際際滷shows by User: SvetaSmirnova / http://www.slideshare.net/images/logo.gif 際際滷shows by User: SvetaSmirnova / Thu, 18 Apr 2024 17:31:03 GMT 際際滷Share feed for 際際滷shows by User: SvetaSmirnova MySQL 2024: 舒亠仄 仗亠亠仂亟亳 仆舒 MySQL 8, 亠仍亳 于 5. 于 舒亳于舒亠? /slideshow/mysql-2024-mysql-8-5/267334433 mysql2024-240418173103-db326826
25 仂从磡舒 2023 亞仂亟舒 Oracle 仗亠从舒亳仍舒 舒从亳于仆 仗仂亟亟亠亢从 MySQL 5.7. 亅仂 亰仆舒亳, 仂 仂亳 仗亳仄仂亠 从 仍亠仆亳礆 于 于亠亳亳 8: - 仂于仂仄 亳亠仄仆仂仄 仍仂于舒 - 弌仂于亠仄亠仆仆仂仄 SQL - 仂亟亟亠亢从亠 JSON, NoSQL, MySQL Shell, 亳 于仂亰仄仂亢仆仂亳 舒弍仂舒 MySQL 从舒从 MongoDB - 丕仍亠仆亳礆 于 仂仗亳仄亳亰舒仂亠 亰舒仗仂仂于 亳 亟亳舒亞仆仂亳从亠 仂亶 亟仂从仍舒亟 亟仍 舒亰舒弍仂亳从仂于 仗亳仍仂亢亠仆亳亶 仗仂亟 MySQL. 亊 仆亠 弍亟 舒从舒亰于舒 从舒从 从仂仆亳亞亳仂于舒 亠于亠 亳 仂从亳ﾑ 仆舒 亠亞仂 亳仗仂仍亰仂于舒仆亳亳.]]>
25 仂从磡舒 2023 亞仂亟舒 Oracle 仗亠从舒亳仍舒 舒从亳于仆 仗仂亟亟亠亢从 MySQL 5.7. 亅仂 亰仆舒亳, 仂 仂亳 仗亳仄仂亠 从 仍亠仆亳礆 于 于亠亳亳 8: - 仂于仂仄 亳亠仄仆仂仄 仍仂于舒 - 弌仂于亠仄亠仆仆仂仄 SQL - 仂亟亟亠亢从亠 JSON, NoSQL, MySQL Shell, 亳 于仂亰仄仂亢仆仂亳 舒弍仂舒 MySQL 从舒从 MongoDB - 丕仍亠仆亳礆 于 仂仗亳仄亳亰舒仂亠 亰舒仗仂仂于 亳 亟亳舒亞仆仂亳从亠 仂亶 亟仂从仍舒亟 亟仍 舒亰舒弍仂亳从仂于 仗亳仍仂亢亠仆亳亶 仗仂亟 MySQL. 亊 仆亠 弍亟 舒从舒亰于舒 从舒从 从仂仆亳亞亳仂于舒 亠于亠 亳 仂从亳ﾑ 仆舒 亠亞仂 亳仗仂仍亰仂于舒仆亳亳.]]> Thu, 18 Apr 2024 17:31:03 GMT /slideshow/mysql-2024-mysql-8-5/267334433 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL 2024: 舒亠仄 仗亠亠仂亟亳 仆舒 MySQL 8, 亠仍亳 于 5. 于 舒亳于舒亠? SvetaSmirnova 25 仂从磡舒 2023 亞仂亟舒 Oracle 仗亠从舒亳仍舒 舒从亳于仆 仗仂亟亟亠亢从 MySQL 5.7. 亅仂 亰仆舒亳, 仂 仂亳 仗亳仄仂亠 从 仍亠仆亳礆 于 于亠亳亳 8: - 仂于仂仄 亳亠仄仆仂仄 仍仂于舒 - 弌仂于亠仄亠仆仆仂仄 SQL - 仂亟亟亠亢从亠 JSON, NoSQL, MySQL Shell, 亳 于仂亰仄仂亢仆仂亳 舒弍仂舒 MySQL 从舒从 MongoDB - 丕仍亠仆亳礆 于 仂仗亳仄亳亰舒仂亠 亰舒仗仂仂于 亳 亟亳舒亞仆仂亳从亠 仂亶 亟仂从仍舒亟 亟仍 舒亰舒弍仂亳从仂于 仗亳仍仂亢亠仆亳亶 仗仂亟 MySQL. 亊 仆亠 弍亟 舒从舒亰于舒 从舒从 从仂仆亳亞亳仂于舒 亠于亠 亳 仂从亳ﾑ 仆舒 亠亞仂 亳仗仂仍亰仂于舒仆亳亳. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mysql2024-240418173103-db326826-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 25 仂从磡舒 2023 亞仂亟舒 Oracle 仗亠从舒亳仍舒 舒从亳于仆 仗仂亟亟亠亢从 MySQL 5.7. 亅仂 亰仆舒亳, 仂 仂亳 仗亳仄仂亠 从 仍亠仆亳礆 于 于亠亳亳 8: - 仂于仂仄 亳亠仄仆仂仄 仍仂于舒 - 弌仂于亠仄亠仆仆仂仄 SQL - 仂亟亟亠亢从亠 JSON, NoSQL, MySQL Shell, 亳 于仂亰仄仂亢仆仂亳 舒弍仂舒 MySQL 从舒从 MongoDB - 丕仍亠仆亳礆 于 仂仗亳仄亳亰舒仂亠 亰舒仗仂仂于 亳 亟亳舒亞仆仂亳从亠 仂亶 亟仂从仍舒亟 亟仍 舒亰舒弍仂亳从仂于 仗亳仍仂亢亠仆亳亶 仗仂亟 MySQL. 亊 仆亠 弍亟 舒从舒亰于舒 从舒从 从仂仆亳亞亳仂于舒 亠于亠 亳 仂从亳ﾑ 仆舒 亠亞仂 亳仗仂仍亰仂于舒仆亳亳.
MySQL 2024: 舒亠仄 仗亠亠仂亟亳 仆舒 MySQL 8, 亠仍亳 于 5. 于 舒亳于舒亠? from Sveta Smirnova
]]> 104 0 https://cdn.slidesharecdn.com/ss_thumbnails/mysql2024-240418173103-db326826-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Database in Kubernetes: Diagnostics and Monitoring /slideshow/database-in-kubernetes-diagnostics-and-monitoring/258364703 svetasmirnovak8database-230611132611-f8501a0a
Kubernetes is the new cool in 2023. Many database installations are on Kubernetes now. And this creates challenges for Support engineers because traditional monitoring and diagnostic tools work differently on bare hardware and Kubernetes. In this session, I will focus on differences in methods we use to collect metrics, describe challenges that Percona Support hits when working with database installations on Kubernetes, and discuss how we resolve them. This talk will cover all database technologies we support: MySQL, MongoDB, and PostgreSQL. Presented at Percona Live 2023]]>
Kubernetes is the new cool in 2023. Many database installations are on Kubernetes now. And this creates challenges for Support engineers because traditional monitoring and diagnostic tools work differently on bare hardware and Kubernetes. In this session, I will focus on differences in methods we use to collect metrics, describe challenges that Percona Support hits when working with database installations on Kubernetes, and discuss how we resolve them. This talk will cover all database technologies we support: MySQL, MongoDB, and PostgreSQL. Presented at Percona Live 2023]]> Sun, 11 Jun 2023 13:26:11 GMT /slideshow/database-in-kubernetes-diagnostics-and-monitoring/258364703 SvetaSmirnova@slideshare.net(SvetaSmirnova) Database in Kubernetes: Diagnostics and Monitoring SvetaSmirnova Kubernetes is the new cool in 2023. Many database installations are on Kubernetes now. And this creates challenges for Support engineers because traditional monitoring and diagnostic tools work differently on bare hardware and Kubernetes. In this session, I will focus on differences in methods we use to collect metrics, describe challenges that Percona Support hits when working with database installations on Kubernetes, and discuss how we resolve them. This talk will cover all database technologies we support: MySQL, MongoDB, and PostgreSQL. Presented at Percona Live 2023 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovak8database-230611132611-f8501a0a-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Kubernetes is the new cool in 2023. Many database installations are on Kubernetes now. And this creates challenges for Support engineers because traditional monitoring and diagnostic tools work differently on bare hardware and Kubernetes. In this session, I will focus on differences in methods we use to collect metrics, describe challenges that Percona Support hits when working with database installations on Kubernetes, and discuss how we resolve them. This talk will cover all database technologies we support: MySQL, MongoDB, and PostgreSQL. Presented at Percona Live 2023
Database in Kubernetes: Diagnostics and Monitoring from Sveta Smirnova
]]> 109 0 https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovak8database-230611132611-f8501a0a-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Database Monitoring: Must, Good and Nice to Have /slideshow/mysql-database-monitoring-must-good-and-nice-to-have/258364636 svetasmirnovamustgoodnice-230611132140-f006b307
It is very easy to find if a database installation is having issues. You only need to enable Operating System monitoring. A disk, memory, or CPU usage change will alert you about the problems. But they would not show *why* the trouble happens. You need the help of database-specific monitoring tools. As a Support Engineer, I am always very upset when handling complaints about the database behavior lacking specific database monitoring data because I cannot help! There are two reasons database and system administrators do not enable necessary instrumentation. The first is a natural or expected performance impact. Second is the lack of knowledge on what needs to be on to resolve a particular issue. In this talk, I will cover both concerns. I will show which monitoring instruments will give information on what causes disk, memory, or CPU problems. I will teach you how to use them. I will uncover which performance impact these instruments have. I will use both MySQL command-line client and open-source graphical instrument Percona Monitoring and Management (PMM) for the examples.]]>
It is very easy to find if a database installation is having issues. You only need to enable Operating System monitoring. A disk, memory, or CPU usage change will alert you about the problems. But they would not show *why* the trouble happens. You need the help of database-specific monitoring tools. As a Support Engineer, I am always very upset when handling complaints about the database behavior lacking specific database monitoring data because I cannot help! There are two reasons database and system administrators do not enable necessary instrumentation. The first is a natural or expected performance impact. Second is the lack of knowledge on what needs to be on to resolve a particular issue. In this talk, I will cover both concerns. I will show which monitoring instruments will give information on what causes disk, memory, or CPU problems. I will teach you how to use them. I will uncover which performance impact these instruments have. I will use both MySQL command-line client and open-source graphical instrument Percona Monitoring and Management (PMM) for the examples.]]> Sun, 11 Jun 2023 13:21:40 GMT /slideshow/mysql-database-monitoring-must-good-and-nice-to-have/258364636 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Database Monitoring: Must, Good and Nice to Have SvetaSmirnova It is very easy to find if a database installation is having issues. You only need to enable Operating System monitoring. A disk, memory, or CPU usage change will alert you about the problems. But they would not show *why* the trouble happens. You need the help of database-specific monitoring tools. As a Support Engineer, I am always very upset when handling complaints about the database behavior lacking specific database monitoring data because I cannot help! There are two reasons database and system administrators do not enable necessary instrumentation. The first is a natural or expected performance impact. Second is the lack of knowledge on what needs to be on to resolve a particular issue. In this talk, I will cover both concerns. I will show which monitoring instruments will give information on what causes disk, memory, or CPU problems. I will teach you how to use them. I will uncover which performance impact these instruments have. I will use both MySQL command-line client and open-source graphical instrument Percona Monitoring and Management (PMM) for the examples. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovamustgoodnice-230611132140-f006b307-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> It is very easy to find if a database installation is having issues. You only need to enable Operating System monitoring. A disk, memory, or CPU usage change will alert you about the problems. But they would not show *why* the trouble happens. You need the help of database-specific monitoring tools. As a Support Engineer, I am always very upset when handling complaints about the database behavior lacking specific database monitoring data because I cannot help! There are two reasons database and system administrators do not enable necessary instrumentation. The first is a natural or expected performance impact. Second is the lack of knowledge on what needs to be on to resolve a particular issue. In this talk, I will cover both concerns. I will show which monitoring instruments will give information on what causes disk, memory, or CPU problems. I will teach you how to use them. I will uncover which performance impact these instruments have. I will use both MySQL command-line client and open-source graphical instrument Percona Monitoring and Management (PMM) for the examples.
