Introduction to Apache Hadoop and the Hadoop Ecosystem :
- Apache Hadoop Overview
- Data Ingestion and Storage
- Data Processing
- Data Analysis and Exploration
- Other Ecosystem Tools
Apache Hadoop File Storage :
- Apache Hadoop Cluster Components
- HDFS Architecture
- Using HDFS
Distributed Processing on an Apache Hadoop:
- YARN Architecture
- Working With YARN
- Apache Spark Basics
- What is Apache Spark?
- Starting the Spark Shell
- Using the Spark Shell
Working with DataFrames and Schemas :
- Creating DataFrames from Data Sources
- Saving DataFrames to Data Sources
- DataFrame Schemas
- Eager and Lazy Execution
- Analyzing Data with DataFrame Queries
Transforming Data with RDDs :
- Writing and Passing Transformation Functions
- Transformation Execution
- Converting Between RDDs and DataFrames
Aggregating Data with Pair RDDs :
- Key-Value Pair RDDs
- Other Pair RDD Operations
Querying Tables and Views with Apache Spark SQL :
- Querying Tables in Spark Using SQL
- Querying Files and Views
- The Catalog API
- Comparing Spark SQL, Apache Impala, and
Writing, Configuring, and Running Apache Spark Applications :
- Writing a Spark Application
- Building and Running an Application
- Application Deployment Mode
- The Spark Application Web UI
Common Patterns in Apache Spark Data Processing :
- Common Apache Spark Use Cases
- Iterative Algorithms in Apache Spark
- Machine Learning
Executive Program in Hadoop Developer
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