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Database partitioning is a technique that breaks down large tables into smaller tables called partition and allows clients to hit fewer partitions, therefore, minimizes the search space and optimizes the queries as a result.
In this class, we will explain Database Partitioning in detail, the different types of partitioning, its pros and cons and finally we will do a demo using PostgreSQL which will be your project for this class.
In this project, you will spin up a new PostgreSQL database instance on Docker, insert millions of rows in the table, measure the performance of a query. Then partition the table into many partitions and attempt the query again.
You can use the one-million-pg.txt as a guide for the commands you need to complete this project.
Step 1 – Prepare Database and Large Table
Spin up Postgres Instance on Docker, Create Table and Insert millions of rows and index
Step 2 – Execute multiple queries on the Table
Execute multiple queries to see the performance on the large table
Step 3 – Create and Attach Partitioned Tables
Create several tables that will eventually become attached partitions.
Step 4 – Populate Partitions
Copy the rows from the original table to the partitions
Step 5 – Query the partitions and compare the size
Compare the performance and data size on each partition
Classbaze Grade®
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Popularity
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