The Big Data Hadoop Certification course is designed to give you in-depth knowledge of the Big Data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop and Flume for data ingestion with our big data training.
Understand Hadoop Distributed File System (HDFS) and YARN architecture, and learn how to work with them for storage and resource management Understand MapReduce and its characteristics and assimilate advanced MapReduce concepts Ingest data using Sqoop and Flume Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations Understand and work with HBase, its architecture and data storage, and learn the difference between HBase and RDBMS Gain a working knowledge of Pig and its components Do functional programming in Spark, and implement and build Spark applications Understand resilient distribution datasets (RDD) in detail Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques Understand the common use cases of Spark and various interactive algorithms Learn Spark SQL, creating, transforming, and querying data frames Prepare for Cloudera CCA175 Big Data certification
- 40 hours of instructor-led training
- 5 real-life industry projects using Hadoop and Spark
- Training on Yarn, MapReduce, Pig, Hive, Impala, HBase, and Apache Spark
- 24 hours of self-paced video
- Hands-on practice on CloudLab
- Aligned to Cloudera CCA175 certification exam
- Practical assignments at the end of every session.
- Practical learning experience with live project work and examples.
- Lectures 0
- Quizzes 0
- Duration 20 hours
- Skill level Beginner
- Language English, Hindi
- Students 34
- Certificate No
- Assessments Yes