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feat(taskbroker): Retry activations that miss their heartbeat #847
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2c5bcbb
feat(taskbroker): Retry activations that miss their heartbeat
evanh e25bcae
feat(taskbroker): Add BatchUpdateHeartbeat handler
evanh 2a60241
ref(taskbroker): Read ids from BatchUpdateHeartbeat request
evanh 24459dc
build(taskbroker): Bump sentry_protos to 0.106.0
evanh f58d33a
fix(taskbroker): Ignore zero heartbeat and test deadline bump
evanh 5aaa1b0
ref(taskbroker): Check both deadlines in one upkeep query and add hea…
evanh 8f5b09d
ref(taskbroker): Restore per-reason upkeep queries and skip rows with…
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| ALTER TABLE inflight_taskactivations ADD COLUMN heartbeat INTEGER; | ||
| ALTER TABLE inflight_taskactivations ADD COLUMN heartbeat_deadline TIMESTAMPTZ; |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| ALTER TABLE inflight_taskactivations ADD COLUMN heartbeat INTEGER; | ||
| ALTER TABLE inflight_taskactivations ADD COLUMN heartbeat_deadline INTEGER; |
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Curious about the performance here. We batch ids per worker call, but heartbeats from different workers aren't grouped on the broker the way set_task_status is through update_tx and the flusher. I'm not saying we need that, but I'd like to understand the impact. For set status, batching across worker calls gave us significant gains.
Maybe to help answer this later, could we add a metrics for:
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Added in 5aaa1b0:
grpc_server.batch_update_heartbeat.ids(ids per call) and.durationhistograms on bothupdate_heartbeatandbatch_update_heartbeat. That gives us the data to decide on a cross-worker flusher later.