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WIP: resolve bigquery cache datetime format issue #331

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@aaronsteers aaronsteers commented Aug 9, 2024

Reported in slack:

Log from repro in new "example" script:

google.api_core.exceptions.BadRequest: 400 Error while reading data, error message: JSON table encountered too many errors, giving up. Rows: 1; errors: 1. Please look into the errors[] collection for more details.; reason: invalid, message: Error while reading data, error message: JSON table encountered too many errors, giving up. Rows: 1; errors: 1. Please look into the errors[] collection for more details.; reason: invalid, message: Error while reading data, error message: JSON processing encountered too many errors, giving up. Rows: 1; errors: 1; max bad: 0; error percent: 0; reason: invalid, message: Error while reading data, error message: JSON parsing error in row starting at position 0: Couldn't convert value to timestamp: Could not parse '2020-10-22T21:03:23.000+0000' as a timestamp. Required format is YYYY-MM-DD HH:MM[:SS[.SSSSSS]] or YYYY/MM/DD HH:MM[:SS[.SSSSSS]] Field: createddate; Value: 2020-10-22T21:03:23.000+0000

BigQuery expects a colon in timezone part: +00:00 instead of +0000.

Summary by CodeRabbit

  • New Features
    • Introduced a script for transferring data securely from Salesforce to Google BigQuery using the Airbyte framework.
    • Added functionality for caching data during the transfer process, ensuring smooth data migration.
    • Enhanced reporting with stream names and record counts for better data visibility.
    • Added a new script specifically for facilitating data migration from Salesforce to a BigQuery destination.

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coderabbitai bot commented Aug 9, 2024

Walkthrough

Walkthrough

The new scripts run_salesforce_to_bigquery_cache.py and run_salesforce_to_bigquery_destination.py enhance the data migration process from Salesforce to Google BigQuery using the Airbyte framework. They securely manage credentials and configurations, facilitate data extraction, and optimize performance through caching. This implementation improves integration capabilities while ensuring sensitive information is handled securely and efficiently.

Changes

File Change Summary
examples/run_salesforce_to_bigquery_cache.py Introduced a script for transferring data from Salesforce to BigQuery with secure credential management and data caching.
examples/run_salesforce_to_bigquery_destination.py Added a script to facilitate direct migration from Salesforce to BigQuery, managing credentials securely and optimizing data writing through Airbyte.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant Salesforce
    participant BigQuery
    participant Airbyte
    participant SecretManager

    User->>SecretManager: Request Credentials
    SecretManager-->>User: Provide Salesforce and BigQuery Credentials
    User->>Airbyte: Initiate Data Transfer
    Airbyte->>Salesforce: Fetch Source Configuration
    Airbyte->>Salesforce: Validate Configuration
    Airbyte->>Salesforce: Retrieve Data Streams
    Airbyte->>BigQuery: Create Temporary Credential File
    Airbyte->>BigQuery: Initialize Cache
    Airbyte->>Salesforce: Read Data Streams
    Airbyte->>BigQuery: Cache Data
    Airbyte->>User: Provide Data Transfer Summary
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Does this summary and the table effectively capture the changes made? Let me know if you'd like to adjust anything!


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@aaronsteers aaronsteers changed the title wip: resolve bigquery cache datetime format issue WIP: resolve bigquery cache datetime format issue Aug 10, 2024
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Actionable comments posted: 0

Outside diff range, codebase verification and nitpick comments (1)
examples/run_salesforce_to_bigquery_destination.py (1)

1-5: Consider updating the usage comment.

The usage comment references run_salesforce_to_bigquery_cache.py, but this file is run_salesforce_to_bigquery_destination.py. Should this be updated to reflect the correct script name? Wdyt?

-    poetry run python examples/run_salesforce_to_bigquery_cache.py
+    poetry run python examples/run_salesforce_to_bigquery_destination.py

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