The json in kafka is a complex nested json, how to parse it and put it into clickhouse
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To parse complex nested JSON data in Kafka and insert it into ClickHouse, you can follow the steps below:
- Create a Kafka engine table to read data from Kafka. For example:
CREATE TABLE my_kafka_table (
key String,
value String
) ENGINE = Kafka()
SETTINGS kafka_broker_list = 'localhost:9092',
kafka_topic_list = 'my_topic',
kafka_format = 'JSON',
kafka_row_delimiter = '\n'
In the example above, we create a table named "my_kafka_table" to read data from Kafka.
- Create a new table to store the data read from Kafka. In the new table, you need to specify a data schema that matches the structure of the JSON data. For example, if the JSON data contains fields such as id, name, and address, you can create a new table as follows:
CREATE TABLE my_clickhouse_table (
id Int64,
name String,
address String
) ENGINE = MergeTree()
ORDER BY id
In the example above, we create a table named "my_clickhouse_table" to store the parsed JSON data. The data schema includes fields such as id, name, and address, where name and address are string types.
- Use a SELECT statement to select data from the Kafka engine table, and use the JSONExtract function to parse the JSON data. For example:
SELECT
JSONExtract(value, 'id') AS id,
JSONExtract(value, 'name') AS name,
JSONExtract(value, 'address') AS address
FROM my_kafka_table
In the example above, we use the JSONExtract function to extract the values of fields such as id, name, and address from the JSON data.
- Insert the SELECT query results into the new table. For example:
INSERT INTO my_clickhouse_table (id, name, address)
SELECT
JSONExtract(value, 'id') AS id,
JSONExtract(value, 'name') AS name,
JSONExtract(value, 'address') AS address
FROM my_kafka_table
In the example above, we insert the SELECT query results into the new table named "my_clickhouse_table".
Note that if the JSON data contains arrays, you can use the "[]" notation to specify the array index. For example, if the JSON data contains an array named "phone_numbers", you can use the following syntax to select the first element from the array:
JSONExtract(value, 'phone_numbers[1]')
In summary, by using the JSONExtract function in ClickHouse and the correct data schema, you can easily parse complex nested JSON data from Kafka and store it in ClickHouse.