Abstract
LSM-trees have emerged as the write-optimized index of choice for key-value stores and relational database systems. LSM-trees typically rely on a storage manager on top of a file system for storing data on Solid-State Drives (SSDs). The I/O path thus comprises four layers, each independently managing similar indirection, journaling, and garbage collection mechanisms. Such overhead is increasingly problematic. First, the advent of microsecond-scale SSDs makes it necessary to streamline the I/O software stack. Second, the increasing performance gap between storage and CPU makes it necessary to reduce CPU storage overhead. A solution is to collapse LSM, file system, and SSD management layers into a single software layer embedded on computational storage. Specific commercial solutions are already available. In this short paper, we describe the design space for LSM management on computational storage.
Original language | English |
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Title of host publication | 15th International Workshop on Data Management on New Hardware, DaMoN 2019 |
Publisher | Association for Computing Machinery, Inc. |
Publication date | 1 Jul 2019 |
Article number | 3329927 |
ISBN (Electronic) | 9781450368018 |
DOIs | |
Publication status | Published - 1 Jul 2019 |
Externally published | Yes |
Event | 15th International Workshop on Data Management on New Hardware, DaMoN 2019, Held with ACM SIGMOD/PODS 2019 - Amsterdam, Netherlands Duration: 1 Jul 2019 → … |
Conference
Conference | 15th International Workshop on Data Management on New Hardware, DaMoN 2019, Held with ACM SIGMOD/PODS 2019 |
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Country/Territory | Netherlands |
City | Amsterdam |
Period | 01/07/2019 → … |
Sponsor | Oracle, SAP |
Series | Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems |
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Bibliographical note
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