Index impact on INSERT and UPDATE in SQL - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main effect of having indexes on INSERT operations in a database?

Indexes slow down INSERT operations because the database must update the index data structures every time a new row is added.

beginner

How do indexes affect UPDATE operations in a database?

Indexes can slow down UPDATE operations, especially if the updated columns are part of the index, because the index entries must be updated as well.

intermediate

Why might a database slow down when many indexes exist on a table during data modification?

Because each INSERT or UPDATE requires updating all related indexes, more indexes mean more work and slower data modification.

beginner

True or False: Indexes only affect SELECT queries and have no impact on INSERT or UPDATE performance.

False. Indexes improve SELECT speed but slow down INSERT and UPDATE because they need to be maintained.

intermediate

What is a good practice to balance index use for fast queries and acceptable INSERT/UPDATE speed?

Create indexes only on columns frequently used in queries and avoid unnecessary indexes on columns that change often.

How do indexes affect the speed of INSERT operations?

A They speed up INSERT operations

B They slow down INSERT operations

C They have no effect on INSERT operations

D They prevent INSERT operations

Indexes slow down INSERT operations because the database must update the index data structures for each new row.

Which type of operation is most affected by indexes?

A INSERT and UPDATE

B DELETE only

C SELECT only

D No operations are affected

INSERT and UPDATE operations are affected because indexes must be updated when data changes.

If you update a column that is part of an index, what happens?

A The update fails

B The index is ignored

C The index is automatically updated

D The index is deleted

The database updates the index entries to reflect the new values.

What is a downside of having many indexes on a table?

A Indexes get ignored

B Faster INSERT and UPDATE

C No change in performance

D Slower INSERT and UPDATE

More indexes mean more work to update them during data changes, slowing down INSERT and UPDATE.

What should you consider when creating indexes to balance performance?

A Index only frequently queried columns

B Index only columns that never change

C Never use indexes

D Index every column

Indexing frequently queried columns improves SELECT speed without overly slowing INSERT and UPDATE.

Explain how indexes impact the performance of INSERT and UPDATE operations in a database.

Think about what happens behind the scenes when data changes.

Describe best practices for using indexes to balance query speed and data modification performance.

Consider when indexes help and when they cause slowdowns.

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