streamsx.kafka 1.3.0

IBM Streams Kafka integration

Overview

Provides functions to read messages from a Kafka broker as a stream and submit tuples to a Kafka broker 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 subscribe and publish functions.

It is also possible to use different application configurations for subscribe and publish 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
import streamsx.kafka as kafka
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 servers
# assuming, the broker is running on localhost, port 9092
kafka_props = {}
kafka_props['bootstrap.servers'] = 'localhost:9092'
kafka.publish(to_kafka, 'TEST', kafka_props)

# Subscribe to same topic as a stream
from_kafka = kafka.subscribe(topology, 'TEST', kafka_props, CommonSchema.String)

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

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

Documentation

• streamsx.kafka package documentation