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1. MASSIVE.JS DB QUERY RETURNING NO RESULTS TESTED IN SQL TABS INSTALL
2. MASSIVE.JS DB QUERY RETURNING NO RESULTS TESTED IN SQL TABS DRIVER

Whenever someone connects to PostgreSQL using psycopg2 python driver, they create a connection object followed by a cursor object.

PostgreSQL supports two types of database cursors: app/requirements.txt psycopg2-binary=2.8.6 So let us add it as a requirement to our project.

MASSIVE.JS DB QUERY RETURNING NO RESULTS TESTED IN SQL TABS INSTALL

We need to install psycopg2-binary as a requirement. It starts the PostgreSQL database container and creates a database called `dvdrental.` Now, we can restore data from the backup file by entering into the database container like this: $ docker-compose exec db /bin/bash # You are in container now pg_restore -U postgres -d dvdrental /tmp/dvdrental.tar d option starts the docker container as a daemon. For that, run the docker-compose up command from your favourite terminal or shell. Now, let us start the database and restore the DVD rental data.

MASSIVE.JS DB QUERY RETURNING NO RESULTS TESTED IN SQL TABS DRIVER

In this article, we use PostgreSQL, Psycopg2 driver to illustrate the different capabilities of cursors. Simply put, It will enable a developer to design a solution that can work with vast amounts of data without any problem. There is much more a cursor can do apart from merely holding data from a SQL query result.Ī cursor can also paginate the results from a SQL query, allow moving forward and backward across rows etc. People who worked with PostgreSQL and Python might have already worked with an object called `cursor` in their code. Now coming to the second way, we can use database cursors. It is thereby discouraged to go in the direction of increasing memory whenever your application crashes due to memory limits. There could be possible under-utilization of resources. Suppose you pre-allocate huge memory for your application anticipating vast amounts of data in future.No guarantee increasing memory can future-proof your solution.I hope the first way is not so attractive because of two reasons: Use database cursors to throttle data to manageable limits.Set the memory of application high(thereby goes the costs up).There are generally two ways an application can handle vast amounts of SQL query results: As a developer, you should know cursors well to optimize your application.īefore you immerse into the article, if you are new to programming or want to learn Python in-person, please checkout: What if the application’s memory (ECS task, EC2 instance or a VM) cannot hold that million records SQL response and crashes the entire application? To your surprise, at the end of this article, you’ll know the solution. Ex: Fetch data of a million records for processing into your application. Have you ever wondered why database cursors even exist? I bet there will be instances where a developer wants to load massive SQL query response data in their application.