Merge pull request #286635 from Albertyang0/2024_09-Monthly-broken-links-fix-jianleishen

2024_09 - Fix monthly broken links - jianleishen

Author: prmerger-automator[bot]

articles/data-factory/data-flow-troubleshoot-connector-format.md

@@ -240,7 +240,7 @@ You use Azure PostgreSQL as a source or sink in the data flow such as previewing
 If you use the flexible server or Hyperscale (Citus) for your Azure PostgreSQL server, since the system is built via Spark upon Azure Databricks cluster, there's a limitation in Azure Databricks blocks our system to connect to the Flexible server or Hyperscale (Citus). You can review the following two links as references.
 - [Handshake fails trying to connect from Azure Databricks to Azure PostgreSQL with SSL](/answers/questions/170730/handshake-fails-trying-to-connect-from-azure-datab.html)
 
-- [MCW-Real-time-data-with-Azure-Database-for-PostgreSQL-Hyperscale](https://github.com/microsoft/MCW-Real-time-data-with-Azure-Database-for-PostgreSQL-Hyperscale/blob/master/Hands-on%20lab/HOL%20step-by%20step%20-%20Real-time%20data%20with%20Azure%20Database%20for%20PostgreSQL%20Hyperscale.md)<br/>
+- MCW-Real-time-data-with-Azure-Database-for-PostgreSQL-Hyperscale<br/>
     Refer to the content in the following picture in this article：<br/>
 
     :::image type="content" source="./media/data-flow-troubleshoot-connector-format/handshake-failure-cause-2.png" alt-text="Screenshot that shows the referring content in the article above.":::

articles/data-factory/format-avro.md

@@ -117,7 +117,7 @@ The below table lists the properties supported by an avro sink. You can edit the
 ## Data type support
 
 ### Copy activity
-Avro [complex data types](https://avro.apache.org/docs/current/spec.html#schema_complex) are not supported (records, enums, arrays, maps, unions, and fixed) in Copy Activity.
+Avro complex data types are not supported (records, enums, arrays, maps, unions, and fixed) in Copy Activity.
 
 ### Data flows
 When working with Avro files in data flows, you can read and write complex data types, but be sure to clear the physical schema from the dataset first. In data flows, you can set your logical projection and derive columns that are complex structures, then auto-map those fields to an Avro file.

articles/data-factory/supported-file-formats-and-compression-codecs-legacy.md

@@ -530,7 +530,7 @@ To use Avro format in a Hive table, you can refer to [Apache Hive's tutorial](ht
 
 Note the following points:
 
-* [Complex data types](https://avro.apache.org/docs/current/spec.html#schema_complex) are not supported (records, enums, arrays, maps, unions, and fixed).
+* Complex data types are not supported (records, enums, arrays, maps, unions, and fixed).
 
 ## <a name="compression-support"></a> Compression support (legacy)