Query optimization with EXPLAIN in Supabase - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to show the query plan for selecting all users.

Supabase

EXPLAIN [1] * FROM users;

Drag options to blanks, or click blank then click option'

ASELECT

BANALYZE

CDELETE

DINSERT

Attempts:

3 left

💡 Hint

Common Mistakes

Using DELETE or INSERT after EXPLAIN instead of SELECT.

Omitting the SELECT keyword.

The EXPLAIN SELECT statement shows the query plan for a SELECT query.

2fill in blank

medium

Complete the code to get detailed execution statistics for a query.

Supabase

EXPLAIN [1] SELECT * FROM orders WHERE amount > 100;

Drag options to blanks, or click blank then click option'

AANALYZE

BCOSTS

CBUFFERS

DVERBOSE

Attempts:

3 left

💡 Hint

Common Mistakes

Using VERBOSE which only adds detail to the plan but does not run the query.

Using COSTS or BUFFERS without ANALYZE.

The ANALYZE option runs the query and shows actual execution statistics.

3fill in blank

hard

Fix the error in the EXPLAIN statement to correctly show the query plan with buffers.

Supabase

EXPLAIN ANALYZE [1] BUFFERS SELECT * FROM products;

Drag options to blanks, or click blank then click option'

AON

BAND

COR

DWITH

Attempts:

3 left

💡 Hint

Common Mistakes

Using AND or OR instead of WITH.

Placing BUFFERS before ANALYZE.

The correct syntax is EXPLAIN ANALYZE WITH BUFFERS to include buffer usage.

4fill in blank

hard

Fill both blanks to create a query that explains the plan with costs and verbose output.

Supabase

EXPLAIN [1] [2] SELECT * FROM customers WHERE city = 'Paris';

Drag options to blanks, or click blank then click option'

ACOSTS

BANALYZE

CVERBOSE

DBUFFERS

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing ANALYZE with COSTS and VERBOSE incorrectly.

Using BUFFERS when not running the query.

Using COSTS VERBOSE shows estimated costs and detailed plan info without running the query.

5fill in blank

hard

Fill all three blanks to explain and analyze a query with costs, buffers, and verbose output.

Supabase

EXPLAIN [1] WITH [2] [3] SELECT * FROM sales WHERE total > 500;

Drag options to blanks, or click blank then click option'

AANALYZE

BBUFFERS

CVERBOSE

DCOSTS

Attempts:

3 left

💡 Hint

Common Mistakes

Placing VERBOSE instead of COSTS or BUFFERS.

Omitting WITH before options.

The correct order is ANALYZE WITH COSTS BUFFERS to run the query and show costs and buffer usage.

Practice

1. What is the main purpose of using EXPLAIN in Supabase queries?

easy

A. To execute the query faster automatically

B. To see how the database plans to run your query

C. To delete data from the database

D. To create new tables in the database

Solution

1. Step 1: Understand the role of EXPLAIN

   EXPLAIN shows the query plan, which is how the database intends to run the query.

2. Step 2: Differentiate EXPLAIN from other commands

   It does not execute or change data; it only provides information about query execution.

3. Final Answer:

   To see how the database plans to run your query -> Option B

4. Quick Check:

   EXPLAIN = query plan info [OK]

Hint: EXPLAIN shows query plans, not data changes [OK]

Common Mistakes:

• Thinking EXPLAIN runs the query faster
• Confusing EXPLAIN with data modification commands
• Assuming EXPLAIN creates or deletes tables

2. Which of the following is the correct syntax to get detailed execution info of a query in Supabase?

easy

A. EXPLAIN ANALYZE SELECT * FROM users;

B. EXPLAIN SELECT * FROM users;

C. ANALYZE EXPLAIN SELECT * FROM users;

D. SELECT EXPLAIN ANALYZE * FROM users;

Solution

1. Step 1: Recall the syntax for detailed query execution

   To get real execution details, use EXPLAIN ANALYZE before the query.

2. Step 2: Check each option's syntax

   EXPLAIN ANALYZE SELECT * FROM users; correctly places EXPLAIN ANALYZE before the SELECT statement; others are incorrect or invalid.

3. Final Answer:

   EXPLAIN ANALYZE SELECT * FROM users; -> Option A

4. Quick Check:

   EXPLAIN ANALYZE = detailed execution [OK]

Hint: Use EXPLAIN ANALYZE before SELECT for details [OK]

Common Mistakes:

• Swapping EXPLAIN and ANALYZE order
• Placing EXPLAIN inside SELECT
• Using ANALYZE without EXPLAIN

3. Given the EXPLAIN output shows a sequential scan on a large table, what is the likely effect on query performance?

medium

A. The query will be very fast because it uses an index

B. The query will fail due to missing indexes

C. The query will only scan a small part of the table

D. The query might be slow because it reads the whole table

Solution

1. Step 1: Understand sequential scan meaning

   A sequential scan reads every row in the table, which can be slow for large tables.

2. Step 2: Compare with index scan

   Index scans read only relevant rows, making queries faster; sequential scans do not use indexes.

3. Final Answer:

   The query might be slow because it reads the whole table -> Option D

4. Quick Check:

   Seq scan = full table read, slower [OK]

Hint: Seq scan reads all rows, slowing large queries [OK]

Common Mistakes:

• Assuming sequential scan uses indexes
• Thinking sequential scan reads only part of table
• Confusing failure with slow performance

4. You run EXPLAIN ANALYZE SELECT * FROM orders WHERE customer_id = 123; but notice the query is slow. What is a likely cause and fix?

medium

A. No index on customer_id; add an index on that column

B. The query syntax is wrong; rewrite the SELECT statement

C. The database is offline; restart the server

D. The table orders does not exist; create it first

Solution

1. Step 1: Analyze slow query cause

   Slow queries filtering by a column often mean missing indexes on that column.

2. Step 2: Suggest fix based on EXPLAIN ANALYZE

   Adding an index on customer_id helps the database find rows faster, improving speed.

3. Final Answer:

   No index on customer_id; add an index on that column -> Option A

4. Quick Check:

   Missing index = slow filter; add index [OK]

Hint: Slow filtered query? Check indexes on filter columns [OK]

Common Mistakes:

• Assuming syntax error causes slowness
• Restarting server without checking query plan
• Thinking missing table causes slow query

5. You want to optimize a complex query joining two large tables. The EXPLAIN ANALYZE shows nested loops causing slow performance. What is the best approach to improve it?

hard

A. Increase the database server's CPU without changing the query

B. Remove all indexes to force sequential scans

C. Add indexes on join columns and rewrite query to use explicit JOIN syntax

D. Split the query into multiple smaller queries without joins

Solution

1. Step 1: Understand nested loops impact

   Nested loops join can be slow on large tables without proper indexes on join columns.

2. Step 2: Apply optimization techniques

   Adding indexes on join columns helps the database find matching rows faster. Using explicit JOIN syntax clarifies the query for optimization.

3. Final Answer:

   Add indexes on join columns and rewrite query to use explicit JOIN syntax -> Option C

4. Quick Check:

   Indexes + clear JOIN = faster joins [OK]

Hint: Index join columns and use explicit JOIN for speed [OK]

Common Mistakes:

• Removing indexes causing slower scans
• Splitting queries losing join benefits
• Relying only on hardware upgrades