MySQL Database Monitoring: Must, Good and Nice to Have from Sveta Smirnova
]]> 308 0 https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovamustgoodnice-230611132140-f006b307-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Cookbook: Recipes for Developers /slideshow/mysql-cookbook-recipes-for-developers/254313603 cookbook-pu-2022-221118222943-bc8f417d
MySQL Cookbook 4th edition was released this summer. We are the book's authors and will show you how to "cook" MySQL. We will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility, modern SQL for analytics, and Group Replication for high availability. We will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. We will touch on some of the exciting features of MySQL Spatial Indexes and Geographical Data, Using a Full-Text Search, and more. We're hoping this talk will be interesting for both developers and administrators of MySQL.]]>
MySQL Cookbook 4th edition was released this summer. We are the book's authors and will show you how to "cook" MySQL. We will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility, modern SQL for analytics, and Group Replication for high availability. We will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. We will touch on some of the exciting features of MySQL Spatial Indexes and Geographical Data, Using a Full-Text Search, and more. We're hoping this talk will be interesting for both developers and administrators of MySQL.]]> Fri, 18 Nov 2022 22:29:43 GMT /slideshow/mysql-cookbook-recipes-for-developers/254313603 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Cookbook: Recipes for Developers SvetaSmirnova MySQL Cookbook 4th edition was released this summer. We are the book's authors and will show you how to "cook" MySQL. We will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility, modern SQL for analytics, and Group Replication for high availability. We will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. We will touch on some of the exciting features of MySQL Spatial Indexes and Geographical Data, Using a Full-Text Search, and more. We're hoping this talk will be interesting for both developers and administrators of MySQL. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/cookbook-pu-2022-221118222943-bc8f417d-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> MySQL Cookbook 4th edition was released this summer. We are the book&#39;s authors and will show you how to &quot;cook&quot; MySQL. We will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility, modern SQL for analytics, and Group Replication for high availability. We will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. We will touch on some of the exciting features of MySQL Spatial Indexes and Geographical Data, Using a Full-Text Search, and more. We&#39;re hoping this talk will be interesting for both developers and administrators of MySQL.
MySQL Cookbook: Recipes for Developers from Sveta Smirnova
]]> 143 0 https://cdn.slidesharecdn.com/ss_thumbnails/cookbook-pu-2022-221118222943-bc8f417d-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Performance for DevOps /SvetaSmirnova/mysql-performance-for-devops-254313579 devopsperf-221118222353-1b42ce84
MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility for three different roles: Development, DBA, and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge gained by MySQL DBAs after years or focusing on a single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show a minimal but most effective set of options to improve MySQL performance. For illustrations, I will use real user stories gained from my Support experience and Percona Kubernetes operators for PXC and MySQL.]]>
MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility for three different roles: Development, DBA, and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge gained by MySQL DBAs after years or focusing on a single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show a minimal but most effective set of options to improve MySQL performance. For illustrations, I will use real user stories gained from my Support experience and Percona Kubernetes operators for PXC and MySQL.]]> Fri, 18 Nov 2022 22:23:53 GMT /SvetaSmirnova/mysql-performance-for-devops-254313579 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Performance for DevOps SvetaSmirnova MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility for three different roles: Development, DBA, and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge gained by MySQL DBAs after years or focusing on a single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show a minimal but most effective set of options to improve MySQL performance. For illustrations, I will use real user stories gained from my Support experience and Percona Kubernetes operators for PXC and MySQL. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/devopsperf-221118222353-1b42ce84-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility for three different roles: Development, DBA, and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge gained by MySQL DBAs after years or focusing on a single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show a minimal but most effective set of options to improve MySQL performance. For illustrations, I will use real user stories gained from my Support experience and Percona Kubernetes operators for PXC and MySQL.
MySQL Performance for DevOps from Sveta Smirnova
]]> 82 0 https://cdn.slidesharecdn.com/ss_thumbnails/devopsperf-221118222353-1b42ce84-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Test Framework 亟仍 仗仂亟亟亠亢从亳 从仍亳亠仆仂于 亳 于亠亳亳从舒亳亳 弍舒亞仂于 /slideshow/mysql-test-framework/252105171 mtrsmirnova-220701214634-5603bc24
Talk for TestDriven Conf: https://tdconf.ru/2022/abstracts/8763 MySQL Test Framework (MTR) 仂 亠亶仄于仂从 亟仍 亠亞亠亳仂仆仆 亠仂于 MySQL. 丐亠 亟仍 仆亠亞仂 仗亳 舒亰舒弍仂亳从亳 MySQL 亳 亰舒仗从舒ﾑ 于仂 于亠仄 仗仂亟亞仂仂于从亳 从 仆仂于仄 亠仍亳亰舒仄. MTR 仄仂亢仆仂 亳仗仂仍亰仂于舒 亳 仗仂-亟亞仂仄. 亊 亠亞仂 亳仗仂仍亰, 仂弍 亠亳仂于舒 仗仂弍仍亠仄, 仂 从仂仂 仂仂弍舒ﾑ 从仍亳亠仆, 亳 仗仂亟于亠亢亟舒 仂仂弍亠仆亳 仂弍 仂亳弍从舒 (bug reports) 仂亟仆仂于亠仄亠仆仆仂 仆舒 仆亠从仂仍从亳 于亠亳 MySQL. 亳 仗仂仄仂亳 MTR 仄仂亢仆仂: * 仗仂亞舒仄仄亳仂于舒 仍仂亢仆亠 舒亰于于舒仆亳; * 亠亳仂于舒 仗仂弍仍亠仄 仆舒 仆亠从仂仍从亳 于亠亳 MySQL/Percona/MariaDB-亠于亠仂于 仗亳 仗仂仄仂亳 仂亟仆仂亶 从仂仄舒仆亟; * 亠亳仂于舒 仆亠从仂仍从仂 仂亟仆仂于亠仄亠仆仆 仂亠亟亳仆亠仆亳亶; * 仗仂于亠 仂亳弍从亳 亳 于仂亰于舒舒亠仄亠 亰仆舒亠仆亳; * 舒弍仂舒 亠亰仍舒舒仄亳 亰舒仗仂仂于, 舒仆亳仄仄亳 仗仂亠亟舒仄亳 亳 于仆亠仆亳仄亳 从仂仄舒仆亟舒仄亳. 丐亠 仄仂亢亠 弍 亰舒仗亠仆 仆舒 仍ﾐ頴笑 仄舒亳仆亠 MySQL-, Percona- 亳仍亳 MariaDB-亠于亠仂仄. 亊 仗仂从舒亢, 从舒从 舒弍仂舒 MySQL Test Framework, 亳 仆舒亟亠ﾑ, 仂 于 仂亢亠 仗仂仍ﾐ頴狐亠 仂 亳仆仄亠仆.]]>
