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Oracle Big Data Spatial and Graph

Spatial and graph analytic services and data models that support Big Data workloads on Apache Hadoop and NoSQL database technologies.

Overview

Oracle Big Data Spatial and Graph includes two main components: A property graph database and 35 built-in graph analytics that discover relationships, recommendations and other graph patterns in big data and a wide range of spatial analysis functions and services to evaluate data based on how near or far something is to one another, whether something falls within a boundary or region, or to process and visualize geospatial map data and imagery.

Data Sheet, Feature Overviews and White Papers
Presentations, Articles and Webcasts

Hands on Labs

Applying Hadoop Spatial Analysis To Big Data

In this lab, you will learn how to use and apply geo-enrichment and data harmonization services, and geographic and location analysis functions for categorizing and filtering your big data workloads. It will show you how to:

  • Load common log data like twitter feeds to HDFS, and perform spatial analysis on that data.
  • Develop a RecordReader for this sample data so that spatial analysis functions can be applied to records in the data.
  • Create and use a spatial index for such data.
  • Use RecordReaders for additional data formats like Shape and JSON.
  • Use the HTML5 mapping API to create interactive visualization applications on HDFS data.

Applying Hadoop Spatial Analysis to Big Data (January 2018) (Zip file - 35.3MB)

Applying Spark Spatial Analysis To Big Data

In this lab, you will learn how to explore and analyze data from HDFS, from the Oracle database or streamed data. It will show you how to:

  • Load common log data like twitter feeds to HDFS, and perform spatial analysis on that data.
  • Create and use a spatial index for such data.
  • Filter spatial and non-spatial data with Spark SQL.
  • Perform spatial join analysis using data from HDFS and from the Oracle Database.
  • Perform a nearest neighbor analysis.
  • Use the Streaming API and monitor the results in real time.
  • Use the REST API as data source for the Map API to display the results on map.
  • Use the HTML5 mapping API to create interactive visualization applications on HDFS data.

Applying Spark Spatial Analysis to Big Data (January 2018) (Zip file - 9.3MB)

Gain Insight into Your Graph Data

This hands-on lab will show you how to use the key APIs to manipulate property graph data stored in either Oracle NoSQL Database or Apache HBase, perform powerful text query to find vertices and edges of interest, and to pick suitable analytics to gain insight into your data. Specifically, it will use a real-world social graph to illustrate:

  • Core data access layer functions on both Oracle NoSQL Database and Apache HBase
  • Built-in graph analytics including community detection, connectivity, ranking, and recommendation
  • SolrCloud based distributed text search for graph elements
  • Property graph visualization with Cytoscape integration

Accessing the Hands-on Lab:

  • Download the Big Data Lite Virtual Machine here
  • Click the desktop "Refresh Samples" icon, and follow the instructions to fetch the Big Data Spatial and Graph Property Graph HoL/Demo.
  • When the refresh is done, open the following page with the built-in Firefox browser: file:///u01/property_graph_demo/property_graph_hol_big_data_lite_vm_2015_Nov.htm

Partners

Partner Product Description
Graph Visualization Tools
Tom Sawyer Software Perspectives Tom Sawyer Perspectives is an advanced graphics-based Software Development Kit (SDK) for federating data from multiple sources and building enterprise-class graph and data visualization and analysis applications.
Open Source Cytoscape Network Visualizer "Cytoscape is an open source software platform for visualizing complex-networks and integrating these with any type of attribute data. Plugins are available for various kinds of problem domains, including bioinformatics, social network analysis, and semantic web."