PPT-Massive Spatial Query on the

Kepler Architecture Presentation in the 2017 ASAP International Conference Wenhai Li School of Computer Wuhan University 7112017 Content Motivation Driving Spatial Join in GPU CellDriven Execution on Virtual Warp. Jingren Zhou. Microsoft Corp.. Large-scale Distributed Computing. Large data centers (x1000 machines): storage and computation. Key technology for search . (Bing, Google, Yahoo). Web data analysis, user log analysis, relevance studies, etc.. Group 4: . Nipun . Garg, Surabhi . Mithal. http://www-users.cs.umn.edu/~smithal/. Chapter Organization. 2. OLD Organization. 5.1 . Evaluation of Spatial Operations . 5.2 . Query Optimization . 5.3 . A . Deep Dive into Spatial Indexing. Michael Rys. Principal Program Manager. Microsoft Corporation. @. SQLServerMike. DBI405. Q: Why is my Query . so. Slow?. A: . Usually . because the index isn’t being used.. Introduction to Spatial Computing CSE 5ISC. Some slides . adapted from . Worboys. . and . Duckham. (2004) . GIS: A Computing Perspective. , Second Edition, CRC Press. Two classes per week. Tuesday and Friday 2:30pm – 4:00pm. SpatialHadoop. Type: Research Paper (Experimental evaluation). Authors: Ahmed . Eldawy. , . Louai. . Alarabi. , Mohamed F. . Mokbel. Presented by: Siddhant Kulkarni. Term: Fall 2015. Motivation. Spatial-Keyword Queries Over Stream. Xiang Wang. 1*. , Ying Zhang. 2. , . Wenjie. . Zhang. 1. ,. . Xuemin. . Lin. 1. , . Wei Wang. 1. 1. The University of New South Wales, Australia. 2. University . Robert Christensen. , Feifei Li. University of Utah. Lu Wang, Ke Yi. Hong Kong University. Of Science and Technology. Motivation. Geo Spatial Data is being collected on a massive scale. Approximate aggregations is fast and often effective for this data. Standard Database Query Languages. Outline. What is a Query? Query Language. ?. Example Database Tables. SQL Overview: 3 Components. SELECT statement with 1 table. Multi-table SELECT statements. Why spatial extensions are needed?. Dong Xie. *, Feifei Li*, Bin Yao. . , Gefei Li. . , Liang Zhou. . , . Minyi. . Guo. . Spatial Data is Ubiquitous!. Location-based Services. IoT. Projects & Sensor Networks. Social Media. Problems of Existing Systems. Queries in . R-trees. Apostolos. Papadopoulos . and . Yannis. . Manolopoulos. Presenter: Uma . Kannan. Contents. Introduction. Spatial . data Management Research . Spatial . Access Methods . Research. Ke. Deng, . Kexin. . Xie. , Kevin . Zheng. and . Xiaofang. Zhou. 9/06/2016. 1. 2. Chapter Overview. Trajectory Query Classification. Trajectory Similarity Measure. Trajectory Data Index. Trajectory Query Processing. Location-based Services 2.0. Mohamed F. . Mokbel. Department of Computer Science and Engineering. University of Minnesota. www.cs.umn.edu/~mokbel. mokbel@cs.umn.edu. Location-based Services. Many people like to use these advanced technologies and devices. Xu*. ,. . Zheng Yang*, . N. ic. hola. s. . D. . Lane^, . Zuwei. . Yin. *. *School of Software, Tsinghua University. ^University. . College. . London. . and. . Bell. . Labs. 9.13. . in. . Maui,. Adapted from a talk by. : . Sapna. Jain & R. . Gokilavani. Some slides taken from . Jingren. Zhou's talk on Scope :. isg.ics.uci.edu/slides/MicrosoftSCOPE.pptx. Map-reduce framework. Good abstraction of group-by-aggregation operations.