Book: Advanced ANSI SQL Dynamic Data Structure Modeling and Hierarchical Processing, new edition published by Artech House Publishers 2013. This new book edition describes and demonstrates powerful new dynamic hierarchical processing capabilities and discusses the new hierarchical discoveries that made them possible. These new capabilities should make their way into mainstream SQL use. Readers will be able to experiment with these new hierarchical capabilities using the available SQL hierarchical prototype.
A Complimentary Structured Data Query Language to Google’s Dart, SOA World Magazine, September 21, 2011, Dart is a new structured data programming language from Google. While unstructured data has become extremely useful, structured data is still extremely important because it keeps businesses running day in and day out. Programming languages still need to be coded by hand and most Google users are not programmers. To fill this large gap for most Google users who have no programming experience, a structured data query language would be very useful. Query languages operate by what data or information is wanted and not how to access or derive it. No programming is necessary to use. This is very similar to a standard Google request. This allows anyone to specify a powerful structured data query request. http://soa.sys-con.com/node/1989463 Dynamic Structured Data Processing and Its Automatic Metadata Maintenance,TDAN, The Data Administration Newsletter, Sept. 1, 2011, There is no reason that highly principled structured data processing has to be limited to static data structures. Static structured data processing is to dynamic structured data processing what the teletype is to the telephone. Dynamic structure data can be several orders of magnitude greater than static structured data for ease of use, flexibility and solving problems. This opens up an entirely new, faster, easier and more powerful world of uses for structured data. This flexible dynamic structured processing allows changes to the structure of the data as it becomes necessary to solve the problem at hand. This article presents an example of such a dynamic structured data processing example and how it operates.
SQL Peer-to-Peer Dynamic Structured Data Processing Collaboration, SOA World Magazine, June 18, 2011, Unstructured and XML semi structured data is now used more than structured data. Unstructured data is useful because of its fuzzy processing applied to this more common ubiquitous data. But fixed structured data still keeps businesses running day in and day out which requires consistent predictable highly principled processing for correct results. This means structured data cannot be replaced by unstructured or semi structured data. For this reason, it would be very useful to have a general purpose peer-to-peer collaboration capability that can utilize highly principled hierarchical data processing and its flexible and advanced structured processing to support dynamically structured data and its dynamic structured processing. This flexible dynamic structured processing can change the structure of the data as necessary for the required processing while preserving the relational and hierarchical data principles and semantics of the data to derive correct structured data results even after structure transformations. http://soa.sys-con.com/node/1875139 SQL Transparent Hierarchical Processing of Relational, XML and IMS Data, XML Magazine, April 7th, 2011, Current SQL support of relational, XML and hierarchical legacy data such as IMS is driven by flattening the hierarchical data in order to integrate it naturally with relational (flat) data so that it can be processed relationally. Unfortunately, this strips out the natural semantics in hierarchical data which has the capability to dynamically increase the value of the data being processed and to perform powerful hierarchical operations. The SQL-92 standard introduced the LEFT Outer Join which offers a powerful alternative to standard relational processing that can be used to perform full hierarchical processing naturally and inherently. Thisenables SQL to seamlessly and transparently integrate relational data at a full hierarchical structured data processing level with XML, IMS and other forms of legacy hierarchical data. This will be covered in this article.
Naturally Increasing Data Value with Hierarchical Structures, XML Magazine, March 10, 2011. Hierarchical structures have an inherent ability for significant data value increases beyond the data collected. This will be shown to exist in hierarchical structures and even more powerfully in their natural hierarchical processing capabilities. These demonstrate flexible and efficient ways to increase data value automatically and will be discussed in this article. SQL will be used to perform a wide range of hierarchical processing operations that easily demonstrate these increasing data value capabilities.
ANSI SQL Can Combine Advantages and Principles of Relational and Hierarchical Data Processing, Database Journal, Jan. 20, 2011, This article describes how relational and hierarchical data processing can be seamlessly combined in a way that supports and preserves both hierarchical and relational processing advantages while avoiding their disadvantages.
