000097654 001__ 97654
000097654 005__ 20190316233902.0
000097654 037__ $$aCONF
000097654 245__ $$aTashkent+: Memory-Aware Load Balancing and Update Filtering in Replicated Databases
000097654 269__ $$a2007
000097654 260__ $$c2007
000097654 336__ $$aConference Papers
000097654 520__ $$a<font color=#ff0000><b>BEST PAPER AWARD</b></font><br><br>We present a memory-aware load balancing (MALB) technique to dispatch transactions to replicas in a replicated database. Our MALB algorithm exploits knowledge of the working sets of transactions to assign them to replicas in such a way that they execute in main memory, thereby reducing disk I/O. In support of MALB, we introduce a method to estimate the size and the contents of transaction working sets. We also present an optimization called update filtering that reduces the overhead of update propagation between replicas.<BR><BR> We show that MALB greatly improves performance over other load balancing techniques – such as round robin, least connections, and locality-aware request distribution (LARD) – that do not use explicit information on how transactions use memory. In particular, LARD demonstrates good performance for read-only static content Web workloads, but it gives performance inferior to MALB for database replication as it does not efficiently handle large requests. MALB combined with update filtering further boosts performance over LARD. <BR><BR> We build a prototype replicated system, called Tashkent+, with which we demonstrate that our MALB and update filtering techniques improve performance of the TPC-W and RUBiS benchmarks. In particular, in a 16-replica cluster and using the ordering mix of TPC-W, MALB doubles the throughput over least connections and improves throughput 52% over LARD. MALB with update filtering further improves throughput to triple that of least connections and more than double that of LARD. Our techniques exhibit super-linear speedup; the throughput of the 16-replica cluster is 37 times the peak throughput of a standalone database due to better use of the cluster’s memory.
000097654 6531_ $$aDatabase replication
000097654 6531_ $$aLoad balancing
000097654 700__ $$0243754$$aElnikety, Sameh$$g157494
000097654 700__ $$0243753$$aDropsho, Steven$$g162067
000097654 700__ $$0243160$$aZwaenepoel, Willy$$g155705
000097654 7112_ $$aEuroSys$$cLisbon, Portugal$$dMarch 2007
000097654 773__ $$tEuroSys 2007
000097654 8564_ $$s216371$$uhttps://infoscience.epfl.ch/record/97654/files/tashkentPlus.pdf$$zn/a
000097654 909C0 $$0252226$$pLABOS$$xU10700
000097654 909CO $$ooai:infoscience.tind.io:97654$$pconf$$pIC$$qGLOBAL_SET
000097654 937__ $$aLABOS-CONF-2006-023
000097654 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000097654 980__ $$aCONF