Best Sqoop Courses 2021
Best Sqoop Tutorials 2021
Mastering Apache SQOOP with Hadoop,Hive, MySQL (Mac & Win)
Why apache sqoop
Apache sqoop is designed to import data from relational databases such as oracle, mysql, etc. To hadoop systems. Hadoop is ideal for batch processing huge amounts of data. This is the industry standard these days. In real-life scenarios, using sqoop, you can move data from relational tables to hadoop, and then take advantage of hadoop’s parallel processing capabilities to process huge amounts of data and generate meaningful information about the data. Hadoop processing results can again be stored in relational tables using the sqoop export feature.
Big data analytics starts with data ingestion and that’s where apache sqoop comes in. This is the first step in preparing the data.
About this course
In this course, you will learn step by step everything you need to know about apache sqoop and how to integrate it into the hadoop ecosystem. With each concept explained with real world examples, you will learn how to create data pipelines to move data from hadoop in / out. In this course, you will learn in detail the following main concepts:
Apache sqoop – subject import << mysql to hadoop / hive >>
Default hadoop storage
Specific target on hadoop storage
Overwrite existing data
Load specific columns from mysql table
Control the data splitting logic
Defaults to a single mapper when needed
Sqoop options files
Debugging sqoop operations
Import data in various file formats – text, sequence, avro, parquet & orc
Data compression during import
Custom query execution
Handling null strings and non-string values
Setting delimiters for imported data files
Definition of escape characters
Incremental data loading
Write directly in the hive table
Use of hcatalog parameters
Import of all tables from the mysql database
Import the whole mysql database into the hive database
Apache sqoop – export topics << hadoop / hive to mysql >>
Move data from hadoop to the mysql table
Move specific columns from hadoop to a mysql table
Avoid partial export problems
Update operation when exporting
Apache sqoop – job topics << automation >>
Create a sqoop job
List existing sqoop jobs
Check metadata on sqoop tasks
Run sqoop job
Delete sqoop job
Enable password storage for easy execution in production
What you will expect after completing this course
After completing this course, you will tackle one of the most requested topics in the certifications below. You will also need to take other lessons to fully prepare for the test. We will be launching more courses soon.
1. Cca spark and hadoop developer exam (cca175)
2. Hortonworks data platform (hdp) certified developer exam (hdpcd)
You will also get step-by-step instructions to install all the required tools and components on your machine in order to run all the examples provided in this course. Each video will explain the whole process in detail and in an easy to understand way.
You will have access to the working code so that you can play with and develop it. All code examples work and will be shown in video lessons.
Windows users will need to install a virtual machine on their device to set up a single node hadoop cluster, while macbook or linux users can directly install the hadoop and sqoop components on their machines. The step-by-step process is illustrated in the course.
Big Data Analytics Using Sqoop and Hive
Data is the new oil in this digital age.
Are you planning to start your career in Big Data Analytics? Then you have landed in the right place.
In this course, you will learn how to organize, analyze, and interpret large sources of information.
We cover all the essential fundamental knowledge of Big Data Analytics and provide end-to-end real-world project practices.
The course contains
Understanding of Big Data and MapReduce
How to transfer data from different sources using Sqoop
Manipulate Data in HDFS Using HIVE
Real Hands Experience Project