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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