Recently, One of our client reached our Remote DBA team with a requirement to reduce the size of the table as it is having many text columns with huge number of records. At preliminary check , I have validated the table size and its row format, as it was  in compressed  format already. 

Later I checked on other possibilities to compress the text columns further, At that time, then I came across per-column compression feature in Percona MySQL server (From 5.7.17-11) which features individual column compression and we were using …

Overview The Skinny

In this blog post we explore various options for performance tuning MySQL server for better slave replication performance.

A Tungsten Cluster relies upon the Tungsten Replicator to move events from the master node to the slaves. Once the event has been transferred to the slave as THL on disk, the slave applier will then attempt to write it to the database. The Replicator can only apply events as fast as MySQL allows. If the MySQL server is somehow slow or blocking, then the Replicator will be as well.

A properly-tuned database server in addition to infrastructure and SysAdmin best practices will go quite a long way towards high-performance slave apply.

The Question Recently, a customer asked us:

During one of our load tests, we had a peak of 60k writes/min, averaging …

As people are getting back from vacations and application traffic is going back and hitting database backend hard, it is a good time to think about performance and prepare for the winter holiday spike. Whenever you are on-premise or in the cloud, questions are the same:

• Are we satisfied with the current MySQL performance?
• How much traffic are we currently serving?
• Is there enough capacity to stay stable as traffic increases?
• What would be the best way to stay cost-effective as we grow?

Unfortunately, the answers are not so obvious and require a thorough performance analysis. However, there is a chance that your problem has already been solved by someone else. I do not mean StackOverflow (which is a beautiful place, by the way), but some higher level questions which people usually discuss at conferences, and we have several of them ongoing or just a couple of weeks away.

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Author: Robert Agar

MySQL is one of the most popular relational database platforms in the world. As such, it is used as the backend of many mission-critical applications across all sectors of business and industry. If you are a DBA or database developer there is a high probability that you are working with MySQL now or will be in the near future.

One of the primary responsibilities of a DBA is to optimize the performance of their databases. There are many ways to accomplish this feat, and all of them have an important point in common. You need knowledge concerning the operation of your systems before you can expect to make intelligent modifications to them. All of the methods used to tune and optimize your databases are identified by studying metrics regarding their current performance and using this data to plan appropriate action.

The right tools are required to gather the information needed to …

Late one evening, I was staring at one of our large MySQL installations and noticed the database was hovering around 7-10 run queue length (48 cores, ~500 gigs memory, fusionIO cards). I had been scratching my head on how to get more throughput from the database. This blog records the changes I made to tune performance in order to achieve a 300% better throughput in MySQL. I tested my theories on MySQL 5.6/Maria 10.1. While with 5.7 DBAs would turn to performance_schema for the supporting metrics, I hope that you find the process interesting nevertheless.

View from an Oracle RDBMS DBA…

For context, I came to MySQL from a background as an Oracle RDBMS DBA, and this informs my expectations. For this exercise, unlike with Oracle RDBMS, I had no access to view wait events so that I could see where my database was struggling. At least, no access in MySQL 5.6/Maria 10.1 without taking a performance hit by using …

Please join Percona CEO Peter Zaitsev as he presents “Performance Analyses and Troubleshooting Technologies for Databases” on Wednesday, August 7th, 2019 at 11:00 AM PDT (UTC-7).

Register Now

Have you heard about the USE Method (Utilization – Saturation – Errors), RED (Rate – Errors – Duration) or Golden Signals (Latency – Traffic – Errors – Saturations)?

In this presentation, we will talk briefly about these different-but-similar “focuses” and discuss how we can apply them to data infrastructure performance analysis troubleshooting and monitoring.

We will use MySQL as an example, but most of this talk applies to other database technologies as well.

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Sometimes, the MySQL Optimizer chooses a wrong plan, and a query that should execute in less than 0.1 second ends-up running for 12 minutes !  This is not a new problem: bugs about this can be traced back to 2014, and a blog post on this subject was published in 2015.  But even if this is old news, because this problem recently came yet again to my attention, and because this is still not fixed in MySQL 5.7 and 8.0, this is a subject worth writing about.

The MySQL Optimizer

Before looking at the problematic query, we have to say a few words about the optimizer.  The Query Optimizer is the part of query execution that chooses the query plan.  A Query Execution Plan is the way MySQL chooses to execute a specific query.  It …

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MySQL Connector/Python 8 made the C Extension the default for the platform/Python version combinations supporting it. One thing that was missing from the C Extension implementation (unless you used the _mysql_connector module) was support for prepared statements. That has been taken care of with the release of version 8.0.17.

The two main advantages of using prepared statements are security and performance. The security comes in as you can pass query parameters and have them applied server-side, so you are sure they are quoted and escaped correctly taking the data type into consideration. The performance benefit happens, when you execute the same query (except for the parameters) several times as MySQL will prepare it only …

Are you looking to get started with the world’s most popular open-source database, and wondering how you should setup your MySQL hosting? So many default to Amazon RDS, when MySQL performs exceptionally well on Azure Cloud. While Microsoft Azure does offer a managed solution, Azure Database, the solution has some major limitations you should know about before migrating your MySQL deployments. In this post, we outline the best way to host MySQL on Azure, including managed solutions, instance types, high availability replication, backup, and disk types to use to optimize your cloud database performance.

MySQL DBaaS vs. Self-Managed MySQL

The first thing to consider when weighing between self-management and a MySQL Database-as-a-Service …

MySQL has introduced the concept of functional index in MySQL 8.0.13. It is one of the much needed feature for query optimisation , we have seen about histogram in my last blog. Let us explore the functional index and its use cases.

For the below explanation, I have used a production scenario which has 16 core cpu, 32GB RAM and with MySQL version 8.0.16(Latest at the time of writing).

MySQL do support indexing on columns or prefixes of column values (length).

Example: 

mysql>show create table app_user\G
*************************** 1. row ***************************
Table: app_user
Create Table: CREATE TABLE `app_user` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`ad_id` int(11) DEFAULT NULL,
`source` varchar(32) DEFAULT NULL,
`medium` varchar(32) DEFAULT NULL,
`campaign` varchar(32) DEFAULT NULL,
`timestamp` …