The Top 10 SQL Hierarchical Data Processing Capabilities, Database Journal, December 12, 2010,The article describes a list of ANSI SQL's most useful and powerful hierarchical capabilities. These capabilities are tightly integrated and build upon each other. For this reason they are specified in this building block order: http://www.databasejournal.com/features/article.php/3915331/article.htm
Extending SQL's Inherent Hierarchical Processing Operation, Database Journal, November 18, 2010, This article covers multipath operations that require a different hierarchical logic than SQL naturally produced hierarchical processing. These include nonlinear data ordering, the automatic renormalization of data to remove replicated data, and the dynamic navigationless hierarchical query processing of network structures. http://www.databasejournal.com/features/mssql/article.phpr/3912771/article.htm
Hierarchical Data Structure Virtualization in SQL,Database Journal, October 20, 2010, Data structure virtualization is the constructing of a data structure utilizing pieces or fragments from other data structures. This article demonstrates how Data structure virtualization can be done in ANSI SQL utilizing hierarchical processing techniques to produce hierarchically structured virtualized output.
A YesSQL Cloud Alternative,Database Journal, Sept 16 2010, A lot has been written about the "NoSQL" alternative as an alternative to SQL and other large database systems for a lighter, faster, cheaper alternative for the cloud. Most of these light weight database processors ignore data processing principles and lack the ability to turn data into information. This SQL trade-off may not be necessary by using SQL hierarchical processing as described in this article. http://www.databasejournal.com/features/article.php/3903626/article.htm
Hierarchical Data Structure Transformation in SQL, Database Journal, August 17, 2010, The two basic types of data structure transformation terms, Restructuring and Reshaping, are used interchangeably with data structure transformations. This article categorizes and defines these two types of data structure transformations. It uses SQL to demonstrate these different structure transformations by using SQL's natural hierarchical data structure processing capability along with data fragment manipulation.
Dynamic Data Driven Variable Hierarchical Structures in SQL, Database Journal, July 16, 2010, SQL can support the creation of variable hierarchical structures in a number of differently controlled operations that can be combined. Three have been shown in the previous articles in this series on SQL Hierarchical Processing. These have been dynamic: hierarchical structure data modeling; hierarchical structure joining; and SQL's variable SELECT list to specify the output. This article describes data driven variable structure generation and in a future article variable structure creation will be described using structure transformations. All of these different structure operations all generate structures in a different way.
Extending Hierarchical Data Modeling Demonstrated in SQL, Database Journal, June 18, 2010, The capability of extending the limits of combining multiple node hierarchical structures has not been fully explored. This article presents a solution to advanced structure combining that is simple to use, generic and freely extends the way hierarchical structures can be semantically combined to produce advanced new hierarchical data structure mashups that dynamically increase the value of the data.
The Power Behind SQL's Inherent Multipath LCA Hierarchical Processing, Database Journal, May 20, 2010. This article describes the advanced capabilities of hierarchical multipath query processing by demonstrating the little known Lowest Common Ancestor (LCA) processing that enables multipath hierarchical query processing to always produce correct meaningful results automatically. It will explain how multipath processing dynamically increases the data value of the data by accurately querying it from multiple pathways.
SQL's Optimized Hierarchical Data Processing Driven by its Data Structure,Database Journal, April 21, 2010. This article demonstrates how hierarchical data processing can be optimally driven automatically by its hierarchical structure semantics. When applied to SQL hierarchical data processing, this structured semantics offers optimization beyond current relational processing. In addition, this hierarchical optimization works with SQL dynamic processing and offers new relational capabilities.
ANSI SQL Hierarchical Data Processing Basics,Database Journal, March 17, 2010. The SQL-92 standard unknowingly and without planning introduced the capability to perform full hierarchical data processing with its introduction of the LEFT Outer Join operation. This natural hierarchical processing capability and its application for automatic and transparent XML processing will be explained in this article.
Ten Problems with XQuery and the SQL/XML Standard, Database Journal, February 17, 2010. XQuery and SQL/XML standard are processors for XML. The design and development of these two XML processors also influence the capabilities that each other have. SQL/XML was designed to try to match the capabilities of XQuery as closely as possible and XQuery was designed not only to support XML, but also to support relational processing. Therefore, these two products do affect each other, which may negatively influence their capabilities by retarding their natural and separate growth pattern and directions. These problems are covered in this article and also how they can be solved with ANSI SQL's natural hierarchical capability.
