Query history and profiling in Snowflake - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Understanding Query History Table Output

You run the following query in Snowflake to check recent query history:

SELECT query_id, user_name, execution_status, total_elapsed_time FROM table(information_schema.query_history()) WHERE user_name = 'ANALYST' ORDER BY start_time DESC LIMIT 3;

What will the total_elapsed_time column represent in the output?

Snowflake

SELECT query_id, user_name, execution_status, total_elapsed_time FROM table(information_schema.query_history()) WHERE user_name = 'ANALYST' ORDER BY start_time DESC LIMIT 3;

A The time in microseconds spent transferring data to the client.

B The time in seconds the query spent waiting in the queue before execution.

C The CPU time consumed by the query during execution.

D The total time in milliseconds that the query took to execute from start to finish.

💡 Hint

Think about what 'elapsed time' usually means in timing contexts.

The total_elapsed_time column shows the full duration the query took to run, measured in milliseconds, from start to finish including all processing time.

🧠 Conceptual

intermediate

Identifying Query Failures from History

You want to find all queries that failed in the last 24 hours using Snowflake's query history. Which execution_status value should you filter for to get only failed queries?

A 'SUCCESS'

B 'CANCELED'

C 'FAILED'

D 'RUNNING'

💡 Hint

Think about the status that indicates a query did not complete successfully.

The execution_status 'FAILED' indicates queries that ended with an error and did not complete successfully.

❓ Architecture

advanced

Optimizing Query Profiling for Large Workloads

Your Snowflake account runs thousands of queries daily. You want to efficiently analyze query performance trends over the past week without scanning the entire query history table. Which approach is best to reduce query time and cost?

A Use the QUERY_HISTORY function without any filters and rely on Snowflake to optimize automatically.

B Use the QUERY_HISTORY view with a filter on start_time to limit to the last week and select only needed columns.

C Query the QUERY_HISTORY table without filters to get all data and then filter in your application.

D Download the entire query history table and analyze it locally in a spreadsheet.

💡 Hint

Filtering early reduces data scanned and speeds up queries.

Filtering on start_time in the QUERY_HISTORY view limits data scanned, reducing cost and improving query speed. Selecting only needed columns also helps.

❓ security

advanced

Controlling Access to Query History Data

Which Snowflake role should you assign to a user to allow them to view query history but prevent them from modifying any data or running queries themselves?

A MONITOR

B SYSADMIN

C ACCOUNTADMIN

D PUBLIC

💡 Hint

This role is designed for read-only monitoring tasks.

The MONITOR role grants read-only access to account usage and query history without permissions to modify data or run queries.

✅ Best Practice

expert

Interpreting Query Profile for Performance Bottlenecks

You examine the query profile for a slow-running Snowflake query. The profile shows a large amount of time spent in the 'Spilled to Disk' operation. What does this indicate and what is the best next step?

A The query ran out of memory and spilled data to disk, slowing performance; increase warehouse size or optimize query to reduce memory use.

B The query is waiting on network I/O; check network connectivity and retry.

C The query is blocked by locks; kill blocking queries to proceed.

D The query completed successfully with no issues; no action needed.

💡 Hint

Spilling to disk usually means memory limits were exceeded.

Spilled to Disk means Snowflake had to write intermediate data to disk because memory was insufficient, causing slower query execution. Increasing warehouse size or rewriting the query can help.

Practice

1. What is the main purpose of the QUERY_HISTORY view in Snowflake?

easy

A. To see details of past queries executed in the system

B. To create new tables and schemas

C. To manage user permissions and roles

D. To monitor network traffic between Snowflake and clients

Solution

1. Step 1: Understand the role of QUERY_HISTORY

   The QUERY_HISTORY view stores information about queries that have already run, including their text, execution time, and status. Its main purpose is to see details of past queries executed in the system.

2. Final Answer:

   To see details of past queries executed in the system -> Option A

3. Quick Check:

   QUERY_HISTORY = past query details [OK]

Hint: QUERY_HISTORY shows past queries and their info [OK]

Common Mistakes:

• Confusing QUERY_HISTORY with user management
• Thinking it manages network or security settings
• Assuming it creates or modifies database objects

2. Which SQL clause correctly filters queries executed by a specific user in the QUERY_HISTORY view?

easy

A. FILTER BY USER = 'john_doe'

B. WHERE USER_NAME = 'john_doe'

C. SELECT USER_NAME FROM QUERY_HISTORY WHERE 'john_doe'

D. HAVING USER_NAME = 'john_doe'

Solution

1. Step 1: Recall SQL filtering syntax

   To filter rows in SQL, the WHERE clause is used with a condition like USER_NAME = 'value'. WHERE USER_NAME = 'john_doe' is valid and standard SQL syntax.

