How To Check Query Execution Time In Php

We were unsure of wither it was the internet connection, browsers having a hard time rendering nested tables, or mysql queries taking too long to execute. We've all come across the dreaded fatal error of max execution time once or twice, it can be a pain. PHP's maximum execution time is set at 30 seconds as a bare default, but in some cases, it needs to be higher. PHP has your back though, you can change the default settings by using one function; ini_set(). The first is the exact setting you want to change, and the second is the number of seconds you want to set that setting at. MySQL can use this technique on complex WHERE clauses, so you may see nested operations in the Extra column for some queries.

This often works very well, but sometimes the algorithm's buffering, sorting, and merging operations use lots of CPU and memory resources. This is especially true if not all of the indexes are very selective, so the parallel scans return lots of rows to the merge operation. Recall that the optimizer doesn't account for this cost—it optimizes just the number of random page reads. This can make it "underprice" the query, which might in fact run more slowly than a plain table scan. The intensive memory and CPU usage also tends to impact concurrent queries, but you won't see this effect when you run the query in isolation.

So this change is not possible unless you own the server and you are the only user. In a shared hosting our host may not like to change any settings of php.ini for our requirement. So there is a option to set the file execution time for the particular file at the individual file end.

This adjustment of time limit has no effect if php is running in safe mode. Let us try to learn how this works.To know the php.ini setting for Maximum execution time, run this simple code. The MySQL slow query log is a log that MySQL sends slow, potentially problematic queries to.

This logging functionality comes with MySQL but is turned off by default. What queries are logged is determined by customizable server variables that allow for query profiling based on an application's performance requirements. Generally the queries that are logged are queries that take longer than a specified amount of time to execute or queries that do not properly hit indexes. Powerful and reliable, DPM simplifies database performance monitoring and MS SQL database query optimization.

Monitoring SQL database performance with DPM can be more efficient than using a slow query log, but it's also more thorough. For example, slow query logs don't track CPU usage and can only run for short periods, as they require an immense amount of storage. By contrast, DPM is built to offer 24/7 database performance monitoring, capture valuable information, and supply comprehensive database performance analytics. You can access query samples and explain plans or correlate query behavior with system metrics to troubleshoot performance issues and optimize SQL queries more efficiently.

Sometimes, when a query joins tables, it drastically increases the result set's row count, which can lead to a slow execution time. Before joining tables, try to reduce their size, as explained above. Most such queries we see are accidents (because the server doesn't complain), or are the result of laziness rather than being designed that way for optimization purposes.

In fact, we suggest that you set the server's SQL_MODE configuration variable to include ONLY_FULL_GROUP_BY so it produces an error instead of letting you write a bad query. MySQL executes this query in two steps, which correspond to the two rows in the output. The first step is to find the desired row in the film table. Because the query optimizer has a known quantity to use in the lookup, this table's ref type is const. For example, if you need to retrieve specific information from a database, you can perform a SQL query.

However, databases are limited by their hardware's processing capabilities, which can result in slow queries. By engaging in SQL table optimization and reducing the number of calculations your software and hardware must perform, you can optimize SQL query performance and reduce their execution time. The number of threads created on a single node for query execution is configured per cache and by default equals 1. You can change the value by setting the CacheConfiguration.queryParallelism parameter. If you create SQL tables using the CREATE TABLE command, you can use a cache template to set this parameter.

The parsing and optimizing stage outputs a query execution plan, which MySQL's query execution engine uses to process the query. The plan is a data structure; it is not executable byte-code, which is how many other databases execute queries. Because the server doesn't store statistics, the MySQL query optimizer has to ask the engines for statistics on the tables in a query. The optimizer can use this information to help it decide on the best execution plan. We see how these statistics influence the optimizer's choices in later sections.

Indexes and column nullability can often help MySQL optimize away these expressions. For example, to find the minimum value of a column that's leftmost in a B-Tree index, MySQL can just request the first row in the index. It can even do this in the query optimization stage, and treat the value as a constant for the rest of the query. Similarly, to find the maximum value in a B-Tree index, the server reads the last row. If the server uses this optimization, you'll see "Select tables optimized away" in the EXPLAIN plan. This literally means the optimizer has removed the table from the query plan and replaced it with a constant.

This chapter begins with general query design considerations—the things you should consider first when a query isn't performing well. We then dig much deeper into query optimization and server internals. We show you how to find out how MySQL executes a particular query, and you'll learn how to change the query execution plan. Finally, we look at some places MySQL doesn't optimize queries well and explore query optimization patterns that help MySQL execute queries more efficiently. Instead, use DPM to gain better visibility into your databases and their performance. Once you've identified which queries need improvement, it's time to optimize them.

As previously mentioned, reducing the number of calculations your software and hardware perform during a query can lead to optimal SQL query performance and a reduced execution time. Here are some tips and best practices for MS SQL database query optimization. The setting "Maximum time limit" lets you restrict the maximum PHP execution time that Moodle will allow without any output being displayed. If you have a front-end server with its own time limit, set this value lower to receive PHP errors in logs. An index, as you would expect, is a data structure that the database uses to find records within a table more quickly. Indexes are built on one or more columns of a table; each index maintains a list of values within that field that are sorted in ascending or descending order.

Rather than sorting records on the field or fields during query execution, the system can simply access the rows in order of the index. Stored programs can generally contain any number of DML or DDL statements in them. To avoid the situations mentioned above, support for setting max execution time for stored programs themselves, as well as SELECT statements within them, was removed. Support for setting max execution time limits was also removed in relation to stored programs. It is a PHP built-in function specifically to set the maximum execution time limit of your PHP scripts. It's to be called from your PHP script as in the previous method, and the following example is to also set the limit to 300 seconds .

