DataStream API for Apache Flink

Apache Flink DataStream API – Common Operations

The DataStream API in Apache Flink provides a rich set of operations that allow you to process data in real-time with flexibility and power. Below are some of the commonly used methods in this API, along with simple descriptions.

• map(Function)

    Transforms each element by applying a function and produces one result per input. Used for simple conversions or calculations.

• flatMap(Function)

    Similar to map, but can return zero, one, or many results per input element. Useful for splitting or filtering data.

• filter(Function)

    Filters out elements that don’t satisfy a given condition. Only elements that return true are kept.

• keyBy(KeySelector)

    Partitions the stream into keyed streams based on a selected key. Essential for grouped transformations like reduce and windowing.

• reduce(Function)

    Combines elements in a keyed stream using a reduce function, continuously emitting aggregated results.

• join(DataStream)

    Joins two streams on a key within a time window. Useful when combining information from different data sources.

• union(DataStream)

    Combines multiple data streams of the same type into a single stream. Useful for merging sources.

These operations form the building blocks for building powerful real-time applications in Flink. You can chain these methods to create complex and scalable data pipelines.

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