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Add arch for module 2
Signed-off-by: Danny Chiao <danny@tecton.ai>
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module_2/README.md

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In this module, we introduce the concept of on demand transforms. These are transformations that execute on-the-fly and accept as input other feature views or request data.
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On a high level, the flow of data will look like
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![](odfv_arch.png)
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<h2>Table of Contents</h2>
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- [Workshop](#workshop)
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- Because a source feature view can have a `PushSource`, this means we can also apply a consistent last-mile transformation on both batch and streaming features.
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- Note that the above has a single `inputs` Pandas dataframe as input. This joins together all the sources for the `OnDemandFeatureView`
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![](odfv_arch.png)
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## Step 4: Apply features
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```console
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$ feast apply

module_2/odfv_arch.png

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