Talk for TestDriven Conf: https://tdconf.ru/2022/abstracts/8763 MySQL Test Framework (MTR) 仂 亠亶仄于仂从 亟仍 亠亞亠亳仂仆仆 亠仂于 MySQL. 丐亠 亟仍 仆亠亞仂 仗亳 舒亰舒弍仂亳从亳 MySQL 亳 亰舒仗从舒ﾑ 于仂 于亠仄 仗仂亟亞仂仂于从亳 从 仆仂于仄 亠仍亳亰舒仄. MTR 仄仂亢仆仂 亳仗仂仍亰仂于舒 亳 仗仂-亟亞仂仄. 亊 亠亞仂 亳仗仂仍亰, 仂弍 亠亳仂于舒 仗仂弍仍亠仄, 仂 从仂仂 仂仂弍舒ﾑ 从仍亳亠仆, 亳 仗仂亟于亠亢亟舒 仂仂弍亠仆亳 仂弍 仂亳弍从舒 (bug reports) 仂亟仆仂于亠仄亠仆仆仂 仆舒 仆亠从仂仍从亳 于亠亳 MySQL. 亳 仗仂仄仂亳 MTR 仄仂亢仆仂: * 仗仂亞舒仄仄亳仂于舒 仍仂亢仆亠 舒亰于于舒仆亳; * 亠亳仂于舒 仗仂弍仍亠仄 仆舒 仆亠从仂仍从亳 于亠亳 MySQL/Percona/MariaDB-亠于亠仂于 仗亳 仗仂仄仂亳 仂亟仆仂亶 从仂仄舒仆亟; * 亠亳仂于舒 仆亠从仂仍从仂 仂亟仆仂于亠仄亠仆仆 仂亠亟亳仆亠仆亳亶; * 仗仂于亠 仂亳弍从亳 亳 于仂亰于舒舒亠仄亠 亰仆舒亠仆亳; * 舒弍仂舒 亠亰仍舒舒仄亳 亰舒仗仂仂于, 舒仆亳仄仄亳 仗仂亠亟舒仄亳 亳 于仆亠仆亳仄亳 从仂仄舒仆亟舒仄亳. 丐亠 仄仂亢亠 弍 亰舒仗亠仆 仆舒 仍ﾐ頴笑 仄舒亳仆亠 MySQL-, Percona- 亳仍亳 MariaDB-亠于亠仂仄. 亊 仗仂从舒亢, 从舒从 舒弍仂舒 MySQL Test Framework, 亳 仆舒亟亠ﾑ, 仂 于 仂亢亠 仗仂仍ﾐ頴狐亠 仂 亳仆仄亠仆.]]> Fri, 01 Jul 2022 21:46:34 GMT /slideshow/mysql-test-framework/252105171 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Test Framework 亟仍 仗仂亟亟亠亢从亳 从仍亳亠仆仂于 亳 于亠亳亳从舒亳亳 弍舒亞仂于 SvetaSmirnova Talk for TestDriven Conf: https://tdconf.ru/2022/abstracts/8763 MySQL Test Framework (MTR) 仂 亠亶仄于仂从 亟仍 亠亞亠亳仂仆仆 亠仂于 MySQL. 丐亠 亟仍 仆亠亞仂 仗亳 舒亰舒弍仂亳从亳 MySQL 亳 亰舒仗从舒ﾑ 于仂 于亠仄 仗仂亟亞仂仂于从亳 从 仆仂于仄 亠仍亳亰舒仄. MTR 仄仂亢仆仂 亳仗仂仍亰仂于舒 亳 仗仂-亟亞仂仄. 亊 亠亞仂 亳仗仂仍亰, 仂弍 亠亳仂于舒 仗仂弍仍亠仄, 仂 从仂仂 仂仂弍舒ﾑ 从仍亳亠仆, 亳 仗仂亟于亠亢亟舒 仂仂弍亠仆亳 仂弍 仂亳弍从舒 (bug reports) 仂亟仆仂于亠仄亠仆仆仂 仆舒 仆亠从仂仍从亳 于亠亳 MySQL. 亳 仗仂仄仂亳 MTR 仄仂亢仆仂: * 仗仂亞舒仄仄亳仂于舒 仍仂亢仆亠 舒亰于于舒仆亳; * 亠亳仂于舒 仗仂弍仍亠仄 仆舒 仆亠从仂仍从亳 于亠亳 MySQL/Percona/MariaDB-亠于亠仂于 仗亳 仗仂仄仂亳 仂亟仆仂亶 从仂仄舒仆亟; * 亠亳仂于舒 仆亠从仂仍从仂 仂亟仆仂于亠仄亠仆仆 仂亠亟亳仆亠仆亳亶; * 仗仂于亠 仂亳弍从亳 亳 于仂亰于舒舒亠仄亠 亰仆舒亠仆亳; * 舒弍仂舒 亠亰仍舒舒仄亳 亰舒仗仂仂于, 舒仆亳仄仄亳 仗仂亠亟舒仄亳 亳 于仆亠仆亳仄亳 从仂仄舒仆亟舒仄亳. 丐亠 仄仂亢亠 弍 亰舒仗亠仆 仆舒 仍ﾐ頴笑 仄舒亳仆亠 MySQL-, Percona- 亳仍亳 MariaDB-亠于亠仂仄. 亊 仗仂从舒亢, 从舒从 舒弍仂舒 MySQL Test Framework, 亳 仆舒亟亠ﾑ, 仂 于 仂亢亠 仗仂仍ﾐ頴狐亠 仂 亳仆仄亠仆. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mtrsmirnova-220701214634-5603bc24-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Talk for TestDriven Conf: https://tdconf.ru/2022/abstracts/8763 MySQL Test Framework (MTR) 仂 亠亶仄于仂从 亟仍 亠亞亠亳仂仆仆 亠仂于 MySQL. 丐亠 亟仍 仆亠亞仂 仗亳 舒亰舒弍仂亳从亳 MySQL 亳 亰舒仗从舒ﾑ 于仂 于亠仄 仗仂亟亞仂仂于从亳 从 仆仂于仄 亠仍亳亰舒仄. MTR 仄仂亢仆仂 亳仗仂仍亰仂于舒 亳 仗仂-亟亞仂仄. 亊 亠亞仂 亳仗仂仍亰, 仂弍 亠亳仂于舒 仗仂弍仍亠仄, 仂 从仂仂 仂仂弍舒ﾑ 从仍亳亠仆, 亳 仗仂亟于亠亢亟舒 仂仂弍亠仆亳 仂弍 仂亳弍从舒 (bug reports) 仂亟仆仂于亠仄亠仆仆仂 仆舒 仆亠从仂仍从亳 于亠亳 MySQL. 亳 仗仂仄仂亳 MTR 仄仂亢仆仂: * 仗仂亞舒仄仄亳仂于舒 仍仂亢仆亠 舒亰于于舒仆亳; * 亠亳仂于舒 仗仂弍仍亠仄 仆舒 仆亠从仂仍从亳 于亠亳 MySQL/Percona/MariaDB-亠于亠仂于 仗亳 仗仂仄仂亳 仂亟仆仂亶 从仂仄舒仆亟; * 亠亳仂于舒 仆亠从仂仍从仂 仂亟仆仂于亠仄亠仆仆 仂亠亟亳仆亠仆亳亶; * 仗仂于亠 仂亳弍从亳 亳 于仂亰于舒舒亠仄亠 亰仆舒亠仆亳; * 舒弍仂舒 亠亰仍舒舒仄亳 亰舒仗仂仂于, 舒仆亳仄仄亳 仗仂亠亟舒仄亳 亳 于仆亠仆亳仄亳 从仂仄舒仆亟舒仄亳. 丐亠 仄仂亢亠 弍 亰舒仗亠仆 仆舒 仍ﾐ頴笑 仄舒亳仆亠 MySQL-, Percona- 亳仍亳 MariaDB-亠于亠仂仄. 亊 仗仂从舒亢, 从舒从 舒弍仂舒 MySQL Test Framework, 亳 仆舒亟亠ﾑ, 仂 于 仂亢亠 仗仂仍ﾐ頴狐亠 仂 亳仆仄亠仆.
MySQL Test Framework 亟仍 仗仂亟亟亠亢从亳 从仍亳亠仆仂于 亳 于亠亳亳从舒亳亳 弍舒亞仂于 from Sveta Smirnova
]]> 34 0 https://cdn.slidesharecdn.com/ss_thumbnails/mtrsmirnova-220701214634-5603bc24-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Cookbook: Recipes for Your Business /slideshow/mysql-cookbook-recipes-for-your-business/251841015 pl22mysqlcookbooksveta-220524002627-1d3a35b1
These slides are for my talk at Percona Live 2022: https://sched.co/10KEo MySQL Cookbook 4th edition (https://www.target.com/p/mysql-cookbook-4th-edition-by-sveta-smirnova-alkin-tezuysal-paperback/-/A-85851771) is planned to be released this spring. I am one of the authors of the book and will show you how to "cook" MySQL. I will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility; modern SQL for analytics, and Group Replication for high availability. I will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. I expect this talk will be interesting for MySQL application developers. ]]>
These slides are for my talk at Percona Live 2022: https://sched.co/10KEo MySQL Cookbook 4th edition (https://www.target.com/p/mysql-cookbook-4th-edition-by-sveta-smirnova-alkin-tezuysal-paperback/-/A-85851771) is planned to be released this spring. I am one of the authors of the book and will show you how to "cook" MySQL. I will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility; modern SQL for analytics, and Group Replication for high availability. I will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. I expect this talk will be interesting for MySQL application developers. ]]> Tue, 24 May 2022 00:26:27 GMT /slideshow/mysql-cookbook-recipes-for-your-business/251841015 SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Cookbook: Recipes for Your Business SvetaSmirnova These slides are for my talk at Percona Live 2022: https://sched.co/10KEo MySQL Cookbook 4th edition (https://www.target.com/p/mysql-cookbook-4th-edition-by-sveta-smirnova-alkin-tezuysal-paperback/-/A-85851771) is planned to be released this spring. I am one of the authors of the book and will show you how to "cook" MySQL. I will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility; modern SQL for analytics, and Group Replication for high availability. I will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. I expect this talk will be interesting for MySQL application developers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pl22mysqlcookbooksveta-220524002627-1d3a35b1-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> These slides are for my talk at Percona Live 2022: https://sched.co/10KEo MySQL Cookbook 4th edition (https://www.target.com/p/mysql-cookbook-4th-edition-by-sveta-smirnova-alkin-tezuysal-paperback/-/A-85851771) is planned to be released this spring. I am one of the authors of the book and will show you how to &quot;cook&quot; MySQL. I will show you a few tasks with different priorities, such as JSON in MySQL for those who need flexibility; modern SQL for analytics, and Group Replication for high availability. I will also show how to write programs using JavaScript and Python languages, X DevAPI, and MySQL Shell. I expect this talk will be interesting for MySQL application developers.
MySQL Cookbook: Recipes for Your Business from Sveta Smirnova
]]> 308 0 https://cdn.slidesharecdn.com/ss_thumbnails/pl22mysqlcookbooksveta-220524002627-1d3a35b1-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction into MySQL Query Tuning for Dev[Op]s /slideshow/introduction-into-mysql-query-tuning-for-devops/249772312 qtdevops-210717011329
Percona Live Online 2021 talk: https://www.percona.com/resources/videos/introduction-mysql-query-tuning-for-devops In this talk I will show how to get started with MySQL Query Tuning. I will make a short introduction into physical table structure and demonstrate how it may influence query execution time. Then we will discuss basic query tuning instruments and techniques, mainly EXPLAIN command with its latest variations. You will learn how to understand its output and how to rewrite queries or change table structure to achieve better performance.]]>
Percona Live Online 2021 talk: https://www.percona.com/resources/videos/introduction-mysql-query-tuning-for-devops In this talk I will show how to get started with MySQL Query Tuning. I will make a short introduction into physical table structure and demonstrate how it may influence query execution time. Then we will discuss basic query tuning instruments and techniques, mainly EXPLAIN command with its latest variations. You will learn how to understand its output and how to rewrite queries or change table structure to achieve better performance.]]> Sat, 17 Jul 2021 01:13:29 GMT /slideshow/introduction-into-mysql-query-tuning-for-devops/249772312 SvetaSmirnova@slideshare.net(SvetaSmirnova) Introduction into MySQL Query Tuning for Dev[Op]s SvetaSmirnova Percona Live Online 2021 talk: https://www.percona.com/resources/videos/introduction-mysql-query-tuning-for-devops In this talk I will show how to get started with MySQL Query Tuning. I will make a short introduction into physical table structure and demonstrate how it may influence query execution time. Then we will discuss basic query tuning instruments and techniques, mainly EXPLAIN command with its latest variations. You will learn how to understand its output and how to rewrite queries or change table structure to achieve better performance. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/qtdevops-210717011329-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Percona Live Online 2021 talk: https://www.percona.com/resources/videos/introduction-mysql-query-tuning-for-devops In this talk I will show how to get started with MySQL Query Tuning. I will make a short introduction into physical table structure and demonstrate how it may influence query execution time. Then we will discuss basic query tuning instruments and techniques, mainly EXPLAIN command with its latest variations. You will learn how to understand its output and how to rewrite queries or change table structure to achieve better performance.