Controlling Hierarchical Structure Processing From SQL TDAN, The Data Administration Newsletter, January 1, 2010.This article presents some of the more powerful and advanced hierarchical processing operations and capabilities possible with ANSI SQL hierarchical full multipath processing. This is the third TDAN.com article in a series on using ANSI SQL's inherent hierarchical processing to integrate and process relational and XML data at a full hierarchical processing level. It presents some of the more powerful and advanced hierarchical processing operations and capabilities possible with ANSI SQL hierarchical full multipath processing. These include heterogeneous structure integration, hierarchical structure data mashups, hierarchical processing optimization, global hierarchical views and queries, hierarchical data filtering, dynamic structure control, and dynamic structured XML output.
Creating More Value than is Captured with Hierarchical Data Structures Using SQL, TDAN, The Data Administration Newsletter, October 1, 2009. This article explores the ways hierarchical structures can be used to significantly increase data value and its utilization. Hierarchical structures are very unique not only in how well they organize data, but also in how they naturally capture more meaning than is stored with the data. Even more impressive is their ability to dynamically process this natural goldmine of meaning in unlimited ways that further increases the value of the stored data. With the increased use of hierarchical XML data structures today, there is an incredible amount of unused data value potential available.
The Ghost in the Machine, ANSI SQL Inherent Hierarchical Data Processing , TDAN, The Data Administration Newsletter, August 1, 2009. Hierarchical processing is still being limited to flat two dimensional linear path processing by relational processing. This will change when database professionals realize that ANSI SQL relational processing can now support full multipath nonlinear hierarchical processing. The physical or scientific proof that this technology exists and works can be difficult to find since relational processing was not designed to support full hierarchical processing and could be hiding in plain site or buried deep in the relational engine. This article will find it and expose it.
The Semantics of Meaningful XML Keyword Search using SQL,Semantic Universe web site, April 15, 2009. This article explains how ANSI SQL’s natural Lowest Common Ancestor (LCA) processing solves the XML Keyword Search Problem by eliminating unmeaningful results. The solution explained in this article can be used for other semantic web uses to eliminate unmeaningful results for hierarchical structured data sources.
Performing Hierarchical Restructuring Using ANSI SQL, DevX, April 15, 2009. This article explains how ANSI SQL processing can support full nonlinear hierarchical restructuring transformations. It describes a number of techniques involved and explains why this processing works and is hierarchically accurate.
Automatic Full Parallel Processing of Hierarchical SQL Queries, DevX, Feb 22, 2009. Because they're fully and naturally parallelizable, hierarchical structures can be processed in parallel automatically, which in turn enables automatic, efficient, and optimized use of multicore processors at a level not achieved before. This article shows how to implement a complete and automatic parallel processing solution for hierarchical query processing. Making the process automatic is critical, because hardware manufacturers aren't likely to stop at two, four, or eight cores in chips; future chips will have 64 or even 128 cores. The only way to use all these cores effectively is to make the process automatic. http://www.devx.com/SpecialReports/Article/40939/1954?pf=true
ANSI SQL Semantically Controlled Any-to-Any Data Structure Reshaping, Semantic Universe web site, Feb 20, 2009. This article describes how ANSI SQL can perform breakthrough any-to-any hierarchical data structure reshaping. These are transformations that are performed utilizing only the structure semantics in the data assuring correct semantic results:
Creating Hierarchical Data Structure Mashups, DevX, Jan 15, 2009. This article describes how ANSI SQL can define complex logical relational and physical XML hierarchical structures and then join these complex heterogeneous hierarchical structures together dynamically in any way. It also describes a breakthrough in hierarchical data modeling.
Navigationless Database XML: Hierarchical Data Processing, DevX, Sept 23, 2008. This article explains that current XML hierarchical database query processing is basically limited to single path linear hierarchical processing. Eliminating manual navigation from database XML processing removes these XML limitations, allowing navigationless structure processing to be unrestricted and performed automatically. This article describes how business applications can take advantage of these powerful new capabilities stemming from properly processed database XML data, using advanced hierarchical processing. It also delves into the underlying hierarchical structure principles and processing.
Where is the Query in XQuery ? TDAN, The Data Administration Newsletter, July 1, 2008.This article points out the important query characteristics missing from XQuery. It does this by comparing XQuery to SQLfX®, an ANSI SQL hierarchical XML query processor.
