Sizing Considerations

This section explains how to determine the necessary size of hardware resources (disk space and RAM) for your Exasol database.

The output of the hardware sizing calculations in this section are:

  • Required total disk space, which is the sum of the required database disk space and required backup disk space
  • Required database RAM

Factors that impact sizing

There are several factors that affect your sizing calculation for Exasol. These are the most common ones:

  • The expected volume of your raw data: The volume of your uncompressed data has the largest impact on the sizing estimation. The larger the data volume, the more storage space is required.
  • Performance: Performance depends mainly on the amount of RAM provided to the database. You may use the most common value (10 % of uncompressed data) or go for more precise values by calculating the amount of active data or using the values of Exasol system tables.
  • Cluster redundancy: Your planned redundancy for the cluster impacts the required storage space. If you are planning to have a redundancy of “2” – the same data is stored in two segments – the required storage space is doubled.
  • Number of reserve nodes: Reserve nodes are used in case of a node failure. Reserve nodes need to have the same hardware configuration as the active nodes in a cluster. For more information, see Fail Safety (Cloud).
  • Backup strategy: Certain backup strategies require more storage space. If you plan on storing backups in-cluster with a redundancy of “2”, then this must be taken into account in the sizing estimation. For more information, see Backup and Restore.
  • Operating system memory swap: Exasol recommends setting 10 % of total RAM as OS memory swap. If you specify that, you need to consider the total available physical RAM for your cluster and how much of it is going to be usable for the database after allocating RAM for OS memory swap.

Database disk space

The estimation for required database disk space includes the following:

  • Compressed data volume: The volume of data once it has been compressed.
  • Index volume: Indexes are automatically created and maintained by Exasol databases and require database disk space.
  • Statistical and auditing data volume: Statistical data volume is small. However, if you switch auditing on in the system, the required disk space increases because each login and each query is stored in the corresponding auditing tables.
  • Reserve space for fragmentation: The persistent volume can become fragmented to some degree. It is advisable to reserve additional disk space to avoid problems with insufficient disk space due to fragmentation.
  • Reserve space for temporary data: When intermediate results do not fit into the database RAM they are swapped out to a temporary volume, which causes significant performance deterioration. We therefore recommend that you reserve extra headroom for temporary DB RAM.

Database disk space calculation

Use the following equation to calculate the required database disk space:

[(compressed data volume + index volume + statistical and auditing data volume) * redundancy] + fragmentation + temp headroom volume

Example

In this example we have the following input data:

  • Compressed data (net): 1000 GiB
  • Indexes (15 % of compressed data): 150 GiB
  • Statistical and auditing data (5 % of compressed data): 50 GiB
  • Redundancy: 2
  • Headroom for temp and fragmentation (60% of compressed data without redundancy): 720 GiB

Which gives us this result:

Compressed data (net) Overall data volume (net) Overall data volume with redundancy Total DB disk space

1000 GiB

 

1200 GiB

1000 GiB (compressed data) + 200 GiB(indexes + statistical & auditing data)

2400 GiB

1200 GiB x 2

3200 GiB

2400 GiB (overall data volume with redundancy) + 720 GiB (60% of overall data volume)

Database RAM (DB RAM)

An Exasol database typically performs well with database RAM of 10 % of the raw (uncompressed) data volume. In addition to this basic assumption, there are additional variables that affect the estimation of the required DB RAM:

  • Index volume: Higher index volumes can negatively impact system performance and require more DB RAM.

  • Reserve space for temporary data: When intermediate results do not fit into the DB RAM they are swapped out to a temporary volume, which causes significant performance deterioration. We therefore recommend that you reserve extra headroom for temporary DB RAM.

  • User defined functions (UDFs): When processing large amounts of data using user-defined functions, the RAM required for those UDFs needs to be available on every node. The UDFs are executed in parallel, which means that there can be as many instances of a UDF per node as there are cores. Therefore, you have to consider the total amount of RAM that the UDF instances need for processing the queries. For example, if a query uses 500 MiB per UDF instance on a 72 core machine in an 8-node cluster, this requires an additional 282 GiB of DB RAM.

    You can also specify how many UDF instances are created within the UDF. For more information, see UDF Instance Limiting.

  • Additional software: Additional processes running on the nodes, such as monitoring services, may require that you reserve additional RAM headroom. In this case, refer to the respective software vendor’s documentation regarding RAM usage.

Database RAM calculation

Use the following equation to calculate the required database RAM:

MAX( compressed data volume * database RAM estimation %, index size * index scale factor ) + compressed data * temporary DB RAM headroom % + MAX_UDF_RAM * number-of-cores * number-of-nodes

If you have a running system, you can use the RECOMMENDED_DB_RAM_SIZE_* columns of the EXA_DB_SIZE_* statistical system tables to get a recommended database RAM size. For more information, see Statistical System Tables.

Example

In this example we have the following input data:

  • Index scale factor: 1.3
  • Temporary DB RAM headroom: 0.0

The resulting formula would then be:

MAX(1000GiB * 20%, 150GiB * 1.3) + 1000GiB * 0% = 200GiB

Which gives us this result:

Compressed data (net) Overall data volume Estimated required DB RAM

1000 GiB

1200 GiB

200 GiB

Choose EC2 Instance Type

Amazon EC2 instance types are named according to the following convention:

instance types

When choosing EC2 instance types for your Exasol deployments on AWS, use the following guidelines:

Instance family: Depending on your requirements, we recommend:

  • c for workloads that require high CPU performance
  • r for workloads that are data-heavy but compute-light
  • m for a balance between CPU and memory optimization

Instance generation: Use the latest available generation for the selected instance type.

Processor family: Use only a (AMD) or i (Intel) processors. AWS Graviton (ARM) processors are not supported.

  • Which processor architectures are available may differ depending on the instance generation.
  • A certain processor family be implicit for some instance types.

Additional capability: Always specify d (instance store volumes).

Exasol will not work if the “d” option is omitted.

Instance size: Choose instance sizes based on Sizing Considerations and the total RAM that will be used by all your instances.

See also:

For more information about EC2 instance types, refer to Instance types - Amazon Elastic Compute Cloud.