What is the limit for loading data directly from your computer using the BigQuery web UI?
The BigQuery web UI, part of the Google Cloud Platform (GCP), provides users with a convenient and user-friendly interface for loading data directly from their computers into BigQuery. However, there are certain limitations to consider when using this method.
The limit for loading data directly from your computer using the BigQuery web UI is 10MB for uncompressed files. This means that any individual file you upload must not exceed this size. It is important to note that this limit is for uncompressed files, and if your data is compressed, it must be smaller than 10MB when uncompressed.
Additionally, there is a limit on the total size of the data you can load in a single request. The maximum size for a load job, which includes all the files being loaded, is 15TB. This means that if you have multiple files to load, the combined size of all the files must not exceed this limit.
To illustrate this, let's consider an example. If you have a CSV file that is 8MB in size, you can load it directly into BigQuery using the web UI. However, if you have a file that is 12MB, it will exceed the 10MB limit for uncompressed files and you will not be able to load it directly. In this case, you may need to consider alternative methods such as using the BigQuery command-line tool or the BigQuery API to load the data.
It is worth mentioning that these limits are specific to loading data directly from your computer using the BigQuery web UI. If you need to load larger files or datasets, there are alternative methods available, such as using Cloud Storage to stage your data before loading it into BigQuery. Cloud Storage allows you to store and manage large amounts of data, and it integrates seamlessly with BigQuery.
The limit for loading data directly from your computer using the BigQuery web UI is 10MB for uncompressed files, and the total size of the data you can load in a single request is limited to 15TB. If your data exceeds these limits, you may need to explore alternative methods such as using the BigQuery command-line tool or the BigQuery API, or consider using Cloud Storage to stage your data.
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