LogECMem: Coupling Erasure-Coded In-Memory Key-Value Stores with Parity Logging

In-memory key-value stores are often used to speed up Big Data workloads on modern HPC clusters. To maintain their high availability, erasure coding has been recently adopted as a low-cost redundancy scheme instead of replication. Existing erasure-coded update schemes, however, have either low perfo...

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Published in:SC21: International Conference for High Performance Computing, Networking, Storage and Analysis pp. 01 - 14
Main Authors: Cheng, Liangfeng, Hu, Yuchong, Ke, Zhaokang, Xu, Jia, Yao, Qiaori, Feng, Dan, Wang, Weichun, Chen, Wei
Format: Conference Proceeding
Language:English
Published: ACM 14.11.2021
Subjects:
Costs
Couplings
Erasure coding
High performance computing
Key-value stores
Maintenance engineering
Memory management
Parity logging
Prototypes
Redundancy
Update
ISSN:2167-4337
Online Access:Get full text
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Abstract In-memory key-value stores are often used to speed up Big Data workloads on modern HPC clusters. To maintain their high availability, erasure coding has been recently adopted as a low-cost redundancy scheme instead of replication. Existing erasure-coded update schemes, however, have either low performance or high memory overhead. In this paper, we propose a novel parity logging-based architecture, HybridPL, which creates a hybrid of in-place update (for data and XOR parity chunks) and log-based update (for the remaining parity chunks), so as to balance the update performance and memory cost, while maintaining efficient single-failure repairs. We realize HybridPL as an in-memory key-value store called LogECMem, and further design efficient repair schemes for multiple failures. We prototype LogECMem and conduct experiments on different workloads. We show that LogECMem achieves better up-date performance over existing erasure-coded update schemes with low memory overhead, while maintaining high basic I/O and repair performance.
AbstractList In-memory key-value stores are often used to speed up Big Data workloads on modern HPC clusters. To maintain their high availability, erasure coding has been recently adopted as a low-cost redundancy scheme instead of replication. Existing erasure-coded update schemes, however, have either low performance or high memory overhead. In this paper, we propose a novel parity logging-based architecture, HybridPL, which creates a hybrid of in-place update (for data and XOR parity chunks) and log-based update (for the remaining parity chunks), so as to balance the update performance and memory cost, while maintaining efficient single-failure repairs. We realize HybridPL as an in-memory key-value store called LogECMem, and further design efficient repair schemes for multiple failures. We prototype LogECMem and conduct experiments on different workloads. We show that LogECMem achieves better up-date performance over existing erasure-coded update schemes with low memory overhead, while maintaining high basic I/O and repair performance.
Author Ke, Zhaokang
Chen, Wei
Yao, Qiaori
Cheng, Liangfeng
Xu, Jia
Hu, Yuchong
Feng, Dan
Wang, Weichun
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  organization: HIKVISION,Hangzhou,China
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Snippet In-memory key-value stores are often used to speed up Big Data workloads on modern HPC clusters. To maintain their high availability, erasure coding has been...
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StartPage 01
SubjectTerms Costs
Couplings
Erasure coding
High performance computing
Key-value stores
Maintenance engineering
Memory management
Parity logging
Prototypes
Redundancy
Update
Title LogECMem: Coupling Erasure-Coded In-Memory Key-Value Stores with Parity Logging
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