JSON

Creating a data generator for JSON. You will have the ability to generate and validate JSON files via Docker.

Requirements

• 10 minutes
• Git
• Gradle
• Docker

Get Started

First, we will clone the data-caterer-example repo which will already have the base project setup required.

JavaScalaYAMLUI

git clone git@github.com:data-catering/data-caterer-example.git

git clone git@github.com:data-catering/data-caterer-example.git

git clone git@github.com:data-catering/data-caterer-example.git

Run Data Caterer UI via the 'Quick Start' found here.

Plan Setup

Create a new Java or Scala class.

• Java: src/main/java/io/github/datacatering/plan/MyJSONJavaPlan.java
• Scala: src/main/scala/io/github/datacatering/plan/MyJSONPlan.scala

Make sure your class extends PlanRun.

JavaScala

import io.github.datacatering.datacaterer.java.api.PlanRun;

public class MyJSONJavaPlan extends PlanRun {
}

import io.github.datacatering.datacaterer.api.PlanRun

class MyJSONPlan extends PlanRun {
}

This class defines where we need to define all of our configurations for generating data. There are helper variables and methods defined to make it simple and easy to use.

Connection Configuration

Within our class, we can start by defining the connection properties to read/write from/to JSON.

JavaScala

var accountTask = json(
    "customer_accounts",                    //name
    "/opt/app/data/customer/account_json",  //path
    Map.of()                                //additional options
);

Additional options can be found here.

val accountTask = json(
  "customer_accounts",                    //name         
  "/opt/app/data/customer/account_json",  //path
  Map()                                   //additional options
)

Additional options can be found here.

Schema

Depending on how you want to define the schema, follow the below:

• Manual schema guide
• Automatically detect schema from the data source, you can simply enable configuration.enableGeneratePlanAndTasks(true)
• Automatically detect schema from a metadata source

Let's create a task for generating data as accounts and then generate data for transactions, which will be related to the accounts generated.

JavaScala

var accountTask = json("customer_accounts", "/opt/app/data/customer/account_json")
        .schema(
            field().name("account_id"),
            field().name("balance").type(new DecimalType(5, 2)),
            field().name("created_by"),
            field().name("open_time").type(TimestampType.instance()),
            field().name("status"),
            field().name("customer_details")
                .schema(
                    field().name("name"),
                    field().name("age").type(IntegerType.instance()),
                    field().name("city")
                )
        );

val accountTask = json("customer_accounts", "/opt/app/data/customer/account_json")
  .schema(
    field.name("account_id"),
    field.name("balance").`type`(new DecimalType(5, 2)),
    field.name("created_by"),
    field.name("open_time").`type`(TimestampType),
    field.name("status"),
    field.name("customer_details")
      .schema(
        field.name("name"),
        field.name("age").`type`(IntegerType),
        field.name("city")
      )
  )

Additional Configurations

At the end of data generation, a report gets generated that summarises the actions it performed. We can control the output folder of that report via configurations. We will also enable the unique check to ensure any unique fields will have unique values generated.

JavaScala

var config = configuration()
        .generatedReportsFolderPath("/opt/app/data/report")
        .enableUniqueCheck(true);

execute(myPlan, config, accountTask, transactionTask);

val config = configuration
  .generatedReportsFolderPath("/opt/app/data/report")
  .enableUniqueCheck(true)

execute(myPlan, config, accountTask, transactionTask)

Run

Now we can run via the script ./run.sh that is in the top level directory of the data-caterer-example to run the class we just created.

./run.sh
#input class MyJSONJavaPlan or MyJSONPlan
#after completing, let's pick an account and check the transactions for that account
account=$(head -1 docker/sample/customer/account_json/part-00000-* | sed -nr 's/.*account_id":"(.+)","balance.*/\1/p')
echo "Head account record:"
head -1 docker/sample/customer/account_json/part-00000-*
echo $account
echo "Transaction records:"
cat docker/sample/customer/transaction_json/part-0000* | grep $account

It should look something like this.

Head account record:
{"account_id":"ACC00047541","balance":445.62,"created_by":"event","open_time":"2024-03-13T00:31:38.836Z","status":"suspended","customer_details":{"name":"Joey Gaylord","age":44,"city":"Lake Jose"}}
ACC00047541
Transaction records:
{"account_id":"ACC00047541","full_name":"Joey Gaylord","amount":31.485424217447527,"time":"2023-11-07T04:50:20.875Z","date":"2023-11-07"}
{"account_id":"ACC00047541","full_name":"Joey Gaylord","amount":79.22177964401857,"time":"2024-02-01T15:15:38.289Z","date":"2024-02-01"}
{"account_id":"ACC00047541","full_name":"Joey Gaylord","amount":56.06230355456882,"time":"2024-02-29T21:42:42.473Z","date":"2024-02-29"}

Congratulations! You have now made a data generator that has simulated a real world data scenario. You can check the JsonJavaPlan.java or JsonPlan.scala files as well to check that your plan is the same.

Validation

If you want to validate data from a JSON source, follow the validation documentation found here to help guide you.