spark1

Question 1

Spark is best suited for_____data.
* Real time
* virtual
* structured
* All of the above

Answer 1

All of the above

Question 2

Which of the following is a feature of Apache Spark?
* Speeds
* Supports multiple languages
* Advanced Analytics
* All of the above

Answer 2

All of the above

Question 3

What does Spark Engine do?
* Scheduling
* Distributing data across cluster
* Monitoring data across cluster
* all of the above

Answer 3

all of the above

Question 4

RDD can NOT be created from data stored on?
* LocalFS
* Oracle
* S3
* HDFS

Answer 4

Oracle

Question 5

For resource management spark can use?
* Yam
* Mesos
* Standalone cluster manager
* All of the above

Answer 5

All of the above

Question 6

Fault Tolerance in RDD is achieved using?
* Immutable nature of RDD
* DAG(Directed Acyclic Graph) or Data Lineage
* Both A&B
* Neither A nor B

Answer 6

Both A&B

Question 7

What is transformation in Spark RDD?
* Takes RDD as input and produces one or more RDD as output
* Return final results of RDD computations
* The way to sent results from executors to the driver
* None of the above

Answer 7

Takes RDD as input and produces one or more RDD as output

Question 8

Which of the following is a feature of Spark RDD?
* In-memory computation
* Lazy evaluations
* Fault Tolerance
* All of the mentioned

Answer 8

All of the mentioned

Question 9

Four main component built in top of spark core

Answer 9

• Spark ML
• Spark SQL
• Spark streaming
• Spark GraphX

Question 10

Describe Spark ML

Answer 10

Spark ML provides simple APIs for execute the functions (classifications , clustering , regression) and creating execution pipelines

Question 11

Describe spark SQL

Answer 11

spark module for working with structured data

Question 12

Describe spark streaming

Answer 12

large-scale near-real-time stream processing framework

Question 13

Describe spark GraphX

Answer 13

spark API for graphs-parallel computation, include
-growing collection of graph algorithms
-builders to simplify graph analytics tasks

Question 14

features of HIVE

Answer 14

good abstraction
declarative language
less error prone
easier to learn & analyze
compile to java map-reduce code

Question 15

Four key component at Hive architecture

Answer 15

meta store
thrift server
driver
Hive QL
Hive CLI

Question 16

Different mode of execution in Apache pig

Question 17

4 Pig vs sql

Question 18

3 Key component of HBase

Answer 18

HBase RegionServer
HBase Master
ZooKeeper

Question 19

6 HBase vs DBMS

Question 20

Role of the zookeeper in HBase architecture

Answer 20

managing the state and configuration of the HBase cluster, providing distributed coordination, leader election, and synchronization and locking services. !!!!!!!!!!!!!!!!!!!!!!

Question 21

4 How Zookeeper achieves constantly, and how it achieves performance

Question 22

__ is a distributed graph processing framework on top of Spark.
* MLlib
* Spark streaming
* GrapghX
* None of the above

Answer 22

GrapghX

Question 23

Spark is 100x faster than MapReduce due to?
* In-memory computing
* Development in scala
* Stream processing
* Spark SQL

Answer 23

In-memory computing

Question 24

creating RDD

Answer 24

load from external RDD
create RDD from another RDD
parallelizing a centralized collection

Question 25

transformation oparation examples

Answer 25

map , filter . join

Question 26

action operations examples

Answer 26

count ,collect ,reduce . save

Question 27

lazy evaluation

Answer 27

not computed right away

Question 28

rdd fault tolerance

Answer 28

no replication in memory , lineage

Question 29

lineage graph

Answer 29

maintain dependencies between rdd go back to the closest disk based rdd

Question 30

representation of RDD

Answer 30

data part:----- metadata information:------

Question 31

data part:----- metadata information:------

Answer 31

data part: multiple partiotions metadata information: dependencies on parent rdd

Question 32

narrow dependency ex

Answer 32

filter map

Question 33

wide dependency ex

Answer 33

join grouping

Question 34

DAG

Answer 34

directed acycling graph

Question 35

spark is faster than hadoop especially for

Answer 35

iterative algorithms

Question 36

spark need more -------- than hadoop

Answer 36

memory

Question 37

map() operate ------ record

Answer 37

entire record

Question 38

mapValues() operate ------ record

Answer 38

second component of the record

Question 39

cash()=persist(---------)

Answer 39

persist(MEMORY_ONLY)

Question 40

benefits of spark SQL

Answer 40

can executes SQL operators optimizations like RDBMS build on top and extends RDD easy integration with other spark libraries

Question 41

spark streaming requirements

Answer 41

scalable to large cluster second-scale latencies simple programming model integrated with batch & interactive processing efficient fault tolerance

Question 42

spark streaming motivation

Answer 42

many important applications process large stream live data require large cluster to handle workload require latencies of few seconds