Query execution plans in DBMS Theory - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding the purpose of a query execution plan

What is the main purpose of a query execution plan in a database management system?

A To show the step-by-step operations the database will perform to execute a query

B To store the results of a query permanently

C To encrypt the data retrieved by a query

D To create a backup of the database before running a query

💡 Hint

Think about how the database decides to get data efficiently.

A query execution plan details the steps and methods the database engine uses to retrieve data for a query. It helps understand and optimize query performance.

📋 Factual

intermediate

Identifying components of a query execution plan

Which of the following is NOT typically part of a query execution plan?

A Data encryption algorithms

B Index scans

C Filter conditions

D Join methods

💡 Hint

Consider what a query execution plan focuses on: data retrieval, not security.

Query execution plans include index scans, join methods, and filter conditions to describe how data is accessed and combined. Encryption is unrelated to execution plans.

🔍 Analysis

advanced

Analyzing query execution plan output

Given a query execution plan showing a full table scan instead of an index scan, what is the most likely impact on query performance?

A There will be no difference in performance

B The query will run faster because full scans use less memory

C The query will likely run slower because scanning the whole table is less efficient

D The query will fail due to missing indexes

💡 Hint

Think about how much data the database reads in each case.

A full table scan reads every row, which is slower than using an index to find specific rows quickly. This usually causes slower query performance.

❓ Comparison

advanced

Comparing join methods in execution plans

Which join method in a query execution plan is generally more efficient for large tables with indexes available?

A Nested loop join

B Merge join

C Cartesian join

D Hash join

💡 Hint

Consider which join method benefits from sorted data and indexes.

Merge joins are efficient for large sorted datasets and can use indexes effectively. Nested loops are better for small datasets, hash joins for unsorted data, and Cartesian joins are usually inefficient.

❓ Reasoning

expert

Interpreting cost estimates in query execution plans

A query execution plan shows a high estimated cost for a particular operation. What does this cost represent?

A The number of rows returned by the query

B The monetary cost charged by the database provider for running the query

C The time in seconds the query will take to complete

D The estimated amount of resources like CPU and I/O the database expects to use for that operation

💡 Hint

Think about what 'cost' means in the context of query planning, not billing or exact time.

The cost in a query execution plan estimates the resources like CPU and disk I/O needed to perform an operation. It helps the optimizer choose the most efficient plan.

Practice

1. What is the main purpose of a query execution plan in a database?

easy

A. To backup the database

B. To show how the database will execute a query step-by-step

C. To create new tables automatically

D. To store the query results permanently

Solution

1. Step 1: Understand what a query execution plan is

   A query execution plan explains the steps the database takes to run a query.

2. Step 2: Identify the main purpose

   The plan helps users see how the database processes the query to optimize performance.

3. Final Answer:

   To show how the database will execute a query step-by-step -> Option B

4. Quick Check:

   Query execution plan = execution steps [OK]

Hint: Execution plans show query steps clearly [OK]

Common Mistakes:

• Confusing plans with data storage
• Thinking plans create tables
• Assuming plans backup data

2. Which SQL command is commonly used to view the query execution plan before running a query?

easy

A. SHOW PLAN

B. RUN

C. EXPLAIN

D. DESCRIBE

Solution

1. Step 1: Recall the command to view execution plans

   The SQL command EXPLAIN is used to display how a query will be executed.

2. Step 2: Differentiate from other commands

   RUN executes queries, SHOW PLAN is not standard, and DESCRIBE shows table structure.

3. Final Answer:

   EXPLAIN -> Option C

4. Quick Check:

   View plan = EXPLAIN [OK]

Hint: Use EXPLAIN to see query plans [OK]

Common Mistakes:

• Using RUN to view plans
• Confusing DESCRIBE with EXPLAIN
• Assuming SHOW PLAN is standard

3. Given the query SELECT * FROM employees WHERE department_id = 5;, what does the execution plan likely show?

medium

A. A full table scan of employees

B. A join operation with another table

C. A sort operation on employee names

D. An index scan on department_id if indexed

Solution

1. Step 1: Analyze the query condition

   The query filters employees by department_id = 5. If department_id has an index, the database uses it.

2. Step 2: Understand execution plan behavior

   If indexed, the plan shows an index scan to quickly find matching rows instead of scanning the whole table.

3. Final Answer:

   An index scan on department_id if indexed -> Option D

4. Quick Check:

   Indexed filter = index scan [OK]

Hint: Indexed columns use index scan in plans [OK]

Common Mistakes:

• Assuming full table scan always happens
• Expecting join when none exists
• Thinking sorting is automatic

4. A query execution plan shows a full table scan but the query filters on a column that has an index. What is the likely cause?

medium

A. The query uses a function on the indexed column

B. The index is corrupted or unusable

C. The database always prefers full scans

D. The table is empty

Solution

1. Step 1: Understand why indexes may be ignored

   If a query applies a function (like LOWER or CAST) on an indexed column, the index cannot be used directly.

2. Step 2: Rule out other options

   Corrupted indexes are rare and usually cause errors; databases do not always prefer full scans; empty tables do not cause full scans.

3. Final Answer:

   The query uses a function on the indexed column -> Option A

4. Quick Check:

   Functions on indexed columns block index use [OK]

Hint: Functions on indexed columns disable index use [OK]

Common Mistakes:

• Assuming index corruption without error
• Believing full scans are default
• Thinking empty tables cause scans

5. You want to optimize a slow query that joins two large tables. The execution plan shows a nested loop join causing delays. What is a good approach to improve performance?

hard

A. Create indexes on the join columns to enable hash or merge joins

B. Remove all indexes to force full table scans

C. Rewrite the query to use subqueries instead of joins

D. Increase the database cache size without changing the query

Solution

1. Step 1: Identify the cause of slow join

   Nested loop joins are slow on large tables without indexes on join columns.

2. Step 2: Apply indexing to improve join method

   Creating indexes on join columns allows the database to use faster join methods like hash or merge joins.

3. Step 3: Evaluate other options

   Removing indexes slows queries; rewriting to subqueries may not help; increasing cache alone may not fix join inefficiency.

4. Final Answer:

   Create indexes on the join columns to enable hash or merge joins -> Option A

5. Quick Check:

   Indexes on join keys speed joins [OK]

Hint: Index join columns to speed up joins [OK]

Common Mistakes:

• Dropping indexes thinking it helps
• Assuming subqueries are always faster
• Relying only on cache size increase