Apache Beam

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

With origins from Stanford U., Paraxia-Plus-10 is a Windows based optical design program specifically optimized for laser resonator and laser beam propagation applications. Its drag and drop layout mode enables real time visualization of beam properties using the “Digital Laser Workbench”. Laser engineers/designers can access laser beam data not generally available from geometric ray tracing optical design codes. Tools include optimization, tolerance analysis, stability plots, and FFT based rigorous beam propagation of arbitrary input beams. This enables simulation of diffraction effects and beam deviations from decentered and/or laser damaged components. Waist size and location is listed relative to each component, and beam diameter and beam radius of curvature is available anywhere along the beam path. Users can supply code to extend capabilities, and to enable scripting. The program is used worldwide by, consultants, laser companies, & govt. labs, often with multiple copies.