How to remove the File Format from the database in Snowflake

This recipe helps you remove the File Format from the database in Snowflake

Recipe Objective: How to remove the File Format from the database in Snowflake?

Snowflake is one of the few enterprise-ready cloud data warehouses that brings simplicity without sacrificing features. It automatically scales, both up and down, to get the right balance of performance vs. cost. Snowflake's claim to fame is that it separates computers from storage. This is significant because almost every other database, Redshift included, combines the two, meaning you must size for your largest workload and incur the cost that comes with it. In this scenario, we will learn how to create a database in Snowflake and how to a file format, list all the formats and remove the File Format From data base.

Learn How to Build a Data Pipeline in Snowflake

System requirements :

Step 1: Log in to the account

We need to log in to the snowflake account. Go to snowflake.com and then log in by providing your credentials. Follow the steps provided in the link above.

Step 2: Select Database

To select the database which you created earlier, we will use the "use" statement

Syntax of the statement:

Use database [database-name];

Example of the statement:

use database dezyre_test;

Step 3: Create File Format

Creates a named file format that describes a set of staged data to access or load into Snowflake tables.

Syntax of the statement:

CREATE [ OR REPLACE ] FILE FORMAT [ IF NOT EXISTS ] TYPE = { CSV | JSON | AVRO | ORC | PARQUET | XML } [ formatTypeOptions ] [ COMMENT = '' ]

Example of the statement:

create or replace file format my_csv_format type = csv field_delimiter = '|' skip_header = 1 null_if = ('NULL', 'null') empty_field_as_null = true compression = gzip;

The output of the above statement:

bigdata_1.jpg

Step 4: List the file formats

Here we are going to list all the file formats in the database.

Syntax of the statement:

SHOW FILE FORMATS [ LIKE '' ] [ IN { ACCOUNT | [ DATABASE ] | [ SCHEMA ] } ]

Example of the statement:

show file formats;

The output of the above statement:

bigdata_2.jpg

Step 5: Remove the file format

Here we are going to Remove or drop the specified file format from the current/specified schema as shown below.

Syntax of the statement:

DROP FILE FORMAT [ IF EXISTS ]

Example of the statement:

drop file format my_csv_format;

The output of the above statement:

bigdata_3.jpg

Conclusion

Here we learned to remove the File Format from the database in Snowflake.

What Users are saying..

profile image

Anand Kumpatla

Sr Data Scientist @ Doubleslash Software Solutions Pvt Ltd
linkedin profile url

ProjectPro is a unique platform and helps many people in the industry to solve real-life problems with a step-by-step walkthrough of projects. A platform with some fantastic resources to gain... Read More

Relevant Projects

Build a Spark Streaming Pipeline with Synapse and CosmosDB
In this Spark Streaming project, you will learn to build a robust and scalable spark streaming pipeline using Azure Synapse Analytics and Azure Cosmos DB and also gain expertise in window functions, joins, and logic apps for comprehensive real-time data analysis and processing.

PySpark Tutorial - Learn to use Apache Spark with Python
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

Python and MongoDB Project for Beginners with Source Code-Part 2
In this Python and MongoDB Project for Beginners, you will learn how to use Apache Sedona and perform advanced analysis on the Transportation dataset.

SQL Project for Data Analysis using Oracle Database-Part 3
In this SQL Project for Data Analysis, you will learn to efficiently write sub-queries and analyse data using various SQL functions and operators.

AWS CDK Project for Building Real-Time IoT Infrastructure
AWS CDK Project for Beginners to Build Real-Time IoT Infrastructure and migrate and analyze data to

PySpark Project to Learn Advanced DataFrame Concepts
In this PySpark Big Data Project, you will gain hands-on experience working with advanced functionalities of PySpark Dataframes and Performance Optimization.

Airline Dataset Analysis using PySpark GraphFrames in Python
In this PySpark project, you will perform airline dataset analysis using graphframes in Python to find structural motifs, the shortest route between cities, and rank airports with PageRank.

AWS Snowflake Data Pipeline Example using Kinesis and Airflow
Learn to build a Snowflake Data Pipeline starting from the EC2 logs to storage in Snowflake and S3 post-transformation and processing through Airflow DAGs

Graph Database Modelling using AWS Neptune and Gremlin
In this data analytics project, you will use AWS Neptune graph database and Gremlin query language to analyse various performance metrics of flights.

Hands-On Real Time PySpark Project for Beginners
In this PySpark project, you will learn about fundamental Spark architectural concepts like Spark Sessions, Transformation, Actions, and Optimization Techniques using PySpark