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    <p><strong>Monitoring.</strong> Use some tools to monitor performance, and saturation of CPU, memory, and I/O. Make trend lines so you know where your next bottleneck will be before you get there.</p> <p><strong>Testing.</strong> Create mock data so you have 10 million rows on a testing server <em>today.</em> Benchmark the queries you have in your application and see how well they perform as the volume of data increases. You might be surprised at what breaks down first, or it may go exactly as predicted. The point is that you can <em>find out</em>.</p> <p><strong>Maintenance.</strong> Make sure your application and infrastructure support some downtime, because that's always necessary. You might have to defrag and rebuild your indexes. You might have to refactor some of the table structure. You might have to upgrade the server software or apply patches. To do this without interrupting continuous operation, you'll need some redundancy built in to the design.</p> <p><strong>Research.</strong> Find the best journals and blogs for the database brand you're using, and read them (e.g. <a href="http://www.mysqlperformanceblog.com" rel="nofollow noreferrer">http://www.mysqlperformanceblog.com</a> if you use MySQL). You can ask good questions like the one you ask here, but also read what other people are asking, and what they're being advised to do about it. You can learn solutions to problems that you don't even have yet, so that <em>when</em> you have them, you'll have some strategies to employ.</p>
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    1. POensuring database performance as data volume increases
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    1. COThe issue with mock data I see is the diversity of values especially on the indexes columns. Unless it reflects the way real life data would be distributed, I feel the results cant be taken seriously. But yes, we would anyway be creating the mock data.
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      1. USSathya
    2. COYou already can calculate the distribution of real data based on the current real data you have. You can then generate test data with the same distribution characteristics. You mention the diversity of values on indexes columns. I don't see why you can't calculate the current distribution and then generate test data with the same pattern.
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      1. USRibaldEddie
    3. CORight, you don't have to generate absolutely random test data. Though it it's true that your current small data set can't predict perfectly what the data diversity will be when you have millions of rows, I don't agree that this means "the results can't be taken seriously." Realistically, a test with synthetic data is accurate enough to help you tune your SQL queries.
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