MapReduce is a data-parallelization framework for processing big-data applications on large suites of computers. The system attempts to decrease interprocess communication by moving computation toward data. Spark is an open-source cluster-computing framework. It uses in-memory primitives to accelerate computation.

The session will focus on Azure services and related products like MapReduce, Apache Spark, Azure HDInsight, Azure Synapse Serverless Spark Pool & Azure Databricks

In this workshop we will take a deep dive in distributed computing with Azure Big data services.

Further Learning : https://aka.ms/ComputingonthecloudSpark-LM-12/2

Speaker : Shivam Sharma

Speaker BIO- Shivam is an author, cloud architect, speaker, and Co-Founder at TechScalable. Being passionate about ever evolving technology he works on Azure, GCP, Machine Learning, Kubernetes & DevOps. He is also a Microsoft Certified Trainer. He architects’ solutions on Cloud as well on-premises using wide array of platforms/technologies.

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