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Productionalizing Spark Streaming Applications
Taking your Big Data Spark Streaming job out of the Test Environment and getting it ready for prime-time in Production.
The Apache Spark project has become an essential tool in a Big Data Engineers toolkit. It includes many capabilities ranging from a highly performant Batch processing engine to a near-real-time Streaming Engine.
Spark Streaming
At Clairvoyant, we’ve been working with clients who are interested in building Highly Performant Real-time Big Data systems for their business. Many use cases have come up including Alert Engines, Processing IoT Data, and much more. We’ve dabbled in several types of technologies including Apache Nifi, Apache Flume, Apache Flink, and more. But one of our favorite technologies to use is Spark Streaming.
Spark Streaming is an extension to Core Apache Spark that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Source data streams can be any of the following as described in the below image and more.
