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IntegrateGuru
Advocate I
Advocate I

Methods for handling the asynchronous nature of the SQL Endpoint?

The SQL Analytics endpoint is asynchronous to the underlying lakhouse data. For example, you can retrieve 'old' and 'new' data rows that are inserted to a delta table from a copy-data pipeline activity, when using the 'overwrite' option. It is pretty easy to see this for yourself if you do a lookup on a table directly after a copy-data pipeline activity. Eventually the endpoint will catch up and none of the 'old' data will be returned.

Does anyone have any methods for getting data out of a sql endpoint while being able to deterministically identify that the data is accurate and up to date, outside of 'just wait and hope you wait long enough' or 'don't trust the sql endpoint'?

Are there any plans to enhance the current capabilites or create tools to identify if the endpoint is currently performing data operations? 

1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hi @IntegrateGuru ,

Ensuring that data retrieved from a SQL Analytics endpoint is accurate and up-to-date can be challenging due to its asynchronous nature. Here are a few methods and best practices that might help:

 

1. Add timestamp columns to your tables to track when rows are inserted or updated. This can help you identify the most recent data.

2. Use an event-driven architecture where your data pipeline emits events when data is successfully loaded. Your application can listen for these events and only query the data once it receives a confirmation event.

 

Of course you can also refer to this document for more information: How Do I Measure Endpoint Security Effectiveness? - Palo Alto Networks

 

 

Best Regards

Yilong Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

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1 REPLY 1
Anonymous
Not applicable

Hi @IntegrateGuru ,

Ensuring that data retrieved from a SQL Analytics endpoint is accurate and up-to-date can be challenging due to its asynchronous nature. Here are a few methods and best practices that might help:

 

1. Add timestamp columns to your tables to track when rows are inserted or updated. This can help you identify the most recent data.

2. Use an event-driven architecture where your data pipeline emits events when data is successfully loaded. Your application can listen for these events and only query the data once it receives a confirmation event.

 

Of course you can also refer to this document for more information: How Do I Measure Endpoint Security Effectiveness? - Palo Alto Networks

 

 

Best Regards

Yilong Zhou

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

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