🔥Free Big Data Hadoop and Spark Developer course: https://www.simplilearn.com/learn-hadoop-spark-basics-skillup?utm_campaign=Skillup-BigData&utm_medium=DescriptionFirstFold&utm_source=youtube
Hadoop is a famous Big Data framework; this video on Hadoop will acquaint you with the term Big Data and help you understand the importance of Hadoop. Here, you will also learn about the three main components of Hadoop, namely, HDFS, MapReduce, and YARN. In the end, we will have a quiz on Hadoop. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let’s get started and learn all about Hadoop.
Don’t forget to take the quiz at 05:11!
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Simplilearn’s Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab.
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Who should take up this Big Data and Hadoop Certification Training Course?
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists
Learn more at: https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=Hadoop&utm_medium=Description&utm_source=youtube
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Don't forget to take the quiz at 05:11! 🔥Explore Our FREE Courses With Completion Certificate: https://www.youtube.com/watch?v=-caxhMlw_04
a
let r be the number of replications, B number of data chunks. Then is it correct to say that ''r<B'' for the distributed storage to make sense(otherwise each node would have to store the entire data)? also, if f is the number of failing nodes at any point, then ''f<r'' should hold to preserve the entirety of data?
Ensure fault tolerance
Cool
quiz 05:11 My answer is A, B, and C.
C: Ensure fault tolerance
Replica nodes help in fault tolerance but I think it may also help in load balance as replica nodes which can also take part in search queries which reduce load on one node
ENSURE FAULT TOLERANCE
C . ensure fault tolerance
C
Very well explained video 💯
Answer of Advantage of 3x replication Schema in HDFS is Option C that is ensure Fault Tolerance.
answer: Ensures fault tolerance
C
https://youtu.be/oxQ7CGN8egI
YouTube research ????
Amazing…..answer is C
The answer is fault tolarence
Awesome explanation…thank you !!
My Answer to Quiz is C. select C because it can split lots of multiple blocks to compute. and they can copy all data from other blocks, so whichever one or more are broken, the data is not lost.
all of the above right answer
Ensures fault tolerance
Loved the content
Fault tolerance is the answer
amazing content, you guys are the best!!!!!