A Partitioning Framework for Aggressive Data Skipping

PVLDB, pp. 1617-1620, 2014.

Cited by: 12|Bibtex|Views27|Links
EI

Abstract:

We propose to demonstrate a fine-grained partitioning framework that reorganizes the data tuples into small blocks at data loading time. The goal is to enable queries to maximally skip scanning data blocks. The partition framework consists of four steps: (1) workload analysis, which extracts features from a query workload, (2) augmentatio...More

Code:

Data:

Your rating :
0

 

Tags
Comments