Introduction When working with complex data, you often come across nested JSON structures that are stored in a single column. These nested structures can be difficult to analyze in their raw form, so flattening the JSON column becomes essential for data preparation. Dataflows in Microsoft Fabric provide a powerful way...
Introduction In distributed computing environments like Apache Spark, efficient data handling is critical for performance. One useful feature for optimizing computations is broadcast variables. Broadcast variables allow you to share large read-only data across all nodes in a Spark cluster without duplicating the data for each task. In this tutorial,...
Introduction Microsoft Fabric offers a gallery of sample datasets that can be used to perform and practice Real-Time Analytics. These sample data sets offer a great opportunity to gain experience and familiarize yourself with the technologies and services in the Real-Time Intelligence Experience. In this tutorial we will show you...
Introduction In this tutorial, we will explore how to read a Delta table into a PySpark DataFrame. Goal A Delta table stored in a lakehouse should be read into a PySpark DataFrame. Prequestisies ☑️ Notebook created We have already created the notebook "dlnerds_notebook". If you want to know...
Introduction In this tutorial, we will walk through the steps required to write a PySpark DataFrame to a Delta table in Microsoft Fabric. We'll start by creating an example DataFrame, then demonstrate how to write it to a Delta table. Goal An example PySpark DataFrame should be created...
Introduction In this tutorial, we will show you how to get a randomly sampled subset of a PySpark DataFrame. In order to do this, we will use the sample() function of PySpark. What is the sample() Function? The sample() function in PySpark is used to create a new DataFrame by...
Introduction In Microsoft Fabric, there are several activities that can be added to a data pipeline. One import activity is the Notebook activity. In this tutorial, we will explain step-by-step how to add a Notebook activity to a data pipeline using the Data Factory user interface. Goal A CSV File...
Introduction In this tutorial, we will show you how to concatenate multiple string columns of a PySpark DataFrame into a single column. In order to do this, we will use the functions concat() and concat_ws() of PySpark. Import Libraries First, we import the following python modules: from pyspark.sql...
Introduction In this tutorial, we will show you how to remove the leading and trailing whitespaces from a string column of a PySpark DataFrame. In order to do this, we will use the functions trim(), ltrim() and rtrim() of PySpark. Import Libraries First, we import the following python modules: from...