Ad hoc queries allow you to flexibly SELECT query conditions based on your needs. The system can generate corresponding statistical reports based on your needs. Ad hoc queries are the most different from normal application queries. Ad hoc queries are customized and developed by users. Ad hoc queries have a concept in the data warehouse field called ad hoc queries ". Ad hoc queries refer to queries defined by users based on their current needs when using the system. Ad hoc queries are generated in many ways. The most common method is to use the ad hoc query tool. Common Data presentation tools provide ad hoc queries. The common method is to map dimension tables and fact tables in the data warehouse to the semantic layer. You can select tables at the semantic layer to establish associations between tables and generate SQL statements. Ad-hoc queries and general queries have no essential difference in SQL statements. The difference between them is that the common query is known in system design and implementation, and we can optimize these queries by building indexes, partitions, and other technologies during system implementation, these queries are highly efficient. Ad hoc queries are produced temporarily when users are using them, and the system cannot optimize these queries in advance. Ad hoc queries are also an important indicator for evaluating data warehouses. Ad hoc queries are usually located in a relational data warehouse, that is, EDW or ROLAP. Multi-dimensional databases have their own storage methods. Ad hoc queries are no different from normal queries. In a data warehouse system, the more ad hoc queries are used, the higher the requirements for data warehouses and the higher the requirements for data model symmetry. The symmetric Data Model is the same for all queries, which is also an advantage of dimensional modeling.
Ad hoc query
