On Log-Structured Merge For Solid-State Drives

2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017)(2017)

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摘要
Log-structure merge (LSM) is an increasingly prevalent approach to indexing, especially for modern write-heavy workloads. LSM organizes data in levels with geometrically increasing sizes. Records enter the top level; whenever a level fills up, it is merged down into the next level. Hence, the index is updated only through merges and records are never updated in-place. While originally conceived to avoid slow random accesses of hard drives, LSM also turns out to be especially suited to solid-state drives, or any block-based storage with expensive writes.We study how to further reduce writes in LSM. Traditionally, LSM always merges an overflowing level fully into the next. We investigate in depth how partial merges save writes and prove bounds on their effectiveness. We propose new algorithms that make provably good decisions on whether to perform a partial merge, and if yes, which part of a level to merge. We also show how to further reduce writes by reusing data blocks during merges. Overall, our approach offers better worst-case guarantees and better practical performance than existing LSM variants.
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关键词
log-structured merge,LSM,solid-state drives,indexing,writeheavy workloads,data organization,hard drives,block-based storage,expensive writes,partial merge,data block reuse
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