Massively Parallel Processing (MPP)
GPTKB entity
Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:architecture
|
| gptkbp:can_be_used_with |
gptkb:Hadoop
gptkb:Spark |
| gptkbp:designed_for |
large-scale data processing
|
| gptkbp:developed_by |
various technology companies
|
| gptkbp:enables |
high performance computing
|
| https://www.w3.org/2000/01/rdf-schema#label |
Massively Parallel Processing (MPP)
|
| gptkbp:includes |
control nodes
data nodes |
| gptkbp:is_adopted_by |
gptkb:financial_services
government agencies large enterprises research institutions |
| gptkbp:is_beneficial_for |
data integration
real-time analytics business reporting |
| gptkbp:is_challenged_by |
network latency
data consistency issues data skew complexity of management |
| gptkbp:is_characterized_by |
fault tolerance
parallel execution scalability data distribution |
| gptkbp:is_compared_to |
distributed computing
shared memory systems |
| gptkbp:is_evaluated_by |
performance benchmarks
cost-effectiveness reliability assessments scalability tests |
| gptkbp:is_implemented_in |
data warehouses
cloud computing platforms |
| gptkbp:is_optimized_for |
read-heavy workloads
analytical queries |
| gptkbp:is_part_of |
data architecture
cloud architecture |
| gptkbp:is_supported_by |
distributed databases
parallel file systems |
| gptkbp:is_used_by |
data scientists
business intelligence tools |
| gptkbp:is_used_in |
big data analytics
data warehousing |
| gptkbp:requires |
high-speed interconnects
|
| gptkbp:supports |
gptkb:machine_learning
SQL queries data mining |
| gptkbp:uses |
multiple processors
|
| gptkbp:bfsParent |
gptkb:Amazon_Redshift
|
| gptkbp:bfsLayer |
5
|