A. Platform overview

Project Information Management Platform (Group Level) ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l A tɔŋ "Internet + Intelligent Transportation" service model, ye cloud computing, big data and Internet of Things technology, integrate relevant core resources, to control, data, visualization for all-dimensional real-time regulation of project management, build a group project management big data center, build an internet collaboration, intelligent production, scientific management of construction project information ecosystem, and use this data in a virtual reality environment with the IoT gathered engineering information for data mining analysis, provide process trend prediction and expert projections, realize engineering construction visualization intelligent management, to improve project management information level, to provide big data services to the group through project's big data mining, big data analysis. Ka tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ tɛmɛ

II. Ajuiɛɛr Platform

Platform kënë bɛ kɛ̈ɛ̈l ye kɛ̈ɛ̈l ye kɛ̈ɛ̈l ye kɛ̈ɛ̈l ye kɛ̈ɛ̈l ye kɛ̈ɛ̈l ye kɛ̈ɛ

Platform kënë ye IoT, sensor technology tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈ɔ̈u bɛ̈n ya tɔ̈

Platform kënë ee tɛ̈n yenë kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔc ye kɔ

Platform kënë bɛ kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈

Platform kënë ee käke data management, application maintenance, ku data exchange subsystem looi ago käke data interaction ku operational maintenance kɛ̈k peei ya looi.

Platform kënë bɛ akutnhom de Big Data ya gäm në luɔɔi de Big Data Mining, Big Data Data Analysis.

3. Arkitektur Teknoloji Platform

HDFS: Hadoop Distributed File System (Hadoop Distributed File System) ye data access ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l ye kɛ̈l

Yarn: Hadoop 2.0 resource management system, a ye resource module ye kɔc bɛ̈ɛ̈i ye kɔc bɛ̈ɛ̈i ye kɔc bɛ̈ɛ̈i ye kɔc bɛ̈ɛ̈i ye.

Spark: One-stop distributed computing framework ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r ye kɛ̈ɛ̈r.

Elk: A bɛ SQL engine ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n ye kɛ̈n.

Storm: A distributed, reliable, and error tolerant real-time streaming data processing system, and provides query languages such as SQL (StreamCQL). Storm: A distributed, reliable, and error tolerant real-time streaming data processing system, and provides query languages such as SQL (StreamCQL). Storm: A distributed, reliable, and error tolerant real-time streaming data processing system

MPP: Large scale parallel processing database, provides high scale, high performance, high stability, low cost large scale parallel processing database, replaces traditional digital warehouse systems, to provide support for enterprise business decisions. MPP: Large scale parallel processing database, provides high scale, high performance, high stability, low cost large scale parallel processing database, replaces traditional digital warehouse systems, to provide support for enterprise business decisions.

4. Platform Features

Real-time processing: Platform ye data caching, distributed stream computing engine ye data collection real-time, real-time analysis and give results, support multiple data sources, processing speed, achieve high concurrency, high availability. Platform ye data caching, distributed stream computing engine ye data collection real-time, real-time analysis and give results, support multiple data sources, processing speed, achieve high concurrency, high availability.

Interactive query: stream data, file data and so on are organized through an interactive query engine according to a data model suitable for interactive query, to conduct interactive analysis and query of data.

Offline Processing: Data wɛ̈ɛ̈r laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar laar Ka tɛmɛ MapReduce, Spark, Hive wala Spark SQL.

Fusion Number Position: Fusion Number Position supports horizontal expansion, full-component HA, row mixing, extremely fast query analysis, compatible with traditional SQL, supports smooth application migration, solving traditional number positions' poor timeliness, scaling costs high, scaling disrupts business and other issues, achieving efficient business decisions.

5. Software interface diagram