Скачать или смотреть Understanding the Query ID Uniqueness in Amazon Redshift: What You Need to Know

Discover how `Query IDs` in Amazon Redshift work, including recycling and best practices for logging to ensure data integrity.
---
This video is based on the question https://stackoverflow.com/q/69117616/ asked by the user 'Yauheni Khvainitski' ( https://stackoverflow.com/u/13153337/ ) and on the answer https://stackoverflow.com/a/69121822/ provided by the user 'Bill Weiner' ( https://stackoverflow.com/u/13350652/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Is query id unique in Redshift

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the Query ID Uniqueness in Amazon Redshift: What You Need to Know

When working with Amazon Redshift, it's essential to have a solid understanding of how query IDs function and their implications for your data management strategies. A common question arises: Are query IDs unique in Redshift? This guide delves into this concern, shedding light on query ID uniqueness, how often they change, and best practices for logging.

The Nature of Query IDs in Redshift

In Amazon Redshift, a query ID serves as an identifier for each SQL execution. As mentioned in the Redshift documentation, the query ID can be particularly useful when joining various system views, like when accessing the SVL_STORED_PROC_CALL.QUERY attribute.

Key Insights:

Query IDs are NOT Permanent: It's important to recognize that query IDs will recycle. This means that after a certain number of queries—affected by your cluster's workload—query IDs will start from scratch.

Recycling Timeframe: The exact timing for when query IDs recycle can vary based on the volume of queries being executed. Therefore, in clusters with very high query throughput, this recycling might happen more frequently.

Should You Rely Solely on Query IDs?

Given that query IDs can recycle, relying solely on query IDs for logging or joining operations can lead to complications. For instance, if you're trying to track queries over a long period, you may encounter duplicate identifiers, which could muddle your analysis.

Recommendations for Logging:

Combine Identifiers: To avoid confusion and ensure uniqueness in your logs, it is advisable to use a combination of:

Query ID: The unique identifier for each query.

Transaction ID (xid): This helps distinguish different transactions that might occur in quick succession.

Process ID (pid): This identifies the specific process that executed the query, which can help in situations where the same query is run multiple times.

Timestamp: Adding the timestamp of the execution provides a time reference, further ensuring that you can tell different queries apart even if they share the same base identifiers.

Example Structure for Logging:

By employing the combination strategy, your logging table can look something like this:

Query IDTransaction IDProcess IDTimestamp12345123678902023-01-01 12:00:0012345124678912023-01-01 12:05:00Conclusion

In conclusion, while query IDs in Amazon Redshift can be a powerful tool for identifying SQL executions, their recycling nature limits their effectiveness if used alone for long-term logging or analysis. By combining query IDs with other identifiers like xid, pid, and timestamps, you can create a robust logging system that maintains clarity and data integrity.

This strategy not only prevents ambiguity but also ensures that your analytics can be reliably performed over time. Understanding how to manage these identifiers will greatly enhance the quality of your work with Amazon Redshift.