Getting Started with ScalarDB Cluster SQL via Spring Data JDBC for ScalarDB

This tutorial describes how to create a sample application by using ScalarDB Cluster SQL via Spring Data JDBC for ScalarDB.

Prerequisites for this sample application

• One of the following Java Development Kits (JDKs):
  • Oracle JDK 8
  • OpenJDK 8 from Eclipse Temurin, Amazon Corretto, or Microsoft
• ScalarDB Cluster running on a Kubernetes cluster
  • We assume that you have a ScalarDB Cluster running on a Kubernetes cluster that you deployed by following the instructions in Set Up ScalarDB Cluster on Kubernetes by Using a Helm Chart.

note

This sample application only works with Java 8. However, ScalarDB itself works with Java LTS versions, which means that you can use Java LTS versions for your application that uses ScalarDB. For details on the requirements of ScalarDB, such as which Java versions can be used, see Requirements.

In this tutorial, we assume that you have a ScalarDB Cluster running on a Kubernetes cluster that you deployed by following the instructions in Set Up ScalarDB Cluster on Kubernetes by Using a Helm Chart.

In addition, you need access to the ScalarDB Cluster GitHub repository, packages in the ScalarDB Cluster repository, and packages in the ScalarDB SQL repository. These repositories are available only to users with a commercial license and permission. To get a license and permission, please contact us.

You also need to set the gpr.user property to your GitHub username and the gpr.key property to your personal access token. To do so, you must either add these properties in ~/.gradle/gradle.properties or specify the properties by using the -P option when running the ./gradlew command as follows:

./gradlew run ... -Pgpr.user=<YOUR_GITHUB_USERNAME> -Pgpr.key=<YOUR_PERSONAL_ACCESS_TOKEN>

Or you can use environment variables, such as USERNAME for your GitHub username and TOKEN for your personal access token.

export USERNAME=<YOUR_GITHUB_USERNAME>
export TOKEN=<YOUR_PERSONAL_ACCESS_TOKEN>

For more details, see Developer Guide for ScalarDB Cluster with the Java API.

Sample application

This tutorial illustrates the process of creating a sample e-commerce application, where items can be ordered and paid for with a line of credit by using Spring Data JDBC for ScalarDB.

The following diagram shows the system architecture of the sample application:

                                 +------------------------------------------------------------------------------------------------------------------------------+
                                 | [Kubernetes Cluster]                                                                                                         |
                                 |                                                                                                                              |
                                 |                          [Pod]                                                     [Pod]                         [Pod]       |
 +------------------------+      |                                                                                                                              |
 |        SQL CLI         |      |                        +-------+                                          +-----------------------+                          |
 | (indirect client mode) | --+  |                  +---> | Envoy | ---+                               +---> | ScalarDB Cluster Node | ---+                     |
 +------------------------+   |  |                  |     +-------+    |                               |     +-----------------------+    |                     |
                              |  |                  |                  |                               |                                  |                     |
                              |  |   +---------+    |     +-------+    |     +--------------------+    |     +-----------------------+    |     +------------+  |
                              +--+-> | Service | ---+---> | Envoy | ---+---> |      Service       | ---+---> | ScalarDB Cluster Node | ---+---> | PostgreSQL |  |
 +------------------------+   |  |   | (Envoy) |    |     +-------+    |     | (ScalarDB Cluster) |    |     +-----------------------+    |     +------------+  |
 |   Sample application   |   |  |   +---------+    |                  |     +--------------------+    |                                  |                     |
 |  with Spring Data JDBC |   |  |                  |     +-------+    |                               |     +-----------------------+    |                     |
 |      for ScalarDB      | --+  |                  +---> | Envoy | ---+                               +---> | ScalarDB Cluster Node | ---+                     |
 | (indirect client mode) |      |                        +-------+                                          +-----------------------+                          |
 +------------------------+      |                                                                                                                              |
                                 +------------------------------------------------------------------------------------------------------------------------------+

Step 1. Clone the ScalarDB Samples repository

git clone https://github.com/scalar-labs/scalardb-samples.git
cd scalardb-samples/spring-data-sample

Step 2. Modify scalardb-sql.properties

You need to modify scalardb-sql.properties to connect to ScalarDB Cluster as well. But before doing so, you need to get the EXTERNAL-IP address of the service resource of Envoy (scalardb-cluster-envoy) as follows:

kubectl get svc scalardb-cluster-envoy
NAME                     TYPE           CLUSTER-IP      EXTERNAL-IP   PORT(S)           AGE
scalardb-cluster-envoy   LoadBalancer   10.105.121.51   localhost     60053:30641/TCP   16h

In this case, the EXTERNAL-IP address is localhost.

