Since MySQL 5.7 we have a new player in the field, MySQL InnoDB Cluster. This is an Oracle High Availability solution that can be easily installed over MySQL to get High Availability with multi-master capabilities and automatic failover.

This solution consists in 3 components: InnoDB Group Replication, MySQL Router and MySQL Shell, you can see how these components interact in this graphic:

In this three blog post series, we will cover each of this components to get a sense of what this tool provides and how it can help with architecture decisions.

Group Replication

This is …

This post is mainly inspired by findings from the previous testing of MySQL 8.0 on TPCC workload(s) and observations from IO-bound Sysbench OLTP on Optane -vs- SSD. But also by several "urban myths" I'm often hearing when discussing with users about their IO-bound OLTP performance problems :
Myth #1 : "if I'll double the number of my storage drives -- I'll get x2 times better TPS !"

• this was mostly true during "HDD era", and again..
• (ex.: a single thread app doing single random IO reads from a single HDD will not go faster by doing the same from 2x HDD -- similar like single thread workload will not run faster on 8CPU cores -vs- 2CPU cores, etc.)
• all depends …

MySQL Performance on IO-bound workloads is still extremely depending on the underlaying storage layer (thus is directly depending on your Storage Performance).. Indeed, flash storage is definitively changing the game, but even with flash there is, as usual, "flash and flash" -- all storage vendors are improving their stuff constantly, so every time you have something new to discover and to learn ;-)) During all my MySQL 8.0 GA tests I was very pleasantly surprised by IO performance delivered by Intel Optane SSD. However, what the storage device can deliver alone on pure IO tests is not at all the same to what you could observe when it's used by MySQL -- unfortunately, in the past I've observed many cases when with a device claimed to be x2 times faster we were even not observing 10% gain.. But MySQL 8.0 is probably the most best placed MySQL version today to re-visit all this IO-bound story (there are many "under-hood" changes in the code helping to …

In MySQL 8.0 there are two new features designed to support lock handling: NOWAIT and SKIP LOCKED. In this post, we’ll look at how MySQL 8.0 handles hot rows. Up until now, how have you handled locks that are part of an active transaction or are hot rows? It’s likely that you have the application attempt to access the data, and if there is a lock on the requested rows, you incur a timeout and have to retry the transaction. These two new features help you to implement sophisticated lock handling scenarios allowing you to handle timeouts better and improve the application’s performance.

To demonstrate I’ll use this product table.

mysql> select @@version;
+-----------+
| @@version |
+-----------+
| 8.0.11    |
+-----------+
1 row in set (0.00 sec)

CREATE TABLE `product` (
`p_id` int(11) NOT NULL AUTO_INCREMENT,
`p_name` varchar(255) DEFAULT NULL,
`p_cost` decimal(19,4) NOT NULL,
`p_availability` enum('YES','NO') …

I just posted an article on the Percona Community Blog.  You can access it following this link:

A Nice Feature in MariaDB 10.3: no InnoDB Buffer Pool in Core Dumps

I do not know if I will stop publishing posts on my personal blog or use both, I will see how things go.  In the rest of this post, I will share why I published there and how things went in the process.

So there is a Percona

MariaDB 10.3 is now generally available (10.3.7 was released GA on 2018-05-25). The article What’s New in MariaDB Server 10.3 by the MariaDB Corporation lists three key improvements in 10.3: temporal data processing, Oracle compatibility features, and purpose-built storage engines. Even if I am excited about MyRocks and curious on Spider, I am also very interested in less flashy but still very important changes that make running the database in production easier. This post describes such improvement: no InnoDB Buffer Pool in core dumps.

Hidden in the …

As Mydbops we have consulted  many large scale MySQL deployments. This presentation is about one of our customer who is one of the largest retailer in North America. This is about their data migration to InnoDB Cluster ( MySQL ) from an enterprise database.

In this blog, we will see the very basic thing “I” of “ACID” and an important property of Transaction ie., “ISOLATION”

The isolation defines the way in which the MySQL server (InnoDB) separates each transaction from other concurrent running transaction in the server and also ensures that the transactions are processed in a reliable way. If transactions are not isolated then one transaction could modify the data that another transaction is reading hence creating data inconsistency. Isolation levels determine how isolated the transactions are from each other.

MySQL supports all four the isolation levels that SQL-Standard defines.The four isolation levels are

• READ UNCOMMITTED
• READ COMMITTED
• REPEATABLE READ
• SERIALIZABLE

The Isolation level’s can be set globally or session based on our requirements.

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.

…

The Write Ahead Log (WAL) is one of the most important components of a database. All the changes to data files are logged in the WAL (called the redo log in InnoDB). This allows to postpone the moment when the modified pages are flushed to disk, still protecting from data losses.…