Big Data Analytics

(i) What are the main components of Big Data ?

1. Map Reduce
2. Reduce
3. YARN
4. All of these

(ii) Hadoop achieves readability by replicating the data across multiple hosts and lence does not require........storage on hosts :

1. RAID
2. ZFS
3. Operating System
4. None of these

(iii) ............has the worlds largest Hadoop cluster :

1. Apple
2. Datamatics
3. Facebook
4. None of these

(iv) Hive also support custom extensions writter is..........:

1. C#
2. Java

(v) ............is genes at purpose computing model and sustime system for distributed data analytics :

1. MapReduce
2. Drill
3. Oozie
4. None of these

(vi) ............is the slave/wark es node and hoeds the user data in the form of Data Blocks :

1. Data Node
2. Name Node
3. Data Block
4. Replication

(vii) HDFS is implemented in ............programming language :

1. C++
2. Java
3. Scala
4. None of these

(viii) ............is the default partitioner for partioning key space :

1. Hash pax
2. Partitioner
3. Hash Partitioner
4. None of these

(ix) ............maps input key/value pains to a set inter mediate key/value points :

1. Mapper
2. Reducer
3. Both (a) and (b)
4. None of these

(x) ............is an online NOSQL developed by cloudera :

1. Hcatalog
2. Hbase
3. Imphala
4. Oozic

(xi) What are the different features of Big Data Analytics ?

1. Open Source
2. Scalability
3. Data Recovery
4. All of above

(xii) All of the following accurately describe Hadoop, except :

1. Oper Source
2. Real time
3. Java based
4. Distributed computing approach

(xiii) ............hides the limitation of java behind a powerful and concise clojure API for cascading :

1. Scalding
2. Cascalog
3. Hcatalog
4. H calding

(xiv) Which package contains most fundamental functions to seen R ?

1. Root
2. Child
3. Base
4. Pasent

(xv) Advanced usecss can write.........code to manipulate R objects directly :

1. C, C++
2. C++ java
3. Java, C
4. Java