When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
This OnDemand offering provides you with a 180-day subscription that begins on the date of purchase.
Skills Gained
- The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysis
- The fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with Hadoop tools
- How Pig, Hive, and Impala improve productivity for typical analysis tasks
- Joining diverse datasets to gain valuable business insight
- Performing real-time, complex queries on datasets
Prerequisites
This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Knowledge of SQL is assumed, as is basic Linux command-line familiarity. Knowledge of at least one scripting language (e.g., Bash scripting, Perl, Python, Ruby) would be helpful but is not essential. Prior knowledge of Apache Hadoop is not required.
Course Details
Cloudera University’s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Cloudera presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages.
Hadoop Fundamentals
- The Motivation for Hadoop
- Hadoop Overview
- Data Storage: HDFS
- Distributed Data Processing: YARN, MapReduce, and Spark
- Data Processing and Analysis: Pig, Hive, and Impala
- Data Integration: Sqoop
- Other Hadoop Data Tools
- Exercise Scenarios Explanation
Introduction to Pig
- What Is Pig?
- Pig’s Features
- Pig Use Cases
- Interacting with Pig
Basic Data Analysis with Pig
- Pig Latin Syntax
- Loading Data
- Simple Data Types
- Field Definitions
- Data Output
- Viewing the Schema
- Filtering and Sorting Data
- Commonly-Used Functions
Processing Complex Data with Pig
- Storage Formats
- Complex/Nested Data Types
- Grouping
- Built-In Functions for Complex Data
- Iterating Grouped Data
Multi-Dataset Operations with Pig
- Techniques for Combining Data Sets
- Joining Data Sets in Pig
- Set Operations
- Splitting Data Sets
Pig Troubleshooting and Optimization
- Troubleshooting Pig
- Logging
- Using Hadoop’s Web UI
- Data Sampling and Debugging
- Performance Overview
- Understanding the Execution Plan
- Tips for Improving the Performance of Your Pig Jobs
Introduction to Hive and Impala
- What Is Hive?
- What Is Impala?
- Schema and Data Storage
- Comparing Hive to Traditional Databases
- Hive Use Cases
Querying with Hive and Impala
- Databases and Tables
- Basic Hive and Impala Query Language Syntax
- Data Types
- Differences Between Hive and Impala Query Syntax
- Using Hue to Execute Queries
- Using the Impala Shell
Data Management
- Data Storage
- Creating Databases and Tables
- Loading Data
- Altering Databases and Tables
- Simplifying Queries with Views
- Storing Query Results
Data Storage and Performance
- Partitioning Tables
- Choosing a File Format
- Managing Metadata
- Controlling Access to Data
Relational Data Analysis with Hive and Impala
- Joining Datasets
- Common Built-In Functions
- Aggregation and Windowing
Working with Impala
- How Impala Executes Queries
- Extending Impala with User-Defined Functions
- Improving Impala Performance
Analyzing Text and Complex Data with Hive
- Complex Values in Hive
- Using Regular Expressions in Hive
- Sentiment Analysis and N-Grams
- Conclusion
Hive Optimization
- Understanding Query Performance
- Controlling Job Execution Plan
- Bucketing
- Indexing Data
Extending Hive
- SerDes
- Data Transformation with Custom Scripts
- User-Defined Functions
- Parameterized Queries
Choosing the Best Tool for the Job
- Comparing MapReduce, Pig, Hive, Impala, and
- Relational Databases
- Which to Choose?
Does the course schedule include a Lunchbreak?
Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.
How can someone reach me during class?
If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.
What languages are used to deliver training?
Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.
What does GTR stand for?
GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.
How do I find an ExitCertified training location?
We have training locations across the United States and Canada. View a full list of classroom training locations.
Which delivery formats are available?
At ExitCertified we offer training that is Instructor-Led, Online, Virtual and Self-Paced.
Does ExitCertified deliver group training?
Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.
Does ExitCertified deliver group training?
Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.
The setup of the lab was quite good.
The course material is quite good as well.
the professor was very clean and help students wih the labs when needed, Thank you.
Great first experience with ExitCertified. I look forward to many more trainings.
it was good and very informative. Instructure covered everything in detail.
The course material and the instructor were very good. This course met all my requirements.
