robertcankney/kafka-connect-field-and-time-partitioner

Kafka Connect Store Partitioner by custom fields and time

Kafka Connect Field and Time Based Partitioner

Summary

• Partition initially by custom fields and then by time.

• It extends TimeBasedPartitioner, so any existing time based partition config should be fine i.e. path.format will be respected.

• In order to make it work, set "partitioner.class"="com.canelmas.kafka.connect.FieldAndTimeBasedPartitioner" and "partition.field.name"="<comma separated custom fields in your record>" in your connector config.

• Set partition.field.format.path=false if you don't want to use field labels for partitions names.

  {
      ...
      "s3.bucket.name" : "data", 
      "partition.field.name" : "appId,eventName,country",   
      "partition.field.format.path" : true,
      "path.format": "'year'=YYYY/'month'=MM/'day'=dd",
      ...
  }          

  will produce an output in the following format :

  /data/appId=XXXXX/eventName=YYYYYY/country=ZZ/year=2020/month=11/day=30

Example

KCONNECT_NODES=("localhost:18083" "localhost:28083" "localhost:38083")

for i in "${!KCONNECT_NODES[@]}"; do
    curl ${KCONNECT_NODES[$i]}/connectors -XPOST -H 'Content-type: application/json' -H 'Accept: application/json' -d '{
        "name": "connect-s3-sink-'$i'",
        "config": {     
            "topics": "events",
                "connector.class": "io.confluent.connect.s3.S3SinkConnector",
                "tasks.max" : 10,
                "flush.size": 50,
                "rotate.schedule.interval.ms": 600,
                "rotate.interval.ms": -1,
                "s3.part.size" : 5242880,
                "s3.region" : "us-east-1",
                "s3.bucket.name" : "playground-parquet-ingestion",        
                "topics.dir": "data",
                "storage.class" : "io.confluent.connect.s3.storage.S3Storage",        
                "partitioner.class": "com.canelmas.kafka.connect.FieldAndTimeBasedPartitioner",
                "partition.field.name" : "appId,eventName",
                "partition.duration.ms" : 86400000,
                "path.format": "'year'=YYYY/'month'=MM/'day'=dd",
                "locale" : "US",
                "timezone" : "UTC",        
                "format.class": "io.confluent.connect.s3.format.parquet.ParquetFormat",
                "key.converter": "org.apache.kafka.connect.storage.StringConverter",
                "value.converter": "io.confluent.connect.avro.AvroConverter",
                "value.converter.schema.registry.url": "http://schema-registry:8081",
                "schema.compatibility": "NONE",                
                "timestamp.extractor": "RecordField",
                "timestamp.field" : "clientCreationDate",
                "parquet.codec": "snappy"                            
        }
    }'
done

Installation Guide

1. Before building make sure maven and java development kit is install.
2. Firstly build the package using the following command mvn package.
3. After building the package a new jar will created in target/connect-fieldandtime-partitioner-1.1.0-SNAPSHOT.jar copy the jar file into the s3 plugin directory.
4. Restart the connector if the user use helm redeploy the helm so that it can detect the plugin.

Tips

Where is the plugin?

If the plugin was installed via confluent-hub the jar file should be copy to /usr/share/confluent-hub-components/confluentinc-kafka-connect-s3/lib/ however if kafka-connect-s3-sink was installed somewhere else place the jar file in the same directory as the connector plugin jars.