参考文献
[1]周晓云,何大曾,刘慎权.一种层次化模型构造方法[J].中国图象图形学报,1997,2(8):7-13.
[2]CLARK J H.Hierarchical geometric models for visible surface algorithms[J].Communications of the ACM,1976,19(10):547-554.
[3]ACHARYA S,GIBBONS P B,POOSALA V.Aqua:A fast decision support systems using approximate query answers[C]//Proceedings of the 26th International Conference on Very Large Data Bases,Morgan Kaufmann Publishers Inc.,2000:754-757.
[4]ACHARYA S,GIBBONS P B,POOSALA V.Congressional samples for approximate answering of group-by queries[J].Ac M sIGMoD Record,2000,29(2):487-498.
[5]WU S,OOI B C,TAN K L.Continuous sampling for online aggregation over multiple queries[C]//Proceedings of the 2010 International Conference on Management of Data,2010:651-662.
[6]HELLERSTEIN J M,HAAS P J,WANG H J.Online aggregation[J].Ac M sIGMoD Record,1997,26(2):171-182.
[7]HAAS P J.Large-sample and deterministic confidence intervals for online aggregation[C]//International Conference on Scientific and Statistical Database Management,1997:51-62.
[8]JOSHI S,JERMAINE C.Sampling-based estimators for subset-based queries[J].The VLDB Journal,2009,18(1):181-202.
[9]JOSHI S,JERMAINE C.Robust stratified sampling plans for low selectivity queries[C]//IEEE International Conference on Data Engineering,2008:199-208.
[10]MENG X.Scalable simple random sampling and stratified sampling[C]//International Conference on Machine Learning,2013:531-539.
[11]GIBBONS P B,MATIAS Y.New sampling-based summary statistics for improving approximate query answers[J].Ac M sIGMoD Record,1999,27(2):331-342.
[12]CHAUDHURI S,DAS G,NARASAYYA V.Optimized stratified sampling for approximate query processing[J].Acm Transactions on Database Systems,2007,32(2):9.
[13]OZSOYOGLU G,DU K,GURUSWAMY S,et al.Processing realtime,non-aggregate queries with time-constraints in CASE-DB[C]//Proceedings of the 8th International Conference on Data Engineering,1992:410-417.
[14]HOU W C.Relational aggregate query processing techniques for realtime databases[M].Case Western Reserve University,Cleveland,OH USA.1989.
[15]CHRISTODOULAKIS S.On the estimation and use of selectivities in database performance evaluation[J].Technical Report CS-89-24,Department of Computer Science,1989.
[16]VRBSKY S V,LIU W S.An object-oriented query processor that produces monotonically improving approximate answers[C]//International Conference on Data Engineering,1991:472-481.
[17]MOZAFARI B,NIU N.A handbook for building an approximate query engine[J].IEEE Data Engineering Bulletin,2015,38(3):3-29.
[18]ACHARYA S,GIBBONS P B,POOSALA V,et al.Join synopses for approximate query answering[C]//Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data,Association for Computing Machinery,1999:275-286.
[19]BARBARáD,DUMOUCHEL W,FALOUTSOS C,et al.The New Jersey data reduction report[J].IEEE Data Engineering Bulletin,1997,20:3-45.
[20]SHANMUGASUNDARAM J,FAYYAD U,BRADLEY P S.Compressed data cubes for OLAP aggregate query approximation on continuous dimensions[C]//ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,1999:223-232.
[21]LAZARIDIS I,MEHROTRA S.Progressive approximate aggregate queries with a multi-resolution tree structure[C]//ACM SIGMOD International Conference on Management of Data,2001:401-412.
[22]KORN F,JAGADISH H V,FALOUTSOS C.Efficiently supporting ad hoc queries in large datasets of time sequences[J].Ac M sIGMoD Record,1999,26(2):289-300.
[23]BARBAR D,SULLIVAN M.Quasi-cubes:exploiting approximations in multidimensional databases[J].Ac M sIGMoD Record,1997,26(3):12-17.
