Delay in Updating BigQuery Table from CSV File on Cloud Storage

[wojtek_sftmp]

I have a CSV file stored in Google Cloud Storage that gets regularly overwritten with a new file of the same name but containing a different amount of data. The file has around 20,000 records and is approximately 4 MB in size.

The BigQuery table is created based on this file, and data updates correctly according to the file's contents. However, I sometimes experience a delay in data synchronization between the file in Cloud Storage and the table in BigQuery. This delay lasts a few minutes, and the data seems to be updated only after another import action is triggered.

Has anyone experienced something similar or could provide some advice on reducing or eliminating these delays in the update process?

[ms4446 · Accepted solution]

It's not uncommon to experience occasional delays when synchronizing data between GCS and BigQuery, especially when using automatic update mechanisms. These delays can be caused by several factors, including the processing time of BigQuery load jobs, GCS notification latencies, and sequential handling of file updates. While BigQuery is strongly consistent, there may still be brief delays as the system processes new data.

To reduce or eliminate these delays, it's important to monitor the load job status in the Cloud Console or with the bq command-line tool to identify bottlenecks. If delays are frequent, using Cloud Functions or Pub/Sub to trigger updates more reliably can help ensure that the BigQuery load job runs immediately after file changes occur. While optimizing partitioning and clustering improves query performance, it won't reduce data loading time directly.

Additionally, implementing freshness checks, such as adding a timestamp column to track when data was last updated, can help ensure the data's accuracy and timeliness. If these delays continue or severely impact your workflow, reaching out to Google Cloud Support for further assistance may be beneficial to diagnose specific BigQuery configuration issues.

[jangemmar]

@wojtek_sftmp In addition, please take note of the limitations when you load CSV files into BigQuery from a Cloud Storage bucket:

• Your files must meet the CSV file size limits described in the load jobs limits.
• When you load CSV data, values in DATE columns must use the dash (-) separator and the date must be in the following format: YYYY-MM-DD (year-month-day).
• When you load CSV data, values in TIMESTAMP columns must use a dash (-) or slash (/) separator for the date portion of the timestamp, and the date must be in one of the following formats: YYYY-MM-DD (year-month-day) or YYYY/MM/DD (year/month/day). The hh:mm:ss (hour-minute-second) portion of the timestamp must use a colon (:) separator

I hope this helps.