Abstract
In real-world NoSQL deployments, users have to trade off CPU, memory, I/O bandwidth and storage space to achieve the required performance and efficiency goals. Data compression is a vital component to improve storage space efficiency, but reading compressed data increases response time. Therefore, compressed data stores rely heavily on using the memory as a cache to speed up read operations. However, as large DRAM capacity is expensive, NoSQL databases have become costly to deploy and hard to scale. In our work, we present a persistent caching mechanism for Apache Cassandra on a high-throughput, low-latency FPGA-based NVMe Flash accelerator (CAPI-Flash), replacing Cassandra's in-memory cache. Because flash is dramatically less expensive per byte than DRAM, our caching mechanism provides Apache Cassandra with access to a large caching layer at lower cost. The experimental results show that for read-intensive workloads, our caching layer provides up to 85% improved throughput and also reduces CPU usage by 25% compared to default Cassandra.
Original language | English |
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Title of host publication | 2018 IEEE 11th International Conference on Cloud Computing (CLOUD) |
Editors | R. Bilof |
Place of Publication | Piscataway |
Publisher | IEEE |
Pages | 220-228 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-5386-7235-8 |
ISBN (Print) | 978-1-5386-7236-5 |
DOIs | |
Publication status | Published - 2018 |
Event | CLOUD 2018 IEEE : 11th International Conference on Cloud Computing (CLOUD) - San Francisco, United States Duration: 10 Sept 2018 → 10 Sept 2018 |
Conference
Conference | CLOUD 2018 IEEE |
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Country/Territory | United States |
City | San Francisco |
Period | 10/09/18 → 10/09/18 |
Keywords
- Apache Cassandra
- CAPI
- CAPI Flash
- Cloud Computing
- Distributed Databases
- Flash Storage
- High performance Caching
- High Throughput Caching
- NoSQL Databases
- Nvme Flash
- Persistent Caching
- Power Systems
- Read Cache
- Solid State Drives
- Storage Accelerators