What is a distributed cache in Hadoop?

In Hadoop, a distributed cache refers to a mechanism that allows the sharing and distribution of small, read-only files or archives (such as JAR files, scripts, or configuration files) across all nodes in a Hadoop cluster. The purpose of the distributed cache is to make these files available to all nodes in the cluster during the execution of a MapReduce job or a Hadoop job.

The primary use case for the distributed cache is to distribute files or resources that are needed by the tasks running on individual nodes of the cluster. Instead of having each node independently access a centralized file system to fetch these resources, the distributed cache ensures that the necessary files are copied to each node's local file system, making them readily accessible for processing.

Here are the key points related to the distributed cache in Hadoop:

1. Small, Read-Only Files:

   • The distributed cache is designed for distributing relatively small files that are read-only. Examples include configuration files, lookup tables, or external libraries required for the MapReduce job.

2. Efficient Data Access:

   • By distributing these files to every node in the cluster, Hadoop ensures efficient access to the required resources during the execution of MapReduce tasks. This reduces the need for repetitive data transfer over the network.

3. Files are Cached Locally:

   • The distributed cache copies the files to each task's local file system on the node where the task is running. This local caching enhances data locality, as tasks can access the required files without network overhead.

4. Accessing Distributed Cache in MapReduce:

   • In a MapReduce job, you can specify files to be added to the distributed cache using the DistributedCache API. The files are then accessible in the setup() method of the mapper and reducer classes.
   java

   // Adding a file to the distributed cache DistributedCache.addCacheFile(new URI("hdfs://path/to/your/file"), job.getConfiguration());
   • The added files can be accessed in the setup() method using DistributedCache.getLocalCacheFiles().
   java

   // Accessing the distributed cache files in the setup method Path[] cacheFiles = DistributedCache.getLocalCacheFiles(job.getConfiguration());

5. Hadoop Streaming and Distributed Cache:

   • In Hadoop Streaming, a feature that allows the use of non-Java programs as mappers or reducers, the distributed cache is commonly used to distribute scripts, executables, or other auxiliary files needed by the streaming tasks.

The distributed cache is a valuable feature in Hadoop as it contributes to the efficiency and performance of MapReduce jobs by reducing data transfer overhead and ensuring that required files are readily available on each node in the cluster during job execution.