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
- Support for reading XML 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
git clone https://github.com/streamthoughts/kafka-connect-file-pulse.git
cd kafka-connect-file-pulse
You can build kafka-connect-file-pulse with Maven using standard lifecycle.
mvn clean package
Connector will be package into an archive file compatible with confluent-hub client :
./connect-file-pulse-plugin/target/components/packages/streamthoughts-kafka-connect-file-pulse-plugin-<FILEPULSE_VERSION>.zip
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
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
(output)
...
{"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
(output)
{"hostname":"f51d45f96ed5","status":"SCHEDULED","metadata":{"name":"kafka-connect.log","path":"/var/log/kafka","size":172559,"lastModified":1560772525000,"inode":1705406,"hash":661976312},"offset":{"position":-1,"rows":0,"timestamp":1560772525527}}
{"hostname":"f51d45f96ed5","status":"STARTED","metadata":{"name":"kafka-connect.log","path":"/var/log/kafka","size":172559,"lastModified":1560772525000,"inode":1705406,"hash":661976312},"offset":{"position":-1,"rows":0,"timestamp":1560772525719}}
{"hostname":"f51d45f96ed5","status":"READING","metadata":{"name":"kafka-connect.log","path":"/var/log/kafka","size":172559,"lastModified":1560772525000,"inode":1705406,"hash":661976312},"offset":{"position":174780,"rows":1911,"timestamp":1560772535322}}
...
5 ) Stop all containers
docker-compose down
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
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