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updated login endpoint to controller-svc-external

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This commit is contained in:
Bill Liang
2019-08-05 12:42:26 -07:00
parent 3779327a32
commit c846036409
7 changed files with 14 additions and 14 deletions
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samples/features/sql-big-data-cluster/app-deploy/RollDice/README.md
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@@ -41,10 +41,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name> -p <password>
```
3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `roll-dice.R` files are located:
```bash
samples/features/sql-big-data-cluster/app-deploy/SSIS/README.md
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@@ -32,10 +32,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
3. Replace `[SA_PASSWORD]` in the `spec.yaml` file with the password for SQL user `sa`.
4. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `back-up-db.dtsx` files are located:
samples/features/sql-big-data-cluster/app-deploy/addpy/README.md
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@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `add.py` files are located:
```bash
samples/features/sql-big-data-cluster/app-deploy/magic8ball/README.md
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@@ -41,10 +41,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `magic8ball.py` files are located:
```bash
samples/features/sql-big-data-cluster/app-deploy/mleap/README.md
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@@ -38,10 +38,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
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).
samples/features/sql-big-data-cluster/app-deploy/sentiment-analysis/README.md
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@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
3. Deploy the application by running the following command, specifying the folder where your `spec.yaml`, `sentiment.rds` and `sentiment.R` files are located:
```bash
samples/features/sql-big-data-cluster/app-deploy/sumofsq/README.md
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@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
## Run this sample
1. Clone or download this sample on your computer.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
```bash
azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
```
3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `sum_of_squares.R` files are located:
```bash