Download Oracle Spatial 11g Essentials.1z0-595.TestKing.2017-11-27.40q.vcex

SDO_GEOM.SDO_AREA Format SDO_GEOM.SDO_AREA(        geom  IN SDO_GEOMETRY,         dim   IN SDO_DIM_ARRAY          [, unit  IN VARCHAR2]       ) RETURN NUMBER; or SDO_GEOM.SDO_AREA(        geom  IN SDO_GEOMETRY,         tol   IN NUMBER          [, unit  IN VARCHAR2]       ) RETURN NUMBER; Description Returns the area of a two-dimensional polygon. Parameters geom Geometry object. dim Dimensional information array corresponding to geom, usually selected from one of the xxx_SDO_GEOM_METADATA views. unit Unit of measurement: a quoted string with unit= and an SDO_UNIT value from the MDSYS.SDO_AREA_UNITS table (for example, 'unit=SQ_KM').If this parameter is not specified, the unit of measurement associated with the data is assumed. For geodetic data, the default unit of measurement is square meters. tol Tolerance value References: https://docs.oracle.com/database/121/SPATL/sdo_geom-sdo_area.htm#SPATL1110

A: Regardless of what type of data is associated with a theme (except for WMS themes, which represent externally rendered map layers), the MapViewer styling rules still need to be defined for each theme, and the styles referenced by the styling rules must exist and be stored in the database as part of the mapping metadata. D: A WFS theme is a special kind of MapViewer theme that supports the rendering of data delivered using the Open GIS Consortium (OGC) Web Feature Service (WFS) protocol, specifically the WFS 1.0.0 implementation specification. WFS theme are conceptually similar to geometry themes, and users are able to render and label features. The WFS operations GetCapabilities, DescribeFeatureType, and GetFeature are used when rendering a WFS theme. When a WFS service is accessed, MapViewer caches the information about capabilities and feature types. References: https://docs.oracle.com/cd/E12839_01/web.1111/e10145/vis_concepts.htm#JIMPV9548

Oracle Spatial provides different types of converters to convert the geometry data to GML (both Version 2.1 and Version 3.1.1), KML, and the well-known text and binary (WKT and WKB) representations. These converters are provided as PL/SQL functions and Java APIs. References: https://www.safaribooksonline.com/library/view/applying-and-extending/9781849686365/ch02s07.htmlhttps://docs.oracle.com/database/121/SPATL/sdo_util-from_wktgeometry.htmhttps://docs.oracle.com/database/121/SPATL/sdo_util-to_wkbgeometry.htm#SPATL1250

Operations defined by the CSW standard include:Transaction (optional): create/edit metadata by 'pushing' the metadata to the server Harvest (optional): create/update metadata by asking the server to 'pull' metadata from somewhereGetCapabilities: "allows CSW clients to retrieve service metadata from a server"DescribeRecord: "allows a client to discover elements of the information model supported by the target catalogue service. The operation allows some or all of the information model to be described". GetRecords: search for records, returning record IDsGetRecordById: "retrieves the default representation of catalogue records using their identifier"GetDomain (optional): "used to obtain runtime information about the range of values of a metadata record element or request parameter"Note: Catalog Service for the Web (CSW), sometimes seen as Catalog Service - Web, is a standard for exposing a catalogue of geospatial records in XML on the Internet (over HTTP). The catalogue is made up of records that describe geospatial data (e.g. KML), geospatial services (e.g. WMS), and related resources. References: https://en.wikipedia.org/wiki/Catalog_Service_for_the_Web

A spatial R-tree index can index spatial data of up to four dimensions. An R-tree index approximates each geometry by a single rectangle that minimally encloses the geometry (called the minimum bounding rectangle, or MBR), as shown in figure below.     For a layer of geometries, an R-tree index consists of a hierarchical index on the MBRs of the geometries in the layer, as shown in the figure below.     1 through 9 are geometries in a layer. a, b, c, and d are the leaf nodes of the R-tree index, and contain minimum bounding rectangles of geometries, along with pointers to the geometries. For example, a contains the MBR of geometries 1 and 2, b contains the MBR of geometries 3 and 4, and so on. A contains the MBR of a and b, and B contains the MBR of c and d. The root contains the MBR of A and B (that is, the entire area shown). References: https://docs.oracle.com/cd/B28359_01/appdev.111/b28400/sdo_intro.htm#SPATL459

Example Simple translation of a shapefile into Oracle. The table 'ABC' will be created with the features from abc.shp and attributes from abc.dbf. % ogr2ogr -f OCI OCI:warmerda/[email protected] abc.shpReferences: http://www.gdal.org/drv_oci.html

Partitioning is used in data management solutions to address issues of manageability, scalability, and performance C: Here are some Oracle partitioning capabilities that can enhance scalability and performance:Search multiple table or index partitions in parallel Spread the I/O load associated with table or index accesses across multiple controllers Store data physically on disk so that data that is likely to be processed together is close together on disk Eliminate partitions from consideration based on a partition key D: There are many meaningful benefits of partitioning to enhance manageability in a DBMS solution.These benefits include the ability to:Backup data on a partition-by-partition basis Restore data on a partition-by-partition basis Load a partition at a time Store data in different tablespaces on a partition-by-partition basis Rebuild indexes on a partition-by-partition basis References: http://download.oracle.com/otndocs/products/spatial/pdf/spatial_wp10_bestprac.pdf, page 4

Oracle Spatial GeoRaster 10g Release 2 provides a plugin architecture to support wavelet compression schemes such as those from LizardTech. Users who install the LizardTech plugin may compress GeoRaster objects using any of three wavelet compression types:MrSID Generation 2, MrSID Generation 3 and LizardTech JPEG 2000. References: http://doc.lizardtech.com/uploads/2012/02/georaster-lizardtech-mrsid-129598.pdf

The spatial analysis and mining features in Oracle Spatial let you exploit spatial correlation by using the location attributes of data items in several ways: for binning (discretizing) data into regions (such as categorizing data into northern, southern, eastern, and western regions), for materializing the influence of neighborhood (such as number of customers within a two-mile radius of each store), and for identifying colocated data items (such as video rental stores and pizza restaurants). References: https://docs.oracle.com/cd/B28359_01/appdev.111/b28400/sdo_sam_concepts.htm#SPATL070

Sdo_aggr_mbr returns the minimum bounding rectangle (MBR) of the specified geometries, that is, a single rectangle that minimally encloses the geometries. References: https://docs.oracle.com/database/121/SPATL/sdo_aggr_mbr.htm