关键词: 工业大数据, 联机分析处理(OLAP)模型架构, 多维分析, JSON文档结构

Abstract: The growing industrial big data made data analysis and mining extremely complicated since they had complex correlations and multi-source heterogeneous characteristics in the intelligent manufacturing processes. However, the traditional industrial big data analysis approach based on the relational database or data warehouse was not flexible to deal with multi-source heterogeneous data and was less efficient to do search and analysis operations. An OLAP model architecture of industrial big data was presented based on JSON document structure, which might use Key-Value data to flexibly define diverse industrial data structure. The table structure in the dimensional information was converted into a JSON-based document structure, and the dimensional information contained in the fact table was stored by nested document. Then constructing a document tree and the analysis target was the root node, and used Elasticsearch to store the document structure tree and built an inverted index, which might improve the efficiency of the data analysis query. The query and analysis operations were transformed into the traversal and query operations in the document contents. An intelligent parsing engine which might design custom search conditions and query statements was realized to generate intelligent visualization chart related to multidimensional industrial data.

Key words: industrial big data, online analytical processing(OLAP) model architecture, multi-dimensional analysis, JSON document structure