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Copy file name to clipboardexpand all lines: docs/connector-development/cdk-python/schemas.md
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### Performance consideration
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Transofrming each object on the fly would add some time for each object processing. This time is depends on object/schema complexitiy and hardware configuration.
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Transforming each object on the fly would add some time for each object processing. This time is depends on object/schema complexitiy and hardware configuration.
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There is some performance benchmark we've done with ads\_insights facebook schema \(it is complex schema with objects nested inside arrays ob object and a lot of references\) and example object. Here is average transform time per single object, seconds:
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There are some performance benchmarks we've done with ads\_insights facebook schema \(it is complex schema with objects nested inside arrays ob object and a lot of references\) and example object. Here is the average transform time per single object, seconds:
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```text
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regular transform:
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0.0006139181846665452
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```
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On my PC \(AMD Ryzen 7 5800X\) it took 0.8 milliseconds per one object. As you can see most time \(~ 75%\) is taken by jsonschema traverse/validation routine and very little \(less than 10 %\) by actual converting. Processing time can be reduced by skipping jsonschema type checking but it would be no warnings about possible object jsonschema inconsistency.
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On my PC \(AMD Ryzen 7 5800X\) it took 0.8 milliseconds per object. As you can see most time \(~ 75%\) is taken by jsonschema traverse/validation routine and very little \(less than 10 %\) by actual converting. Processing time can be reduced by skipping jsonschema type checking but it would be no warnings about possible object jsonschema inconsistency.
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