XPath Navigation Holding Back the SQL/XML Database Industry, Ken North’s SQL Summit Site, Jan 18, 2008. This original article identifies the advantages that are gained from navigationless XML access and processing for XML databases. XML was designed for markup and its hierarchical relationships which exceeds standard database hierarchical relationships and principles. Standard database processing with its limited standard hierarchical relationships can be processed navigationless allowing it to support more complex full multi-leg hierarchical processing and this article explains these additional capabilities.
XML Restructuring and Reshaping Should Not be Considered the Same, Ken North’s SQL Summit Site, May 9, 2007. This original article identifies and makes clear the differences between the two types of structure transforms and associates them with the different terms restructuring and reshaping. It then gives examples of both with a method that uses a conceptual model. The conceptual model works with both Restructuring and Reshaping that operates on both linear and nonlinear structures. The structure transformation can also transform linear structures to nonlinear structures and visa versa.
What's Still Wrong With SQL Native XML Integration Solution,DM Review Direct Newsletter 12/9/06. Same lack of progress in the SQLXML integration marketplace. Nonlinear processing is where we should be headed with its accurate and nonprocedural hierarchical processing that leverages the natural capabilities in the XML databases and SQL hierarchical processors. This is where SQLfX® is taking us.
XML Nonlinear Processing Limitations Due to Relational Mindset, DM Review Direct Newsletter, May 28, 2006. This article describes nonlinear hierarchical processing, its advanced capabilities, and how they extend beyond linear hierarchical processing. The XML industry today has limited itself to linear processing which requires procedural type navigation and operations. The current XML hierarchical processing today is not based on a principled hierarchical processing foundation because of its procedural operation. Nonlinear processing is nonprocedural and is based solidly on hierarchical principles that are automatically applied for the user regardless of the number of legs that require access in the query.
A Platform-Neutral Solution to Native XML Integration with SQL,Ken North’s SQL Summit Site, Dec 4, 2005. This article suggests a solution for XML integration is to use the hierarchical processing capabilities defined by SQL-92. It explores reasons behind the current SQL native XML integration industry’s slow start, what we should expect from this type of product, what is actually possible, and what hurdles are in the way to accomplish possible advances.
SQL Has It and XQuery Does Not-- Automatic LCA Processing, DM Review Direct Newsletter, July 29, 2005. This article points out that ANSI SQL can nonprocedurally hierarchically process multi-leg hierarchical structures while XQuery requires the user to procedurally specify the multi-leg hierarchical processing that is necessary to process the query. The reason for this is that ANSI SQL automatically supports Lowest Common Ancestor (LCA) logic which is necessary for multi-leg hierarchical processing, and XQuery does not automatically support LCA logic. This requires the XQuery user to specify this complex logic.
Can SQL be Saved FROM XML?, DM Review Direct Newsletter, June 24, 2005. This articledescribes all the bad things that are happening to ANSI SQL in order to support XML at all cost. The article goes on to show why all of these unsound changes to SQL ideology are not necessary because ANSI SQL can automatically support them without change and do a better job of it.
Using ANSI SQL as a Conceptual Hierarchical Data Modeling and Processing Language for XML, The Journal of Conceptual Data Modeling, May 2005. What makes this paper of significant importance to the SQL/XML industry is it proves how standard ANSI SQL can perform full multi-leg hierarchical processing. It explains how the relational Cartesian processing engine automatically and inherently performs Lowest Common Ancestor (LCA) logic that's required to perform hierarchical processing.
Automatically Utilizing XML's Untapped Semantic Goldmine, DM Review’s Direct Newsletter, Feb. 11, 2005. This article identifies the vast amount of hierarchical semantics in XML and other hierarchical structures that is not being utilized to process multi-leg structures. It goes on to demonstrate generally how this hierarchical structure semantics can be automatically utilized by 4GL's to nonprocedurally process these multi-leg structures. It goes on further to demonstrate specifically how SQL as a nonprocedural query language performs this multi-leg hierarchical processing naturally and inherently while fully operating naturally under ANSI SQL's syntax and semantics to increase the value of the data.
The Marriage of XML TO ANSI SQL, Fully Utilizing XML's Hierarchical Structures, DM Review online, July 16, 2004.This is a high level overview of our ANSI SQL native XML integration technology and product written for the DM Review's audience. It explains how SQL can perform hierarchically allowing it to integrate with XML at a seamless and full hierarchical level which automatically utilizes the hierarchical semantics in the hierarchical input structures to seamlessly and transparently integrate with XML.
