Category: Spark Streaming

Data streaming with Arka runtime APIs

The Arka runtime is Megh’s data streaming framework. Arka enables applications to build custom data pipelines spanning multiple devices and accelerators. Low-level details are abstracted away by Arka’s resource manager, which maps an application’s pipeline request to the pool of available hardware. This technology enables low-latency, low-overhead data streaming over complex functional topologies through Arka’s

Read More »

Implementing a CPU-based real-time video analytics pipeline

With growth in available data and computation power, use of video analytics solutions has been growing visibly. Most real-time video analytics use-cases, however, require response times in milliseconds—a level of performance that both CPUs and GPUs cannot always meet when it comes to inference. Here we discuss implementation of a real-time video analytics pipeline on

Read More »

Implementing a real-time, deep learning pipeline with Spark Streaming

With the current information age defining the third wave, we are facing an explosion of real-time data, which is in turn increasing demand for real-time analytics. A real-time analytics solution pipeline typically utilizes a streaming library and an analytics platform. Apache Spark is an open-source, distributed computing platform designed to run analytics payloads on a

Read More »

Categories

Categories