HDP Developer: Apache Pig and Hive - Virtual

Overview

This course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. Topics include: Hadoop, YARN, HDFS, MapReduce, data ingestion, workflow definition and using Pig and Hive to perform data analytics on Big Data. Labs are executed on a 7-node HDP cluster.

Audience

Software developers who need to understand and develop applications for Hadoop.

Prerequisites

Please note: Hortonworks courses are delivered using electronic courseware. for delegates attending remotely (Virtual classes or Attend from Anywhere) you must ensure that you have dual monitors or a single monitor plus tablet device. Dual monitors are required in order to allow you to view labs and lab instructions on separate screens.

Technical pre-requisites

  • Delegates should be familiar with programming principles and have experience in software development.
  • SQL knowledge is also helpful.
  • No prior Hadoop knowledge is required.

Syllabus

  • Describe Hadoop, YARN and use cases for Hadoop
  • Describe Hadoop ecosystem tools and frameworks
  • Describe the HDFS architecture
  • Use the Hadoop client to input data into HDFS
  • Transfer data between Hadoop and a relational database
  • Explain YARN and MaoReduce architectures
  • Run a MapReduce job on YARN
  • Use Pig to explore and transform data in HDFS
  • Use Hive to explore Understand how Hive tables are defined and implementedand analyze data sets
  • Use the new Hive windowing functions
  • Explain and use the various Hive file formats
  • Create and populate a Hive table that uses ORC file formats
  • Use Hive to run SQL-like queries to perform data analysis
  • Use Hive to join datasets using a variety of techniques, including Map-side joins and Sort-Merge-Bucket joins
  • Write efficient Hive queries
  • Create ngrams and context ngrams using Hive
  • Perform data analytics like quantiles and page rank on Big Data using the DataFu Pig library
  • Explain the uses and purpose of HCatalog
  • Use HCatalog with Pig and Hive
  • Define a workflow using Oozie
  • Schedule a recurring workflow using the Oozie Coordinator

Hands-On Labs

  • 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 and transform data using Pig
  • Split and join a dataset 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 and sessionize clickstream data
  • Compute quantiles of NYSE stock prices
  • Use Hive to compute ngrams on Avro-formatted files
  • Define an Oozie workflow

Training provider

Teaching mode: Classroom - Instructor Led
Duration: 4 days
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