Markus Schaber wrote:
John Arbash Meinel schrieb:
I am doing research for a project of mine where I need to store several billion values for a monitoring and historical tracking system for a big computer system. My currect estimate is that I have to store (somehow) around 1 billion values each month (possibly more).
If you have that 1 billion perfectly distributed over all hours of the day, then you need 1e9/30/24/3600 = 385 transactions per second.
I hope that he does not use one transaction per inserted row.
In your in-house tests, we got a speedup factor of up to some hundred when bundling rows on insertions. The fastest speed was with using bunches of some thousand rows per transaction, and running about 5 processes in parallel.
You're right. I guess it just depends on how the data comes in, and what you can do at the client ends. That is kind of where I was saying put a machine in front which gathers up the information, and then does a batch update. If your client can do this directly, then you have the same advantage.
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