Chapter 1: Introduction to Spark Stored Procedures

Google has taken a significant step by enabling the creation and execution of Spark stored procedures within BigQuery. This enhancement promotes interoperability with various platforms and frameworks.

Apache Spark is a widely-used, open-source analytics engine designed for large-scale data processing. It offers a programming interface that supports data parallelism and fault tolerance. Users can utilize languages such as Python, Scala, Java, and R for their data processing needs.

With this new feature, BigQuery now supports the creation of Spark stored procedures written in Python, Java, and Scala—though R is currently not included. This functionality is now generally available, making it viable for production environments. Users can leverage the PySpark editor in BigQuery to develop stored procedures in Python.

To execute these stored procedures in BigQuery, you can utilize a Google SQL query, much like how SQL stored procedures are executed. Google provides two methods for creating a Spark stored procedure using Python:

1. Utilize the CREATE PROCEDURE statement via the query editor.
2. Add your Python code using the PySpark editor. Once created, the stored procedure can be saved.

While in the BigQuery user interface, the options for PySpark Procedures are located under the tab for composing a new query, allowing users to begin writing Stored Procedures. Here’s a basic code snippet to get you started:

# Create procedure with main_file_uri option

CREATE PROCEDURE PROJECT_ID.DATASET.PROCEDURE_NAME(PROCEDURE_ARGUMENT)

WITH CONNECTION CONNECTION_NAME

OPTIONS (

engine="SPARK", runtime_version="RUNTIME_VERSION",

main_file_uri=["MAIN_JAR_URI"]);

LANGUAGE JAVA|SCALA

For additional details and coding examples, I recommend consulting Google’s official documentation, which is linked below. This advancement further opens BigQuery to various platforms and environments, particularly because Spark is a prevalent tool in data analytics. It could also facilitate the transition for organizations planning to migrate from Apache and Spark-based solutions to BigQuery.

Chapter 2: Learning More Through Video

In this informative video, "5. Introduction to Routines in BigQuery | Stored Procedure, User Defined Functions & Table Functions," you will gain deeper insights into how to effectively utilize routines within BigQuery, including stored procedures and user-defined functions.