Update based on PR feedback

Author: adam-christian-software

plugins/spark/README.md

@@ -27,10 +27,10 @@ REST endpoints, and provides implementations for Apache Spark's
 
 Right now, the plugin only provides support for Spark 3.5, Scala version 2.12 and 2.13, and depends on iceberg-spark-runtime 1.9.1.
 
-The Polaris Spark client supports catalog management for both Iceberg and Delta Lake tables. It routes all Iceberg table
-requests to the Iceberg REST endpoints and routes all Delta Lake table requests to the Generic Table REST endpoints.
+The Polaris Spark client supports catalog management for both Iceberg and Delta tables. It routes all Iceberg table
+requests to the Iceberg REST endpoints and routes all Delta table requests to the Generic Table REST endpoints.
 
-The Spark Client requires at least delta 3.2.1 to work with Delta Lake tables, which requires at least Apache Spark 3.5.3.
+The Spark Client requires at least delta 3.2.1 to work with Delta tables, which requires at least Apache Spark 3.5.3.
 
 # Start Spark with local Polaris service using the Polaris Spark plugin
 The following command starts a Polaris server for local testing, it runs on localhost:8181 with default
@@ -116,16 +116,16 @@ bin/spark-shell \
 --conf spark.sql.sources.useV1SourceList=''
 ```
 
-# Limitations
+# Current Limitations
 The following describes the current limitations of the Polaris Spark client:
 
 ## General Limitations
-1. The Polaris Spark client only supports Iceberg and Delta Lake tables. It does not support other table formats like CSV, JSON, etc.
+1. The Polaris Spark client only supports Iceberg and Delta tables. It does not support other table formats like CSV, JSON, etc.
 2. Generic tables (non-Iceberg tables) do not currently support credential vending.
 
-## Delta Lake Limitations
-1. Create table as select (CTAS) is not supported for Delta Lake tables. As a result, the `saveAsTable` method of `Dataframe`
+## Delta Table Limitations
+1. Create table as select (CTAS) is not supported for Delta tables. As a result, the `saveAsTable` method of `Dataframe`
    is also not supported, since it relies on the CTAS support. 
-2. Create a Delta Lake table without explicit location is not supported. 
-3. Rename a Delta Lake table is not supported. 
+2. Create a Delta table without explicit location is not supported. 
+3. Rename a Delta table is not supported. 
 4. ALTER TABLE ... SET LOCATION is not supported for DELTA table.

plugins/spark/v3.5/getting-started/README.md

@@ -17,12 +17,12 @@
   under the License.
 -->
 
-# Getting Started with Apache Spark and Apache Polaris With Delta Lake and Iceberg
+# Getting Started with Apache Spark and Apache Polaris With Delta and Iceberg
 
 This getting started guide provides a `docker-compose` file to set up [Apache Spark](https://spark.apache.org/) with Apache Polaris using
 the new Polaris Spark Client.
 
-The Polaris Spark Client enables manage of both Delta Lake and Iceberg tables using Apache Polaris.
+The Polaris Spark Client enables manage of both Delta and Iceberg tables using Apache Polaris.
 
 A Jupyter notebook is started to run PySpark, and Polaris Python client is also installed to call Polaris APIs
 directly through Python Client.

plugins/spark/v3.5/spark/src/main/java/org/apache/polaris/spark/utils/DeltaHelper.java

@@ -29,12 +29,12 @@
 import org.slf4j.LoggerFactory;
 
 /**
- * Helper class for integrating Delta Lake table functionality with Polaris Spark Catalog.
+ * Helper class for integrating Delta table functionality with Polaris Spark Catalog.
  *
  * <p>This class is responsible for dynamically loading and configuring a Delta Catalog
  * implementation to work with Polaris. It sets up the Delta Catalog as a delegating catalog
- * extension with Polaris Spark Catalog as the delegate, enabling Delta Lake table operations
- * through Polaris.
+ * extension with Polaris Spark Catalog as the delegate, enabling Delta table operations through
+ * Polaris.
  *
  * <p>The class uses reflection to configure the Delta Catalog to behave identically to Unity
  * Catalog, as the current Delta Catalog implementation is hardcoded for Unity Catalog. This is a

site/content/in-dev/unreleased/generic-table.md

@@ -22,7 +22,7 @@ type: docs
 weight: 435
 ---
 
-The generic tables framework provides support for non-Iceberg table formats including Delta Lake, CSV, etc. With this framework, you can:
+The generic tables are non-Iceberg tables. Table can be multiple formats including Delta, CSV, etc. With this framework, you can:
 - Create a generic table under a namespace
 - Load a generic table
 - Drop a generic table
@@ -162,6 +162,6 @@ For the complete and up-to-date API specification, see the [Catalog API Spec](ht
 
 There are some known limitations for the generic table support:
 1. Generic tables provide limited spec information. For example, there is no spec for Schema or Partition. 
-2. There is no commit coordination provided by Polaris. It is the responsibility of the engine to coordinate commits.
+2. There is no commit coordination provided by Polaris. It is the responsibility of the engine to coordinate loading and committing data. The catalog is only aware of the generic table fields above.
 3. There is no update capability provided by Polaris. Any update to a generic table must be done through a drop and create.
 4. Generic tables do not support credential vending.

site/content/in-dev/unreleased/polaris-spark-client.md

@@ -119,16 +119,16 @@ If you would like to use a version of the Spark client that is currently not yet
 build a Spark client jar locally from source. Please check out the Polaris repo and refer to the Spark plugin
 [README](https://github.com/apache/polaris/blob/main/plugins/spark/README.md) for detailed instructions.
 
-## Limitations
+## Known Limitations
 The following describes the current limitations of the Polaris Spark client:
 
 ### General Limitations
-1. The Polaris Spark client only supports Iceberg and Delta Lake tables. It does not support other table formats like CSV, JSON, etc.
+1. The Polaris Spark client only supports Iceberg and Delta tables. It does not support other table formats like CSV, JSON, etc.
 2. Generic tables (non-Iceberg tables) do not currently support credential vending.
 
-### Delta Lake Limitations
-1. Create table as select (CTAS) is not supported for Delta Lake tables. As a result, the `saveAsTable` method of `Dataframe`
+### Delta Table Limitations
+1. Create table as select (CTAS) is not supported for Delta tables. As a result, the `saveAsTable` method of `Dataframe`
    is also not supported, since it relies on the CTAS support.
-2. Create a Delta Lake table without explicit location is not supported.
-3. Rename a Delta Lake table is not supported.
+2. Create a Delta table without explicit location is not supported.
+3. Rename a Delta table is not supported.
 4. ALTER TABLE ... SET LOCATION is not supported for DELTA table.