Performance tuning FAQ

Of course. Here are 20 scenario-based interview questions about database performance tuning, along with detailed answers.

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Scenario-Based Questions and Answers

Scenario 1: Slow-Running Report

Question: A critical daily report that used to run in 5 minutes now takes over an hour. You haven't changed the query. What are the first three things you investigate?

Answer:

1. Check for data volume growth: The amount of data has likely increased significantly. A query that performed well on a small dataset might be inefficient on a large one, especially if it relies on full table scans or poor join strategies.

2. Look for index issues: The indexes might have become fragmented due to high data turnover (inserts, updates, deletes). You would check the fragmentation level and rebuild or reorganize them if necessary.

3. Investigate statistics freshness: Outdated statistics can lead the query optimizer to choose a bad execution plan. You would check the last update time of table and index statistics and update them to reflect the current data distribution.

Scenario 2: High CPU Usage

Question: The database server's CPU usage is consistently at 95% during peak hours, causing slow application response times. How do you identify the root cause?

Answer:

You would use database performance monitoring tools to identify the top resource-consuming queries. You can query system views (like sys.dm_exec_query_stats in SQL Server or pg_stat_statements in PostgreSQL) to find the queries with the highest CPU time. Once identified, you'd analyze their execution plans to pinpoint inefficient operations, such as full table scans or complex sorts, and tune them by adding or modifying indexes.

Scenario 3: Application Deadlocks

Question: The application team reports frequent deadlocks, causing transactions to fail randomly. What steps do you take to troubleshoot and fix this problem?

Answer:

First, you'd enable deadlock tracing or logging to capture a deadlock graph. The graph will show you the two transactions involved, the resources (tables or rows) they are trying to lock, and the order of their requests. The solution usually involves one of these strategies:

• Modify transaction logic: Ensure all transactions acquire locks in the same, consistent order to prevent a circular wait.

• Reduce transaction scope: Make transactions as short as possible to minimize the time locks are held.

• Use a different isolation level: In some cases, changing the transaction isolation level (e.g., from SERIALIZABLE to READ COMMITTED) can reduce the frequency of locks.

Scenario 4: Slow INSERT Operations

Question: A nightly batch job that inserts millions of rows is taking too long. What could be the issue, and how would you optimize it?

Answer:

The problem is often related to indexes and constraints. Every INSERT operation must update all indexes on the table, which can be very slow.

• Drop and recreate indexes: For a large bulk load, it's often faster to drop all non-clustered indexes, perform the inserts, and then recreate them after the data is loaded.

• Disable constraints: Temporarily disable foreign key and check constraints during the load and re-enable them after, as this saves time by not checking every inserted row.

• Batching: If possible, insert the data in smaller batches instead of a single massive transaction to reduce the size of the transaction log and memory pressure.

Scenario 5: High Disk I/O

Question: The database server's disk I/O is consistently high, slowing down the entire system. How do you find the source of the I/O bottleneck?

Answer:

You would use system monitoring tools and database performance views to identify the objects causing the high I/O.

• Find I/O-intensive queries: Look for queries performing a high number of logical or physical reads. The WHERE and JOIN clauses of these queries are good candidates for index optimization.

• Check for full table scans: High I/O is often a symptom of full table scans, where the database has to read a huge amount of data from disk.

• Analyze index usage: Verify if the most I/O-intensive tables have proper indexes on the columns used in their WHERE and JOIN clauses. A missing index is a common culprit.

Scenario 6: Inefficient Joins

Question: A query joining five large tables is taking a long time. The execution plan shows a NESTED LOOPS join on two very large tables. Is this a good sign, and how would you fix it?

Answer:

A NESTED LOOPS join is efficient only when the outer table is small. In this case, with two large tables, it's a very poor choice, as the inner table is scanned for every row of the outer table.

You would investigate if there are proper indexes on the join columns of the inner table. A lack of an index forces a table scan. The query optimizer may have also picked the wrong join order. You could add an index to the inner table's join column, which would enable a more efficient join method like a MERGE or HASH join.

*Scenario 7: The "SELECT " Problem

Question: A developer is using SELECT * in many queries. Explain why this is a performance problem and what you would advise.

Answer:

Using SELECT * is problematic because:

• Increased Network Traffic: It sends unnecessary data over the network, which can be a significant bottleneck for large result sets.

• Inefficient I/O: The database has to read more data pages from disk than necessary.

• Prevents Covered Indexes: The query optimizer cannot use a covered index (an index that contains all the required columns) because SELECT * forces it to fetch every column from the base table.

  You would advise the developer to explicitly list only the columns they need in their SELECT statement.

Scenario 8: Parameter Sniffing Issue

Question: A stored procedure runs fast for some users but is very slow for others. You suspect a parameter sniffing problem. What is it, and how can you resolve it?

Answer:

Parameter sniffing is when the query optimizer creates an execution plan based on the very first parameter value it "sniffs" when the procedure is first executed. If subsequent parameter values are skewed (e.g., the first user queries a rare value, and the next user queries a very common value), the cached plan may be inefficient for the second user.

To resolve this, you can:

• Use the RECOMPILE option on the stored procedure to force a new plan for every execution.

• Use OPTION (RECOMPILE) within the query itself.

• Use OPTIMIZE FOR UNKNOWN or declare local variables to copy parameter values, which prevents the optimizer from sniffing the initial value.

Scenario 9: Table with Many Columns

Question: You have a table with over 100 columns, and queries on it are slow. What's the potential issue?

