Understanding Retract Updates in FlinkSQL: Append vs Retract Modes
FlinkSQL's retract updates allow handling of data modifications in streaming queries by using toRetractStream, contrasting with the append-only toAppendStream mode, and this article explains the differences, when each mode applies, and provides illustrative examples and visual diagrams.
If you encounter an error like
Table is not an append-only table. Use the toRetractStream() in order to handle add and retract messages.while using FlinkSQL, you need to understand the concept of retract updates.
Introduction : In simple terms, a "retract update" corresponds to the traditional update operation in databases; in streaming scenarios, a retract represents how data updates are processed.
When converting a table to a stream in FlinkSQL, you can choose between toAppendStream and toRetractStream. Selecting toAppendStream by mistake will cause errors for update or delete operations.
Difference
Append Mode : This mode can only be used when a table is strictly append‑only, i.e., it only receives INSERT statements and never updates previously emitted results. Attempting updates or deletions in this mode will fail.
Retract Mode : This mode is always available. It returns a boolean flag where true indicates an insertion and false indicates a retraction, thus supporting updates and deletions.
According to the official documentation, if data is only being appended, use Append mode; otherwise, use Retract mode, especially when the SQL contains COUNT() or GROUP BY clauses.
Below is an example illustrating the output of retract updates:
The result shows groups of operations where true represents a write and false represents a retraction.
We will publish a separate article detailing how FlinkSQL implements retract updates.
Signed-in readers can open the original source through BestHub's protected redirect.
This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactand we will review it promptly.
Big Data Technology & Architecture
Wang Zhiwu, a big data expert, dedicated to sharing big data technology.
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