Generate synthetic manifests for performance tests #1495
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serramatutu
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Nov 4, 2024
| * Minimize the number of parameters required. | ||
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| Notes: | ||
| * The synthetic manifest groups semantic models into two types - ones containing measures, and others containing dimensions. |
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I suppose this still captures the relevant behavior from production models, so it's fine? Is there anything extra we'd able to test by relaxing this and creating "mixed" models?
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Same question for the other constraints: you can reach all measures via all dimensions etc.
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So those are simplifications to make it easier to generate semantic models and to make it easier to generate queries for metric. Mixed models would make it mimic production better, but I didn't think the added complexity would flesh out any performance cases that much better.
serramatutu
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Nov 4, 2024
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This PR adds a few classes to generate a synthetic manifest. The synthetic manifest can then be used to profile performance and scaling behavior.