TY - GEN
T1 - Flow algorithms for parallel query optimization
AU - Deshpande, Amol
AU - Hellerstein, Lisa
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - We address the problem of minimizing the response time of a multi-way join query using pipelined (inter-operator) parallelism, in a parallel or a distributed environment. We observe that in order to fully exploit the parallelism in the system, we must consider a new class of " interleaving" plans, where multiple query plans are used simultaneously to minimize the response time of a query (or to maximize the tuple-throughput of the system). We cast the query planning problem in this environment as a "flow maximization problem", and present polynomial-time algorithms that (statically) And the optimal set of plans to use for a given query, for a large class of multi-way join queries. Our proposed algorithms also naturally extend to query optimization over web services. Finally we present an extensive experimental evaluation that demonstrates both the need to consider such plans in parallel query processing and the effectiveness of our algorithms.
AB - We address the problem of minimizing the response time of a multi-way join query using pipelined (inter-operator) parallelism, in a parallel or a distributed environment. We observe that in order to fully exploit the parallelism in the system, we must consider a new class of " interleaving" plans, where multiple query plans are used simultaneously to minimize the response time of a query (or to maximize the tuple-throughput of the system). We cast the query planning problem in this environment as a "flow maximization problem", and present polynomial-time algorithms that (statically) And the optimal set of plans to use for a given query, for a large class of multi-way join queries. Our proposed algorithms also naturally extend to query optimization over web services. Finally we present an extensive experimental evaluation that demonstrates both the need to consider such plans in parallel query processing and the effectiveness of our algorithms.
UR - http://www.scopus.com/inward/record.url?scp=52649111582&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=52649111582&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2008.4497484
DO - 10.1109/ICDE.2008.4497484
M3 - Conference contribution
AN - SCOPUS:52649111582
SN - 9781424418374
T3 - Proceedings - International Conference on Data Engineering
SP - 754
EP - 763
BT - Proceedings of the 2008 IEEE 24th International Conference on Data Engineering, ICDE'08
T2 - 2008 IEEE 24th International Conference on Data Engineering, ICDE'08
Y2 - 7 April 2008 through 12 April 2008
ER -