小白通过debezium将pgsql cdc数据同步至kafka之后,使用我们flink的sql client提交测试任务,但当kafka端cdc json数据一开始发送,任务即报错,通过web ui log查看界面发现错误日志如下,还请大佬帮忙分析,谢谢!CREATE TABLE pgsql_person_cdc(
id BIGINT,
name STRING,
age STRING,
sex STRING,
phone STRING
) WITH (
'connector' = 'kafka',
'topic' = 'postgres.public.person',
'properties.bootstrap.servers' = 'localhost:9092',
'properties.group.id' = 'pgsql_cdc',
'format' = 'debezium-json',
'debezium-json.schema-include' = 'true'
)
CREATE TABLE sql_out (
id BIGINT,
name STRING,
age STRING,
sex STRING,
phone STRING
) WITH (
'connector' = 'print'
)
INSERT INTO sql_out SELECT * FROM pgsql_person_cdc;
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错误日志:
java.io.IOException: Corrupt Debezium JSON message '{"schema":{"type":"struct","fields":[{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"string","optional":true,"field":"name"},{"type":"string","optional":true,"field":"age"},{"type":"string","optional":true,"field":"sex"},{"type":"string","optional":true,"field":"phone"}],"optional":true,"name":"postgres.public.person.Value","field":"before"},{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"string","optional":true,"field":"name"},{"type":"string","optional":true,"field":"age"},{"type":"string","optional":true,"field":"sex"},{"type":"string","optional":true,"field":"phone"}],"optional":true,"name":"postgres.public.person.Value","field":"after"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"version"},{"type":"string","optional":false,"field":"connector"},{"type":"string","optional":false,"field":"name"},{"type":"int64","optional":false,"field":"ts_ms"},{"type":"string","optional":true,"name":"io.debezium.data.Enum","version":1,"parameters":{"allowed":"true,last,false"},"default":"false","field":"snapshot"},{"type":"string","optional":false,"field":"db"},{"type":"string","optional":false,"field":"schema"},{"type":"string","optional":false,"field":"table"},{"type":"int64","optional":true,"field":"txId"},{"type":"int64","optional":true,"field":"lsn"},{"type":"int64","optional":true,"field":"xmin"}],"optional":false,"name":"io.debezium.connector.postgresql.Source","field":"source"},{"type":"string","optional":false,"field":"op"},{"type":"int64","optional":true,"field":"ts_ms"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"id"},{"type":"int64","optional":false,"field":"total_order"},{"type":"int64","optional":false,"field":"data_collection_order"}],"optional":true,"field":"transaction"}],"optional":false,"name":"postgres.public.person.Envelope"},"payload":{"before":null,"after":{"id":2,"name":"liushimin","age":"24","sex":"man","phone":"155555555"},"source":{"version":"1.2.0.Final","connector":"postgresql","name":"postgres","ts_ms":1595409754151,"snapshot":"false","db":"postgres","schema":"public","table":"person","txId":569,"lsn":23632344,"xmin":null},"op":"u","ts_ms":1595409754270,"transaction":null}}'.
at org.apache.flink.formats.json.debezium.DebeziumJsonDeserializationSchema.deserialize(DebeziumJsonDeserializationSchema.java:136) ~[flink-json-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:56) ~[flink-connector-kafka-base_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.partitionConsumerRecordsHandler(KafkaFetcher.java:181) ~[flink-connector-kafka_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.runFetchLoop(KafkaFetcher.java:141) ~[flink-connector-kafka_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:755) ~[flink-connector-kafka-base_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:100) ~[flink-dist_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:63) ~[flink-dist_2.11-1.11.0.jar:1.11.0]
at org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:201) ~[flink-dist_2.11-1.11.0.jar:1.11.0]
Caused by: java.lang.NullPointerException
at org.apache.flink.formats.json.debezium.DebeziumJsonDeserializationSchema.deserialize(DebeziumJsonDeserializationSchema.java:120) ~[flink-json-1.11.0.jar:1.11.0]
... 7 more
2020-07-22 17:22:34,415 INFO org.apache.flink.runtime.taskmanager.Task [] - Freeing task resources for Source: TableSourceScan(table=[[default_catalog, default_database, pgsql_person_cdc]], fields=[id, name, age, sex, phone]) -> Sink: Sink(table=[default_catalog.default_database.sql_out], fields=[id, name, age, sex, phone]) (1/1) (b553cb66df6e47a27e7dae8466b684ab).
2020-07-22 17:22:34,418 INFO org.apache.flink.runtime.taskexecutor.TaskExecutor [] - Un-registering task and sending final execution state FAILED to JobManager for task Source: TableSourceScan(table=[[default_catalog, default_database, pgsql_person_cdc]], fields=[id, name, age, sex, phone]) -> Sink: Sink(table=[default_catalog.default_database.sql_out], fields=[id, name, age, sex, phone]) (1/1) b553cb66df6e47a27e7dae8466b684ab.
2020-07-22 17:22:34,461 INFO org.apache.flink.runtime.taskexecutor.slot.TaskSlotTableImpl [] - Free slot TaskSlot(index:0, state:ACTIVE, resource profile: ResourceProfile{cpuCores=1.0000000000000000, taskHeapMemory=384.000mb (402653174 bytes), taskOffHeapMemory=0 bytes, managedMemory=512.000mb (536870920 bytes), networkMemory=128.000mb (134217730 bytes)}, allocationId: 495bb5a0cd877808674b29890b6b8bc0, jobId: 3feda3a191fcb8e0da891b9fda1ee532).
2020-07-22 17:22:34,462 INFO org.apache.flink.runtime.taskexecutor.DefaultJobLeaderService [] - Remove job 3feda3a191fcb8e0da891b9fda1ee532 from job leader monitoring.
2020-07-22 17:22:34,462 INFO org.apache.flink.runtime.taskexecutor.TaskExecutor [] - Close JobManager connection for job 3feda3a191fcb8e0da891b9fda1ee532.
====================================分割线======================================*来自志愿者整理的flink邮件归档
代码在为before这条数据设置rowKind时抛了一个NPE,before正常应该是不为null的。 看起来是你的数据问题,一条 update 的changelog, before 为null, 这是不合理的,没有before的数据,是无法处理after的数据的。 如果确认是脏数据,可以开启ignore-parse-errors跳过[1]
祝好 Leonard [1]https://ci.apache.org/projects/flink/flink-docs-master/dev/table/connectors/formats/debezium.html#debezium-json-ignore-parse-errors https://ci.apache.org/projects/flink/flink-docs-master/dev/table/connectors/formats/debezium.html#debezium-json-ignore-parse-errors
{ "payload": { "before": null, "after": { "id": 2, "name": "liushimin", "age": "24", "sex": "man", "phone": "155555555" }, "source": { "version": "1.2.0.Final", "connector": "postgresql", "name": "postgres", "ts_ms": 1595409754151, "snapshot": "false", "db": "postgres", "schema": "public", "table": "person", "txId": 569, "lsn": 23632344, "xmin": null }, "op": "u", "ts_ms": 1595409754270, "transaction": null } }*来自志愿者整理的flink邮件归档
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