[24]MARGARITIS D,FALOUTSOS C,THRUN S.NetCube:a scalable tool for fast data mining and compression[C]//Proceedings of the 27th International Conference on Very Large Data Bases,2001:311-320.
[25]AGARWAL S,IYER A P,PANDA A,et al.Blink and it＇s done:Interactive queries on very large data[J].Proceedings of the Vldb Endowment,2012,5(12):1902-1905.
[26]AGARWAL S,MOZAFARI B,PANDA A,et al.Blink DB:queries with bounded errors and bounded response times on very large data[C]//Proceedings of the 8th ACM European Conference on Computer Systems,Association for Computing Machinery,2013:29-42.
[27]STONEBRAKER M,CATTELL R.10 rules for scalable performance in＇simple operation'datastores[J].Communications of the ACM,2011,54(6):72-80.
[28]ROUSSOPOULOS N,KELLEY S,FR,et al.Nearest neighbor queries[C]//Proceedings of the 1995 ACM SIGMOD international conference on Management of data,ACM,1995:71-79.
[29]CHEN Z,SHEN H T,ZHOU X,et al.Monitoring path nearest neighbor in road networks[C]//Proceedings of the 2009 ACM SIGMOD International Conference on Management of data,ACM,2009:591-602.
[30]HUANG Q,FENG J,ZHANG Y,et al.Query-aware locality-sensitive hashing for approximate nearest neighbor search[J].Proceedings of the Vldb Endowment,2015,9(1):1-12.
[31]TAO Y,SHENG C.Fast nearest neighbor search with keywords[J].IEEE transactions on knowledge and data engineering,2014,26(4):878-888.
[32]SOMMER C.Shortest-path queries in static networks[J].ACM Computing Surveys,2014,46(4):1-31.
[33]TAO Y,SHENG C,PEI J.On k-skip shortest paths[C]//Proceedings of the 2011 ACM SIGMOD International Conference on Management of data,ACM,2011:421-432.
[34]WU L,XIAO X,DENG D,et al.Shortest path and distance queries on road networks:an experimental evaluation[J].Proceedings of the Vldb Endowment,2012,5(5):406-417.
[35]YAN D,ZHAO Z,NG W.Efficient processing of optimal meeting point queries in Euclidean space and road networks[J].Knowledge And Information Systems,2015,42(2):319-351.
[36]WEI H,YU J X,LU C,et al.Reachability querying:an independent permutation labeling approach[J].Proceedings of the Vldb Endowment,2014,7(12):1191-1202.
[37]NG W,CHENG J,LIU S,et al.Finding distance-preserving subgraphs in large road networks[C]//Proceedings of the 2013 IEEE International Conference on Data Engineering,IEEE Computer Society,2013:625-636.
[38]SELLIS T K,ROUSSOPOULOS N,FALOUTSOS C.The R+-Tree:a dynamic index for multi-dimensional objects[C]//Proceedings of the 13th International Conference on Very Large Data Bases,Morgan Kaufmann Publishers Inc.,1987:507-518.
[39]GUTTMAN A.R-trees:a dynamic index structure for spatial searching[C]//Proceedings of the 1984 ACM SIGMOD International Conference on Management of Data,ACM,1984:47-57.
[40]BECKMANN N,KRIEGEL H-P,SCHNEIDER R,et al.The R*-tree:an efficient and robust access method for points and rectangles[C]//Proceedings of the 1990 ACM SIGMOD international conference on Management of data,1990:322-331.
[41]SAMET H.The quadtree and related hierarchical data structures[J].ACM Computing Surveys,1984,16(2):187-260.
[42]ROBINSON J T.The K-D-B-tree:a search structure for large multidimensional dynamic indexes[C]//Proceedings of the 1981 ACM SIGMOD International Conference on Management of Data,ACM,1981:10-18.
[43]TAO Y,YI K,SHENG C,et al.Quality and efficiency in high dimensional nearest neighbor search[C]//Proceedings of the 2009 ACM SIGMOD International Conference on Management of data,ACM,2009:563-576.
