The paper "AJoin: Ad-hoc Stream Joins at Scale" written by Jeyhun Karimov, Tilmann Rabl and Volker Markl has been accepted for VLDB 2020.
Abstract
The processing model of state-of-the-art stream processing en-gines is designed to execute long-running queries one at a time. However, with the advance of cloud technologies and multi-tenant systems, multiple users share the same cloud for stream query processing. This results in many ad-hoc stream queries sharing common stream sources. Many of these queries include joins.
There are two main limitations that hinder performing ad-hoc stream join processing. The first limitation is missed optimization potential both in stream data processing and query optimization layers. The second limitation is the lack of dynamicity in query execution plans.
