[
https://issues.apache.org/jira/browse/FLINK-39718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ran Tao updated FLINK-39718:
----------------------------
Description:
When using a distributed pipeline source with Paimon sink, the job may fail if
the target table does not already exist.
The failure happens in *DistributedPrePartitionOperator*. The previous
*PaimonHashFunction* rebuilds the hash function at this stage and immediately
accesses the external Paimon catalog to load the target table. If
the table has not been created yet, *catalog.getTable(...)* throws
TableNotExistException, and the job fails in the pre-partition stage.
This issue is usually not exposed in MySQL-CDC pipelines because MySQL-CDC uses
regular topology. In that path, CreateTableEvent is handled by SchemaOperator
first, and MetadataApplier creates the downstream table before records enter
*RegularPrePartitionOperator*. As a result, the previous PaimonHashFunction can
usually find the target table from the catalog.
For distributed pipeline sources, the execution order is different:
pre-partitioning happens before the target table is created by
*MetadataApplier* in the schema coordination phase.
This issue is not specific to Kafka. It can affect any distributed pipeline
source with the same execution order.
was:
When using distributed pipeline source(such as kafka, We've implemented a kafka
pipeline within the company, but this is a common/universal problem.) with
Paimon sink in distributed topology, the job may fail before the sink finishes
auto-creating the target table.
The failure happens in *DistributedPrePartitionOperator*. The previous
*PaimonHashFunction* rebuilds the hash function at this stage and immediately
accesses the external Paimon catalog to load the target table. However, in the
auto-created table case, the sink-side table creation has not happened yet, so
catalog.getTable(...) throws TableNotExistException and the job fails in
pre-partition stage.
This issue is usually not exposed in MySQL-CDC pipelines because MySQL-CDC uses
regular topology. In that path, CreateTableEvent is handled by SchemaOperator
first, and the sink-side MetadataApplier creates the downstream table before
records enter RegularPrePartitionOperator. As a result, the old
PaimonHashFunction can usually find the target table from catalog.
*A distributed pipeline source behaves differently because it uses a
distributed topology, where pre-partitioning happens before the target table is
created by the sink MetadataApplier in the schema coordination phase.*
Paimon or other pipeline sinks that support automatic table creation should
support distributed topologies, even if there isn't currently a connector for a
distributed pipeline source.
> [pipeline][paimon] Paimon pipeline sink fails with distributed source when
> target table does not exist
> ------------------------------------------------------------------------------------------------------
>
> Key: FLINK-39718
> URL: https://issues.apache.org/jira/browse/FLINK-39718
> Project: Flink
> Issue Type: Bug
> Components: Flink CDC
> Reporter: Ran Tao
> Priority: Major
>
> When using a distributed pipeline source with Paimon sink, the job may fail
> if the target table does not already exist.
> The failure happens in *DistributedPrePartitionOperator*. The previous
> *PaimonHashFunction* rebuilds the hash function at this stage and immediately
> accesses the external Paimon catalog to load the target table. If
> the table has not been created yet, *catalog.getTable(...)* throws
> TableNotExistException, and the job fails in the pre-partition stage.
> This issue is usually not exposed in MySQL-CDC pipelines because MySQL-CDC
> uses regular topology. In that path, CreateTableEvent is handled by
> SchemaOperator first, and MetadataApplier creates the downstream table before
> records enter *RegularPrePartitionOperator*. As a result, the previous
> PaimonHashFunction can usually find the target table from the catalog.
> For distributed pipeline sources, the execution order is different:
> pre-partitioning happens before the target table is created by
> *MetadataApplier* in the schema coordination phase.
> This issue is not specific to Kafka. It can affect any distributed pipeline
> source with the same execution order.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
