:page-aliases: configuration/event-flattening.adoc
// Category: debezium-using
// Type: assembly
// ModuleID: extracting-source-record-after-state-from-debezium-change-events
// Title: Extracting source record `after` state from {prodname} change events
[id="new-record-state-extraction"]
= New Record State Extraction

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ifdef::community[]
[NOTE]
====
This single message transformation (SMT) is supported for only the SQL database connectors. For the MongoDB connector, see the xref:{link-mongodb-event-flattening}[documentation for the MongoDB equivalent to this SMT].
====
endif::community[]

A {prodname} data change event has a complex structure that provides a wealth of information. Kafka records that convey {prodname} change events contain all of this information.
However, parts of a Kafka ecosystem might expect Kafka records that provide a flat structure of field names and values.
To provide this kind of record, {prodname} provides the event flattening single message transformation (SMT). Configure this transformation when consumers need Kafka records that have a format that is simpler than Kafka records that contain {prodname} change events.

The event flattening transformation is a
link:https://kafka.apache.org/documentation/#connect_transforms[Kafka Connect SMT].

ifdef::product[]
This transformation is available to only SQL database connectors.

The following topics provide details:

* xref:description-of-debezium-change-event-structure[]
* xref:behavior-of-debezium-event-flattening-transformation[]
* xref:configuration-of-debezium-event-flattening-transformation[]
* xref:example-of-adding-debezium-metadata-to-the-kafka-record[]
* xref:options-for-configuring-debezium-event-flattening-transformation[]
endif::product[]

// Type: concept
// ModuleID: description-of-debezium-change-event-structure
// Title: Description of {prodname} change event structure
== Change event structure

{prodname} generates data change events that have a complex structure.
Each event consists of three parts:

* Metadata, which includes but is not limited to:

** The operation that made the change
** Source information such as the names of the database and table where the change was made
** Time stamp for when the change was made
** Optional transaction information

* Row data before the change
* Row data after the change

For example, part of the structure of an `UPDATE` change event looks like this:

[source,json,indent=0]
----
{
	"op": "u",
	"source": {
		...
	},
	"ts_ms" : "...",
	"before" : {
		"field1" : "oldvalue1",
		"field2" : "oldvalue2"
	},
	"after" : {
		"field1" : "newvalue1",
		"field2" : "newvalue2"
	}
}
----

ifdef::community[]
More details about change event structure are provided in
xref:{link-connectors}[the documentation for each connector].
endif::community[]

This complex format provides the most information about changes happening in the system.
However, other connectors or other parts of the Kafka ecosystem usually expect the data in a simple format like this:

[source,json,indent=0]
----
{
	"field1" : "newvalue1",
	"field2" : "newvalue2"
}
----

To provide the needed Kafka record format for consumers, configure the event flattening SMT.

// Type: concept
// ModuleID: behavior-of-debezium-event-flattening-transformation
// Title: Behavior of {prodname} event flattening transformation
[[event-flattening-behavior]]
== Behavior

The event flattening SMT extracts the `after` field from a {prodname} change event in a Kafka record. The SMT replaces the original change event with only its `after` field to create a simple Kafka record.

You can configure the event flattening SMT for a {prodname} connector or for a sink connector that consumes messages emitted by a {prodname} connector. The advantage of configuring event flattening for a sink connector is that records stored in Apache Kafka contain whole {prodname} change events. The decision to apply the SMT to a source or sink connector depends on your particular use case.

You can configure the transformation to do any of the following:

* Add metadata from the change event to the simplified Kafka record. The default behavior is that the SMT does not add metadata.

* Keep Kafka records that contain change events for `DELETE` operations in the stream. The default behavior is that the SMT drops Kafka records for `DELETE` operation change events because most consumers cannot yet handle them.

A database `DELETE` operation causes {prodname} to generate two Kafka records:

* A record that contains `"op": "d",` the `before` row data, and some other fields.
* A tombstone record that has the same key as the deleted row and a value of `null`. This record is a marker for Apache Kafka. It indicates that
link:{link-kafka-docs}/#compaction[log compaction] can remove all records that have this key.

Instead of dropping the record that contains the `before` row data, you can configure the event flattening SMT to do one of the following:

* Keep the record in the stream and edit it to have only the `"value": "null"` field.

* Keep the record in the stream and edit it to have a `value` field that contains the key/value pairs that were in the `before` field with an added `"__deleted": "true"` entry.

Similary, instead of dropping the tombstone record, you can configure the event flattening SMT to keep the tombstone record in the stream.

