This provides a computational tool for big data computation.
esProc provides an easy-to-implement computation framework for big data. It is able to support Hadoop distributed file system or the HDFS. This tool is suitable for large data volumes that impose a huge computational workload. The tool copes with such requirements with high degree of concurrency and is able to handle heterogeneous multi-data-source applications. It also provides a scripting language to ease implementation. The HDFS is designed to run on commodity hardware. However, there are significant differences. HDFS provides fault-tolerance. High throughput access to application data is provided for applications that have large data sets. It supports streaming data access and the applications that need such access are the ones supported and these are typically batch processes rather than interactive ones. The data sets handled by such applications are typically in the gigabytes. This is a script package designed for computations involving databases.
This script helps increase efficiency of development in Java, reporting and the web applications. It offers an intuitive grid style, step-by-step computation concepts implementation, specialized debugging features, agile syntax, and all-round and well-defined computing setup, etc. This tool gives developers a convenient middleware that communicates with applications through JDBC and implements parallel computation outside the database and in external-memory. That relieves computational pressures on the database and storage. esProc offers a user-friendly IDE. Reporting tools to reference the computed result is done conveniently through JDBC interface. Complex business computation needs can be decomposed and defined in a grid provided by the tool. These sub-tasks are simple objectives that the larger goals have been broken into. This is a very good tool.