US 11,768,834 B1Granted

Storing and querying general data type documents in SQL relational databases

AssigneeNewday Database Technology, Inc.

InventorBruce Amberden

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Abstract

Many types of data files can only be stored in SQL databases as Blobs—Binary Large Objects, that the database can only handle as a whole. This limits searches within the Blob. Here improved methods are taught for automatically analyzing potential Blob files, and assigning at least certain classes of potential Blob files to General Data Type documents. In some cases, the potential Blob may be automatically analyzed and mapped to a JSON document type, and this JSON document type then automatically mapped into appropriate lists of JSON-document-nodes and tables that can be stored in the SQL database, and subsequently queried. This enables much data within the (to prior art) Blob to be queried at more detailed granularity. This data can then be retrieved and used to reconstruct some or all of the original General Data Type document, which would otherwise be a Blob to prior art methods.

Claims20

Dependent claims

A method of storing and retrieving at least portions of General Data Type Documents (GDTD) using Structured Query Language (SQL) Relational Databases (SQL-RDB), said method comprising:

obtaining at least one GDTD formatted according to a General Data Type (GDT);
wherein said GDT comprises any of JavaScript Object Notation (JSON) document data types, markup language document data types, and text document data types;
wherein said General Data Type Document (GDTD) is a stand-alone, self-contained, single data set instance that conforms to at least one of said GDT;
wherein, for at least some of said GDT, a GDT relational schema that specifies how to transform said GDTD into at least one list of GDT-document-nodes and corresponding GTD-document-node records suitable for storage in data tables of said SQL-RDB is either known or can be identified;
wherein said GDT-document-nodes comprise tuples composed of GDT-structure fields and GDT-content-value fields, wherein said GDT-structure fields specify how to assemble lists of said GDT-document-nodes back into said GDTD;
selecting, using at least one computer processor and computer memory, at least one GDT relational schema specifying a mapping between at least one said GDTD and at least one said SQL-RDB;
using said GDT relational schema to convert said GDTD into a corresponding list of GDT-document-node records for insertion into matching schema-defined SQL-RDB tables;
generating and executing SQL select queries or SQL general join-select queries to search for specific sets of GDT-document-node records or joined GDT-document-node records in specific SQL-RDB tables;
returning those selected GDT-document-node records from those SQL-RDB tables that match said SQL select query or SQL general join-select queries;
reassembling said GDT-document-node records into at least portions of said GDTD by using said GDT-document-node records to assemble said selected GDT-document-node records back into at least portions of matching GDTD.

7 more elements

A system for storing and retrieving at least portions of General Data Type Documents (GDTD) using Structured Query Language (SQL) Relational Databases (SQL-RDB), said system comprising:

at least one processor and memory;
said at least one processor and memory configured to run at least one SQL RDB Management Application (SQL-RDBMA);
said at least one processor configured to obtain at least one GDTD formatted according to a General Data Type (GDT);
wherein said GDT comprises any of JavaScript Object Notation (JSON) document data types, markup language document data types, text document data types, and other document data types, and said General Data Type Document (GDTD) is a stand-alone, self-contained, single data set instance that conforms to at least one of said GDT;
wherein, for at least some of said GDT, said memory further comprises, or said processor is configured to obtain, a GDT relational schema that specifies how to transform said GDTD into at least one list of GDT-document-nodes and corresponding GTD-document-node records suitable for storage in data tables of said SQL-RDB;
wherein said GDT-document-nodes comprise tuples composed of GDT-structure fields and GDT-content-value fields, wherein said GDT-structure fields specify how to assemble lists of said GDT-document-nodes back into GDTD;
said at least one processor configured to select at least one GDT relational schema specifying a mapping between at least one said GDTD and at least one said SQL-RDB;
said at least one processor configured to use said GDT relational schema to convert said GDTD into a corresponding list of GDT-document-node records for insertion into matching schema-defined SQL-RDB tables;
said at least one processor configured to generate and execute SQL select queries or SQL general join-select queries to search for specific sets of GDT-document-node records or joined GDT-document-node records in specific SQL-RDB tables;
said at least one processor configured to return those selected GDT-document-node records from those SQL-RDB tables that match said SQL select query or SQL general join-select queries;
said at least one processor configured to reassemble said GDT-document-node records into at least portions of said GDTD by using said GDT-document-node records to assemble said selected GDT-document-node records back into at least portions of matching GDTD.

8 more elements

Dependencies are inferred from the claim text.