Efficient Incremental Computation of Aggregations over Sliding Windows - Archive ouverte HAL Access content directly
Conference Papers Acta Médica Costarricense Year : 2021

Efficient Incremental Computation of Aggregations over Sliding Windows

(1, 2) , (3) , (1, 2)
1
2
3

Abstract

Computing aggregation over sliding windows, i.e., finite subsets of an unbounded stream, is a core operation in streaming analytics. We propose PBA (Parallel Boundary Aggregator), a novel parallel algorithm that groups continuous slices of streaming values into chunks and exploits two buffers, cumulative slice aggregations and left cumulative slice aggregations, to compute sliding window aggregations efficiently. PBA runs in (1) time, performing at most 3 merging operations per slide while consuming () space for windows with partial aggregations. Our empirical experiments demonstrate that PBA can improve throughput up to 4× while reducing latency, compared to state-of-the-art algorithms.
Fichier principal
Vignette du fichier
PBA_BDA21.pdf (1.3 Mo) Télécharger le fichier

Dates and versions

lirmm-03468587 , version 1 (07-12-2021)

Identifiers

  • HAL Id : lirmm-03468587 , version 1

Cite

Chao Zhang, Reza Akbarinia, Farouk Toumani. Efficient Incremental Computation of Aggregations over Sliding Windows. BDA 2021 - 37e Conférence sur la Gestion de Données - Principes, Technologies et Applications, Oct 2021, Virtual, France. ⟨lirmm-03468587⟩
91 View
83 Download

Share

Gmail Facebook Twitter LinkedIn More