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Apache Spark Training

Apache Spark Training

Welcome to KONCPT AI’s 5-day Apache Spark Training program! This intensive course offers a deep dive into Spark fundamentals, architecture, programming, and advanced topics. Through lectures, hands-on exercises, and real-world applications, participants will gain expertise in using Spark as a unified analytics engine for large-scale data processing in corporate projects.

Description

Welcome to the 5-day Apache Spark Training program by KONCPT AI. This intensive Corporate training is designed to provide participants with a thorough understanding of Apache Spark, an open-source unified analytics engine for large-scale data processing. This course covers Spark fundamentals, architecture, programming, and advanced topics through a combination of lectures, hands-on exercises, and real-world applications.

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Course Content


Introduction to Apache Spark

  1. Overview of Big Data and Apache Spark
  2. The evolution of Apache Spark
  3. Apache Spark ecosystem and components
  4. Installing and setting up Spark
  5. Spark architecture and execution model
  6. Introduction to RDDs (Resilient Distributed Datasets)
  7. Basic operations on RDDs
  8. Hands-on exercises: Setting up a Spark environment
  9. Introduction to Spark Shell
  10. Key use cases for Apache Spark

Spark Programming with RDDs

  1. Deep dive into RDDs
  2. Transformations and actions
  3. Lazy evaluation and lineage
  4. Key-Value Pair RDDs
  5. Data partitioning and persistence
  6. Advanced RDD operations (joins, groupBy, aggregations)
  7. Hands-on exercises: Programming with RDDs
  8. Fault tolerance in Spark
  9. Performance tuning for RDDs
  10. Best practices for RDD usage

Spark SQL and DataFrames

  1. Introduction to Spark SQL
  2. The Catalyst optimizer
  3. DataFrames and Datasets
  4. Creating DataFrames and Datasets
  5. Transformations and actions on DataFrames
  6. SQL queries with Spark SQL
  7. Hands-on exercises: Working with DataFrames and Spark SQL
  8. Integrating Spark SQL with external data sources
  9. Performance tuning for Spark SQL
  10. Use cases for Spark SQL and DataFrames

Spark Streaming and Structured Streaming

  1. Introduction to Spark Streaming
  2. DStream abstraction and operations
  3. Fault tolerance and checkpointing
  4. Windowed computations and stateful transformations
  5. Structured Streaming overview
  6. Programming with Structured Streaming
  7. Hands-on exercises: Developing streaming applications with Spark
  8. Integrating Spark Streaming with Kafka and other data sources
  9. Performance tuning for streaming applications
  10. Use cases for Spark Streaming and Structured Streaming

Advanced Spark Topics and Real-World Applications

  1. Machine Learning with Spark MLlib
  2. Building machine learning models with Spark
  3. Graph processing with GraphX
  4. Running Spark on YARN, Mesos, and Kubernetes
  5. Spark deployment and cluster management
  6. Hands-on exercises: Advanced Spark applications
  7. Monitoring, debugging, and tuning Spark applications
  8. Case studies and industry examples
  9. Building a complete big data pipeline with Spark
  10. Future trends and developments in Apache Spark


Contact us

By the end of this 5-day training program, participants will have a comprehensive understanding of Apache Spark and be equipped to build, manage, and optimize Spark applications for various big data processing needs. Join us at KONCPT AI to advance your Spark skills and unlock new opportunities in big data analytics!

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