Introduction to Redshift table size
Redshift provides the different types of functionality to the user, in which that table size is one of the functions that are provided by Redshift. Basically, Redshift table size is used to get all the basic information about a user-defined table that is the size of the table as per user requirement. In another word, we can say that it only works on the user-defined table, not for system-generated tables. By using the table size command, we can list all tables from a specified database with their size as well as it also shows the smallest size and largest size table that is automatically ordered from largest to smallest tables.
select “name of table”, size of table, number of rows from each table from svv_table_info;
In the above syntax, we use a select statement to display the size of the table with different parameters as follows.
name of table: name of table means actual table name that is created by the user, basically we can consider it as a column name.
size of table: size of table is a column, basically it is used to store the size of a user-defined table.
number of rows from each table: number of rows column is used to display the total number of rows from each user-defined table.
svv_table_info: svv_table_info is used to show the summary of the tables from the database, basically it is a filter.
How to get table size in Redshift?
Now let’s see how we can get the size of the table in Redshift as follows. Before table size, we must know what is a database and what is table as follows.
Basically, database understanding is the fundamental and significant advance that will set up your data set plan on a strong establishment. In light of your database understanding, you can use numerous conditions for your potential benefit just as having the option to settle on educated choices and a reasonable execution vision. The database assists you with setting power over different boundaries, including your normal database stockpiling and even how well questions perform. Set aside an effort to completely comprehend your database and the current connections before you go on to building your inquiries.
Preceding making your data set, you need to set up your Amazon redshift’s bunch and guarantee that everything is going and all around associated with your SQL customer apparatus. A solitary bunch can have numerous database bases.
After creating the database, we can create the multiple tables inside the single database. Basically, we can create the table as per user requirement that means what is the column we require, what is the size of that table etc. A table is an assortment of related information held in a table configuration inside a data set. It comprises segments and lines.
Basically, the table contains a combination of different columns and rows, and users can create a table with different types of constraints such as primary key, foreign key, etc. as per their requirements. When we create a table at that time it allocates some space on cloud or local systems with respect to number columns and number rows.
In straightforward Amazon, Redshift provides the different utilities to show the size of the table. This content looks (and, indeed, is) somewhat intricate, yet fundamentally it tends to be executed to rapidly return a rundown of all the client tables in the framework, alongside different data about each table. The vital section for our motivations is Mbytes, which shows the all outsize, in megabytes, of that specific table.
Shows synopsis data for tables in the data set. The view channels framework tables and shows just client characterized tables. We can utilize the SVV_TABLE_INFO view to analyze and address table plans that can impact inquiry execution, incorporating issues with pressure encoding, circulation keys, sort style, information conveyance slant, table size, and insights. The SVV_TABLE_INFO see doesn’t return any data for void tables.
Now let’s see different examples of table size for better understanding in Redshift as follows. Before executing the table size command, we must create the table by using the following command as follows.
create table product(
product_id int not null,
product_name varchar(255) not null,
product_cost decimal(15,2) not null,
primary key (product_id));
In the above example, we use create table statement to create the index during table creation as shown, in this example; we created a product table with different attributes with different data types as shown. Here we add the primary key on the product_id column name as shown. The final output or we can say the final result of the above statement we can illustrate by using the following screenshot as follows.
Now let’s execute the table size command as follows.
select “table”, encoded, size, tbl_rows from svv_table_info;
In the above example, we use svv_table_info to display the size of the table as per user requirements. In this example, we use a select clause with different parameters as follows.
table: basically it is a column name that contains all names of the user-defined
encoded: It is also a column name and it is used to show whether the particular table is encoded or not.
Size: it used to show the size of the table.
tbl_rows: it is used to show many rows present inside the table.
The final output or we can say that result of the above statement we can illustrate by using the following screenshot as follows.
Here we created only a single table but you can create multiple tables and apply different parameters with table size commands such as diststyle, sortley1, etc.
We hope from this article you learn more about the Redshift table size. From the above article, we have learned the basic concept as well as the syntax of the Redshift table size and we also see the different examples of the Redshift table size. From this article, we learned how and when we use the Redshift table size.
This is a guide to Redshift table size. Here we discuss the basic concept as well as the syntax of the Redshift table size and we also see the different examples. You may also have a look at the following articles to learn more –