IEEE Transactions on Parallel and Distributed Systems · 2020 · 19 citations · 36 references
ComputingComputer ScienceComputer SystemsData ManagementDistributed SystemsStorage SystemsData Storage SystemsDistributed StorageDistributed Storage SystemsFile SystemsMetadata ManagementStorage ManagementData DiscoveryDistributed File System ArchitectureIndexingIndexing SystemsMetadataMetadata IndexingScalable Data ManagementScalable Indexing
Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.
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The Hadoop Distributed File System
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Sage A. Weil, Scott Brandt, Ethan L. Miller et al. · eScholarship (California Digital Library) · 2006 · 1.4K citations · Full text
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