Being fully ACID compliant has advantages if you solely rely on data integrity and procedures. However, to have this type of security and rollback system comes at the cost of performance. You can usually rollback and any time and recover from any crashes. You can also use a value of 2. This value makes the MySQL server a little less reliable, but it improves performance if you notice that you don't have the best performance for your application. In most cases, this is a safe option.
The final option is 0. Setting a value to 0 improves performance, but you also have the chance to lose some data if you need to rollback transactions. This option is the least recommended, but it can help performance for servers that need extensive performance tuning. This variable is a little more difficult to understand if you're not familiar with RAID disk performance. The default value is fdatasync.
This value is common when you have a battery backup cache component. The setting controls how logs are flushed to disk instead of memory. As the name suggest, this variable controls the buffer size for log files. For regular databases with little traffic, the default value of 1MB is sufficient. However, this value is small when you have several large field data types such as blobs. The buffer fills up quickly, and you no longer have the performance that you need. If you have several write transactions with large data type values, you should increase the value of the variable to help with performance.
This variable is beneficial when you have the same query that's run several times an hour. However, many database administrators suggest that this variable is a known bottleneck and should be changed. Some database administrators suggest that it should be disabled altogether. Current MySQL versions disable this option by default.
This variable option is used when you don't have good indexing and optimized queries and need a way to remedy the situation. This variable is used when you need to do a point in time recovery from your log files.
If you use MySQL as a replication master, then you must enable this variable value. A point in time recovery happens when you lose data or have corrupted data that occurred at a specific time.
When you need to recover from a crash at a specific time, you can use the binary log to recover your data. These files grow to enormous sizes, and the server continues to store new log files with a new numeric extension.
It should be obvious, then, that the log files can eat up disk space. You won't need log files for an extensive amount of time, so you should purge these files when they are no longer needed.
Set this variable value to the number of days you want to keep log files. For instance, keep log files for 30 days if your corporate policy requires log files for 30 days.
This value will purge files every 30 days instead of requiring you to manually purge files each month. We discussed tuning the MySQL engine using configuration options, but you can also speed up the database by tuning queries. Queries that aren't optimized properly can degrade performance especially when there is a high number of records returned. As a database administrator, you can review SQL queries to ensure that they are optimized for performance.
Let's take a look at some optimization methods you can use for queries. Querying on indexes speed up queries tremendously. Take a look at the following query. Instead, you should use queries on indexes. The above query would turn into the following:. Another optimization technique is to set indexes on columns where you join tables. Let's take a look at the following query. Putting aside that the above query would not give accurate results from the join, our goal is to point out the optimization that's needed on this query.
Joining tables on columns that aren't indexed and poorly structured degrades performance on those queries. Instead, the query looks at both the name and address column. Although there are two pairs of customers with the same name, their addresses are different.
The result returns the first distinct name along with the address, making the statement less ambiguous. Try to use an inner join whenever possible. An outer join looks at additional data outside the specified columns. For example, the following two queries output the same result:. While most engines have the same runtime for the two methods, in some database systems one runs faster than the other.
However, they add additional sorting and reading of the database. You can then adjust the phrasing of your query to avoid unintentional table scans or other performance hits. Proceed with caution and make minor changes at a time.
The recommendation is to start with small values around 10MB and then increase to no more than MB. If you have large chunks of data, increase this value. Take note of the RAM required to run other system resources. This is directly related to the type and speed of your storage drive. You can adjust this value to better match your hardware.
Look for bottlenecks hardware and software , queries that are doing more work than needed, and consider using automated tools and the EXPLAIN function to evaluate your database. Optimizing MySQL tables helps reorder information in a dedicated storage server to improve data input and output speeds. Check out our guide on how to optimize MySQL tables. Balance the Four Main Hardware Resources 2.
Optimize Queries 6. Use Indexes Where Appropriate 7. Functions in Predicates 8. Introduction MySQL is a popular open-source database application that stores and structures data in a way that is meaningful and readily accessible.
Was this article helpful? Goran Jevtic. Working with multiple departments and on various projects, he has developed an extraordinary understanding of cloud and virtualization technology trends and best practices. Next you should read. Global query cache size is applies for all sessions, we can disable for session using below command,. In this article ,We have performed how to do MySQL Performance tuning and optimization by changing in MySQL Configuration like increase mysql connection,increase open file limit,reduce wait timeout,increase buffer pool size and increase query cache.
If you are facing any issues and need support, please share error message in below comment box. I am working as DevOps Engineer and having 5 years of Experience. Make sure you put a value higher than the amount of memory; by accident once, probably a finger slipped, and I put nine times the amount of free memory.
The database was throwing random errors. Typically, having multiple buffer pool instances is appropriate for systems that allocate multiple gigabytes to the InnoDB buffer pool, with each instance being one gigabyte or larger. Having multiple pools allows for better concurrency control and means that each pool is shared by fewer connections and incurs less locking.
Increasing the number of the pool is beneficial in case multiple connections perform heavy operations. They can affect insert performance if the database is used for reading other data while writing. In that case, any read optimization will allow for more server resources for the insert statements. Part of ACID compliance is being able to do a transaction, which means running a set of operations together that either all succeed or all fail.
The transaction log is needed in case of a power outage or any kind of other failure. The database can then resume the transaction from the log file and not lose any data. There are three possible settings, each with its pros and cons. MySQL writes the transaction to a log file and flushes it to the disk on commit.
With this option, MySQL will write the transaction to the log file and will flush to the disk at a specific interval once per second.
With this option, MySQL flushes the transaction to OS buffers, and from the buffers, it flushes to the disk at each interval that will be the fastest. This flag allows you to change the commit timeout from one second to another value, and on some setups, changing this value will benefit performance. I believe it has to do with systems on Magnetic drives with many reads. Naturally, we will want to use the host as the primary key, which makes perfect sense.
The problem with that approach, though, is that we have to use the full string length in every table you want to insert into: A host can be 4 bytes long, or it can be bytes long. Inserting the full-length string will, obviously, impact performance and storage. The problem becomes worse if we use the URL itself as a primary key, which can be one byte to bytes long and even more.
The solution is to use a hashed primary key. Instead of using the actual string value, use a hash. Some filesystems support compression like ZFS , which means that storing MySQL data on compressed partitions may speed the insert rate. The reason is that if the data compresses well, there will be less data to write, which can speed up the insert rate. Inserting to a table that has an index will degrade performance because MySQL has to calculate the index on every insert.
In case there are multiple indexes, they will impact insert performance even more. BTW, when I considered using custom solutions that promised consistent insert rate, they required me to have only a primary key without indexes, which was a no-go for me.
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