Skip to content

MySQL

Creating a data generator for MySQL. You will build a Docker image that will be able to populate data in MySQL for the tables you configure.

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.

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.

If you already have a MySQL instance running, you can skip to this step.

MySQL Setup

Next, let's make sure you have an instance of MySQL up and running in your local environment. This will make it easy for us to iterate and check our changes.

cd docker
docker-compose up -d mysql

Permissions

Let's make a new user that has the required permissions needed to push data into the MySQL tables we want.

SQL Permission Statements 
GRANT INSERT ON <schema>.<table> TO data_caterer_user;

Following permissions are required when enabling configuration.enableGeneratePlanAndTasks(true) as it will gather metadata information about tables and columns from the below tables.

SQL Permission Statements 
GRANT SELECT ON information_schema.columns TO < user >;
GRANT SELECT ON information_schema.statistics TO < user >;
GRANT SELECT ON information_schema.key_column_usage TO < user >;

Plan Setup

Create a new Java or Scala class.

  • Java: src/main/java/io/github/datacatering/plan/MySQLJavaPlan.java
  • Scala: src/main/scala/io/github/datacatering/plan/MySQLPlan.scala

Make sure your class extends PlanRun.

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

public class MySQLJavaPlan extends PlanRun {
}

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

class MySQLPlan 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 connect to MySQL.

var accountTask = mysql(
    "customer_mysql",                                   //name
    "jdbc:mysql://host.docker.internal:3306/customer",  //url
    "root",                                             //username
    "root",                                             //password
    Map.of()                                            //optional additional connection options
)

Additional options such as SSL configuration, etc can be found here.

val accountTask = mysql(
    "customer_mysql",                                   //name
    "jdbc:mysql://host.docker.internal:3306/customer",  //url
    "root",                                             //username
    "root",                                             //password
    Map()                                               //optional additional connection options
)

Additional options such as SSL configuration, etc can be found here.

In application.conf: 

jdbc {
    customer_mysql {
        url = "jdbc:mysql://jdbc:mysql://host.docker.internal:3306/customer/customer"
        user = "root"
        password = "root"
        driver = "com.mysql.cj.jdbc.Driver"
    }
}

Schema

Let's create a task for inserting data into the customer.accounts and customer.balances tables as defined underdocker/data/sql/mysql/customer.cql. This table should already be setup for you if you followed this step.

Trimming the connection details to work with the docker-compose MySQL, we have a base MySQL connection to define the table and schema required. Let's define each field along with their corresponding data type. You will notice that the text fields do not have a data type defined. This is because the default data type is StringType which corresponds to text in MySQL.

{
    var accountTask = mysql("customer_mysql", "jdbc:mysql://host.docker.internal:3306/customer")
            .table("customer", "accounts")
            .schema(
                    field().name("account_number"),
                    field().name("amount").type(DoubleType.instance()),
                    field().name("created_by"),
                    field().name("created_by_fixed_length"),
                    field().name("open_timestamp").type(TimestampType.instance()),
                    field().name("account_status")
            );
}

val accountTask = mysql("customer_mysql", "jdbc:mysql://host.docker.internal:3306/customer")
  .table("customer", "accounts")
  .schema(
    field.name("account_number"),
    field.name("amount").`type`(DoubleType),
    field.name("created_by"),
    field.name("created_by_fixed_length"),
    field.name("open_timestamp").`type`(TimestampType),
    field.name("account_status")
  )

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

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.

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

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

Execute

To tell Data Caterer that we want to run with the configurations along with the accountTask, we have to call execute . So our full plan run will look like this.

public class MySQLJavaPlan extends PlanRun {
    {
        var accountTask = mysql("customer_mysql", "jdbc:mysql://host.docker.internal:3306/customer")
                .table("customer", "accounts")
                .schema(
                        field().name("account_number").regex("ACC[0-9]{8}").primaryKey(true),
                        field().name("amount").type(DoubleType.instance()).min(1).max(1000),
                        field().name("created_by").expression("#{Name.name}"),
                        field().name("created_by_fixed_length").sql("CASE WHEN account_status IN ('open', 'closed') THEN 'eod' ELSE 'event' END"),
                        field().name("open_timestamp").type(TimestampType.instance()).min(java.sql.Date.valueOf("2022-01-01")),
                        field().name("account_status").oneOf("open", "closed", "suspended", "pending")
                );

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

        execute(config, accountTask);
    }
}

class MySQLPlan extends PlanRun {
  val accountTask = mysql("customer_mysql", "jdbc:mysql://host.docker.internal:3306/customer")
    .table("customer", "accounts")
    .schema(
      field.name("account_number").primaryKey(true),
      field.name("amount").`type`(DoubleType).min(1).max(1000),
      field.name("created_by").expression("#{Name.name}"),
      field.name("created_by_fixed_length").sql("CASE WHEN account_status IN ('open', 'closed') THEN 'eod' ELSE 'event' END"),
      field.name("open_timestamp").`type`(TimestampType).min(java.sql.Date.valueOf("2022-01-01")),
      field.name("account_status").oneOf("open", "closed", "suspended", "pending")
    )

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

  execute(config, accountTask)
}

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 MySQLJavaPlan or MySQLPlan
#after completing
docker exec docker-mysql-1  mysql -u root "-proot" "customer" -e "SELECT COUNT(1) FROM customer.accounts; SELECT * FROM customer.accounts LIMIT 10;"

Your output should look like this.

COUNT(1)
10
id  account_number  account_status  created_by  created_by_fixed_length customer_id_int customer_id_smallint    customer_id_bigint  customer_id_decimal customer_id_real    customer_id_double  open_date   open_timestamp  last_opened_time    payload_bytes
1   0507581306  suspended   Pete Pouros event   510 NULL    NULL    NULL    NULL    NULL    NULL    2023-08-08 06:55:09 NULL    NULL
2   0998204877  pending Kraig Balistreri    event   987 NULL    NULL    NULL    NULL    NULL    NULL    2023-09-04 10:09:27 NULL    NULL
3   1491488574  pending Mrs. Ali DuBuque    event   43  NULL    NULL    NULL    NULL    NULL    NULL    2024-05-11 06:43:07 NULL    NULL
4   5209805789  suspended   Lorilee Gislason    event   975 NULL    NULL    NULL    NULL    NULL    NULL    2023-08-30 20:54:40 NULL    NULL
5   5901422604  closed  Elbert Johnston eod 369 NULL    NULL    NULL    NULL    NULL    NULL    2023-08-07 13:46:58 NULL    NULL
6   7930880350  pending Charlie McCullough  event   797 NULL    NULL    NULL    NULL    NULL    NULL    2024-02-05 15:16:46 NULL    NULL
7   8248715689  pending Mila Becker event   236 NULL    NULL    NULL    NULL    NULL    NULL    2024-06-07 08:51:29 NULL    NULL
8   8709384015  closed  Dinah Zemlak    eod 965 NULL    NULL    NULL    NULL    NULL    NULL    2024-01-14 20:58:51 NULL    NULL
9   9463221576  closed  Les Hettinger   eod 83  NULL    NULL    NULL    NULL    NULL    NULL    2023-06-27 16:05:22 NULL    NULL
10  9903967165  closed  Ms. Napoleon Walker eod 795 NULL    NULL    NULL    NULL    NULL    NULL    2023-10-07 13:42:24 NULL    NULL

Also check the HTML report, found at docker/sample/report/index.html, that gets generated to get an overview of what was executed.

Sample report

Validation

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