Avro Training
Introduction to Avro
Avro is a framework for data serialization in Apache Hadoop and other big data systems. This module introduces Avro, covering its core features, schema definition, and use cases in data serialization and exchange.
Getting Started with Avro
Learn how to get started with Avro, including installation, configuration, and basic usage. This section covers the essentials of Avro, including how to define and use schemas for data serialization.
Avro Schema Definition
Discover how to define schemas in Avro. Learn about the schema types, field definitions, and data types supported by Avro. Understand how schemas ensure data compatibility and support schema evolution.
Data Serialization and Deserialization
Gain skills in data serialization and deserialization using Avro. Learn how to serialize data into Avro format and deserialize it back into usable objects. Explore Avro’s compact, fast, and efficient serialization mechanisms.
Integration with Big Data Systems
Learn how to integrate Avro with big data systems such as Apache Hadoop, Apache Kafka, and Apache Spark. Explore how Avro is used for data exchange and storage in these ecosystems.
Handling Schema Evolution
Discover how Avro handles schema evolution. Learn about backward and forward compatibility, schema versioning, and how to manage schema changes over time without disrupting data processing.
Avro Tools and Libraries
Explore Avro tools and libraries for working with Avro data. Learn about command-line tools for schema management, libraries for various programming languages, and how to use them in your projects.
Performance Optimization and Best Practices
Learn about performance optimization and best practices for using Avro. Explore techniques for optimizing serialization and deserialization performance, managing schema evolution, and ensuring efficient data processing.
Case Studies and Real-World Applications
Review case studies and real-world applications of Avro. Learn from practical examples of Avro implementations in different industries and understand how organizations have leveraged Avro for efficient data serialization and processing.
Avro Syllabus
Introduction to Avro
- Overview of Avro
- Importance and Use Cases of Avro
- Understanding Serialization and Deserialization
- Comparison with Other Serialization Formats
Avro Architecture
- Avro Data Types
- Avro Schemas
- Primitive Types
- Complex Types
- Logical Types
- Schema Evolution and Compatibility
Avro Schemas
- Defining Avro Schemas
- Schema Declaration and Syntax
- Nested Schemas
- Schema Registry
Working with Avro
- Writing Avro Data
- Reading Avro Data
- Avro Tools and Utilities
- Integrating Avro with Big Data Ecosystems
Avro with Apache Kafka
- Using Avro with Kafka
- Schema Registry in Kafka
- Producing and Consuming Avro Messages
- Handling Schema Evolution in Kafka
Avro with Apache Hadoop
- Using Avro with Hadoop
- Writing Avro Data to HDFS
- Reading Avro Data from HDFS
- MapReduce with Avro Data
Avro with Apache Spark
- Using Avro with Spark
- Reading and Writing Avro Data in Spark
- Schema Handling in Spark
- Optimizing Avro Operations in Spark
Avro with Other Big Data Technologies
- Avro with Apache Hive
- Avro with Apache Pig
- Avro with Apache Flink
- Avro with Apache NiFi
Serialization and Deserialization APIs
- Serialization APIs
- Deserialization APIs
- Handling Different Data Formats
- Performance Tuning
Advanced Avro Concepts
- Custom Data Types and Logical Types
- Avro IDL (Interface Definition Language)
- Avro with REST APIs
- Security and Access Control
Training
Basic Level Training
Duration : 1 Month
Advanced Level Training
Duration : 1 Month
Project Level Training
Duration : 1 Month
Total Training Period
Duration : 3 Months
Course Mode :
Available Online / Offline
Course Fees :
Please contact the office for details