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Kafka integration for IBM Streams topology applications

Project description

Overview

Provides functions to read messages from Kafka brokers including the IBM Event Streams cloud service as a stream and submit tuples to Kafka brokers as messages.

The broker configuration must be done with properties in an application configuration or by using a dictionary variable. The minimum set of properties must contain the bootstrap.servers configuration, which is valid for both consumers and producers, i.e. for the KafkaConsumer and KafkaProducer classes.

It is also possible to use different application configurations for consumer and producer when special consumer or producer configs must be used.

Sample

A simple hello world example of a Streams application publishing to a topic and the same application consuming the same topic:

from streamsx.topology.topology import Topology
from streamsx.topology.schema import CommonSchema
from streamsx.topology.context import submit, ContextTypes
from streamsx.kafka import KafkaConsumer, KafkaProducer
import time

def delay(v):
    time.sleep(5.0)
    return True

topology = Topology('KafkaHelloWorld')

to_kafka = topology.source(['Hello', 'World!'])
to_kafka = to_kafka.as_string()
# delay tuple by tuple
to_kafka = to_kafka.filter(delay)

# Publish a stream to Kafka using TEST topic, the Kafka server is at localhost
producer = KafkaProducer(config={'bootstrap.servers': 'localhost:9092'},
                         topic='TEST')
to_kafka.for_each(producer)

# Subscribe to same topic as a stream
consumer = KafkaConsumer(config={'bootstrap.servers': 'localhost:9092'},
                         schema=CommonSchema.String,
                         topic='TEST')
from_kafka = topology.source(consumer)

# You'll find the Hello World! in stdout log file:
from_kafka.print()

submit(ContextTypes.DISTRIBUTED, topology)
# The Streams job is kept running.

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