BenchMarking AVRO JSON ORC PARQUET FILE FORMATS
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BenchMarking AVRO JSON ORC PARQUET FILE FORMATS

Leveraging AVRO file format to store data in Hadoop and improve application performance
0.5 (1 rating)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
9 students enrolled
Created by Ashok M
Last updated 3/2017
English
Current price: $10 Original price: $20 Discount: 50% off
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Includes:
  • 1.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • You would learn what is Avro
  • Creating a hive table with Avro format
  • how to work with Serialization,deserialization and Externalization
View Curriculum
Requirements
  • Basic knowledge of Computers
  • Knowledge of sql
  • Knowledge of corejava
Description

Apache AVRO is a very popular data serialization format in the Hadoop technology stack.

It is used widely in Hadoop stack i.e in hive,pig,mapreduce componenets.

It stores metadata also along with Actual data.

It is a rowbased oriented data storage format.

Provides schema evaluation and block compression.

Metadata will be represented in JSON file

Avro depends heavily on its schema. It allows every data to be written with no prior knowledge of the schema. It serializes fast and the resulting serialized data is lesser in size. Schema is stored along with the Avro data in a file for any further processing.

In RPC, the client and the server exchange schemas during the connection. This exchange helps in the communication between same named fields, missing fields, extra fields, etc.

Avro schemas are defined with JSON that simplifies its implementation in languages with JSON libraries.

Like Avro, there are other serialization mechanisms in Hadoop such as Sequence Files, Protocol Buffers, and Thrift.


Who is the target audience?
  • For all Bigdata Developers
  • For all Middleware developers
  • For all Java developers
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Curriculum For This Course
9 Lectures
01:35:17
+
Introduction
5 Lectures 22:54


Deserialization
05:10

Custom Serialization
07:41

+
AVRO
3 Lectures 41:50
BenchMark Various FileFormats
33:16


Hive table with Avro
06:19
+
Hbase Bulk Loading
1 Lecture 30:33
How to do Hbase Bulk Loading
30:33
About the Instructor
Ashok M
2.4 Average rating
61 Reviews
329 Students
29 Courses
Architect

I am  Reddy having 10 years of IT experience.For the last 4 years I have been working on Bigdata.
From Bigdata perspective,I had working experience on Kafka,Spark,and Hbase,cassandra,hive technologies.
And also I had working experience with AWS and Java technologies.

I have the experience in desigining and implemeting lambda architecture solutions in bigdata

Has experience in Working with Rest API and worked in various domains like financial ,insurance,manufacuring.

I am so passinate about  new technologies.


BigDataTechnologies  is a online training provider and has many experienced lecturers who will proivde excellent training.

BigDataTechnologies has extensive experience in providing training for Java,AWS,iphone,Mapredue,hive,pig,hbase,cassandra,Mongodb,spark,storm and Kafka.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges.

Main objective is to provide high quality content to all students