qzyu999 commented on code in PR #3424:
URL: https://github.com/apache/fluss/pull/3424#discussion_r3598231434


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website/docs/streaming-lakehouse/integrate-data-lakes/catalogs/glue.md:
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@@ -0,0 +1,411 @@
+---
+title: AWS Glue
+sidebar_position: 2
+---
+
+# AWS Glue
+
+## Introduction
+
+[AWS Glue](https://aws.amazon.com/glue/) is a serverless data integration 
service that includes a central metadata repository known as the AWS Glue Data 
Catalog. The Glue Data Catalog is compatible with Apache Iceberg, making it a 
convenient option for managing Iceberg table metadata on AWS.
+
+This guide explains how to configure Fluss to use AWS Glue as its Iceberg 
catalog. For general Iceberg integration details (table mapping, data types, 
limitations), see [Iceberg](../formats/iceberg.md).
+
+## How It Works
+
+When Fluss is configured with AWS Glue as its Iceberg catalog:
+
+1. **Data ingestion**: Applications write data to Fluss tables using the Fluss 
client (Java/Python), Flink SQL, or any Kafka-compatible producer. Fluss stores 
this data in its real-time log (similar to Kafka topics).
+2. **Tiering to Iceberg**: A separate Flink job (the [tiering 
service](maintenance/tiered-storage/lakehouse-storage.md#start-the-datalake-tiering-service))
 periodically reads accumulated data from Fluss, converts it to Parquet format, 
writes the files to S3, and commits an Iceberg snapshot to the Glue Data 
Catalog.
+3. **Query via Athena/Spark/Trino**: Any Iceberg-compatible engine can 
discover and query the tiered tables through AWS Glue — no additional 
configuration needed.

Review Comment:
   Hi @leekeiabstraction, added union read section in the Usage Example (see 
"Query Data with Flink (Union Read)"). Also added a NOTE clarifying that PK 
table union reads are not yet supported with Iceberg per @fresh-borzoni's 
feedback (c0af314f).



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