mongo-hadoop
A library enabling MongoDB to serve as input source or output destination for Hadoop MapReduce tasks and ecosystem tools.
What is mongo-hadoop?
MongoDB Connector for Hadoop is a library that enables MongoDB to function as an input source or output destination for Hadoop MapReduce tasks and other Hadoop ecosystem tools. It allows data stored in MongoDB or its BSON backup files to be processed using distributed computing frameworks like Spark, Pig, Hive, and Flume. The connector solves the problem of integrating NoSQL document data with big data processing pipelines without extensive data transformation.
Data engineers and developers working with Hadoop ecosystems who need to process MongoDB data in distributed computing workflows. It's particularly useful for teams using both MongoDB for operational data and Hadoop for analytical processing.
Developers choose this connector because it provides native integration between MongoDB and Hadoop tools, supports flexible data sourcing from various MongoDB deployments, and enables query-based filtering for efficient data processing. Its ability to work with BSON backup files on cloud storage like S3 adds deployment flexibility.
Overview
MongoDB Connector for Hadoop
Use Cases
Best For
- Processing MongoDB data with Hadoop MapReduce jobs
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