Configuring Drill

Drill is highly configurable. This document focuses on MapR-related configurations and refers to the open source Apache Drill documentation for generic information. Key things to configure are:

• Drill memory Determine the amount of direct memory allocated to a Drillbit for query processing in a Drill cluster
• Resources for a shared Drillbit Configure queues and parallelization for supporting multiple users sharing a Drillbit. Support separate Drillbits running on different nodes in the cluster.
• Multitenancy
• User impersonation
• User authentication
• Drill impersonation with Hive authorization
• Volumes to use for spooling Use the drill.exec.sort.external.spill.directories option to set MapReduce volumes or local volumes for spooling to improve performance and stripe data across as many disks as possible.
• Persistent configuration storage
• Access rights

Drill typically runs along side other workloads, including the following:

• MapReduce
• Yarn
• HBase
• Hive and Pig
• Spark

You need to plan and configure these resources for use with Drill and other workloads:

• Memory
• CPU
• Disk

Configuring Access Rights

If the security in your organization limits access to MapR-DB/HBase tables, you might experience a problem querying the tables. If you have 777 file-level permissions to a table, yet a query returns no results, you might need to add your user name to the maprcli access list (ACL).