Support multi-clusters active-active data consistent checker

[Leavrth]

What problem does this PR solve?

Issue Number: close #4244

What is changed and how it works?

This PR introduces a consistency validation tool for multi-cluster active-active TiCDC deployments. It connects to each cluster’s PD(etcd) and S3 sink, verifies critical changefeed settings (for example canal-json, date-separator=day, and expected file index width), then continuously watches checkpoints and sink files to advance a unified time window across clusters. Within each window, the checker compares local writes and replicated records by primary key and timestamp to detect anomalies such as missing data, redundant data, out-of-order updates, and LWW violations. The recorder persists checkpoints and reports atomically, so the process is resumable after failures and suitable for long-running, auditable consistency monitoring.

Check List

Tests

• Unit test
• Integration test
• Manual test (add detailed scripts or steps below)

Questions

Will it cause performance regression or break compatibility?

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

Release note

None

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[gemini-code-assist]

Summary of Changes

Hello @Leavrth, 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 introduces a robust multi-cluster-consistency-checker tool designed to ensure data integrity across distributed TiCDC environments. It provides a comprehensive framework for monitoring active-active replication scenarios by consuming and analyzing data from S3 sinks. The tool systematically identifies potential data discrepancies, such as loss, redundancy, and LWW violations, offering critical insights into the health of multi-cluster setups.

Highlights

• New Tool Introduction: A new command-line tool, multi-cluster-consistency-checker, has been introduced to monitor and verify data consistency across multiple TiCDC clusters.
• Consistency Checking Logic: The tool includes sophisticated logic to detect data loss, data redundancy, and Last-Write-Wins (LWW) violations by comparing data streams from different clusters within defined time windows.
• S3 Data Consumption: It features a Consumer component capable of discovering and downloading schema and DML files from S3 sinks, and a TableParser to process CSV data into structured records.
• Dynamic Checkpoint Monitoring: The CheckpointWatcher and S3Watcher components enable dynamic monitoring of changefeed checkpoints in etcd and S3, ensuring checks are performed on up-to-date data.
• Configurable Operation: The checker is highly configurable via a TOML file, allowing users to specify log levels, report directories, tables to monitor, and details for each cluster involved in the consistency check.

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Code Review

This pull request introduces a new tool, multi-cluster-consistency-checker, to verify data consistency across multiple TiCDC clusters. A security audit identified two medium-severity information exposure vulnerabilities: the exposure of S3 credentials in initialization output and the logging of full database records (potentially containing PII or secrets) at the Error level when inconsistencies are detected. Recommendations include masking credentials in URIs and reducing the log level or detail for database records. Furthermore, critical issues were found regarding capturing loop variables in goroutines, which could lead to race conditions and incorrect behavior. There are also opportunities to improve code maintainability by refactoring duplicated logic in the checker and fixing a minor issue in the configuration parsing.

[Leavrth]

closed by #4246