MPP (Massively Parallel Processing) is a database architecture that distributes data across multiple CPUs and disks. It allows massive queries to be executed quickly by breaking them into smaller parallel queries. An MPP database distributes data across independent nodes that are managed by independent processing units, allowing hundreds of processors to work simultaneously on an application. MPP provides increased speed, scalability, and high availability needed to handle large and complex queries for big data.

1. Database Systems MPP
University Colegio Mayor de Cundinamarca
Realized: Andrés Alirio Barragán Idarraga
Jhonatan Yordano Lázaro Mejía

2. Database systems MPP

3. multiple sets of CPU and disk space
MPP is the most mature and proven
mechanism to store and analyze large
amounts of data.
It is equivalent to tens and hundreds of personal
computers each of which houses a small piece
of a large data set. this allows the execution of
the massive query quickly, since many smaller
independent queries are running simultaneously,
instead of a single large query.
An MPP database distributes the data in
Independent piers, managed by independent processing,
and the resources of the central processing unit (CPU)

4. MPP
Conceptually, it is the same as having
pieces of data loaded in multiple
networks, connected to personal
computers hosted in the same host
(host). MPP is the coordinated
processing of a program by multiple
processors that work in different parts of
the program, and with each of the
processors using its own operating
system and memory. Normally, MPP
processors communicate using some
messaging interface. In some
implementations, hundreds of
processors can work in the same
application.

5. In essence, parallel processing is
becoming very important in the world of
database computing.
This involves taking a large task,
dividing it into smaller tasks, and then
working with each of these smaller
tasks simultaneously (Mahapatra,
2010). The objective of this "divide and
conquer" approach is to complete the
more complex task in a shorter time
than what it would have taken to
complete a large part.

6. Three reasons are confirming the use of database
processing:
1
Need for increased speed and performance(database sizes are
increasing, queries are becoming more complex- especially in data
warehouse systems- and database software must cope in some
way to the growing demands that derive from this complexity).
2
Need for scalability.The databases grow rapidly and the companies
need a means to scale (upload their services) easily and with the
minimum cost.
3 Need for high availability.It refers to the need to maintain a
database and execute it with minimal or no delay. The companies
need to accompany users 24 hours a day with the growing use of
fixed and mobile internet.

7. One known application of MPP is Kognitio WX2,
which uses the full power of basic hardware to
provide a fast means of accessing massive volumes
of data without the need for any indexing technique.
Other typical applications of MPP are Oracle
Parallel Server, and the Greenplum database that
works well with MPP.
MPP

8. MPP databases typically provide an SQL interface and a
relational database management system (RDBMS) that runs on
a cluster of servers connected to each other by high-speed
interconnection. The figure shows the components of an
RDBMS that is normally included in SQL-en-Hadoop
solutions.