esProc is pure JAVA product with complete computation system and agile syntax, supportive of high-performance parallel computation. It can effectively enhance computing performance, improve development efficiency, relieve pressure of database and optimize database management.
Enhancing computing performance
esProc is specialized in Big Data computation, and it can not only be deployed in single server, but also on multiple servers to conduct parallel computation. Parallel computation can disperse concentrated large computation on multiple servers to enhance computing performance by distributing computation.
esProc supports computation on single database or multiple data sources, which means computation can be accomplished among various databases or between database and non-database. Especially, esProc can access HDFS, provides external-memory computation mechanism and is capable to process big data.
esProc not only supports computation on structured data, but also non-structured data. Its computing system is flexible and users could easily customize their algorithm.
Improving development efficiency
esProc is data-computing script written in the grid, with support of cell name reference, step-by-step computation, observation on steps details, simplifying complex computing goal into simple steps, and real debugging function.
esProc has agile syntax and supports set data, dissociative record, ordered set, object reference as well as set-type grouping, allowing users to conduct computation freely with higher development efficiency than SQL/SP.
In addition, esProc can output JDBC directly and easier to integrate with JAVA code and reporting tools.
Alleviating workload on database
esProc has complete computing ability and can be deployed on low-end server to improve computation performance via parallel multiple node. Therefore, esProc can exist as computational middleware, which is responsible for computation service between database layer and application layer. Since the computation pressure from outside has been greatly reduced, database can work on data security management and storage service more efficiently.
esProc can efficiently share the computation pressure of database which is helpful for database hardware and software cost reduction.
Optimizing database management
esProc supports HDFS, external-memory file, parallel computation and node expansion. Therefore, with the increasing temporary tables and stored procedures, esProc can be adopted to compute these redundant data while Database only needs to be responsible for the storage and security of core data. In this case, the cost on dedicated storage device and server of database can be reduced.
In addition, esProc adopts tree-structured file system to store data. New and old redundant data and organization access can be conveniently managed in this way, which is more intuitive and convenient than traditional database without physical layering. Data management is also effectively optimized.