// Type: concept
// ModuleID: configuration-of-debezium-event-flattening-transformation
// Title: Configuration of {prodname} event flattening transformation
== Configuration

Configure the {prodname} event flattening SMT in a Kafka Connect source or sink connector by adding the SMT configuration details to your connector's configuration. To obtain the default behavior, in a `.properties` file, you would specify something like the following:

[source]
----
transforms=unwrap,...
transforms.unwrap.type=io.debezium.transforms.ExtractNewRecordState
----

As with any Kafka Connect connector configuration, you can set `transforms=` to multiple, comma-separated, SMT aliases in the order in which you want Kafka Connect to apply the SMTs.

The following `.properties` example sets several event flattening SMT options:

[source]
----
transforms=unwrap,...
transforms.unwrap.type=io.debezium.transforms.ExtractNewRecordState
transforms.unwrap.drop.tombstones=false
transforms.unwrap.delete.handling.mode=rewrite
transforms.unwrap.add.fields=table,lsn
----

`drop.tombstones=false`:: Keeps tombstone records for `DELETE` operations in the event stream.

`delete.handling.mode=rewrite`:: For `DELETE` operations, edits the Kafka record by flattening the `value` field that was in the change event. The `value` field directly contains the key/value pairs that were in the `before` field. The SMT adds `__deleted` and sets it to `true`, for example:
+
[source,json,indent=0]
----
"value": {
  "pk": 2,
  "cola": null,
  "__deleted": "true"
}
----

`add.fields=table,lsn`:: Adds change event metadata for the `table` and `lsn` fields to the simplified Kafka record.

.Customizing the configuration
The connector might emit many types of event messages (heartbeat messages, tombstone messages, or metadata messages about transactions or schema changes).
To apply the transformation to a subset of events, you can define xref:options-for-applying-the-transformation-selectively[an SMT predicate statement that selectively applies the transformation] to specific events only.

// Type: concept
// ModuleID: example-of-adding-debezium-metadata-to-the-kafka-record
// Title: Example of adding {prodname} metadata to the Kafka record
== Adding metadata

The event flattening SMT can add original, change event metadata to the simplified Kafka record. For example, you might want the simplified record's header or value to contain any of the following:

* The type of operation that made the change
* The name of the database or table that was changed
* Connector-specific fields such as the Postgres LSN field

ifdef::community[]
For more information on what is available see xref:{link-connectors}[the documentation for each connector].
endif::community[]

To add metadata to the simplified Kafka record's header, specify the `add.headers` option.
To add metadata to the simplified Kafka record's value, specify the `add.fields` option.
Each of these options takes a comma separated list of change event field names. Do not specify spaces. When there are duplicate field names, to add metadata for one of those fields, specify the struct as well as the field. For example:

----
transforms=unwrap,...
transforms.unwrap.type=io.debezium.transforms.ExtractNewRecordState
transforms.unwrap.add.fields=op,table,lsn,source.ts_ms
transforms.unwrap.add.headers=db
transforms.unwrap.delete.handling.mode=rewrite
----

With that configuration, a simplified Kafka record would contain something like the following:

[source,json,indent=0]
----
{
 ...
	"__op" : "c",
	"__table": "MY_TABLE",
	"__lsn": "123456789",
	"__source_ts_ms" : "123456789",
 ...
}
----

Also, simplified Kafka records would have a `__db` header.

In the simplified Kafka record, the SMT prefixes the metadata field names with a double underscore. When you specify a struct, the SMT also inserts an underscore between the struct name and the field name.

To add metadata to a simplified Kafka record that is for a `DELETE` operation, you must also configure `delete.handling.mode=rewrite`.

// Type: concept
// Title: Options for applying the event flattening transformation selectively
// ModuleID: options-for-applying-the-event-flattening-transformation-selectively
[id="options-for-applying-the-event-flattening-transformation-selectively"]
== Options for applying the event-flattening transformation selectively

In addition to the change event messages that a {prodname} connector emits when a database change occurs, the connector also emits other types of messages, including heartbeat messages, and metadata messages about schema changes and transactions.
Because the structure of these other messages differs from the structure of the change event messages that the SMT is designed to process, it's best to configure the connector to selectively apply the SMT, so that it processes only the intended data change messages.

For more information about how to apply the SMT selectively, see xref:{link-smt-predicates}#applying-transformation-selectively[Configure an SMT predicate for the transformation].

ifdef::community[]
[id="configuration-options"]
endif::community[]

// Type: reference
// ModuleID: options-for-configuring-debezium-event-flattening-transformation
// Title: Options for configuring {prodname} event flattening transformation
== Configuration options

The following table describes the options that you can specify to configure the event flattening SMT.

