The latest from the MySQL community

Like I said, I never had much reason to use table compression, and only recently looked into the topic. MySQL Page Compression looks a lot easier at the database end of things, but relies on hole punching support in the file system. Let’s have a look at what that means.

Files, Inodes and Arrays of Blocks

The original Unix filesystem saw the disk as a sea of blocks, which were represented in a free map as an array of bits. Files have numbers, which are an index into an array of so-called inode structures. Inodes store the files metadata and contain an array of block numbers, which make up the actual file. The array is folded multiple times, to optimize for the more common case of small files: The first few block numbers were stored in the inode, followed by a pointer to a block containing file block numbers, then a pointer …

Like I said, I never had much reason to use table compression, and only recently looked into the topic. MySQL Page Compression looks a lot easier at the database end of things, but relies on hole punching support in the file system. Let’s have a look at what that means.

Files, Inodes and Arrays of Blocks

The original Unix filesystem saw the disk as a sea of blocks, which were represented in a free map as an array of bits. Files have numbers, which are an index into an array of so-called inode structures. Inodes store the files metadata and contain an array of block numbers, which make up the actual file. The array is folded multiple times, to optimize for the more common case of small files: The first few block numbers were stored in the inode, followed by a pointer to a block containing file block numbers, then a pointer to a block containing pointers to blocks of file block numbers and so on.

The block list inside …

Here’s a second post focusing on the performance of MySQL on ZFS in cloud environments. In the first post, MySQL/ZFS Performance Update, we compared the performances of ZFS and ext4. This time we’ll look at the benefits of using ephemeral storage devices. These devices, called ephemeral in AWS, local in Google cloud, and temporary in Azure, are provided directly by the virtualization host. They are not network-attached and are not IO throttled, at least compared to regular storage. Not only can they handle a high number of IOPs, but their IO latency is also very low. For simplicity, we’ll name these devices local ephemeral. They can be quite large: Azure lsv2, Google Cloud n2, and AWS i3 instance types offer TBs of fast NVMe local ephemeral storage.

The main drawback of local ephemeral …

I never had much reason to use table compression, so I largely ignored the topic in MySQL. I knew that MySQL had table compression since 5.1, but I also knew the implementation was horribly complicated and double stored all data. There is also page compression, a feature introduced with 5.7, which replaces table compression and works much better.

Table Compression

Table Compression is available in MySQL 5.1 and newer. It is used by setting an InnoDB table up with ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8 or similar, for even smaller key block sizes. A lot of status tables in INFORMATION_SCHEMA.%CMP% are available to monitor it.

Table compression creates smaller pages (in the size you specify with KEY_BLOCK_SIZE), and loads and stores compressed pages of this smaller size from and to the …

We observe a large number of messages of the kind

The table '../tmp/#sql…' is full

Before MySQL 8

In older Versions of MySQL, implied temporary tables are being created, whenever your EXPLAIN contained the phrase using temporary.

In this case, MySQL would create an in-memory temporary table to materialize an intermediate query result, and then continue to process the data from there. If that temporary table was larger than some configurable limit, the temporary table would instead be converted to a MyISAM table on disk, streamed out, and then work would continue with this.

This has a large number of disadvantages:

• A table in the MEMORY storage engine can have no variable length columns. That means, any VARCHAR column gets converted to a CHAR column in the MEMORY version of that table.
  …

Title: Procedure for MySQL Database Installation ( 5.7.xx – Enterprise) and setup for SSL on RHEL

Purpose of the Document

Procedure for MySQL Database Installation ( 5.7.xx – Enterprise) and setup for SSL on RHEL

Procedure

=====================================================================

MySQL Database Installation –RHEL 7.x – DB Version 5.7.x – Enterprise Edition

=====================================================================

The below procedure is related to MySQL Database Installation Version 5.7.x on RHEL 7.x. ( Enterprise Edition)

(1) Check the OS version of RHEL by using below command.

[root@DB_Server ~]# cat /etc/redhat-release

(2) Create local group for dba

groupadd -g 1020 dba

(3) Create local user for mysql

useradd -g dba -u 888 -d /export/home/mysql -m mysql or useradd -g dba -u 888 -d /data/mysql …

This blog post is inspired by Jesper's recent blog post on how the automatic update of InnoDB persistent statistics may never trigger if servers are restarted frequently. However, the matter is even worse! In this blog post I will show that even when the automatic recalculation is performed, there are no guarantees as to when the server will see the changes.

Myths about persistent statistics

I must admit that I, for a long time, believed in the myths I was told about when updates to InnoDB's index statistics become visible to the query optimizer. There were basically two variants:

• The updated statistics will only be visible to new connections (i.e., sessions that are started after the statistics was updated)
• When a new connection accesses the table, the updated statistics …

MySQL, the world’s most popular open source database, is available as a managed cloud service in Oracle Cloud Infrastructure (OCI) under the name of MySQL Database Service (MDS).

This is the sixth episode of “Discovering MySQL Database Service“, a series of tutorials where I will show you, step by step, how to use MySQL Database Service and some other Oracle Cloud Infrastructure services.

In this episode, we’ll introduce the concept of Security Lists a virtual firewall to control traffic at the network packet level.

The post Discovering MySQL Database Service – Episode 6 – Update the Private Subnet Security List first appeared on dasini.net - Diary of a MySQL expert.

In part 1 of the series about Point-in-Time Recovery in OCI MDS, we saw how to stream the binary log to Object Storage.

In this blog post, we will see how we can restore the data up to certain point.

The high level process is simple:

1. we need to restore the last backup just before the point we want to return to
2. find the last GTID that was executed in that backup (not 100% mandatory but can accelerate the process)
3. choose what is the objective:
   1. just skip one transaction (following transaction could depend on it)
   2. recover up to that transaction and skip all the following ones
4. replay the binary logs taking in consideration the chosen option of point 3

The scenario …

Since MySQL 5.6 InnoDB has supported persistent index statistics. This means that when you restart MySQL, InnoDB does not have to recalculate the statistics for the tables, rather it can read the statistics from its persistent storage. This has several advantages over the transient statistics, but as it turns out, there is also a catch: MySQL may under some circumstances never get around to update the index statistics. This particularly affects instances that are restarted frequently and tables with a large number of rows.

Information

Persistent statistics are the default, so unless you have explicitly chosen not to use them, then you are.

Background

Before I dive into why there are scenarios where persistent statistics are never updated, it is necessary to recap how persistent statistics work. Every time the statistics are updated, the result is stored in the mysql.innodb_index_stats table with …