2026-09-19T09:21:46Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/101460 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Gupta, Indranil Raina, Ashwini 2018-09-27T16:17:16Z 2018-09-27T16:17:16Z 2018-05-09 2018-08 This thesis targets the growing area of interactive data analytics engines. It builds upon a system called Getafix, an intelligent data replication and placement algorithm, and optimizes Getafix for running mixed queries over a heterogeneous cluster. The new algorithm is called Getafix-H, a cluster aware version of Getafix replication algorithm, with built-in optimizations for segment balancing and cluster auto-tiering. We integrated Getafix-H as an extension to Getafix inside Druid, a modern open-source interactive data analytics engine. We present experimental results using workloads from Yahoo!’s production Druid cluster. Compared to Getafix, Getafix-H improves the tail latency by 18% and reduces memory usage by up to 27% (2-3X improvement over Scarlett). In presence of stragglers, Getafix-H improves tail latency by 55% and reduces memory usage by upto 20% compared to Getafix. Getafix-H enables sysadmins to auto-tier a heterogeneous cluster with the tiering accuracy of up to 80%. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-09-27 without embargo terms The student, Ashwini Raina, accepted the attached license on 2018-05-08 at 12:00. The student, Ashwini Raina, submitted this Thesis for approval on 2018-05-08 at 12:14. This Thesis was approved for publication on 2018-05-09 at 12:46. DSpace SAF Submission Ingestion Package generated from Vireo submission #12563 on 2018-09-27 at 10:43:43 Made available in DSpace on 2018-09-27T16:17:16Z (GMT). No. of bitstreams: 2 RAINA-THESIS-2018.pdf: 578295 bytes, checksum: 50e840637ea2e1e73dbcf2a17e240bb6 (MD5) LICENSE.txt: 4210 bytes, checksum: c8b606cf11f891caea015bfab8b34141 (MD5) Previous issue date: 2018-05-09 application/pdf http://hdl.handle.net/2142/101460 en Copyright 2018 Ashwini Raina Real-time analytics, data replication Optimizing interactive analytics engines for heterogeneous clusters text text Computer Science Computer Science University of Illinois at Urbana-Champaign Thesis M.S.