Lune

ICDE2022Top-tier venue

On inter-operator data transfers in query processing

Harshad Deshmukh, Bruhathi Sundarmurthy, Jignesh M. Patel

2022Year
1Citations

Abstract

In designing query processing primitives, a crucial design choice is the method for data transfer between two operators in a query plan. As we were considering this critical design mechanism for an in-memory database system that we are building, we quickly realized that (surprisingly) there isn't a clear definition of this concept. Papers are full of ad hoc use of terms like pipelining and blocking, but these terms are not crisply defined, making it hard to fully understand the results attributed to these concepts. To address this limitation, we introduce a clear terminology for how to think about data transfer between operators in a query pipeline. We argue that there isn't a clear definition of pipelining and blocking, and that there is a full spectrum of techniques based on a simple concept called unit-of-transfer. Next, we develop an analytical model for inter-operator communication, and highlight the key parameters that impact performance (for in-memory database settings). Armed with this model, we then apply it to the system we are designing and highlight the insights that we gathered from this exercise. We find that the gap between the traditional “pipelining” and “non-pipelining” methods of query processing, w.r.t. key factors such as performance and memory footprint is quite narrow, and thus system designers should likely rethink the notion of “pipelining” vs. “blocking” for in-memory database systems.

Ask about this paper

Ask your agent about it.

Lune has read the top-tier papers around this one, so every answer names the papers it rests on.

Questions to start from

Your agent calls

Lunesearch_papers

Ask in Lune

Free to start. No credit card required.

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines