使用YARN Hadoop的公司
Its fundamental idea is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM).
使用YARN Hadoop的公司列表
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"yarn-hadoop\"
]
}"Technology
is any of
YARN Hadoop
员工数7.2k收入$30MSoftware DevelopmentYARN Hadoop中置信度
员工数8.9k收入$1.9BSoftware DevelopmentYARN Hadoop低置信度
员工数360IT Services and IT ConsultingYARN Hadoop低置信度
员工数4收入$3.1MTravel ArrangementsYARN Hadoop低置信度
员工数297IT Services and IT ConsultingYARN Hadoop低置信度
员工数73k收入$6BSoftware DevelopmentYARN Hadoop低置信度
员工数1.4k收入$520MTechnology, Information and MediaYARN Hadoop低置信度
我们拥有关于8家公司和用户使用YARN Hadoop的数据。我们的YARN Hadoop用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 YARN Hadoop 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
YARN (Yet Another Resource Negotiator) is a cluster management technology that plays a fundamental role in Apache Hadoop. It is designed to manage resources and schedule tasks efficiently in a distributed environment. YARN serves as the architectural center of Hadoop, separating the resource management and job scheduling/monitoring functions, enabling Hadoop to support more varied processing approaches and a broader array of applications.
YARN Hadoop falls under the category of Cluster Management, which involves the management of resources across a cluster of machines. In the context of YARN Hadoop, it specifically focuses on efficiently allocating resources like CPU and memory to applications running on a Hadoop cluster. By providing a flexible and scalable framework for resource management, YARN allows organizations to run a wide range of distributed applications effectively.
Initially introduced in 2012 by Hortonworks, YARN Hadoop emerged as a significant advancement in the Hadoop ecosystem, addressing the limitations of the previous Hadoop MapReduce framework. The motivation behind creating YARN was to enhance the performance, scalability, and flexibility of Hadoop by decoupling resource management from job scheduling. This architectural shift laid the foundation for a more versatile and robust Hadoop framework, enabling businesses to process and analyze vast amounts of data more efficiently.
Currently, YARN Hadoop holds a considerable market share within the Cluster Management category, being widely adopted by organizations seeking to harness the power of distributed computing for big data processing. With the increasing demand for scalable and efficient data processing solutions, the market share of YARN Hadoop is expected to grow in the future. As businesses continue to leverage big data analytics for gaining insights and driving decision-making, technologies like YARN Hadoop will play a crucial role in enabling data-driven innovation and growth.