google-big-queryHow do I use Google Big Query Storage?

Google BigQuery Storage is a cloud-based data storage system that can store and query petabytes of data. It is a fully managed, serverless, and cost-effective data warehouse. It provides a secure, reliable, and high-performance environment for storing and querying data.

To use BigQuery Storage, you must first create a BigQuery dataset. This can be done using the BigQuery web UI, the BigQuery command-line tool, or the BigQuery API. After creating a dataset, you can then upload data to BigQuery Storage. Data can be uploaded in CSV, JSON, Avro, or Parquet formats.

Once the data is uploaded, you can query the data using SQL-like syntax. For example, the following code queries a BigQuery dataset to find the average age of people in the dataset:

SELECT AVG(age)
FROM `mydataset.mytable`

The output of the query would be the average age of people in the dataset.

You can also use BigQuery Storage to store and query large datasets. For example, the following code stores a large dataset in BigQuery Storage:

bq load --source_format=CSV mydataset.mytable gs://mybucket/mydata.csv

The above code stores the data from the file mydata.csv in the Google Cloud Storage bucket mybucket into the BigQuery dataset mydataset.

BigQuery Storage provides a secure, reliable, and cost-effective environment for storing and querying large datasets. It is a great choice for data storage and analysis.

Helpful links

• BigQuery Documentation
• BigQuery Storage Pricing

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