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How to flatten nested JSON with ksqlDB

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How to flatten nested JSON with ksqlDB

Consider a topic containing product orders. Each order contains data about the customer and the product, specified as nested data. In this tutorial, we'll write a program that transforms each order into a new version that contains all the data as flat fields.

Setup

You have JSON data in a topic that has the following structure:

{
  "id": "1",
  "timestamp": "2020-01-18 01:12:05",
  "amount": 84.02,
  "customer": {
    "first_name": "Roberto",
    "last_name": "Smithe",
    "phone_number": "1234567899",
    "address": {
      "street": "street SDF",
      "number": "8602",
      "zipcode": "27640",
      "city": "Raleigh",
      "state": "NC"
    }
  },
  "product": {
    "sku": "P12345",
    "name": "Highly Durable Glue",
    "vendor": {
      "vendor_name": "Acme Corp",
      "country": "US"
    }
  }
}

The first step to working with this nested JSON is to create a stream over the topic and use the STRUCT keyword to define the fields that contain nested data:

CREATE STREAM orders (
    id VARCHAR,
    timestamp VARCHAR,
    amount DOUBLE,
    customer STRUCT<first_name VARCHAR,
                    last_name VARCHAR,
                    phone_number VARCHAR,
                    address STRUCT<street VARCHAR,
                                   number VARCHAR,
                                   zipcode VARCHAR,
                                   city VARCHAR,
                                   state VARCHAR>>,
    product STRUCT<sku VARCHAR,
                   name VARCHAR,
                   vendor STRUCT<vendor_name VARCHAR,
                                 country VARCHAR>>)
    WITH (KAFKA_TOPIC='orders',
          VALUE_FORMAT='JSON',
          TIMESTAMP='TIMESTAMP',
          TIMESTAMP_FORMAT='yyyy-MM-dd HH:mm:ss',
          PARTITIONS=1);

Next, create a stream that will extract the nested fields into a flat structure:

CREATE STREAM flattened_orders AS
    SELECT
        id AS order_id,
        timestamp AS order_ts,
        amount AS order_amount,
        customer->first_name AS cust_first_name,
        customer->last_name AS cust_last_name,
        customer->phone_number AS cust_phone_number,
        customer->address->street AS cust_addr_street,
        customer->address->number AS cust_addr_number,
        customer->address->zipcode AS cust_addr_zipcode,
        customer->address->city AS cust_addr_city,
        customer->address->state AS cust_addr_state,
        product->sku AS prod_sku,
        product->name AS prod_name,
        product->vendor->vendor_name AS prod_vendor_name,
        product->vendor->country AS prod_vendor_country
    FROM
        orders;

Notice the pattern of STRUCT->STRUCT->FIELD to drill down to the nested fields.

Now when you want to run query selecting certain attributes of an order you can use much simpler queries:

SELECT
    order_id,
    order_ts,
    order_amount,
    cust_first_name,
    cust_last_name,
    prod_name
FROM flattened_orders
EMIT CHANGES;

Running the example

You can run the example backing this tutorial in one of two ways: locally with the ksql CLI against Kafka and ksqlDB running in Docker, or with Confluent Cloud.

Local With Docker

Prerequisites

Run the commands

Clone the confluentinc/tutorials GitHub repository (if you haven't already) and navigate to the tutorials directory:

git clone git@github.com:confluentinc/tutorials.git
cd tutorials

Start ksqlDB and Kafka:

docker compose -f ./docker/docker-compose-ksqldb.yml up -d

Next, open the ksqlDB CLI:

docker exec -it ksqldb-cli ksql http://ksqldb-server:8088

Run the following SQL statements to create the orders stream backed by Kafka running in Docker and populate it with test data.

