Oracle Loader for Hadoop & Oracle SQL Connector for HDFS
Oracle Loader for Hadoop
Oracle Loader for Hadoop (OLH), part of Oracle Big Data Connectors, is a MapReduce utility to optimize data loading from Hadoop into Oracle Database. OLH sorts, partitions, and converts data into Oracle Database formats on Hadoop, and loads the converted data into the database. By preprocessing the data to be loaded as a Hadoop job on a Hadoop cluster, Oracle Loader for Hadoop reduces the CPU and IO utilization on the database.
Oracle Loader for Hadoop has online and offline options. Both load the sorted and transformed data in parallel into the correct partition in the database.
Oracle SQL Connector for Hadoop Distributed File System (HDFS)
Oracle SQL Connector for HDFS, part of Oracle Big Data Connectors, is a high speed connector for accessing data on HDFS directly from Oracle Database. Oracle SQL Connector for HDFS gives users the flexibility of accessing and importing data from HDFS at any time, as needed by their application.
The connector for HDFS enables the creation of an external table in Oracle Database, enabling direct SQL access on data stored in HDFS. The data can be in delimited files or in Oracle data pump files created by Oracle Loader for Hadoop.
Presentations and White Papers
Big Data Connectors: High-Performance Integration for Hadoop and Oracle Database—Organizations face the need to integrate both structured and unstructured data for advanced analysis. Hadoop is increasingly used to process unstructured data, and this data has to be combined with structured business data in relational databases for analysis. Oracle Big Data Connectors enable this by providing high performance connectivity between Hadoop and Oracle Database and optimized Oracle R analysis of data on Hadoop along with database resident data. Further, data processing and integration on Hadoop can be driven by a graphical user interface. This presentation gives a technical overview of these products. Melli Annamalai, Sue Mavris and Rob Abbott Oracle OpenWorld 2012 Presentation (October 2012)