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Merged
hangfei merged 8 commits into from
Jun 1, 2022
Merged

Product sample #314

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90eb026
[Feathr] Add a example for product recommendation
hangfei Jun 1, 2022
7d6854c
[feathr] Take os set cred out
hangfei Jun 1, 2022
2c958fc
[feathr] Take os set cred out
hangfei Jun 1, 2022
5db8a30
[feathr] Improve text
hangfei Jun 1, 2022
bbcbb6f
[feathr] Product recommendation
hangfei Jun 1, 2022
8ed054a
Merge branch 'main' of https://github.com/linkedin/feathr into produc…
hangfei Jun 1, 2022
4c9c62a
remove unused notebook
hangfei Jun 1, 2022
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add img
hangfei Jun 1, 2022
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15 changes: 7 additions & 8 deletions ..._user_workspace/product_rating_demo.ipynb → ...rkspace/product_recommendation_demo.ipynb
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Expand Up @@ -19,7 +19,8 @@
"6. Materialize feature value to online store.\n",
"7. Fetch feature value in real-time from online store for online scoring.\n",
"\n",
"In this tutorial, we use Feathr Feature Store to create a model that predict users rating for a product."
"In this tutorial, we use Feathr Feature Store to create a model that predict users rating for a product. The feature flow is as below:\n",
"[Feature Flow](https://github.com/linkedin/feathr/blob/main/docs/images/product_recommendation_overview.png?raw=true)"
]
},
{
Expand Down Expand Up @@ -328,7 +329,7 @@
"# User purchase history dataset.\n",
"# Used to generate user features. This is activity type data, so we need to use aggregation to genearte features.\n",
"import pandas as pd\n",
"pd.read_csv(\"https://azurefeathrstorage.blob.core.windows.net/public/sample_data/product_recommendation_sample/user_purchase_history_mock_data\")"
"pd.read_csv(\"https://azurefeathrstorage.blob.core.windows.net/public/sample_data/product_recommendation_sample/user_purchase_history_mock_data.csv\")"
]
},
{
Expand Down Expand Up @@ -536,8 +537,7 @@
"if client.spark_runtime == 'databricks':\n",
" output_path = 'dbfs:/feathrazure_test.avro'\n",
"else:\n",
" # output_path = feathr_output_path\n",
" output_path = 'abfss://[email protected]/feathr_output/product_recommendation_output/'\n",
" output_path = feathr_output_path\n",
"\n",
"\n",
"feature_query = FeatureQuery(\n",
Expand All @@ -548,7 +548,6 @@
" \"feature_user_totla_purchase_in_90days\",\n",
" \"feature_user_purchasing_power\"], key=user_id)\n",
"settings = ObservationSettings(\n",
" # observation_path=\"wasbs://[email protected]/sample_data/green_tripdata_2020-04_with_index.csv\",\n",
" observation_path=\"wasbs://[email protected]/sample_data/product_recommendation_sample/user_observation_mock_data.csv\",\n",
" event_timestamp_column=\"event_timestamp\",\n",
" timestamp_format=\"yyyy-MM-dd\")\n",
Expand Down Expand Up @@ -605,7 +604,7 @@
"metadata": {},
"outputs": [],
"source": [
"# remove columns\n",
"# drop non-feature columns\n",
"from sklearn.ensemble import GradientBoostingRegressor\n",
"final_df = df_res\n",
"final_df.drop([\"event_timestamp\"], axis=1, inplace=True, errors='ignore')\n",
Expand Down Expand Up @@ -695,7 +694,7 @@
"metadata": {},
"outputs": [],
"source": [
"res = client.get_online_features('productRecommendationDemoFeature', '1', [\n",
"client.get_online_features('productRecommendationDemoFeature', '2', [\n",
" 'feature_user_age', 'feature_user_gift_card_balance'])"
]
},
Expand All @@ -705,7 +704,7 @@
"metadata": {},
"outputs": [],
"source": [
"client.multi_get_online_features(\"productRecommendationFeatureSetting\", [\"1\", \"2\"], [\n",
"client.multi_get_online_features('productRecommendationDemoFeature', ['1', '2'], [\n",
" 'feature_user_age', 'feature_user_gift_card_balance'])\n"
]
},
Expand Down