Container represents a resource (memory) on a single node at a given cluster.
In yarn, we have containers similar to slots in Map Reduce. Each container will take care of the execution of a single entity like the MapReduce. In precise, a container executes a single unit of work. In MapReduce, a container can be said as a map or a reduce task.
In Hadoop 1.x a slot is allocated by the JobTracker to run each MapReduce task. Then the TaskTracker spawns a separate JVM for each task(unless JVM reuse is not enabled).
In Hadoop 2.x, Container is a place where a unit of work is executed. For instance, each MapReduce task(not the entire job) runs in one container.
An application/job will run on one or more containers.
Set of system resources are allocated for each container, currently, CPU core and RAM are supported. Each node in a Hadoop cluster can run several containers.
If you want to know more about Yarn, refer to the following video tutorial:
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