SingleStore Managed Service

Cluster Components
Key Components

The following components are fundamental to a SingleStore DB cluster. They are also key terms that are used throughout the documentation.

Cluster

A cluster encompasses all of the nodes that are included in a complete SingleStore DB installation. A cluster contains aggregator nodes and leaf nodes.

Node

A node is a server that has an installation of a SingleStore DB instance. See Node Requirements for SingleStore DB Commands to learn about the commands supported by different types of nodes.

Leaf

A leaf is a node that stores a subset of a cluster’s data. A cluster typically contains many leaves.

Partition

A partition contains a subset (a shard) of a database’s data. A leaf contains multiple partitions. When you run CREATE DATABASE, SingleStore DB splits the database into partitions, which are distributed evenly among available leaves. With CREATE DATABASE, you can specify the number of partitions with the PARTITIONS=X option. If you don’t specify the number of partitions explicitly, the default is used (the number of leaves times the value of the default_partitions_per_leaf engine variable.Engine Variables

Types of Tables

A distributed table’s data is distributed across partitions. By contrast, a reference table’s data is replicated, in full, to all nodes in a cluster.

A temporary table is distributed, but is not persisted.

Aggregator

An aggregator is a node that routes queries to the leaves, aggregates intermediate the results, and sends the results back to the client. There are two types of aggregators: master and child. A cluster contains exactly one master aggregator, a specialized aggregator responsible for cluster monitoring and failover. A cluster may also contain zero or more child aggregators (depending on query volume).

Aggregator to Leaf Ratio

The minimal setup for a SingleStore DB cluster is just one aggregator (the master aggregator) and one leaf. You can add more aggregators, which will read metadata from the master aggregator, and can run DML commands on the leaves.

The number of deployed aggregator and leaf nodes determines the storage size and performance of a cluster. Typical deployments have a 5:1 ratio of leaf:aggregator nodes. In a well-designed cluster:

  • Applications that require higher connection capabilities from application servers have a higher aggregator-to-leaf node ratio.

  • Applications with larger storage requirements have a higher leaf-to-aggregator node ratio.