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Data Mining Ii - 1Dl460 DATA MINING II - 1DL460 Spring 2017 A second course in data mining! ! http://www.it.uu.se/edu/course/homepage/infoutv2/vt17 Kjell Orsborn! Uppsala Database Laboratory! Department of Information Technology, Uppsala University, ! Uppsala, Sweden Kjell Orsborn - UDBL - IT - UU 17-03-09 1 Introductory to Spatial Databases Kjell Orsborn - UDBL - IT - UU 17-03-09 2 Spatial Database • A spatial database is a database that is optimized to store and query data that represents objects defined in a geometric space. – Most spatial databases allow representing simple geometric objects such as points, lines and polygons. ! – Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and triangulated irregular networks (TINs) . ! – Conventional databases developed to manage various numeric and character types of data! – Spatial databases require additional functionality to process spatial data types efficiently, and developers have often added geometry or feature data types. ! • The Open Geospatial Consortium developed the Simple Features Access specification (first released in 1997) and sets standards for adding spatial functionality to database systems.! • The SQL/MM Spatial ISO/EIC standard is a part the SQL/MM multimedia standard and extends the Simple Features standard with data types that support circular interpolations. Kjell Orsborn - UDBL - IT - UU 17-03-09 3 tributors to SQL/MM did not want to move forward with a Spatio-temporal support until SQL/Temporal developed.2 In the mean time, thefocus of spatial standard lied on keeping it aligned with the OGC specification and the standards developed by the technical com- mitee ISO/TC 211, for example [ISO02a, ISO02b]. The prefix ST for the spatial tables, PSfrag replacementstypes, and methods was not changed during the organizational changes of the standards, Geometryhowever. Today, one might want to interpret it as Spatial Type. SpatialReferenceSystem Point Curve2.2 Geometry Type Hierarchy Surface CollectionThe OGC geometry class hierarchy is adapted for the corresponding SQL type hierarchy LineStringThethat is definedSQL/MMin the SQL/MM Spatialstandard. Figure 2ISO/EICshows the standardized standardtype hierarchy. PolygonThe shaded types are the not-instantiable types.3 All types are used to represent geometric MultiSurfacefeatures in the 2-dimensionalSQL spatialspace (R ). type hierarchy MultiCurve MultiPoint Line ST Geometry LinearRing MultiPolygon MultiLineString ST Surface ST Curve ST Point ST GeomCollection ST CurvePolygon ST MultiSurface ST MultiCurve ST MultiPoint ST Polygon ST MultiPolygon ST MultiLineString ST LineString ST CircularString ST CompoundCurve ST MultiCircString Figure 2: SQL Type Hierarchy Kjell Orsborn - UDBL - IT - UU 17-03-09 4 The major differences between the SQL type hierarchy and the OGC geometry class hierarchy are the omission of the derived types Line and LinearRing, and the addition 2SQL/Temporal was not any further developed and, like SQL/MM Part, subsequently withdrawn completely. 3It is implementation-defined whether ST MultiCurve and ST MultiSurface are instantiable or not, even though they are shown as not-instantiable in figure 2. Spatial Database • Features of spatial databases: • Spatial databases use a spatial index to speed up database operations! • Spatial databases can perform a wide variety of spatial operations. The following operations and many more are specified by the Open Geospatial Consortium standard: – Spatial Measurements: computes line length, polygon area, the distance between geometries, etc. – Spatial Functions: modify existing features to create new ones, for example by providing a buffer around them, intersecting features, etc. – Spatial Predicates: allows true/false queries about spatial relationships between geometries. Examples include "do two polygons overlap" or 'is there a residence located within a mile of the area we are planning to build the landfill?' (see DE-9IM) – Geometry Constructors: creates new geometries, usually by specifying the vertices (points or nodes) which define the shape. – Observer Functions: queries which return specific information about a feature such as the location of the center of a circle! • Some databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB. Kjell Orsborn - UDBL - IT - UU 17-03-09 5 Spatial Database • Spatial indices are used by spatial databases (databases which store information related to objects in space) to optimize spatial queries. • Conventional index types do not efficiently handle spatial queries such as how far two points differ, or whether points fall within a spatial area of interest. • Common spatial index methods include: – R-tree (also R+ tree, R* tree, Hilbert R-tree): Typically the preferred method for indexing spatial data. Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size. – X-tree – kd-tree – m-tree – an m-tree index can be used for the efficient resolution of similarity queries on complex objects as compared using an arbitrary metric. – Quadtree and Octree – UB-tree (a B+ tree (information only in the leaves) with records stored according to Z-order,) – Space-filling curve, Hilbert (curve), Z-order (curve) – and others (HHCode, Grid (spatial index), Point access method, Binary space partitioning (BSP- Tree subdividing space by hyperplanes) Kjell Orsborn - UDBL - IT - UU 17-03-09 6 Spatial Database Systems • Caliper extends the Raima Data Manager with spatial data types, functions, and utilities. • Boeing's Spatial Query Server spatially enables Sybase ASE. • Smallworld VMDS, the native GE Smallworld GIS database • SpatiaLite extends Sqlite with spatial datatypes, functions, and utilities. • IBM DB2 Spatial Extender can spatially-enable any edition of DB2 • ClusterPoint offers native indexed support for distances, range matching and polygon matching, as well as aggregation. • Oracle Spatial • Oracle Locator • Vertica Place, the geo-spatial extension for HP Vertica, adds OGC-compliant spatial features to the relational column-store database. • Microsoft SQL Server has support for spatial types since version 2008 • PostgreSQL DBMS uses the spatial extension PostGIS to implement the standardized data type geometry and corresponding functions. • Teradata Geospatial includes 2D spatial functionality (OGC-compliant) in its data warehouse system. Kjell Orsborn - UDBL - IT - UU 17-03-09 7 Spatial Database Systems • MonetDB/GIS extension for MonetDB adds OGS Simple Features to the relational column- store database. • Linter SQL Server supports spatial types and spatial functions according to the OpenGIS specifications. • MySQL DBMS implements the data type geometry, plus some spatial functions implemented according to the OpenGIS specifications. As of MySQL 5.0.16, MyISAM, InnoDB, NDB, BDB, and ARCHIVE support spatial features. • Neo4j – a graph database that can build 1D and 2D indexes as B-tree, Quadtree and Hilbert curve directly in the graph • AllegroGraph – a graph database which provides a novel mechanism for efficient storage and retrieval of two-dimensional geospatial coordinates for RDF data. It includes an extension syntax for SPARQL queries. • MarkLogic, MongoDB, RavenDB, and RethinkDB support geospatial indexes in 2D. • Esri has a number of both single-user and multiuser geodatabases. • SpaceBase, a real-time spatial database. • CouchDB a document-based database system that can be spatially enabled by a plugin called Geocouch Kjell Orsborn - UDBL - IT - UU 17-03-09 8 Spatial Database Systems • CartoDB, a cloud-based geospatial database on top of PostgreSQL with PostGIS • StormDB, an upcoming cloud-based database on top of PostgreSQL with geospatial capabilities • AsterixDB, an open-source big data management system with native geospatial capabilities • Kinetica, a GPU-accelerated analytics database optimized for geospatial analytics on large datasets. • SpatialDB by MineRP, OGC spatial database with spatial type extensions for the Mining Industry • H2 supports geometry types and spatial indices. An extension called H2GIS available on Maven Central gives full OGC Simple Features support. • GeoMesa is a cloud-based spatio-temporal database built on top of Apache Accumulo and Apache Hadoop. GeoMesa supports full OGC Simple Features support and a GeoServer plugin. • Ingres 10S and 10.2 include native comprehensive spatial support. Ingres includes the Geospatial Data Abstraction Library cross-platform spatial data translator. • Tarantool supports geospatial queries with R-tree index. • SAP HANA supports geospatial with SPS08 • Redis with the Geo API Kjell Orsborn - UDBL - IT - UU 17-03-09 9 Spatial Database Systems • GeoMesa – Yes yes (Simple Features) yes (JTS) no (manufacturable with GeoTools) no parts of the funcions, a few examples with Simple Feature Access in Java Virtual Machine and Apache Spark are all kinds of tasks solvable yes • ESRI GIS Tools for Hadoop – yes yes (own specific API) yes (union, difference, intersect, clip, cut, buffer, equals, within, contains, crosses, and touches) no no just briefly forking yes • Rasdaman – yes just raster raster manipulation with rasqlyes with Web Coverage Service or Web Processing Service detailed wiki own defined function in enterprise edition no • PostgreSQL with PostGIS – noyes (Simple Features and raster) yes (Simple Feature Access and raster functions) yes yes
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