Big query not updating data across two days

[DenisProxy]

Hello, i have some issue with Big Query data export, it's not problem with events limits (490 thouthands)

I not got any warning messages from system, since my last reconnect with GA. And first day after reconnect was succsessful.

But after this, last two days data exports only in users table (every day), but events table not modifying.

Help me please with undersanding what it may to be

[ms4446]

Possible Issues with BigQuery Data Export:

1. Configuration Error:

   • Ensure that the connection between Google Analytics and BigQuery is properly established. Double-check the export settings, including the frequency of exports and the specific datasets targeted for export.

2. Data Delay:

   • Data export can sometimes be delayed. Refer to the BigQuery documentation to understand the typical time frames for data processing and export, especially for large datasets.

3. Sampling:

   • For standard Google Analytics properties with high data volumes, sampling might affect the completeness of exported data. Review the Google Analytics documentation on sampling, particularly if you're not using GA 360, which is less prone to significant sampling issues.

4. Permissions Issue:

   • Verify that the service account used for the BigQuery transfer has appropriate permissions, such as BigQuery Data Editor and BigQuery Job User, to write data to the destination tables.

5. Data Schema Mismatch:

   • If there have been changes in the Google Analytics data structure, ensure these are reflected in the BigQuery table schema to prevent data transfer failures.

Troubleshooting Steps:

1. Check Google Cloud Console:

   • Utilize the "Logs Explorer" in the Google Cloud console to filter for logs related to BigQuery and your transfer configuration. Look for error messages that could indicate the cause of the issue.

2. Review BigQuery Documentation:

   • Consult the BigQuery documentation for any known issues or recent updates that might impact your data export process.

3. Run a Test Export:

   • Conduct a test export with a small dataset to determine if the problem persists. Compare the exported data with the original data in Google Analytics for any discrepancies.

4. Reach Out to Google Cloud Support:

   • If the problem remains unresolved, contact Google Cloud Support with detailed information about your issue, including any relevant screenshots and logs.

Additional Resources:

• BigQuery Data Export Documentation: Exporting Data from BigQuery
• Google Analytics Help on Data Sampling: About Data Sampling

[DenisProxy]

Internal table expired, say please what it may to be?

[ms4446]

When you encounter the message "Internal table expired" in the context of a database system like Google BigQuery, it typically refers to a situation where a temporary or transient table created during query execution or data processing has expired. Here are some key points to understand about this issue:

1. Temporary Tables:

   • BigQuery and similar database systems often create temporary tables for various internal operations. These tables are used to store intermediate results during query execution or data processing tasks.

2. Expiration of Temporary Tables:

   • These temporary tables are usually set to expire after a certain period. This is to ensure efficient use of resources and to clean up unnecessary data that is no longer needed after the completion of operations.

3. Causes of Expiration:

   • The expiration message can occur if a query or operation takes too long, and the temporary table it relies on expires before the operation completes.
   • It might also happen if there's a delay in the execution pipeline, where the temporary table is created but not used immediately.

4. Impact on Operations:

   • When a temporary table expires, any operations depending on that table may fail or return incomplete results.

5. Resolution Steps:

   • Retry the Operation: Sometimes, simply retrying the operation can resolve the issue, especially if the expiration was due to temporary delays or system load.
   • Optimize Queries: If the issue is recurring, consider optimizing your queries to ensure they run more efficiently and complete before the temporary tables expire.
   • Check System Status: Ensure there are no ongoing issues with the database service that might be causing unusual delays or operational hiccups.
   • Contact Support: If the problem persists and you cannot identify a clear cause, it may be helpful to contact the support team for the database service you are using. They can provide more specific guidance and help identify if there are any underlying issues with the system.

6. Preventive Measures:

   • Regularly review and optimize queries and database operations to prevent timeouts and ensure efficient use of resources.
   • Stay informed about the best practices for using your specific database system to avoid common pitfalls that might lead to such issues.