An Algorithm for Tunable Memory Compression of Time-Based Windows for Stream Aggregates
Paper in proceeding, 2023
Based on this observation, this work proposes an algorithm for streaming aggregation that allows for control of memory usage through lossless compression. The algorithm provides a "knob" to control the amount of state that should be compressed, prioritizing the compression of old over fresh data when performing streaming aggregation. Together with a detailed algorithmic description, this work presents preliminary results from a fully implemented prototype on top of the Liebre SPE, showing the effectiveness of the proposed approach.
Stream Processing
Stream Aggregate
Compression
Author
Vincenzo Massimiliano Gulisano
Network and Systems
Euro-Par 2023: Parallel Processing
0302-9743 (ISSN) 1611-3349 (eISSN)
Limassol, Cyprus,
Subject Categories
Computer Science
Computer Systems