Why architecture matters here

Count-Min failures come from wrong dimensions + weak hashes. Architecture matters because d + w + hash choice decide accuracy.

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The architecture: every piece explained

The top strip is the algorithm. Item x. d hash functions. w counters per row. Increment.

The middle row is guarantees. Query. Overestimate. Error bound. Merge.

The lower rows are practice. Conservative update. Use cases. Ops — sizing + heavy hitters.

Count-Min sketch — hash tables + counters + estimate + mergecount events with tiny memoryItem xarrivesd hash functionsone per tablew counters per rowd × w totalIncrementeach row at its bucketQuerymin across rowsOverestimatehash collisions addError boundε · N with prob 1-δMergeelementwise sumConservative updatereduce overestimationUse casestop-K / heavy hitters / streamingOps — sizing + audit + heavy-hitter extractionminknowboundaggregateimproveapplyapplyoperateoperate
Count-Min sketch layout + query + merge.
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End-to-end flow

End-to-end: streaming events keyed by URL. Increment count in d × w sketch. Query returns min for top-K URLs. Merges per-shard sketches elementwise. Error bound ε=0.01 with δ=0.001 sized for corpus.