metrics: add DML rows affected metric

[wk989898]

What problem does this PR solve?

Issue Number: ref #3889

What is changed and how it works?

• New DML Rows Affected Metric: Introduced ExecDMLEventRowsAffectedCounter to track the number of rows affected by DML operations (insert, update, delete) in the sink, providing granular insights into data changes.
• Grafana Dashboard Integration: Added a new panel named "Sink Event Row Affected Count / s" to the ticdc_new_arch.json, ticdc_new_arch_next_gen.json, and ticdc_new_arch_with_keyspace_name.json Grafana dashboards to visualize this new metric, enhancing monitoring capabilities.
• Enhanced DML Tracking Logic: Modified the DML preparation and execution logic in mysql_writer_dml.go to record both actual and expected affected rows for each DML type, leveraging a new rowTypes field in preparedDMLs.
• Statistics Module Update: The pkg/metrics/statistics.go file now includes dedicated functions (RecordTotalRowsAffected and RecordRowsAffected) to accurately record these new row affected metrics, ensuring comprehensive data collection.

Check List

Tests

• Unit test
• Integration test
• Manual test (add detailed scripts or steps below)
• No code

Questions

Will it cause performance regression or break compatibility?

Do you need to update user documentation, design documentation or monitoring documentation?

Release note

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[gemini-code-assist]

Summary of Changes

Hello @wk989898, 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 enhances TiCDC's monitoring capabilities by introducing a new metric that precisely tracks the number of rows affected by Data Manipulation Language (DML) operations as they are flushed to the downstream system. This provides critical insights into the volume and type of data changes being replicated, improving observability and enabling more accurate performance analysis of the data synchronization process. The new metric is also integrated into the existing Grafana dashboards for immediate visualization.

Highlights

• New DML Rows Affected Metric: Introduced ExecDMLEventRowsAffectedCounter to track the number of rows affected by DML operations (insert, update, delete) in the sink, providing granular insights into data changes.
• Grafana Dashboard Integration: Added a new panel named "Sink Event Row Affected Count / s" to the ticdc_new_arch.json, ticdc_new_arch_next_gen.json, and ticdc_new_arch_with_keyspace_name.json Grafana dashboards to visualize this new metric, enhancing monitoring capabilities.
• Enhanced DML Tracking Logic: Modified the DML preparation and execution logic in mysql_writer_dml.go to record both actual and expected affected rows for each DML type, leveraging a new rowTypes field in preparedDMLs.
• Statistics Module Update: The pkg/metrics/statistics.go file now includes dedicated functions (RecordTotalRowsAffected and RecordRowsAffected) to accurately record these new row affected metrics, ensuring comprehensive data collection.

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[gemini-code-assist]

Code Review

This pull request introduces a new metric, ticdc_sink_dml_event_affected_row_count, to monitor the number of rows affected by DML operations in the sink. The changes are well-implemented, including the definition of the new Prometheus counter, the logic in the MySQL sink to track DML row types, and the recording of both expected and actual affected row counts. The Grafana dashboards have also been updated to visualize this new metric. I have a couple of suggestions for pkg/sink/mysql/mysql_writer_dml.go to improve code maintainability and cleanliness.

[gemini-code-assist]

Many SQL generation functions in this file, such as this one, now return three separate slices: []string, [][]interface{}, and []common.RowType. This makes the function signatures complex and harder to maintain. To improve code clarity, consider encapsulating these related values into a struct. For example:

type dmlGroup struct {
    sqls     []string
    values   [][]interface{}
    rowTypes []common.RowType
}

This would simplify function signatures to something like func (w *Writer) generateBatchSQL(...) *dmlGroup. You could even potentially reuse or adapt the existing preparedDMLs struct for this purpose, which would further improve consistency.

[gemini-code-assist]

This commented-out code appears to be a remnant from development and should be removed to keep the codebase clean.