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Displaying posts with tag: monitoring (reset)
MySQL Monitoring and Reporting Using the MySQL Shell

MySQL Shell is the advanced MySQL client, which has many excellent features. In this blog, I am going to explain the MySQL shell commands “\show” and “\watch”. Both commands are very useful to monitor the MySQL process. It provides more insights into the foreground and background threads as well. 


“\show” and “\watch” are the MySQL shell commands, which can be executed using the Javascript (JS), Python (Py), and SQL interfaces. Both commands are providing the same information, but the difference is you can refresh the results when using the command “\watch”. The refresh interval is two seconds. 

  • \show: Run the specified report using the provided options and arguments.
  • \watch: Run the specified report using the provided options and arguments, and refresh the results at regular intervals.

Below are the available options you can use with the “\show” …

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Point-In-Time Recovery in Kubernetes Operator for Percona XtraDB Cluster – Architecture Decisions

Point-In-Time Recovery (PITR) for MySQL databases is an important feature that is essential and covers common use cases, like a recovery to the latest possible transaction or roll-back the database to a specific date before some bad query was executed. Percona Kubernetes Operator for Percona XtraDB Cluster (PXC) added support for PITR in version 1.7, and in this blog post we are going to look into the technical details and decisions we made to implement this feature.

Architecture Decisions Store Binary Logs on Object Storage

MySQL uses …

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Q&A on Webinar “Using PMM to Identify and Troubleshoot Problematic MySQL Queries”

Hi and thanks to all who attended my webinar on Tuesday, January 26th titled Using PMM to Identify & Troubleshoot Problematic MySQL Queries!

Like we do after all our webinars, we compile the list of questions that were answered verbally and also those that were posed yet remained unanswered since we ran out of time during the broadcast.  Before we get to the questions, I wanted to make sure to include a link to the RED Method for MySQL Queries by Peter Zaitsev, Percona’s CEO:

Hi Michael, you suggested that table create and update times should be ignored. Surely these values come from information_schema.tables? Does that not reflect what I would see …

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Webinar January 26: Using Percona Monitoring and Management to Identify and Troubleshoot Problematic MySQL Queries

Join us as Michael Coburn, Percona Product Manager, discusses two methods to identify and troubleshoot problematic MySQL queries using the RED Method and Percona Monitoring and Management (PMM) Query Analytics. He will also highlight specific Dashboards in PMM that visualize the rate, errors, and duration of MySQL events that may be impacting the stability and performance of your database instance.

Please join Michael Coburn, Product Manager, Percona, on Tuesday, January 26th, 2021 at 2:30 pm for his webinar “Using Percona Monitoring and Management to Identify and Troubleshoot Problematic MySQL Queries”.

Watch Recorded Webinar

If you can’t attend, …

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On the Observability of Outliers

At work, I am in an ongoing discussion with a number of people on the Observability of Outliers. It started with the age-old question “How do I find slow queries in my application?” aka “What would I want from tooling to get that data and where should that tooling sit?”

As a developer, I just want to automatically identify and isolate slow queries!

Where I work, we do have SolarWinds Database Performance Monitor aka Vividcortex to find slow queries, so that helps. But that collects data at the database, which means you get to see slow queries, but maybe not application context.

There is also work done by a few developers which instead collects query strings, query execution times and query counts at the application. This has access to the call stack, so it can tell you which code generated the query that was slow.

It …

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Adjusting MySQL 8.0 Memory Parameters

So you’ve just added some more memory to your MySQL server; now what? If you’ve been around the MySQL block for a while, you know that nothing is automatically changed to take advantage of this new system RAM. Let’s have a look at a few parameters you would want to adjust.

InnoDB Parameters innodb_buffer_pool_size

The InnoDB buffer pool is “…the memory area that holds cached InnoDB data for both tables and indexes.” This parameter is probably the #1 tuning parameter in MySQL. If your buffer pool is too small, then InnoDB must spend extra CPU/Disk time, loading, and unloading pages in/out of memory. This is time better spent executing your queries.

The default size of this cache is 128MB; woefully small for any serious database. Increasing the size of this cache allows more frequently accessed pages to remain in memory for the fastest access. Obviously, you do not need a buffer pool which is larger than your …

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Understanding MySQL Memory Usage with Performance Schema

Understanding how MySQL uses memory is key to tuning it for optimal performance as well as troubleshooting cases of unexpected memory usage, i.e. when you have MySQL Server using a lot more than you would expect based on your configuration settings.

Early in MySQL history, understanding memory usage details was hard and included a lot of guesswork.  Is it possible that some queries running require a large temporary table or allocated a lot of memory for stored user variables?  Are any stored procedures taking an unexpectedly high amount of memory? All could be reasons for excessive MySQL memory usage, but you would not easily see if that is just the case.

All that changed with MySQL 5.7, which added memory instrumentation in Performance Schema, and with MySQL 8.0, this instrumentation is enabled by default, so you can get this data from pretty much any running instance.

If you’re looking for current memory …

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How to Find Query Slowdowns Using Percona Monitoring and Management

Visibility is a blessing, and with databases, visibility is a must. That’s true not only for metrics but for the queries themselves. Having info on all the stats around query execution is priceless, and Percona Monitoring and Management (PMM) offers that in the form of the Query Analytics dashboard (QAN).

But where to start? QAN helps you with that by calculating the query profile. What is the profile? It’s a rank of queries, ordered by Load, so it is easy to spot the heaviest queries hitting your database. The Load is defined as the “Average Active Queries” but can also be defined as a mix of Query Execution Time Plus Query count. In other words, all the time the query was alive and kicking.

The Profile in PMM 2.10.0 looks like this:

The purpose of this profile is to facilitate the task of finding the …

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MySQL Query Performance Troubleshooting: Resource-Based Approach

When I speak about MySQL performance troubleshooting (or frankly any other database), I tend to speak about four primary resources which typically end up being a bottleneck and limiting system performance: CPU, Memory, Disk, and Network.

It would be great if when seeing what resource is a bottleneck, we could also easily see what queries contribute the most to its usage and optimize or eliminate them. Unfortunately, it is not as easy as it may seem.

First, MySQL does not really provide very good instrumentation in those terms, and it is not easy to get information on how much CPU usage, Disk IO, or Memory a given query caused.  Second, direct attribution is not even possible in a lot of cases. For example, disk writes from flushing data from the InnoDB buffer pool in the …

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A Simple MySQL Plugin to Retrieve System Metrics

Ever wanted to extend MySQL and add some feature you think it is missing?  With MySQL plugins, you can do exactly that.  One thing that has bothered me for several years is that you cannot easily retrieve system metrics from within MySQL.  Whether I am connecting via a remote connection or looking to add features to monitoring without the need for another interface with the server, I have wanted to retrieve system metrics without leaving the MySQL interface.

So, I started a Proof of Concept for this.  My goal was to get metrics such as RAM (total, used, free), system load, CPU utilization, disk utilization for the file system containing the datadir, and more.  My objective was to do this as efficiently within MySQL as possible.  For this, I chose to utilize standard C libraries in as few lines of code as possible without having to scrape system files or run commands to get the data.  The …

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