Add import stats to import summary

[vish-cs]

Add import stats to ImportStatusSummary for easily tracking metrics
Add DataVolume field to spanner ImportStatus table
Minor clean up

[gemini-code-assist]

Summary of Changes

Hello @vish-cs, 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 significantly enhances the monitoring and diagnostic capabilities of the import executor. By introducing a dedicated ObservabilityData structure and integrating its population throughout the import workflow, it now captures detailed metrics on data processing, execution times, and row counts for each stage. This enhancement provides a clearer, more granular view of import performance and status, facilitating better debugging and operational insights without cluttering the main execution logic.

Highlights

• New ObservabilityData Dataclass: Introduced a new ObservabilityData dataclass to centralize the collection of import metrics, including data sizes, row counts, and execution times for various processing stages.
• Enhanced Metric Collection and Reporting: Detailed metrics such as source data size, MCF data size, validation data size, number of rows processed, and execution times for script, MCF generation, and validation stages are now collected and used for comprehensive logging and status reporting.
• Centralized GCS Upload Skip Logic: The logic to conditionally skip GCS uploads has been centralized within the _upload_file_helper function, simplifying conditions across different parts of the import process.
• Streamlined Main Execution Logic: The main.py file has been simplified by removing redundant time tracking and final status logging, as these responsibilities are now handled by the import_executor.py module using the new observability features.

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[gemini-code-assist]

Code Review

This pull request introduces observability data collection to the import executor by adding an ObservabilityData dataclass to track metrics like data sizes and execution times. While enhancing observability is a valuable goal, the current implementation has some significant issues. The use of a global variable for state is problematic and, more critically, it is not reset between executions, which will lead to incorrect metrics. Additionally, there is a lack of error handling when parsing a report file, which could cause the import process to crash. I have provided specific comments and suggestions to address these concerns.