GENERATING SQL QUERIES FROM DECLARATIVE QUERIES FOR SEMI-STRUCTURED DATA

• US 20170024434A1
• Filed: 02/11/2016
• Published: 01/26/2017
• Est. Priority Date: 07/24/2015
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Behnen, Marion E.
• Application Number:
  US15/041,129
• Publication Number:
  US 20170024434A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2452 Query translation
• CPC Class Codes: G06F 16/24534 Query rewriting; Transformation
• CPC Class Codes: G06F 16/284 Relational databases

Abstract

A method for generating database queries from declarative queries having a known syntax. The method includes a query preparation software receiving a declarative query for a relational database management system, in a known system form. The query preparation software then analyzes the declarative query to build a set of generic query tasks with identified data types. The query preparation software then optimizes the set of generic query tasks and builds a target database query from the optimized generic query tasks reflecting features of a target database. The method further includes submitting the target database query to the targeted database and receiving results from the target database query.

Claims

1. A method for generating database queries from declarative queries having a known syntax comprising:

receiving, by one or more processors, a set of JavaScript Object Notation (JSON) query statements and an identification of a target database that supports Structured Query Language (SQL) queries;

analyzing, by one or more processors, the set of JSON query statements to build a first set of generic language-independent query tasks with identified data types, wherein fields in the set of JSON query statements map to attributes in the first set of generic language-independent query tasks;

optimizing, by one or more processors, the first set of generic language-independent query tasks by performing one or more of;

adding tasks, re-arranging tasks, and combining subsets of tasks;

building, by one or more processors, a first target database query from the optimized first set of generic language-independent query tasks reflecting features of the target database;

submitting, by one or more processors, the first target database query to the target database;

receiving, by one or more processors, a declarative query that does not include a set of JSON query statements;

analyzing, by one or more processors, the declarative query to build a second set of language-independent generic query tasks with identified data types, wherein fields in the declarative query map to attributes in the second set of language-independent generic query tasks;

optimizing, by one or more processors, the second set of generic query tasks by performing one or more of;

adding tasks, re-arranging tasks, and combining subsets of tasks;

building, by one or more processors, a second target database query from the optimized second set of language-independent generic query tasks reflecting features of the target database;

submitting, by one or more processors, the second target database query to the target database; and

providing, by one or more processors, a user with an interface for adjusting specific features and/or properties in order to customize generation of subsequent target database queries.