Mao Jiayi created FLINK-39757:
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Summary: Fix unable to coerce complex types (ARRAY/MAP/ROW) to
STRING
Key: FLINK-39757
URL: https://issues.apache.org/jira/browse/FLINK-39757
Project: Flink
Issue Type: Bug
Components: Flink CDC
Reporter: Mao Jiayi
When using CDC pipelines with schema merging operations that involve *complex
types (ARRAY, MAP, ROW)* being coerced to {*}STRING type{*}, the job may fail
due to missing type conversion logic in {*}SchemaMergingUtils{*}.
The failure happens in {*}SchemaMergingUtils.coerceObject(){*}. When attempting
to coerce complex types to STRING during schema merging, the utility only
handles primitive types and binary data conversions. If the original field is a
MapData, ArrayData, or RecordData, the coercion logic falls through to the
default toString() conversion, which either produces incorrect string
representations or fails entirely because these complex types don't have proper
toString() implementations for string coercion.
This issue is usually not exposed in simple type scenarios because primitive
types (INTEGER, VARCHAR, BOOLEAN, TIMESTAMP, etc.) have direct coercion paths
to STRING through existing conversion rules. The schema merging logic works
correctly for these basic type conversions, as they can be directly transformed
without special handling.
However, when CDC pipelines involve schema evolution or field type changes
where complex types need to be merged into STRING columns, the missing
conversion logic becomes critical. For example, when merging a table with
*ARRAY<INT>* column into a target table with *STRING* column at the same
position, *SchemaMergingUtils* cannot properly serialize the array data
structure into its string representation, causing the merge operation to fail
or produce incorrect results.
This issue is not specific to any particular source connector. It can affect
any CDC pipeline with schema merging scenarios involving complex-to-STRING type
coercion, regardless of whether the source is MySQL, PostgreSQL, Kafka, or any
other distributed pipeline source with schema evolution capabilities.
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