2. Final Answer:

   WHERE USER_NAME = 'john_doe' -> Option B

3. Quick Check:

   Filter with WHERE clause = WHERE USER_NAME = 'john_doe' [OK]

Hint: Use WHERE to filter rows by user name [OK]

Common Mistakes:

• Using FILTER BY instead of WHERE
• Misplacing HAVING without GROUP BY
• Incorrect SELECT syntax without WHERE

3. Given the query:

SELECT query_text, total_elapsed_time FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) WHERE execution_status = 'FAILED' ORDER BY start_time DESC LIMIT 1;

What does this query return?

medium

A. The most recent failed query's text and its total elapsed time

B. All successful queries ordered by start time

C. The oldest failed query's text and elapsed time

D. An error because QUERY_HISTORY is not a table

Solution

1. Step 1: Analyze the query clauses

   The query uses TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) to access query history, filters for execution_status = 'FAILED', orders by start_time DESC (most recent first), and limits to 1 row, returning the most recent failed query's text and total elapsed time.

2. Final Answer:

   The most recent failed query's text and its total elapsed time -> Option A

3. Quick Check:

   Filter failed + order desc + limit 1 = most recent failed query [OK]

Hint: ORDER BY DESC + LIMIT 1 gets latest record [OK]

Common Mistakes:

• Thinking QUERY_HISTORY is a normal table
• Confusing oldest vs most recent due to ORDER BY
• Ignoring the WHERE filter on execution_status

4. You wrote this query to find slow queries but it returns no results:

SELECT query_text FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) WHERE total_elapsed_time > 1000;

What is the likely issue?

medium

A. The TABLE() function cannot be used with QUERY_HISTORY

B. QUERY_HISTORY does not have total_elapsed_time column

C. The query_text column cannot be selected from QUERY_HISTORY

D. total_elapsed_time is in microseconds, so 1000 is too small a threshold

Solution

1. Step 1: Check the unit of total_elapsed_time

   In Snowflake, total_elapsed_time is measured in microseconds, so 1000 microseconds (1 millisecond) is too small a threshold, and few or no queries exceed it, resulting in no results.

2. Final Answer:

   total_elapsed_time is in microseconds, so 1000 is too small a threshold -> Option D

3. Quick Check:

   Elapsed time unit = microseconds, threshold too low [OK]

Hint: Check units: elapsed time is microseconds, not milliseconds [OK]

Common Mistakes:

• Assuming elapsed time is in seconds or milliseconds
• Thinking QUERY_HISTORY lacks columns
• Misusing TABLE() function syntax

5. You want to profile query performance by grouping queries by user and calculating average execution time. Which query correctly achieves this?

hard

A. SELECT user_name, SUM(total_elapsed_time) FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) WHERE execution_status = 'SUCCESS';

B. SELECT user_name, total_elapsed_time FROM QUERY_HISTORY GROUP BY user_name;

C. SELECT user_name, AVG(total_elapsed_time) AS avg_time FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) GROUP BY user_name ORDER BY avg_time DESC;

D. SELECT user_name, AVG(total_elapsed_time) FROM QUERY_HISTORY WHERE total_elapsed_time > 1000 ORDER BY user_name;

Solution

1. Step 1: Identify correct aggregation and grouping

   To get average execution time per user, use AVG(total_elapsed_time) with GROUP BY user_name from TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()), as in SELECT user_name, AVG(total_elapsed_time) AS avg_time ... GROUP BY user_name ORDER BY avg_time DESC.

2. Final Answer:

   SELECT user_name, AVG(total_elapsed_time) AS avg_time FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) GROUP BY user_name ORDER BY avg_time DESC; -> Option C

3. Quick Check:

   Group by user + AVG + ORDER BY avg_time = SELECT user_name, AVG(total_elapsed_time) AS avg_time FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY()) GROUP BY user_name ORDER BY avg_time DESC; [OK]

Hint: Use GROUP BY user_name with AVG for profiling [OK]

Common Mistakes:

• Missing GROUP BY when using aggregation
• Selecting columns without aggregation
• Not using TABLE() function for QUERY_HISTORY