Intel Granulate blogs: Spark
Cloudera vs Databricks vs Snowflake: Choosing the Right Data Management Platform for Your Needs
Dive into the world of three major players in data management: Cloudera, Databricks, and Snowflake, and discover which one is right for your...
Optimizing AI: Large-Scale Data Processing and Analytics
The second in Intel Granulate’s series, Optimizing AI, a deep dive into optimizing Large-scale Data Processing and Analytics applications for...
Spark Streaming (Spark Structured Streaming): the Basics and a Quick Tutorial
Spark Structured Streaming is a newer streaming engine that provides a declarative API, offers end-to-end fault tolerance, and supports more...
Azure Databricks: Spark on Steroids in the Azure Cloud
Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services platform.
Session Recap: Best Practices for Embracing EKS for Spark Workloads
If you missed the live session, read this recap on the best practices for embracing EKS for Spark workloads.
Pyspark Tutorial: Setup, Key Concepts, and MLlib Quick Start
PySpark is a library that lets you work with Apache Spark in Python. Apache Spark is an open-source distributed general-purpose...
Spark vs. Kafka: 5 Key Differences and How to Choose
Apache Spark is an open-source, distributed system for processing large volumes of data. Apache Kafka is an open-source, high performance...
Apache Spark: Quick Start and Tutorial
Apache Spark is an open-source, distributed computing system for big data processing. Get a full tutorial and see how to get started with Apache...
Optimizing Resource Allocation for Apache Spark
Resource allocation for Apache Spark and how you can configure and optimize your Spark environment for maximum performance.