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Introduction to Redshift Cluster

Redshift cluster is used to handle a large amount of data, we can create up to 128 node clusters in redshift. Basically, compute node and leader node are the main components available, compute node has its own dedicated CPU, memory and storage device we can execute the query using compute node we can create multiple nodes in a single cluster. The leader node manages the communication between the client application and computes node. Leader node first compiles the code after compiling it will distribute the code to the compute nodes, and then assign data to each node.

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Syntax

Given below is the syntax mentioned:

1. Create redshift cluster

Amazon configuration

Database configurations

Cluster permissions settings

Provide IAM role name

Advanced network and security configuration

Advanced database configurations

Maintenance.

Backup of cluster

Create cluster

2. Delete redshift cluster

3. Modify

4. Reboot

How Cluster Work in Redshift?

We can create a single as well as a multinode cluster in redshift. Basically, it contains a node. Every redshift cluster contains the leader and computes nodes. At the time of launching, we need to specify the options like node type, the node type which specifies the RAM, CPU and storage capacity of the clusters. On the basis of the node type, the cost is defined.

Following are the node type available in redshift:

RA3 node contains the following node types:

ra3.xlplus: It will contain the 4 virtual CPU, 32 GB RAM, 32 TB storage space and 2-16 node range.

ra3.4xlarge: It will contain the 12 virtual CPU, 96 GB RAM, 128 TB storage space and 2-32 node range.

ra3.16xlarge: It will contain the 48 virtual CPU, 384 GB RAM, 128 TB storage space and 2-128 node range.

Dense node contains the following node types:

ds2.xlarge: It will contain the 4 virtual CPU, 31 GB RAM, 2 TB storage space and 2-32 node range.

ds2.xlarge: It will contain the 36 virtual CPU, 244 GB RAM, 16 TB storage space and 2-128 node range.

Dense compute node contains the following node types:

dc2.large: It will contain the 2 virtual CPU, 15 GB RAM, 160 GB storage space and 1-32 node range.

dc2.xlarge: It will contain the 32 virtual CPU, 244 GB RAM, 2.56 TB storage space and 2-128 node range.

dc1.large: It will contain the 2 virtual CPU, 15 GB RAM, 160 GB storage space and 1-32 node range.

ds1.8xlarge: It will contain the 32 virtual CPU, 244 GB RAM, 2.56 TB storage space and 2-128 node range.

Below are the main parameters which were used at the time of cluster management.

Analyze threshold percent

Json configuration

Statement timeout

Search path

Require SSL

Query group

Extra float digits

Enable user activity logging

Examples of Redshift Cluster

Given below are the examples mentioned:

Example #1

a. First we have configured the cluster information.

Nodes: 2

Output:

b. Configuring sample data for the cluster.

Sample data: Yes

Output:

c. In database configuration we need to provide the user name and password.

Admin user password: ***********

Output:

d. Configuring the cluster permission.

Available IAM roles: AWSServiceRoleForRedshift

Output:

e. Configuring the network and security option.

Publicly accessible: disable

Output:

f. Configuring database details.

Encryption: disabled

Output:

g. Configuring the maintenance window for the cluster.

Output:

h. Configuring the backup.

Cluster relocation: no

Output:

i. Create redshift cluster

Example #2

In the below example, we are rebooting the name as amazon-redshift-cluster.

Output:

Example #3

In the below example, we have to delete the name as amazon-redshift-cluster.

Output:

Conclusion

It is useful to execute the query faster. Leader and compute nodes are the two components available. After creating amazon we can optimize, resize and reboot and delete the cluster. We can create it using 2-128 node.