HDP Developer Apache Pig and Hive Training

This training is recommended for developers who know how to create apps in analyzing Big data stored in Apache Hadoop by utilizing Hive and Pig.

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Course Overview

This training is recommended for developers who know how to create apps to analyze Big data stored in Apache Hadoop by utilizing Hive and Pig.

The topics also cover HDFS, data ingestion, Hadoop, data ingestion and workflow definition, and utilizing Pig and Hive in performing data analytics stored on Big Data.

The course also covers an introductory course in Spark SQL and Spark Core.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

What you will learn

Describing about YARN and utilize cases for Hadoop.
Describing about Hadoop frameworks and ecosystem tools.
Describing Hadoop frameworks and ecosystem tools.
Describing about HDFS architecture.
Utilizing the Hadoop client and input data into HDFS.
Transferring of data between Hadoopn and relation database.
Explaining MaoReduce architectures and YARN.
Running MapReduce job on YARN.
Utilizing Pig to transform and explore data in HDFS.
Understanding about Hive Tables which are implemented and defined.
Utilizing the functionalities used in Hive Windows.
Utilizing Hive to analyze and explore datasets.
Utilizing and explaining about the several Hive File Formats.
Populating and creating a Hive table that utilized ORC file supported extension.
Utilizing Hive to execute SQL queries in performing data analysis.
Utilizing Hive for joining data sets and utilizing widespread techniques.
Writing effectual Hive queries.
Performing data analytics utilizing the DataFu Pig library.
Explaining the purposes and utilizing HCatalog.
Scheduling and defining about Oozie workflow.
Presenting high-level architecture and Spark ecosystem.
Exploring DataFrame API and Spark SQL.

Who Should Attend This Course?

This training is intended for software developers who want to gain knowledge in developing apps for Hadoop.

Prerequisites

The recommended prerequisite for this course is familiarity with software development and programming principles. However, any specific knowledge of Hadoop is not required.

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📘 HDP Developer Apache Pig and Hive Outline

Use HDFS commands to add/remove files and folders
Use Sqoop to transfer data between HDFS and a RDBMS
Run MapReduce and YARN application jobs
Explore, transform, split and join datasets using Pig
Use Pig to transform and export a dataset for use with Hive
Use HCatLoader and HCatStorer
Use Hive to discover useful information in a dataset
Describe how Hive queries get executed as MapReduce jobs
Perform a join of two datasets with Hive
Use advanced Hive features: windowing, views, ORC files
Use Hive analytics functions
Write a custom reducer in Python
Analyze clickstream data and compute quantiles with DataFu
Use Hive to compute ngrams on Avro-formatted files
Define an Oozie workflow
Use Spark Core to read files and perform data analysis
Create and join DataFrames with Spark SQL

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