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المؤلفTang, Mingjie
المؤلفYu, Yongyang
المؤلفMalluhi, Qutaibah M.
المؤلفOuzzani, Mourad
المؤلفAref, Walid G.
تاريخ الإتاحة2024-07-17T07:14:38Z
تاريخ النشر2015
اسم المنشورProceedings of the VLDB Endowment
المصدرScopus
المعرّفhttp://dx.doi.org/10.14778/3007263.3007310
الرقم المعياري الدولي للكتاب21508097
معرّف المصادر الموحدhttp://hdl.handle.net/10576/56731
الملخصWe present LocationSpark, a spatial data processing system built on top of Apache Spark, a widely used distributed data processing system. LocationSpark offers a rich set of spatial query operators, e.g., range search, kNN, spatio-textual operation, spatial-join, and kNN-join. To achieve high performance, LocationSpark employs various spatial indexes for in-memory data, and guarantees that immutable spatial indexes have low overhead with fault tolerance. In addition, we build two new layers over Spark, namely a query scheduler and a query executor. The query scheduler is responsible for mitigating skew in spatial queries, while the query executor selects the best plan based on the indexes and the nature of the spatial queries. Furthermore, to avoid unnecessary network communication overhead when processing overlapped spatial data, We embed an efficient spatial Bloom filter into LocationSpark's indexes. Finally, LocationSpark tracks frequently accessed spatial data, and dynamically ushes less frequently accessed data into disk. We evaluate our system on real workloads and demonstrate that it achieves an order of magnitude performance gain over a baseline framework.
اللغةen
الناشرVLDB Endowment
الموضوعData handling
Fault tolerance
Location
Scheduling
Spatial distribution
Data management system
Distributed data processing
Network communication overhead
Performance Gain
Real workloads
Spatial data processing
Spatial indexes
Spatial queries
Information management
العنوانLocationSpark: A distributed in-memory data management system for big spatial data
النوعConference
الصفحات1565-1568
رقم العدد13
رقم المجلد9
dc.accessType Abstract Only


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