Introduction into MySQL Query Tuning for Dev[Op]s from Sveta Smirnova
]]> 180 0 https://cdn.slidesharecdn.com/ss_thumbnails/qtdevops-210717011329-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 仂亳亰于仂亟亳亠仍仆仂 MySQL 亟仍 DevOps /slideshow/mysql-devops/249772265 mysqlperfdevops-210717011011
Talk for the DevOps Pro Moscow 2021: https://www.devopspro.ru/Sveta-Smirnova/ 仂亳亰于仂亟亳亠仍仆仂 MySQL 仄仂亢仆仂 仍亳 仗亳 仗仂仄仂亳 仂仗亳仄亳亰舒亳亳 亰舒仗仂仂于, 仆舒仂亠从 MySQL 亠于亠舒 亳 亢亠仍亠亰舒. 丐舒亟亳亳仂仆仆仂 亳 亰舒亟舒亳 舒仗亠亟亠仍磿亳 仄亠亢亟 亠仄 仂仍礆亳: 舒亰舒弍仂亳从, 亟仄亳仆亳舒仂 弍舒亰 亟舒仆仆 亳 弌亳亠仄仆亶 亟仄亳仆亳舒仂. 丐亠仗亠 亢亠 于亠 亳 亰舒亟舒亳 亠舒亠 DevOps, 仂 仆亠仗仂仂 亟仍 仂亟仆仂亞仂 亠仍仂于亠从舒. 仂仄 亟仂从仍舒亟亠 舒从舒亢 仂弍 仂仆仂于仆 仂仗亳仄亳亰舒亳, 从仂仂亠 亠舒ﾑ 弍仂仍亳仆于仂 仗仂弍仍亠仄 仗仂亳亰于仂亟亳亠仍仆仂亳 MySQL. 仍 亳仍仍ﾑ舒亳亶 弍亟 亳仗仂仍亰仂于舒 亠舒仍仆亠 仗仂仍亰仂于舒亠仍从亳亠 亳仂亳亳 亳 Percona Kubernetes Operator. ]]>
Talk for the DevOps Pro Moscow 2021: https://www.devopspro.ru/Sveta-Smirnova/ 仂亳亰于仂亟亳亠仍仆仂 MySQL 仄仂亢仆仂 仍亳 仗亳 仗仂仄仂亳 仂仗亳仄亳亰舒亳亳 亰舒仗仂仂于, 仆舒仂亠从 MySQL 亠于亠舒 亳 亢亠仍亠亰舒. 丐舒亟亳亳仂仆仆仂 亳 亰舒亟舒亳 舒仗亠亟亠仍磿亳 仄亠亢亟 亠仄 仂仍礆亳: 舒亰舒弍仂亳从, 亟仄亳仆亳舒仂 弍舒亰 亟舒仆仆 亳 弌亳亠仄仆亶 亟仄亳仆亳舒仂. 丐亠仗亠 亢亠 于亠 亳 亰舒亟舒亳 亠舒亠 DevOps, 仂 仆亠仗仂仂 亟仍 仂亟仆仂亞仂 亠仍仂于亠从舒. 仂仄 亟仂从仍舒亟亠 舒从舒亢 仂弍 仂仆仂于仆 仂仗亳仄亳亰舒亳, 从仂仂亠 亠舒ﾑ 弍仂仍亳仆于仂 仗仂弍仍亠仄 仗仂亳亰于仂亟亳亠仍仆仂亳 MySQL. 仍 亳仍仍ﾑ舒亳亶 弍亟 亳仗仂仍亰仂于舒 亠舒仍仆亠 仗仂仍亰仂于舒亠仍从亳亠 亳仂亳亳 亳 Percona Kubernetes Operator. ]]> Sat, 17 Jul 2021 01:10:11 GMT /slideshow/mysql-devops/249772265 SvetaSmirnova@slideshare.net(SvetaSmirnova) 仂亳亰于仂亟亳亠仍仆仂 MySQL 亟仍 DevOps SvetaSmirnova Talk for the DevOps Pro Moscow 2021: https://www.devopspro.ru/Sveta-Smirnova/ 仂亳亰于仂亟亳亠仍仆仂 MySQL 仄仂亢仆仂 仍亳 仗亳 仗仂仄仂亳 仂仗亳仄亳亰舒亳亳 亰舒仗仂仂于, 仆舒仂亠从 MySQL 亠于亠舒 亳 亢亠仍亠亰舒. 丐舒亟亳亳仂仆仆仂 亳 亰舒亟舒亳 舒仗亠亟亠仍磿亳 仄亠亢亟 亠仄 仂仍礆亳: 舒亰舒弍仂亳从, 亟仄亳仆亳舒仂 弍舒亰 亟舒仆仆 亳 弌亳亠仄仆亶 亟仄亳仆亳舒仂. 丐亠仗亠 亢亠 于亠 亳 亰舒亟舒亳 亠舒亠 DevOps, 仂 仆亠仗仂仂 亟仍 仂亟仆仂亞仂 亠仍仂于亠从舒. 仂仄 亟仂从仍舒亟亠 舒从舒亢 仂弍 仂仆仂于仆 仂仗亳仄亳亰舒亳, 从仂仂亠 亠舒ﾑ 弍仂仍亳仆于仂 仗仂弍仍亠仄 仗仂亳亰于仂亟亳亠仍仆仂亳 MySQL. 仍 亳仍仍ﾑ舒亳亶 弍亟 亳仗仂仍亰仂于舒 亠舒仍仆亠 仗仂仍亰仂于舒亠仍从亳亠 亳仂亳亳 亳 Percona Kubernetes Operator. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mysqlperfdevops-210717011011-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Talk for the DevOps Pro Moscow 2021: https://www.devopspro.ru/Sveta-Smirnova/ 仂亳亰于仂亟亳亠仍仆仂 MySQL 仄仂亢仆仂 仍亳 仗亳 仗仂仄仂亳 仂仗亳仄亳亰舒亳亳 亰舒仗仂仂于, 仆舒仂亠从 MySQL 亠于亠舒 亳 亢亠仍亠亰舒. 丐舒亟亳亳仂仆仆仂 亳 亰舒亟舒亳 舒仗亠亟亠仍磿亳 仄亠亢亟 亠仄 仂仍礆亳: 舒亰舒弍仂亳从, 亟仄亳仆亳舒仂 弍舒亰 亟舒仆仆 亳 弌亳亠仄仆亶 亟仄亳仆亳舒仂. 丐亠仗亠 亢亠 于亠 亳 亰舒亟舒亳 亠舒亠 DevOps, 仂 仆亠仗仂仂 亟仍 仂亟仆仂亞仂 亠仍仂于亠从舒. 仂仄 亟仂从仍舒亟亠 舒从舒亢 仂弍 仂仆仂于仆 仂仗亳仄亳亰舒亳, 从仂仂亠 亠舒ﾑ 弍仂仍亳仆于仂 仗仂弍仍亠仄 仗仂亳亰于仂亟亳亠仍仆仂亳 MySQL. 仍 亳仍仍ﾑ舒亳亶 弍亟 亳仗仂仍亰仂于舒 亠舒仍仆亠 仗仂仍亰仂于舒亠仍从亳亠 亳仂亳亳 亳 Percona Kubernetes Operator.
