riteshghorse commented on code in PR #30783:
URL: https://github.com/apache/beam/pull/30783#discussion_r1543368304
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examples/notebooks/beam-ml/bigtable_enrichment_transform.ipynb:
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@@ -601,9 +617,9 @@
"id": "F-xjiP_pHWZr"
},
"source": [
- "To make a prediction, use the following fields: `product_id`,
`quantity`, `price`, `customer_id`, and `customer_location`. Retrieve the value
of the `customer_location` field from Bigtable.\n",
+ "The enrichment transform performs a
[`cross_join`](https://beam.apache.org/releases/pydoc/current/apache_beam.transforms.enrichment.html#apache_beam.transforms.enrichment.cross_join)
by default. To override this behavior, the transform accepts a `join_fn`
lambda function. The lambda function takes two dictionaries as input and
returns an enriched row.\n",
"\n",
- "Because the enrichment transform performs a
[`cross_join`](https://beam.apache.org/releases/pydoc/current/apache_beam.transforms.enrichment.html#apache_beam.transforms.enrichment.cross_join)
by default, design the custom join to enrich the input data. This design
ensures that the join includes only the specified fields."
+ "For our ecommerce use case, to make a prediction, it needs the
following fields: `product_id`, `quantity`, `price`, `customer_id`, and
`customer_location`. Design the custom join to enrich the input data such that
the enriched row has these fields."
Review Comment:
I've changed the structure for this
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