Monitoring MySQL and HeatWave

In this episode, Lois Houston and Nikita Abraham chat with MySQL expert Perside Foster on the importance of keeping MySQL performing at its best. They discuss the essential tools for monitoring MySQL, tackling slow queries, and boosting overall performance.

 

They also explore HeatWave, the powerful real-time analytics engine that brings machine learning and cross-cloud flexibility into MySQL.

 

MySQL 8.4 Essentials: https://mylearn.oracle.com/ou/course/mysql-84-essentials/141332/226362

Oracle University Learning Community: https://education.oracle.com/ou-community

LinkedIn: https://www.linkedin.com/showcase/oracle-university/

X: https://x.com/Oracle_Edu

 

Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.

 

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Episode Transcript:

 

00:00

Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started!

00:25

Lois: Welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me today is Nikita Abraham, Team Lead: Editorial Services.

Nikita: Hey everyone! In our last two episodes, we spoke about MySQL backups, exploring their critical role in data recovery, error correction, data migration, and more.

Lois: Today, we’re switching gears to talk about monitoring MySQL instances. We’ll also explore the features and benefits of HeatWave with Perside Foster, a MySQL Principal Solution Engineer at Oracle.

01:02

Nikita: Hi, Perside! We’re thrilled to have you here for one last time this season. So, let’s start by discussing the importance of monitoring systems in general, especially when it comes to MySQL.

Perside: Database administrators face a lot of challenges, and these sometimes appear in the form of questions that a DBA must answer. One of the most basic question is, why is the database slow? To address this, the next step is to determine which queries are taking the longest. Queries that take a long time might be because they are not correctly indexed. Then we get to some environmental queries or questions. How can we find out if our replicas are out of date? If lag is too much of a problem? Can I restore my last backup? Is the database storage likely to fill up any time soon? Can and should we consider adding more servers and scaling out the system?

And when it comes to users and making sure they're behaving correctly, has the database structure changed? And if so, who did it and what did they do? And more generally, what security issues have arisen? How can I see what has happened and how can I fix it? Performance is always at the top of the list of things a DBA worries about. The underlying hardware will always be a factor but is one of the things a DBA has the least flexibility with changing over the short time. The database structure, choice of data types and the overall size of retained data in the active data set can be a problem.

03:01

Nikita: What are some common performance issues that database administrators encounter?

Perside: The sort of SQL queries that the application runs can be an issue. 90% of performance problems come from the SQL index and schema group. 

03:18

Lois: Perside, can you give us a checklist of the things we should monitor?

Perside: Make sure your system is working. Monitor performance continually. Make sure replication is working. Check your backup. Keep an eye on disk space and how it grows over time. Check when long running queries block your application and identify those queries. Protect your database structure from unauthorized changes. Make sure the operating system itself is working fine and check that nothing unusual happened at that level. Keep aware of security vulnerabilities in your software and operating system and ensure that they are kept updated. Verify that your database memory usage is under control.

04:14

Lois: That’s a great list, Perside. Thanks for that. Now, what tools can we use to effectively monitor MySQL?    

Perside: The slow query log is a simple way to monitor long running queries. Two variables control the log queries. Long_query_time. If a query takes longer than this many seconds, it gets logged. And then there's min_exam_row_limit. If a query looks at more than this many rows, it gets logged. The slow query log doesn't ordinarily record administrative statements or queries that don't use indexes. Two variables control this, log_slow_admin_statements and log_queries_not_using_indexes. Once you have found a query that takes a long time to run, you can focus on optimizing the application, either by limiting this type of query or by optimizing it in some way.

05:23

Nikita: Perside, what tools can help us optimize slow queries and manage data more efficiently?

Perside: To help you with processing the slow query log file, you can use the MySQL dump slow command to summarize slow queries. Another important monitoring feature of MySQL is the performance schema. It's a system database that provides statistics of how MySQL executes at a low level.