仂亳亰于仂亟亳亠仍仆仂 MySQL 亟仍 DevOps from Sveta Smirnova
]]> 89 0 https://cdn.slidesharecdn.com/ss_thumbnails/mysqlperfdevops-210717011011-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 MySQL Performance for DevOps /SvetaSmirnova/mysql-performance-for-devops oct26mysqlperformancefordevopssvetasmirnova-201101181844
MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility of three different roles: Development, DBA and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge, gained by MySQL DBAs after years or focus on the single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show minimal, but the most effective, set of options which will improve MySQL performance. For illustrations, I will use real user stories, gained by my Support experience, and Kubernetes operators, now available from all main MySQL eco-system vendors: Oracle, MariaDB, and Percona. Presented at Open Source Summit Europe 2020: https://sched.co/eCGf]]>
MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility of three different roles: Development, DBA and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge, gained by MySQL DBAs after years or focus on the single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show minimal, but the most effective, set of options which will improve MySQL performance. For illustrations, I will use real user stories, gained by my Support experience, and Kubernetes operators, now available from all main MySQL eco-system vendors: Oracle, MariaDB, and Percona. Presented at Open Source Summit Europe 2020: https://sched.co/eCGf]]> Sun, 01 Nov 2020 18:18:44 GMT /SvetaSmirnova/mysql-performance-for-devops SvetaSmirnova@slideshare.net(SvetaSmirnova) MySQL Performance for DevOps SvetaSmirnova MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility of three different roles: Development, DBA and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge, gained by MySQL DBAs after years or focus on the single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show minimal, but the most effective, set of options which will improve MySQL performance. For illustrations, I will use real user stories, gained by my Support experience, and Kubernetes operators, now available from all main MySQL eco-system vendors: Oracle, MariaDB, and Percona. Presented at Open Source Summit Europe 2020: https://sched.co/eCGf <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/oct26mysqlperformancefordevopssvetasmirnova-201101181844-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> MySQL performance can be improved by tuning queries, server options, and hardware. Traditionally it was an area of responsibility of three different roles: Development, DBA and System Administrators. Now DevOps handle these all. But there is a gap. Knowledge, gained by MySQL DBAs after years or focus on the single product is hard to gain when you focus on more than one. This is why I am doing this session. I will show minimal, but the most effective, set of options which will improve MySQL performance. For illustrations, I will use real user stories, gained by my Support experience, and Kubernetes operators, now available from all main MySQL eco-system vendors: Oracle, MariaDB, and Percona. Presented at Open Source Summit Europe 2020: https://sched.co/eCGf
MySQL Performance for DevOps from Sveta Smirnova
]]> 579 0 https://cdn.slidesharecdn.com/ss_thumbnails/oct26mysqlperformancefordevopssvetasmirnova-201101181844-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 How to Avoid Pitfalls in Schema Upgrade with Percona XtraDB Cluster /slideshow/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster/239044481 pxcddlpl-201101172355
Percona XtraDB Cluster (PXC) is a 100% synchronized cluster in regards to DML operations. It is ensured by the optimistic locking model and ability to rollback transaction which cannot be applied on all nodes. However, DDL operations are not transactional in MySQL. This adds complexity when you need to change the schema of the database. Changes made by DDL may affect the results of the queries. Therefore all modifications must replicate on all nodes prior to the next data access. For operations that run momentarily, it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to the safest synchronous blocking schema upgrade method: TOI, - PXC supports more relaxed, though not safe, method RSU. RSU: Rolling Schema Upgrade is advertised to be non-blocking. But you still need to take care of updates, running while you are performing such an upgrade. Surprisingly, even updates on not related tables and schema can cause RSU operation to fail. In this talk, I will uncover nuances of PXC schema upgrades and point to details you need to take special care about. Further Information Schema change is a frequent task, and many do not expect any surprises with it. However, the necessity to replay the changes to all synchronized nodes adds complexity. I made a webinar on a similar topic which was recorded and available for replay. Now I have found that I share a link to the webinar to my Support customers approximately once per week. Not having a good understanding of how schema change works in the cluster leads to lockups and operation failures. This talk will provide a checklist that will help to choose the best schema change method. Presented at Percona Live Online: https://perconaliveonline2020.sched.com/event/ePm2/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster]]>
Percona XtraDB Cluster (PXC) is a 100% synchronized cluster in regards to DML operations. It is ensured by the optimistic locking model and ability to rollback transaction which cannot be applied on all nodes. However, DDL operations are not transactional in MySQL. This adds complexity when you need to change the schema of the database. Changes made by DDL may affect the results of the queries. Therefore all modifications must replicate on all nodes prior to the next data access. For operations that run momentarily, it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to the safest synchronous blocking schema upgrade method: TOI, - PXC supports more relaxed, though not safe, method RSU. RSU: Rolling Schema Upgrade is advertised to be non-blocking. But you still need to take care of updates, running while you are performing such an upgrade. Surprisingly, even updates on not related tables and schema can cause RSU operation to fail. In this talk, I will uncover nuances of PXC schema upgrades and point to details you need to take special care about. Further Information Schema change is a frequent task, and many do not expect any surprises with it. However, the necessity to replay the changes to all synchronized nodes adds complexity. I made a webinar on a similar topic which was recorded and available for replay. Now I have found that I share a link to the webinar to my Support customers approximately once per week. Not having a good understanding of how schema change works in the cluster leads to lockups and operation failures. This talk will provide a checklist that will help to choose the best schema change method. Presented at Percona Live Online: https://perconaliveonline2020.sched.com/event/ePm2/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster]]> Sun, 01 Nov 2020 17:23:55 GMT /slideshow/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster/239044481 SvetaSmirnova@slideshare.net(SvetaSmirnova) How to Avoid Pitfalls in Schema Upgrade with Percona XtraDB Cluster SvetaSmirnova Percona XtraDB Cluster (PXC) is a 100% synchronized cluster in regards to DML operations. It is ensured by the optimistic locking model and ability to rollback transaction which cannot be applied on all nodes. However, DDL operations are not transactional in MySQL. This adds complexity when you need to change the schema of the database. Changes made by DDL may affect the results of the queries. Therefore all modifications must replicate on all nodes prior to the next data access. For operations that run momentarily, it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to the safest synchronous blocking schema upgrade method: TOI, - PXC supports more relaxed, though not safe, method RSU. RSU: Rolling Schema Upgrade is advertised to be non-blocking. But you still need to take care of updates, running while you are performing such an upgrade. Surprisingly, even updates on not related tables and schema can cause RSU operation to fail. In this talk, I will uncover nuances of PXC schema upgrades and point to details you need to take special care about. Further Information Schema change is a frequent task, and many do not expect any surprises with it. However, the necessity to replay the changes to all synchronized nodes adds complexity. I made a webinar on a similar topic which was recorded and available for replay. Now I have found that I share a link to the webinar to my Support customers approximately once per week. Not having a good understanding of how schema change works in the cluster leads to lockups and operation failures. This talk will provide a checklist that will help to choose the best schema change method. Presented at Percona Live Online: https://perconaliveonline2020.sched.com/event/ePm2/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pxcddlpl-201101172355-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Percona XtraDB Cluster (PXC) is a 100% synchronized cluster in regards to DML operations. It is ensured by the optimistic locking model and ability to rollback transaction which cannot be applied on all nodes. However, DDL operations are not transactional in MySQL. This adds complexity when you need to change the schema of the database. Changes made by DDL may affect the results of the queries. Therefore all modifications must replicate on all nodes prior to the next data access. For operations that run momentarily, it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to the safest synchronous blocking schema upgrade method: TOI, - PXC supports more relaxed, though not safe, method RSU. RSU: Rolling Schema Upgrade is advertised to be non-blocking. But you still need to take care of updates, running while you are performing such an upgrade. Surprisingly, even updates on not related tables and schema can cause RSU operation to fail. In this talk, I will uncover nuances of PXC schema upgrades and point to details you need to take special care about. Further Information Schema change is a frequent task, and many do not expect any surprises with it. However, the necessity to replay the changes to all synchronized nodes adds complexity. I made a webinar on a similar topic which was recorded and available for replay. Now I have found that I share a link to the webinar to my Support customers approximately once per week. Not having a good understanding of how schema change works in the cluster leads to lockups and operation failures. This talk will provide a checklist that will help to choose the best schema change method. Presented at Percona Live Online: https://perconaliveonline2020.sched.com/event/ePm2/how-to-avoid-pitfalls-in-schema-upgrade-with-percona-xtradb-cluster
How to Avoid Pitfalls in Schema Upgrade with Percona XtraDB Cluster from Sveta Smirnova
]]> 356 0 https://cdn.slidesharecdn.com/ss_thumbnails/pxcddlpl-201101172355-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 How to migrate from MySQL to MariaDB without tears /SvetaSmirnova/how-to-migrate-from-mysql-to-mariadb-without-tears migration-201017130432
Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/migrate-mysql/ MariaDB is a drop-in replacement for MySQL. Initial migration is simple: start MariaDB over the old MySQL datadir. Later your application may notice that some features work differently than with MySQL. These are MariaDB improvements, so this is good and, likely the reason you migrated. In this session, I will focus on the differences affecting application performance and behavior. In particular, features sharing the same name, but working differently. ]]>
Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/migrate-mysql/ MariaDB is a drop-in replacement for MySQL. Initial migration is simple: start MariaDB over the old MySQL datadir. Later your application may notice that some features work differently than with MySQL. These are MariaDB improvements, so this is good and, likely the reason you migrated. In this session, I will focus on the differences affecting application performance and behavior. In particular, features sharing the same name, but working differently. ]]> Sat, 17 Oct 2020 13:04:32 GMT /SvetaSmirnova/how-to-migrate-from-mysql-to-mariadb-without-tears SvetaSmirnova@slideshare.net(SvetaSmirnova) How to migrate from MySQL to MariaDB without tears SvetaSmirnova Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/migrate-mysql/ MariaDB is a drop-in replacement for MySQL. Initial migration is simple: start MariaDB over the old MySQL datadir. Later your application may notice that some features work differently than with MySQL. These are MariaDB improvements, so this is good and, likely the reason you migrated. In this session, I will focus on the differences affecting application performance and behavior. In particular, features sharing the same name, but working differently. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/migration-201017130432-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/migrate-mysql/ MariaDB is a drop-in replacement for MySQL. Initial migration is simple: start MariaDB over the old MySQL datadir. Later your application may notice that some features work differently than with MySQL. These are MariaDB improvements, so this is good and, likely the reason you migrated. In this session, I will focus on the differences affecting application performance and behavior. In particular, features sharing the same name, but working differently.
How to migrate from MySQL to MariaDB without tears from Sveta Smirnova
]]> 394 0 https://cdn.slidesharecdn.com/ss_thumbnails/migration-201017130432-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Modern solutions for modern database load: improvements in the latest MariaDB versions /slideshow/modern-solutions-for-modern-database-load-improvements-in-the-latest-mariadb-versions/238901680 newfeatures105-201017130129
Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/improvements/ MariaDB is famous for working well in high-performance environments. But our view of what to call high-performance changes over time. Every year we get faster data transfer speed; more devices connected to the Internet; more users and, as a result, more data. Challenges, which developers have to solve, are getting harder. This session shows what engineers do to keep the product up to date, focusing on MariaDB improvements that make it different from its predecessor, MySQL.]]>
Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/improvements/ MariaDB is famous for working well in high-performance environments. But our view of what to call high-performance changes over time. Every year we get faster data transfer speed; more devices connected to the Internet; more users and, as a result, more data. Challenges, which developers have to solve, are getting harder. This session shows what engineers do to keep the product up to date, focusing on MariaDB improvements that make it different from its predecessor, MySQL.]]> Sat, 17 Oct 2020 13:01:29 GMT /slideshow/modern-solutions-for-modern-database-load-improvements-in-the-latest-mariadb-versions/238901680 SvetaSmirnova@slideshare.net(SvetaSmirnova) Modern solutions for modern database load: improvements in the latest MariaDB versions SvetaSmirnova Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/improvements/ MariaDB is famous for working well in high-performance environments. But our view of what to call high-performance changes over time. Every year we get faster data transfer speed; more devices connected to the Internet; more users and, as a result, more data. Challenges, which developers have to solve, are getting harder. This session shows what engineers do to keep the product up to date, focusing on MariaDB improvements that make it different from its predecessor, MySQL. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/newfeatures105-201017130129-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at MariaDB Server Fest 2020: https://mariadb.org/fest2020/improvements/ MariaDB is famous for working well in high-performance environments. But our view of what to call high-performance changes over time. Every year we get faster data transfer speed; more devices connected to the Internet; more users and, as a result, more data. Challenges, which developers have to solve, are getting harder. This session shows what engineers do to keep the product up to date, focusing on MariaDB improvements that make it different from its predecessor, MySQL.