[44]HELLERSTEIN J M,NAUGHTON J F,PFEFFER A.Generalized search trees for database systems[C]//Proceedings of the 21th International Conference on Very Large Data Bases,Morgan Kaufmann Publishers Inc.,1995:562-573.
[45]RAMSAK F,MARKL V,FENK R,et al.Integrating the UB-tree into a database system kernel[C]//Proceedings of the 26th International Conference on Very Large Data Bases,Morgan Kaufmann Publishers Inc.,2000:263-272.
[46]BERCHTOLD S,KEIM D A,KRIEGEL H-P.The X-tree:an index structure for high-dimensional data[C]//Proceedings of the 22th International Conference on Very Large Data Bases,Morgan Kaufmann Publishers Inc.,1996:28-39.
[47]CAO X,CONG G,JENSEN C S,et al.Collective spatial keyword querying[C]//Proceedings of the 2011 ACM SIGMOD International Conference on Management of data,ACM,2011:373-384.
[48]CHEN L,CONG G,JENSEN C S,et al.Spatial keyword query processing:an experimental evaluation[J].Proceedings of the Vldb Endowment,2013,6(3):217-228.
[49]ZHANG D,CHEE Y M,MONDAL A,et al.Keyword search in spatial databases:towards searching by document[C]//Proceedings of the 2009 IEEE International Conference on Data Engineering,IEEE Computer Society,2009:688-699.
[50]CORRAL A,MANOLOPOULOS Y,THEODORIDIS Y,et al.Closest pair queries in spatial databases[C]//Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data,ACM,2000:189-200.
[51]SHARIFZADEH M,SHAHABI C.The spatial skyline queries[C]//Proceedings of the 32nd international conference on Very large data bases,VLDB Endowment,2006:751-762.
[52]LIN X,MA S,ZHANG H,et al.One-pass error bounded trajectory simplification[J].Proceedings of the Vldb Endowment,2017,10(7):841-852.
[53]LONG C,WONG R C-W,JAGADISH H V.Direction-preserving trajectory simplification[J].Proceedings of the Vldb Endowment,2013,6(10):949-960.
[54]LONG C,WONG R C-W,JAGADISH H V.Trajectory simplification:on minimizing the direction-based error[J].Proceedings of the Vldb Endowment,2014,8(1):49-60.
[55]MUCKELL J,OLSEN P W,HWANG J-H,et al.Compression of trajectory data:a comprehensive evaluation and new approach[J].GeoInformatica,2014,18(3):435-460.
[56]WANG L,CHRISTENSEN R,LI F,et al.Spatial online sampling and aggregation[J].Proceedings of the Vldb Endowment,2015,9(3):84-95.
[57]TAO Y,HU X,CHOI D-W,et al.Approximate MaxRSin spatial databases[J].Proceedings of the Vldb Endowment,2013,6(13):1546-1557.
[58]THORUP M,ZWICK U.Approximate distance oracles[J].Journal of the ACM,2005,52(1):1-24.
[59]LOHR S.The age of big data[J].New York Times,2012,11.
[60]KITCHIN R.Big data and human geography Opportunities,challenges and risks[J].Dialogues in Human Geography,2013,3(3):262-267.
[61]PHILIP CHEN C,ZHANG C-Y.Data-intensive applications,challenges,techniques and technologies:A survey on Big Data[J].Information Sciences,2014,275:314-347.
[62]CUGLER D C,OLIVER D,EVANS M R,et al.Spatial big data:platforms,analytics,and science[J].GeoJournal,2013.
[63]ELDAWY A,MOKBEL M F.The era of big spatial data:challenges and opportunities[C]//IEEE 16th International Conference on Mobile Data Management,2015:7-10.
[64]LIN J,DYER C.Data-intensive text processing with Map Reduce[J].Synthesis Lectures on Human Language Technologies,2010,3(1):1-177.
