# Kafka Connect ExtractField SMT Usage Reference for Confluent Cloud The `org.apache.kafka.connect.transforms.ExtractField` Apache Kafka® Single Message Transformation (SMT) extracts a single field from a complex, non-primitive key or value, such as a Map or Struct, and replaces the entire key or value with the extracted field. It passes any `null` value through unmodified. Use the concrete transformation type designed for the record key (`org.apache.kafka.connect.transforms.ExtractField$Key`) or value (`org.apache.kafka.connect.transforms.ExtractField$Value`). ## Examples The following examples show how to use `ExtractField` by itself and together with a second SMT. ### Extract field name The following configuration snippet shows how to use `ExtractField` to extract the field name `"id"`. ```json "transforms": "ExtractField", "transforms.ExtractField.type": "org.apache.kafka.connect.transforms.ExtractField$Value", "transforms.ExtractField.field": "id" ``` Before: `{"id": 42, "cost": 4000}` After: `42` ## Properties | Name | Description | Type | Default | Valid Values | Importance | |---------|------------------------|--------|-----------|----------------|--------------| | `field` | Field name to extract. | String | | | Medium | ## Chained Transformation You can use SMTs together to perform a more complex transformation. The following examples show how the `ValueToKey` and `ExtractField` SMTs are chained together to set the key for data coming from a [JDBC Connector](../../../../kafka-connect-jdbc/current/index.html). During the transform, `ValueToKey` copies the message `c1` field into the message key and then `ExtractField` extracts just the integer portion of that field. ```json "transforms": "createKey,extractInt", "transforms.createKey.type": "org.apache.kafka.connect.transforms.ValueToKey", "transforms.createKey.fields": "c1", "transforms.extractInt.type": "org.apache.kafka.connect.transforms.ExtractField$Key", "transforms.extractInt.field": "c1" ``` The following shows what the message looked like before the transform. ```none "./bin/kafka-avro-console-consumer \ --bootstrap-server localhost:9092 \ --property schema.registry.url=http://localhost:8081 \ --property print.key=true \ --from-beginning \ --topic mysql-foobar null {"c1":{"int":1},"c2":{"string":"foo"},"create_ts":1501796305000,"update_ts":1501796305000} null {"c1":{"int":2},"c2":{"string":"foo"},"create_ts":1501796665000,"update_ts":1501796665000} ``` After the connector configuration is applied, new rows are inserted (piped) into the MySQL table: ```none "echo "insert into foobar (c1,c2) values (100,'bar');"|mysql --user=username --password=pw demo ``` The following is displayed in the Avro console consumer. Note that the key (the first value on the line) matches the value of c1, which was defined with the transforms. ```none 100 {"c1":{"int":100},"c2":{"string":"bar"},"create_ts":1501799535000,"update_ts":1501799535000} ``` ## Predicates Transformations can be configured with *predicates* so that the transformation is applied only to records which satisfy a condition. You can use predicates in a transformation chain and, when combined with the [Kafka Connect Filter (Kafka) SMT Usage Reference for Confluent Cloud](filter-ak.md#ak-filter), predicates can conditionally filter out specific records. For details and examples, see [Predicates](filter-ak.md#predicates).