CREATE STREAM orders (
    id VARCHAR,
    timestamp VARCHAR,
    amount DOUBLE,
    customer STRUCT<first_name VARCHAR,
                    last_name VARCHAR,
                    phone_number VARCHAR,
                    address STRUCT<street VARCHAR,
                                   number VARCHAR,
                                   zipcode VARCHAR,
                                   city VARCHAR,
                                   state VARCHAR>>,
    product STRUCT<sku VARCHAR,
                   name VARCHAR,
                   vendor STRUCT<vendor_name VARCHAR,
                                 country VARCHAR>>)
    WITH (KAFKA_TOPIC='orders',
          VALUE_FORMAT='JSON',
          TIMESTAMP='TIMESTAMP',
          TIMESTAMP_FORMAT='yyyy-MM-dd HH:mm:ss',
          PARTITIONS=1);
INSERT INTO orders (id, timestamp, amount, customer, product)
    VALUES ('1', '2024-01-18 01:12:05', 89.99,
    STRUCT(first_name := 'Bob',
           last_name := 'Smith',
           address := STRUCT(street := 'Main',
                             number := '12',
                             zipcode := '01020',
                             city := 'Springfield',
                             state := 'MA')),
    STRUCT(sku := '87923',
           name := 'deck of cards',
           vendor := STRUCT(vendor_name := 'Best Brands',
                             country := 'US')));

INSERT INTO orders (id, timestamp, amount, customer, product)
    VALUES ('2', '2024-01-18 01:12:05', 89.99,
    STRUCT(first_name := 'Jane',
           last_name := 'Jackson',
           address := STRUCT(street := 'Conservation Way',
                             number := '81',
                             zipcode := '01020',
                             city := 'Springfield',
                             state := 'MA')),
    STRUCT(sku := '3992',
           name := 'dog leash',
           vendor := STRUCT(vendor_name := 'Petz',
                             country := 'US')));

Next, create a stream that will extract the nested fields into a flat structure. Note that we first tell ksqlDB to consume from the beginning of the stream.

SET 'auto.offset.reset'='earliest';

CREATE STREAM flattened_orders AS
    SELECT
        id AS order_id,
        timestamp AS order_ts,
        amount AS order_amount,
        customer->first_name AS cust_first_name,
        customer->last_name AS cust_last_name,
        customer->phone_number AS cust_phone_number,
        customer->address->street AS cust_addr_street,
        customer->address->number AS cust_addr_number,
        customer->address->zipcode AS cust_addr_zipcode,
        customer->address->city AS cust_addr_city,
        customer->address->state AS cust_addr_state,
        product->sku AS prod_sku,
        product->name AS prod_name,
        product->vendor->vendor_name AS prod_vendor_name,
        product->vendor->country AS prod_vendor_country
    FROM
        orders;

Now query certain flattened attributes of the orders:

SELECT
    order_id,
    order_ts,
    order_amount,
    cust_first_name,
    cust_last_name,
    prod_name
FROM flattened_orders
EMIT CHANGES;

The query output should look like this:

+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+
|ORDER_ID             |ORDER_TS             |ORDER_AMOUNT         |CUST_FIRST_NAME      |CUST_LAST_NAME       |PROD_NAME            |
+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+
|1                    |2020-01-18 01:12:05  |89.99                |Bob                  |Smith                |deck of cards        |
|2                    |2024-01-18 01:12:05  |89.99                |Jane                 |Jackson              |dog leash            |
+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+

When you are finished, exit the ksqlDB CLI by entering CTRL-D and clean up the containers used for this tutorial by running:

docker compose -f ./docker/docker-compose-ksqldb.yml down
Confluent Cloud

Prerequisites

Create Confluent Cloud resources

Login to your Confluent Cloud account:

confluent login --prompt --save

Install a CLI plugin that will streamline the creation of resources in Confluent Cloud:

confluent plugin install confluent-cloud_kickstart

Run the following command to create a Confluent Cloud environment and Kafka cluster. This will create resources in AWS region us-west-2 by default, but you may override these choices by passing the --cloud argument with a value of aws, gcp, or azure, and the --region argument that is one of the cloud provider's supported regions, which you can list by running confluent kafka region list --cloud <CLOUD PROVIDER>

confluent cloud-kickstart --name ksqldb-tutorial \
  --environment-name ksqldb-tutorial \
  --output-format stdout

Now, create a ksqlDB cluster by first getting your user ID of the form u-123456 when you run this command:

confluent iam user list

And then create a ksqlDB cluster called ksqldb-tutorial with access linked to your user account:

confluent ksql cluster create ksqldb-tutorial \
  --credential-identity <USER ID>

Run the commands

Login to the Confluent Cloud Console. Select Environments in the lefthand navigation, and then click the ksqldb-tutorial environment tile. Click the ksqldb-tutorial Kafka cluster tile, and then select ksqlDB in the lefthand navigation.