[65]CHEN Y,ALSPAUGH S,BORTHAKUR D,et al.Energy efficiency for large-scale mapreduce workloads with significant interactive analysis[C]//Proceedings of the 7th ACM European Conference on Computer Systems,ACM,2012:43-56.
[66]MOISE D,SHESTAKOV D,GUDMUNDSSON G,et al.Indexing and searching 100m images with map-reduce[C]//Proceedings of the 3rd ACM conference on International conference on multimedia retrieval,ACM,2013:17-24.
[67]DEAN J,GHEMAWAT S.Map Reduce:a flexible data processing tool[J].Communications of the ACM,2010,53(1):72-77.(https://www.daowen.com)
[68]DEAN J,GHEMAWAT S.Map Reduce:simplified data processing on large clusters[J].Communications of the ACM,2008,51(1):107-113.
[69]LEE K-H,LEE Y-J,CHOI H,et al.Parallel data processing with Map Reduce:a survey[J].Ac M sIGMoD Record,2012,40(4):11-20.
[70]NEUMEYER L,ROBBINS B,NAIR A,et al.S4:Distributed stream computing platform[C]//IEEE International Conference on Data Mining Workshops,IEEE,2010:170-177.
[71]WHITE T.Hadoop:The definitive guide[M].O’Reilly Media,USA.2015.
[72]ZAHARIA M,CHOWDHURY M,DAS T,et al.Fast and interactive analytics over Hadoop data with Spark[J].Usenix,2012,37(4):45-51.
[73]SPARKS E R,TALWALKAR A,SMITH V,et al.MLI:An API for distributed machine learning[C]//IEEE 13th International Conference on Data Mining,IEEE,2013:1187-1192.
[74]ZAHARIA M,CHOWDHURY M,DAS T,et al.Resilient distributed datasets:A fault-tolerant abstraction for in-memory cluster computing[C]//Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation,USENIX Association,2012:2-2.
[75]ZAHARIA M,CHOWDHURY M,FRANKLIN M J,et al.Spark:cluster computing with working sets[J].HotCloud,2010,10(10-10):95.
[76]ZAHARIA M,XIN R S,WENDELL P,et al.Apache Spark:a unified engine for big data processing[J].Communications of the ACM,2016,59(11):56-65.
[77]YOU S,ZHANG J,LE G.Large-scale spatial join query processing in Cloud[C]//IEEE International Conference on Data Engineering Workshops,2015:34-41.
[78]AJI A,WANG F,VO H,et al.Hadoop-GIS:a high performance spatial data warehousing system over Map Reduce[J].Proceedings of the Vldb Endowment,2013,6(11):1009-1020.
[79]ELDAWY A,MOKBEL M F.Spatial Hadoop:a MapReduce framework for spatial data[C]//IEEE International Conference on Data Engineering,2015:1352-1363.
[80]YU J,WU J,SARWAT M.GeoSpark:a cluster computing framework for processing large-scale spatial data[C]//Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems,2015:1-4.
[81]LENKA R K,BARIK R K,GUPTA N,et al.Comparative qnalysis of Spatial Hadoop and GeoSpark for geospatial big data analytics[C]//2016 2nd International Conference on Contemporary Computing and Informatics,IEEE,2016.
[82]GüNTHER O,MüLLER R.From GISystems to GIServices:spatial computing on the internet marketplace[M].Springer US,Boston,MA USA.1999:445-448.
[83]张犁,林晖,李斌.互联网时代的地理信息系统[J].测绘学报,1998,(1):12-18.
[84]钱新林,张福浩,刘纪平.全矢量WebGIS架构研究[J].测绘通报,2012,(S1):768.
[85]ANTONIOU V,MORLEY J,HAKLAY M.Tiled Vectors:a method for vector transmission over the Web[C]//International Symposium on Web and Wireless Geographical Information Systems,Springer,2009:56-71.
[86]SAMPLE J T,IOUP E.Tile-based geospatial information systems:principles and practices[M].Springer US,New York,NY USA.2010.
[87]GOU L M,ZHU M Z,YAN-MING L I.Study on web map tile service based on RESTful[J].Computer Engineering and Design,2012,33(9):3609-3616.
