Access history and audit logging in Snowflake - Time & Space Complexity

Time Complexity: Access history and audit logging

O(n log n)

Understanding Time Complexity

When we check access history and audit logs in Snowflake, we want to know how long it takes to get results as the amount of data grows.

We ask: How does the time to fetch logs change when there are more records?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

SELECT event_time, user_name, action
FROM snowflake.account_usage.access_history
WHERE event_time > DATEADD(day, -7, CURRENT_TIMESTAMP())
ORDER BY event_time DESC
LIMIT 1000;
    

This query fetches the last 1000 access events from the past week, ordered by time.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Scanning the access_history table for events in the last 7 days.
• How many times: The database scans all matching rows for the 7-day period before sorting and limiting results.

How Execution Grows With Input

As the number of access events in the last 7 days grows, the scan and sort take longer.

Input Size (n)	Approx. Operations
10	About 10 rows scanned and sorted
100	About 100 rows scanned and sorted
1000	About 1000 rows scanned and sorted

Pattern observation: The work grows roughly in direct proportion to the number of rows scanned before limiting.

Final Time Complexity

Time Complexity: O(n log n)

This means the time grows a bit faster than the number of rows because sorting takes extra steps.

Common Mistake

[X] Wrong: "Fetching audit logs always takes the same time no matter how many records there are."

[OK] Correct: The database must scan and sort all matching rows, so more records mean more work and longer time.

Interview Connect

Understanding how log queries scale helps you design better monitoring and troubleshooting tools in real projects.

Self-Check

"What if we added a clustering key on event_time? How would the time complexity change?"

Practice

1. What does the ACCESS_HISTORY view in Snowflake primarily provide?

easy

A. Information about who accessed data and when

B. Details about Snowflake account billing

C. List of all database tables and schemas

D. Performance metrics of queries

Solution

1. Step 1: Understand the purpose of ACCESS_HISTORY

   The ACCESS_HISTORY view records user activity related to data access in Snowflake.

2. Step 2: Identify what ACCESS_HISTORY tracks

   It tracks who accessed what data and when, useful for audit and compliance.

3. Final Answer:

   Information about who accessed data and when -> Option A

4. Quick Check:

   ACCESS_HISTORY = Data access logs [OK]

Hint: ACCESS_HISTORY logs user data access events only [OK]

Common Mistakes:

• Confusing ACCESS_HISTORY with billing or performance views
• Thinking it shows database structure
• Assuming it tracks query performance

2. Which of the following is the correct syntax to query the ACCESS_HISTORY view for all accesses in the last 7 days?

easy

A. SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME = CURRENT_DATE - 7;

B. SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME < CURRENT_DATE + 7;

C. SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME > CURRENT_DATE - 7;

D. SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME BETWEEN CURRENT_DATE AND CURRENT_DATE + 7;

Solution

1. Step 1: Understand date filtering in Snowflake SQL

   To get records from the last 7 days, filter where ACCESS_TIME is greater than current date minus 7 days.

2. Step 2: Check each option's date condition

   SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME > CURRENT_DATE - 7; correctly uses ACCESS_TIME > CURRENT_DATE - 7 to get recent records.

3. Final Answer:

   SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME > CURRENT_DATE - 7; -> Option C

4. Quick Check:

   Date filter for last 7 days = SELECT * FROM ACCESS_HISTORY WHERE ACCESS_TIME > CURRENT_DATE - 7; [OK]

Hint: Use > CURRENT_DATE - 7 for last 7 days filter [OK]

Common Mistakes:

• Using < instead of > for recent dates
• Using = which matches only one day
• Using BETWEEN with future dates incorrectly

3. What will be the result of this query?

SELECT USER_NAME, COUNT(*) AS ACCESS_COUNT
FROM ACCESS_HISTORY
WHERE OBJECT_NAME = 'CUSTOMERS'
GROUP BY USER_NAME
ORDER BY ACCESS_COUNT DESC
LIMIT 3;

medium

A. All users who accessed any object named CUSTOMERS

B. An error because OBJECT_NAME is not a valid column

C. The total number of accesses to all objects

D. Top 3 users who accessed the CUSTOMERS object most frequently

Solution

1. Step 1: Analyze the query components

   The query counts accesses per user filtered by OBJECT_NAME = 'CUSTOMERS'.

