How to load data from SFTP to BigQuery
Learn how to use Airbyte to synchronize your SFTP data into BigQuery within minutes.
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How to Sync to Manually
Step 1: Set Up Google Cloud SDK
Begin by installing the Google Cloud SDK on your local machine. This will provide you with the necessary command-line tools to interact with Google Cloud services. You can download it from the [Google Cloud SDK website](https://cloud.google.com/sdk/docs/install). After installation, authenticate your session using the command `gcloud auth login`.
Step 2: Create a Google Cloud Storage Bucket
In the Google Cloud Console, navigate to the Cloud Storage section and create a new bucket. This bucket will temporarily store the data files you transfer from the SFTP server. Ensure the bucket is in the same region as your BigQuery dataset to minimize costs and latency.
Step 3: Download Data from SFTP
Use a secure method to download the required data files from the SFTP server onto your local machine. You can use command-line tools like `sftp` or `scp`. For example:
```bash
sftp user@host:/path/to/file /local/path
```
Ensure that the data files are in a format compatible with BigQuery, such as CSV, JSON, or Avro.
Step 4: Upload Data to Google Cloud Storage
Once the data files are downloaded, upload them to your Google Cloud Storage bucket. Use the `gsutil` command from the Google Cloud SDK to perform the upload:
```bash
gsutil cp /local/path/to/file gs://your-bucket-name/
```
Step 5: Prepare BigQuery Dataset and Table
In the Google Cloud Console, navigate to BigQuery and create a new dataset if one does not already exist. Within the dataset, create a table that matches the schema of the data you plan to import. Define the data types for each column carefully to avoid errors during import.
Step 6: Load Data from Cloud Storage to BigQuery
Use the BigQuery console or the `bq` command-line tool to load your data from Google Cloud Storage into BigQuery. You can do this via the following command:
```bash
bq load --source_format=CSV dataset_name.table_name gs://your-bucket-name/file.csv
```
Adjust the `--source_format` flag according to your file type, such as `NEWLINE_DELIMITED_JSON` or `AVRO`.
Step 7: Verify Data Transfer and Clean Up
After the data is loaded into BigQuery, verify the transfer by querying the table and checking for consistency and completeness. Once confirmed, clean up by deleting the temporary files from your local machine and the Google Cloud Storage bucket to free up space and reduce costs:
```bash
gsutil rm gs://your-bucket-name/file.csv
```
By following these steps, you can efficiently move data from an SFTP server to BigQuery without relying on third-party tools.