The cluster may take a few minutes to be provisioned. Once its status is Up, click the cluster name and scroll down to the editor.

In the query properties section at the bottom, change the value for auto.offset.reset to Earliest so that ksqlDB will consume from the beginning of the stream we create.

Enter the following statements in the editor and click Run query. This creates the orders stream and populates it with test data.

CREATE STREAM orders (
    id VARCHAR,
    timestamp VARCHAR,
    amount DOUBLE,
    customer STRUCT<first_name VARCHAR,
                    last_name VARCHAR,
                    phone_number VARCHAR,
                    address STRUCT<street VARCHAR,
                                   number VARCHAR,
                                   zipcode VARCHAR,
                                   city VARCHAR,
                                   state VARCHAR>>,
    product STRUCT<sku VARCHAR,
                   name VARCHAR,
                   vendor STRUCT<vendor_name VARCHAR,
                                 country VARCHAR>>)
    WITH (KAFKA_TOPIC='orders',
          VALUE_FORMAT='JSON',
          TIMESTAMP='TIMESTAMP',
          TIMESTAMP_FORMAT='yyyy-MM-dd HH:mm:ss',
          PARTITIONS=1);

INSERT INTO orders (id, timestamp, amount, customer, product)
    VALUES ('1', '2024-01-18 01:12:05', 89.99,
    STRUCT(first_name := 'Bob',
           last_name := 'Smith',
           address := STRUCT(street := 'Main',
                             number := '12',
                             zipcode := '01020',
                             city := 'Springfield',
                             state := 'MA')),
    STRUCT(sku := '87923',
           name := 'deck of cards',
           vendor := STRUCT(vendor_name := 'Best Brands',
                             country := 'US')));

INSERT INTO orders (id, timestamp, amount, customer, product)
    VALUES ('2', '2024-01-18 01:12:05', 89.99,
    STRUCT(first_name := 'Jane',
           last_name := 'Jackson',
           address := STRUCT(street := 'Conservation Way',
                             number := '81',
                             zipcode := '01020',
                             city := 'Springfield',
                             state := 'MA')),
    STRUCT(sku := '3992',
           name := 'dog leash',
           vendor := STRUCT(vendor_name := 'Petz',
                             country := 'US')));

Next, create a stream that will extract the nested fields into a flat structure.

CREATE STREAM flattened_orders AS
    SELECT
        id AS order_id,
        timestamp AS order_ts,
        amount AS order_amount,
        customer->first_name AS cust_first_name,
        customer->last_name AS cust_last_name,
        customer->phone_number AS cust_phone_number,
        customer->address->street AS cust_addr_street,
        customer->address->number AS cust_addr_number,
        customer->address->zipcode AS cust_addr_zipcode,
        customer->address->city AS cust_addr_city,
        customer->address->state AS cust_addr_state,
        product->sku AS prod_sku,
        product->name AS prod_name,
        product->vendor->vendor_name AS prod_vendor_name,
        product->vendor->country AS prod_vendor_country
    FROM
        orders;

Now query certain flattened attributes of the orders:

SELECT
    order_id,
    order_ts,
    order_amount,
    cust_first_name,
    cust_last_name,
    prod_name
FROM flattened_orders
EMIT CHANGES;

The query output should look like this:

+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+
|ORDER_ID             |ORDER_TS             |ORDER_AMOUNT         |CUST_FIRST_NAME      |CUST_LAST_NAME       |PROD_NAME            |
+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+
|1                    |2020-01-18 01:12:05  |89.99                |Bob                  |Smith                |deck of cards        |
|2                    |2024-01-18 01:12:05  |89.99                |Jane                 |Jackson              |dog leash            |
+---------------------+---------------------+---------------------+---------------------+---------------------+---------------------+

Clean up

When you are finished, delete the ksqldb-tutorial environment by first getting the environment ID of the form env-123456 corresponding to it:

confluent environment list

Delete the environment, including all resources created for this tutorial:

confluent environment delete <ENVIRONMENT ID>
Do you have questions or comments? Join us in the #confluent-developer community Slack channel to engage in discussions with the creators of this content.