Leveraging Keys In Key-Value SSD for Production Workloads

Manoj P. Saha, Omkar Desai, Bryan S. Kim, Janki Bhimani

Research output: Chapter in Book/Entry/PoemConference contribution

Abstract

Key-Value SSDs reduce host-side resource utilization for unstructured data management by streamlining the I/O stack. However, designing a robust Key-Value SSD with resource constrained flash controllers has always been a challenge. The key-to-page (K2P) mapping inside KV-SSD, which consolidates multiple layers of indirection in the traditional block I/O storage, has its own shortcomings. The sparsely populated NVMe KV namespace leads to very large index, which cannot be optimized similar to hybrid- or block-FTL in block-SSDs. In addition, the background index management tasks (e.g. compaction on LSM-tree index) also lead to performance degradation. Moreover, existing KV index design is not equipped to tackle fast changing workload patterns. These shortcomings have stalled the adoption of KV-SSDs in production environments. In this work, we take the position that these shortcomings can be addressed by leveraging the information embedded inside keys about application keyspaces and groups as prefixes. The prefixes can be used to partition the monolithic large index into smaller ones. We demonstrate a naive prefix-based index partitioning mechanism inside KV-SSD that can reduce on-flash index accesses for multiple production workloads and discuss the shortcomings of this approach. Lastly, we discuss our proposed design of a society of indices that initialize, interact and evolve based on workload characteristics over time.

Original languageEnglish (US)
Title of host publicationHPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery, Inc
Pages327-328
Number of pages2
ISBN (Electronic)9798400701559
DOIs
StatePublished - Aug 7 2023
Event32nd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2023 - Orlando, United States
Duration: Jun 16 2023Jun 23 2023

Publication series

NameHPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing

Conference

Conference32nd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2023
Country/TerritoryUnited States
CityOrlando
Period6/16/236/23/23

Keywords

  • KV indexing
  • data storage
  • key prefix
  • key-value SSD

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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