Learn Apache Flink :Flink is a Apache Spark Competitor

Course details

Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities.

Features

• A streaming-first runtime that supports both batch processing and data streaming programs

• Elegant and fluent APIs in Java and Scala

• A runtime that supports very high throughput and low event latency at the same time

• Support for event time and out-of-order processing in the DataStream API, based on the Dataflow Model

• Flexible windowing (time, count, sessions, custom triggers) accross different time semantics (event time, processing time)

• Fault-tolerance with exactly-once processing guarantees

• Natural back-pressure in streaming programs

• Libraries for Graph processing (batch), Machine Learning (batch), and Complex Event Processing (streaming)

• Built-in support for iterative programs (BSP) in the DataSet (batch) API

• Custom memory management for efficient and robust switching between in-memory and out-of-core data processing algorithms

• Compatibility layers for Apache Hadoop MapReduce and Apache Storm

• Integration with YARN, HDFS, HBase, and other components of the Apache Hadoop ecosystem