SQL Dialect for Dimensional Database Querying
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Solution Overview
Problem
Users face difficulties in accessing and querying dimensional databases due to the lack of SQL-based access, requiring specialized programming to combine data with non-dimensional databases, which is problematic for those without a programming background and limits the utilization of dimensional databases.
Innovation Solution
A SQL dialect is developed to enable querying and combining data from dimensional and non-dimensional data stores using a single query, allowing dimensions and measurements to be included in SELECT statements and utilizing table-identifier prefixes to specify each table, thereby facilitating access and manipulation of data across different database types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a specialized query language like MDX is used to access dimensional databases, then the database can provide aggregated data views and support dimensional analysis, but users without programming background find it difficult to query and the syntax is different from SQL
Solution Approach 1:
The patent introduces an intermediary layer that translates SQL queries into dimensional database query language (MDX). This mediator component allows users to continue using familiar SQL syntax while the system automatically converts it to the appropriate dimensional query language, thus maintaining ease of operation while preserving dimensional database query capabilities
Solution Approach 2:
The patent makes the dimensional database query system universal by enabling it to accept standard SQL queries in addition to native dimensional query language. This multi-functionality allows the system to serve both traditional SQL users and advanced dimensional analysis users through a single interface, improving accessibility without sacrificing specialized capabilities
2Adaptability or versatility
If specialized programming is required to combine data from dimensional and non-dimensional databases, then data integration can be achieved, but the complexity increases and limits utilization by users without programming background
Solution Approach 1:
The patent merges the querying of dimensional and non-dimensional databases into a single unified SQL query interface. Instead of requiring separate programming approaches for each database type, the system allows users to combine queries across both database types using standard SQL syntax, thus reducing complexity while maintaining integration capabilities
Solution Approach 2:
The patent segments the query processing into distinct components: the SQL parser, the query translator, and the execution engine. This segmentation allows the system to handle different database types through modular processing steps, making the overall complex task of integrating dimensional and non-dimensional data manageable through standardized interfaces
Data Source
AI summary
In one embodiment, a method includes defining a slice of a dimensional database. The slice includes at least one dimension and at least one measurement and is expressable as a table. The method further includes building, in a structured query language (SQL) dialect, a single query that queries the slice and one or more non-dimensional databases. The SQL dialect represents the at least one dimension, the at least one measurement, and data attributes of the one or more non-dimensional databases. In addition, the method includes parsing the single query. The parsing includes generating a dimensional query for the dimensional database and a non-dimensional query for each of the one or more non-dimensional databases. Furthermore, the method includes executing the dimensional query on the dimensional database. Moreover, the method includes, for each non-dimensional database of the one or more non-dimensional databases, executing the non-dimensional query on the non-dimensional database.