streamsx.kafka 0.1.0

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. 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 from streamsx.topology.context import ContextTypes import streamsx.kafka as kafka import time

def delay (v):

time.sleep (5.0) return True

topo = Topology(‘KafkaHelloWorld’)

to_kafka = topo.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 # (bootstrap.servers) are configured in the application configuration ‘kafka_props’. kafka.publish (to_kafka, ‘TEST’, ‘kafka_props’)

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

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

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

Documentation

• streamsx.kafka package documentation <http://streamsxkafka.readthedocs.io/en/pypackage/>