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The Hadoop Developer exam evaluates individuals' proficiency in developing, implementing, and optimizing Apache Hadoop-based applications and data processing workflows. Hadoop developers are responsible for designing and coding MapReduce jobs, Hive queries, Pig scripts, and Spark applications to process and analyze large volumes of structured and unstructured data stored in Hadoop clusters. This exam assesses candidates' knowledge of Hadoop ecosystem components, programming languages, and development frameworks used in big data analytics.
The Hadoop Developer exam covers the following topics :-
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Yes, it demonstrates essential development skills sought in data engineering and analytics roles.
This exam is focused specifically on Hadoop development, not system administration.
Java is essential for MapReduce development, but knowledge of Python is useful for tools like Pig and Hive.
Basic familiarity is helpful, but the exam content starts from foundational concepts.
MapReduce is a programming model used to process large data sets in parallel across a Hadoop cluster.
Both are used for querying data, but Hive uses SQL-like syntax, while Pig uses a scripting language better suited for procedural data flows.
Oozie is a workflow scheduler that automates and manages Hadoop jobs in production.
Yes, especially for streaming and log data ingestion.
Sqoop is used to import/export data between Hadoop and traditional relational databases.
The exam evaluates practical knowledge through scenario-based and concept-driven questions.