More memory is always good and it is recommended to purchase as much as the budget allows. Applications such as Impala and Cloudera Search are often configured to use large amounts of heap, and a mixed workload cluster supporting both services should have sufficient RAM to allow all required services.

It is critical to performance that the total memory allocated to all Hadoop-related processes (including processes such as HBase) is less than the total memory on the node, taking into account the operating system and non-Hadoop processes. Oversubscribing the memory on a system can lead to the Linux kernel’s out-of-memory process killer being invoked and important processes being terminated. Performance might be affected by over-allocation of memory to a Hadoop process, as this can lead to long Java garbage collection pauses. For processes such as HBase, you must factor in aspects such as off heap bucket cache configuration.

For optimum performance, confer with your hardware vendor for defining optimal memory configuration layout.

While 128 GB RAM can be accommodated, this typically constrains the amount of memory allocated to services such as YARN and Impala, thereby reducing the query capacity of the cluster. 256 GB RAM is recommended with higher values also possible.