Batch processing is a widely used technique for efficiently processing very large amounts of data collected over a specified period of time. HadoopMapReduce is a distributed processing framework within batch processing that schedules, monitors, distributes, and re-distributes any failed tasks. Some challenges in batch processing include slow output, inadequacies in infrastructure for machine learning, and increased consumption in CPU.
Acelero software optimizes the HadoopMapReduce framework to reduce batch processing time and improve CPU utilization. With Acelero, business users are able to draw the most value from their data analytics exercise. For example; without Acelero, a batch job could run for 20 minutes utilizing 4 servers, whereas, with Acelero, the same job will run for 10 minutes on 2 servers!
Acelero is simple plug and play software that has been certified by Cloudera and MapR that allows for a 1.5 to 3 times performance improvements without having to do any code changes, re-architect, or purchase additional hardware.
Acelero is comprised of patent-pending technologies related to data sorting, parallel processing, process deduplication, adaptive caching, and compression for Big Data applications. Acelero supports the latest versions of all major Hadoop platforms.