This post covers Questions & Answers asked by trainees in our Big Data Hadoop Administration Webinar in which we have covered Introduction of Big Data, What Is Big Data & 4 V’s, Big Data Use Cases, Big Data Types: Structure, Un-Structured & Semi-Structured and much more.
We recently had a Masterclass on Big Data Hadoop Administration covering What, Why & How in that webinar there were a lot of questions. Most of these questions were answered in Webinar however not all questions were covered because of time. We’ll be adding these questions over a period of time in Private Facebook Group for BigData & Hadoop and will also post these questions with answer in our blog.
These are the few questions, which we feel is common to everyone, so we have chosen these question asked by the attendees during the webinar.
Q. According to the market, Which tools are important in Hadoop?
–> As Hadoop has multiple tools for Data Crunching lets deep dive into few of them.
Hadoop Distributed File System: The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications.
HBase: HBase is a column-oriented database management system that runs on top of HDFS. It is well suited for sparse data sets, which are common in many big data use cases
HIVE: The Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL
Sqoop: Sqoop is a tool designed to transfer data between Hadoop and relational databases
Pig: Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs
ZooKeeper: ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services
NOSQL: Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontally scalable. The original intention has been modern web-scale databases.
There are other tools as well but these are one of the important ones.
Q. I am working as Linux admin, I would like to know about Hadoop admin and I want to shift into Hadoop admin?
- It is a very good choice for a Linux admin to go for Big Data administration.
- Hadoop is a popular framework for handling Big data and it is the distributed computing framework for handling Big data.
- There are a few skills that are required to become a good Hadoop administrator.
- Since you already know Linux it will be easy for you to understand the concepts:
- General operational expertise such as good troubleshooting skills, understanding of system’s capacity, bottlenecks, basics of memory, CPU, OS, storage, and networks
- Should have very good knowledge of Unix based File System
- Knowledge of Networking (since its distributed framework)
- Thorough understanding of when to scale and how to scale
- Deep Understanding of Hadoop architecture
- When it comes to coding Hadoop admin will not be writing any Java MapReduce programs. But he should have knowledge of JVM and its capabilities since all the jobs in Hadoop runs on JVM.
- Hadoop stack has many tools like Pig, Hive, HBase, Spark, ZooKeeper, Oozie and many more. You should have an architectural understanding of all these tools and configure them to work with Hadoop.
These are one of the few questions which were asked during our webinar on Big Data Hadoop Administration covering What, Why & How. If you have any question related to Big Data, you can either ask by commenting on the blog or just write back to us at email@example.com.
You will get to know all of this and deep-dive into each concept related to BigData & Hadoop, once you will get enrolled in our Big Data Hadoop Administration Training
Related /Further Readings
If you are just starting out in BigData & Hadoop then I highly recommend you to go through these posts below, first:
- Big Data Hadoop Keypoints & Things you must know to Start learning Big Data & Hadoop, check here
- Big Data & Hadoop Overview, Concepts, Architecture, including Hadoop Distributed File System (HDFS), Check here
- Hadoop Distribution: Cloudera vs Hortonwork Check here
Next Task For You
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