Next, open scalardb-sql.properties:

vim scalardb-sql.properties

Then, modify scalardb-sql.properties as follows:

scalar.db.sql.connection_mode=cluster
scalar.db.sql.cluster_mode.contact_points=indirect:localhost

To connect to ScalarDB Cluster, you need to specify cluster for the scalar.db.sql.connection_mode property. In addition, you will use the indirect client mode and connect to the service resource of Envoy in this tutorial. For details about the client modes, see Developer Guide for ScalarDB Cluster with the Java API.

Step 3. Load a schema

To load a schema, you need to use the SQL CLI. You can download the SQL CLI from ScalarDB Releases. After downloading the JAR file, you can use SQL CLI for Cluster by running the following command:

java -jar scalardb-cluster-sql-cli-3.9.7-all.jar --config scalardb-sql.properties --file schema.sql

Step 4. Modify application.properties

Then, you need to modify application.properties to connect to ScalarDB Cluster as well:

vim src/main/resources/application.properties

Similar to scalardb-sql.properties, you need to specify cluster for the scalar.db.sql.connection_mode property and use the indirect client mode. To do so, modify application.properties as follows:

spring.datasource.driver-class-name=com.scalar.db.sql.jdbc.SqlJdbcDriver
spring.datasource.url=jdbc:scalardb:\
?scalar.db.sql.connection_mode=cluster\
&scalar.db.sql.cluster_mode.contact_points=indirect:localhost\
&scalar.db.consensus_commit.isolation_level=SERIALIZABLE\
&scalar.db.sql.default_namespace_name=sample

Step 5. Load the initial data

Before running the sample application, you need to load the initial data by running the following command:

./gradlew run --args="LoadInitialData"

After the initial data has loaded, the following records should be stored in the tables:

• For the sample.customers table:

customer_id	name	credit_limit	credit_total
1	Yamada Taro	10000	0
2	Yamada Hanako	10000	0
3	Suzuki Ichiro	10000	0

• For the sample.items table:

item_id	name	price
1	Apple	1000
2	Orange	2000
3	Grape	2500
4	Mango	5000
5	Melon	3000

Step 6. Run the sample application

Let's start with getting information about the customer whose ID is 1:

./gradlew run --args="GetCustomerInfo 1"
...
{"customer_id":1,"name":"Yamada Taro","credit_limit":10000,"credit_total":0}
...

Then, place an order for three apples and two oranges by using customer ID 1. Note that the order format is <Item ID>:<Count>,<Item ID>:<Count>,...:

./gradlew run --args="PlaceOrder 1 1:3,2:2"
...
{"order_id":"2358ab35-5819-4f8f-acb1-12e73d97d34e","customer_id":1,"timestamp":1677478005400}
...

You can see that running this command shows the order ID.

Let's check the details of the order by using the order ID:

./gradlew run --args="GetOrder 2358ab35-5819-4f8f-acb1-12e73d97d34e"
...
{"order_id":"2358ab35-5819-4f8f-acb1-12e73d97d34e","timestamp":1677478005400,"customer_id":1,"customer_name":"Yamada Taro","statements":[{"item_id":1,"item_name":"Apple","price":1000,"count":3,"total":3000},{"item_id":2,"item_name":"Orange","price":2000,"count":2,"total":4000}],"total":7000}
...

Then, let's place another order and get the order history of customer ID 1:

./gradlew run --args="PlaceOrder 1 5:1"
...
{"order_id":"46062b16-b71b-46f9-a9ff-dc6b0991259b","customer_id":1,"timestamp":1677478201428}
...
./gradlew run --args="GetOrders 1"
...
[{"order_id":"46062b16-b71b-46f9-a9ff-dc6b0991259b","timestamp":1677478201428,"customer_id":1,"customer_name":"Yamada Taro","statements":[{"item_id":5,"item_name":"Melon","price":3000,"count":1,"total":3000}],"total":3000},{"order_id":"2358ab35-5819-4f8f-acb1-12e73d97d34e","timestamp":1677478005400,"customer_id":1,"customer_name":"Yamada Taro","statements":[{"item_id":1,"item_name":"Apple","price":1000,"count":3,"total":3000},{"item_id":2,"item_name":"Orange","price":2000,"count":2,"total":4000}],"total":7000}]
...

