Mapper is a software component used in data processing frameworks, such as Hadoop, to process and transform input data into intermediate key-value pairs. It performs the first stage of the MapReduce programming model, enabling distributed and parallel computation of large datasets across multiple nodes.
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About Mapper
Mapper was introduced as part of the Hadoop framework, which was created by Doug Cutting and Mike Cafarella in 2005. It was designed to address the need for processing large datasets across distributed systems efficiently. The concept of Mapper, along with the MapReduce model, originated from a paper published by Google in 2004, detailing their approach to handling vast amounts of data using parallel processing techniques.
Strengths of Mapper included efficient parallel processing, scalability, and fault tolerance. Weaknesses involved complexity in programming, high latency for small datasets, and resource-intensive operations. Competitors of Mapper included Apache Spark, Apache Flink, and Google Cloud Dataflow.
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How to hire a Mapper expert
A Mapper expert must have strong skills in Java or Python programming, proficiency in Hadoop ecosystem tools, experience with HDFS (Hadoop Distributed File System), knowledge of data processing and transformation techniques, and familiarity with distributed computing concepts.
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