This is probably the simplest way to check a query execution time, without having to install anything else. Just fire up the command line , run MYSQL, and execute the SQL query. By default, the maximum execution time for PHP scripts is set to 30 seconds.

If a script runs for longer than 30 seconds, PHP stops the script and reports an error. You can control the amount of time PHP allows scripts to run by changing the max_execution_time directive in your php.ini file. MySQL doesn't generate byte-code to execute a query, as many other database products do.

Instead, the query execution plan is actually a tree of instructions that the query execution engine follows to produce the query results. The final plan contains enough information to reconstruct the original query. If you execute EXPLAIN EXTENDED on a query, followed by SHOW WARNINGS, you'll see the reconstructed query. You may also need to look at Apache's timeout setting , I changed max execution time value in php.ini, and still got stopped by Apache's timeout value in the httpd.conf file. The slow query log is extremely helpful in singling out problematic queries and profiling overall query performance.

When query profiling with the slow query log, a developer can get an in-depth understanding of how an application's MySQL queries are performing. Using a tool such as mysqldumpslow, monitoring and evaluating the slow query log becomes manageable and can easily be incorporated into the development process. Now that problematic queries have been identified, the next step is to tune the queries for maximum performance. By adding EXPLAIN to the beginning of a query, you can view your query execution plan and get a better idea of how long your runtime will be.

Though it's not always completely accurate, your query execution plan will display both your query's execution order and its cost . To understand the order of execution, start reading your query execution plan from the bottom up. Up until MySQL 5.7 you had no easy way to protect yourself from large amounts of users DDoSing your database with long running queries.

In addition the PHP max_execution_time does not apply to waiting for network calls as shown in this previous blog post on max_execution_time. This means your PHP scripts and MySQL connections can be blocked as long as a query runs, worst case for several minutes or hours. The option is readily available in cPanel's dashboard and can be used to change PHP's maximum execution time limit. Unfortunately, MySQL does not tell you how many of the rows it accessed were used to build the result set; it tells you only the total number of rows it accessed. Many of these rows could be eliminated by a WHERE clause and end up not contributing to the result set.

In the previous example, after removing the index on sakila.film_actor, the query accessed every row in the table and the WHERE clause discarded all but 10 of them. Only the remaining 10 rows were used to build the result set. Understanding how many rows the server accesses and how many it really uses requires reasoning about the query. One common mistake is assuming that MySQL provides results on demand, rather than calculating and returning the full result set. We often see this in applications designed by people familiar with other database systems.

They think MySQL will provide them with these 10 rows and stop executing the query, but what MySQL really does is generate the complete result set. The client library then fetches all the data and discards most of it. The best solution is to add a LIMIT clause to the query. One last question to address is how the slow query log will affect performance.

In general it is safe to run the slow query log in a production environment; neither the CPU nor the I/O load should be a concern ¹ ². However, there should be some strategy for monitoring the log size to ensure the log file size does not get too big for the file system. Also, a good rule of thumb when running the slow query log in a production environment is to leave long_query_time at 1s or higher. When this flag is set, the query optimizer will not reorder tables in joins. In other words, the order in which joins are applied during query execution will be the same as specified in the query.

Without this flag, the query optimizer can reorder joins to improve performance. However, sometimes it might make an incorrect decision. This flag helps to control and explicitly specify the order of joins instead of relying on the optimizer. The query itself may not always be responsible for slow execution times, as other events occurring elsewhere can sometimes result in suboptimal performance.

To enable auto_explain, you must change the auto_explain.log_min_duration parameter to a value other than -1. This value is the minimum statement execution time in milliseconds that, if it's passed and the statement runs, its execution plan is logged. The simplest way is to run the query in the command line, MYSQL is set to show the query execution time by default. This article describes how to change the maximum execution time for PHP scripts by using the max_execution_time directive in a php.ini file. Make sure there are indexes on the columns in the ON or USING clauses.

See "Indexing Basics" on Indexing Basics for more about indexing. If you're joining tables A and B on column c and the query optimizer decides to join the tables in the order B, A, you don't need to index the column on table B. In general, you need to add indexes only on the second table in the join order, unless they're needed for some other reason.

When sorting a join, MySQL may perform the filesort at two stages during the query execution. If the ORDER BY clause refers only to columns from the first table in the join order, MySQL can filesort this table and then proceed with the join. If this happens, EXPLAIN shows "Using filesort" in the Extra column.

Otherwise, MySQL must store the query's results into a temporary table and then filesort the temporary table after the join finishes. In this case, EXPLAIN shows "Using temporary; Using filesort" in the Extracolumn. If there's a LIMIT, it is applied after the filesort, so the temporary table and the filesort can be very large. Of all possible query plans, and it grows very quickly—a 10-table join can be executed up to 3,628,800 different ways! When the search space grows too large, it can take far too long to optimize the query, so the server stops doing a full analysis.

Instead, it resorts to shortcuts such as "greedy" searches when the number of tables exceeds the optimizer_search_depth limit. Of course, as smart as the optimizer is, there are times when it doesn't give the best result. Sometimes you may know something about the data that the optimizer doesn't, such as a fact that's guaranteed to be true because of application logic. A query can often be executed many different ways and produce the same result. If MySQL does find a match in the query cache, it must check privileges before returning the cached query.

This is possible without parsing the query, because MySQL stores table information with the cached query. If the privileges are OK, MySQL retrieves the stored result from the query cache and sends it to the client, bypassing every other stage in query execution. Many applications cache "objects" that map directly to tables. In this example, if the object with the tag mysql is already cached, the application can skip the first query. If you find posts with an id of 123, 567, or 9098 in the cache, you can remove them from the IN() list. If only one of the tables changes frequently, decomposing a join can reduce the number of cache invalidations.