The key idea is to build and maintain a partitioning tree on top of the dataset. The partitioning tree allows us to answer queries with predicates by reading a ...
[PDF] A Robust Partitioning Scheme for Ad-Hoc Query Workloads
itu.dk › assets › publications › socc17
ABSTRACT. Data partitioning is crucial to improving query performance and several workload-based partitioning techniques have been proposed.
In this paper, we propose Amoeba, a distributed storage system that uses adaptive multi-attribute data partitioning to efficiently support ad-hoc as well as ...
Amoeba is proposed, a distributed storage system that uses adaptive multi-attribute data partitioning to efficiently support ad-hoc as well as recurring ...
ABSTRACT. Data partitioning is crucial to improving query performance and several workload-based partitioning techniques have been proposed.
Sep 11, 2017 · Repartitioning ONLY happens when reduction in the total cost of the query workload is greater than re-partitioning cost. Solves constant re- ...
In this paper, we propose Amoeba, a distributed storage system that uses adaptive multi-attribute data partitioning to efficiently support ad-hoc as well as ...
People also ask
How to enable Optimize for ad hoc workloads in SQL Server?
What are different data partitioning techniques in parallel database system?
In this paper, we propose Amoeba, a distributed storage system that uses adaptive multi-attribute data partitioning to efficiently support ad-hoc as well as ...
The system creates a robust upfront partitioning tree, designed to benet all possible queries, and then adapts it over time in response to the actual workload.
A robust partitioning scheme for ad-hoc query workloads. A Shanbhag, A Jindal, S Madden, J Quiane, AJ Elmore. Proceedings of the 2017 symposium on Cloud ...