# -*- 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
from pyflink.common.time import Time
from pyflink.common.typeinfo import Types
from pyflink.datastream.state import ValueStateDescriptor, StateTtlConfig
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):
ttl_config = StateTtlConfig \
.new_builder(Time.seconds(120)) \
.set_update_type(StateTtlConfig.UpdateType.OnCreateAndWrite) \
.set_state_visibility(StateTtlConfig.StateVisibility.NeverReturnExpired) \
.build()
desciption_map=MapStateDescriptor('process_id_map_bus_seq', Types.STRING(), Types.STRING())
desciption_map.enable_time_to_live(ttl_config)
self.process_id_to_bus_seq = runtime_context.get_map_state(desciption_map)
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:
if self.process_id_to_bus_seq.contains(unique_key):
self.process_id_to_bus_seq.remove(unique_key)
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(100) \
.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", "")
source = json.loads(message)['source']
except:
source = '999999'
return source
data_stream.key_by(get_line_key).flat_map(MyMapFunction(),output_type=Types.MAP(Types.STRING(), Types.STRING())).set_parallelism(2).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()文章来源:https://www.toymoban.com/news/detail-543951.html
# 执行任务
env.execute('xxx')
文章来源地址https://www.toymoban.com/news/detail-543951.html
到了这里,关于pyflink中的状态ttl设置的文章就介绍完了。如果您还想了解更多内容,请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章,希望大家以后多多支持TOY模板网!