Publication | Closed Access
LSM-Based Storage and Indexing
22
Citations
7
References
2015
Year
Unknown Venue
Cluster ComputingEngineeringStorage ManagementComputer ArchitectureStorage StructureSemantic WebInformation RetrievalData ScienceData MiningManagementData IntegrationParallel ComputingData ManagementKnowledge DiscoveryLsm-based StorageComputer ScienceReal-time QueriesDistributed Query ProcessingQuery OptimizationTemporal DatabaseData IndexingAsterixdb SystemParallel ProgrammingApproximate Query AnsweringSocial-media Data ExplosionBig Data
With the social-media data explosion, near real-time queries, particularly those of a spatio-temporal nature, can be challenging. In this paper, we show how to efficiently answer queries that target recent data within very large data sets. We describe a solution that exploits a natural partitioning property that LSM-based indexes have for components, allowing us to filter out many components when answering queries. Our solution is generalizable to any LSM-based index structure, and can be applied not just on temporal fields (e.g., based on recency), but on any "time-correlated fields" such as Universally Unique Identifiers (UUIDs), user-provided integer ids, etc. We have implemented and experimentally evaluated the solution in the context of the AsterixDB system.
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