How do I manage a large MySQL database?

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What I've understood so far to improve the performance for very large tables: (for innoDB tables which is my case) increasing the innodb_buffer_pool_size (e.g., up to 80% of RAM). . having proper indexes on the table (using EXPLAN on queries) partitioning the table. MySQL Sharding or clustering.

Can MySQL handle large database?

MySQL was not designed for running complicated queries against massive data volumes which requires crunching through a lot of data on a huge scale. MySQL optimizer is quite limited, executing a single query at a time using a single thread.

How do you manage a large database?

Here are 11 tips for making the most of your large data sets.1Cherish your data. “Keep your raw data raw: don't manipulate it without having a copy,” says Teal. ... 2Visualize the information.3Show your workflow. ... 4Use version control. ... 5Record metadata. ... 6Automate, automate, automate. ... 7Make computing time count. ... 8Capture your environment.Eleven tips for working with large data sets - Nature

Can MySQL handle 1 million records?

Millions of rows is fine, tens of millions of rows is fine - provided you've got an even remotely decent server, i.e. a few Gbs of RAM, plenty disk space. You will need to learn about indexes for fast retrieval, but in terms of MySQL being able to handle it, no problem.

How do I speed up a large MySQL database?

Tips to Improve MySQL Query Performance1Optimize Your Database. You need to know how to design schemas to support efficient queries. ... 2Optimize Joins. Reduce the join statements in queries. ... 3Index All Columns Used in 'where', 'order by', and 'group by' Clauses. INDEXES. ... 4Use Full-Text Searches. ... 5MySQL Query Caching.Tips to Improve MySQL Query Performance - Bridge Global

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