ScaleOut Analytics Server
ScaleOut Analytics Server combines a scalable, in-memory data grid (IMDG) with powerful computational features to deliver near real-time map/reduce analytics. This platform employs a simplified form of map/reduce that reduces development time and accelerates performance.ScaleOut Analytics Server enables applications to execute user-defined methods in parallel on a selected set of data and then combine the results with user-defined merge algorithms. It stores datasets as objects in a scalable, in-memory data grid, minimizing data motion and providing fast results. Performing analysis with... Read more
188.8.131.52 (Other available versions)
Linux/Unix, Amazon Linux 2012.09
64-bit Amazon Machine Image (AMI) (Read more)
AWS Services Required
Amazon EC2, Amazon EBS
- Ease of Use: Map/reduce methods are written as in-memory Java methods without use of APIs to access data from the in-memory data grid. Data for analysis is selected using parallel query based on object properties.
- Automatic code shipping: Ships application code and dependent libraries to each server and deploys them, creating an execution environment on the in-memory data grid. Applications can pre-stage the execution environment to optimize performance.
- Fast Performance, No Tuning: Automatically executes map and reduce methods in parallel across multiple cores within each server and all servers within the in-memory data grid. The grid merges results across servers to provide an in-memory result.
ScaleOut Analytics Server combines a scalable, in-memory data grid (IMDG) with powerful computational features to deliver near real-time map/reduce analytics. This platform employs a simplified form of map/reduce that reduces development time and accelerates performance.
ScaleOut Analytics Server enables applications to execute user-defined methods in parallel on a selected set of data and then combine the results with user-defined merge algorithms. It stores datasets as objects in a scalable, in-memory data grid, minimizing data motion and providing fast results.
Performing analysis with ScaleOut Analytics Server requires no special knowledge of parallel programming. The user writes methods to analyze data and merge results using standard Java methods, then uses queries on object properties to select objects for analysis. In addition, the software automatically deploys application code and dependent libraries on all grid servers, eliminating time-consuming setup.
Using Single Method Invocation (SMI), applications can invoke a method on a specified set of objects, supply parameters to invocation, and receive the method's result value. SMI can be used to analyze a targeted set of stored objects, or to update them without replacing their full contents in a manner similar to stored procedures in database systems.
NOTE: At this time, this product instance must be launched using the "Launch with EC2 Console" option.
- Version: 184.108.40.206
- Available on AWS Marketplace Since: 11/02/2012
To administer this product, ScaleOut Software, Inc. provides a StateServer Management Console on Windows, and a command-line Python script combined with a Web Management Console for Linux. To acquire these tools on your management workstation, download and install the latest ScaleOut StateServer Remote Client installer for Linux operating systems or the ScaleOut StateServer installer for Windows systems from our Support Downloads page: http://www.scaleoutsoftware.com/support/support-downloads/ . On Windows operating systems, select the Remote Client/Cloud Mgt. setup type.Once installed, please see the ScaleOut StateServer Help file for step-by-step instructions to launch and manage ScaleOut StateServer on Amazon EC2. This help file can be found in the product installation directory on your local system, or online at http://www.scaleoutsoftware.com/support/product-documentation/ ...
ScaleOut Analytics Server
Standard Support & Maintenance plan included in pricing. Gold and Platinum Support available through ScaleOut Software directly. See http://www.scaleoutsoftware.com/support/options/ for more details.
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