Can MySQL handle billions of rows?

Yes the data size is too big than RAM. A- All the fields are string type. we have used varchar(127) for all.

How many rows of data can MySQL handle?

Originally Answered: What is the max rows a MySQL database can store per table? The limit is usually your primary key. If your PK is an unsigned INT, then you will be able to store 4294967295 rows. Make it an unsigned BIGINT and you will be able to store 18446744073709551615 rows.

How do you handle a large query?

What I’ve understood so far to improve the performance for very large tables:

1. (for innoDB tables which is my case) increasing the innodb_buffer_pool_size (e.g., up to 80\% of RAM).
2. having proper indexes on the table (using EXPLAN on queries)
3. partitioning the table.
4. MySQL Sharding or clustering.

How can I speed up my BCP export?

The following tips can help make BCP fly.

1. Tip 1: Always use fast BCP.
2. Tip 2: Run BCP from the server.
3. Tip 3: Use local named pipes.BR> When BCP runs on the same machine as SQL Server, using local named pipes greatly speeds the process.
4. Tip 4: Place BCP and SQL Server data on separate disks.

Can MySQL handle tables which will hold about 300 million records?

Can Mysql handle tables which will hold about 300 million records? — again, yes. The limit is somewhere around a trillion rows. (for innoDB tables which is my case) increasing the innodb_buffer_pool_size (e.g., up to 80\% of RAM). Also, I found some other MySQL performance tunning settings here in percona blog — yes

Why MySQL will conduct a full table scan on 500 rows?

First, it is clear that MySQL will conduct a full table scan because key column is ‘ NULL ‘. Second, MySQL server has clearly indicated that it’s going to conduct a full scan on the 500 rows in our database. To optimize the above query, we can just add an index to the ‘ customer_id ‘ field using the below syntax:

Why is MySQL so slow with large tables?

Why MySQL could be slow with large tables? — range scans lead to I/O, which is the slow part. Can Mysql handle tables which will hold about 300 million records? — again, yes. The limit is somewhere around a trillion rows. (for innoDB tables which is my case) increasing the innodb_buffer_pool_size (e.g., up to 80\% of RAM).

What are the disadvantages of using mymysql indexes?

MySQL indexes may take up more space and decrease performance on inserts, deletes, and updates. However, if your table has more than 10 rows, they can considerably reduce select query execution time.