|
gptkbp:instance_of
|
gptkb:Joint_Task_Force
|
|
gptkbp:can
|
long-running tasks
tasks across clusters
|
|
gptkbp:can_be_configured_for
|
YAML files
|
|
gptkbp:can_be_extended_by
|
custom plugins
|
|
gptkbp:can_be_used_for
|
gptkb:machine_learning
data analysis
ETL processes
data visualization
data pipelines
|
|
gptkbp:can_be_used_in
|
cloud environments
local environments
|
|
gptkbp:can_be_used_to
|
scale applications
|
|
gptkbp:can_be_used_with
|
gptkb:XGBoost
gptkb:Tensor_Flow
gptkb:Python
gptkb:Py_Torch
|
|
gptkbp:can_handle
|
large datasets
streaming data
|
|
gptkbp:designed_for
|
parallel computing
|
|
gptkbp:enables
|
scalable data processing
|
|
gptkbp:has
|
web-based dashboard
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Dask Scheduler
|
|
gptkbp:integrates_with
|
gptkb:Pandas
gptkb:Num_Py
gptkb:Scikit-learn
|
|
gptkbp:is_available_on
|
gptkb:Git_Hub
|
|
gptkbp:is_compatible_with
|
gptkb:Jupyter_notebooks
|
|
gptkbp:is_designed_for
|
high-performance computing
|
|
gptkbp:is_documented_in
|
Dask documentation
|
|
gptkbp:is_integrated_with
|
gptkb:Kubernetes
gptkb:Apache_Spark
gptkb:Docker
gptkb:Ray
|
|
gptkbp:is_maintained_by
|
Dask community
|
|
gptkbp:is_open_source
|
gptkb:true
|
|
gptkbp:is_optimized_for
|
task dependencies
task execution
|
|
gptkbp:is_part_of
|
gptkb:Dask.distributed
|
|
gptkbp:is_used_by
|
gptkb:researchers
data scientists
data engineers
|
|
gptkbp:manages
|
distributed computing resources
|
|
gptkbp:monitors
|
task progress
|
|
gptkbp:part_of
|
gptkb:Dask
|
|
gptkbp:provides
|
fault tolerance
real-time monitoring
dynamic task scheduling
API for task submission
|
|
gptkbp:supports
|
asynchronous programming
task scheduling
multi-threading
multi-processing
|
|
gptkbp:utilizes
|
worker nodes
|
|
gptkbp:written_in
|
gptkb:Python
|
|
gptkbp:bfsParent
|
gptkb:Dask
|
|
gptkbp:bfsLayer
|
5
|