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Update managed-io.md for release 2.74.0-RC1#38527

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Update managed-io.md for release 2.74.0-RC1#38527
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updates_managed_io_docs_2.74.0_rc1

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@Abacn Abacn commented May 18, 2026

Content generated from release 2.74.0-RC1.

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Summary of Changes

Hello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request updates the Managed IO documentation for the Apache Beam 2.74.0-RC1 release. The changes primarily involve adding new configuration options for various IO connectors and correcting existing documentation to accurately reflect the current capabilities and parameter requirements for supported databases and services.

Highlights

  • Documentation Updates: Updated the managed-io.md documentation to reflect changes for the 2.74.0-RC1 release, including new configuration options and corrected table definitions.
  • Configuration Additions: Added new configuration parameters such as autosharding, distribution_mode, and sort_fields to various IO connectors to improve flexibility and performance.
  • Connector Refactoring: Reorganized and corrected the documentation for SQLSERVER, BIGQUERY, MYSQL, and POSTGRES connectors to ensure accuracy regarding supported parameters and read/write operations.
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Code Review

This pull request updates the Managed IO documentation by adding new configuration parameters for Iceberg, such as autosharding, distribution_mode, and sort_fields. It also reorganizes the sections for Kafka, BigQuery, and various JDBC connectors to improve the structure. The review feedback highlights several opportunities to improve documentation quality, including replacing placeholder 'n/a' descriptions with meaningful content, ensuring consistent formatting for bootstrap servers, restoring missing schema details for Kafka, and fixing potential HTML rendering issues within table cells by using explicit line breaks.

</td>
<td>
A list of host/port pairs to use for establishing the initial connection to the Kafka cluster. The client will make use of all servers irrespective of which servers are specified here for bootstrapping—this list only impacts the initial hosts used to discover the full set of servers. | Format: host1:port1,host2:port2,...
A list of host/port pairs to use for establishing the initial connection to the Kafka cluster. The client will make use of all servers irrespective of which servers are specified here for bootstrapping—this list only impacts the initial hosts used to discover the full set of servers. This list should be in the form `host1:port1,host2:port2,...`
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medium

The description format for bootstrap_servers here is inconsistent with the one used in the KAFKA Write section (line 590). It is better to use a consistent format across the documentation.

Suggested change
A list of host/port pairs to use for establishing the initial connection to the Kafka cluster. The client will make use of all servers irrespective of which servers are specified here for bootstrapping—this list only impacts the initial hosts used to discover the full set of servers. This list should be in the form `host1:port1,host2:port2,...`
A list of host/port pairs to use for establishing the initial connection to the Kafka cluster. The client will make use of all servers irrespective of which servers are specified here for bootstrapping—this list only impacts the initial hosts used to discover the full set of servers. | Format: host1:port1,host2:port2,...

</td>
<td>
The encoding format for the data stored in Kafka. Valid options are: RAW,JSON,AVRO,PROTO
n/a
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medium

The description for the required field topic is "n/a". This should be updated with a meaningful description.

Suggested change
n/a
The Kafka topic to read from.

</td>
<td>
If the redistribute is using offset deduplication mode.
n/a
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medium

The description for the required field topic is "n/a". This should be updated with a meaningful description.

Suggested change
n/a
The Kafka topic to write to.

</td>
<td>
The schema in which the data is encoded in the Kafka topic. For AVRO data, this is a schema defined with AVRO schema syntax (https://avro.apache.org/docs/1.10.2/spec.html#schemas). For JSON data, this is a schema defined with JSON-schema syntax (https://json-schema.org/). If a URL to Confluent Schema Registry is provided, then this field is ignored, and the schema is fetched from Confluent Schema Registry.
n/a
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medium

The description for schema has been replaced with "n/a", which is a regression from the previous version. It should be restored to provide necessary context for users.

Suggested change
n/a
The schema in which the data is encoded in the Kafka topic. For AVRO data, this is a schema defined with AVRO schema syntax (https://avro.apache.org/docs/1.10.2/spec.html#schemas). For JSON data, this is a schema defined with JSON-schema syntax (https://json-schema.org/). If a URL to Confluent Schema Registry is provided, then this field is ignored, and the schema is fetched from Confluent Schema Registry.

Comment on lines +834 to +836
Defines distribution of write data. Supported distributions:
- none: don't shuffle rows (default)
- hash: shuffle rows by partition key before writing data
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medium

The markdown list inside the HTML <td> tag might not render correctly because it lacks proper indentation and line breaks. For consistency with other entries in this file, consider using <br> for line breaks and ensuring the list items are indented.

Suggested change
Defines distribution of write data. Supported distributions:
- none: don't shuffle rows (default)
- hash: shuffle rows by partition key before writing data
Defines distribution of write data. Supported distributions:<br>
- none: don't shuffle rows (default)<br>
- hash: shuffle rows by partition key before writing data

Comment on lines +902 to +903
Fields used to set the table's sort order, applied when the table is created. Each entry has the form `<term> [asc|desc] [nulls first|nulls last]`, where `<term>` is a field name or one of the partition transforms (e.g. `bucket(col, 4)`, `day(ts)`). Direction defaults to ascending; null order defaults to nulls-first for ascending and nulls-last for descending. Note: this sets the table's declared sort order as metadata; it does not cause Beam to physically sort records before writing.
For more information on sort orders, please visit https://iceberg.apache.org/spec/#sort-orders.
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medium

There is a raw newline between the description and the link. This can cause rendering issues within an HTML table cell in some markdown processors. Consider using a <br> and maintaining consistent indentation.

Suggested change
Fields used to set the table's sort order, applied when the table is created. Each entry has the form `<term> [asc|desc] [nulls first|nulls last]`, where `<term>` is a field name or one of the partition transforms (e.g. `bucket(col, 4)`, `day(ts)`). Direction defaults to ascending; null order defaults to nulls-first for ascending and nulls-last for descending. Note: this sets the table's declared sort order as metadata; it does not cause Beam to physically sort records before writing.
For more information on sort orders, please visit https://iceberg.apache.org/spec/#sort-orders.
Fields used to set the table's sort order, applied when the table is created. Each entry has the form `<term> [asc|desc] [nulls first|nulls last]`, where `<term>` is a field name or one of the partition transforms (e.g. `bucket(col, 4)`, `day(ts)`). Direction defaults to ascending; null order defaults to nulls-first for ascending and nulls-last for descending. Note: this sets the table's declared sort order as metadata; it does not cause Beam to physically sort records before writing.<br>
For more information on sort orders, please visit https://iceberg.apache.org/spec/#sort-orders.

@@ -1076,17 +1104,6 @@ For more information on table properties, please visit https://iceberg.apache.or
n/a
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medium

The description for the required field jdbc_url is "n/a". This should be updated with a meaningful description.

Suggested change
n/a
Connection URL for the JDBC sink.

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