[flink] support offset lag#3350
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Pull request overview
This PR adds Kafka-style “records lag” (offset backlog) metrics to the Fluss Flink source reader so users can observe how far each subscribed bucket is behind, complementing Flink’s existing event-time lag metric.
Changes:
- Introduces per-bucket gauges for
logEndOffsetandrecordsLag, plus reader-level aggregate gauges (recordsLagMax,recordsLagSum,laggingBuckets). - Adds a periodic background refresher that calls
Admin#listOffsets(..., LatestSpec)to keep log end offsets updated for streaming buckets. - Adds unit tests validating records-lag tracking and aggregate gauges.
Reviewed changes
Copilot reviewed 5 out of 5 changed files in this pull request and generated 2 comments.
Show a summary per file
| File | Description |
|---|---|
fluss-flink/fluss-flink-common/src/main/java/org/apache/fluss/flink/source/metrics/FlinkSourceReaderMetrics.java |
Adds new per-bucket and aggregate lag metrics and tracking state. |
fluss-flink/fluss-flink-common/src/main/java/org/apache/fluss/flink/source/reader/LogEndOffsetRefresher.java |
New scheduled component to refresh latest offsets via Admin listOffsets. |
fluss-flink/fluss-flink-common/src/main/java/org/apache/fluss/flink/source/reader/FlinkSourceSplitReader.java |
Wires metrics registration, starts/stops refresher, and updates metrics during reads. |
fluss-flink/fluss-flink-common/src/test/java/org/apache/fluss/flink/source/metrics/FlinkSourceReaderMetricsTest.java |
Adds unit test coverage for records lag and aggregate gauges. |
fluss-common/src/main/java/org/apache/fluss/config/ConfigOptions.java |
Adds configurable refresh interval for log end offset refreshing. |
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| flinkSourceReaderMetrics.recordLogEndOffset(scanBucket, lastRecord.logOffset() + 1); | ||
| // We keep the maximum message timestamp in the fetch for calculating lags |
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| if (!active || logEndOffset < 0 || nextConsumedOffset < 0) { | ||
| return 0L; | ||
| } |
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Purpose
Linked issue: close #3349
Flink currently exposes
currentFetchEventTimeLag, but it measures event-time lag rather than offset backlog. For Fluss log reading, we need a Kafka-style records lag metric so users can understand how far each subscribed source-reader bucket is behind.Relying only on timestamp lag can be misleading, especially for backfill jobs that subscribe to multiple time partitions. Older partitions may always appear to have a large event-time lag, even when their records have already been fully consumed.
Brief change log
Tests
API and Format
Documentation