Big Data 6 min read

How Apache Paimon Manages Snapshot Expiration: Synchronous vs Asynchronous Modes

This article explains Apache Paimon's snapshot expiration mechanism, comparing synchronous and asynchronous execution modes, their advantages and drawbacks, and how table properties control expiration to balance data consistency, performance, and back‑pressure in large‑scale data processing systems.

Big Data Technology & Architecture
Big Data Technology & Architecture
Big Data Technology & Architecture
How Apache Paimon Manages Snapshot Expiration: Synchronous vs Asynchronous Modes

How Paimon Manages Snapshot Expiration

Paimon’s writer creates one to two snapshots on each commit; each snapshot adds new data files and marks some older files as deleted. The marked files are not physically removed immediately because Paimon supports time‑travel to earlier snapshots, and they are only deleted when the snapshots expire.

When new changes are committed, Paimon automatically triggers expiration. The expiration behavior is controlled by the table property snapshot.expire.execution-mode. By default, Paimon synchronously deletes expired snapshots, which can cause back‑pressure if many files need to be removed. Users can set the property to "async" to enable asynchronous expiration.

Synchronous Expiration Mode (sync)

Advantages

Clear operation order : Operations are executed strictly sequentially, ensuring that the system state is stable after each step, which is beneficial for scenarios requiring strong data consistency.

High data‑consistency guarantee : Because the deletion is performed synchronously, downstream queries and analyses always see a consistent snapshot state.

Disadvantages

Performance impact : Deleting a large number of files can be time‑consuming, slowing down overall system responsiveness.

Potential back‑pressure : Upstream operators may be blocked while waiting for snapshot deletion, affecting data ingestion pipelines.

Asynchronous Expiration Mode (async)

Advantages

Improved system responsiveness : Deletion runs in the background, preventing blocking of new writes or queries and allowing higher throughput in high‑concurrency scenarios.

Reduced back‑pressure risk : Since file removal does not block upstream operators, data flows more smoothly through the pipeline.

Disadvantages

Complex data‑consistency maintenance : As files are removed asynchronously, there may be moments when queries see partially deleted data, requiring additional mechanisms such as caching strategies or version control to ensure consistency.

Increased operational management difficulty : Background deletion tasks need monitoring, retry logic, and resource management to guarantee stable operation.

Choosing between synchronous and asynchronous expiration depends on the specific workload requirements, balancing consistency guarantees against performance and operational complexity.

Original Source

Signed-in readers can open the original source through BestHub's protected redirect.

Sign in to view source
Republication Notice

This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactadmin@besthub.devand we will review it promptly.

Data ConsistencySynchronousApache Paimonsnapshot expiration
Big Data Technology & Architecture
Written by

Big Data Technology & Architecture

Wang Zhiwu, a big data expert, dedicated to sharing big data technology.

0 followers
Reader feedback

How this landed with the community

Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.