Download JAR files tagged by performance with all dependencies

This Tool provides the means to monitor the performance of Spring Batch applications without the need to manipulate the respective code basis. Through Listeners and AOP it evaluates the throughput of a monitored Job and writes the result to a simble database-schema (a file-based H2 by default). It measures the performance of Job, Step, Chunk, Reader/Processor/Writer/Tasklet down to indivdual Items. Installation/Usage: 1. Add the springBatchPerformanceMonitoring-dependency to your POM 2. Add the de.viadee.spring.batch.infrastructure.Configurator.class to your Spring-Application-Context (via @Import on your Configuration) 3. Run the Job 4. By default the monitoring result is written to project-folder/target/database/monitoringDB.mv.db

The TraceView Java instrumentation agent. Contains the required jar, configuration file and native libraries for Windows and Linux. TraceView provides application performance monitoring for Java web apps through this agent. The files contained here allow for event tracking within your application to identify latency timings between your application layers. More options can be found here: http://docs.traceview.solarwinds.com/Instrumentation/java.html#configuring-instrumentation. For other information on our Java agent please visit http://docs.traceview.solarwinds.com/Instrumentation/java.html.

The crypto4j library provides a simple and pluggable crypto abstraction library for Java, including both cryptographic primitives and the artifacts defined in the JOSE standard. This library separates the cryptographic primitives from the JOSE artifacts. The library uses the algorithms available through JCA (JCE). The implementations of the cryptographic primitives provided in this library rely on the standard JCA implementation, and can be configured and extended through the JCA mechanisms. The JOSE portion of the library allows custom extensions by either replacing the provided JOSE artifact implementations with custom implementations, or by adding new JOSE artifacts, for instance in form of additional algorithms, which is particularly useful in case that the JOSE standard is updated or in case custom extensions to the JOSE standard should be implemented. The implementations available in this library generally come in two variants: a standard implementation of the primitives and advanced algorithms, and a high-performance implementation that takes advantage of implementation patterns that do not compromise cryprographic security, but speed up the overall processing time.

The AppNeta Java instrumentation agent. Contains the required jar, configuration file and native libraries for Windows and Linux. AppNeta provides application performance monitoring for Java web apps through this agent. The files contained here allow for event tracking within your application to identify latency timings between your application layers. More options can be found here: https://docs.appneta.com/java#configuring-instrumentation. For other information on our Java agent please visit https://docs.appneta.com/java.

This is an open source library that allows generating performance indicators easily for java based application. This library is configurable through an xml file (similar to log4j) in order to define the performance object types, dimensions, counters, the output format and statistics generation periodicity. Those statistics can be saved as a file (xml/json) or injected directly in a database. Then they can be correlated and analyzed through any Business Intelligence solution in order to check the application performance and quality: number of transactions, ratio of successful and failure ...

ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.

MASSIS is a framework that facilitates the simulation of scenarios with multiple agents (representing people, robots, sensors, etc.) in indoor environments (i.e., in a building). MASSIS provides support for designing spaces and specifying the behavior of the elements and agents in them It is possible to define a great diversity of behaviours, from a simple sensor to the decisions of a person. MASSIS has been designed to keep this flexibility withough hindering performance. The framework is capable of supporting thousands of agents, each one with an specific behavior.

The Infinispan Spring Integration project provides Spring integration for Infinispan, a high performance distributed cache. Its primary features are * An implementation of org.springframework.cache.CacheManager, Spring's central caching abstraction, backed by Infinispan's EmbeddedCacheManager. To be used if your Spring-powered application and Infinispan are colocated, i.e. running within the same VM. * An implementation of org.springframework.cache.CacheManager backed by Infinispan's RemoteCacheManager. To bes used if your Spring-powered application accesses Infinispan remotely, i.e. over the network. * An implementation of org.springframework.cache.CacheManager backed by a CacheContainer reference. To be used if your Spring- powered application needs access to a CacheContainer defined outside the application (e.g. retrieved from JNDI) * Spring namespace support allowing shortcut definitions for all the components above In addition, Infinispan Spring Integration offers various FactoryBeans for facilitating creation of Infinispan core classes - Cache, CacheManager, ... - within a Spring context.

The Virtuoso server module (ks-server-virtuoso) provides an implementation of the Triple Store server-side component (API in ks-triplestore) on top of the OpenLink Virtuoso triple store, a scalable native code triple store that is accessed as an external service. The Virtuoso Sesame driver, which builds on the Virtuoso JDBC driver, is used to remotely access the Virtuoso server for writing data and performing SPARQL queries. For performance reasons, data modification is performed in a non-transactional way, with the module managing possible failures in a way that trigger the external repopulation of the Virtuoso triple store starting from the master copy of data stored in the Data Store component.