About this course

Course type Premium
Course code VCLHWAHDPH2
Duration 4 Days
Special Notices

Please note: This course is delivered by accredited Hortonworks instructors. The syllabus includes specific use cases and examples to help illustrate and reinforce the theory and the functionality of the technology being explored. Where possible, the instructor will provide further examples and answer questions relevant to an individual delegates specific application of the technology. However, due to the complexity of the technology and the breadth of application across industries, this may not always be possible in the classroom environment.

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.

Target 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.

Outline

  • 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

Premium Course

4 Days

Duration
Delivery Method

Delivery method

Virtual learning

Recreates a classroom experience online, enabling full interactions with the learning professional leading the course.

Find dates and prices

Sorry, we don't have any public dates scheduled for this course, but it can be run as a closed event for your company.
Please contact us for details on alternative ways we can help you 0845 757 3888 or email us at info@qa.com.

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