Modern solutions for modern database load: improvements in the latest MariaDB versions from Sveta Smirnova
]]> 330 0 https://cdn.slidesharecdn.com/ss_thumbnails/newfeatures105-201017130129-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 How Safe is Asynchronous Master-Master Setup? /slideshow/how-safe-is-asynchronous-mastermaster-setup-238901665/238901665 asynctd2020-201017125746
Presented at Percona MySQL Tech Day on September 10, 2020: https://www.percona.com/tech-days#mysql It is common knowledge that built-in asynchronous active-active replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous source-source replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. ]]>
Presented at Percona MySQL Tech Day on September 10, 2020: https://www.percona.com/tech-days#mysql It is common knowledge that built-in asynchronous active-active replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous source-source replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. ]]> Sat, 17 Oct 2020 12:57:45 GMT /slideshow/how-safe-is-asynchronous-mastermaster-setup-238901665/238901665 SvetaSmirnova@slideshare.net(SvetaSmirnova) How Safe is Asynchronous Master-Master Setup? SvetaSmirnova Presented at Percona MySQL Tech Day on September 10, 2020: https://www.percona.com/tech-days#mysql It is common knowledge that built-in asynchronous active-active replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous source-source replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/asynctd2020-201017125746-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at Percona MySQL Tech Day on September 10, 2020: https://www.percona.com/tech-days#mysql It is common knowledge that built-in asynchronous active-active replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous source-source replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters.
How Safe is Asynchronous Master-Master Setup? from Sveta Smirnova
]]> 441 0 https://cdn.slidesharecdn.com/ss_thumbnails/asynctd2020-201017125746-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 弌仂于亠仄亠仆仆仂仄 舒亶仍仂亟 - 仂于亠仄亠仆仆亠 亠亠仆亳: MySQL 8.0 亳 仍亠仆亳 Percona /slideshow/mysql-80-percona-238467274/238467274 mysql8-200913144006
MySQL 于亠亞亟舒 亳仗仂仍亰仂于舒仍亳 仗仂亟 于仂从仂亶 仆舒亞亰从仂亶. 亠亟舒仂仄 舒 弍舒亰舒 弍仍舒 亳 仂舒 舒仄仄 仗仂仗仍仆仄 弍从仆亟仂仄 亟仍 web. 亟仆舒从仂 仆舒亳 仗亠亟舒于仍亠仆亳 仂 舒亶仍仂亟亠 从舒亢亟仄 亞仂亟仂仄 舒亳ﾑ. 仂仍舒 从仂仂 仗亠亠亟舒亳 亟舒仆仆 -> 弍仂仍亠 仂亶于 仗仂亟从仍ﾑ亠仆亳亠仄 从 亳仆亠仆亠 -> 弍仂仍亠 仗仂仍亰仂于舒亠仍亠亶 -> 弍仂仍亠 亟舒仆仆. 舒亟舒亳, 仂亳亠 仗亠亠亟 舒亰舒弍仂亳从舒仄亳 MySQL, 从舒亢亟仄 亞仂亟仂仄 仍仂亢仆ﾑ. 仂仄 亟仂从仍舒亟亠 舒从舒亢 从舒从 仄亠仆磿亳 亠仆舒亳亳 亳仗仂仍亰仂于舒仆亳 MySQL 亰舒 [仗仂亳] 25 仍亠 亠 亳仂亳亳 亳 仂 亟亠仍舒仍亳 亳仆亢亠仆亠, 仂弍 MySQL 仂舒于舒仍舒 舒从舒仍仆仂亶. 亰舒仂仆亠仄 舒从亳亠 亠仄, 从舒从 舒弍仂舒 弍仂仍亳仄 从仂仍亳亠于仂仄 舒从亳于仆 仂亠亟亳仆亠仆亳亶 亳 于仂从亳仄亳 仂弍仄舒仄亳 亟舒仆仆. 亊 仗仂从舒亢 仆舒从仂仍从仂 仂于亠仄亠仆仆亠 于亠亳亳 仍亠 仗舒于仍ﾑ 于仂亰仂亳仄亳 仆舒亞亰从舒仄亳. 亊 仆舒亟亠ﾑ, 仂 仗仂仍亠 仄仂亠亞仂 亟仂从仍舒亟舒 亠 仍舒亠仍亳, 从仂仂亠 亳仗仂仍亰ﾑ 舒亠 于亠亳亳, 亰舒仂 仂弍仆仂于亳 亳 亠, 从仂 亢亠 仂弍仆仂于亳仍亳, 亰仆舒ﾑ 从舒从 亳仗仂仍亰仂于舒 仂于亠仄亠仆仆亶 MySQL 仆舒 仗仂仍仆 仄仂仆仂. 仂亳舒仆舒 仆舒 从仂仆亠亠仆亳亳 OST 2020: https://ostconf.com/materials/2857#2857]]>
MySQL 于亠亞亟舒 亳仗仂仍亰仂于舒仍亳 仗仂亟 于仂从仂亶 仆舒亞亰从仂亶. 亠亟舒仂仄 舒 弍舒亰舒 弍仍舒 亳 仂舒 舒仄仄 仗仂仗仍仆仄 弍从仆亟仂仄 亟仍 web. 亟仆舒从仂 仆舒亳 仗亠亟舒于仍亠仆亳 仂 舒亶仍仂亟亠 从舒亢亟仄 亞仂亟仂仄 舒亳ﾑ. 仂仍舒 从仂仂 仗亠亠亟舒亳 亟舒仆仆 -> 弍仂仍亠 仂亶于 仗仂亟从仍ﾑ亠仆亳亠仄 从 亳仆亠仆亠 -> 弍仂仍亠 仗仂仍亰仂于舒亠仍亠亶 -> 弍仂仍亠 亟舒仆仆. 舒亟舒亳, 仂亳亠 仗亠亠亟 舒亰舒弍仂亳从舒仄亳 MySQL, 从舒亢亟仄 亞仂亟仂仄 仍仂亢仆ﾑ. 仂仄 亟仂从仍舒亟亠 舒从舒亢 从舒从 仄亠仆磿亳 亠仆舒亳亳 亳仗仂仍亰仂于舒仆亳 MySQL 亰舒 [仗仂亳] 25 仍亠 亠 亳仂亳亳 亳 仂 亟亠仍舒仍亳 亳仆亢亠仆亠, 仂弍 MySQL 仂舒于舒仍舒 舒从舒仍仆仂亶. 亰舒仂仆亠仄 舒从亳亠 亠仄, 从舒从 舒弍仂舒 弍仂仍亳仄 从仂仍亳亠于仂仄 舒从亳于仆 仂亠亟亳仆亠仆亳亶 亳 于仂从亳仄亳 仂弍仄舒仄亳 亟舒仆仆. 亊 仗仂从舒亢 仆舒从仂仍从仂 仂于亠仄亠仆仆亠 于亠亳亳 仍亠 仗舒于仍ﾑ 于仂亰仂亳仄亳 仆舒亞亰从舒仄亳. 亊 仆舒亟亠ﾑ, 仂 仗仂仍亠 仄仂亠亞仂 亟仂从仍舒亟舒 亠 仍舒亠仍亳, 从仂仂亠 亳仗仂仍亰ﾑ 舒亠 于亠亳亳, 亰舒仂 仂弍仆仂于亳 亳 亠, 从仂 亢亠 仂弍仆仂于亳仍亳, 亰仆舒ﾑ 从舒从 亳仗仂仍亰仂于舒 仂于亠仄亠仆仆亶 MySQL 仆舒 仗仂仍仆 仄仂仆仂. 仂亳舒仆舒 仆舒 从仂仆亠亠仆亳亳 OST 2020: https://ostconf.com/materials/2857#2857]]> Sun, 13 Sep 2020 14:40:06 GMT /slideshow/mysql-80-percona-238467274/238467274 SvetaSmirnova@slideshare.net(SvetaSmirnova) 弌仂于亠仄亠仆仆仂仄 舒亶仍仂亟 - 仂于亠仄亠仆仆亠 亠亠仆亳: MySQL 8.0 亳 仍亠仆亳 Percona SvetaSmirnova MySQL 于亠亞亟舒 亳仗仂仍亰仂于舒仍亳 仗仂亟 于仂从仂亶 仆舒亞亰从仂亶. 亠亟舒仂仄 舒 弍舒亰舒 弍仍舒 亳 仂舒 舒仄仄 仗仂仗仍仆仄 弍从仆亟仂仄 亟仍 web. 亟仆舒从仂 仆舒亳 仗亠亟舒于仍亠仆亳 仂 舒亶仍仂亟亠 从舒亢亟仄 亞仂亟仂仄 舒亳ﾑ. 仂仍舒 从仂仂 仗亠亠亟舒亳 亟舒仆仆 -> 弍仂仍亠 仂亶于 仗仂亟从仍ﾑ亠仆亳亠仄 从 亳仆亠仆亠 -> 弍仂仍亠 仗仂仍亰仂于舒亠仍亠亶 -> 弍仂仍亠 亟舒仆仆. 舒亟舒亳, 仂亳亠 仗亠亠亟 舒亰舒弍仂亳从舒仄亳 MySQL, 从舒亢亟仄 亞仂亟仂仄 仍仂亢仆ﾑ. 仂仄 亟仂从仍舒亟亠 舒从舒亢 从舒从 仄亠仆磿亳 亠仆舒亳亳 亳仗仂仍亰仂于舒仆亳 MySQL 亰舒 [仗仂亳] 25 仍亠 亠 亳仂亳亳 亳 仂 亟亠仍舒仍亳 亳仆亢亠仆亠, 仂弍 MySQL 仂舒于舒仍舒 舒从舒仍仆仂亶. 亰舒仂仆亠仄 舒从亳亠 亠仄, 从舒从 舒弍仂舒 弍仂仍亳仄 从仂仍亳亠于仂仄 舒从亳于仆 仂亠亟亳仆亠仆亳亶 亳 于仂从亳仄亳 仂弍仄舒仄亳 亟舒仆仆. 亊 仗仂从舒亢 仆舒从仂仍从仂 仂于亠仄亠仆仆亠 于亠亳亳 仍亠 仗舒于仍ﾑ 于仂亰仂亳仄亳 仆舒亞亰从舒仄亳. 亊 仆舒亟亠ﾑ, 仂 仗仂仍亠 仄仂亠亞仂 亟仂从仍舒亟舒 亠 仍舒亠仍亳, 从仂仂亠 亳仗仂仍亰ﾑ 舒亠 于亠亳亳, 亰舒仂 仂弍仆仂于亳 亳 亠, 从仂 亢亠 仂弍仆仂于亳仍亳, 亰仆舒ﾑ 从舒从 亳仗仂仍亰仂于舒 仂于亠仄亠仆仆亶 MySQL 仆舒 仗仂仍仆 仄仂仆仂. 仂亳舒仆舒 仆舒 从仂仆亠亠仆亳亳 OST 2020: https://ostconf.com/materials/2857#2857 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mysql8-200913144006-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> MySQL 于亠亞亟舒 亳仗仂仍亰仂于舒仍亳 仗仂亟 于仂从仂亶 仆舒亞亰从仂亶. 亠亟舒仂仄 舒 弍舒亰舒 弍仍舒 亳 仂舒 舒仄仄 仗仂仗仍仆仄 弍从仆亟仂仄 亟仍 web. 亟仆舒从仂 仆舒亳 仗亠亟舒于仍亠仆亳 仂 舒亶仍仂亟亠 从舒亢亟仄 亞仂亟仂仄 舒亳ﾑ. 仂仍舒 从仂仂 仗亠亠亟舒亳 亟舒仆仆 -&gt; 弍仂仍亠 仂亶于 仗仂亟从仍ﾑ亠仆亳亠仄 从 亳仆亠仆亠 -&gt; 弍仂仍亠 仗仂仍亰仂于舒亠仍亠亶 -&gt; 弍仂仍亠 亟舒仆仆. 舒亟舒亳, 仂亳亠 仗亠亠亟 舒亰舒弍仂亳从舒仄亳 MySQL, 从舒亢亟仄 亞仂亟仂仄 仍仂亢仆ﾑ. 仂仄 亟仂从仍舒亟亠 舒从舒亢 从舒从 仄亠仆磿亳 亠仆舒亳亳 亳仗仂仍亰仂于舒仆亳 MySQL 亰舒 [仗仂亳] 25 仍亠 亠 亳仂亳亳 亳 仂 亟亠仍舒仍亳 亳仆亢亠仆亠, 仂弍 MySQL 仂舒于舒仍舒 舒从舒仍仆仂亶. 亰舒仂仆亠仄 舒从亳亠 亠仄, 从舒从 舒弍仂舒 弍仂仍亳仄 从仂仍亳亠于仂仄 舒从亳于仆 仂亠亟亳仆亠仆亳亶 亳 于仂从亳仄亳 仂弍仄舒仄亳 亟舒仆仆. 亊 仗仂从舒亢 仆舒从仂仍从仂 仂于亠仄亠仆仆亠 于亠亳亳 仍亠 仗舒于仍ﾑ 于仂亰仂亳仄亳 仆舒亞亰从舒仄亳. 亊 仆舒亟亠ﾑ, 仂 仗仂仍亠 仄仂亠亞仂 亟仂从仍舒亟舒 亠 仍舒亠仍亳, 从仂仂亠 亳仗仂仍亰ﾑ 舒亠 于亠亳亳, 亰舒仂 仂弍仆仂于亳 亳 亠, 从仂 亢亠 仂弍仆仂于亳仍亳, 亰仆舒ﾑ 从舒从 亳仗仂仍亰仂于舒 仂于亠仄亠仆仆亶 MySQL 仆舒 仗仂仍仆 仄仂仆仂. 仂亳舒仆舒 仆舒 从仂仆亠亠仆亳亳 OST 2020: https://ostconf.com/materials/2857#2857
弌仂于亠仄亠仆仆仂仄 舒亶仍仂亟 - 仂于亠仄亠仆仆亠 亠亠仆亳: MySQL 8.0 亳 仍亠仆亳 Percona from Sveta Smirnova
]]> 575 0 https://cdn.slidesharecdn.com/ss_thumbnails/mysql8-200913144006-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 How to Avoid Pitfalls in Schema Upgrade with Galera /slideshow/how-to-avoid-pitfalls-in-schema-upgrade-with-galera/226915412 galeraschema-200204205934
Galera Cluster for MySQL is a 100% synchronized cluster in regards to data modification operations (DML). It is ensured by the optimistic locking model and ability to rollback a transaction, which cannot be applied on all nodes. However, schema changes (DDL operations) are not transactional in MySQL, which adds complexity when you need to perform an upgrade or change schema of the database. Changes made by DDL may affect results of the queries. Therefore all modifications must replicate on all nodes prior next data access. For operations which run momentarily it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to safest synchronous blocking schema upgrade method TOI Galera also supports more relaxed, thought not safe, method RSU. In her talk Sveta will describe which pitfalls you can hit while performing the change using one or another method, why and how to avoid them. Presented at MariaDB Day Brussels 0202 2020: https://mariadb.org/mariadb-day-brussels-0202-2020-provisional-schedule/]]>
Galera Cluster for MySQL is a 100% synchronized cluster in regards to data modification operations (DML). It is ensured by the optimistic locking model and ability to rollback a transaction, which cannot be applied on all nodes. However, schema changes (DDL operations) are not transactional in MySQL, which adds complexity when you need to perform an upgrade or change schema of the database. Changes made by DDL may affect results of the queries. Therefore all modifications must replicate on all nodes prior next data access. For operations which run momentarily it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to safest synchronous blocking schema upgrade method TOI Galera also supports more relaxed, thought not safe, method RSU. In her talk Sveta will describe which pitfalls you can hit while performing the change using one or another method, why and how to avoid them. Presented at MariaDB Day Brussels 0202 2020: https://mariadb.org/mariadb-day-brussels-0202-2020-provisional-schedule/]]> Tue, 04 Feb 2020 20:59:34 GMT /slideshow/how-to-avoid-pitfalls-in-schema-upgrade-with-galera/226915412 SvetaSmirnova@slideshare.net(SvetaSmirnova) How to Avoid Pitfalls in Schema Upgrade with Galera SvetaSmirnova Galera Cluster for MySQL is a 100% synchronized cluster in regards to data modification operations (DML). It is ensured by the optimistic locking model and ability to rollback a transaction, which cannot be applied on all nodes. However, schema changes (DDL operations) are not transactional in MySQL, which adds complexity when you need to perform