Skip to main content

IBM Streams Kafka integration

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

streamsx.kafka-1.6.0.tar.gz (21.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

streamsx.kafka-1.6.0-py2.py3-none-any.whl (24.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file streamsx.kafka-1.6.0.tar.gz.

File metadata

  • Download URL: streamsx.kafka-1.6.0.tar.gz
  • Upload date:
  • Size: 21.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.6

File hashes

Hashes for streamsx.kafka-1.6.0.tar.gz
Algorithm Hash digest
SHA256 ac4701687c0d6d0d18b6c444e30d0db7e8122bdc1f5f133cb7bd9cc42621fe1e
MD5 6bac6eb5e1b5a9ada3a3e16fad015508
BLAKE2b-256 b688b646479f9ddf8e275262768ff0dbaaf4be11ecd6f44942594a7f6d19f48c

See more details on using hashes here.

File details

Details for the file streamsx.kafka-1.6.0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for streamsx.kafka-1.6.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 e7f82c6866fcb4c5989ad93aa01aefab539b570df938a3cc7e680cbd0633d458
MD5 8ba950cc2a5743f0c6835b1139ffdcfc
BLAKE2b-256 922f48ae754fca60eb0eacbfc77326eba2e1785a98259f65ec7c4c6a094d312b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page