Optimal tracking of distributed heavy hitters and quantiles
We consider the the problem of tracking heavy hitters and quantiles in the distributed
streaming model. The heavy hitters and quantiles are two important statistics for
characterizing a data distribution. Let A be a multiset of elements, drawn from the universe
U={1,..., u}. For a given 0≤ Φ≤ 1, the Φ-heavy hitters are those elements of A whose
frequency in A is at least Φ| A|; the Φ-quantile of A is an element x of U such that at most Φ|
A| elements of A are smaller than A and at most (1-Φ)| A| elements of A are greater than x …
streaming model. The heavy hitters and quantiles are two important statistics for
characterizing a data distribution. Let A be a multiset of elements, drawn from the universe
U={1,..., u}. For a given 0≤ Φ≤ 1, the Φ-heavy hitters are those elements of A whose
frequency in A is at least Φ| A|; the Φ-quantile of A is an element x of U such that at most Φ|
A| elements of A are smaller than A and at most (1-Φ)| A| elements of A are greater than x …
[PDF][PDF] Optimal Tracking of Distributed Heavy Hitters and Quantiles
Q Zhang - 2009 - pdfs.semanticscholar.org
… Picture from the tutorial “Streaming in a connected world: Querying and tracking distributed
data streams” at VLDB 06 and SIGMOD 07 … All Quantiles: A is a set of distinct elements from
a totally ordered universe. … Need a data structure to extract ϵ-approximate quantile for any x. …
data streams” at VLDB 06 and SIGMOD 07 … All Quantiles: A is a set of distinct elements from
a totally ordered universe. … Need a data structure to extract ϵ-approximate quantile for any x. …
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