Apache Kude is a Solution for Hadoop Storage Challenge
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Apache Kude is a Solution for Hadoop Storage Challenge

Learning Apache Kude which is a Solution for Hadoop Storage Challenge
0.0 (0 ratings)
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.
3 students enrolled
Created by Ashok M
Last updated 3/2017
English
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Current price: $10 Original price: $20 Discount: 50% off
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Includes:
  • 39 mins on-demand video
  • 1 Article
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Learning about Kudu functionality
  • Learning about Kudu Architecture
  • How Kudu helps in Hadoop
View Curriculum
Requirements
  • Basic knowledge of Computers
  • Basic knowledge of java
  • Basic knowledge of Hadoop
Description

In order to scale out to large datasets and large clusters, Kudu splits tables into smaller units called tablets. This splitting can be configured on a per-table basis to be based on hashing, range partitioning, or a combination thereof. This allows the operator to easily trade off between parallelism for analytic workloads and high concurrency for more online ones.

In order to keep your data safe and available at all times, Kudu uses the Raft consensus algorithm to replicate all operations for a given tablet. Raft, like Paxos, ensures that every write is persisted by at least two nodes before responding to the client request, ensuring that no data is ever lost due to a machine failure. When machines do fail, replicas reconfigure themselves within a few seconds to maintain extremely high system availability.

The use of majority consensus provides very low tail latencies even when some nodes may be stressed by concurrent workloads such as Spark jobs or heavy Impala queries. But unlike eventually consistent systems, Raft consensus ensures that all replicas will come to agreement around the state of the data, and by using a combination of logical and physical clocks, Kudu can offer strict snapshot consistency to clients that demand it.

Who is the target audience?
  • This course is for students
  • This course is for all developers
  • This is for all Architects
  • This is for all Managers
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Curriculum For This Course
+
Introduction
1 Lecture 01:20
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Apache Kudu
4 Lectures 37:13

Realtime Usecase DEMO-part1
08:01

Realtime Usecase DEMO-part2
20:09

Wrap-up
00:02
About the Instructor
Ashok M
2.4 Average rating
61 Reviews
330 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