Apache Spark™ 3.5 and Databricks Runtime 14.0 have brought an exciting feature to the table: Python user-defined table functions (UDTFs). In this blog...

In Apache Spark™, Python User-Defined Functions (UDFs) are among the most popular features. They empower users to craft custom code tailored to their...

There are many factors in a PySpark program's performance. PySpark supports various profiling tools to expose tight loops of your program and allow...

In Apache Spark™, declarative Python APIs are supported for big data workloads. They are powerful enough to handle most common use cases. Furthermore...

At Databricks, nothing makes us happier than making our users more productive, which is why we are delighted to announce a native adapter...

At Databricks, we strive to provide a world-class development experience for data scientists and engineers, and new features are constantly getting added to...

Koalas is an open source project which provides a drop-in replacement for pandas, enabling efficient scaling out to hundreds of worker nodes for...

Koalas was first introduced last year to provide data scientists using pandas with a way to scale their existing big data workloads by...

This is a guest community post from Haejoon Lee, a software engineer at Mobigen in South Korea and a Koalas contributor. pandas is...

Try this notebook in Databricks Apache Spark 2.4 introduces 29 new built-in functions for manipulating complex types (for example, array type), including higher-order...