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SCHEDULE: NOV 15-20, 2015
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HydraDB: A Resilient RDMA-Driven Key-Value Middleware for In-Memory Cluster Computing
SESSION: Scalable Storage Systems
EVENT TYPE: Papers
EVENT TAG(S): Storage, Data-Intensive Computing
TIME: 2:30PM - 3:00PM
SESSION CHAIR(S): Gabriel Antoniu
AUTHOR(S):Yandong Wang, Li Zhang, Jian Tan, Min Li, Yuqing Gao, Xavier Guerin, Xiaoqiao Meng, Shicong Meng
ROOM:18CD
ABSTRACT:
In this paper, we describe our experiences and lessons learned from building an in-memory key-value middleware, called HydraDB. HydraDB synthesizes a collection of state-of-the-art techniques, including high-availability, RDMA, as well as multicore-awareness, etc, to deliver a high-throughput, low-latency access service in a reliable manner for cluster computing applications.
The uniqueness of HydraDB lies in its design commitment to exploit RDMA to comprehensively optimize various aspects of a general-purpose key-value store, including latency-critical operations, read enhancement, and replications for high-availability service, etc. Meanwhile, HydraDB strives to efficiently utilize multicore systems to prevent data manipulation from curbing the performance of RDMA.
Many teams in our organization have adopted HydraDB to improve the execution of their cluster computing frameworks, including MapReduce, Sensemaking analytics and Call Record Processing. In addition, performance evaluation with a variety of YCSB workloads also shows that HydraDB substantially outperforms several existing in-memory key-value stores by an order of magnitude.
Chair/Author Details:
Gabriel Antoniu (Chair) - French Institute for Research in Computer Science and Automation|
Yandong Wang - IBM Corporation
Li Zhang - IBM Corporation
Jian Tan - IBM Corporation
Min Li - IBM Corporation
Yuqing Gao - Microsoft Corporation
Xavier Guerin - Tower Research Capital LLC
Xiaoqiao Meng - Pinterest, Inc.
Shicong Meng - Facebook
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