HDP Developer: Apache Pig and Hive
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.
Duration 4 days
Software developers who need to understand and develop
applications for Hadoop.
• 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
• Understand how Hive tables are defined and implemented
• Use Hive to explore 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
• Write efficient Hive queries
• Create ngrams and context ngrams using Hive
• Perform data analytics using the DataFu Pig library
• Explain the uses and purpose of HCatalog
• Use HCatalog with Pig and Hive
• Define and schedule an Oozie workflow
• Present the Spark ecosystem and high-level architecture
• Perform data analysis with Spark's Resilient Distributed
• Explore Spark SQL and the DataFrame API
• 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
Students should be familiar with programming principles and
have experience in software development. SQL knowledge is also
helpful. No prior Hadoop knowledge is required.
50% Hands-‐on Labs
Hortonworks offers a comprehensive certification program that
identifies you as an expert in Apache Hadoop. Visit
hortonworks.com/training/certification for more information.
Unlimited teas, coffees & soft drinks provided. Lunch is also provided.
Cancellation & Reschedule Policy
You must provide a written notice to Big Data Partnership at least 2 weeks' prior to the start of the class if you cannot attend this class. Big Data Partnership will transfer your registration to a future class of equal or lesser value.
Students who fail to cancel within 2 weeks' and/or do not attend the class, will not receive a refund and will be charged the full amount.
Big Data Partnership can cancel or reschedule at any time at our discretion. In the event that the class is cancelled or rescheduled, we will work with you to apply your registration to another date or refund your fee in full. Big Data Partnership is not responsible for non-refundable travel or other expenses incurrred by the student.
If you have any questions concerning this class, please do not hesitate to contact email@example.com.
When & Where
Big Data Partnership
Big Data Partnership is the leading European-based big data service provider.
Our team has deep expertise across a wide range of big data technologies and data science techniques.
Our recent projects have included:
- the Apache Hadoop ecosystem
- Apache Spark
- Apache Cassandra
And a range of other NoSQL databases & search technologies.
Big Data Partnership helps organisations across all industries become more data-driven by reducing costs and grasping new big-data opportunities, rapidly and at low risk.
We help you Discover why and how to become data driven; we work with you to Develop and prove the value of this approach; we Deliver cost effective solutions which exploit faster and more scalable technology. We reduce risk by Training your staff in the necessary new skills and by providing Support.
For more information, visit http://www.bigdatapartnership.com.