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Displaying posts with tag: mysql performance (reset)
Tuning MyRocks for performance

There are basically two things which I majorly like about using MyRocks, 1. LSM Advantage – smaller space & lower write amplification and 2. Best of MySQL like replication, storage engine centric database infrastructure operations and MySQL orchestration tools. Facebook built RocksDB as an embeddable and persistent key-value store with lower amplification factor () compared to InnoDB. Let me explain a scenario were InnoDB proves less efficient compared to RocksDB in SSD:
We know InnoDB is constrained by a fixed compressed page size. Alignment during fragmentation and compression causes extra unused space because the leaf nodes are not full. Let’s consider a InnoDB table with a compressed page size of 8KB. A 16KB in-memory page compressed to 5KB still uses 8KB on storage. Adding to this, each entry in the primary key index has 13 bytes of metadata (6 byte transaction id + 7 byte rollback pointer), and …

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MySQL Replication Notes


The MySQL Replication was my first project as a Database Administrator (DBA) and I have been working with Replication technologies for last few years and I am indebted to contribute my little part for development of this technology. MySQL supports different replication topologies, having better understanding of basic concepts will help you in building and managing various and complex topologies. I am writing here, some of the key points to taken care when you are building MySQL replication. I consider this post as a starting point for building a high performance and consistent MySQL servers.  Let me start with below key points Hardware. MySQL Server Version MySQL Server Configuration Primary Key Storage Engine I will update this post with relevant points, whenever I get time. I am trying to provide generic concepts and it will be applicable to all version of MySQL, however, some of the concepts are new and applicable to latest versions …

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Installation and configuration of Percona XtraDB Cluster on CentOS 7.3

This blog will show how to install the Percona XtraDB Cluster on three CentOS 7.3 servers, using the packages from Percona repositories. This is a step-by-step installation and configuration blog, We recommend Percona XtraDB Cluster for maximum availability / reliability and scale-out READ/WRITE optimally. We are an private-label independent and vendor neutral consulting, support, managed services and education solutions provider for MySQL, MariaDB, Percona Server and ClickHouse with core expertise in performance, scalability, high availability and database reliability engineering. All our blog posts are purely focussed on education and research across open source database systems infrastructure operations. To engage us for building and managing web-scale database infrastructure operations, Please contact us on contact@minervadb.com

This cluster will be assembled of three servers/nodes:

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Installation and configuration of Percona XtraDB Cluster on CentOS 7.3

This blog will show how to install the Percona XtraDB Cluster on three CentOS 7.3 servers, using the packages from Percona repositories. This is a step-by-step installation and configuration blog, We recommend Percona XtraDB Cluster for maximum availability / reliability and scale-out READ/WRITE optimally. We are an private-label independent and vendor neutral consulting, support, managed services and education solutions provider for MySQL, MariaDB, Percona Server and ClickHouse with core expertise in performance, scalability, high availability and database reliability engineering. All our blog posts are purely focussed on education and research across open source database systems infrastructure operations. To engage us for building and managing web-scale database infrastructure operations, Please contact us on contact@minervadb.com  

This cluster will be assembled of three …

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Saving With MyRocks in The Cloud

The main focus of a previous blog post was the performance of MyRocks when using fast SSD devices. However, I figured that MyRocks would be beneficial for use in cloud workloads, where storage is either slow or expensive.

In that earlier post, we demonstrated the benefits of MyRocks, especially for heavy IO workloads. Meanwhile, Mark wrote in his blog that the CPU overhead in MyRocks might be significant for CPU-bound workloads, but this should not be the issue for IO-bound workloads.

In the cloud the cost of resources is a major consideration. Let’s review the annual cost for the processing and storage …

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Auditing MariaDB for Secured Database Infrastructure Operations

When you are building Database Infrastructure for an data sensitive business (like financial services, digital commerce, advertising media solutions, healthcare etc. ) governed by compliance and policies, You are expected to maintain the audit log of the transactions to investigate, if you ever suspect something unacceptable (i.e., user updating / deleting data) happening to your database . MariaDB provides Audit Plugin (MariaDB started including by default the Audit Plugin from versions 10.0.10 and 5.5.37, and it can be installed in any version from MariaDB 5.5.20.) to log the server activity, Although the MariaDB Audit Plugin has some unique features available only for MariaDB, it can be used also with MySQL. MariaDB Audit Plugin log the details like who connected to server (i.e., username and host), what queries were executed, the tables accessed and server variables changed. This information is retained in a rotating log file or sent to …

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On MySQL and Intel Optane performance

Recently, Dimitri published the results of measuring MySQL 8.0 on Intel Optane storage device. In this blog post, I wanted to look at this in more detail and explore the performance of MySQL 8, MySQL 5.7 and Percona Server for MySQL using a similar set up. The Intel Optane is a very capable device, so I was puzzled that Dimitri chose MySQL options that are either not safe or not recommended for production workloads.

Since we have an Intel Optane in our labs, I wanted to run a similar benchmark, but using settings that we would recommend our customers to use, namely:

  • use innodb_checksum
  • use innodb_doublewrite
  • use binary logs with sync_binlog=1
  • enable (by default) Performance …
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Data Integrity and Performance Considerations in MySQL Semisynchronous Replication

MySQL semisynchronous replication provides improved data integrity because when a commit returns successfully, it’s known that the data exists in at least two places – the master and its slave. In this blog post, we review some of the MySQL hosting configurations that influence the data integrity and performance aspects of semisynchronous replication. We’ll be using InnoDB storage engine and GTID-based replication in a 3-node replica set (master and 2 slaves), which will ensure there is redundancy in the slaves. This means that if there are issues with one slave, we can fall back on the other.

Configurations Applicable to Both Master and Slave Nodes

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What is MySQL partitioning ?

MySQL partitioning makes data distribution of individual tables (typically we recommend partition for large & complex I/O table for performance, scalability and manageability) across multiple files based on partition strategy / rules. In very simple terms, different portions of table are stored as separate tables in different location to distribute I/O optimally. The user defined division of data by some rule is known as partition function, In MySQL we partition data by RANGE of values / LIST of values / internal hashing function / linear hashing function. By restricting the query examination on the selected partitions by matching rows increases the query performance by multiple times compared to the same query on a non partitioned table, This methodology is also called partition pruning (trimming of unwanted partitions), Please find below example of partition pruning:

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Chunk Change: InnoDB Buffer Pool Resizing

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.

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