Flink实现kafka到kafka、kafka到doris的精准一次消费

1 流程图

2 Flink来源表建模

--来源-城市topic
CREATE TABLE NJ_QL_JC_SSJC_SOURCE (
record string 
) WITH (
	'connector' = 'kafka',
	'topic' = 'QL_JC_SSJC',
	'properties.bootstrap.servers' = '172.*.*.*:9092',
	'properties.group.id' = 'QL_JC_SSJC_NJ_QL_JC_SSJC_SOURCE',
    'scan.startup.mode' = 'group-offsets',
    'properties.isolation.level' = 'read_committed',
    'properties.auto.offset.reset' = 'earliest',
	'format' = 'raw'
);
--来源-中台kafka-topic
CREATE TABLE ODS_QL_JC_SSJC_SOURCE (
sscsdm string,
extract_time TIMESTAMP,
record string
) WITH (
	'connector' = 'kafka',
	'topic' = 'ODS_QL_JC_SSJC',
	'properties.bootstrap.servers' = '172.*.*.*:21007,172.*.*.*:21007,172.*.*.*:21007',
	'properties.security.protocol' = 'SASL_PLAINTEXT',
	'properties.sasl.kerberos.service.name' = 'kafka',
	'properties.kerberos.domain.name' = 'hadoop.hadoop.com',
	'properties.group.id' = 'ODS_QL_JC_SSJC_SOURCE_ODS_QL_JC_SSJC_SOURCE',
	'scan.startup.mode' = 'group-offsets',
   'properties.auto.offset.reset' = 'earliest',
   'properties.isolation.level' = 'read_committed',
   'sink.semantic' = 'exactly-once',
	'format' = 'json'
);

3 Flink去向表建模

--去向-中台kafka-topic
CREATE TABLE KAFKA_ODS_QL_JC_SSJC_SINK  (
sscsdm string,
extract_time TIMESTAMP,
record string
) WITH (
	'connector' = 'kafka',
	'topic' = 'ODS_QL_JC_SSJC',
	'properties.bootstrap.servers' = '172.*.*.*:21007,172.*.*.*:21007,172.*.*.*:21007',
	'properties.security.protocol' = 'SASL_PLAINTEXT',
	'properties.sasl.kerberos.service.name' = 'kafka',
	'properties.kerberos.domain.name' = 'hadoop.hadoop.com',
	'format' = 'json', 
   'properties.transaction.timeout.ms' = '900000'
);
--去向-Doris表
CREATE TABLE DORIS_ODS_QL_JC_SSJC_SINK (
	sscsdm STRING,
	extract_time TIMESTAMP,
	record STRING
) WITH (
	'connector' = 'doris',
	'fenodes' = '3.*.*.*:8030,3.*.*.*:8030,3.*.*.*:8030',
	'table.identifier' = 'doris_d.ods_ql_jc_ssjc',
	'username' = 'root',
	'password' = '********',
   'sink.properties.two_phase_commit' = 'true' 
);