an upgrade or change schema of the database. Changes made by DDL may affect results of the queries. Therefore all modifications must replicate on all nodes prior next data access. For operations which run momentarily it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to safest synchronous blocking schema upgrade method TOI Galera also supports more relaxed, thought not safe, method RSU. In her talk Sveta will describe which pitfalls you can hit while performing the change using one or another method, why and how to avoid them. Presented at MariaDB Day Brussels 0202 2020: https://mariadb.org/mariadb-day-brussels-0202-2020-provisional-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/galeraschema-200204205934-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Galera Cluster for MySQL is a 100% synchronized cluster in regards to data modification operations (DML). It is ensured by the optimistic locking model and ability to rollback a transaction, which cannot be applied on all nodes. However, schema changes (DDL operations) are not transactional in MySQL, which adds complexity when you need to perform an upgrade or change schema of the database. Changes made by DDL may affect results of the queries. Therefore all modifications must replicate on all nodes prior next data access. For operations which run momentarily it can be easily achieved, but schema changes may take hours to apply. Therefore in addition to safest synchronous blocking schema upgrade method TOI Galera also supports more relaxed, thought not safe, method RSU. In her talk Sveta will describe which pitfalls you can hit while performing the change using one or another method, why and how to avoid them. Presented at MariaDB Day Brussels 0202 2020: https://mariadb.org/mariadb-day-brussels-0202-2020-provisional-schedule/
How to Avoid Pitfalls in Schema Upgrade with Galera from Sveta Smirnova
]]> 301 1 https://cdn.slidesharecdn.com/ss_thumbnails/galeraschema-200204205934-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 How Safe is Asynchronous Master-Master Setup? /slideshow/how-safe-is-asynchronous-mastermaster-setup/226915044 asyncfosdem2020-200204205537
It is common knowledge that built-in asynchronous master-master (active-active) replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous master-master replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. Presented in "MySQL, MariaDB and Friends devroom" at Fosdem in 2020: https://fosdem.org/2020/schedule/event/mysql_master_master/]]>
It is common knowledge that built-in asynchronous master-master (active-active) replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous master-master replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. Presented in "MySQL, MariaDB and Friends devroom" at Fosdem in 2020: https://fosdem.org/2020/schedule/event/mysql_master_master/]]> Tue, 04 Feb 2020 20:55:37 GMT /slideshow/how-safe-is-asynchronous-mastermaster-setup/226915044 SvetaSmirnova@slideshare.net(SvetaSmirnova) How Safe is Asynchronous Master-Master Setup? SvetaSmirnova It is common knowledge that built-in asynchronous master-master (active-active) replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous master-master replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. Presented in "MySQL, MariaDB and Friends devroom" at Fosdem in 2020: https://fosdem.org/2020/schedule/event/mysql_master_master/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/asyncfosdem2020-200204205537-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> It is common knowledge that built-in asynchronous master-master (active-active) replication is not safe. I remember times when the official MySQL User Reference Manual stated that such an installation is not recommended for production use. Some experts repeat this claim even now. While this statement is generally true, I worked with thousands of shops that successfully avoided asynchronous replication limitations in active-active setups. In this talk, I will show how they did it, demonstrate situations when asynchronous master-master replication is the best possible high availability option and beats such solutions as Galera or InnoDB Clusters. I will also cover common mistakes, leading to disasters. Presented in &quot;MySQL, MariaDB and Friends devroom&quot; at Fosdem in 2020: https://fosdem.org/2020/schedule/event/mysql_master_master/
How Safe is Asynchronous Master-Master Setup? from Sveta Smirnova
]]> 533 1 https://cdn.slidesharecdn.com/ss_thumbnails/asyncfosdem2020-200204205537-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction to MySQL Query Tuning for Dev[Op]s /slideshow/introduction-to-mysql-query-tuning-for-devops/179348671 qtdevops-191005204425
To get data, we query the database. MySQL does its best to return requested bytes as fast as possible. However, it needs human help to identify what is important and should be accessed in the first place. Queries, written smartly, can significantly outperform automatically generated ones. Indexes and Optimizer statistics, not limited to the Histograms only, help to increase the speed of the query a lot. In this session, I will demonstrate by examples of how MySQL query performance can be improved. I will focus on techniques, accessible by Developers and DevOps rather on those which are usually used by Database Administrators. In the end, I will present troubleshooting tools which will help you to identify why your queries do not perform. Then you could use the knowledge from the beginning of the session to improve them.]]>
To get data, we query the database. MySQL does its best to return requested bytes as fast as possible. However, it needs human help to identify what is important and should be accessed in the first place. Queries, written smartly, can significantly outperform automatically generated ones. Indexes and Optimizer statistics, not limited to the Histograms only, help to increase the speed of the query a lot. In this session, I will demonstrate by examples of how MySQL query performance can be improved. I will focus on techniques, accessible by Developers and DevOps rather on those which are usually used by Database Administrators. In the end, I will present troubleshooting tools which will help you to identify why your queries do not perform. Then you could use the knowledge from the beginning of the session to improve them.]]> Sat, 05 Oct 2019 20:44:25 GMT /slideshow/introduction-to-mysql-query-tuning-for-devops/179348671 SvetaSmirnova@slideshare.net(SvetaSmirnova) Introduction to MySQL Query Tuning for Dev[Op]s SvetaSmirnova To get data, we query the database. MySQL does its best to return requested bytes as fast as possible. However, it needs human help to identify what is important and should be accessed in the first place. Queries, written smartly, can significantly outperform automatically generated ones. Indexes and Optimizer statistics, not limited to the Histograms only, help to increase the speed of the query a lot. In this session, I will demonstrate by examples of how MySQL query performance can be improved. I will focus on techniques, accessible by Developers and DevOps rather on those which are usually used by Database Administrators. In the end, I will present troubleshooting tools which will help you to identify why your queries do not perform. Then you could use the knowledge from the beginning of the session to improve them. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/qtdevops-191005204425-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> To get data, we query the database. MySQL does its best to return requested bytes as fast as possible. However, it needs human help to identify what is important and should be accessed in the first place. Queries, written smartly, can significantly outperform automatically generated ones. Indexes and Optimizer statistics, not limited to the Histograms only, help to increase the speed of the query a lot. In this session, I will demonstrate by examples of how MySQL query performance can be improved. I will focus on techniques, accessible by Developers and DevOps rather on those which are usually used by Database Administrators. In the end, I will present troubleshooting tools which will help you to identify why your queries do not perform. Then you could use the knowledge from the beginning of the session to improve them.
