Amazon Web Services is a cloud platform with more than 165 fully-featured services. From startups to large enterprises to government agencies, AWS is used by millions of customers for powering their infrastructure at a lower cost. Amazon Redshift does the same for big data analytics and data warehousing.
It contains columnar data store with billions of rows of data that are parallel placed with each other. It is the fastest-growing service offered by the AWS. But what exactly is Amazon Redshift? On the fundamental level, it is a combination of two technologies – Column-oriented technologies (columnar data store) and MPP (massively parallel processing).
This type of database management system uses sections of columns instead of rows to store the data. This is mainly used in big data, analytics, and data warehouse applications. Other benefits of reducing a column-oriented database are that the need for joins is reduced and queries are resolved quickly.
When it comes to row-oriented databases, performing operations is not that efficient. Columnar databases flip the dataset which makes it easy to perform operations. Amazon Redshift is an affordable, fast, and easy way to get your operation up and running.
This means that a large number of computers or processors are performing computations simultaneously in a parallel fashion. Along with AWS and EC2, Amazon Redshift involves deploying a cluster. Deploying a singer server or node is not possible in RedShift. The cluster has a leader followed by nodes. Depending on the sort key you have specified for the table, the data will be spread across the cluster optimizing its ability to solve queries.
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This is a data warehouse service that uses MPP and column-orientation to perform operations of data warehouses, ELT, big data, and analytics. It is a linearly scalable database system that can run easily, quickly, and cheaply. You can start working with a couple of hundred gigabytes of data and move on to petabytes. This helps you in acquiring insights for your organization.
If you haven’t used Amazon Redshift before, you must try the following guides and books:
AWS Command Line Interface or Amazon Redshift console can be used for managing clusters in an interactive way. If you want to programmatically manage clusters, you can use the AWS Software Development Kit or the Amazon Redshift Query API.
Amazon Redshift was made to handle database migrations and large scale datasets. It is based on PostgreSQL 8.0.2’s older version. In November 2012, a preview beta was released. Three months later, on 15th February 2013, a full release of Redshift was made. Redshift has more than 6,5000 deployments which make it the biggest cloud data warehouse deployments.
In the APN Partner program of Amazon, it has listed a number of proprietors and tested their tools like Actuate Corporation, Qlik, Looker, Logi Analytics, IBM Cognos, InetSoft, Actian, etc.
Using Amazon Redshift over traditional data warehouses will offer you the following benefits:
Every value used in the Amazon Redshift has a data type with a certain set of properties. It also can constrain the values the given argument or column can contain. You need to declare the data type while creating the table. The following data types are used in Amazon Redshift tables:
|SMALLINT||INT2||Signed two-byte integer|
|INTEGER||INT, INT4||Signed four-byte integer|
|BIGINT||INT8||Signed eight-byte integer|
|DECIMAL||NUMERIC||Exact numeric of selectable precision|
|REAL||FLOAT4||Single precision floating-point number|
|DOUBLE PRECISION||FLOAT8, FLOAT||Double precision floating-point number|
|BOOLEAN||BOOL||Logical Boolean (true/false)|
|CHAR||CHARACTER, NCHAR, BPCHAR||Fixed-length character string|
|VARCHAR||CHARACTER VARYING, NVARCHAR, TEXT||Variable-length character string with a user-defined limit|
|DATE||Calendar date (year, month, day)|
|TIMESTAMP||TIMESTAMP WITHOUT TIME ZONE||Date and time (without time zone)|
|TIMESTAMPTZ||TIMESTAMP WITH TIME ZONE||Date and time (with time zone)|
The following steps will help you in setting up a Redshift instance, loading data, and running basic queries on the dataset.
To get started with Amazon Redshift, you need to have the following prerequisites:
Your cluster needs to have permission to access the data and the resources. The AWS Identity and Access Management (IAM) is used to provide permissions. To do this, you can either provided the IAM user’s AWS access key or through an IAM role which is attached to the cluster. Creating an IAM role will safeguard your access credential for the AWS and protect your sensitive data. Here are the steps you need to follow:
Before you launch the cluster, remember that it is live and a standard usage fee will be charged to you until you delete the cluster. Here is what you need to do for launching an Amazon Redshift Cluster:
This creates a default database with the name dev from the Quick Launch.
Configuring a security group for authorizing access is required before connecting the cluster. Follow the below-mentioned steps if you used the EC2-VPC platform for launching the cluster:
For using the Amazon Redshift cluster as a host for querying databases, you have the following two options:
1. Using the Query Editor
You need permission for accessing the Query editor. For enabling access, you need to attach the AWS IAM user you use for accessing the cluster to the AmazonRedshiftReadOnlyAccess and AmazonRedshiftQueryEditor policies for IAM. Here is how you can do that:
For using the Query editor you need to perform the following tasks:
2. Using a SQL Client
Using the SQL client to connect cluster includes the following steps:
Right now you are connected to a database named dev. After this comes creating tables, uploading data to these tables and trying a query. Here are the steps you need to follow:
Study the Amazon Redshift database developer guide to get information regarding the syntax required for creating table statements.
For loading the data, you can either provide key-based or role-based authentication.
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