InnoDB depends on operating system threads to process the requests from user transactions, These transactions include requests to InnoDB before commit or rollback. The modern operating systems and servers with multi-core processors, where context switching is efficient, most workloads run well without any limit on the number of concurrent threads. InnoDB can efficiently control the number of concurrently executing operating system threads (and thus the number of requests that are processed at any one time) to minimize context switching between threads. if the number of threads concurrently executing is at a pre-defined limit, the new request sleeps for a short time before it tries again. The requests which cannot be rescheduled after the sleep is put in a first-in/first-out queue and eventually is processed. Threads waiting for locks are not counted in the number of concurrently executing threads.To limit the number of …[Read more]
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Please join Percona’s Principal Support Escalation Specialist Sveta Smirnova as she presents Troubleshooting Best Practices: Monitoring the Production Database Without Killing Performance on Wednesday, June 27th at 11:00 AM PDT (UTC-7) / 2:00 PM EDT (UTC-4).
During the MySQL Troubleshooting webinar series, I covered many monitoring and logging tools such as:
- General, slow, audit, binary, error log files
- Performance Schema
- Information Schema
- System …
Since MySQL 5.7.5, we have been able to resize dynamically the InnoDB Buffer Pool. This new feature also introduced a new variable — innodb_buffer_pool_chunk_size — which defines the chunk size by which the buffer pool is enlarged or reduced. This variable is not dynamic and if it is incorrectly configured, could lead to undesired situations.
Let’s see first how innodb_buffer_pool_size , innodb_buffer_pool_instances and innodb_buffer_pool_chunk_size interact:
The buffer pool can hold several instances and each instance is divided into chunks. There is some information that we need to take into account: the number of instances can go from 1 to 64 and the total amount of chunks should not exceed 1000.
So, for a server with 3GB RAM, a buffer pool of 2GB with 8 instances and chunks at default value (128MB) we are going to get 2 chunks per instance:
This means that there will be 16 chunks.
This post is about a very simple approach / step-by-step InnoDB log (aka transaction logs)resize, We don’t do this activity regularly but when we have to resize InnoDB log files, there will be a MySQL downtime. This post will be a like a checklist for anyone who want to resize InnoDB log files without any mistakes, We made this task in multiple steps so that you can follow much better:
Step 1 – Check existing logs and their size:
[root@localhost ~]# lsof -c mysqld | grep ib_logfile mysqld 1018 mysql 5uW REG 253,0 50331648 180228 /var/lib/mysql/ib_logfile0 mysqld 1018 mysql 11uW REG 253,0 50331648 180229 /var/lib/mysql/ib_logfile1
Step 2 – Shutdown MySQL
[root@localhost ~]# systemctl stop mysqld [root@localhost ~]# systemctl status mysqld ● mysqld.service - MySQL Server Loaded: loaded …[Read more]
In transaction processing systems we have to guarantee the transaction committed will be durable permanently. For example, In an online commerce platform, The completed transaction will remain safe even if the system crashes. This can be achieved by flushing the transactional log records to non-volatile storage devices before acknowledging the commit. MySQL guarantees maximum durability of transaction by optimally setting following system variables :
innodb_doublewrite (enabled by default)
InnoDB stores all data twice, first to doublewrite buffer (storage area in system tablespace to write pages that are flushed from InnoDB buffer pool, before written in data file). If ever operating system / storage / mysqld process crash during the middle of page write, InnoDB can still find a durable copy of the page from doublewrite buffer for recovery. Though data is written twice, the doublewrite buffer …[Read more]
We often enable MySQL slow_query_log to proactively troubleshoot the performance, There is so lot of information with-in slow_query_log which is enough to address most common (even complex ones occasionally) MySQL performance bottlenecks. What if we haven’t planned for the log lifecycle management of slow query log ? Your log will really grow huge (we keep long_query_time as-low-as 1 second), So we have to plan for slow_query_log rotating to avoid MySQL outage due to “no space left in the disk” to grow further. There are two ways you can do log rotate, I have explained below:
- Manual log rotating (We use it only when there is an emergency)
- Using logrotate to automatic MySQL log rotation (We love it, MinervaDB is an big fan of MySQL automation & DevOps. but we also recommend to use it very carefully)
Step-by-step manual log rotating …[Read more]
To change the number or the size of your InnoDB redo log files, please follow the steps below:
Step 1: Stop the MySQL server and confirm that it has shutdown without any errors
Step 2: Edit my.cnf to configure innodb_log_file_size (log file size) and innodb_log_files_in_group (number of log files)
Step 3: Restart MySQL server
If ever InnoDB finds innodb_log_file_size differs from the redo log files, It writes a log checkpoint, closes and removes the old log files, create again new log files at requested size and opens the new log files.
The post How to change the number or size of InnoDB Redo Log Files ? appeared first on MySQL Consulting, …[Read more]
This blog compares how PostgreSQL and MySQL handle millions of queries per second.
Anastasia: Can open source databases cope with millions of queries per second? Many open source advocates would answer “yes.” However, assertions aren’t enough for well-grounded proof. That’s why in this blog post, we share the benchmark testing results from Alexander Korotkov (CEO of Development, Postgres Professional) and Sveta Smirnova (Principal Technical Services Engineer, Percona). The comparative research of PostgreSQL 9.6 and MySQL 5.7 performance will be especially valuable for environments with multiple databases.
The idea behind this research is to provide an honest comparison for the two popular RDBMSs. Sveta and Alexander wanted to test the most recent versions of both MySQL and PostgreSQL with the same tool, under the same challenging …[Read more]
1. Tune those queries
By far the biggest bang for your buck is query optimization. Queries can be functionally correct and meet business requirements without being stress tested for high traffic and high load. This is why we often see clients with growing pains, and scalability challenges as their site becomes more popular. This also makes sense. It wouldn't necessarily be a good use of time to tune a query for some page off in a remote corner of your site, that didn't receive real-world traffic. So some amount of reactive tuning is common and appropriate.
Enable the slow query log and watch it. Use …[Read more]
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