Curso de Apache Hadoop Pig & Hive

por | 22 / 03 / 15







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Curso de Apache Hadoop Pig and Hive

Curso de Apache Hadoop Pig and Hive

Treinamento oficial Hortonworks onde somos a primeira empresa no Brasil a ministrar esse curso. Curso para desenvolvedores e analistas em sistemas voltados para Big Data.  Serão abordados os módulos Pig e Hive. Material em inglês. Curso ministrado em português. 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, using Pig and Hive to perform data analytics on Big Data and an introduction to Spark Core and Spark SQL. TARGET AUDIENCE Software developers who need to understand and develop applications for Hadoop.
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WHAT WILL I LEARN?

  • Describe Hadoop, YARN and use cases forHadoop
  • 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 MapReduce 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 implemented and 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
  • Present the Spark ecosystem and high-level architecture
  • Perform data analysis with Spark’s Resilient Distributed Dataset API
  • Explore Spark SQL and the DataFrame API
  • 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
  • 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

QUAL O DIFERENCIAL DA CETAX?

COFFEE-BREAK

Lanche durante o(s) intervalo(s) do curso.


AMBIENTE WIFI

Internet wireless gratuita (Leve seu Notebook).

KIT BOAS-VINDAS

Bloco de anotações; Caneta ou lapiseira.


MATERIAL DIDÁTICO

Apostila digital completa para estudo posterior.

CERTIFICADO

Certificação de aluno da TutorPro/Cetax.


ACESSO A PLATAFORMA

3 meses de acesso à plataforma de ensino.

QUEM IRÁ ME ENSINAR?

Marco Garcia

Marco Garcia

Instrutor

Com mais de 20 anos de experiência em T.I, sendo 15 exclusivamente com Business Intelligence e Data Warehouse. Marco Garcia é formado pela FATEC-SO, com MBA pela FGV; possui certificado pelo Kiimball University – EUA, onde teve aula pessoalmente com Ralph Kimball, um dos principais gurus do Data Warehouse. Também realizou cursos no TDWI, maior entidade de pequisa de Data Warehouses do mundo. Além da sua experiência acadêmica, vivenciou, profissionalmente, diversos projetos em bancos, financeiras, construtoras, varejo, marketing e outros.

Cursos Internacionais

Dimensional Modeling in Depth
Margy Ross / Ralph Kimball – Kimball Group
Washington D.C / USA

Data Warehouse ETL in Depth

Ralph Kimball – Kimball Group
Washington D.C / USA
TDWI – The Data Warehouse Institute – USA – 2011

  • Data Warehousing Architectures: Choosing the Right Data Warehousing
  • Designing the Data Warehouse for High Performance
  • Mastering BI with Best-Practice Architectures and Data Models
  • TDWI Master Data Management Fundamentals
  • Agile Data Warehousing 101: An Introduction to Accelerated BI/DW
  • Down and Dirty with Data Quality: A Hands-On Experience with Data Cleansing


TDWI – The Data Warehouse Institute – USA – 2013

  • The Art of Estimating Data Warehousing Projects
  • Big Data: What’s All the Hadoop?
  • Big Data: Beyond the Hadoop-la
  • Big Data: The Tipping Point
  • Building the “Big Data” Warehouse
  • TDWI Project Management for Business Intelligence
  • TDWI Master Data Management Fundamentals

PARCEIRO OFICIAL

 Parceiro oficial: