[Docs] Add documentation for Row Tracking

docs/source/delta-row-tracking.md

@@ -0,0 +1,113 @@
+---
+description: Learn how <Delta> row tracking allows tracking how rows change across table versions.
+orphan: 1
+---
+
+# Use row tracking for Delta tables
+
+Row tracking allows <Delta> to track row-level lineage in a <Delta> table. When enabled on a <Delta> table, row tracking adds two new metadata fields to the table:
+
+- **Row IDs** provide rows with an identifier that is unique within the table. A row keeps the same ID whenever it is modified using a `MERGE` or `UPDATE` statement.
+
+- **Row commit versions** record the last version of the table in which the row was modified. A row is assigned a new version whenever it is modified using a `MERGE` or `UPDATE` statement.
+
+.. note:: This feature is available in <Delta> 3.2.0 and above. This feature is in experimental support mode with [_](#limitations).
+
+## Enable row tracking
+
+You must explicitly enable row tracking using one of the following methods:
+
+- **New table**: Set the table property `delta.enableRowTracking = true` in the `CREATE TABLE` command.
+
+  ```sql
+  -- Create an empty table
+  CREATE TABLE student (id INT, name STRING, age INT) TBLPROPERTIES ('delta.enableRowTracking' = 'true');
+
+  -- Using a CTAS statement
+  CREATE TABLE course_new
+  TBLPROPERTIES ('delta.enableRowTracking' = 'true')
+  AS SELECT * FROM course_old;
+
+  -- Using a LIKE statement to copy configuration
+  CREATE TABLE graduate LIKE student;
+
+  -- Using a CLONE statement to copy configuration
+  CREATE TABLE graduate CLONE student;
+```
+
+- **Existing table**: Set the table property `'delta.enableRowTracking' = 'true'` in the `ALTER TABLE` command.
+
+  ```sql
+  ALTER TABLE grade SET TBLPROPERTIES ('delta.enableRowTracking' = 'true');
+  ```
+
+- **All new tables**: Set the configuration `spark.databricks.delta.properties.defaults.enableRowTracking = true` for the current session in the `SET` command.
+
+  .. code-language-tabs::
+    ```sql
+    SET spark.databricks.delta.properties.defaults.enableRowTracking = true;
+    ```
+
+    ```python
+    spark.conf.set("spark.databricks.delta.properties.defaults.enableRowTracking", True)
+    ```
+
+    ```scala
+    spark.conf.set("spark.databricks.delta.properties.defaults.enableRowTracking", true)
+    ```
+
+.. important:: Because cloning a <Delta> table creates a separate history, the row ids and row commit versions on cloned tables do not match that of the original table.
+
+.. important:: Enabling row tracking on existing table will automatically assign row ids and row commit versions to all existing rows in the table. This process may cause multiple new versions of the table to be created and may take a long time.
+
+.. warning:: Tables created with row tracking enabled have the row tracking <Delta> table feature enabled at creation and use <Delta> writer version 7. Table protocol versions cannot be downgraded, and tables with row tracking enabled are not writeable by <Delta> clients that do not support all enabled <Delta> writer protocol table features. See [_](/versioning.md).
+
+### Row tracking storage
+
+Enabling row tracking may increase the size of the table. <Delta> stores row tracking metadata fields in hidden metadata columns in the data files. Some operations, such as insert-only operations do not use these hidden columns and instead track the row ids and row commit versions using metadata in the <Delta> log. Data reorganization operations such as `OPTIMIZE` and `REORG` cause the row ids and row commit versions to be tracked using the hidden metadata column, even when they were stored using metadata.
+
+## Read row tracking metadata fields
+
+The row ids and row commit versions metadata fields are not automatically included when reading the table. Instead, these metadata fields must be manually selected from the hidden `_metadata` column which is available for all tables in <AS>.
+
+.. code-language-tabs::
+  ```sql
+  SELECT _metadata.row_id, _metadata.row_commit_version, * FROM table_name;
+  ```
+
+  ```python
+  spark.read.table("table_name") \
+    .select("_metadata.row_id", "_metadata.row_commit_version", "*")
+  ```
+
+  ```scala
+  spark.read.table("table_name")
+    .select("_metadata.row_id", "_metadata.row_commit_version", "*")
+  ```
+
+## What is the schema of the row tracking metadata fields?
+
+Row tracking adds the following metadata fields that can be accessed when reading a table:
+
+| Column name                    | Type | Values                                                                       |
+|--------------------------------|------|------------------------------------------------------------------------------|
+| `_metadata.row_id`             | Long | The unique identifier of the row.                                            |
+| `_metadata.row_commit_version` | Long | The table version at which the row was last inserted or updated. |
+
+## Disable row tracking
+
+Row tracking can be disabled to reduce the storage overhead of the metadata fields. After disabling row tracking the metadata fields remain available, but all rows always get assigned a new id and commit version whenever they are touched by an operation.
+
+```sql
+ALTER TABLE table_name SET TBLPROPERTIES (delta.enableRowTracking = false);
+```
+
+.. important:: Disabling row tracking does not remove the corresponding table feature and does not downgrade the table protocol version.
+
+## Limitations
+
+The following limitations exist:
+
+- The row ids and row commit versions metadata fields cannot be accessed while reading the [Change data feed](/delta/delta-change-data-feed.md).
+
+.. include:: /shared/replacements.md

docs/source/index.md

@@ -26,6 +26,7 @@ This is the documentation site for <Delta>.
     delta-clustering
     delta-deletion-vectors
     delta-drop-feature
+    delta-row-tracking
     delta-apidoc
     delta-storage
     delta-uniform

docs/source/versioning.md

@@ -25,6 +25,7 @@ The following <Delta> features break forward compatibility. Features are enabled
    V2 Checkpoints, [Delta Lake 3.0.0](https://github.com/delta-io/delta/releases/tag/v3.0.0),[V2 Checkpoint Spec](https://github.com/delta-io/delta/blob/master/PROTOCOL.md#v2-spec)
    Domain metadata, [Delta Lake 3.0.0](https://github.com/delta-io/delta/releases/tag/v3.0.0),[Domain Metadata Spec](https://github.com/delta-io/delta/blob/master/PROTOCOL.md#domain-metadata)
    Clustering, [Delta Lake 3.1.0](https://github.com/delta-io/delta/releases/tag/v3.1.0),[_](/delta-clustering.md)
+   Row Tracking, [Delta Lake 3.2.0](https://github.com/delta-io/delta/releases/tag/v3.2.0),[_](/delta-row-tracking.md)
 
 <a id="table-protocol"></a>
 
@@ -105,6 +106,7 @@ The following table shows minimum protocol versions required for <Delta> feature
    Timestamp without Timezone,7,3,[TimestampNTZType](https://spark.apache.org/docs/latest/sql-ref-datatypes.html)
    Iceberg Compatibility V1,7,2,[IcebergCompatV1](https://github.com/delta-io/delta/blob/master/PROTOCOL.md#iceberg-compatibility-v1)
    V2 Checkpoints,7,3,[V2 Checkpoint Spec](https://github.com/delta-io/delta/blob/master/PROTOCOL.md#v2-spec)
+   Row Tracking,7,3,[_](/delta-row-tracking.md)
 
 <a id="upgrade"></a>