Query profiling and the query plan in Snowflake - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a query plan in Snowflake?

A query plan is a detailed step-by-step guide that Snowflake uses to execute a query efficiently. It shows how data is accessed, joined, and processed.

beginner

What does query profiling help you understand?

Query profiling helps you see how long each part of a query takes and where resources are used, so you can find slow parts and improve performance.

intermediate

Which Snowflake feature shows the query plan visually?

The Query Profile page in Snowflake's UI shows the query plan visually with steps and timing, helping you understand query execution.

intermediate

Why is understanding the query plan important?

Understanding the query plan helps you spot inefficient operations like full table scans or expensive joins, so you can optimize your queries.

beginner

What is a common sign of a slow query in the query profile?

A common sign is a step that takes much longer than others or uses a lot of resources, indicating a bottleneck in the query.

What does the query plan in Snowflake show?

A The cost of Snowflake credits

B The number of users running queries

C How Snowflake will run the query step-by-step

D The size of the database

The query plan shows the detailed steps Snowflake uses to run a query.

Where can you find the visual query plan in Snowflake?

A Warehouse monitor

B Query Profile page

C Billing dashboard

D User settings

The Query Profile page displays the visual query plan.

What is a key benefit of query profiling?

A Changing user passwords

B Backing up data

C Creating new tables

D Identifying slow parts of a query

Query profiling helps find slow or resource-heavy parts of a query.

If a query step takes much longer than others, what does it indicate?

A A bottleneck or inefficiency

B The query is finished

C The database is empty

D The user is logged out

A long-running step usually means a bottleneck in the query.

Which of these is NOT shown in a Snowflake query plan?

A User login history

B Data access methods

C Steps to execute the query

D Join operations

User login history is not part of the query plan.

Explain what a query plan is and why it is useful in Snowflake.

Think about how Snowflake decides to run your query.

Describe how query profiling can help improve query performance.

Consider what you learn by looking at each part of the query.

Practice

1. What does the EXPLAIN command in Snowflake do?

easy

A. Shows the steps Snowflake will take to run a query

B. Runs the query and returns the results

C. Deletes the query from history

D. Optimizes the query automatically

Solution

1. Step 1: Understand the purpose of EXPLAIN

   The EXPLAIN command shows the query plan, which details how Snowflake will execute the query step-by-step without running it.

2. Step 2: Differentiate EXPLAIN from other commands

   Unlike running the query or deleting history, EXPLAIN only provides the plan, not results or changes.

3. Final Answer:

   Shows the steps Snowflake will take to run a query -> Option A

4. Quick Check:

   EXPLAIN = Shows query plan [OK]

Hint: EXPLAIN previews query steps without running it [OK]

Common Mistakes:

• Thinking EXPLAIN runs the query
• Confusing EXPLAIN with query deletion
• Assuming EXPLAIN optimizes automatically

2. Which of the following is the correct syntax to get the query plan for a SELECT statement in Snowflake?

easy

A. SHOW PLAN FOR SELECT * FROM my_table;

B. EXPLAIN SELECT * FROM my_table;

C. DESCRIBE QUERY SELECT * FROM my_table;

D. PLAN QUERY SELECT * FROM my_table;

Solution

1. Step 1: Recall Snowflake syntax for query plans

   Snowflake uses the EXPLAIN keyword before a query to show its plan.

2. Step 2: Verify syntax correctness

   Only EXPLAIN SELECT ... is valid; other options are not recognized commands.

3. Final Answer:

   EXPLAIN SELECT * FROM my_table; -> Option B

4. Quick Check:

   EXPLAIN + query = correct syntax [OK]

Hint: Use EXPLAIN before your query to see the plan [OK]

Common Mistakes:

• Using SHOW PLAN which is not valid in Snowflake
• Trying DESCRIBE QUERY which is incorrect
• Using PLAN QUERY which is not a command

3. Given the query plan shows a step with a large number of rows scanned and a high cost, what does this indicate?

medium

A. Snowflake will skip this step automatically

B. The query is efficient and fast

C. This step may slow down the query and use more resources

D. The query will return no results

Solution

1. Step 1: Interpret rows scanned and cost in query plan

   A large number of rows scanned and high cost means this step requires more work and resources.

2. Step 2: Understand impact on query performance

   Such steps usually slow down the query and increase resource usage, not speed it up or skip it.

3. Final Answer:

   This step may slow down the query and use more resources -> Option C

4. Quick Check:

   High rows scanned = slower step [OK]

Hint: High rows scanned means slower query step [OK]

Common Mistakes:

• Assuming high cost means faster query
• Thinking Snowflake skips costly steps
• Confusing cost with query result count

4. You ran EXPLAIN SELECT * FROM orders WHERE order_date > '2023-01-01'; but the plan shows a full table scan. What is a likely reason?

medium

A. There is no index or clustering on order_date

B. The query syntax is incorrect

C. Snowflake does not support filtering on dates

D. The table is empty

Solution

1. Step 1: Analyze why full table scan occurs

   Full table scans happen when no index or clustering helps filter data efficiently.

2. Step 2: Check other options for validity

   The query syntax is correct, Snowflake supports date filters, and an empty table would not cause a full scan.

3. Final Answer:

   There is no index or clustering on order_date -> Option A

4. Quick Check:

   No index = full scan [OK]

Hint: No index or clustering causes full scans [OK]

Common Mistakes:

• Thinking syntax error causes full scan
• Believing Snowflake can't filter dates
• Assuming empty table causes full scan

5. You want to optimize a slow query that joins two large tables. The query plan shows a costly step performing a large shuffle of data between nodes. What is the best approach to reduce this cost?

hard

A. Increase the warehouse size without changing the query

B. Add more columns to the SELECT clause

C. Run the query without a WHERE clause

D. Use clustering keys to co-locate join keys and reduce data shuffle

Solution

1. Step 1: Understand data shuffle in join operations

   Data shuffle happens when data must move between nodes to match join keys, which is costly.

2. Step 2: Use clustering keys to optimize joins

   Clustering keys organize data so join keys are stored together, reducing shuffle and improving speed.

3. Step 3: Evaluate other options

   Adding columns or removing filters increases data processed; increasing warehouse size helps but does not reduce shuffle.

4. Final Answer:

   Use clustering keys to co-locate join keys and reduce data shuffle -> Option D

5. Quick Check:

   Clustering keys reduce shuffle cost [OK]

Hint: Clustering keys reduce costly data shuffle in joins [OK]

Common Mistakes:

• Adding columns increases data, not reduces cost
• Removing WHERE clause slows query
• Relying only on warehouse size ignores shuffle