Apache Kafka Training

ACTE provides Apache Kafka Training in Pune that is both real-time and placement-focused. Our Apache Kafka training ranges from beginner to intermediate, with classroom and online learning options available. The Apache Kafka course curriculum is designed to land you a job in a well-known MNC company in Pune as soon as you complete your Apache Kafka training.

Our Apache Kafka instructors in Pune are highly trained and experienced working professionals with hands-on real-world experience. We developed our course material and syllabus in response to the needs of our students to assist them in achieving their professional objectives. In our Training program, you will learn how to use Apache Kafka.

Apache Kafka is a stream-processing framework that implements a software bus. It is a Scala and Java-based open-source development platform developed by the Apache Software Foundation. The goal of the project is to provide a single, high-throughput, low-latency platform for real-time data flows.

Apache Kafka training is designed especially for developers and architects who want to build integration solutions using EIPs (Enterprise Integration Patterns) through Apache Kafka Online Course. This can also be enrolled by students and fresher who are interested to develop or start their career with Apache Kafka.

After completing this Apache Kafka training course, you will understand,

• The fundamentals of systems integrations and ESB patterns.
• The syntax and composition of Apache Kafka.
• Enterprise integration patterns and components for Apache Kafka.
• Apache Kafka best practices.
• Advanced concepts, like retry patterns, exception handling, and dead letter channels.

Curriculum:

• Module 1: Introduction to Apache Kafka
• High Availability
• Scaling
• Advantages and Challenges
• Module 2: Introduction to Big Data
• What is Big data
• Big Data opportunities,Challenges
• Characteristics of Big data
• Module 3: Introduction to Apache Kafka
• Apache Kafka Distributed File System
• Comparing Apache Kafka & SQL
• Industries using Apache Kafka
• Data Locality
• Apache Kafka Architecture
• Map Reduce & HDFS
• Using the Apache Kafka single node image (Clone)
• Module 4: Apache Kafka Distributed File System (HDFS)
• HDFS Design & Concepts
• Blocks, Name nodes and Data nodes
• HDFS High-Availability and HDFS Federation
• Apache Kafka DFS The Command-Line Interface
• Basic File System Operations
• Anatomy of File Read,File Write
• Block Placement Policy and Modes
• More detailed explanation about Configuration files
• Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
• How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
• FSCK Utility. (Block report)
• How to override default configuration at system level and Programming level
• HDFS Federation
• ZOOKEEPER Leader Election Algorithm
• Exercise and small use case on HDFS
• Module 5: Map Reduce
• Map Reduce Functional Programming Basics
• Map and Reduce Basics
• How Map Reduce Works
• Anatomy of a Map Reduce Job Run
• Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
• Job Completion, Failures
• Shuffling and Sorting
• Splits, Record reader, Partition, Types of partitions & Combiner
• Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
• Types of Schedulers and Counters
• Comparisons between Old and New API at code and Architecture Level
• Getting the data from RDBMS into HDFS using Custom data types
• Distributed Cache and Apache Kafka Streaming (Python, Ruby and R)
• YARN
• Sequential Files and Map Files
• Enabling Compression Codec’s
• Map side Join with distributed Cache
• Types of I/O Formats: Multiple outputs, NLINEinputformat
• Handling small files using CombineFileInputFormat
• And more.