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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.

JCQL is a tool allowing to generate boilerplate java code from existing cassandra schema. It is intended to be used with Cassandra 2.1+ due to support of UDTs (User Defined Types)/Tuples/Collections. Cassandra's UDTs/Tuples/Collections and an ability to introspect schema through java driver make it possible to automatically generate POJOs and corresponding mappers between database and java models. Properly generated java code saves development efforts and is less error-prone compared to hand coding. Accompanied with proper CI and deployment it can also guarantee consistency between database and java models at any point of application lifecycle from development to production rollout. JCQL does not rely on java reflection or annotations which means all discrepancies between actual cassandra schema and what client code expects it to be will be identified during compilation not at runtime in the middle of the night right after production release. No need to worry about Cassandra client code performance implications due to use of reflection.

A bottom-up rewrite machine is a compiler construction tool that is often used in the compiler's back end to convert a tree-structured representation of a program into machine code -- or, in Java's case, bytecode. JBurg can also be used as a general-purpose dynamic programming engine. JBurg is descended from iburg-class BURGs, described in Fraser, Hanson, and Proebsting's paper, "Engineering a Simple, Efficient Code Generator Generator." JBurg brings similar O(N) minimum-cost tree rewriting capabilities to Java, and also allows the programmer to specify transitions between non-terminal states, that are significantly more powerful than iburg's transitive closures: JBurg transformation rules allow the transformation to inject additional program logic, which makes a JBurg specification more like a grammar than like a list of pattern-matching rules.

This is a specialized version of the Clirr Maven Plugin. It adds capabilities for excluding specific error types, as well as separating code into three, rather than two, subgroups: Internal code (no checks) Externally invoked code (Annotated with an "externally invoked" annotation, same as Externally implemented, but adding methods to interfaces and abstract classes is allowed) Externally implemented code (Assumed default. Full backwards compatibility required *unless* an interface is annotated with a defined adaptor annotation, in which case full backwards compatibility is required for the adaptor class, but the rules of @ExternallyInvoked apply to the interface itself) Clirr is a tool that checks Java libraries for binary and source compatibility with older releases. Basically you give it two sets of jar files and Clirr dumps out a list of changes in the public API. The clirr-maven-plugin can be configured to break the build, if it detects incompatible api changes. In a continuous integration process, the clirr-maven-plugin can automatically prevent accidental introduction of binary or source compatibility problems. Additionally, the plugin can generate a report as part of the generated site.

The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the Hibersap project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=sapjco3.jar

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.