The batch operating task for associating new insurance policies with historical policies is very time-consuming,

The execution of stored procedure for bank L’s loan agreements takes 2 hours, which seriously affects the whole batch operating task! How to solve it?

The backend for querying the current account details with Bank S’s mobile banking is Elastic Search, and the code table of business entities needs to be pre-associated redundantly with the detail wide table. When the business entity changes, the large table with hundreds of millions of data must be refreshed, which takes several hours.

Bank X divides its over 100 million customers into thousands of groups, hoping to calculate the intersection of any number of customer groups, filter by dimensions, and also hoping to obtain the results in seconds. Click to learn: Open-source SPL speeds up intersection calculation of customer groups in bank user profile by 200+ times

Current situation analysis

Bank B’s e-banking self-service analysis system (“the system” for short) needs to query the customer transaction details on the specified date, and the business personnel can set the filtering condition on the interface at will to filter and query in tens of millions of data per day. The query results are used to find the target customer, formulate the marketing plan and evaluate the effect of campaign and so on. However, the existing system can only support five concurrent accesses, which is far from meeting the access needs of a large number of business personnel.

Why does this happen? The reason is that the backend of the system is unable to support more concurrency accesses. The system is directly connected to its backend, i.e., bank B’s central data warehouse. The data warehouse, however, is not specially for the system but shared by the whole bank, and also undertakes other application tasks such as batch running. Since the data warehouse has 48 cluster nodes, almost reaching its upper limit, and cannot be expanded any more, it can only provide the system with five connections, and it is impossible to provide more. Moreover, despite there are five connections, it is difficult to ensure smooth use. Once the data warehouse performs other important tasks, the operation of the system will be very laggy. continue reading →

Only with one day is the query on detail data speeded up by more than 2000 times. It’s amazing! Click to learn more:Open-source SPL Speeds up Query on Detail Table of Group Insurance by 2000+ Times