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Description
YARN's core concept revolves around the division of resource management and job scheduling/monitoring into distinct daemons, aiming for a centralized ResourceManager (RM) alongside individual ApplicationMasters (AM) for each application. Each application can be defined as either a standalone job or a directed acyclic graph (DAG) of jobs. Together, the ResourceManager and NodeManager create the data-computation framework, with the ResourceManager serving as the primary authority that allocates resources across all applications in the environment. Meanwhile, the NodeManager acts as the local agent on each machine, overseeing containers and tracking their resource consumption, including CPU, memory, disk, and network usage, while also relaying this information back to the ResourceManager or Scheduler. The ApplicationMaster functions as a specialized library specific to its application, responsible for negotiating resources with the ResourceManager and coordinating with the NodeManager(s) to efficiently execute and oversee the execution of tasks, ensuring optimal resource utilization and job performance throughout the process. This separation allows for more scalable and efficient management in complex computing environments.
Description
Elastic Cloud Server (ECS) offers secure and scalable computing resources that can be accessed on-demand, allowing for the flexible deployment of various applications and workloads. It ensures worry-free protection through comprehensive security measures. General computing ECSs strike a balance between computing power, memory, and network resources, making them suitable for applications with light to moderate workloads. For applications that handle substantial data volumes, memory-optimized ECSs with extensive memory capabilities and support for ultra-high I/O EVS disks and adaptable bandwidths are ideal. Alternatively, disk-intensive ECSs cater to applications that require efficient sequential read/write operations on massive datasets stored locally, such as those used in distributed Hadoop environments, along with large-scale parallel data processing and log management. These disk-intensive ECSs are compatible with HDDs, come with a standard network bandwidth of 10GE, and provide high packets per second (PPS) performance with minimal network latency, making them well-suited for demanding data-intensive tasks. Overall, ECS offers versatile options tailored to meet diverse computing needs in various industries.
API Access
Has API
API Access
Has API
Integrations
ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Astera Dataprep
Cloudera Data Platform
DX Unified Infrastructure Management
Huawei Cloud
Huawei Cloud Elastic Volume Service
Hue
Integrations
ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Astera Dataprep
Cloudera Data Platform
DX Unified Infrastructure Management
Huawei Cloud
Huawei Cloud Elastic Volume Service
Hue
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$6.13 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Apache Software Foundation
Founded
1999
Country
Uniited States
Website
hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html
Vendor Details
Company Name
Huawei
Founded
1987
Country
China
Website
www.huaweicloud.com/intl/en-us/product/ecs.html