Index impact on INSERT and UPDATE in SQL - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

How do indexes affect INSERT operations?

When you insert a new row into a table that has multiple indexes, what happens behind the scenes?

A The database updates all indexes related to the table to include the new row, which can slow down the INSERT.

B The database duplicates the inserted row in each index without updating the main table.

C Only the primary key index is updated during INSERT; other indexes update later asynchronously.

D Indexes are ignored during INSERT operations to speed up data entry.

💡 Hint

Think about what must happen to keep indexes accurate when new data is added.

When inserting, the database must update all indexes to include the new row so queries using those indexes remain accurate. This adds overhead and can slow down INSERT operations.

🧠 Conceptual

intermediate

Why can UPDATE operations be slower on indexed columns?

Updating a column that is part of an index can be slower than updating a non-indexed column. Why?

A Because the database duplicates the entire table when an indexed column is updated.

B Because updates on indexed columns are blocked until all queries finish.

C Because the database must update the index entries related to the changed column, adding extra work.

D Because indexed columns cannot be updated once created.

💡 Hint

Consider what happens to the index when the data it tracks changes.

When an indexed column is updated, the database must update the index entries to reflect the new values, which adds overhead and can slow down the UPDATE operation.

❓ query_result

advanced

Effect of indexes on INSERT speed

Given a table users with 3 indexes, you run two INSERT queries: one on the table with indexes and one after dropping all indexes. Which query runs faster?

SQL

INSERT INTO users (id, name, email) VALUES (101, 'Alice', '[e-mail]');

A The INSERT on the table without indexes runs slower because indexes optimize data storage.

B The INSERT on the table without indexes runs faster because no index updates are needed.

C Both INSERTs run at the same speed because indexes do not affect INSERT performance.

D The INSERT on the table with indexes runs faster because indexes speed up data insertion.

💡 Hint

Think about the extra work indexes require during data insertion.

Indexes require updating during INSERT, which adds overhead. Without indexes, the database only inserts the row, so it is faster.

❓ query_result

advanced

Impact of updating indexed vs non-indexed columns

Consider a table products with an index on the price column. You run these two UPDATE queries:

UPDATE products SET price = price * 1.1 WHERE id = 5;
UPDATE products SET description = 'New model' WHERE id = 5;

Which UPDATE is expected to take longer?

A The UPDATE on the <code>price</code> column takes longer because it updates the index.

B The UPDATE on the <code>description</code> column takes longer because it is a text field.

C Both UPDATEs take the same time because indexes do not affect UPDATE speed.

D The UPDATE on the <code>description</code> column takes longer because it triggers index rebuilds.

💡 Hint

Consider which columns have indexes and what updating them requires.

Updating an indexed column requires updating the index entries, which adds overhead. Updating a non-indexed column does not affect indexes and is usually faster.

📝 Syntax

expert

Identify the error in index update during INSERT trigger

Given this trigger code to update a custom index table after INSERT, what error will it cause?

CREATE TRIGGER update_index AFTER INSERT ON orders
FOR EACH ROW
BEGIN
  INSERT INTO orders_index(order_id, customer_id) VALUES (NEW.order_id, NEW.customer_id);
END;

A Runtime error because NEW keyword cannot be used in AFTER INSERT triggers.

B No error; the trigger works correctly.

C Logical error because the trigger causes infinite recursion.

D Syntax error due to missing delimiter declaration before trigger creation.

💡 Hint

Check if the trigger syntax requires special delimiter handling.

In many SQL dialects like MySQL, creating triggers requires changing the delimiter temporarily to avoid syntax errors. Missing this causes a syntax error.

Practice

1. What is the main impact of having many indexes on a table when performing INSERT operations?

easy

A. Inserts become slower because each index must be updated.

B. Inserts become faster because indexes help locate where to insert.

C. Inserts are unaffected by indexes.

D. Inserts cause indexes to be deleted automatically.

Solution

1. Step 1: Understand how indexes affect inserts

   When inserting a new row, the database must update all indexes related to that table to keep them accurate.

2. Step 2: Analyze the effect on performance

   Updating multiple indexes adds overhead, making inserts slower as more indexes exist.

