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EASY: Efficient segment assignment strategy for reducing tail latencies in pinot

  • Seyyed Ahmad Javadi
  • , Harsh Gupta
  • , Robin Manhas
  • , Shweta Sahu
  • , Anshul Gandhi
  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Customer facing online services, such as LinkedIn and Uber, rely on scalable and low-latency data stores to maintain acceptable query tail latencies. An important challenge for managing the performance of these systems is the assignment of newly created data segments to data nodes to balance load. Given the rate at which these services are accessed (thus generating new data), the segment assignment problem is particularly important. This paper presents EASY, an efficient segment assignment strategy that leverages analytical modeling to predict the future load induced by data segments, thus allowing for long-term balancing of load across data nodes. Our implementation and evaluation of EASY on Pinot shows that we can significantly reduce query tail latencies in the presence of dynamically generated data segments.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 38th International Conference on Distributed Computing Systems, ICDCS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1432-1437
Number of pages6
ISBN (Electronic)9781538668719
DOIs
StatePublished - Jul 19 2018
Event38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018 - Vienna, Austria
Duration: Jul 2 2018Jul 5 2018

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2018-July

Conference

Conference38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018
Country/TerritoryAustria
CityVienna
Period07/2/1807/5/18

Keywords

  • Pinot
  • Segment assignment strategy
  • Tail latency

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