Unlike user databases, performance schema does not persist data to disk. It uses its own storage engine that is flushed every time we start MySQL. And it has almost no interaction with the storage media, making it very fast.

This performance information belongs only to the specific instance, so it's not replicated to other systems. Also, performance schema does not grow infinitely large. Instead, each row is recorded in a fixed size ring buffer. This means that when it's full, it starts again at the beginning. The SYS schema is another system database that's strongly related to performance schema.

06:49

Nikita: And how can the SYS schema enhance our monitoring efforts in MySQL?

Perside: It contains helper objects like views and stored procedures. They help simplify common monitoring tasks and can help monitor server health and diagnose performance issues. Some of the views provide insights into I/O hotspots, blocking and locking issues, statements that use a lot of resources in various statistics on your busiest tables and indexes.

07:26

Lois: Ok… can you tell us about some of the features within the broader Oracle ecosystem that enhance our ability to monitor MySQL?

Perside: As an Oracle customer, you also have access to Oracle Enterprise Manager. This tool supports a huge range of Oracle products. And for MySQL, it's used to monitor performance, system availability, your replication topology, InnoDB performance characteristics and locking, bad queries caught by the MySQL Enterprise firewall, and events that are raised by the MySQL Enterprise audit.

08:08

Nikita: What would you say are some of the standout features of Oracle Enterprise Manager?

Perside: When you use MySQL in OCI, you have access to some really powerful features. HeatWave MySQL enables continuous monitoring of query statistics and performance. The health monitor is part of the MySQL server and gathers raw data about the performance of queries. You can see summaries of this information in the Performance Hub in the OCI Console. For example, you can see average statement latency or top 100 statements executed.

MySQL metrics lets you drill in with your own custom monitoring queries. This works well with existing OCI features that you might already know. The observability and management framework lets you filter by resource type and across several dimensions. And you can configure OCI alarms to be notified when some condition is reached.

09:20

Lois: Perside, could you tell us more about MySQL metrics?

Perside: MySQL metrics uses the raw performance data gathered by the health monitor to measure the important characteristic of your servers. This includes CPU and storage usage and information relevant to your database connection and queries executed. With MySQL metrics, you can create your own custom monitoring queries that you can use to feed graphics. This gives you an up to the minute representation of all the performance characteristics that you're interested in.

You can also create alarms that trigger on some performance condition. And you can be notified through the OCI alarms framework so that you can be aware instantly when you need to deal with some issue. 

10:22

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10:47

Nikita: Welcome back! Now, let’s dive into the key features of HeatWave, the cloud service that integrates with MySQL. Can you tell us what HeatWave is all about?

Perside: HeatWave is the cloud service for MySQL. MySQL is the world's leading database for web applications. And with HeatWave, you can run your online transaction processing or OLTP apps in the cloud. This gives you all the benefits of cloud deployments while keeping your MySQL-based web application running just like they would on your own premises.

As well as OLTP applications, you need to run reports with Business Intelligence and Analytics Dashboards or Online Analytical Processing, or OLAP reports. The HeatWave cluster provides accelerated analytics queries without requiring extraction or transformation to a separate reporting system. This is achieved with an in-memory analytics accelerator, which is part of the HeatWave service.

In addition, HeatWave enables you to create Machine Learning models to embed artificial intelligence right there in the database. The ML accelerator performs classification, regression, time-series forecasting, anomaly detection, and other functions provided by the various models that you can embed in your architecture.

HeatWave can also work directly with storage outside the database. With HeatWave Lakehouse, you can run queries directly on data stored in object storage in a variety of formats without needing to import that data into your MySQL database.

12:50

Lois: With all of these exciting features in HeatWave, Perside, what core MySQL benefits can users continue to enjoy?

Perside: The reason why you chose MySQL in the first place, it's still a relational database and with full transactional support, low latency, and high throughput for your online transaction processing app. It has encryption, compression, and high availability clustering.

It also has the same large database support with up to 256 terabytes support. It has advanced security features, including authentication, data masking, and database firewall. But because it's part of the cloud service, it comes with automated patching, upgrades, and backup. And it is fully supported by the MySQL team.

