Apache Spark Stored Procedures Enter BigQuery

BigQuery users can now create and run Spark stored procedures using BigQuery APIs, allowing them to extend their queries with Spark-based data processing

BigQuery data processing beyond SQL may require Spark-based business logic or Apache Spark expertise

To create, test, and implement your PySpark code, BigQuery Studio offers a Python editor as part of its unified interface for all data practitioners

After testing, the process is kept in a BigQuery dataset, and it can be accessed and controlled in the same way as your SQL procedures

BigQuery Spark stored procedures can be configured to install packages required for code execution

For data science, data engineering, and machine learning on single-node computers or clusters, Apache Spark is a multi-language engine

On a laptop, train machine learning algorithms, and then use the same code to scale to thousands of machines in fault-tolerant cluster

An advanced distributed SQL engine for large-scale data is the foundation of Apache Spark