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Data Ingestion with Python Cookbook
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With the connection tested and SparkSession configured, the next step is to ingest the data from PostgreSQL, filter it, and save it in an analytical format called a Parquet file. Don’t worry about how Parquet files work for now; we will cover it in the following chapters.
This recipe aims to use the connection we created with our JDBC database and ingest the data from the world_population
table.
This recipe will use the same dataset and code as the Configuring a JDBC connection recipe to connect to the PostgreSQL database. Ensure your Docker container is running or your PostgreSQL server is up.
This recipe continues from the content presented in Configuring a JDBC connection. We will now learn how to ingest the data inside the Postgres database.
Following on from our previous code, let’s read the data in our database as follows:
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