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Batch processing is a pervasive workload pattern, expressed by a distinct application organization and execution model. It is found across virtually every industry, applied to such tasks as statement generation, bank postings, risk evaluation, credit score calculation, inventory management, portfolio optimization, and on and on. Nearly any bulk processing task from any business sector is a candidate for batch processing. Batch processing is typified by bulk-oriented, non-interactive, background execution. Frequently long- running, it may be data or computationally intensive, execute sequentially or in parallel, and may be initiated through various invocation models, including ad hoc, scheduled, and on-demand. Batch applications have common requirements, including logging, checkpointing, and parallelization. Batch workloads have common requirements, especially operational control, which allow for initiation of, and interaction with, batch instances; such interactions include stop and restart.

The Java Algebra System (JAS) is an object oriented, type safe and multi-threaded approach to computer algebra. JAS provides a well designed software library using generic types for algebraic computations implemented in the Java programming language using the JVM runtime infrastructure. The library can be used as any other Java software package or it can be used interactively or interpreted through a jython (Java Python) or jruby (Java Ruby) front end, there is also an Android App based on Ruboto (jruby for Android). The focus of JAS is at the moment on commutative, solvable and non-commutative polynomials, power series, Groebner bases, factorization, real and complex roots and applications. By the use of Java as implementation language JAS is 64-bit and multi-core CPU ready and can make use of mutiple CPUs where available. JAS can run on a wide variety of devices ranging from Android to compute clusters (using MPJ a Java Message Passing Interface (MPI) or OpenMPI).

Batch processing is a pervasive workload pattern, expressed by a distinct application organization and execution model. It is found across virtually every industry, applied to such tasks as statement generation, bank postings, risk evaluation, credit score calculation, inventory management, portfolio optimization, and on and on. Nearly any bulk processing task from any business sector is a candidate for batch processing. Batch processing is typified by bulk-oriented, non-interactive, background execution. Frequently long- running, it may be data or computationally intensive, execute sequentially or in parallel, and may be initiated through various invocation models, including ad hoc, scheduled, and on-demand. Batch applications have common requirements, including logging, checkpointing, and parallelization. Batch workloads have common requirements, especially operational control, which allow for initiation of, and interaction with, batch instances; such interactions include stop and restart.

Batch processing is a pervasive workload pattern, expressed by a distinct application organization and execution model. It is found across virtually every industry, applied to such tasks as statement generation, bank postings, risk evaluation, credit score calculation, inventory management, portfolio optimization, and on and on. Nearly any bulk processing task from any business sector is a candidate for batch processing. Batch processing is typified by bulk-oriented, non-interactive, background execution. Frequently long- running, it may be data or computationally intensive, execute sequentially or in parallel, and may be initiated through various invocation models, including ad hoc, scheduled, and on-demand. Batch applications have common requirements, including logging, checkpointing, and parallelization. Batch workloads have common requirements, especially operational control, which allow for initiation of, and interaction with, batch instances; such interactions include stop and restart.

relay-jdbc allows a JDBC connection to be relayed through an intermediate relay server: it is both a JDBC driver (client) and a JDBC relay server. It is a fork of https://github.com/AugeoSoftware/VJDBC project, where Aleksei Yu. Semenov has implemented a number of brilliant improvements of the orignal VJDBC project hosted on http://vjdbc.sourceforge.net Original Developers were: Hunter Payne ([email protected]) and Michael Link ([email protected]). For all pre-existing code, credits go to the original respective author. This product brings the original VJDBC concept further and (apart from code quality improvements and bug fixes) implements complete separation of the underlying transport mechanism, introducing support for connecting directly through a SSH pipe, where the relay server interacts with the client through standard I/O pipes. The re-designed transport architecture supports easy development of new transport implementations, allowing this JDBC relay to be quickly adapted to a variety of exotic environments.