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Version: Python

How to write your own custom parser for Kafka

Although Deephaven has built-in support for parsing certain types of Kafka data such as JSON, you may want to write your own parser for your Kafka data. This guide will show you how to write your own Kafka data parser.

Custom function​

Writing your own custom Kafka parser starts with defining your own function. Our guide on writing Python functions covers how to do this.

For a Kafka stream, your custom function should take a single parameter that represents a single entry from the Kafka stream.

Once you have your custom function defined, you simply use a table update to create a new column containing the value of the parsed stream.

This example shows how to create a Person class containing name and age attributes derived from a binary Kafka stream of JSON strings.

from deephaven.stream.kafka import consumer as kt

from dataclasses import dataclass
import json

def get_raw_kafka():
    return kt.consume(
        { 'bootstrap.servers' : 'redpanda:29092',
          'value.deserializer': 'org.apache.kafka.common.serialization.ByteArrayDeserializer' },
        'test.topic',
        table_type=kt.TableType.Append,
        key_spec=kt.KeyValueSpec.IGNORE,
        value_spec=kt.simple_spec('Bytes'),
        offsets=kt.ALL_PARTITIONS_SEEK_TO_END,
    )

@dataclass
class Person:
    age: int
    name: str

def my_parser(raw_bytes) -> Person:
    json_object = json.loads(bytes(raw_bytes))
    return Person(age=json_object["age"], name=json_object["name"])

my_raw_table = get_raw_kafka()

my_parsed_table = my_raw_table\
    .update(["Person=(org.jpy.PyObject)my_parser(Bytes)"])\
    .view([
        "Age=(int)Person.age",
        "Name=(String)Person.name"
    ])