I was doing some benchmarks on MySQL. Both locally and on Google Cloud SQL. And one performance issue struck me.
Batch inserts are as slow as individual inserts
What it means basically is if you insert 10,000 rows, one row at a time or 10,000 in a batch, it takes about the same time. You pay a server round-trip for each row. How uncool is that? I’ve never seen a database behave this way. I’m already not a big SQL fan. This doesn’t help me become one.
Turns out there’s an easy fix, that is not activated by default by Connector/J, the MySQL jdbc driver. Add
rewriteBatchedStatements=true to the connection properties and there you go, the batch is executed in batch mode with a single round-trip to the server. That’s a huge improvement.
Why on Earth is it not the default?
I don’t have a good answer to this question. I’ve got a bad answer though: When values are sent in batch, all values must fit into the
max_allowed_packet envelope. If it doesn’t fit, the query will fail. So, it’s safer to let each row fit than try to fit all rows.
A good implementation would activate this behaviour by default, get rid of the
max_allowed_packet altogether and use as many server round-trip (one per N rows, not one per row) as needed to send all the data.
Well at least I solved my problem…
Yes and No. Yes, I solved this batch insert counterintuitive behaviour. No, every round trip to the server is still very long. Specially on the Cloud Platform, whether I use Google Cloud SQL or my own SQL hosted on a Compute Engine instance.
Maybe I need to search for some more counterintuitive magic property!