Скачать или смотреть Resolving bq load Errors: Handling Datetime with Milliseconds in Google BigQuery

Learn how to efficiently handle datetime formatting issues in Google BigQuery when using `bq load`, especially for milliseconds.
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Resolving bq load Errors: Handling Datetime with Milliseconds in Google BigQuery

When working with Google BigQuery, you may encounter various issues with data loading, particularly with datetime formats. A common problem arises when your data contains datetime fields with milliseconds, resulting in errors during the loading process. Understanding how to troubleshoot and resolve these errors is crucial for maintaining smooth data operations.

The Problem: Datetime with Milliseconds

Imagine you have a CSV file structured like this:

[[See Video to Reveal this Text or Code Snippet]]

When trying to load this data into BigQuery using the bq load command, you might receive an error specifically related to the IssuedDate column due to the presence of milliseconds in its format.

Your Command

The command you might have used would look something like this:

[[See Video to Reveal this Text or Code Snippet]]

As straightforward as this process seems, the presence of milliseconds in your datetime fields can lead to complications. Unfortunately, BigQuery does not provide options to control or change the date formats during the bq load process.

The Solution: Using STRING and PARSE_DATETIME

While it’s frustrating that you cannot directly specify datetime formats in the bq load command, there’s a workaround that can save the day. Here’s how to resolve the issue:

Step 1: Load Datetime as STRING

Instead of trying to load the IssuedDate as a datetime, you should load it as a STRING data type. You can do this by adjusting your data schema accordingly when executing your load command.

Step 2: Postprocess with PARSE_DATETIME

After successfully loading the data, you can convert the STRING back to a DATETIME type using the PARSE_DATETIME function provided by BigQuery. Here’s how you can do this:

Example Code

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Code

%Y-%m-%d %H:%M:%E*S: This is the format string that indicates the layout of your datetime data. Here, %E*S handles the fractional seconds (the milliseconds).

'2014-07-04 14:43:41.963000000': This is the datetime string that you want to parse.

By following these steps, you’ll not only resolve the loading error but also ensure that your datetime data is formatted correctly for future queries and analyses.

Conclusion

Handling datetime fields with milliseconds in Google BigQuery can be challenging, especially when using bq load. By treating such fields as STRING during loading and applying PARSE_DATETIME for conversion after the fact, you can effectively manage and utilize your datetime data without running into errors. Remember, though it may require an extra step, this approach keeps your workflow efficient and your data reliable.

If you have further questions or if you encounter any challenges, feel free to reach out for assistance. Happy querying!