How to load data from Parquet File to BigQuery

Learn how to use Airbyte to synchronize your Parquet File data into BigQuery within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Parquet File connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up BigQuery for your extracted Parquet File data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Parquet File to BigQuery in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

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How to Sync to Manually

Step 1: Set up Google Cloud Platform (GCP) Project

1. Go to the Google Cloud Console: https://console.cloud.google.com/

2. Create a new project or select an existing one.

3. Enable billing for the project if it's not already enabled.

1. Navigate to the "APIs & Services" dashboard.

2. Click on "+ ENABLE APIS AND SERVICES".

3. Search for "BigQuery API" and enable it for your project.

1. Go to the "IAM & Admin" section, then select "Service accounts".

2. Create a new service account with a role that has permissions to access BigQuery (e.g., BigQuery Admin).

3. Create a key for the service account in JSON format and download it.

1. Download and install the Google Cloud SDK from: https://cloud.google.com/sdk/docs/install

2. Initialize the SDK by running `gcloud init` and follow the prompts to authenticate and set your default project.

1. Ensure your Parquet files are accessible. If they are on your local machine, make sure they are in a directory that you can easily navigate to.

2. If the Parquet files are large, consider splitting them into smaller chunks to optimize the upload and import process.

1. Create a new bucket in GCS or use an existing one.

2. Use `gsutil cp` command to upload Parquet files to the bucket:

```

gsutil cp /path/to/your/parquet/files/*.parquet gs://your-bucket-name/parquet-files/

```

3. Ensure the files are successfully uploaded to the GCS bucket.

1. In the BigQuery Console, create a new dataset where you will store your imported data.

2. Define a schema for your BigQuery table that corresponds to the schema of your Parquet files. You can define the schema manually or let BigQuery auto-detect it during the import process.

1. In the BigQuery Console, navigate to your dataset.

2. Click on "CREATE TABLE", and in the source section, select "Google Cloud Storage".

3. Enter the GCS URI of your Parquet files (e.g., `gs://your-bucket-name/parquet-files/*.parquet`).

4. Choose "Parquet" as the source data format.

5. Configure the destination table with the appropriate dataset and table name.

6. (Optional) Choose the schema auto-detection if you did not define a schema in Step 7.

7. Click "Create table" to start the import process.

1. After the import process is complete, run some queries in BigQuery to ensure that the data has been imported correctly.

2. Check for any errors or warnings that might have occurred during the import process.

1. If you no longer need the Parquet files in GCS, delete them to avoid incurring storage costs.

2. Remove any unnecessary service account keys and revoke roles that are no longer needed.

By following these steps, you can move data from Parquet files to Google BigQuery without the need for third-party connectors or integrations. Remember to handle your credentials securely and to follow best practices for managing GCP resources.