anchor.diff:  More details about the message structure are provided in link:../../connectors[the documentation for each connector].
   
   This format allows the user to get most information about changes happening in the system.
  -The downside of using the complex format is that other connectors or other parts of Kafka ecosystem usually expects the data in a simple message format that can generally be described like
  +The downside of using the complex format is that other connectors or other parts of the Kafka ecosystem usually expect the data in a simple message format that can generally be described like so:
   
   [source,json,indent=0]
   ----
   {
  -	"field1", "newvalue1",
  -	"field2", "newvalue2"
  +	"field1" : "newvalue1",
  +	"field2" : "newvalue2"
   }
   ----
   
  -Debezium provides https://kafka.apache.org/documentation/#connect_transforms[a single message transform] that crosses the bridge between the complex and simple format https://github.com/debezium/debezium/blob/master/debezium-core/src/main/java/io/debezium/transforms/UnwrapFromEnvelope.java[UnwrapFromEnvelope] SMT.
  +Debezium provides https://kafka.apache.org/documentation/#connect_transforms[a single message transformation] that crosses the bridge between the complex and simple formats, the https://github.com/debezium/debezium/blob/master/debezium-core/src/main/java/io/debezium/transforms/UnwrapFromEnvelope.java[UnwrapFromEnvelope] SMT.
   
  -The SMT provides two main functions
  +The SMT provides two main functions.
  +It
   
  -* extracts `after` field from examples message and replace the original one with this part
  -* filters delete and tombstone records according to configuration to tune it according to downstream parts requirements
  +* extracts the `after` field from change events and replaces the original event just with this part
  +* optionally filters delete and tombstone records, as per the capabilities and requirements of downstream consumers
   
  -The SMTs can be applied either on source (Debezium) connector or on sink connector.
  -We generally recommend to apply the transformation on sink side as it means that the messages stored in Apache Kafka will contain the whole context. The final decision depends on use case for each user.
  +The SMT can be applied either to a source connector (Debezium) or a sink connector.
  +We generally recommend to apply the transformation on the sink side as it means that the messages stored in Apache Kafka will contain the whole context.
  +The final decision depends on use case for each user.
   
   == Configuration
  -The configuration is a part of source/sink task connector and is expressed in a set of properties
  +The configuration is a part of source/sink task connector and is expressed in a set of properties:
  +
   [source]
   ----
   transforms=unwrap,...
  
positive.code: 
  [NOTE]
  ====
  This SMT is supported only for SQL database plug-ins, not with MongoDB plug-in.
  ====
  
  Debezium generates a data change in a form of a complex message structure. The message consists of three parts
  
  * operation and metadata
  * the row data before change
  * the row data after change
  
  The general message structure for `update` change can look like
  
  [source,json,indent=0]
  ----
  
negative.code: ----
  
  === Record filtering for delete records
  The SMT provides a special handling for events that signals `delete` operation.
  When a `DELETE` is executed on a datasource then Debezium generates two records:
  
  * a record with `d` operation that contains only old row data
  * a record with `null` value and the same key. This record serves as a tombstone marker for Apache Kafka for https://kafka.apache.org/documentation/#compaction[a log compaction process].
  
  Upon processing these two records, the SMT turns the `d` record into another tombstone.
  The user can configure if both records, only one of them or none is filtered out.
  
  [NOTE]
  ====
  