This preface describes significant new features and changes in Oracle Big Data Spatial and Graph User's Guide and Reference for Oracle Big Data Spatial and Graph Release 1.2.
The information about installing and configuring Oracle Big Data Spatial and Graph has been revised and enhanced, especially for Installing and Configuring the Big Data Spatial Image Server.
Oracle Big Data Spatial Vector Analysis has been revised and expanded to cover more operations and options.
Oracle Big Data Spatial Vector Hive Analysis describes spatial functions to analyze the data using Hive.
Hive Spatial Functions provides reference information about the available functions.
Using the Oracle Big Data Spatial and Graph Vector Console provides expanded information abuot using the Oracle Big Data Spatial and Graph Vector Console to perform tasks related to spatial indexing and creating and showing thematic maps.
Using Property Graphs in a Big Data Environment and Using the In-Memory Analyst provide more information and examples. Major additions include:
New SQL-like declarative language for querying property graph data, including a rich set of graph pattern matching capabilities, For details, see Querying Property Graph Data.
New distributed mode for the in-memory analyst. The in-memory analyst can now be run in a distributed mode, in which multiple nodes (computers) form a cluster, partition a large property graph across distributed memory, and work together to provide efficient and scalable graph analytics. For details, see Using the In-Memory Analyst in Distributed Mode.
In-memory analyst support for reading data from HDFS. For details, see Loading Data from HDFS.
New built-in analytics. More built-in analytics have been added, including the following:
Approximate Pagerank is a faster variant of Pagerank that can be used when less precision is acceptable.
Weighted Pagerank considers edge weights.
Personalized SALSA evaluates the relative importance of nodes with respect to a given set of hub nodes.
K-Core computes k-core decomposition of a graph.
For details, see the Oracle Big Data Spatial and Graph In-Memory Analyst Java API Reference (Javadoc).
The Java API Reference (Javadoc) material for Big Data Spatial and Graph reflects many new packages and classes available with this release. The Big Data Appliance Documentation Library has a "Big Data Spatial and Graph" section with links to the available Java API Reference material.