Which is faster: multiple single INSERTs or one multiple-row INSERT?
https://dev.mysql.com/doc/refman/8.0/en/insert-optimization.html
The time required for inserting a row is determined by the following factors, where the numbers indicate approximate proportions:
- Connecting: (3)
- Sending query to server: (2)
- Parsing query: (2)
- Inserting row: (1 × size of row)
- Inserting indexes: (1 × number of indexes)
- Closing: (1)
From this it should be obvious, that sending one large statement will save you an overhead of 7 per insert statement, which in further reading the text also says:
If you are inserting many rows from the same client at the same time, use INSERT statements with multiple VALUES lists to insert several rows at a time. This is considerably faster (many times faster in some cases) than using separate single-row INSERT statements.
I know I'm answering this question almost two and a half years after it was asked, but I just wanted to provide some hard data from a project I'm working on right now that shows that indeed doing multiple VALUE blocks per insert is MUCH faster than sequential single VALUE block INSERT statements.
The code I wrote for this benchmark in C# uses ODBC to read data into memory from an MSSQL data source (~19,000 rows, all are read before any writing commences), and the MySql .NET connector (Mysql.Data.*) stuff to INSERT the data from memory into a table on a MySQL server via prepared statements. It was written in such a way as to allow me to dynamically adjust the number of VALUE blocks per prepared INSERT (ie, insert n rows at a time, where I could adjust the value of n before a run.) I also ran the test multiple times for each n.
Doing single VALUE blocks (eg, 1 row at a time) took 5.7 - 5.9 seconds to run. The other values are as follows:
2 rows at a time: 3.5 - 3.5 seconds
5 rows at a time: 2.2 - 2.2 seconds
10 rows at a time: 1.7 - 1.7 seconds
50 rows at a time: 1.17 - 1.18 seconds
100 rows at a time: 1.1 - 1.4 seconds
500 rows at a time: 1.1 - 1.2 seconds
1000 rows at a time: 1.17 - 1.17 seconds
So yes, even just bundling 2 or 3 writes together provides a dramatic improvement in speed (runtime cut by a factor of n), until you get to somewhere between n = 5 and n = 10, at which point the improvement drops off markedly, and somewhere in the n = 10 to n = 50 range the improvement becomes negligible.
Hope that helps people decide on (a) whether to use the multiprepare idea, and (b) how many VALUE blocks to create per statement (assuming you want to work with data that may be large enough to push the query past the max query size for MySQL, which I believe is 16MB by default in a lot of places, possibly larger or smaller depending on the value of max_allowed_packet set on the server.)