Announcement: MySQL Performance Monitoring in SPM
May 21, 2014byMICK EMMETTLeave a comment
We live in the “data era”. A database of one kind or another lives at the core of virtually every application on the planet. As such, you better monitor your databaseperformance and availability metricsand you better havealertingandanomaly detectionmechanisms to notify you when things go awry before your users start calling you and the spiky-haired boss storms in.
We’re happy to announceMySQL performance monitoringbeing added to ourSPM Performance Monitoring platform. The addition of MySQL monitoring complementsMemcached performance monitoringwe announced earlier today, HBase monitoring as well as theRedis monitoringwe added earlier this year. We’re also announcing other great new additions to SPM in the coming days. Watch this space for details…
The latest release of SPM coversover 150 different MySQL metricsyou can monitor, such as:
- Availability
- Replication
- Connections
- Slow queries
- Cache
- Data in/out
- …and many more
Here’s a glimpse into what SPM for MySQL provides – click on an image to see the full view or look at the actualSPM live demo:
MySQL Overview
MySQL Runtime
MySQL Queries/Questions Rate
MySQL Cache Usage
MySQL Table Stats
Please tell us what you think –@sematext is always listening! Is there something SPM doesn’t monitor that you would really like to monitor?
Why Have Something to Just Monitor MySQL?
…When you can monitor almost everything with one solution — SPM. Many organizations tackle performance monitoring with a mish-mash of different monitoring and alerting tools cobbled together in an uneasy coexistence that is often far from seamless. Think Ganglia+Nagios. SPM takes all that hassle away and makes it easy and comprehensive in one step.
Try SPM Today for Free for 30 Days
Try SPM Performance Monitoring for Free for 30 daysby registering here. There’s no commitment andno credit card required.
We’re Hiring!
If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, and Storm, then drop us a line. We’rehiring planet-wide! Front end and JavaScript Developers, Developer Evangelists, Full-stack Engineers, Mobile App Developers…get in touch!

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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