Why is MySQL could be slow with large tables?

Why is MySQL could be slow with large tables?

Data retrieval, search, DSS, business intelligence applications which need to analyze a lot of rows run aggregates, etc., is when this problem is the most dramatic. Some joins are also better than others. For example, if you have a star join with dimension tables being small, it would not slow things down too much.

Why is my Excel spreadsheet so slow when I have less data?

While the impact on the performance may be negligible when there is less data, it becomes more profound as you add more and more data/calculations to the workbook. 9 out of 10 times, an Excel user would complain about the slow Excel spreadsheets.

How to improve the performance of SQL query?

To improve performance you either need to reduce the result set or perform a nasty trick (eg make a denormalized copy of the data). From your query plan I can conclude that the tables referred to as s, n and q do not have an index on the field they are being joined on.

Which is worse correlated subqueries or joins in SQL?

I am a little suprised as I thought correlated subqueries perform worse than joins. Depending on how much data is in the tables, you may need to place indexes on the columns that are being joined against. Often slow querying speed comes down to lack of an index in the right place.

How to increase the speed of MySQL join?

Also trying using STRAIGHT_JOIN and mention the table that is slower in size in the left, and the bigger one on the right to hint MySQL to choose the first table. Make sure the fields you are matching on are indexed. Matching numeric values is also a quicker than strings.

How to optimize very slow select with left joins over Big?

InnoDb supports fulltext indexes from MySQL 5.7 so if you use 5.5 or 5.6, you should use MyISAM. It’s sometimes even faster for FT searching than InnoDb. Step 2. Insert data from EAV (entity-attribute-value) table. For example stated in question it can be done with 1 simple SQL: Step 3. Select from table with query like this:

How many tables can I join in SQL?

To monitor the effect of the joins on query time execution, I ran my query several times (limiting to first 100 rows), adding a Join to an additional table each time. After joining 12 tables, there was no significant change in query execution time.

How to optimize queries for 25 + million rows?

I am only interested in 4 columns for my criteria and the result should output the count only, for all queries. columns needed: TABLE, FIELD, AFTER, DATE, and there is an index on each of DATE and TABLE. After creating a temp table with only the fields I need, it went down to a 1:40 minutes, which is still very bad.

Which is the fastest way to do a query in MySQL?

This is by far the fastest way. We use this way now since 1998 and had never any wrong number of rows, in all our multi million record tables. You should perform a query for each type, but perhaps that’s faster than the other way. Give it a try.

What causes an app to be slow when loading?

Regardless of data sources you pick, there are common issues making your apps slow in the playing of your app. In this section, let us walk through what they might be. The OnStart event runs when the application is loading and having lots of data called in the OnStart command will slow down the load of the app.

Why does MySQL take a lot of memory?

If you are using MEMORY tables and variable max_heap_table_size is set very high, this can also take a large memory since max_heap_table_size system variable determines how large a table can grow, and there is no conversion to on-disk format. MySQL also has a Performance Schema which is a feature for monitoring MySQL activities at a low level.

How much CPU does MySQL use per minute?

Closed 9 years ago. Recently my server CPU has been going very high. CPU load averages 13.91 (1 min) 11.72 (5 mins) 8.01 (15 mins) and my site has only had a slight increase in traffic. After running a top command, I saw MySQL was using 160% CPU!

Why does MySQL have a high CPU load?

When running ntp (or ntpd) this second was added to your computer’s/server’s clock. MySQLd does not seem to like this extra second on some OS’es, and yields a high CPU load. The quick fix is (as root):

Which is the best way to improve MySQL performance?

This will save space in other indexes that reference the row, and smaller indexes can be accessed more quickly. Primary keys should consist of a value that’s filtered frequently. Using something frequently queried on, like a username, will give you optimal performance.

Is it possible to query two large tables?

But if we do this for two very large tables (50m and 150m rows), it would mean a lot of memory being used up for the intermediate hash, as well as a lot of rows from the other candidate being looked up against this hash table. Appropriate indices weren’t being used in the prepared queries.

Which is better for MySQL performance InnoDB or MyISAM?

It’s worth mentioning that InnoDB boasts several performance improvements over its predecessor, MyISAM. If you’re able to switch from MyISAM to InnoDB, especially for large wide tables, you should notice a performance improvement! InnoDB stores data in a clustered index.

Are there any performance issues with MySQL database?

Performance issues are common problems when administering MySQL databases. Sometimes these problems are, in fact, due to slow queries. In this blog, we’ll deal with slow queries and how to identify these. MySQL has the capability to filter and log slow queries.

Where to put slow query logs in MySQL?

You must ensure that the variable slow_query_log is set to ON, while the slow_query_log_file determines the path where you need to place your slow query logs. If this variable is not set, it will use the DATA_DIR of your MySQL data directory.

Is it better to do a full table scan in MySQL?

In fact, even MySQL optimizer currently does not take it into account. For in-memory workload indexes, access might be faster even if 50% of rows are accessed, while for disk IO bound access we might be better off doing a full table scan even if only a few percent or rows are accessed. Let’s do some computations again.

Why does MySQL higher limit offset slow the query?

The higher LIMIT offset with SELECT, the slower the query becomes, when using ORDER BY *primary_key* That only orders 30 records and same eitherway. So it’s not the overhead from ORDER BY. Now when fetching the latest 30 rows it takes around 180 seconds. How can I optimize that simple query?

When to use limit 0, 30 in MySQL?

Logically speaking, in the LIMIT 0, 30 version, only 30 rows need to be retrieved. In the LIMIT 10000, 30 version, 10000 rows are evaluated and 30 rows are returned. There can be some optimization can be done my the data-reading process, but consider the following:

How many rows does MySQL have to fetch to return 30?

Although it might be that way in actuality, MySQL cannot assume that there are no holes/gaps/deleted ids. So, as bobs noted, MySQL will have to fetch 10000 rows (or traverse through 10000th entries of the index on id) before finding the 30 to return.

How many rows can a MySQL database handle?

If you’ve been reading enough database-related forums, mailing lists, or blogs you have probably heard complains about MySQL being unable to handle more than 1,000,000 (or select any other number) rows by some of the users.

How long does it take for SQL database to failover?

It takes another 1-2 minutes to release the memory back to the OS before the failover occurs and the resource comes up on the other node. If the SQL instance has only limited data in memory the failover happens much more quickly. We looked at I/O and CPU metrics and don’t see any significant issues.