If your database is running slow, it can affect the performance and user experience of your applications. You need to monitor your database performance to identify and troubleshoot the root causes of any issues. In this article, you will learn how to use some common tools and methods to monitor your database performance.
One of the first steps to monitor your database performance is to collect and analyze some basic metrics, such as CPU usage, memory usage, disk space, network latency, and query response time. These metrics can help you understand the overall health and workload of your database server. You can use built-in tools, such as Windows Performance Monitor or Linux top command, to view these metrics in real time or over a period of time. You can also use third-party tools, such as Datadog or SolarWinds, to visualize and alert on these metrics.
There may be various factors involved into a database become very slow. It could be I/O performance, high CPU Usage, Memory, Missing Indexes and Update Statistics. You can run SQL Profiler is a handy tool to capture query execution plan and monitor proactively other than that use DMVs, Activity Monitor(SSMS) to identify the slow performance issue and resolve it.
Uma boa forma de monitorar o seu desempenho é realizar a cria??o de um dashboard. Contendo os KPI's: Percentual de processamento, percentual de uso de disco e memória, quantidade de objetos inválidos, locks, cursores abertos por instancia. Em paralelo monitorar os processos que mais consomem recurso do banco e realizar tunning no código e verificar os índices. Por fim verificar se o mesmo possuir um bom plano de execu??o melhor a nível de banco.
There are several reasons that one database became slow. CPU, I/O, Network, bad query plans, new database version, and new version from application. It is important to understand what changed, if slowness was unexpected or gradually been bad every day. You can use several tools to proactively monitor databases using scripts like Zabbix and Nagios. Tools to identify trends like Grafana. You can create your own scripts and integrate too. Metrics for CPU usage, cursor cache hits (ratio for hard parses and soft parses), IOPS (read and writes), I/O (reads/writes mb/s), latches and pools waits (to check resources availability and responsiveness), network in/out, and number of executions are good metrics to check regularly.
If your database is running slow, you need to monitor its performance and identify the possible bottlenecks: - CPU utilization: A high CPU utilization can indicate that the database is processing a lot of queries or performing complex calculations. - Memory usage: A high memory usage can indicate that the database is caching a lot of data or handling large transactions. - Disk I/O: A high disk I/O can indicate that the database is performing a lot of disk operations, such as reading from tables, writing to logs, or flushing buffers. - Network I/O: A high network I/O can indicate that the database is communicating with a lot of clients or other servers. You can use tools like netstat to monitor the network I/O of your database process.
We can start by collecting and analyzing basic metrics such as CPU usage, memory usage, disk space, network latency, and query response time. This metrics will help us to understand the overall health of the database server. We can use built in tools like task manager, Perfmon etc. We can also use third party tools to monitor the same as Scom, SolarWinds etc.
Another important step to monitor your database performance is to analyze the queries that are running on your database. Queries are the main source of interaction and data manipulation between your database and your applications. You need to identify the queries that are taking too long, consuming too much resources, or causing errors or locks. You can use tools, such as SQL Server Profiler or MySQL Workbench, to capture and analyze the query execution plans, which show how the database engine processes the queries. You can also use tools, such as SQL Sentry or Percona Toolkit, to monitor and optimize the query performance.
The most common cause of locks are transactions. When analyzing queries, you might notice that sometimes a query runs quickly, but other times it's really slow. In this case, there might be another query that is blocking this one. So the slow query does not use a lot of system resources. Transaction locks can be prevented by using the appropriate isolation level. In general, you should avoid long-running transactions in order to prevent locking. Try to keep transactions as short as possible, and commit or roll back them as soon as the work is done.
Query analysis is a process of examining the queries that are executed on your database and identifying the ones that are slow, inefficient, or problematic. Query analysis can help you find and fix issues such as missing indexes, suboptimal joins, excessive locking, or excessive memory usage. Query analysis can also help you optimize your queries for better performance and scalability.
To monitor the performance of a slow-running database, analyzing the queries running on the database is crucial. Identify queries that consume the most CPU, memory, or disk I/O. They might not be slow individually, but their cumulative impact can affect performance. Tools like SQL Server Profiler or MySQL Workbench capture query execution details, helping you analyze execution plans and resource usage.
Database Profiling: Enable database profiling to capture information about slow queries.Analyze the profiling data to identify queries that are taking a long time to execute.
You also MUST understand how the query optimizer works within your particular database, its release level, and the hardware it is running against. For example, an Oracle DB running on standalone hardware may need to be tuned for fewer full table scans ... but if you're running on Exadata Database Machine, full table scans may actually be desirable b/c that platform is designed to handle FTSs within its storage cells. Understand WHY the database works the way it does on the hardware it's running on!
