Statements (54)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:engine
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Spark_SQL
|
| gptkbp:constructed_in |
Spark's execution model
|
| gptkbp:developed_by |
gptkb:software_framework
|
| gptkbp:enables |
distributed computing
advanced optimizations |
| gptkbp:enhances |
gptkb:Spark's_Catalyst_optimizer
query execution |
| gptkbp:facilitates |
gptkb:software_framework
|
| gptkbp:focuses_on |
performance optimization
|
| https://www.w3.org/2000/01/rdf-schema#label |
Tungsten execution engine
|
| gptkbp:improves |
gptkb:resource_utilization
memory management CPU efficiency |
| gptkbp:increased |
gptkb:benchmark
|
| gptkbp:introduced |
gptkb:Spark_1.4
|
| gptkbp:is_compatible_with |
gptkb:park
cloud platforms various data sources |
| gptkbp:is_designed_for |
big data processing
high throughput |
| gptkbp:is_designed_to |
handle complex queries
|
| gptkbp:is_effective_against |
iterative algorithms
|
| gptkbp:is_enhanced_by |
code generation techniques
|
| gptkbp:is_integrated_with |
Data Frames
machine learning libraries |
| gptkbp:is_optimized_for |
data processing
low latency in-memory computing modern hardware |
| gptkbp:is_part_of |
gptkb:Spark_SQL
big data solutions Apache Spark ecosystem data processing frameworks |
| gptkbp:is_scalable |
large datasets
|
| gptkbp:is_used_for |
real-time data processing
data warehousing |
| gptkbp:is_used_in |
ETL processes
data analytics |
| gptkbp:is_utilized_in |
data scientists
|
| gptkbp:provides |
data locality
stream processing capabilities whole-stage code generation |
| gptkbp:reduces |
latency
data serialization costs garbage collection overhead |
| gptkbp:supports |
SQL queries
data transformations RD Ds off-heap storage |
| gptkbp:used_in |
gptkb:park
|
| gptkbp:utilizes |
binary format
|
| gptkbp:written_in |
gptkb:Skrull
|