Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is designed to make data analysis fast and easy by using SQL queries to process large datasets efficiently. BigQuery is part of the Google Cloud Platform and is widely used for its ability to handle large-scale data analytics with ease.
When working with Google BigQuery, you might encounter an error message stating invalidJobTimeout. This error typically occurs when you attempt to set a timeout for a job, but the value specified is not recognized as valid by BigQuery.
The error message might look something like this:
{
"error": {
"code": 400,
"message": "Invalid job timeout",
"status": "INVALID_ARGUMENT"
}
}
The invalidJobTimeout error arises when the timeout duration specified for a BigQuery job does not conform to the expected format or exceeds the permissible limits. BigQuery requires the timeout to be specified in a specific format, typically as a duration in seconds.
To resolve the invalidJobTimeout error, follow these steps:
Ensure that the timeout is specified in seconds. For example, if you want a timeout of 5 minutes, you should set it as 300 seconds.
{
"configuration": {
"query": {
"timeoutMs": 300000
}
}
}
Consult the BigQuery documentation to ensure that your specified timeout does not exceed the maximum allowed duration for a job. Adjust the timeout accordingly if it does.
Once you have verified the format and duration, update your job configuration with the correct timeout value. This can be done through the Google Cloud Console, the BigQuery API, or the gcloud command-line tool.
By ensuring that the job timeout is specified correctly and within the allowed limits, you can avoid the invalidJobTimeout error in Google BigQuery. Always refer to the latest BigQuery API documentation for any updates on job configurations and limitations.
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