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Multi-purpose source connector to stream input files into Kafka
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Connect File Pulse

License CircleCI

Connect File Pulse is a multi-purpose Kafka Connect (source) for streaming files from a local filesystem to Kafka.


Data is frequently exported, shared and integrated between legacy systems, either in near-real time or daily through the use of files. These files can be in a wide variety of formats such as CSV, XML, JSON, Avro, etc. A modern approach is to decouple these systems by distributing these files in Kafka.

Connect File Pulse is a simple solution to easily integrate any type of data into a centralized Apache Kafka platform and distribute it across your organization.

Connect File Pulse is inspired by the features provided by Elasticsearch and Logstash.


  • Recursively scan local directories
  • Reading and writing files into Kafka line by line
  • Support for reading Avro files
  • Parsing and transforming data using built-in or custom filters
  • Error handler definition
  • Monitoring files while they are being written into Kafka
  • Plugeable strategies for cleaning completed files
  • At-least-once guarantee


If you want to read about using Connect File Pulse, the documentation can be found on GitHub Page

Getting Started


Download, Build & Package Connector

git clone
cd kafka-connect-file-pulse

You can build kafka-connect-file-pulse with Maven using standard lifecycle.

mvn clean package

Install Connector Using Confluent Hub

Connector will be package into an archive file compatible with confluent-hub client :



Start Docker Environment

1 ) Run Confluent Platforms with Connect File Pulse

docker-compose build
docker-compose up -d

2 ) Check for Kafka Connect

docker logs --tail="all" -f connect"

3 ) Verify that Connect File Pulse plugin is correctly loaded

curl -sX GET http://localhost:8083/connector-plugins | grep FilePulseSourceConnector

Example : Logs Parsing (Log4j)

This example starts a new connector instance to parse the Kafka Connect container log4j logs before writing them into a configured topic.

1 ) Start a new connector instance

curl -sX POST http://localhost:8083/connectors \
-d @config/connect-file-pulse-quickstart-log4j.json \
--header "Content-Type: application/json" | jq

2 ) Check connector status

curl -X GET http://localhost:8083/connectors/connect-file-pulse-quickstart-log4j | jq

3 ) Consume output topics

docker exec -it -e KAFKA_OPTS="" connect kafka-avro-console-consumer --topic connect-file-pulse-quickstart-log4j --from-beginning --bootstrap-server broker:29092 --property schema.registry.url=http://schema-registry:8081


{"loglevel":{"string":"INFO"},"logdate":{"string":"2019-06-16 20:41:15,247"},"message":{"string":"[main] Scanning for plugin classes. This might take a moment ... (org.apache.kafka.connect.cli.ConnectDistributed)"}}
{"loglevel":{"string":"INFO"},"logdate":{"string":"2019-06-16 20:41:15,270"},"message":{"string":"[main] Loading plugin from: /usr/share/java/schema-registry (org.apache.kafka.connect.runtime.isolation.DelegatingClassLoader)"}}
{"loglevel":{"string":"INFO"},"logdate":{"string":"2019-06-16 20:41:16,115"},"message":{"string":"[main] Registered loader: PluginClassLoader{pluginLocation=file:/usr/share/java/schema-registry/} (org.apache.kafka.connect.runtime.isolation.DelegatingClassLoader)"}}
{"loglevel":{"string":"INFO"},"logdate":{"string":"2019-06-16 20:41:16,115"},"message":{"string":"[main] Added plugin 'org.apache.kafka.common.config.provider.FileConfigProvider' (org.apache.kafka.connect.runtime.isolation.DelegatingClassLoader)"}}

4) Observe Connect status

Connect File Pulse use an internal topic to track the current state of files being processing.

docker exec -it -e KAFKA_OPTS="" connect kafka-console-consumer --topic connect-file-pulse-status --from-beginning --bootstrap-server broker:29092



5 ) Stop all containers

docker-compose down

Example : CSV File Parsing

This example starts a new connector instance that parse a CSV file and filter rows based on column's values before writing record into Kafka.

1 ) Start a new connector instance

curl -sX POST http://localhost:8083/connectors \
-d @config/connect-file-pulse-quickstart-csv.json \
--header "Content-Type: application/json" | jq

2 ) Copy example csv file into container

docker exec -it connect mkdir -p /tmp/kafka-connect/examples
docker cp examples/quickstart-musics-dataset.csv connect://tmp/kafka-connect/examples/quickstart-musics-dataset.csv

3 ) Check connector status

curl -X GET http://localhost:8083/connectors/connect-file-pulse-quickstart-csv | jq

4 ) Check for task completion

docker logs --tail="all" -f connect | grep "Orphan task detected"

5 ) Consume output topics

docker exec -it connect kafka-avro-console-consumer --topic connect-file-pulse-quickstart-csv --from-beginning --bootstrap-server broker:29092 --property schema.registry.url=http://schema-registry:8081


Any feedback, bug reports and PRs are greatly appreciated! See our guideline


Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License

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