Big data technology architecture diagram
2024-09-09 10:25:34 3 Report
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This is a big data technology architecture diagram, designed to illustrate the complex ecosystem of components and processes involved in handling large-scale data operations. The diagram includes elements such as real-time calculation, machine learning, and data storage solutions like MongoDB and HDFS. Key technologies like Kafka, Spark Streaming, and TensorFlow facilitate data processing, while platforms like ElasticSearch and Redis Cluster ensure efficient data retrieval and caching. The architecture supports various services including intelligent recommendations, statistical analysis, and metadata management, all orchestrated through a robust infrastructure involving microservices, message queues, and open-source software.
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Outline/Content
Real-time calculation
MongoDB
Sqoop
Research statistical services
Metadata Management Platform
OpenCV
Machine Learning
Intelligent services
Processing
Intelligent Recommendation Engine
TensorFlow
Statistical analysis library
Analyzing Microservices
Log data
Operations personnel
Storm
Kafka
Spark Streaming
conversion
Model training
ElasticSearch
Document data
Business data
RDBMS
Process data
Flume
Open Platform
Storage layer
Data management repository
RDS
Operation and Maintenance Platform
Cleaning
Product
document
Extract
Development platform
Message Queue
Open SDK
Developer
Redis Cluster
Classification
Cache
BOSS
DataHub
Spark SQL
Open API
middle layer
Kettle
Analysis
Data Service Layer
Task scheduling platform
Data Application Layer
Data中台
Financial statistical services
HBase
Intelligent dispatching engine
deduplication
Operations and maintenance personnel
ElasticSearch cluster
AI Intelligence
HDFS
Source data
Computational layer
Alert Monitoring Platform
Operation and Maintenance Management
Data Quality Platform
Financial data
Industry data
Offline computing
Hive/Pig
Government and enterprise data
User data
Open Source Software
Mahout
Map/Reduce
screen
User statistics service
LogStash
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