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 2.0.
The property graph feature in Oracle Big Data Spatial and Graph enables integration of in-memory analytics and Apache Spark, as explained in Using the In-Memory Analyst to Analyze Graph Data in Apache Spark.
You can convert CSV (comma-separated value) files representing the vertices and edges of a graph to Oracle-defined flat file format definition, as explained in Converting CSV Files for Vertices and Edges to Oracle-Defined Property Graph Flat Files
Support for querying property graph data has been enhanced. Querying Property Graph Data explains this support and provides examples.
You can treat the value of a designated vertex property as one or more labels, as explained in Specifying Labels for Vertices.
When you create custom processing classes, you can use the Oracle Spatial Hadoop Raster Mocking Framework to do perform certain tests by "pretending" to plug the classes into the Oracle Raster Processing Framework, as explained in Using the Oracle Spatial Hadoop Raster Mocking Framework to Test Raster Processing.
Big Data Spatial and Graph Release 2.0 supports property graph indexing using Apache Solr 5.2.x with Hortonworks and Solr 4.10.x with CDH.
In the Java API, convertCSV2OPE is new and takes two offset parameters: lOffsetSVID and lOffsetDVID. convertRDBMSTable2OPE is also new and takes two offset parameters: lSVIDOffset, and lDVIDOffset. These new offset parameters allow you to better handle vertices and edges mapped from multiple data sources.