I use Elasticsearch Sink connector for stream data from kafka to elasticsearch, and I have next question.

I have next structure in kafka topic document

Partition : 0 
Offset: 0
Key: 
Value: 
{
  "attributes": {
    "3": "Mike"
  }
}
Timestamp: 2022-11-03 19:03:34.866

For this data I have next index template in my elasticsearch

{
  "version": 1,
  "index_patterns": [
    "documents-*"
  ],
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "properties": {
      "id": {
        "type": "keyword"
      },
      "cashier": {
        "type": "text"
      }
    }
  }
}

And I have next configuration Elastcisearch Sink Connector

{
  "name": "elasticsearch-sink",
  "config": {
    "connector.class": "io.confluent.connect.elasticsearch.ElasticsearchSinkConnector",
    "tasks.max": "1",
    "topics": "document, document-processing-error",
    "key.ignore": "true",
    "schema.ignore": "true",
    "connection.url": "http://elasticsearch:9200",
    "type.name": "_doc",
    "name": "elasticsearch-sink",
    "key.converter": "org.apache.kafka.connect.storage.StringConverter",
    "value.converter": "org.apache.kafka.connect.json.JsonConverter",
    "value.converter.schemas.enable": "false",
    "flush.synchronously": "true",

    "transforms": "appendTimestampToIX",
    "transforms.appendTimestampToIX.type": "org.apache.kafka.connect.transforms.TimestampRouter",
    "transforms.appendTimestampToIX.topic.format": "${topic}-${timestamp}",
    "transforms.appendTimestampToIX.timestamp.format": "yyyy-MM-dd"
  }
}

In the output I have next data in my index document-2022-11-03

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 1.0,
        "hits": [
            {
                "_index": "document-2022-11-03",
                "_type": "_doc",
                "_id": "document-2022-11-03 0 0",
                "_score": 1.0,
                "_source": {
                    "attributes": {
                        "3": "Mike"
                    }
                }
            }
        ]
    }
}

This works fine, but I need extra transformation for my data, for example if in attribute I have key 3, I need to replace this field and add key cashier and mutate this structure to flat JSON with random id for document, so, in the end output I need next structure (for example)

{
    "took": 1,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 1.0,
        "hits": [
            {
                "_index": "document-2022-11-03",
                "_type": "_doc",
                "_id": "134DaBfWAE6AZUyKUAbjRksjXHTmP6hDxedGm4YhBnZW",
                "_score": 1.0,
                "_source": {
                      "cashier": "Mike"
                }
            }
        ]
    }
}

I tired use next config for replace field but this doesn't work for me

"transforms": "RenameField",
"transforms.RenameField.type": "org.apache.kafka.connect.transforms.ReplaceField$Value",
"transforms.RenameField.renames": "arrtubites.3:cashier"

How can I do this?

CodePudding user response：

ReplaceField transform does not work with nested attributes such as Maps or Objects, only top-level fields of either.

If you want to convert

{
  "attributes": {
    "3": "Mike"
  }
}

Into

{
  "cashier": "Mike"
}

Then, Kafka Streams or ksqlDB are the common recommendations (aka consume elsewhere, and produce to a new topic with the logic that you want to perform).

Logstash may also be an option instead of that Kafka Connect.