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Updating MLeap example
This commit is contained in:
Jeroen ter Heerdt
@@ -43,23 +43,23 @@ To run this sample, you need the following prerequisites.
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```bash
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mssqlctl login -e https://<ip-address-of-endpoint-service-proxy>:30777 -u <user-name> -p <password>
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```
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3. This example uses a Machine Learning Model that predicts the price per square foot of an Airbnb property based on various parameters such as the location and type of dwelling. [More details and information on the example are here](http://mleap-docs.combust.ml/mleap-serving/#load-model). The application you will be deploying as part of this sample is a Random Forest Model that was built in Spark and has been serialized as an MLeap bundle.
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3. This example uses a TensorFlow Machine Learning Model that uses public US Census data predict income. [More details and information on the example are here](https://docs.microsoft.com/en-us/sql/big-data-cluster/train-and-create-machinelearning-models-with-spark?view=sqlallproducts-allversions). The application you will be deploying as part of this sample is a Random Forest Model that was built in Spark and has been [serialized as an MLeap bundle](https://docs.microsoft.com/en-us/sql/big-data-cluster/export-model-with-spark-mleap?view=sqlallproducts-allversions).
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Deploy the app using the `create` command and pass the location of the spec file. In the example below, the spec file is expected to be in the `mleap` folder:
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```bash
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mssqlctl app create --spec ./mleap
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mssqlctl app create --spec ./mleap/
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```
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4. Check the deployment by running the following command:
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1. Check the deployment by running the following command:
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```bash
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mssqlctl app list -n mleap -v [version]
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mssqlctl app list -n mleap-census -v [version]
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```
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Once the app is listed as `Ready` you can continue to the next step.
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5. Now that the app has been deployed you can test if the app works correctly by passing in a sample input that is available in the mleap folder. The deployed app is a RESTful webservice that is [Swagger](swagger.io) compliant. For this sample we will show you how you can test this using the CLI.
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2. Now that the app has been deployed you can test if the app works correctly by passing in a sample input that is available in the `mleap` folder. The deployed app is a RESTful webservice that is [Swagger](swagger.io) compliant. For this sample we will show you how you can test this using the CLI.
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To test the app, run the command below. The input parameter is a `LeapFrame`, a `json` file that describes the parameters and the values provided to the model for predicting the cost per square feet. Note that the input parameter has a special character '@' to indicate that a `json` file is being passed. This command needs to be run within the `mleap` folder.
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To test the app, run the command below. The input parameter is a `MLeapFrame`, a `json` file that describes the parameters and the values provided to the model for predicting the cost per square feet. Note that the input parameter has a special character '@' to indicate that a `json` file is being passed. This command needs to be run within the `mleap` folder.
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```bash
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mssqlctl app run --name mleap --version [version] --input mleap-frame=@frame.json
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mssqlctl app run --name mleap-census --version [version] --input schema=@census_frame.json
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```
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The result will be a json output that includes the prediction along with additional data, including the predicted price per square feet.
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@@ -69,7 +69,7 @@ To run this sample, you need the following prerequisites.
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6. You can clean up the sample by running the following commands:
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```bash
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# delete app
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mssqlctl app delete --name mleap --version [version]
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mssqlctl app delete --name mleap-census --version [version]
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```
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<a name=sample-details></a>
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@@ -82,10 +82,10 @@ The spec file serves as the data required for deploying the app and it contains
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Here is the spec file for this application:
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```yaml
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name: mleap
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name: mleap-census
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version: v1
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runtime: Mleap
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bundleFileName: model.lr.zip
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bundleFileName: census_bundle.zip
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replicas: 2
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poolsize: 2
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```
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@@ -0,0 +1,35 @@
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{
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"rows": [
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[
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17,
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4,
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"<=50K"
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],
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[
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17,
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5,
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"<=50K"
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],
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[
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17,
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5,
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"<=50K"
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]
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],
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"schema": {
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"fields": [
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{
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"name": "age",
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"type": "integer"
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},
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{
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"name": "hours_per_week",
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"type": "integer"
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},
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{
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"name": "income",
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"type": "string"
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}
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]
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}
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}
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@@ -1,45 +0,0 @@
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{
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"schema": {
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"fields": [{
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"name": "state",
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"type": "string"
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}, {
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"name": "bathrooms",
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"type": "double"
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}, {
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"name": "square_feet",
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"type": "double"
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}, {
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"name": "bedrooms",
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"type": "double"
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}, {
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"name": "security_deposit",
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"type": "double"
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}, {
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"name": "cleaning_fee",
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"type": "double"
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}, {
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"name": "extra_people",
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"type": "double"
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}, {
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"name": "number_of_reviews",
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"type": "double"
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}, {
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"name": "review_scores_rating",
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"type": "double"
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}, {
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"name": "room_type",
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"type": "string"
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}, {
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"name": "host_is_superhost",
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"type": "string"
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}, {
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"name": "cancellation_policy",
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"type": "string"
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}, {
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"name": "instant_bookable",
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"type": "string"
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}]
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},
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"rows": [["NY", 2.0, 1250.0, 3.0, 50.0, 30.0, 2.0, 56.0, 90.0, "Entire home/apt", "1.0", "strict", "1.0"]]
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}
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Binary file not shown.
@@ -1,3 +1,3 @@
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name: mleap
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name: mleap-census
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version: v1
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inputs: ./frame.json
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inputs: ./census_frame.json
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@@ -1,6 +1,5 @@
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name: mleap
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name: mleap-census
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version: v1
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runtime: Mleap
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bundleFileName: model.lr.zip
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replicas: 2
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poolsize: 2
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bundleFileName: census_bundle.zip
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replicas: 1
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