ColumnStore Minimum Hardware Specification

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The following table outlines the minimum recommended production server specifications which can be followed for both on premise and cloud deployments:

Single server

ItemDescription
Physical Server4 core Intel / AMD, 32GB Memory
StorageLocal disk with appropriate RAID redundancy or network attached storage

Multi server

ItemDescription
UM Physical Server4 core Intel / AMD, 32GB Memory
PM Physical Server4 core Intel / AMD, 16GB Memory
StorageLocal disk on each PM can be appropriate for systems that can tolerate some down time in the event of server failure. To leverage the automated fail-over capabilities, a networked storage layer such as SAN for on premise or EBS in AWS is a better choice. A distributed filesystem such as the open source GlusterFS will also allow for node fail-over.
Network InterconnectIn a multi server deployment data will be passed around via TCP/IP networking. At least a 1G network is recommended.

Details

These are minimum recommendations and in general the system will perform better with more hardware:

  • More CPU cores and servers will improve query processing response time.
  • More memory will allow the system to cache more data blocks in memory.
  • Faster network will allow data to flow faster between UM and PM nodes.
  • SSD's may be used, however the system is optimized towards block streaming which may perform well enough with HDD's for lower cost.
  • Where it is an option, it is recommended to use bare metal servers for additional performance since ColumnStore will fully consume CPU cores and memory.
  • In general it makes more sense to use a higher core count / higher memory server for single server or 2 server combined deployments.
  • In a deployment with multiple UM nodes the system will round robin requests from the mysqld handling the query to any ExeMgr in the cluster for load balancing. A higher bandwidth network such as 10g or 40g will be of benefit for large result set queries.

For AWS our own internal testing generally uses m4.4xlarge instance types as a cost effective middle ground. The R4.8xlarge has also been tested and performs about twice as fast for about twice the price.

For development purposes, the system will run on typical laptop / desktop hardware down to single core, 4gb memory.

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