One of the factors that can affect your query performance is the indexing and fragmentation of your database tables. Indexes are data structures that help the database engine find and retrieve data faster. However, indexes can also become fragmented over time, due to data changes, deletions, or updates. Fragmented indexes can slow down your queries and increase the disk space and memory usage. You need to monitor the index usage and fragmentation levels, and perform regular maintenance tasks, such as rebuilding or reorganizing the indexes. You can use tools, such as SQL Server Management Studio or Oracle Enterprise Manager, to view and manage the indexes and fragmentation.
Queries can become bad unexpectedly not just because of bad indexes but also when the data change. Example is when the query plan/indexes works when you have few records. But when an application loads thousands of records the previous indexes maybe are not effective anymore. Maybe because statistics are not updated or they really become not efficient (not filtering the data anymore) and the database optimizer needs to pass the whole table. So, query plans can change even if nothing (indexes, parameters, or table design) changed.
Rebuilding involves dropping and recreating indexes. For some reasons, reorganizing indexes can be preferred to rebuilding (especially in SQL Server): - Reorganizing does not affect the statistics. But rebuilding an index will result in invalidation of any execution plans using the index. So SQL Server will need to generate a new execution plan on next run. Since the optimizer does not use the information of the index fragmentation, regenerating statistics and execution plans makes no sense. - During offline rebuilding, the index table is inaccessible (can be avoided by online rebuilding). When reorganizing fails to resolve fragmentation (highly fragmented indexes), rebuilding might come in handy.
Indexing helps to speed up queries by creating pointers to the data, while fragmentation occurs when the data is scattered across different pages. High fragmentation can reduce the efficiency of indexing and slow down your database. You can use tools such as SQL Server Management Studio or Database Engine Tuning Advisor to analyze and optimize your indexes and fragmentation.
Un des éléments qui peuvent influencer les performances de vos requêtes est l’indexation et la fragmentation des tables de votre base de données. Les index sont des structures de données qui aident le moteur de base de données à trouver et à extraire des données plus vite. Mais les index peuvent aussi se fragmenter avec le temps, à cause de changements, de suppressions ou de mises à jour de données. Les index fragmentés peuvent ralentir vos requêtes et augmenter l’espace disque et l’usage de la mémoire. Vous devez contr?ler l’usage et les niveaux de fragmentation des index, et faire des taches de maintenance régulières, comme la reconstruction ou la réorganisation des index.
Another factor that can affect your query performance is the deadlocks and locks that occur on your database. Deadlocks are situations where two or more queries are waiting for each other to release a resource, such as a table or a row. Locks are mechanisms that prevent concurrent access to a resource, to ensure data consistency and integrity. However, deadlocks and locks can also block or delay your queries, and cause errors or timeouts. You need to monitor the deadlocks and locks that are happening on your database, and resolve them by changing the query logic, order, or isolation level. You can use tools, such as SQL Server Activity Monitor or MySQL InnoDB Monitor, to detect and troubleshoot the deadlocks and locks.
One point that is important to monitor is how much time sessions are active and doing query processing. The lock occurs when two sessions try to access the same record (Oracle is row level lock), so, if your monitor long time running queries you can proactively identify sessions that can potentially lock records because they have not executed yet the commit/rollback. Monitor inactive sessions that hold locks over objects need to be monitored too. They denote application errors that are not closing sessions by commit/rollback. So, monitoring these points proactively will help to avoid locks over concurrent sessions. Lastly, check if your table foreign keys has indexes to avoid full table locks during inserts and deletes.
SQL Server Profiler, which can capture and analyze the queries and events that occur on your database server. You can use filters and traces to focus on the aspects of performance that interest you, such as deadlocks and locks. Deadlocks occur when two or more transactions are waiting for each other to release a resource, and neither can proceed. Locks are mechanisms that prevent concurrent access to the same data by different transactions, and they can affect performance if they are held for too long or cause blocking. By monitoring deadlocks and locks, you can find out which queries are causing them, how often they occur, and how long they last.
Deadlocks and locks can be significant performance bottlenecks in a database. deadlocks arise when two or more queries wait for each other to release a resource, creating a stalemate. This can lead to significant delays, timeouts, and user frustration. Tools such as activity monitor, SQL Server Profiler, can be used to find the deadlocks and locks. We can also use TSQL script to find the same. Deadlock will get logged in SQL Server Error-log as well if we have trace 1222 and 1204 enabled.
The top things I can think of in Identifying and resolving deadlocks in a MySQL database involves a combination of monitoring, analyzing logs, and optimizing queries and transactions. Regularly reviewing logs and using the available tools will help you pinpoint the root causes and take appropriate actions to mitigate deadlocks. Another thing that might help is createing a Deadlock Detection in your application, implement deadlock detection and retry mechanisms in your application code. When a deadlock is detected, your application can automatically retry the affected transaction.