13:50

Nikita: Ok… let’s get back to what the HeatWave service entails.

Perside: The HeatWave service is a fully managed MySQL. Through the web-based console, you can deploy your instances and manage backups, enable high availability, resize your instances, create read replicas, and perform many common administration tasks without writing a single line of SQL.

It brings with it the power of OCI and MySQL Enterprise Edition. As a managed service, many routine DBA tests are automated. This includes keeping the instances up to date with the latest version and patches. You can run analytics queries right there in the database without needing to extract and transform your databases, or load them in another dedicated analytics system.

14:52

Nikita: Can you share some common use cases for HeatWave?

Perside: You have your typical OLTP workloads, just like you'd run on prem, but with the benefit of being managed in the cloud. Analytic queries are accelerated by HeatWave. So your reporting applications and dashboards are way faster. You can run both OLTP and analytics workloads from the same database, keeping your reports up to date without needing a separate reporting infrastructure.

15:25

Lois: I’ve heard a lot about HeatWave AutoML. Can you explain what that is?

Perside: HeatWave AutoML enables in-database artificial intelligence and Machine Learning. Externally sourced data stores, such as sensor data exported to CSV, can be read directly from object store. And HeatWave generative AI enables chatbots and LLM content creation.

15:57

Lois: Perside, tell us about some of the key features and benefits of HeatWave.

Perside: Autopilot is a suite of AI-powered tools to improve the performance and applicability of your HeatWave queries. Autopilot includes two features that help cut costs when you provision your service. There's auto provisioning and auto shape prediction. They analyze your existing use case and tell you exactly which shape you must provision for your nodes and how many nodes you need.

Auto parallel loading is used when you import data into HeatWave. It splits the import automatically into an optimum number of parallel streams to speed up your import. And then there's auto data placement. It distributes your data across the HeatWave cluster node to improve your query retrieval performance. Auto encoding chooses the correct data storage type for your string data, cutting down storage and retrieval time.

Auto error recovery automatically recovers a fail node and reloads data if that node becomes unresponsive. Auto scheduling prioritizes incoming queries intelligently. An auto change propagation brings data optimally from your DB system to the acceleration cluster. And then there's auto query time estimation and auto query plan improvement. They learn from your workload. They use those statistics to perform on node adaptive optimization.

This optimization allows each query portion to be executed on every local node based on that node's actual data distribution at runtime. Finally, there's auto thread pooling. It adjusts the enterprise thread pool configuration to maximize concurrent throughput. It is workload-aware, and minimizes resource contention, which can be caused by too many waiting transactions.

18:24

Lois: How does HeatWave simplify analytics within MySQL and with external data sources?

Perside: HeatWave in Oracle Cloud Infrastructure provides all the features you need for analytics, all in one system. Your classic OLTP application run on the MySQL database that you know and love, provision in a DB system. On-line analytical processing is done right there in the database without needing to extract and load it to another analytic system.

With HeatWave Lakehouse, you can even run your analytics queries against external data stores without loading them to your DB system. And you can run your machine learning models and LLMs in the same HeatWave service using HeatWave AutoML and generative AI. HeatWave is not just available in Oracle Cloud Infrastructure. If you're tied to another cloud vendor, such as AWS or Azure, you can use HeatWave from your applications in those cloud too, and at a great price.

19:43

Nikita: That's awesome! Thank you, Perside, for joining us throughout this season on MySQL. These conversations have been so insightful. If you’re interested in learning more about the topics we discussed today, head over to mylearn.oracle.com and search for the MySQL 8.4: Essentials course. 

Lois: This wraps up our season on the essentials of MySQL. But before we go, we just want to remind you to write to us if you have any feedback, questions, or ideas for future episodes. Drop us an email at [email protected]. That’s [email protected].

Nikita: Until next time, this is Nikita Abraham…

Lois: And Lois Houston, signing off!

20:33

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