[88]ZHOU X.Analysis on OpenGIS web map tile service implementation standard[J].Geomatics World,2011.
[89]周旭.OpenGIS网络地图分块服务实现标准(WMTS)分析[J].地理信息世界,2011,(04):10-14+32.
[90]LIU H,NIE Y.Tile-based map service GeoWebCache middleware[C]//IEEE International Conference on Intelligent Computing and Intelligent Systems,2010:692-697.
[91]NIE Y F,XU H,LIU H L.The design and implementation of tile map service[J].Advanced Materials Research,2010,159:714-719.
[92]苗立志,伍蓝,李振龙,等.多源分布式CSW和WMS地理信息服务集成与互操作[J].地理与地理信息科学,2010,26(3):11-14.
[93]王亚平,蒲英霞,刘大伟,等.基于TileStache的多源投影矢量数据瓦片生成技术研究[J].地理信息世界,2015,(1):77-81.
[94]ERIKSSON O,RYDKVIST E.An in-depth analysis of dynamically rendered vector-based maps with WebGL using Mapbox GL JS[D].City:Linköping University,2015.
[95]J.DE LA TORRE J.Organising geo-temporal data with CartoDB,an open source database on the cloud[J].Biodiversity Informatics Horizons,2013.
[96]WOLF E B,MATTHEWS G D,MCNINCH K,et al.OpenStreet Map collaborative prototype,phase one[J].US Geological Survey,2011.
[97]ZIELSTRA D,HOCHMAIR H,NEIS P,et al.Areal delineation of home regions from contribution and editing patterns in OpenStreet Map[J].ISPRS International Journal of Geo-Information,2014,3(4):1211-1233.
[98]CONGOTE J,SEGURA A,KABONGO L,et al.Interactive visualization of volumetric data with WebGL in real-time[C]//Proceedings of the International Conference on Web 3D Technology,2011:137-146.
[99]IWATA S,TAKEI M,TAKENAKA T,et al.Development of information sharing system synchronizing Google maps and WebGL:experiment of space based data visualization and manipulation with operability and utility[J].Aij Journal of Technology and Design,2015,21(48):865-868.
[100]廖明,潘媛芳.WebGIS矢量地图绘制方法的性能分析与比较WebGIS的技术方案[C]//《测绘通报》测绘科学前沿技术论坛,2008:8.
[101]廖明,潘媛芳.WebGIS矢量地图绘制方法的性能比较分析[C]//华东六省一市测绘学会第十一次学术交流会,2009:7.
[102]GOODCHILD M F.Citizens as sensors:the world of volunteered geography[J].GeoJournal,2007,69(4):211-221.
[103]BHARGAVA N,BHARGAVA R,SHARMA N.Integrating WebGIS with WFS and GML[J].International Journal of Computer Science and Communication Networks,2012,2(1).
[104]MICHAELIS C,AMES D P.OGC-GML-WFS-WMS-WCS-WCAS:The Open GIS Alphabet soup and implications for water resources GIS[J].Monthly Notices of the Royal Astronomical Society,2006,351(1):125-132.
[105]LIU J P,YAN F,ZHAO H L.Application of visualization in scientific computing technology[J].Advanced Materials Research,2011,1225(215).
[106]MCCORMICK B H.Visualization in scientific computing[J].ACM SIGBIO Newsletter,1988,10(1).
[107]ZANARINI P,SCATENI R,WIJK J V.Visualization in scientific computing＇95[C]//Proceedings of the Eurographics Workshop,Springer,1998:69-69.
[108]SHIRLEY P.Fundamentals of computer graphics(second edition)[M].北京:人民邮电出版社.2007.
[109]常明,纪俊文.计算机图形学.[M].3版.武汉:华中科技大学出版社,2009.
[110]KAUFMAN A.Rendering,visualization and rasterization hardware[C]//Advances in Computer Graphics Hardware,1993.
[111]ROSENBLUM L J.Scientific visualization.advances and challenges[J].Blaise Pascal University France,1994,30(12):1464-1475.