Un autre élément qui peut influer sur les performances de vos requêtes est la quantité de blocages et de verrous qui surviennent sur votre base de données. Les interblocages sont des cas où deux requêtes ou plus se bloquent mutuellement en attendant qu’une ressource, comme une table ou une ligne, se libère. Les verrous sont des dispositifs qui protègent une ressource contre les accès concurrents, pour assurer la cohérence et l’intégrité des données. Mais les interblocages et les verrous peuvent aussi gêner ou ralentir vos requêtes, et entra?ner des erreurs ou des temps morts.
The final step to monitor your database performance is to check the database configuration settings, such as the memory allocation, cache size, buffer pool, log file, recovery model, and backup strategy. These settings can have a significant impact on your database performance, as they determine how the database engine manages the data and transactions. You need to review and adjust these settings according to your database size, workload, and requirements. You can use tools, such as SQL Server Configuration Manager or MySQL Server Variables, to view and modify the database configuration settings.
Reviewing and adjusting database configuration settings is also crucial for optimal performance. * Memory allocation * Cache size * Log file * Recovery model * Backup strategy * Cost degree of threshold. * Degree of parallelism * Autogrowth * Number of data files * Ports Tools like SQL Server Configuration Manager or MySQL Server Variables allow you to view and modify configuration settings. Tools like SQL Server Management Studio or MySQL Workbench can provide metrics related to memory usage, cache size, and disk I/O. After adjusting any configuration settings, it's crucial to test and monitor the impact on performance and stability.
it’s usually just bad code and/or missing indexes!!! You could also look at configuration settings including disks (slow fast depending on the requirements)
Most importantly: If you haven't started AT THE BEGINNING of this exercise in steps 1-4 previous, don't go rushing over to database initialization parameters and messing around with them unless you understand +precisely+ what each one does. I've seen DBAs do that with multiple parameter changes and then forget to reset them to whatever they were originally, thus affecting dozens or hundreds of other SQL statements that had been running just fine. In other words: Stop tuning your database by doing "the Google, the cut, and the paste." That way lies madness. Understand first WHY the database works the way it does!
To monitor and improve MySQL database performance, follow these steps: Enable MySQL Performance Schema. Analyze query performance and optimize slow queries. Monitor index usage and remove redundant indexes. Use performance tuning tools and MySQL Workbench. Monitor InnoDB storage and defragment tables. Profile the database to identify resource-intensive queries. Follow indexing best practices and update statistics. Implement caching mechanisms to reduce load. Use monitoring tools for continuous performance tracking. Consider hardware scaling or partitioning for scalability. Schedule regular maintenance tasks.
Pour optimiser les performances de votre base de données, vous devez aussi contr?ler les paramètres de configuration de la base de données, comme l’allocation de mémoire, la taille du cache, le pool de mémoires tampons, le fichier journal, le mode de récupération et la stratégie de sauvegarde. Ces paramètres peuvent influencer fortement les performances de votre base de données, car ils définissent comment le moteur de base de données traite les données et les transactions. Vous devez vérifier et modifier ces paramètres selon la dimension de votre base de données, votre charge de travail et vos exigences.
Most importantly: Make sure your DevOps team members understand how to build and test queries and statements effectively. I've walked into large shops where the end users complained incessantly about their Oracle query performance ... but didn't even understand the basics of their database's optimizer and how to realize their shitty code was really at fault. Here's a hint: When you ask your developer "What did the EXPLAIN PLAN show when you tested your query?" and they reply "What's an EXPLAIN PLAN?" ... you have some extra training to do, my friends.
Server Hardware:Ensure that your server hardware meets the recommended specifications for your database workload.Consider upgrading hardware if it's a bottleneck. Caching:Implement caching strategies to reduce the load on your database.Use caching mechanisms at the application level or consider solutions like Redis for caching.
Use every instance of the database being slow to capture information (CPU, memory, disk I/O, user load, query load, ODBC connections, etc) - look for patterns of activity including time of day, day of the week, etc. Build a dashboard that shows the health of each element being monitored - preferably with color coding of contributors. Ideally, setup monitoring and alerting ahead of time so that known contributors to to slow performance are identified and handled well before users are reporting slow performance. Have a well documented and managed/followed change control process (including communication of upcoming changes). Ensure you have the ability to quickly review & access impact of changes that may contribute to performance issues.
It is important to define the baseline. Identify a good day in the history and compare with the bad day. Ask the user to provide more info than just "is slow". Do questions like "every day slow?", "when you notice that it becomes slow?", "application changes during the last days?", "it occurs every time?". These questions will help to troubleshoot the issue and create a baseline.
It is important to understand that this process is not once done-and-forget thing. As a DBA, one would need to keep monitoring the DB metrics and query executions (especially, the top 5/10 heavyweight ones). The DB response will keep on changing as the application and the data evolves. It's always better to take preventive measures rather than trying to put out fire when all the DB breaks.