How to Maintain Database with MySQL optimization experts?

Like all relational databases, MySQL optimization consultation can prove to be a godsend while dealing with a complicated beast such as MySQL that can halt at a time, leaving your applications in the lurch and your business on the line. The truth is, most MySQL performance issues are underlying common mistakes. It is important to eliminate these errors, which are often obscured by some subtlety in your workload or configuration trap, in order to ensure that your MySQL server hums along at top speed, providing stable and consistent performance.

Fortunately, many MySQL performance issues turn out to have similar solutions, making it a manageable task to troubleshoot and tune MySQL consulting services. Here are 10 tips to get great MySQL performance:

Profiling the workload

Profiling the workload of the server is the best way to understand how your server spends its time. You can expose the most costly queries for further tuning by profiling your workload. Time is the most important metric here because you care very little about anything except how quickly it completes when you issue a query against the server.The best way to profile your workload is by using a tool like the query analyzer for MySQL Enterprise Monitor or the Percona Toolkit pt-query-digest. These tools capture server queries and return a task table sorted by decreasing response time order, instantly bubbling up to the top of the most expensive and time-consuming tasks so you can see where to focus your efforts.

Understanding the fundamental resources

Four basic resources are needed for a database server to work: CPU, memory, disk, and network. If any of these are weak, erratic, or overloaded, it is highly likely that the database server will perform poorly. Understanding the basic resources is important in two specific areas: hardware selection and troubleshooting.Ensure good-performing components all around when selecting MySQL hardware. Just as important, they are fairly well balanced against each other. Organizations often choose servers that have fast CPUs and disks but are hungry for memory. In some cases, adding memory is a cheap way to increase performance by magnitude orders, particularly on disk-bound workloads. This may seem counterintuitive, but disks are overused in many cases because there is not enough memory to hold the working data set of the server.

Do not employ MySQL as a queue

Queues and access patterns like queues can sneak into your application without your knowledge. For example, if you set an item’s status so that it can be claimed by a particular worker process before acting on it, then you create a queue unwittingly. It is a common example to mark emails as unsent, send them, and then mark them as sent.Queues cause problems for two main reasons: they serialize your workload, preventing parallel tasks, and often result in a table that includes processing work as well as historical data from long processed jobs. Both add application latency and load MySQL.

Filter results by the cheapest first

A great way to optimize MySQL is first to do cheap, imprecise work, then hard, accurate work on the smaller, resulting data set. Suppose you’re looking for something within a given geographic point radius, for example. The first tool in the toolbox of many programmers is the “Haversine” formula for computing distance along a sphere’s surface. The problem with this technique is that the formula requires a lot of very CPU-intensive trigonometric operations. Great-circle calculations tend to run slowly and skyrocket the machine’s use of the CPU.

Understand the scalability death traps

Scalability isn’t as vague as you might think. There are, in fact, precise mathematical scalability definitions expressed as equations. These equations highlight why systems don’t scale as well as they should. Take the Universal Scalability Law, a definition useful to express and quantify the scalability characteristics of a system. It explains problems of scaling in terms of two basic costs: serialization and crosstalk.

Do not concentrate too much on configuration

DBAs tend to tweak configurations a lot of time. Usually, the result is not a major improvement and can even be very damaging at times. MySQL optimization expert have seen a lot of “optimized” servers crashing all the time, running out of memory, and performing poorly when the workload got a bit more intense.

Look out for pagination queries

Applications that paginate tend to knee the server. These applications typically group and sort in ways that cannot use indexes by showing you a page of results, with a link to go to the next page, and they use a LIMIT and offset that causes the server to do a lot of work generating, then discard rows. The user interface itself can often find optimizations. You can simply display a link to the next page instead of showing the exact number of pages in the results and links to each page individually. You can also avoid people going too far from the first page to go to pages.