Credit usage monitoring in Snowflake - Mini Project: Build & Apply

Credit usage monitoring

📖 Scenario: You work as a data engineer managing Snowflake cloud data warehouse resources. Your team wants to monitor credit usage by different warehouses to control costs.Snowflake charges credits based on warehouse usage. Monitoring credit consumption helps avoid surprises in billing.

🎯 Goal: Build a simple Snowflake SQL script that queries credit usage per warehouse, filters by a threshold, and displays the results.This will help your team quickly see which warehouses are using the most credits.

📋 What You'll Learn

Create a table variable with sample warehouse credit usage data

Add a threshold variable to filter warehouses by minimum credits used

Write a query to select warehouses exceeding the threshold

Display the filtered results

💡 Why This Matters

🌍 Real World

Monitoring credit usage in Snowflake helps control cloud costs and optimize resource allocation.

💼 Career

Data engineers and DevOps professionals use such queries to build cost monitoring dashboards and alerts.

1

Create sample warehouse credit usage data

Create a table variable called warehouse_usage with columns warehouse_name (string) and credits_used (number). Insert these exact rows: ('WH_A', 120), ('WH_B', 80), ('WH_C', 200).

Snowflake

-- Create table variable warehouse_usage with sample data
-- Your code here

Hint

Use a CTE (WITH clause) to create warehouse_usage with the exact rows.

2

Add a credit usage threshold variable

Create a variable called credit_threshold and set it to 100 to filter warehouses with credits used above this value.

Snowflake

WITH warehouse_usage AS (
  SELECT 'WH_A' AS warehouse_name, 120 AS credits_used
  UNION ALL
  SELECT 'WH_B', 80
  UNION ALL
  SELECT 'WH_C', 200
)

-- Set credit_threshold variable to 100
-- Your code here

Hint

Use a CTE named credit_threshold with a single column value set to 100.

3

Select warehouses exceeding the credit threshold

Write a SELECT query joining warehouse_usage and credit_threshold to return warehouse_name and credits_used where credits_used is greater than credit_threshold.value.

Snowflake

WITH warehouse_usage AS (
  SELECT 'WH_A' AS warehouse_name, 120 AS credits_used
  UNION ALL
  SELECT 'WH_B', 80
  UNION ALL
  SELECT 'WH_C', 200
),
credit_threshold AS (
  SELECT 100 AS value
)

-- Select warehouses with credits_used > credit_threshold.value
-- Your code here

Hint

Use a simple join in the FROM clause and filter with WHERE.

4

Display the filtered credit usage results

Run the full query to display the warehouses with credits used above the threshold. The output should show warehouse_name and credits_used columns.

Snowflake

WITH warehouse_usage AS (
  SELECT 'WH_A' AS warehouse_name, 120 AS credits_used
  UNION ALL
  SELECT 'WH_B', 80
  UNION ALL
  SELECT 'WH_C', 200
),
credit_threshold AS (
  SELECT 100 AS value
)
SELECT warehouse_name, credits_used
FROM warehouse_usage, credit_threshold
WHERE credits_used > credit_threshold.value

-- Run the query to display results
-- Your code here

Hint

Run the query as is. The output should list warehouses WH_A and WH_C with their credits used.

Practice

1. What is the main purpose of monitoring credit usage in Snowflake?

easy

A. To control and optimize Snowflake costs

B. To increase the number of warehouses automatically

C. To backup data to external storage

D. To improve query performance by caching

Solution

1. Step 1: Understand credit usage concept

   Credit usage monitoring tracks how many credits Snowflake consumes, which directly affects billing.

2. Step 2: Identify the goal of monitoring

   The goal is to control and optimize costs by understanding usage patterns.

3. Final Answer:

   To control and optimize Snowflake costs -> Option A

4. Quick Check:

   Credit monitoring = Cost control [OK]

Hint: Credit usage monitoring helps manage costs effectively [OK]

Common Mistakes:

• Confusing credit monitoring with performance tuning
• Thinking it automatically scales warehouses
• Assuming it backs up data

2. Which Snowflake view provides detailed credit usage information for warehouses?

easy

A. INFORMATION_SCHEMA.TABLES

B. ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY

C. ACCOUNT_USAGE.LOGIN_HISTORY

D. SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY

Solution

1. Step 1: Identify views related to credit usage

   ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY tracks credit consumption by warehouses.

2. Step 2: Exclude unrelated views

   INFORMATION_SCHEMA.TABLES shows table info, LOGIN_HISTORY tracks logins, QUERY_HISTORY tracks queries but not credit usage.

