Streaming

Sliding Window Sort

Maintain sorted order over a moving window of the most recent elements in a stream.

Sort a stream in bounded chunks by buffering records, sorting each chunk, and emitting sorted runs or partially ordered output.

Maintain deterministic approximate quantiles of a stream with rank error guarantees.

Maintain approximate quantiles of a stream using compact summaries.

Select a random sample from a stream where each item has a nonnegative weight.

Select a uniform random sample from a stream of unknown length using fixed memory.

Maintain the k-th largest value while values arrive one at a time.

Maintain the median of a stream using a max heap and a min heap.

Estimate item frequencies in a stream using a compact hash based summary.

Approximate frequent items in a stream with tighter error bounds than Misra Gries.

Find frequent items in a stream by maintaining a bounded set of counters.

Find frequent items in a stream using bounded memory.

Maintain the k largest elements while values arrive one at a time.

Examine hash-based structures in complete systems: streaming pipelines, graph algorithms, caches, and distributed workflows.

Approximate frequency counting for large key streams using a compact probabilistic data structure with bounded error.