Answer:

A table with a very high number of columns can lead to page splitting. When you update a row, the database may need to move it to a new page to accommodate the change. This can increase I/O and reduce performance. A common solution is to consider horizontal or vertical partitioning. Vertical partitioning involves splitting the table into multiple smaller tables, with frequently accessed columns in one table and rarely accessed ones in another.

Scenario 10: Missing Foreign Key Indexes

Question: You notice a query joining two tables on their foreign key columns is slow. You check, and there is no index on the foreign key column in the child table. Why is this a problem?

Answer:

While a primary key is automatically indexed, a foreign key is not. A foreign key without an index can cause JOINs and DELETE operations on the parent table to perform a full table scan on the child table to check for related rows, which is extremely inefficient and a common performance bottleneck. Adding an index on the foreign key column is the correct solution.

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Continue with a few more scenarios as needed.

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MySQL Performance Tuning: A Comprehensive Guide

MySQL performance tuning is a critical aspect of database administration. ¹ It involves optimizing various factors to ensure optimal performance and efficient resource utilization. ² Here are some key strategies to consider:  

1. Database Design and Schema Optimization

• Normalize Your Data: Break down complex data into simpler, normalized tables to reduce redundancy and improve data integrity.   
• Choose Appropriate Data Types: Select data types that match the data you're storing to minimize storage space and improve query performance.   
• Index Strategically: Create indexes on frequently queried columns to speed up data retrieval. However, avoid over-indexing as it can slow down insert, update, and delete operations.   

2. Query Optimization

• Write Efficient Queries:
  • Minimize the number of queries executed.
  • Use EXPLAIN to analyze query execution plans.
  • Avoid SELECT * and specify only the necessary columns.
  • Use LIMIT and OFFSET clauses judiciously.
  • Optimize JOIN operations.
  • Leverage subqueries and common table expressions (CTEs) effectively.   
• Indexing:
  • Create indexes on columns frequently used in WHERE, JOIN, and ORDER BY clauses.
  • Consider composite indexes for multiple columns.
  • Regularly analyze and optimize indexes.   

3. Hardware and Configuration Optimization

• Hardware:
  • Ensure sufficient CPU, RAM, and disk I/O capacity.   
  • Use solid-state drives (SSDs) for faster data access.   
• MySQL Configuration:
  • Tune MySQL configuration parameters like innodb_buffer_pool_size and innodb_log_file_size.
  • Adjust connection pool settings to handle concurrent connections efficiently.   
  • Optimize memory usage to reduce disk I/O.   

4. Monitoring and Profiling

• Use MySQL's Built-in Tools:
  • SHOW STATUS and SHOW GLOBAL STATUS to monitor server status.
  • EXPLAIN to analyze query execution plans.
  • SLOW QUERY LOG to identify slow-running queries.
• Third-Party Tools:
  • Use tools like Percona Monitoring and Management (PMM) for advanced monitoring and analysis.   

5. Caching

• Query Cache: Enable the query cache to store query results and reuse them.   
• Application-Level Caching: Use caching mechanisms in your application to reduce database load.   

6. Regular Maintenance

• Database Backups: Regularly back up your database to protect against data loss.   
• Optimize Tables: Periodically optimize tables to reclaim unused space.   
• Monitor and Tune: Continuously monitor your database's performance and make adjustments as needed.   

By following these guidelines and leveraging the tools available, you can significantly improve the performance of your MySQL database and ensure optimal application performance.

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MySQL performance tuning 

MySQL performance tuning is the process of optimizing MySQL queries and database systems to improve performance and efficiency. Here are some tips for improving MySQL performance: 

• Indexing:                                       Use appropriate indexing to reduce fetch time. Choose the right data types for indexed columns. 
• Query optimization:               Optimize SELECT statements and avoid SELECT *. Specify only the columns you need. Use joins instead of subqueries. 
• Database schema:                   Normalize your database schema. 
• Resource utilization:               Monitor and analyze resource utilization. 
• Hardware:                                    Tune MySQL for your hardware. 
• Storage engine:                         Switch to the MySQL InnoDB storage engine instead of MyISAM. 
• Version:                                          Update MySQL to the latest version. 
• Performance improvement tools: Use automatic performance improvement tools. 
• Explain function:                      Use the Explain command to understand query execution. 
• GROUP BY:                                   Use GROUP BY instead of SELECT DISTINCT. 
• Predicates:                                  Avoid functions in predicates and avoid wildcard (%) at the beginning of predicates. 
• DISTINCT and UNION:           Use DISTINCT and UNION only if necessary. 
• Select clause:                            Avoid unnecessary columns in the select claus

 

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Oracle Performance Tuning Interview Questions for Freshers

1. What is Performance Tuning?

Ans: Making optimal use of the system using existing resources is called performance tuning.

If you would like to become a professional and build a career in this domain, then visit Mindmajix - a global online training platform: Oracle Performance Tuning Training This course will help you to achieve excellence in this domain.

2. What are the different types of Tunings?

Ans:

1. CPU Tuning
2. Memory Tuning
3. IO Tuning
4. Application Tuning
5. Database Tuning

3. What Mainly Database Tuning contains?

Ans:

1. Hit Ratios
2. Wait for Events

4. What is an optimizer?

Ans: Optimizer is a mechanism that will make the execution plan of an SQL statement

5. Types of Optimizers?

Ans:

1. RBO(Rule-Based Optimizer)
2. CBO(Cost Based Optimizer)

6. Which init parameter is used to make use of Optimizer?

Ans: optimizer_mode= rule—-RBO cost—CBO choose——–First CBO otherwise RBO

7. Which optimizer is the best one?

Ans: CBO

 

8. What are the pre-requested to make use of Optimizer?

Ans:

1. Set the optimizer mode
2. Collect the statistics of an object

9.