[112]ZHU L,ZHU C Y,GU H B,et al.Visualized flight control and flight mechanics calculation[J].Advanced Materials Research,2012,1917(562).
[113]CHANG Y T,SUN S W.A realtime interactive visualization system for knowledge transfer from social media in a big data[C]//2013 9th International Conference on Information,Communications and Signal Processing,2013:1-5.
[114]YOO T S,MA K-L.Taking stock of visualization in scientific computing[J].ACM SIGGRAPH Computer Graphics,2004,38(3).
[115]仇应俊.交互式可视化网格系统GVis研究及实现[D].杭州:浙江大学,2006.
[116]SIMON P.The visual organization:data visualization,big data,and the quest for better decisions[M].John Wiley&Sons,Henderson,Nevada.2014.
[117]KHAN M,SHAH S.Data and information visualization methods,and interactive mechanisms:a survey[J].International Journal of Computer Applications,2011,34(1):1-14.
[118]KUMAR R R.Visualizing big data mining:challenges,problems and opportunities[J].International Journal of Computer Science and Information Technologies,2015,6(4):3933-3937.
[119]HOSKINS M.Common big data challenges and how to overcome them[J].Big Data,2014,2(3):142.
[120]SUCHARITHA V,SUBASH S R,PRAKASH P.Visualization of big data:Its tools and challenges[J].International Journal of Applied Engineering Research,2014,9(18):5277-5290.
[121]CHILDS H,GEVECI B,SCHROEDER W,et al.Research challenges for visualization software[J].Computer,2013,46(5):34-42.
[122]KIM Y I,JI Y K,SUN P.Social network visualization method using inherence relationship of user based on cloud[J].International Journal of Multimedia and Ubiquitous Engineering,2014,9(4):13-20.
[123]ELMQVIST N,FEKETE J D.Hierarchical aggregation for information visualization:overview,techniques,and design guidelines[J].IEEE Transactions on Visualization and Computer Graphics,2009,16(3):439-454.
[124]SARMA A D,LEE H,GONZALEZ H,et al.Efficient spatial sampling of large geographical tables[C]//Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data,Association for Computing Machinery,2012:193-204.
[125]TAKEDA S,KOBAYASHI A,KOBAYASHI H,et al.Irregular trend finder:visualization tool for analyzing time-series big data[C]//Visual Analytics Science and Technology,2012:305-306.
[126]AGRAWAL R,KADADI A,DAI X,et al.Challenges and opportunities with big data visualization[C]//Proceedings of the 7th International Conference on Management of computational and collective intElligence in Digital EcoSystems,Association for Computing Machinery,2015:169-173.
[127]KEAHEY T A.Using visualization to understand big data[J].Technical Report,IBM Corporation,2013:1-16.
[128]LIU Z,JIANG B,HEER J.im Mens:real-time visual querying of big data[C]//Eurographics Conference on Visualization,2013:421-430.
[129]LEE J,PODLASECK M,SCHONBERG E,et al.Analysis and visualization of metrics for online merchandising[C]//The WEBKDD'99 International Workshop on Web Usage Analysis and User Profiling,Springer-VerlagBerlin,Heidelberg,1999:126-141.
[130]AHLBERG C,SHNEIDERMAN B.Visual information seeking:tight coupling of dynamic query filters with starfield displays[C]//Conference Companion on Human Factors in Computing Systems,1994:313-317.
[131]MIHALISIN T,TIMLIN J,SCHWEGLER J.Visualizing multivariate functions,data,and distributions[J].IEEE Computer Graphics and Applications,1991,11(3):28-35.
[132]CARR D B,LITTLEFIELD R J,NICHOLSON W L,et al.Scatterplot matrix techniques for large N[J].Journal of the American Statistical Association,1987,82(398):424-436.
[133]NGUYEN Q V,HUANG M L.EncCon:an approach to constructing interactive visualization of large hierarchical data[J].Information Visualization,2005,4(1):1-21.
