConsumer, TypeInformation
from pyflink.common.typeinfo import Types
from pyflink.datastream.connectors.elasticsearch import Elasticsearch7SinkBuilder, ElasticsearchEmitter, FlushBackoffType
from  pyflink.datastream.connectors import  DeliveryGuarantee
from pyflink.common.serialization import SimpleStringSchema
from datetime import datetime


logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(asctime)s-%(levelname)s-%(message)s")
logger = logging.getLogger(__name__)

# 创建 StreamExecutionEnvironment 对象
env = StreamExecutionEnvironment.get_execution_environment()
env.set_parallelism(1)
#env.add_jars("file:///root/pyflink/flink-sql-connector-kafka_2.11-1.14.4.jar")

TEST_KAFKA_SERVERS = "1.1.101.39:9092,1.1.101.40:9092,1.1.101.42:9092"
TEST_KAFKA_TOPIC = "elink-midsys-flink-topic"
TEST_GROUP_ID = "pyflink_elink_midsys"


def get_kafka_customer_properties(kafka_servers: str, group_id: str):
    properties = {
        "bootstrap.servers": kafka_servers,
        "fetch.max.bytes": "67108864",
        "key.deserializer": "org.apache.kafka.common.serialization.StringDeserializer",
        "value.deserializer": "org.apache.kafka.common.serialization.StringDeserializer",
        "enable.auto.commit": "false",  # 关闭kafka 自动提交,此处不能传bool 类型会报错
        "group.id": group_id,
    }
    return properties


properties = get_kafka_customer_properties(TEST_KAFKA_SERVERS, TEST_GROUP_ID)


class LogEvent:
    # id表示全局流水
    id = None
    # source ip
    source = None
    #进程名字
    fileTag= None
    #文件名字
    fileName = None
    #场景码
    serviceCode = None
    #系统名字
    appName= None
    #时间戳
    timestamp = None
    #偏移量
    offset = None

    def __init__(self, id,source, fileTag,fileName, serviceCode,appName,timestamp,offset,message,index_name):
        self.id=id
        self.source = source
        self.fileTag = fileTag
        self.fileName = fileName
        self.serviceCode = serviceCode
        self.appName = appName
        self.timestamp= timestamp
        self.offset = offset
        self.message = message
        self.index_name = index_name

    def to_dict(self):
        return {
            "id": str(self.id),
            "source": str(self.source),
            "fileTag": str(self.fileTag),
            "fileName":str(self.fileName),
            "serviceCode":str(self.serviceCode),
            "appName":str(self.appName),
            "timestamp":self.timestamp,
            "offset":str(self.offset),
            "message":self.message,
            "index_name": self.index_name
        }


class MyMapFunction(FlatMapFunction):
    def open(self, runtime_context: RuntimeContext):
        self.process_id_to_bus_seq = runtime_context.get_map_state(MapStateDescriptor('process_id_map_bus_seq', Types.STRING(), Types.STRING()))

    def flat_map(self, raw_message):
        id = ''
        source =''
        fileTag =''
        fileName =''
        serviceCode =''
        appName =''
        timestamp =''
        process_id = ''
        offset =''
        message =''
        unique_key =''
        try:
           raw_message = raw_message.replace("\n", "")
           #print(raw_message)
           out=json.loads(raw_message)
           message = out['message']
           source = out['source']
           fileTag = out['file_tag']
           serviceCode='00000'
           appName=out['app_name']
           timestamp=str(out.get('time_nano'))
           offset=out.get('offset')
           fileName=out.get('file_name')
           pattern = r".*?接收数据.*?\d{26}"
           matchObj = re.match(pattern, message)
        except:
             #logger.info('1111111111111111111111111111111')
             return
        if matchObj:
            try:
                pat = re.compile(r".*?接收数据.*?(\d{26}).*?")
                bus_seq = pat.search(message).group(1)
                process_id = message.split()[1]
                unique_key=source+'_'+ appName +'_'+ fileTag +'_'+str(process_id)
                self.process_id_to_bus_seq.put(unique_key, bus_seq)
            except:
                #print('ValueError:', e)
                #logger.info('22222222222222222222222222222222')
                return
        try:         
            process_id = message.split()[1]
            unique_key=source+'_'+ appName +'_'+ fileTag +'_'+str(process_id)
        except:
            #print('ValueError:', e)
            #logger.info('333333333333333333333')
            return
        try:
            bus_seq = self.process_id_to_bus_seq.get(unique_key)
        except:
            return
        if not bus_seq:
            bus_seq = '0'
        id=bus_seq
        # self.r.delete(process_id)
        # log_event = LogEvent(bus_seq.decode('UTF-8'),message)
        # LogEvent['bus_seq']=bus_seq.decode('UTF-8')
        date_str = datetime.now().strftime("%Y%m%d")
        index_name = 'flink-log-elink-midsys-'+ str(date_str)
        try:
            log_event = LogEvent(id,source, fileTag,fileName, serviceCode,appName,timestamp,offset,message,index_name)
        except:
            return
        #print(log_event.to_dict())
        yield log_event.to_dict()


data_stream = env.add_source(
    FlinkKafkaConsumer(topics=TEST_KAFKA_TOPIC,
        properties=properties,
        deserialization_schema=SimpleStringSchema()) \
        .set_commit_offsets_on_checkpoints(True) \
        .set_start_from_latest()
).name(f"消费{TEST_KAFKA_TOPIC}主题数据")

#env.add_jars("file:///root/pyflink/flink-sql-connector-elasticsearch7-3.0.1-1.16.jar")

# .set_hosts(['1.1.101.32:9200','1.1.101.33:9200','1.1.101.38:9200']) \
es_sink = Elasticsearch7SinkBuilder() \
        .set_bulk_flush_backoff_strategy(FlushBackoffType.EXPONENTIAL, 5, 1000) \
        .set_emitter(ElasticsearchEmitter.dynamic_index('index_name')) \
        .set_hosts(['1.1.101.32:9200','1.1.101.33:9200','1.1.101.38:9200']) \
        .set_delivery_guarantee(DeliveryGuarantee.AT_LEAST_ONCE) \
        .set_bulk_flush_max_actions(10) \
        .set_bulk_flush_max_size_mb(2) \
        .set_bulk_flush_interval(1000) \
        .set_connection_request_timeout(30000) \
        .set_connection_timeout(31000) \
        .set_socket_timeout(32000) \
        .build()

def get_line_key(line):
    message = ''
    try:
        message = line.replace("\n", "")
        line = json.loads(message)['message']
        process_id = line.split()[1]
    except:
        process_id = '999999'
    return process_id

# data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(),Types.STRING())).sink_to(es7_sink)
#data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).sink_to(es7_sink).set_parallelism(3)
#data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).sink_to(es7_sink).set_parallelism(3)
data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).sink_to(es_sink).set_parallelism(3)
#data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).print()
#data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).print()

# 执行任务
env.execute('flink_elink_midsys')
 

你可能感兴趣的:(Flink实时计算,kafka,java,分布式)