Introduction to MySQL Query Tuning for Dev[Op]s from Sveta Smirnova
]]> 1077 1 https://cdn.slidesharecdn.com/ss_thumbnails/qtdevops-191005204425-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Billion Goods in Few Categories: How Histograms Save a Life? /slideshow/billion-goods-in-few-categories-how-histograms-save-a-life-178766092/178766092 histogramsplam2019-191003114810
We store data with an intention to use it: search, retrieve, group, sort... To do it effectively the MySQL Optimizer uses index statistics when compiles the query execution plan. This approach works excellently unless your data distribution is not even. Last year I worked on several tickets where data follow the same pattern: millions of popular products fit into a couple of categories and rest used the rest. We had a hard time to find a solution for retrieving goods fast. We offered workarounds for version 5.7. However new MariaDB and MySQL 8.0 feature: histograms, - would work better, cleaner and faster. The idea of the talk was born. Of course, histograms are not a panacea and do not help in all situations. I will discuss: how index statistics physically stored by the storage engine which data exchanged with the Optimizer why it is not enough to make correct index choice when histograms can help and when they cannot differences between MySQL and MariaDB histograms]]>
We store data with an intention to use it: search, retrieve, group, sort... To do it effectively the MySQL Optimizer uses index statistics when compiles the query execution plan. This approach works excellently unless your data distribution is not even. Last year I worked on several tickets where data follow the same pattern: millions of popular products fit into a couple of categories and rest used the rest. We had a hard time to find a solution for retrieving goods fast. We offered workarounds for version 5.7. However new MariaDB and MySQL 8.0 feature: histograms, - would work better, cleaner and faster. The idea of the talk was born. Of course, histograms are not a panacea and do not help in all situations. I will discuss: how index statistics physically stored by the storage engine which data exchanged with the Optimizer why it is not enough to make correct index choice when histograms can help and when they cannot differences between MySQL and MariaDB histograms]]> Thu, 03 Oct 2019 11:48:10 GMT /slideshow/billion-goods-in-few-categories-how-histograms-save-a-life-178766092/178766092 SvetaSmirnova@slideshare.net(SvetaSmirnova) Billion Goods in Few Categories: How Histograms Save a Life? SvetaSmirnova We store data with an intention to use it: search, retrieve, group, sort... To do it effectively the MySQL Optimizer uses index statistics when compiles the query execution plan. This approach works excellently unless your data distribution is not even. Last year I worked on several tickets where data follow the same pattern: millions of popular products fit into a couple of categories and rest used the rest. We had a hard time to find a solution for retrieving goods fast. We offered workarounds for version 5.7. However new MariaDB and MySQL 8.0 feature: histograms, - would work better, cleaner and faster. The idea of the talk was born. Of course, histograms are not a panacea and do not help in all situations. I will discuss: how index statistics physically stored by the storage engine which data exchanged with the Optimizer why it is not enough to make correct index choice when histograms can help and when they cannot differences between MySQL and MariaDB histograms <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/histogramsplam2019-191003114810-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We store data with an intention to use it: search, retrieve, group, sort... To do it effectively the MySQL Optimizer uses index statistics when compiles the query execution plan. This approach works excellently unless your data distribution is not even. Last year I worked on several tickets where data follow the same pattern: millions of popular products fit into a couple of categories and rest used the rest. We had a hard time to find a solution for retrieving goods fast. We offered workarounds for version 5.7. However new MariaDB and MySQL 8.0 feature: histograms, - would work better, cleaner and faster. The idea of the talk was born. Of course, histograms are not a panacea and do not help in all situations. I will discuss: how index statistics physically stored by the storage engine which data exchanged with the Optimizer why it is not enough to make correct index choice when histograms can help and when they cannot differences between MySQL and MariaDB histograms
Billion Goods in Few Categories: How Histograms Save a Life? from Sveta Smirnova
]]> 191 0 https://cdn.slidesharecdn.com/ss_thumbnails/histogramsplam2019-191003114810-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Billion Goods in a Few Categories: When Optimizer Histograms Help and When They Dont /slideshow/a-billion-goods-in-a-few-categories-when-optimizer-histograms-help-and-when-they-dont/174452290 histogramsoow2019-190921043520
Last year this sessions speaker worked on several cases where data followed the same pattern: millions of popular products fit into a couple of categories, and the rest uses the rest. Her team had a hard time finding a solution for retrieving goods quickly. MySQL 8.0 has a feature that resolves such issues: optimizer histograms, storing statistics of an exact number of values in each data bucket. In real life, histograms dont help with all queries accessing nonuniform data. How you write a statement, the number of rows in the table, data distribution: All of these may affect the use of histograms. This presentation shows examples demonstrating how the optimizer works in each case, describes how to create histograms, and covers differences between MySQL and Oracle implementations.]]>
Last year this sessions speaker worked on several cases where data followed the same pattern: millions of popular products fit into a couple of categories, and the rest uses the rest. Her team had a hard time finding a solution for retrieving goods quickly. MySQL 8.0 has a feature that resolves such issues: optimizer histograms, storing statistics of an exact number of values in each data bucket. In real life, histograms dont help with all queries accessing nonuniform data. How you write a statement, the number of rows in the table, data distribution: All of these may affect the use of histograms. This presentation shows examples demonstrating how the optimizer works in each case, describes how to create histograms, and covers differences between MySQL and Oracle implementations.]]> Sat, 21 Sep 2019 04:35:20 GMT /slideshow/a-billion-goods-in-a-few-categories-when-optimizer-histograms-help-and-when-they-dont/174452290 SvetaSmirnova@slideshare.net(SvetaSmirnova) A Billion Goods in a Few Categories: When Optimizer Histograms Help and When They Dont SvetaSmirnova Last year this sessions speaker worked on several cases where data followed the same pattern: millions of popular products fit into a couple of categories, and the rest uses the rest. Her team had a hard time finding a solution for retrieving goods quickly. MySQL 8.0 has a feature that resolves such issues: optimizer histograms, storing statistics of an exact number of values in each data bucket. In real life, histograms dont help with all queries accessing nonuniform data. How you write a statement, the number of rows in the table, data distribution: All of these may affect the use of histograms. This presentation shows examples demonstrating how the optimizer works in each case, describes how to create histograms, and covers differences between MySQL and Oracle implementations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/histogramsoow2019-190921043520-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Last year this sessions speaker worked on several cases where data followed the same pattern: millions of popular products fit into a couple of categories, and the rest uses the rest. Her team had a hard time finding a solution for retrieving goods quickly. MySQL 8.0 has a feature that resolves such issues: optimizer histograms, storing statistics of an exact number of values in each data bucket. In real life, histograms dont help with all queries accessing nonuniform data. How you write a statement, the number of rows in the table, data distribution: All of these may affect the use of histograms. This presentation shows examples demonstrating how the optimizer works in each case, describes how to create histograms, and covers differences between MySQL and Oracle implementations.
A Billion Goods in a Few Categories: When Optimizer Histograms Help and When They Dont from Sveta Smirnova
]]> 319 0 https://cdn.slidesharecdn.com/ss_thumbnails/histogramsoow2019-190921043520-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-SvetaSmirnova-48x48.jpg?cb=1712676143 I work in Percona as Principal Support Engineer for MySQL, its forks and utilities. Before I worked in Bugs Analysis MySQL Support Group since year 2006 in MySQL AB, then Sun, then Oracle. In addition to regular daily tasks of solving tricky support issues and verifying bug reports I also work on bugs priority, closely work with MySQL Enterprise Backup Development Team, manage MySQL Support team hardware and program JSON UDFs. Working on bugs priority and as Support representative in MySQL Enterprise Backup Development Team requires good communication, diplomatic skills as well as great problem solving abilities. I worked with Oracle University on MySQL 5.6 certification, provided "MySQ... svetasmirnova.livejournal.com https://cdn.slidesharecdn.com/ss_thumbnails/mysql2024-240418173103-db326826-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/mysql-2024-mysql-8-5/267334433 MySQL 2024: 舒亠仄 仗亠亠... https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovak8database-230611132611-f8501a0a-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/database-in-kubernetes-diagnostics-and-monitoring/258364703 Database in Kubernetes... https://cdn.slidesharecdn.com/ss_thumbnails/svetasmirnovamustgoodnice-230611132140-f006b307-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/mysql-database-monitoring-must-good-and-nice-to-have/258364636 MySQL Database Monitor...