3. Final Answer:

   Inserts become slower because each index must be updated. -> Option A

4. Quick Check:

   More indexes = slower inserts [OK]

Hint: More indexes slow inserts due to extra updates [OK]

Common Mistakes:

• Thinking indexes speed up inserts
• Believing inserts ignore indexes
• Assuming indexes get deleted on insert

2. Which of the following is the correct syntax to create an index on the email column of a table named users?

easy

A. CREATE INDEX idx_email ON users(email);

B. CREATE users INDEX ON email;

C. INDEX CREATE ON users(email);

D. CREATE INDEX users_email email;

Solution

1. Step 1: Recall standard SQL index creation syntax

   The correct syntax is: CREATE INDEX index_name ON table_name(column_name);

2. Step 2: Match the syntax to options

   CREATE INDEX idx_email ON users(email); matches the correct syntax exactly.

3. Final Answer:

   CREATE INDEX idx_email ON users(email); -> Option A

4. Quick Check:

   CREATE INDEX ... ON table(column) [OK]

Hint: Use CREATE INDEX index_name ON table(column) [OK]

Common Mistakes:

• Swapping table and column names
• Omitting ON keyword
• Incorrect order of keywords

3. Given a table products with a non-clustered index on category_id, what happens internally when you run this query?

UPDATE products SET price = price * 1.1 WHERE category_id = 5;

medium

A. The update ignores the index and scans the whole table.

B. The update is slower because the index on category_id must be rebuilt entirely.

C. The update fails because indexes cannot be used with UPDATE statements.

D. The update is faster because the index helps find rows quickly, but the index must be updated if category_id changes.

Solution

1. Step 1: Understand index use in WHERE clause

   The index on category_id helps quickly find rows where category_id = 5.

2. Step 2: Consider index updates during UPDATE

   Since category_id is not changed, the index entries remain valid; only the data column price is updated.

3. Final Answer:

   The update is faster because the index helps find rows quickly, but the index must be updated if category_id changes. -> Option D

4. Quick Check:

   Index speeds search; update affects data, not index keys [OK]

Hint: Indexes speed WHERE search; update index only if key changes [OK]

Common Mistakes:

• Thinking index rebuilds fully on update
• Assuming update ignores indexes
• Believing update fails with indexes

4. You have a table orders with an index on order_date. You run this query:

UPDATE orders SET order_date = '2024-01-01' WHERE order_id = 100;

But the update is very slow. What is a likely cause?

medium

A. Indexes do not affect update speed, so the cause is elsewhere.

B. The query syntax is incorrect, causing a full table scan.

C. The index on order_date must be updated because the indexed column value changed.

D. The order_id column is not indexed, causing slow search.

Solution

1. Step 1: Identify which columns are indexed and updated

   The order_date column is indexed and is being updated.

2. Step 2: Understand index maintenance on update

   Updating an indexed column requires updating the index entry, which adds overhead and slows the update.

3. Final Answer:

   The index on order_date must be updated because the indexed column value changed. -> Option C

4. Quick Check:

   Updating indexed columns slows updates due to index maintenance [OK]

Hint: Updating indexed columns slows updates due to index changes [OK]

Common Mistakes:

• Ignoring index update cost
• Blaming syntax errors without checking
• Assuming indexes don't affect update speed

5. You manage a large table employees with indexes on department_id and last_name. You notice INSERT and UPDATE operations are slow. Which strategy best balances read speed and write performance?

hard

A. Remove all indexes to speed up writes, sacrificing read speed.

B. Keep only essential indexes used frequently in queries, reducing overhead on writes.

C. Add more indexes to speed up all queries regardless of write cost.

D. Disable indexes during inserts and updates and rebuild them after every operation.

Solution

1. Step 1: Understand the trade-off between indexes and write speed

   More indexes improve read speed but slow down inserts and updates because each index must be maintained.

2. Step 2: Choose a balanced approach

   Keeping only essential indexes used often reduces write overhead while maintaining reasonable read performance.

3. Final Answer:

   Keep only essential indexes used frequently in queries, reducing overhead on writes. -> Option B

4. Quick Check:

   Balance indexes for reads and writes [OK]

Hint: Keep only needed indexes to balance reads and writes [OK]

Common Mistakes:

• Removing all indexes hurting reads
• Adding too many indexes slowing writes
• Rebuilding indexes too often causing delays