Скачать или смотреть PySpark - How to Load BigQuery table into Spark Dataframe

In this tutorial, you will learn "How to read Google bigquery data table into PySpark dataframe?" using PySpark. To accomplish this data ingestion pipeline, we will use the following GCP Storage and #BigQuery libraries:

GCP Storage and BigQuery libraries — Some Google Python libraries can be used to authenticate your Google Cloud account and provide access to work around your GCP components, such as Google #clouds Storage and Google BigQuery datasets. You have to install these libraries in your Databricks Community Edition.
Google Cloud Access Authentication — If you are using Google Cloud functions, then there is no need to authenticate your credentials. Otherwise, you have to store them in a json file and pass them to your PySpark code.

Now, you can see that after following the demo steps together, you can read BigQuery data table by using #google Cloud Access Authentication. Your PySpark code can read your data from Google BigQuery into #pyspark dataframe.

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