Apache Hudi Training

Live Online & Classroom Enterprise Training

Learn how to efficiently manage large-scale data lakes with Apache Hudi, enabling real-time data ingestion, incremental processing, and upsert capabilities for modern big data architectures.

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What is Apache Hudi Training about?

The Apache Hudi course provides hands-on knowledge for managing and processing big data efficiently in cloud or on-premise environments. Hudi (Hadoop Upserts Deletes and Incrementals) brings database-like capabilities to data lakes, allowing data engineers to perform incremental updates and deletes on massive datasets. This course covers Hudi’s core components, architecture, table types (Copy-on-Write and Merge-on-Read), and integration with Spark, Hive, and Presto. By the end, learners will understand how to build scalable, real-time data pipelines using Apache Hudi.

What are the objectives of Apache Hudi Training ?

Understand Apache Hudi’s architecture, components, and storage models.
Learn how to ingest, manage, and query data incrementally in data lakes.
Implement upserts, deletes, and incremental queries using Hudi.
Integrate Apache Hudi with Apache Spark, Hive, and Presto.
Optimize performance, storage, and query efficiency for real-time analytics.

Who is Apache Hudi Training for?

Data Engineers building scalable data pipelines.
Big Data Developers working with Hadoop, Spark, or cloud-based data lakes.
Data Architects designing real-time analytics systems.
ETL Developers seeking incremental data ingestion solutions.
Cloud and Analytics Engineers managing large-scale datasets.

What are the prerequisites for Apache Hudi Training?

Prerequisites:

Basic understanding of Big Data concepts (Hadoop, Spark).
Familiarity with data lake architectures and ETL workflows.
Working knowledge of SQL and data processing frameworks.
Experience with Python, Java, or Scala (recommended).
Understanding of distributed storage and computing systems.

Learning Path:

Introduction to Apache Hudi and Data Lake Challenges
Hudi Architecture, Table Types, and Storage Mechanisms
Ingesting and Managing Data with Apache Spark
Querying Hudi Tables with Hive and Presto
Performance Optimization, Incremental Queries, and Real-World Use Cases

Related Courses:

Apache Spark Developer Essentials
Apache Kafka for Data Streaming
Data Lakehouse with Delta Lake
Big Data Engineering with Databricks

Available Training Modes

Live Online Training

3 Days

Course Outline Expand All

Expand All

Module 1: Introduction to Apache Hudi

Overview of Apache Hudi

Need for Hudi in Big Data Ecosystems

Key Features and Advantages

Comparison with Delta Lake & Apache Iceberg

Use Cases and Industry Applications

Module 2: Hudi Architecture and Components

Understanding Hudi’s Architecture

Hudi Table Types: Copy-on-Write (COW) & Merge-on-Read (MOR)

Data Ingestion & Storage Mechanism

Indexing in Hudi

Role of Timeline Server & Commit Protocol

Module 3: Setting Up Apache Hudi

System Requirements and Installation

Hudi Configuration & Prerequisites

Deploying Hudi on Apache Spark

Working with Hudi on AWS, Azure, GCP

Module 4: Hudi Data Ingestion and Writing

Writing Data to Hudi Tables

Bulk Insert, Upsert, and Delete Operations

Schema Evolution in Hudi

Partitioning and Clustering

Optimizing Write Performance

Module 5: Querying and Reading Data in Hudi

Querying Hudi Tables using Apache Spark

Integration with Presto, Hive, and Trino

Snapshot and Incremental Queries

Querying Data Lake with Hudi

Module 6: Hudi Data Management and Optimizations

Compaction and Cleaning Policies

Clustering for Performance Enhancement

Metadata Management in Hudi

Performance Tuning Strategies

Module 7: Apache Hudi Integration with Big Data Ecosystem

Hudi with Apache Spark

Integration with Apache Flink

Using Hudi with AWS Glue, EMR, Databricks

Combining Hudi with Kafka for Streaming Data

Module 8: Data Governance and Security in Hudi

Managing Metadata & Schema Evolution

Role-based Access Control (RBAC)

Data Lineage and Auditing

Implementing Security Best Practices

Module 9: Advanced Use Cases and Best Practices

Real-time Data Processing with Hudi

Implementing Change Data Capture (CDC)

Scaling Hudi for Large-Scale Workloads

Troubleshooting Common Issues

Who is the instructor for this training?

The trainer for this Apache Hudi Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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