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, definition and using Pig and Hive to perform data analytics on Big Data.
• 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
• 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
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Target Audience / Prerequisites
Students should be familiar with SQL and have a minimal understanding of programming principles. No prior Hadoop knowledge is required.
Data Analysts, BI Analysts, BI Developers, SAS Developers and other types of analysts who need to answer questions and analyze Big Data stored in a Hadoop cluster.
All necessary equipment and infrastructure required to perform lab exercises are provided.
Unlimited teas, coffees & soft drinks 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 firstname.lastname@example.org.
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.