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Hadoop > Learn Hadoop > What is a distributed cache in Hadoop?
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What is a distributed cache in Hadoop?

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A distributed cache in Hadoop is a mechanism to store and share data across nodes in a Hadoop cluster. It's a cache layer that sits between the application and the Hadoop Distributed File System (HDFS). Purpose: 1. _Improves performance_: Reduces data access latency and improves application performance...
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A distributed cache in Hadoop is a mechanism to store and share data across nodes in a Hadoop cluster. It's a cache layer that sits between the application and the Hadoop Distributed File System (HDFS). Purpose: 1. _Improves performance_: Reduces data access latency and improves application performance by storing frequently accessed data in memory. 2. _Enhances scalability_: Allows data to be shared across nodes, reducing data duplication and improving cluster utilization. Types of distributed caches in Hadoop: 1. _Hadoop Distributed Cache (HDC)_: A built-in cache mechanism that stores data in memory and on disk. 2. _Apache Ignite_: An in-memory computing platform that provides a distributed cache and other features. 3. _Apache Hazelcast_: An in-memory data grid that provides a distributed cache and other features. 4. _Redis_: An in-memory data store that can be used as a distributed cache. Key benefits: 1. _Faster data access_ 2. _Improved application performance_ 3. _Reduced data duplication_ 4. _Enhanced scalability_ 5. _Simplified data sharing_ Common use cases: 1. _Data preprocessing_ 2. _Machine learning_ 3. _Real-time analytics_ 4. _Data integration_ 5. _Application caching_ In summary, a distributed cache in Hadoop is a mechanism to store and share data across nodes, improving performance, scalability, and data sharing. read less
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A distributed cache in Hadoop stores files across nodes, making them available to MapReduce tasks for faster access.
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A distributed cache in Hadoop is a feature that allows nodes in a Hadoop cluster to access and cache files locally, improving the efficiency and performance of MapReduce jobs by reducing data transfer time across the cluster.
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