Title :
IBDP: An Industrial Big Data Ingestion and Analysis Platform and Case Studies
Author :
Cun Ji;Shijun Liu;Chenglei Yang;Lei Wu;Li Pan
Author_Institution :
Sch. of Comput. Sci. &
Abstract :
The Internet of Things (IoT) brings traditional Internet industry and society with new trends and promising technologies. For industrial information with high amount and renewal speed characteristics, resulting in difficult data ingestion and analysis, this paper presented an Industrial Big Data ingestion and analysis Platform (IBDP). In the platform, we integrated HDFS, Spark, Hive, HBase, Flume, Sqoop, OpenStack etc. It works well for industrial data ingestion and analysis. In addition, we report some case studies on industrial big data processing flows respect to different data types.
Keywords :
"Big data","Sparks","Crawlers","Heating","Real-time systems","Distributed databases","Data analysis"
Conference_Titel :
Identification, Information, and Knowledge in the Internet of Things (IIKI), 2015 International Conference on
DOI :
10.1109/IIKI.2015.55