MySQL have the nice feature, which helps to write the error log with JSON format . This can be achieved through the MySQL components . In this blog, I am going to show the complete walkthrough involved in this process .

What is MySQL component ?

from MySQL document ,

MySQL Server includes a component-based infrastructure for extending server capabilities. A component provides services that are available to the server and other components. (With respect to service use, the server is a component, equal to other components.) Components interact with each other only through the services they provide.

Link : https://dev.mysql.com/doc/refman/8.0/en/server-components.html

How to enable the JSON logging ?

Step 1 : ( Installing the component ) :

…

Data security plays a major role in current age. Privacy matters a lot. Data masking is one of the Key Features when comes to security.

• In MySQL community versions if you want to mask your data, You can go with a Maxscale load balancer.
• They introduced a new masking filter on the Maxscale 2.1 version.
• My colleague Prasanth written about column-level data masking. For reference click here Column Level Data Masking.
• In MySQL 8.0 Enterprise they have introduced a new security feature called data masking.
• This feature was introduced in MySQL 8.0.13 Enterprise Edition and it provides data masking and de-identification capabilities.

What is Masking ?

• Transformation of existing data to mask it and remove …

MySQL Audit Logging — How to Avoid Data Overload

In the last few months, our solution engineers have had many discussions with security and operation teams about how to implement MySQL auditing. In some cases, these teams have been asked to implement new database auditing in response to a security breach or to meet a regulatory requirement (PCI, HIPPA, GDPR or CCPA).

More often, however, these companies are switching audit strategies because their existing method has led to data overload. They typically start by monitoring everything, sometimes even using the general query log. They quickly learn that even with moderate database activity, the amount of generated data soon becomes overwhelming.

Below are a couple considerations for selecting your audit strategy.

1. Review your schema and identify data that *must* be audited. It’s likely your company’s personal identifiable information (PII) …

Disclaimer: The following blog post does not try to provide a solution for split-brain situations, and the example provided is for demonstrative purposes only. Inconsistencies resulting from a split-brain scenario might possibly be more complex than the one shown, so do not use the following example as a complete guide.

What is Split-Brain?

A split-brain scenario is the result of two data sets (which were originally synced) losing the ability to sync while potentially continuing to receive DMLs over the same rows and ids on both sides. This could have consequences such as data corruption or inconsistencies where each side has data that does not exist on the other side.

For example before split-brain:

After split-brain:

Node1:

Node2:

It can be seen that after the split-brain scenario there are many differences between the nodes:

• Customer row id=2 was deleted …

What You May Not Know About Random Number Generation in Sysbench

Sysbench is a well known and largely used tool to perform benchmarking. Originally written by Peter Zaitsev in early 2000, it has become a de facto standard when performing testing and benchmarking. Nowadays it is maintained by Alexey Kopytov and can be found in Github at https://github.com/akopytov/sysbench.

What I have noticed though, is that while widely-used, some aspects of sysbench are not really familiar to many. For instance, the easy way to expand/modify the MySQL tests is using the lua extension, or the embedded way it handles the random number generation. 

Why This Article? 

I wrote this article with the intent to show how easy it can be to customize sysbench to make it what you need. There are many different ways to extend sysbench use, and one of these is …

One problem I have experienced during logical exporting and importing databases is the tools don’t output any progress indicator (or anything at all really) and using the -v (verbose) switch outputs every single MySQL command being run from the import file. As, importing and exporting of databases  is one of the most frequent activity being performed , I Just felt the need of some tool that could help me check the approximate progress of import and export of databases going on.

So, I searched and fortunately could find a tool named Pipeviewer (PV) which allows a user to see the progress of data through a pipeline, by giving information such as time elapsed, percentage completed (with progress bar), current throughput rate, total data transferred, and ETA .

Installation :

On Centos and RHEL :

[root@vm1 vagrant]# yum install pv

[root@vm1 …

What you may not know about random number generation in sysbench

Sysbench is a well known and largely used tool to perform benchmarking. Originally written by Peter Zaitsev in early 2000, it has become a de facto standard when performing testing and benchmarking. Nowadays it is maintained by Alexey Kopytov and can be found in Github at https://github.com/akopytov/sysbench.

What I have noticed though, is that while widely-used, some aspects of sysbench are not really familiar to many. For instance, the easy way to expand/modify the MySQL tests is using the lua extension, or the embedded way it handles the random number generation.

Why this article? 

I wrote this article with the intent to show how easy it can be to customize sysbench to make it what you need. There are many different ways to extend sysbench use, and one of these is through …

We know well the MySQL Group Replication cluster is functionally working based on the GTID . GTID is mandatory for group replication . Usually, GTID is the combination of source_id ( or server_uuid ) and transaction_id . Do you think the same approach is following in the MySQL Group Replication as well ? Well, this blog mainly going to focus on the below three topics .

• How the binary log GTID events are being generated in the normal MySQL instance ?
• How the binary log GTID events are being generated in the MySQL Group Replication cluster ?
• How to configure the asynchronous replication from Group replication cluster without single point of failure ?

How the binary log GTID events are being generated in normal MySQL instance ?

As I told, the Global Transaction Identifier ( GTID ) will be the combination of server_uuid and transaction_id . …

MySQL is simpler than the Oracle example  because MySQL only has Nested Loops and doesn’t have Hash Join.

Here is the query, like on the Oracle example from the last blog post

select max(t1.data) 
from  t1, t2  
where t1.id = t2.id 
and t1.clus  = 1
;

So there are only 4 examples below which all do NL joins

1. full table scan on T1 and T2
   1. 7.83 secs
2. index on T1 predicate filter column
   1. 7.39 secs
3. index on T2 join column
   1. 0.49 secs
4. index on both T2 join column and T1 predicate filter column
   1. 0.06 secs

There isn’t an idea of “explain analyze” on MySQL until MySQL 8.0.18 and I did my testing on …

A few days ago one of our intern @mydbops reached me with a SQL query. The query scans only a row according to the execution plan. But query does not seems optimally performing.

Below is the SQL query and its explain plan. ( MySQL 5.7 )

select username, role from user_roles where username= '9977223389' ORDER BY role_id DESC LIMIT 1;

Execution plan and table structure

*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: user_roles
   partitions: NULL
         type: index
possible_keys: NULL
          key: PRIMARY
      key_len: 4
          ref: NULL
         rows: 1
     filtered: 10.00
        Extra: Using where
1 row in set, 1 warning (0.00 sec)

show create table user_roles\G
*************************** 1. row ***************************
       Table: …