Data Placement in Bubba

Data Placement in Bubba (1988)

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by George Copeland , William Alexander , Ellen Boughter , Tom Keller

Venue:	PROCEEDINGS OF THE ACM-SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
Citations:	96 - 0 self

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Datum	Value	Source
TITLE	Data Placement in Bubba	INFERENCE
AUTHOR NAME	George Copeland	user correction
AUTHOR AFFIL	MCC	user correction
AUTHOR ADDR	3500 West Balcones Center Dnve; Austm, Texas 78759	user correction
AUTHOR NAME	William Alexander	user correction
AUTHOR AFFIL	MCC	user correction
AUTHOR ADDR	3500 West Balcones Center Dnve; Austm, Texas 78759	user correction
AUTHOR NAME	Ellen Boughter	user correction
AUTHOR AFFIL	MCC	user correction
AUTHOR ADDR	3500 West Balcones Center Dnve; Austm, Texas 78759	user correction
AUTHOR NAME	Tom Keller	user correction
AUTHOR AFFIL	MCC	user correction
AUTHOR ADDR	3500 West Balcones Center Dnve; Austm, Texas 78759	user correction
ABSTRACT	Thus paper examines the problem of data placement in Bubba, a highly-parallel system for data-intensive applications bemg developed at MCC “Highly-parallel” lmplres that load balancmng IS a cntlcal performance issue “Data-mtenave” means data IS so large that operatrons should be executed where the data resides As a result, data placement becomes a cntlcal performance issue In general, determmmg the optimal placement of data across processmg nodes for performance IS a difficult problem We describe our heuristic approach to solvmg the data placement problem w Bubba We then present expenmental results using a specific workload to provide msrght into the problem Several researchers have argued the benefits of deelustering (1 e, spreading each base relation over many nodes) We show that as declustermg IS increased. load balancing contmues to improve However, for transactions mvolvmg complex Joins, further declusterrng reduces throughput because of communications, startup and termmatron overhead We argue that data placement, especially declustermg, m a highly-parallel system must be considered early in the design, so that mechanrsms can be included for supportmg variable declustermg, for mmtmlzmg the most significant overheads associated with large-scale declustenng, and for gathering the required statistics.	user correction
YEAR	1988	INFERENCE
VENUE	PROCEEDINGS OF THE ACM-SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA	user correction
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	27 found	ParsCit 1.0