Last updated by: RichardWhellum, Last updated on: 09/05/2025

How to access data stored in dremio datawarehouse (for data analysts)

info

Document Creation: 21 September, 2024. Last Edited: 21 September, 2024. Authors: Kaleb.
Document Code: DRE2. Effective Date: 21 September, 2024. Expiry Date: 21 September, 2025.

Making a SQL request to dremio in jupyter

The first step in ensuring you have the correct packages installed. Required for this guide can be downloaded with this command.

pip install requests pandas

Then import these into your notebook.

import requests
import json
import pandas as pd

After that declare the api url exactly as below.

api_url = "http://10.137.0.149:5001/dremio_query"

Then declare the headers.

headers = {
    "Content-Type": "application/json"
}

Then the sql query you wish to query the database with.

sql_query = {
    "sql": "SELECT * FROM \"project-3\" \"extended_activities\" LIMIT 10;"
}

As of writing this documentation, users of this api are restricted to using only SELECT queries to prevent malicous use. There is also two usable sources being project-3 and project-2 though the tables within those sources are subject to change in which this documentation will likely be updated with a directory guide.

Then send the post request and store the response.

response = requests.post(api_url, headers=headers, data=json.dumps(sql_query))

Parse the JSON reponse.

result = response.json()

Finally convert it into data frame.

df = pd.DataFrame(result['rows'])

Which you can use just like any other dataframe like:

display(df)