In XML: Using SQL to Link Below the Root, Part 1, The Data Administration Newsletter, April, 2004. This article describes SQL transparent processing of XML. It also describes new data modeling and processing capabilities in ANSI SQL where the lower level structure being linked into the structure being modeled can be linked using a reference to node below the root node which goes against conventional thinking. This article describes the semantics of this powerful new capability and explains why it is possible.
In SQL: Processing XML's Complex Hierarchical structures, Part 2,The Data Administration Newsletter, July, 2004. This article describes how SQL can inherently process XML's Complex Hierarchical structures. These include network structures, variable structures, and structure transformation.
In SQL: Unified Heterogeneous Virtual Hierarchical Views, Part 3, The Data Administration Newsletter, Oct., 2004. This third and final article in this series describes the synergistic effect of SQL hierarchical views and hierarchical optimization and how they come together to make SQL hierarchical views an extremely important part of SQL's overall hierarchical processing capability.
ANSI SQL Hierarchical Processing Can Fully Integrate Native XML, ACM SIGMOD Record, March 2003. This paper describes how and why ANSI SQL can perform fully hierarchically and how this can be utilized to interface completely and seamlessly with native XML. Particular attention is paid to: multi-leg hierarchical processing, how relational Cartesian product processing can automatically perform hierarchically, and the capabilities of hierarchical structures and their semantic processing.
Advanced ANSI SQL Native XML Integration, Part 1, XML Journal, November 2003. This is the first of a two part article that covers ANSI SQL's hierarchical processing capability which includes its ability to seamlessly integrate relational data with native XML and legacy data at a full hierarchical level. Joining hierarchical structures, hierarchical optimization, hierarchical SQL views are also covered.
Advanced ANSI SQL Native XML Integration, Part 2, XML Journal, December 2003. This is the second of a two part article. This part includes advanced XML capabilities such as: node promotion; fragment processing; structure transformation; and processing variable structures.
Advanced ANSI SQL Data Modeling and Structures Processing, Artech House Publishers, 1999. This book fully documents the ANSI SQL Outer Join data modeling and structure processing capability. There is also a chapter on the patented data structure metadata extraction technology, and a chapter on ournested relations prototype that utilizes the data structure extraction patented technology to operate hierarchically on the standard SQL specification.
SQL-Based XML Structured Access, Web Techniques Magazine, June 1999. This article demonstrates how the ANSI SQL Outer Join can be used to hierarchically map to-and-from XML while preservingand following the full ANSI SQL specified hierarchical syntax and semantics.
Universal Data Access: Fulfilling the Promise, Intelligent Enterprise Magazine, Dec. 1998. This article describes how the ANSI SQL Outer Join can be used to perform unified heterogeneous access and processing enabling seamless universal heterogeneous data access directly in SQL.
Advanced Capabilities of the Outer Join, ACM SIGMOD Record, March 1992. This is the seminal paper on the ANSI SQL Outer Join's powerful inherent hierarchical processing capabilities. This paper shortly followed the ratification of the ANSI SQL-92 standard where the Outer Join was introduced.
Taming the ANSI SQL2 Outer Join, Colin White's InfoDB Journal, Vol 6, No 3, Winter 1991/92. This article describes the advanced capabilities of the new outer join. SQL Optimization, Two Steps Forward, One Step Back, DATA BASE Management Magazine, June 1991. This article describes the advances of SQL optimization. Heterogeneous Accessing of SQL, IMS and VSAM Databases, DATABASE Programming & Design Magazine, April 1991. This is part 1 of a two part article. It describes how to heterogeneously integrate relational and hierarchical data. This is explained at a high level using relational and hierarchical examples of different data types.
Heterogeneous Database Processing, A 4GL Case Study, DATABASE Programming & Design Magazine, March 1991. This is part 2 of a two part article. It describes how to heterogeneously integrate relational and hierarchical data and nonprocedurally process the integrated data at an elevated processing level. This is explained at a low level internal implementation level.
Dynamic SQL: Use With Caution, DATABASE Programming & Design Magazine, March 1989. This article describes the problems and benefits of Dynamic SQL.
4GLs, 5GLs, and the Database, DATABASE Programming & Design Magazine, Oct. 1988. This article describes the power and capabilities of 4GLs and 5GLs.