Recent Posts by Sherry LaMonica

Oracle R Connector for Hadoop (ORCH), a collection of R packages that enables Big Data analytics using HDFS, Hive, and Oracle Database from a local R environment, continues to make advancements. ORCH 2.1.0 is now available, providing a flexible framework while remarkably improving performance and adding new analytics based on the ORCH framework.Previous releases enabled users to write MapReduce tasks in the R language and run them in HDFS. The API was then expanded to...

We are pleased to announce that Oracle R Distribution (ORD) for R 2.15.3 is available for download today. This update consists of mostly minor bug fixes, and is the final release of the R 2.x series. Oracle recommends using yum to install ORD from our public yum server.  To install ORD 2.15.3, first remove the previously installed ORD.  For example, if ORD 2.15.2 is installed, remove it along with it's dependencies: 1. Become root sudo su - 2. Uninstall ORD 2.15.2 RPMs, in...

Oracle R Enterprise enables users to generate R graphs at the database server and return them in a variety of ways: an XML representation using base 64 encoding of the PNG images, in a table with a BLOB column containing the PNG images, and interactively returning the actual image to the R user at the client. This last case allows users to generate images at the database server machine and have the actual PNG image display at the user’s client R engine.To take advantage of...

Oracle R Distribution (ORD) for R 2.15.2 on Linux is now available for download from Oracle's public-yum repository.  R 2.15.2 is a maintenance update that includes improved performance and reduced memory usage for some commonly-used functions, increased memory available for data on 64-bit systems, enhanced localization for Polish language users, and a number of bug fixes.  Detailed updates can be found in the NEWS file - see the section 'CHANGES IN R VERSION 2.15.2'.The...

We're pleased to announce the latest release of Oracle R Enterprise, now available for download. Oracle R Enterprise 1.3 features new predictive analytics interfaces for in-database model building and scoring, support for in-database sampling and partitioning techniques, and transparent support for Oracle DATE and TIMESTAMP data types to facilitate data preparation for time series analysis and forecasting. Oracle R Enterprise further enables transparent access to Oracle...

Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low...

Learn howOracle R Enterprise is used to generate new insight and new value to business, answering not only what happened, but why it happened. View this YouTube Oracle Channel video overview describing how analyzing big data using Oracle R Enterprise is different from other analytics tools at Oracle. Oracle R Enterprise (ORE),  a component of the Oracle Advanced Analytics Option, couples the wealth of analytics packages in R with the performance, scalability, andsecurity of...

ore.stepwise for high-performance stepwise regression This guest post from Alexandre Ardelea describes the Oracle R Enterprise deployment in the Oracle micro-processor tools environment. The deployment of ORE within the Oracle micro-processor tools environment introduced a technology that significantly expands our data analysis capabilities and opens the door to new applications. Oracle R Enterprise (ORE) has been recently deployed in the Oracle micro-processor tools...

Modern computer processors are adequately optimized for many statistical calculations, but large data operations may require hours or days to return a result.  Oracle R Enterprise (ORE), a set of R packages designed to process large data computations in Oracle Database, can run many R operations in parallel, significantly reducing processing time. ORE supports parallelism through the transparency layer, where the database is used as a computationalengine, and embedded R...