Search Results for "dataflow"

...These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers.

ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and...

Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level APIs—DataStream and Table/SQL—to express transformations, joins, and stateful patterns, while specialized libraries support CEP, machine learning workflows, and connectors. ...

Static analysis of Python web applications based on theoretical foundations (Control flow graphs, fixed point, dataflow analysis) Detect command injection, SSRF, SQL injection, XSS, directory traveral etc. A lot of customization is possible. For functions from builtins or libraries, e.g. url_for or os.path.join, use the -m option to specify whether or not they return tainted values given tainted inputs, by default this file is used.

...The internals of main() are built using Reactive Programming primitives, which maximizes separation of concerns and provides a fully declarative way of organizing your code. The dataflow is plainly visible in the code, making it readable and traceable. Cycle.js apps are made of pure functions, which means you know they only take inputs and generate predictable outputs, without performing any I/O effects. The building blocks are reactive streams from libraries like xstream, RxJS or Most.js, which greatly simplify code related to events, asynchrony, and errors.

QFlow is a dataflow framework written in Qt which allows interaction of QObjects in a dataflow graphs. Such a workflow can contain graphical modules(QWidgets) which would be displayed during the execution of graph and can interact with other QObjects. Framework consists of Designer and multiple plugins with modules.

The Squidy Interaction Library eases the design of "post-WIMP" user interfaces by unifying various device drivers, frameworks and tracking toolkits in a common library and provides a central and easy-to-use visual design environment. www.squidy-lib.de

sdf4j is a Java framework to manipulate Static Dataflow graphs (SDF).