.Descriptions of event flattening SMT configuration options
[cols="30%a,25%a,45%a",subs="+attributes",options="header"]
|===
|Option
|Default
|Description

|[[extract-new-record-state-drop-tombstones]]xref:{link-event-flattening}#extract-new-record-state-drop-tombstones[`drop.tombstones`]
|`true`
|{prodname} generates a tombstone record for each `DELETE` operation. The default behavior is that event flattening SMT removes tombstone records from the stream. To keep tombstone records in the stream, specify `drop.tombstones=false`.

[id="extract-new-record-state-delete-handling-mode"]
|xref:{link-event-flattening}#extract-new-record-state-delete-handling-mode[`delete.handling{zwsp}.mode`]
|`drop`
|{prodname} generates a change event record for each `DELETE` operation. The default behavior is that event flattening SMT removes these records from the stream. To keep Kafka records for `DELETE` operations in the stream, set `delete.handling.mode` to `none` or `rewrite`. +
 +
Specify `none` to keep the change event record in the stream. The record contains only `"value": "null"`.  +
 +
Specify `rewrite` to keep the change event record in the stream and edit the record to have a `value` field that contains the key/value pairs that were in the `before` field and also add `+__deleted: true+` to the `value`. This is another way to indicate that the record has been deleted. +
 +
When you  specify `rewrite`, the updated simplified records for `DELETE` operations might be all you need to track deleted records. You can consider accepting the default behavior of dropping the tombstone records that the {prodname} connector creates.

[id="extract-new-record-state-route-by-field"]
|xref:{link-event-flattening}#extract-new-record-state-route-by-field[`route.by.field`]
|
|To use row data to determine the topic to route the record to, set this option to an `after` field attribute. The SMT routes the record to the topic whose name matches the value of the specified `after` field attribute. For a `DELETE` operation, set this option to a `before` field attribute. +
 +
For example, configuration of `route.by.field=destination` routes records to the topic whose name is the value of `after.destination`. The default behavior is that a {prodname} connector sends each change event record to a topic whose name is formed from the name of the database and the name of the table in which the change was made. +
 +
If you are configuring the event flattening SMT on a sink connector, setting this option might be useful when the destination topic name dictates the name of the database table that will be updated with the simplified change event record. If the topic name is not correct for your use case, you can configure `route.by.field` to re-route the event.

[id="extract-new-record-state-add-fields-prefix"]
|xref:{link-event-flattening}#extract-new-record-state-add-fields-prefix[`add.fields.prefix`]
| __ (double-underscore)
|Set this optional string to prefix a field.

[id="extract-new-record-state-add-fields"]
|xref:{link-event-flattening}#extract-new-record-state-add-fields[`add.fields`]
|
|Set this option to a comma-separated list, with no spaces, of metadata fields to add to the simplified Kafka record's value. When there are duplicate field names, to add metadata for one of those fields, specify the struct as well as the field, for example `source.ts_ms`. +
 +
Optionally, you can override the field name via `<field name>:<new field name>`, e.g. like so: new field name like `version:VERSION, connector:CONNECTOR, source.ts_ms:EVENT_TIMESTAMP`. Please note that the `new field name` is case-sensitive. +
 +
When the SMT adds metadata fields to the simplified record's value, it prefixes each metadata field name with a double underscore. For a struct specification, the SMT also inserts an underscore between the struct name and the field name. +
 +
If you specify a field that is not in the change event record, the SMT still adds the field to the record's value.

[id="extract-new-record-state-add-headers-prefix"]
|xref:{link-event-flattening}#extract-new-record-state-add-headers-prefix[`add.headers.prefix`]
| __ (double-underscore)
|Set this optional string to prefix a header.

[id="extract-new-record-state-add-headers"]
|xref:{link-event-flattening}#extract-new-record-state-add-headers[`add.headers`]
|
|Set this option to a comma-separated list, with no spaces, of metadata fields to add to the header of the simplified Kafka record. When there are duplicate field names, to add metadata for one of those fields, specify the struct as well as the field, for example `source.ts_ms`. +
 +
Optionally, you can override the field name via `<field name>:<new field name>`, e.g. like so: new field name like `version:VERSION, connector:CONNECTOR, source.ts_ms:EVENT_TIMESTAMP`. Please note that the `new field name` is case-sensitive. +
 +
When the SMT adds metadata fields to the simplified record's header, it prefixes each metadata field name with a double underscore. For a struct specification, the SMT also inserts an underscore between the struct name and the field name. +
 +
If you specify a field that is not in the change event record, the SMT does not add the field to the header.
|===
