https://DevOpsCloud.io -- Cloud Monk Losang Jinpa, Ph.D., MCSE/MCT, GitOps DevOps Engineer

Map

Return to Golang map, CPP <map>, direct mapped, Mapped, Mapper, Mapping, map Function, Functions-Methods, Standard Libraries

The map function is a key operation in distributed data processing frameworks such as MapReduce and Apache Spark. Introduced by Google in 2004, map enables the parallel processing of data by applying a specified function to each item in a dataset independently. In the MapReduce model, the map function takes an input dataset and transforms it into key-value pairs, which are then fed into the reduce step for further aggregation. This approach allows for large-scale data processing by breaking down tasks into smaller, more manageable operations that can be executed in parallel across multiple nodes in a distributed system.

https://en.wikipedia.org/wiki/MapReduce

The map function is particularly useful for processing large datasets, such as those involved in big data analytics. It is often used to perform operations like filtering, transformation, or extracting features from raw data. For example, in a word count program, the map function would take an input string and output pairs of the form (“word”, 1), where each word is counted separately. This allows for data to be processed in parallel, with each node handling a subset of the input. By using map in distributed systems, organizations can efficiently scale their data processing workflows without sacrificing performance or fault tolerance.

https://en.wikipedia.org/wiki/MapReduce#Map_function

In Apache Spark, the map function is not only used for MapReduce-style batch processing, but also in real-time stream processing and machine learning tasks. Spark extends the concept of map to support more flexible data manipulations, allowing users to perform complex transformations and aggregations using its RDD (Resilient Distributed Datasets) abstraction. Unlike MapReduce, which writes intermediate data to disk, Spark processes data in-memory, resulting in faster execution times. The map function is a foundational concept in both batch and real-time distributed computing, enabling more efficient and scalable data workflows.

https://spark.apache.org/docs/latest/rdd-programming-guide.html#transformations

Snippet from Wikipedia: Map: A map is a symbolic depiction of interrelationships, commonly spatial, between things within a space. A map may be annotated with text and graphics. Like any graphic, a map may be fixed to paper or other durable media, or may be displayed on a transitory medium such as a computer screen. Some maps change interactively. Although maps are commonly used to depict geographic elements, they may represent any space, real or fictional. The subject being mapped may be two-dimensional such as Earth's surface, three-dimensional such as Earth's interior, or from an abstract space of any dimension.
Maps of geographic territory have a very long tradition and have existed from ancient times. The word "map" comes from the medieval Latin: Mappa mundi, wherein mappa meant 'napkin' or 'cloth' and mundi 'of the world'. Thus, "map" became a shortened term referring to a flat representation of Earth's surface.

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