MySQL 9.7, a Long-Term Support (LTS) release, incorporates a variety of potential features spanning across multiple technical domains. This article covers some of the primary features introduced and evaluates their practical utility within the MySQL database environment.

Following the End-of-Life (EOL) status of MySQL 8.0, this subsequent LTS release is designed to provide enhanced stability alongside significant architectural innovations.

Let’s discuss each of these features below with some examples and usage.

Flow-control monitoring in Group Replication

Flow control monitoring has been improved and provides more granularity by introducing the additional status variables listed below.

• Gr_flow_control_throttle_count : It denotes the number of transactions that have been throttled.
• Gr_flow_control_throttle_time_sum :It denotes the time in microseconds that transactions have been …

It is time to talk again about Flow control and group replication. This time with a special eye on the use of Group Replication in the Kubernetes context. In this article we will dig a bit on how it works and what are the various side effects. 

The problem

Recently I was refining the calculation I use in the MySQL calculator for Operator given I was constantly encountering a very serious problem with the Percona Server Operator.

The problem is that when the deployment was/is serving a high level of traffic, it will, no matter what, end up in getting OMMKill by the K8 system. 

This because the pod was gradually consuming more and more memory, reaching the memory limit set in the CR specification. 

Now let me clarify a few things, to get straight to the facts.

…

Having a separate DR cluster for production databases is a modern day requirement or necessity for tech and other related businesses that rely heavily on their database systems. Setting up such a [DC -> DR] topology for Percona XtraDB Cluster (PXC), which is a virtually- synchronous cluster, can be a bit challenging in a complex Kubernetes environment.

Here, Percona Operator for MySQL comes in handy, with a minimal number of steps to configure such a topology, which ensures a remote side backup or a disaster recovery solution.

So without taking much time, let’s see how the overall setup and configurations look from a practical standpoint.

PXC Cross-Site/Disaster Recovery

DC Configuration

1) Here we have a three-node PXC cluster running on the DC side.

shell> kubectl get pods -n pxc
NAME                                               READY   STATUS …

“ Of course, in practice, no query optimizer is perfect and there will be edge cases where the way a query is written will impact its performance.”

Q1. What are your current responsibilities as Principal Member of Technical staff?

Kaan Kara : I am contributing as the tech lead for query execution in HeatWave. My main responsibility is implementing new features in HeatWave, maintaining its stability, and supporting our customers with their HeatWave-related use cases.

Q2. Let´s talk about improving database query execution time. The way a query is written has a massive impact on its performance, and developers often face hurdles in structuring them optimally. What is your take on this?

Kaan Kara : SQL is a declarative language. That means, in ideal terms, the database optimizer should produce the best …

There are certain things in life that you can count on …

FOSDEM is back in town, and together with that a new pre-FOSDEM MySQL day, 2 days again this year!

And of course, we definitely have not forgotten … the MySQL Community dinner!

We continue the by now well known tradition of dining together in style with members from all over the community, and invite you to the ICAB venue (the same location as where the pre-FOSDEM MySQL days are being held.

Book your tickets now!!!

The listed ticket price includes a selection of Belgian Speciality …

Sure, wait event times in any database will include some CPU time, though ideally it should be minimal. Waits should be instrumented as close to the off CPU wait event as possible, i.e. if I’m doing an IO, then I want the wait to cover just the read call:

start_wait('my_read_wait');
pread( ... );
end_wait('my_read_wait');

So my function that sets up the read will do some CPU that could get caught under the cover of the wait itself and the call to pread will use some CPU but most of the time should be waiting for the actual I/O if the I/O is coming from storage.

start_wait('my_lock');
semtimedop(...);
end_wait('my_lock');

On MySQL I’ve noticed that average active sessions on CPU are often well below what the host reports as CPU utilization. For example if I have one connection on CPU a 100% of the time on a 2 vCPU host then CPU Utilization should be around 50%.  There might be …

Just  quick post to document a troublesome error when running Jmeter on Mysql

JDBC Request: Cannot load JDBC driver class’com.mysql.jdbc.Driver’ solution

Should be pretty simple, it’s just a question of putting the mysql-connector-java jar file, available at https://dev.mysql.com/downloads/connector/j/, into the classpath for Jmeter. The easiest way for me is to put this into the jmx file:

      <stringProp name=“TestPlan.user_define_classpath”> /Users/kyle.hailey/jars/mysql-connector-java-8.0.29.jar,/home/ec2-user/jars/mysql-connector-java-8.0.29.jar</stringProp>

Notice there is a space ” ” before the first jar file.  Apparently the space  was enough to cause the error. After removing the space , jmeter connected successfully to …

Anyone familiar with Oracle performance tuning knows about ASH , aka active session history. ASH saves a history of every session that is active every collection, which by default is once per second. Once per second is fast enough to give a clear view of database load.

The ASH data comes from v$session which is a structure that contains information on every connection and shows which connections are active, what SQL they are running (SQL_ID) and if they are runnable on CPU or waiting on a wait_event for some resource like an I/O to complete or a lock or latch. It’s a pretty simple select query on v$session to select who is active,  their wait_event and SQL_ID.

On Oracle that gives us a query like:

select sid||':'||serial# session_id,
       username,
       s.sql_id||':'||sql_child_number sqlid,
       decode(state, 'WAITING', wait_class||':'||event, 'CPU') event
from v$session s
where   (( s.wait_time != 0  /* on CPU  */ …

How does one use  NESTING_EVENT_ID?

Below I’ve selected from  events_waits_history_long for a single thread, but none of the  NESTING_EVENT_ID values show up in EVENT_ID or END_EVENT_ID.

To simplify things , I’m just showing the data for one THREAD_ID listed in order of TIMER_START.

mysql>  select 
            THREAD_ID,
            EVENT_ID,
            END_EVENT_ID,
            NESTING_EVENT_ID,
            NESTING_EVENT_TYPE,
            EVENT_NAME,
            SOURCE,
            TIMER_WAIT,
            SPINS,
            OBJECT_SCHEMA,
            OBJECT_NAME,
            INDEX_NAME,
            OBJECT_TYPE,
            OBJECT_TYPE,
            OBJECT_INSTANCE_BEGIN,
            OPERATION,
            NUMBER_OF_BYTES,
            FLAGS 
 from 
           performance_schema.events_waits_history_long 
 where 
            THREAD_ID in ( select max(thread_id) from performance_schema.events_waits_history_long where …

Question: how do I know that one user is waiting for a lock and another  user is burning CPU on MySQL?

i.e. how can I create active session history on MySQL like on Oracle?

Two simple cases I’m looking at

1. session waiting on lock
   1. The wait event is ” wait/io/table/sql/handler” which happens for a number of potential reasons
   2. -> I can join to information_schema views INNODB_LOCK_WAITS & INNODB_TRX but this is heavy, and I’d rather only access those after I know there is a lock waiter.
2. session burning CPU
   1. How do I know from performance schema views that the connection is active and burning CPU?
   2. It has a wait event that shows up wait/synch/mutex/sql/THD::LOCK_thd_data
   3. on Oracle to determine CPU, we just …