# HTTP to MySQL Demo
In this demonstration, you will learn how to orchestrate a data pipeline using http://cloud.spring.io/spring-cloud-dataflow/[Spring Cloud Data Flow] to consume data from an `http` endpoint and write to MySQL database through `jdbc` sink.
We will begin by discussing the steps to prep, configure and operationalize Spring Cloud Data Flow's `admin` Spring Boot application. We will deploy `admin` using the https://github.com/spring-cloud/spring-cloud-dataflow-admin-cloudfoundry[Cloud Foundry] SPI (Service Provider Interface) to demonstrate how Spring Cloud Data Flow takes advantage of _cloud-native_ platform capabilities natively.
# Prerequisites for Pivotal Cloud Foundry
In order to get started, make sure that you have the following components:
* Cloud Foundry instance
* Local build of https://github.com/spring-cloud/spring-cloud-dataflow[Spring Cloud Data Flow]
* Local build of Spring Cloud Data Flow's https://github.com/spring-cloud/spring-cloud-dataflow-admin-cloudfoundry[Cloud-Foundry-Admin]
* The `Book` https://github.com/trisberg/spring-cloud-demo/tree/master/book[domain object] (maven artifact)
* Redis instance
* MySQL instance
## Running the Sample in Cloud Foundry
. Verify that CF instance is reachable
+
```
→ cf api
API endpoint: https://api.system.navy.springapps.io (API version: 2.43.0)
→ cf apps
Getting apps in org sabby-dataflow / space development as sabby...
OK
No apps found
```
+
. Follow the instructions to deploy Spring Cloud Data Flow's `admin` from https://github.com/spring-cloud/spring-cloud-dataflow-admin-cloudfoundry/blob/master/README.adoc[CF SPI] repo
+
. Once you complete step#3 from https://github.com/spring-cloud/spring-cloud-dataflow-admin-cloudfoundry/blob/master/README.adoc[CF SPI] instructions, you'll be able to list the newly deployed `s-c-dataflow-admin` application in Cloud Foundry
+
```
→ cf apps
Getting apps in org sabby-dataflow / space development as sabby...
OK
name requested state instances memory disk urls
s-c-dataflow-admin started 1/1 1G 1G s-c-dataflow-admin.app.navy.springapps.io
```
+
. Notice that `s-c-dataflow-admin` application is started and ready for interaction via `http://s-c-dataflow-admin.app.navy.springapps.io` endpoint
. Connect to Spring Cloud Data Flow's `shell`.
+
```
→ cd <PATH/TO/SPRING-CLOUD-DATAFLOW>
→ java -jar spring-cloud-dataflow-shell/target/spring-cloud-dataflow-shell-1.0.0.BUILD-SNAPSHOT.jar
____ ____ _ __
/ ___| _ __ _ __(_)_ __ __ _ / ___| | ___ _ _ __| |
\___ \| '_ \| '__| | '_ \ / _` | | | | |/ _ \| | | |/ _` |
___) | |_) | | | | | | | (_| | | |___| | (_) | |_| | (_| |
|____/| .__/|_| |_|_| |_|\__, | \____|_|\___/ \__,_|\__,_|
____ |_| _ __|___/ __________
| _ \ __ _| |_ __ _ | ___| | _____ __ \ \ \ \ \ \
| | | |/ _` | __/ _` | | |_ | |/ _ \ \ /\ / / \ \ \ \ \ \
| |_| | (_| | || (_| | | _| | | (_) \ V V / / / / / / /
|____/ \__,_|\__\__,_| |_| |_|\___/ \_/\_/ /_/_/_/_/_/
1.0.0.BUILD-SNAPSHOT
Welcome to the Spring Cloud Data Flow shell. For assistance hit TAB or type "help".
server-unknown:>
```
+
. Connect the `shell` with `admin` running at `http://s-c-dataflow-admin.app.navy.springapps.io`
+
```
server-unknown:>admin config server http://s-c-dataflow-admin.app.navy.springapps.io
Successfully targeted http://s-c-dataflow-admin.app.navy.springapps.io
dataflow:>version
1.0.0.BUILD-SNAPSHOT
```
+
. Create the stream
+
```
dataflow:>stream create --name mysqlstream --definition "http | jdbc --includes='mysql:mysql-connector-java:5.1.37' --spring.datasource.url='jdbc:mysql://<HOST>:<PORT>/<NAME>' --spring.datasource.username=<USERNAME> --spring.datasource.password=<PASSWORD> --tableName=names --columns=name --spring.datasource.driverClassName=com.mysql.jdbc.Driver --initialize=true" --deploy
Created and deployed new stream 'mysqlstream'
```
+
. Verify the stream is successfully deployed
+
```
dataflow:>stream list
```
+
. Notice that `mysqlstream-http` and `mysqlstream-jdbc` https://github.com/spring-cloud/spring-cloud-stream-modules/[Spring Cloud Stream] modules are running as _cloud-native_ (microservice) applications in Cloud Foundry
+
```
→ cf apps
Getting apps in org sabby-dataflow / space development as sabby...
OK
name requested state instances memory disk urls
mysqlstream-http started 1/1 1G 1G mysqlstream-http.app.navy.springapps.io
mysqlstream-jdbc started 1/1 1G 1G mysqlstream-jdbc.app.navy.springapps.io
s-c-dataflow-admin started 1/1 1G 1G s-c-dataflow-admin.app.navy.springapps.io
```
+
. Lookup the `url` for `mysqlstream-http` application from the list above. Post sample data pointing to the `http` endpoint: `<YOUR-mysqlstream-http-APP-URL>/messages`
+
```
dataflow:>script --file <PATH/TO>/spring-cloud-dataflow-samples/http-to-mysql/data.txt
http post --contentType 'application/json' --target http://mysqlstream-http.app.navy.springapps.io/messages --data "{\"name\": \"Spring Boot 1\"}"
> POST (application/json;charset=UTF-8) http://mysqlstream-http.app.navy.springapps.io/messages {"name": "Spring Boot 1"}
> 202 ACCEPTED
...
...
...
```
+
. Use a database utility tool such as http://dbeaver.jkiss.org/[DBeaver] to connect to the MySQL instance. Query the table `book` to list all the 10 rows
+
```
select * from book;
```
image:img/mysql_table_results.png[Table Results]
+
. Now, let's try to take advantage of Pivotal Cloud Foundry's platform capability. Let's scale the `mysqlstream-http` application from 1 to 3 instances
+
```
→ cf scale mysqlstream-http -i 3
Scaling app mysqlstream-http in org sabby-dataflow / space development as sabby...
OK
```
+
. Verify App instances (3/3) running successfully
+
```
→ cf apps
Getting apps in org sabby-dataflow / space development as sabby...
OK
name requested state instances memory disk urls
mysqlstream-http started 3/3 1G 1G mysqlstream-http.app.navy.springapps.io
mysqlstream-jdbc started 1/1 1G 1G mysqlstream-jdbc.app.navy.springapps.io
s-c-dataflow-admin started 1/1 1G 1G s-c-dataflow-admin.app.navy.springapps.io
```
+
. That's it; you're done!
# Summary
In this sample, you have learned:
* How to use Spring Cloud Data Flow in Pivotal Cloud Foundry
* How to use Spring Cloud Data Flow's `shell`
* How to create streaming data pipeline to connect and write to MySQL using Spring Cloud Data Flow
* How to scale data microservice applications in isolation
