Quickstart

Introduction

This guide explains how to set up the Snowflake emulator and use Snowflake CLI to interact with Snowflake resources running on your local machine. You’ll learn how to create a Snowflake database, schema, and table, upload data to a stage, and load data into the table. This quickstart is designed to help you get familiar with the Snowflake emulator and its capabilities.

Prerequisites

• LocalStack for Snowflake
• localstack CLI
• Snowflake CLI

LocalStack for Snowflake works with popular Snowflake integrations to run your SQL queries. This guide uses the Snowflake CLI, but you can also use SnowSQL, DBeaver or the LocalStack Web Application for this purpose.

Instructions

Before you begin, pull the Snowflake emulator image (localstack/snowflake) and start the container:

export LOCALSTACK_AUTH_TOKEN=<your_auth_token>
localstack start --stack snowflake

Check the emulator’s availability by running:

curl -d '{}' snowflake.localhost.localstack.cloud:4566/session

Output

{"success": true}

In this quickstart, we’ll create a student records database that demonstrates how to:

• Create databases, schemas, and tables
• Create stages and upload data using the PUT command
• Load data from CSV files into tables
• Query your data

Create database, schema & table

Create the Snowflake database named STUDENT_RECORDS_DEMO and use it:

CREATE DATABASE IF NOT EXISTS STUDENT_RECORDS_DEMO;
USE DATABASE STUDENT_RECORDS_DEMO;

The output should be:

+-----------------------------------------------------+
| status                                              |
|-----------------------------------------------------|
| Database STUDENT_RECORDS_DEMO successfully created. |
+-----------------------------------------------------+

Create a Snowflake schema named PUBLIC and use it:

CREATE SCHEMA IF NOT EXISTS PUBLIC;
USE SCHEMA PUBLIC;

The output should be:

+---------------------------------------------+
| result                                      |
|---------------------------------------------|
| public already exists, statement succeeded. |
+---------------------------------------------+

Last, create the table STUDENT_DATA in the database:

CREATE OR REPLACE TABLE STUDENT_DATA (
    student_id VARCHAR(50),
    first_name VARCHAR(100),
    last_name VARCHAR(100),
    email VARCHAR(200),
    enrollment_date DATE,
    gpa FLOAT,
    major VARCHAR(100)
);

The output should be:

+------------------------------------------+
| status                                   |
|------------------------------------------|
| Table STUDENT_DATA successfully created. |
+------------------------------------------+

Create file format & stage

Now, create a file format for CSV files:

CREATE OR REPLACE FILE FORMAT csv_format
    TYPE = CSV
    FIELD_DELIMITER = ','
    SKIP_HEADER = 1
    NULL_IF = ('NULL', 'null')
    EMPTY_FIELD_AS_NULL = TRUE;

The output should be:

+----------------------------------------------+
| status                                       |
|----------------------------------------------|
| File format CSV_FORMAT successfully created. |
+----------------------------------------------+

Create a stage for uploading files:

CREATE OR REPLACE STAGE student_data_stage
    FILE_FORMAT = csv_format;

The output should be:

+-----------------------------------------------------+
| ?COLUMN?                                            |
|-----------------------------------------------------|
| Stage area STUDENT_DATA_STAGE successfully created. |
+-----------------------------------------------------+

Upload and load sample data

Create a new file named student_data.csv with sample student records:

student_id,first_name,last_name,email,enrollment_date,gpa,major
S001,John,Smith,john.smith@university.edu,2023-08-15,3.75,Computer Science
S002,Alice,Johnson,alice.johnson@university.edu,2023-08-15,3.92,Mathematics
S003,Bob,Williams,bob.williams@university.edu,2022-08-15,3.45,Engineering
S004,Carol,Brown,carol.brown@university.edu,2024-01-10,3.88,Physics
S005,David,Davis,david.davis@university.edu,2023-08-15,2.95,Biology

Upload the CSV file to the stage using the PUT command:

PUT file://student_data.csv @student_data_stage AUTO_COMPRESS=TRUE;

Note

Adjust the file path to the location of your student_data.csv file.

The output should show the file upload status:

source          |target             |source_size|target_size|source_compression|target_compression|status  |message|
----------------+-------------------+-----------+-----------+------------------+------------------+--------+-------+
student_data.csv|student_data.csv.gz|        425|        262|NONE              |GZIP              |UPLOADED|       |

Now load the data from the stage into the table:

COPY INTO STUDENT_DATA
FROM @student_data_stage
ON_ERROR = 'CONTINUE';

Verify data loading

USE DATABASE STUDENT_RECORDS_DEMO;
USE SCHEMA PUBLIC;

SELECT COUNT(*) as total_students FROM STUDENT_DATA;

The output should be:

+----------------+
| TOTAL_STUDENTS |
|----------------|
| 5              |
+----------------+

Similarly, you can query the student details based on their GPA:

SELECT first_name, last_name, major, gpa
FROM STUDENT_DATA
WHERE gpa >= 3.8
ORDER BY gpa DESC;

The output should be:

FIRST_NAME|LAST_NAME|MAJOR      |GPA |
----------+---------+-----------+----+
Alice     |Johnson  |Mathematics|3.92|
Carol     |Brown    |Physics    |3.88|

Optionally, you can also query your Snowflake resources & data using the LocalStack Web Application, that provides a Worksheet tab to run your SQL queries.

Destroy the local infrastructure

To stop LocalStack and remove locally created resources, use:

localstack stop

LocalStack is ephemeral and doesn’t persist data across restarts. It runs inside a Docker container, and once it’s stopped, all locally created resources are automatically removed. To persist the state of your LocalStack for Snowflake instance, please check out our guide on State Management.

Next Steps

Now that you’ve completed the quickstart, here are some additional features you can explore:

• Load data from cloud storage: You can load data through our Storage Integrations (currently supporting AWS S3) or using a script (see Snowflake Drivers)
• Automate data ingestion: You can configure Snowpipe for automated data ingestion from external sources
• Use your favorite tools: You can continue to work with your favorite tools to develop on LocalStack for Snowflake locally, see Integrations

Further Reading

You can now explore the following resources to learn more about the Snowflake emulator:

• Features: Learn about the Snowflake emulator’s features and how to use them.
• Capabilities: Find information about the Snowflake emulator’s capabilities and how to use them.