Storm Kafka Training Mumbai- Learn from Experts!
Strom Kafka Training in Mumbai with Big Data Analytics
storm and kafka
An oil refinery takes crude oil, distills it, processes it and refines it into useful finished products such as the gas that we buy at the pump. We can think of Storm with Kafka as a similar refinery, but data is the input. A real-time data refinery converts raw streaming data into finished data products, enabling new use cases and innovative business models for the modern enterprise. Storm Kafka Training Mumbai.
Apache Storm is a distributed real-time computation engine that reliably processes unbounded streams of data. While Storm processes stream data at scale, Apache Kafka processes messages at scale. Kafka is a distributed pub-sub real-time messaging system that provides strong durability and fault tolerance guarantees.
Storm and Kafka naturally complement each other, and their powerful cooperation enables real-time streaming analytics for fast-moving big data. HDP 2.2 contains the results of Hortonworks’ continuing focus on making the Storm-Kafka union even more powerful for stream processing.
Apache Storm and Kafka has been to make it easier for developers to ingest and publish data streams from Storm topologies. The first topology ingests raw data streams from Kafka and fans out to HDFS, which serves as persistent store for raw events. Next, a filter Bolt emits the enriched event to a downstream Kafka Bolt that publishes it to a Kafka Topic. As events flow through these stages, the system can keep track of data lineage that allows drill-down from aggregated events to its constituents and can be used for forensic analysis. In a multi-stage pipeline architecture, providing right cluster resources to most intense part of the data processing stages is very critical, an “Isolation Scheduler” in Storm provides the ability to easily and safely share a cluster among many topologies.
In summary, refinery style data processing architecture enables you to:
Incrementally add more topologies/use cases
Tap into raw or refined data streams at any stage of the processing
Modularize your key cluster resources to most intense processing phase of the pipeline
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