Hi, Thanks for the quick response. The use case is not specific to JDBC (JDBC is just an example) but more for custom error handling in all connectors. How would we go about proposing such a new feature to be added to Flink?
On 2021/08/25 09:02:31, Caizhi Weng <t...@gmail.com> wrote: > Hi!> > > As far as I know JDBC does not have this error handling mechanism. Also> > there are very few connectors / formats which support skipping> > erroneous records (for example the csv format).> > > Which type of exception are you faced with? As JDBC connectors, unlike> > message queue connectors, rarely (if ever?) suffer from records with bad> > formats.> > > If you really have the need to handle exceptions you might want to> > implement your own JDBC connector by extending the classes in Flink and> > call each method within a try-catch block.> > > Chong Yun Long <yu...@gojek.com> 于2021年8月25日周三 下午4:46写道：> > > > Hi,> > >> > > Is there any mechanism for handling of errors produced by Flink SQL?> > > It can be useful for various use cases:> > > 1. Logging exceptions and the erroneous row to a kafka topic> > > 2. Ignoring transient exceptions instead of throwing and failing the> > > entire job> > >> > > If there are no such mechanisms may I propose something which looks like> > >> > > WITH (> > > 'connector' = 'jdbc',> > > 'url' = 'jdbc:mysql://localhost:3306/mydatabase',> > > 'table-name' = 'users'> > > 'exception-handler' = <classpath_to_handler_class>);> > >> > >> > > --> > > Regards,> > >> > > Yun Long> > >> >
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