How do you load data into BigQuery from GCS?

 

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To load data into BigQuery from Google Cloud Storage (GCS),

 you use the LOAD DATA process, which supports various formats like CSV, JSON, Avro, Parquet, ORC, and Datastore backups.

You can load data using:

BigQuery Console:

Go to BigQuery UI.

Select a dataset → Click "Create Table".

In the source, choose Google Cloud Storage and provide the GCS URI (e.g., gs://bucket-name/file.csv).

Choose the file format and configure schema manually or auto-detect.

Set other options (delimiter, skip header rows, etc.).

Click "Create Table" to begin the load job.

bq command-line tool:

bash

Copy

Edit

bq load --source_format=CSV dataset.table gs://bucket-name/file.csv schema_file

Python client (BigQuery API):

Use google-cloud-bigquery library to create a LoadJobConfig and submit a load job programmatically.

Scheduled/Automated Load:

Use Cloud Composer, Cloud Functions, or Dataflow to automate loading on a schedule or trigger.

BigQuery handles schema validation and logs errors during the load.

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