Intel®️ Tiber™️ App-Level Optimization blogs: Spark
Hadoop with Hive: Is Hive Still Relevant? 2024 Guide
Hive-Hadoop integration lets users leverage Hadoop’s scalability and efficiency while using familiar SQL syntax to interact with data.
Apache Spark Architecture Simplified
Apache Spark’s architecture handles large-scale data processing. It uses a central coordinator known as the Spark Driver and distributed...
PySpark vs. Spark: 7 Key Differences and How to Choose
Apache Spark is a unified engine for large-scale data processing. PySpark is its Python API, allowing Python programmers to leverage Spark's...
Spark Security: Top Vulnerabilities and 6 Ways to Secure Your Spark
Apache Spark security includes methodologies, tools, and best practices to protect Spark applications and data from unauthorized access, theft,...
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 Tiber App-Level Optimization’s series, Optimizing AI, a deep dive into optimizing Large-scale Data Processing and...
Spark Streaming: Use Cases, Benefits, Architecture, and 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.