anchor.diff:  
   As described above, the PostgreSQL connector represents the changes to rows with events that are structured like the table in which the row exist. The event contains a field for each column value, and how that value is represented in the event depends on the PostgreSQL data type of the column. This section describes this mapping.
   
  -The following table describes how the connector maps each of the PostgreSQL data types to a _literal type_ and _semantic type_ within the events' fields. 
  -
  -Here, the _literal type_ describes how the value is literally represented using Kafka Connect schema types, namely `INT8`, `INT16`, `INT32`, `INT64`, `FLOAT32`, `FLOAT64`, `BOOLEAN`, `STRING`, `BYTES`, `ARRAY`, `MAP`, and `STRUCT`. 
  +The following table describes how the connector maps each of the PostgreSQL data types to a _literal type_ and _semantic type_ within the events' fields.
  +
  +Here, the _literal type_ describes how the value is literally represented using Kafka Connect schema types, namely `INT8`, `INT16`, `INT32`, `INT64`, `FLOAT32`, `FLOAT64`, `BOOLEAN`, `STRING`, `BYTES`, `ARRAY`, `MAP`, and `STRUCT`.
   
   The _semantic type_ describes how the Kafka Connect schema captures the _meaning_ of the field using the name of the Kafka Connect schema for the field.
   
  
positive.code: [[change-events-key]]
  ==== Change event's key
  
  For a given table, the change event's key will have a structure that contains a field for each column in the primary key (or unique key constraint) of the table at the time the event was created. 
  
  Consider a `customers` table defined in the `public` database schema:
  
  
negative.code: |n/a
  |
  
  |`REAL`
  |`FLOAT32`
  |n/a
  |
  
  |`DOUBLE PRECISION`
  |`FLOAT64`
  |n/a
  |
  