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Glauber M Dantas updated FLINK-35392: ------------------------------------- Description: When transforming a DataStream to a Table and then using that table in a Join Lookup, an exception is raised: {{{}"Temporal table join currently only supports 'FOR SYSTEM_TIME AS OF' left table's time attribute field"{}}}. >From what I understood from the issue, it happens as the planner expects that >the Tables part of the Join are registered previously on the Catalog. The solution was to avoid using the DataStream to Table conversion: {{Table kinesisStreamTbl = tblEnv.fromDataStream(}} {{ kinesisDataStream,}} {{ Schema.newBuilder()}} {{ // "proc_time" would be needed to make the lookup using 'FOR SYSTEM_TIME AS OF'; see: [https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/sql/queries/joins/#processing-time-temporal-join]}} {{ .columnByExpression("proc_time", "PROCTIME()")}} {{ .build()}} {{ );}} And instead create and use a Table registered on the Catalog: {{tblEnv.createTable("KinesisInput", TableDescriptor.forConnector("kinesis")...);}} If you need more details, feel free to contact me or you may access the discussion at: [https://stackoverflow.com/questions/78485099/sedona-flink-sql-lookup-on-external-database-failing-when-using-for-system-time] was: When transforming a DataStream to a Table and then using that table in a Join Lookup, an exception is raised: {{{}"Temporal table join currently only supports 'FOR SYSTEM_TIME AS OF' left table's time attribute field"{}}}. >From what I understood from the issue, it happens as the planner expects that >the Tables part of the Join are registered previously on the Catalog. The solution was to avoid using the DataStream to Table conversion: {{Table kinesisStreamTbl = tblEnv.fromDataStream(}} {{ kinesisDataStream,}} {{ Schema.newBuilder()}} {{ // "proc_time" would be needed to make the lookup using 'FOR SYSTEM_TIME AS OF'; see: [https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/sql/queries/joins/#processing-time-temporal-join]}} {{ .columnByExpression("proc_time", "PROCTIME()")}} {{ .build()}} {{ );}} And instead create and use a Table registered on the Catalog: {{tblEnv.createTable("KinesisInput", TableDescriptor.forConnector("kinesis")...);}} If you need more details, you may access the discussion at: [https://stackoverflow.com/questions/78485099/sedona-flink-sql-lookup-on-external-database-failing-when-using-for-system-time] > SQL Lookup Join on external database failing when using 'FOR SYSTEM_TIME AS > OF' statement > ----------------------------------------------------------------------------------------- > > Key: FLINK-35392 > URL: https://issues.apache.org/jira/browse/FLINK-35392 > Project: Flink > Issue Type: Bug > Components: Table SQL / Planner > Affects Versions: 1.18.1 > Reporter: Glauber M Dantas > Priority: Major > > When transforming a DataStream to a Table and then using that table in a Join > Lookup, an exception is raised: {{{}"Temporal table join currently only > supports 'FOR SYSTEM_TIME AS OF' left table's time attribute field"{}}}. > From what I understood from the issue, it happens as the planner expects that > the Tables part of the Join are registered previously on the Catalog. > The solution was to avoid using the DataStream to Table conversion: > > {{Table kinesisStreamTbl = tblEnv.fromDataStream(}} > {{ kinesisDataStream,}} > {{ Schema.newBuilder()}} > {{ // "proc_time" would be needed to make the lookup > using 'FOR SYSTEM_TIME AS OF'; see: > [https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/sql/queries/joins/#processing-time-temporal-join]}} > {{ .columnByExpression("proc_time", "PROCTIME()")}} > {{ .build()}} > {{ );}} > And instead create and use a Table registered on the Catalog: > > {{tblEnv.createTable("KinesisInput", > TableDescriptor.forConnector("kinesis")...);}} > > If you need more details, feel free to contact me or you may access the > discussion at: > [https://stackoverflow.com/questions/78485099/sedona-flink-sql-lookup-on-external-database-failing-when-using-for-system-time] -- This message was sent by Atlassian Jira (v8.20.10#820010)