Terminologies and its types
In-Memory Analytics
In-Database processing
Symmetric Multiprocessor system(SMP)
Massively Parallel Processing
Difference Between Parallel and Distributed Systems
Shared Nothing Architecture
Advantages of a “ shared nothing Architecture”
CAP Theorem Explained
CAP Theorem
2. contents
• Terminologies and its types
• In-Memory Analytics
• In-Database processing
• Symmetric Multiprocessor system(SMP)
• Massively Parallel Processing
• Difference Between Parallel and Distributed Systems
• Shared Nothing Architecture
• Advantages of a “ shared nothing Architecture”
• CAP Theorem Explained
• CAP Theorem
3. Terminologies and its types
• In order to good handle on the big data environment.
• A few key terminologies in this arena
• The different types of terminologies are:
In-Memory Analytics
In-Database processing
Symmetric Multiprocessor system(SMP)
Massively Parallel Processing
Difference Between Parallel and Distributed Systems
Shared Nothing Architecture
CAP Theorem Explained
4. In-Memory Analytics
• Data access from non-volatile storage such as hard disk is a slow process
• The data is required to be fetched from hard disk or secondary storage
• One way combat this challenge is to pre-processor and store data
Example:
cubes, aggregate tables, query sets, etc…
• The initial process of pre-computing and storing data or fetching it from secondary storage
• The problem has been addressed using in-memory analytics
• All the relevant data is stored in Random Access Memory(RAM)or primary storage
6. In-Database processing
• In-database processing is also called as in-database analytics
• The data from various enterprise Online Transaction processing(OLAP) system after cleaning up
example:
de-duplication, scrubbing, etc…
• The huge datasets are then exported to analytical programs for complex and extensive computations.
• Leading database vendors are offering this feature to large business
7. Symmetric Multiprocessor system(SMP)
• SMP is a single common main memory that is shared by two or more identical processors
• To all I/O devices and are controlled by a single operating system instance
• SMP are tightly coupled multiprocessor systems
• Its own high-speed memory, called cache memory and are connected using a system bus
8. Massively Parallel Processing
• Massively Parallel Processing(MPP) refers to the coordinated processing of the programs by a number of
processors working parallel
• Each have their own operating system and dedicated memory
• They works on different parts of the same program
• SMP works with the processors sharing the same operating system and same memory
• SMP is also referred to as tightly-coupled multiprocessing
9. Difference Between Parallel and Distributed Systems
Parallel system Distributed system
Memory Tightly coupled system
shared memory
Weakly coupled system
Distributed memory
Control Global clock control No global clock control
Processor Interconnection Order of Tbps Order of Gbps
Main focus Performance Scientific
Computing
Performance(cost and
scalability) Reliability/
availability
information/resource
sharing
13. Shared Nothing Architecture
• The three most common type of architecture for multiprocessor high transaction rate system
• They are:
Shared Memory(SM)
Shared Disk(SD)
Shared Nothing(SN)
14. Shared Memory(SM)
• A common central memory is shared by multiple processors
Shared Disk(SD)
• Multiple processors share a common collection of disks while having their own private
memory
Shared Nothing(SN)
• If neither memory nor disk is shared among multiple processors
15.
16. Advantages of a “ shared nothing Architecture”
• Fault Isolation:
Its provides the benefit of isolating fault
A fault in a single node is contained and confined
That node exclusive and exposed only through message
• Scalability:
The disk is a shared resource
The controlled and the disk bandwidth are also shared state
A different nodes will have to take turns to access the critical data
A distributed shared disk system thus compromising on scalability
17. CAP Theorem Explained
• The CAP theorem is also called the Brewer’s theorem
• A collection of interconnection nodes that share data
• The three types of CAP theorem they are:
Consistency
Availability
Partition tolerance
18. CAP Theorem
• Consistency
A implies that every read fetches the last write
• Availability
A implies that reads and writes always succeed
Each non-failing node will return a response in a reasonable amount
of time
• Partition tolerance
It implies that the system will continue to function when network partition occurs
