In large IT companies, especially like Google or Baidu, code search is an indispensable and frequent activity in the software development process, which speeds up the development process by learning or reusing existing code. Over the years, a large number of researchers have focused on code search and designed many excellent tools. However, the existing research and tools are mainly on a small-scale or single programming language code data set, not from the actual requirement of industries, and the user's query input is also limited; there is still a lack of a set of industrial-scale massive code retrieval and management technology solutions. This study proposes a code search engine solution and system implementation based on industrial-scale massive data, oriented to the most direct needs of users in the development process, through offline analysis and online analysis, complete the index construction and retrieval of massive code base. Among them, offline analysis is responsible for the acquisition and analysis of code-related data and building an index cluster. The online process is responsible for transforming the user's query, sorting the results of the search, and generating a summary. The system is deployed on the Baidu code base, and the index is built for dozens of TB-level Git code bases. The average retrieval time is within 1s. Since the launch of Baidu's application, the number of visits has gradually increased. There are thousands of users per week and tens of thousands of times searching. The system is widely praised by Baidu engineers.