Chapter 5

Question 1

Data wrangling

Answer 1

filter, cleanse and otherwise prepare the data for downstream analysis

Question 2

storage is required whenever the following

occurs:

Answer 2

external datasets are acquired, or internal data will be used in a Big Data environment
• data is manipulated to be made amenable for data analysis
• data is processed via an ETL activity, or output is generated as a result of an
analytical operation

Question 3

Clusters

Answer 3

collection of servers, or nodes that connected together via network to work as a single unit
Each node in the cluster has its own dedicated resources, such as memory, a processor, and a hard drive.

Question 4

file system

Answer 4

method of storing and organizing data on a storage device, such as flash drives, DVDs and hard drives

Question 5

A file

Answer 5

atomic unit of storage used by the file

system to store data

Question 6

distributed file system

Answer 6

a file system that can store large files spread across the nodes
of a cluster

Question 7

Not-only SQL (NoSQL) database

Answer 7

is a non-relational database that is highly scalable,
fault-tolerant and specifically designed to house semi-structured and unstructured data.
- provides an API-based query interface
- support query languages other than Structured Query Language (SQL)

Question 8

Sharding is

Answer 8

the process of horizontally partitioning a large dataset into a collection of smaller, more manageable datasets called shards.
- Each shard is stored on a separate node and each node is responsible for only the data stored on it.

• Each shard shares the same schema, and all shards collectively represent the complete dataset
• achieve horizontal scalability

Question 9

Horizontal scaling

Answer 9

is a method for increasing a system’s capacity by adding similar or
higher capacity resources alongside existing resources

Question 10

benefits of sharding

Answer 10

A benefit of sharding is that it provides partial tolerance toward failures. In case of a node failure, only data stored on that node is affected.

Question 11

Replication

Answer 11

stores multiple copies of a dataset, known as replicas, on multiple nodes
-provides scalability and availability due to the fact that the same
data is replicated on various nodes
-nodes. Fault tolerance is also achieved since data redundancy
ensures that data is not lost when an individual node fails.

Question 12

There are two different methods

that are used to implement replication

Answer 12

master-slave

• peer-to-peer

Question 13

master-slave replication

Answer 13

all data is written to a master node
write requests, including insert, update and delete, occur on the
master node
data is replicated over to multiple
slave nodes
read requests can be fulfilled by any slave node

Question 14

Master-slave replication is ideal for

Answer 14

read intensive loads rather than write intensive loads

Question 15

One concern with master-slave replication is

Answer 15

read inconsistency
an issue if a slave node is read prior to an update to the master being copied to it
a voting system can be implemented where a read is declared consistent if the majority of the slaves contain the same version of the record

Question 16

peer-to-peer replication

Answer 16

there is not a master-slave relationship between the nodes. Each node, known as a peer, is equally capable of handling reads and writes.

Question 17

Peer-to-peer replication is prone to

Answer 17

write inconsistencies that occur as a result of a

simultaneous update of the same data across multiple peers

Question 18

Pessimistic concurrency

Answer 18

proactive strategy that prevents inconsistency. It uses
locking to ensure that only one update to a record can occur at a time.
However, this is detrimental to availability since the database record being updated remains unavailable until all locks are released.

Question 19

Optimistic concurrency is

Answer 19

reactive strategy that does not use locking. Instead, it
allows inconsistency to occur with knowledge that eventually consistency will be achieved after all updates have propagated.

Question 20

Combining Sharding and Master-Slave Replication

Answer 20

When sharding is combined with master-slave replication, multiple shards become slaves of a single master, and the master itself is a shard.

Question 21

Combining Sharding and Peer-to-Peer Replication

Answer 21

When combining sharding with peer-to-peer replication, each shard is replicated to multiple peers, and each peer is only responsible for a subset of the overall dataset.

Collectively, this helps achieve increased scalability and fault tolerance.

As there is no master involved, there is no single point of failure and fault-tolerance for both read and
write operations is supported

Question 22

CAP Theorem

Answer 22

Consistency, Availability, and Partition tolerance
It states that a distributed database system, running on a cluster, can only provide two of the following three properties:

Question 23

CAP Theorem- Consistency

Answer 23

A read from any node results in the same data across multiple nodes

Question 24

CAP Theorem- Availability

Answer 24

A read/write request will always be acknowledged in the form of a
success or a failure

Question 25

CAP Theorem - Partition tolerance

Answer 25

The database system can tolerate communication outages that

split the cluster into multiple silos and can still service read/write requests

Question 26

ACID

Answer 26

database design principle related to transaction management. It is an acronym that stands for:
• atomicity
• consistency
• isolation
• durability

Question 27

ACID: Atomicity

Answer 27

ensures that all operations will always succeed or fail completely. In other
words, there are no partial transactions.

so if 2 out of 3 transactions are successfully but one is not, database roll backs any partial effects of the transaction and puts the
system back to its prior state

Question 28

ACID: Consistency

Answer 28

ensures that the database will always remain in a consistent state by ensuring that only data that conforms to the constraints of the database schema can be written to the database

ex: wrong data type being added to table

Question 29

Isolation

Answer 29

ensures that the results of a transaction are not visible to other operations until it is complete

ex one person can update at a time

Question 30

Durability

Answer 30

ensures that the results of an operation are permanent. In other words, once a transaction has been committed, it cannot be rolled back. This is irrespective of any system failure.

Question 31

BASE

Answer 31

• basically available
• soft state
• eventual consistency

Question 32

BASE favors

Answer 32

availability over consistency.
In other words, the database is A+P from a CAP perspective.
In essence, BASE leverages optimistic concurrency by relaxing the strong consistency constraints mandated by the ACID properties.

Question 33

“basically available,”

Answer 33

database will always acknowledge a client’s request, either in the form of the requested data or a success/failure notification.

Question 34

Soft state

Answer 34

a database may be in an inconsistent state when data is read; thus, the
results may change if the same data is requested again.

Question 35

Eventual consistency

Answer 35

the state in which reads by different clients, immediately

following a write to the database, may not return consistent results