Purpose: The primary objective for this document is to provide awareness and establish clear understanding of coding standards and best practices to adhere while developing PySpark components. Best Practices are any procedure that is accepted as being the most effective either by consensus or prescription. Practices can range from stylistic to in-depth design methodologies. In […]
Saravanan Ponnaiah
Saravanan Ponnaiah is associated with Perficient as Solution Architect, working in Azure Cloud & Data projects. Having 16+ years of experience working in Microsoft technology platform in Banking & Financial, Insurance, and Digital Forensics domains. Has architected enterprise solutions with Azure Cloud and Data Analytics.
Blogs from this Author
Apache Spark for .Net – Kick Starter
Apache Spark: Apache Spark is a general-purpose distributed processing engine for analytics over large data sets – typically terabytes or petabytes of data. Apache Spark can be used for processing data in batches, real-time streams, machine learning and ad-hoc query. Processing tasks are distributed over a cluster of nodes and data is cached in-memory to […]
Azure Databricks – Capacity Planning for optimum Spark Cluster
Overview: Today the terminology “Data Analytics” becomes a buzz across all industries & enterprises. Every organization strongly believes Data Analytics greatly helps to get insight & accelerate the business strategies in order to grow & lead in their fast and ever-changing markets. Azure Databricks: Azure Databricks is a data analytics platform optimized for the Microsoft […]