People involved: Iraklis Psaroudakis, Manos Athanassoulis
Data warehousing workloads often consist of star queries. Data warehouses optimize and execute each star query as if it was the only one running in the system, using a separate execution plan. In fact, each execution plan is independent of other concurrent star queries even if they are similar or identical. For a small number of concurrent star queries, this approach makes the optimization phase faster and creates efficient execution plans. For higher concurrency, however, it cannot exploit work and data sharing opportunities, resulting in increased contention for I/O and CPU resources.
EXTERNAL FUNDING SOURCES
This work is partially supported in the means of the european funded project BIGFOOT.
Iraklis Psaroudakis, Manos Athanassoulis, Anastasia Ailamaki: “Sharing data and work across concurrent analytical queries.” VLDB 2013.
Iraklis Psaroudakis, Manos Athanassoulis, Matthaios Olma, Anastasia Ailamaki: “Reactive and proactive sharing across concurrent analytical queries.” SIGMOD 2014 (demo).