Internally, the job creates a split for every raster to load. No parameters are required for OBDA environments and a single parameter with the $ALL_ACCESS_FOLDER value is required for non-OBDA environments. This script loads a set of four test rasters into the ohiftest folder in HDFS, 3 rasters of byte data type and 3 bands and 1 raster (DEM) of float32 data type and 1 band. See also Property Graph Sizing Recommendations Manageability through a Groovy-based console to execute Java and Tinkerpop Gremlin APIs Parallel bulk load and export of property graph data in Oracle-defined flat files format Scripting languages support for Groovy and PythonĪ parallel, in-memory graph analytics engineĪ fast, scalable suite of social network analysis functions that include ranking, centrality, recommender, community detection, path finding Text search and query through integration with Apache Lucene and SolrCloud The property graph features of Oracle Big Data Special and Graph support those use cases with the following capabilities:Ī scalable graph database on Apache HBase and Oracle NoSQL Databaseĭeveloper-based APIs based upon Tinkerpop Blueprints, and Java graph APIs Industries including, telecommunications, life sciences and healthcare, security, media and publishing can benefit from graphs.

Typical graph analyses encompass graph traversal, recommendations, finding communities and influencers, and pattern matching. Graphs are commonly used to model, store, and analyze relationships found in social networks, cyber security, utilities and telecommunications, life sciences and clinical data, and knowledge networks. Graphs manage networks of linked data as vertices, edges, and properties of the vertices and edges. Raster operations, including, subsetting, georeferencing, mosaics, and format conversion Support for many image file formats supported by GDAL and image files stored in HDFSĪ sample console to view the set of images that are available Spatial indexing for fast retrieval of data

Topological and distance operations: Anyinteract, Inside, Contains, Within Distance, Nearest Neighbor, and others Support for text-based 2D and 3D geospatial formats, including GeoJSON files, Shapefiles, GML, and WKT, or you can use the Geospatial Data Abstraction Library (GDAL) to convert popular geospatial encodings such as Oracle SDO_Geometry, ST_Geometry, and other supported formatsĪn HTML5-based map client API and a sample console to explore, categorize, and view data in a variety of formats and coordinate systems The Spatial features of Oracle Big Data Special and Graph support those use cases with the following kinds of services.Ībility to associate documents and data with names, such as cities or states, or longitude/latitude information in spatial object definitions for a default administrative hierarchy Georeferenced imagery and sensory data can be analyzed for a variety of business benefits.

Location information can facilitate location-specific offers to customers entering a particular geography, something known as geo-fencing. Location information can also be used to track and categorize entities based on proximity to another person, place, or object, or on their presence a particular area. Businesses can use spatial data as the basis for associating and linking disparate data sets. Spatial location information is a common element of Big Data.

Instaling NetGraph