2. Step 2: Understand GROUP BY and ORDER BY

   It groups by USER_NAME, orders by count descending, and limits to top 3 users.

3. Final Answer:

   Top 3 users who accessed the CUSTOMERS object most frequently -> Option D

4. Quick Check:

   GROUP BY USER_NAME with LIMIT 3 = Top 3 users who accessed the CUSTOMERS object most frequently [OK]

Hint: GROUP BY user and LIMIT 3 shows top 3 users [OK]

Common Mistakes:

• Thinking it lists all users without limit
• Assuming OBJECT_NAME is invalid
• Confusing total accesses with per-user counts

4. You run this query but get an error:

SELECT * FROM ACCESS_HISTORY WHERE USER = 'JOHN';

What is the likely cause and fix?

medium

A. Column USER does not exist; use USER_NAME instead

B. ACCESS_HISTORY view is not accessible to your role

C. Syntax error due to missing semicolon

D. USER is a reserved keyword; enclose in double quotes

Solution

1. Step 1: Check column names in ACCESS_HISTORY

   The correct column for user is USER_NAME, not USER.

2. Step 2: Correct the query column name

   Replace USER with USER_NAME to fix the error.

3. Final Answer:

   Column USER does not exist; use USER_NAME instead -> Option A

4. Quick Check:

   Use USER_NAME column, not USER [OK]

Hint: Use USER_NAME, not USER, as column name [OK]

Common Mistakes:

• Using USER instead of USER_NAME
• Assuming missing semicolon causes error
• Thinking ACCESS_HISTORY is inaccessible

5. You want to audit all SELECT queries on the SALES table in the last 30 days. Which query correctly retrieves this from ACCESS_HISTORY?

hard

A. SELECT QUERY_TEXT, USER_NAME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TYPE = 'INSERT' AND ACCESS_TIME > CURRENT_DATE - 30;

B. SELECT QUERY_TEXT, USER_NAME, ACCESS_TIME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TYPE = 'SELECT' AND ACCESS_TIME > CURRENT_DATE - 30;

C. SELECT * FROM ACCESS_HISTORY WHERE TABLE_NAME = 'SALES' AND QUERY_TYPE = 'SELECT' AND ACCESS_TIME > CURRENT_DATE - 30;

D. SELECT QUERY_TEXT, USER_NAME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TIME < CURRENT_DATE - 30;

Solution

1. Step 1: Identify correct column names and filters

   ACCESS_HISTORY uses OBJECT_NAME for table, ACCESS_TYPE for operation, and ACCESS_TIME for timestamp.

2. Step 2: Check filter conditions for SELECT and last 30 days

   SELECT QUERY_TEXT, USER_NAME, ACCESS_TIME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TYPE = 'SELECT' AND ACCESS_TIME > CURRENT_DATE - 30; filters OBJECT_NAME = 'SALES', ACCESS_TYPE = 'SELECT', and ACCESS_TIME > CURRENT_DATE - 30 correctly.

3. Final Answer:

   SELECT QUERY_TEXT, USER_NAME, ACCESS_TIME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TYPE = 'SELECT' AND ACCESS_TIME > CURRENT_DATE - 30; -> Option B

4. Quick Check:

   Correct columns and filters = SELECT QUERY_TEXT, USER_NAME, ACCESS_TIME FROM ACCESS_HISTORY WHERE OBJECT_NAME = 'SALES' AND ACCESS_TYPE = 'SELECT' AND ACCESS_TIME > CURRENT_DATE - 30; [OK]

Hint: Filter by OBJECT_NAME, ACCESS_TYPE, and recent ACCESS_TIME [OK]

Common Mistakes:

• Using TABLE_NAME or QUERY_TYPE which don't exist
• Filtering for INSERT instead of SELECT
• Using ACCESS_TIME < CURRENT_DATE - 30 (old data)