mirror of
https://github.com/hanzoai/tasks.git
synced 2026-10-04 02:04:03 +00:00
David Reiss
0108f692b9
## What changed? - Add support for per-key rate limits that are scaled by weight (so maintaining dispatch in the same order that tasks are read in). - Refactor simpleLimiter to split parameters and ready time. ## Why? Support simple per-key limits. This uses an LRU cache to track recent tasks by fairness key, default size 2000. With target dispatch rate of 1000 tasks/second/partition, that corresponds to at least 2 seconds of keys (equal in the worst case of fully uniform key distribution, which is unlikely). That means that rates >= 0.5 tasks/second/key/partition should be handled accurately (2 tasks/second/key for default 4 partitions). To handle even lower rates, partition count and task size can be tuned. ## How did you test it? - [ ] built - [ ] run locally and tested manually - [x] covered by existing tests - [x] added new unit test(s) - [ ] added new functional test(s)
27 lines
596 B
Go
27 lines
596 B
Go
package matching
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import commonpb "go.temporal.io/api/common/v1"
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const (
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// minWeight * strideFactor must be >= 1
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strideFactor = 1000
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minWeight = 0.001
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)
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type fairnessWeightOverrides map[string]float32
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func getEffectiveWeight(overrides fairnessWeightOverrides, pri *commonpb.Priority) float32 {
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key := pri.GetFairnessKey()
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weight, ok := overrides[key]
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if !ok {
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weight = pri.GetFairnessWeight()
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}
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// zero means default weight (1.0). negative doesn't make sense, map it to 1.0 also.
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if weight <= 0.0 {
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weight = 1.0
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} else {
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weight = max(weight, minWeight)
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}
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return weight
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}
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