Characterizing, Modeling, and Benchmarking RocksDB Key-Value Workloads at Facebook

Authors: 

Zhichao Cao, University of Minnesota, Twin Cities, and Facebook; Siying Dong and Sagar Vemuri, Facebook; David H.C. Du, University of Minnesota, Twin Cities

Abstract: 

Persistent key-value stores are widely used as building blocks in today's IT infrastructure for managing and storing large amounts of data. However, studies of characterizing real-world workloads for key-value stores are limited due to the lack of tracing/analyzing tools and the difficulty of collecting traces in operational environments. In this paper, we first present a detailed characterization of workloads from three typical RocksDB production use cases at Facebook: UDB (a MySQL storage layer for social graph data), ZippyDB (a distributed key-value store), and UP2X (a distributed key-value store for AI/ML services). These characterizations reveal several interesting findings: first, that the distribution of key and value sizes are highly related to the use cases/applications; second, that the accesses to key-value pairs have a good locality and follow certain special patterns; and third, that the collected performance metrics show a strong diurnal pattern in the UDB, but not the other two.

We further discover that although the widely used key-value benchmark YCSB provides various workload configurations and key-value pair access distribution models, the YCSB-triggered workloads for underlying storage systems are still not close enough to the workloads we collected due to ignorance of key-space localities. To address this issue, we propose a key-range based modeling and develop a benchmark that can better emulate the workloads of real-world key-value stores. This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system.

FAST '20 Open Access Sponsored by NetApp

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BibTeX
@inproceedings {246158,
author = {zhichao Cao and Siying Dong and Sagar Vemuri and David H.C. Du},
title = {Characterizing, Modeling, and Benchmarking RocksDB Key-Value Workloads at Facebook},
booktitle = {18th {USENIX} Conference on File and Storage Technologies ({FAST} 20)},
year = {2020},
isbn = {978-1-939133-12-0},
address = {Santa Clara, CA},
pages = {209--223},
url = {https://www.usenix.org/conference/fast20/presentation/cao-zhichao},
publisher = {{USENIX} Association},
month = feb,
}

Presentation Video