This order history is shown in descending order by timestamp.

The customer's current credit_total is 10000. Since the customer has now reached their credit_limit, which was shown when retrieving their information, they cannot place anymore orders.

./gradlew run --args="GetCustomerInfo 1"
...
{"id": 1, "name": "Yamada Taro", "credit_limit": 10000, "credit_total": 10000}
...
./gradlew run --args="PlaceOrder 1 3:1,4:1"
...
java.lang.RuntimeException: Credit limit exceeded. limit:10000, total:17500
        at sample.SampleService.placeOrder(SampleService.java:102)
        at sample.SampleService$$FastClassBySpringCGLIB$$1123c447.invoke(<generated>)
        at org.springframework.cglib.proxy.MethodProxy.invoke(MethodProxy.java:218)
        at org.springframework.aop.framework.CglibAopProxy$CglibMethodInvocation.invokeJoinpoint(CglibAopProxy.java:793)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:163)
        at org.springframework.aop.framework.CglibAopProxy$CglibMethodInvocation.proceed(CglibAopProxy.java:763)
        at org.springframework.transaction.interceptor.TransactionInterceptor$1.proceedWithInvocation(TransactionInterceptor.java:123)
        at org.springframework.transaction.interceptor.TransactionAspectSupport.invokeWithinTransaction(TransactionAspectSupport.java:388)
        at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:119)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186)
        at org.springframework.aop.framework.CglibAopProxy$CglibMethodInvocation.proceed(CglibAopProxy.java:763)
        at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:708)
        at sample.SampleService$$EnhancerBySpringCGLIB$$a94e1d9.placeOrder(<generated>)
        at sample.command.PlaceOrderCommand.call(PlaceOrderCommand.java:37)
        at sample.command.PlaceOrderCommand.call(PlaceOrderCommand.java:13)
        at picocli.CommandLine.executeUserObject(CommandLine.java:2041)
        at picocli.CommandLine.access$1500(CommandLine.java:148)
        at picocli.CommandLine$RunLast.executeUserObjectOfLastSubcommandWithSameParent(CommandLine.java:2461)
        at picocli.CommandLine$RunLast.handle(CommandLine.java:2453)
        at picocli.CommandLine$RunLast.handle(CommandLine.java:2415)
        at picocli.CommandLine$AbstractParseResultHandler.execute(CommandLine.java:2273)
        at picocli.CommandLine$RunLast.execute(CommandLine.java:2417)
        at picocli.CommandLine.execute(CommandLine.java:2170)
        at sample.SampleApp.run(SampleApp.java:26)
        at org.springframework.boot.SpringApplication.callRunner(SpringApplication.java:768)
        at org.springframework.boot.SpringApplication.callRunners(SpringApplication.java:752)
        at org.springframework.boot.SpringApplication.run(SpringApplication.java:314)
        at org.springframework.boot.SpringApplication.run(SpringApplication.java:1303)
        at org.springframework.boot.SpringApplication.run(SpringApplication.java:1292)
        at sample.SampleApp.main(SampleApp.java:35)
...

After making a payment, the customer will be able to place orders again.

./gradlew run --args="Repayment 1 8000"
...
./gradlew run --args="GetCustomerInfo 1"
...
{"customer_id":1,"name":"Yamada Taro","credit_limit":10000,"credit_total":2000}
...
./gradlew run --args="PlaceOrder 1 3:1,4:1"
...
{"order_id":"0350947a-9003-46f2-870e-6aa4b2df0f1f","customer_id":1,"timestamp":1677478728134}
...

Source code of the sample application

To learn more about Spring Data JDBC for ScalarDB, you can check the source code of the sample application.

See also

For other ScalarDB Cluster tutorials, see the following:

• Getting Started with ScalarDB Cluster
• Getting Started with ScalarDB Cluster GraphQL
• Getting Started with ScalarDB Cluster SQL via JDBC
• Getting Started with Using Go for ScalarDB Cluster
• Getting Started with Using Python for ScalarDB Cluster

For details about developing applications that use ScalarDB Cluster with the Java API, refer to the following:

• Developer Guide for ScalarDB Cluster with the Java API

For details about the ScalarDB Cluster gRPC API, refer to the following:

• ScalarDB Cluster gRPC API Guide
• ScalarDB Cluster SQL gRPC API Guide