HDP Developer: Apache Pig and Hive
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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.
Students should be familiar with programming principles and have experience in software development. SQL knowledge is also helpful. No prior Hadoop knowledge is required.
Hortonworks offers a comprehensive certification program that identifies you as an expert in Apache Hadoop.
Upon completion of this program, participants should be able to:
- 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 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
- Schedule a recurring workflow using the Oozie Coordinator