3. Final Answer:

   ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY -> Option B

4. Quick Check:

   Warehouse credit data = WAREHOUSE_METERING_HISTORY [OK]

Hint: Warehouse credit data is in WAREHOUSE_METERING_HISTORY view [OK]

Common Mistakes:

• Choosing QUERY_HISTORY which tracks queries, not credits
• Confusing LOGIN_HISTORY with credit usage
• Selecting INFORMATION_SCHEMA views unrelated to credits

3. What will the following query return?

SELECT WAREHOUSE_NAME, SUM(CREDITS_USED) AS TOTAL_CREDITS FROM SNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY GROUP BY WAREHOUSE_NAME ORDER BY TOTAL_CREDITS DESC;

medium

A. List of warehouses with their current running queries

B. Total credits used by each user in the account

C. Total credits used by each warehouse, sorted from highest to lowest

D. A syntax error due to missing WHERE clause

Solution

1. Step 1: Analyze the SELECT and GROUP BY

   The query sums credits used grouped by warehouse name.

2. Step 2: Understand ORDER BY clause

   Ordering by TOTAL_CREDITS DESC sorts warehouses from highest to lowest credit usage.

3. Final Answer:

   Total credits used by each warehouse, sorted from highest to lowest -> Option C

4. Quick Check:

   SUM credits by warehouse, ordered DESC = Total credits used by each warehouse, sorted from highest to lowest [OK]

Hint: GROUP BY warehouse sums credits; ORDER BY DESC sorts high to low [OK]

Common Mistakes:

• Thinking it shows user credit usage
• Assuming it lists running queries
• Believing missing WHERE causes syntax error

4. You run this query but get no results:

SELECT WAREHOUSE_NAME, SUM(CREDITS_USED) FROM SNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY WHERE START_TIME > CURRENT_DATE() GROUP BY WAREHOUSE_NAME;

What is the likely cause?

medium

A. Missing GROUP BY clause

B. Syntax error due to missing alias for SUM

C. Incorrect table name used

D. No credit usage recorded today yet

Solution

1. Step 1: Check the WHERE condition

   Filtering START_TIME > CURRENT_DATE() means only today's data is shown.

2. Step 2: Consider data availability

   If no credits used today yet, query returns empty result, not error.

3. Final Answer:

   No credit usage recorded today yet -> Option D

4. Quick Check:

   Empty result = no data matching date filter [OK]

Hint: Empty results often mean no data matches the filter [OK]

Common Mistakes:

• Assuming missing alias causes error
• Thinking table name is wrong
• Believing GROUP BY is missing

5. You want to monitor credit usage by service type (e.g., WAREHOUSE, CLOUD_SERVICES) for the last 7 days. Which query correctly achieves this?

hard

A. SELECT SERVICE_TYPE, SUM(CREDITS_USED) AS TOTAL_CREDITS FROM SNOWFLAKE.ACCOUNT_USAGE.METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE()) GROUP BY SERVICE_TYPE ORDER BY TOTAL_CREDITS DESC;

B. SELECT SERVICE_TYPE, SUM(CREDITS_USED) FROM SNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE()) GROUP BY SERVICE_TYPE;

C. SELECT WAREHOUSE_NAME, SUM(CREDITS_USED) FROM SNOWFLAKE.ACCOUNT_USAGE.METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE()) GROUP BY WAREHOUSE_NAME;

D. SELECT SERVICE_TYPE, CREDITS_USED FROM SNOWFLAKE.ACCOUNT_USAGE.METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE());

Solution

1. Step 1: Identify correct view for service type credit data

   ACCOUNT_USAGE.METERING_HISTORY contains credit usage by service type; WAREHOUSE_METERING_HISTORY is only for warehouses.

2. Step 2: Check query filters and grouping

   Filtering last 7 days with DATEADD and grouping by SERVICE_TYPE is correct; ordering by total credits helps see highest usage.

3. Final Answer:

   SELECT SERVICE_TYPE, SUM(CREDITS_USED) AS TOTAL_CREDITS FROM SNOWFLAKE.ACCOUNT_USAGE.METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE()) GROUP BY SERVICE_TYPE ORDER BY TOTAL_CREDITS DESC; -> Option A

4. Quick Check:

   Use METERING_HISTORY + SERVICE_TYPE + last 7 days = SELECT SERVICE_TYPE, SUM(CREDITS_USED) AS TOTAL_CREDITS FROM SNOWFLAKE.ACCOUNT_USAGE.METERING_HISTORY WHERE START_TIME >= DATEADD(day, -7, CURRENT_DATE()) GROUP BY SERVICE_TYPE ORDER BY TOTAL_CREDITS DESC; [OK]

Hint: Use METERING_HISTORY view and group by SERVICE_TYPE for service credit usage [OK]

Common Mistakes:

• Using WAREHOUSE_METERING_HISTORY for service types
• Not grouping by SERVICE_TYPE
• Selecting credits without aggregation