|By Michael M David||
|September 22, 2011 02:00 PM EDT||
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.
How does a query request automatically operate without being instructed on how to perform the request? This is done by analyzing the semantics in the data structure. Since query languages have the ability to search out meaning, they can derive the most value out of the semantics in the data structure. The first and primary place to look for semantics is in the data structure and should not be ignored even if other types of semantics are available. This is because the data structure drives or guides the meaning of the query.
Structured data often involves hierarchical structures. Hierarchical data structures inherently have a significant amount of structure semantics. Besides having vertical semantics they have horizontal semantics where data across pathways are related. This produces very complex structures requiring complicated data structure user navigation for programming languages. Query languages on the other hand are free to perform the navigation internally without involving the user. In fact, some complex data structures are too complex to handle with user navigation within programming languages. This makes query languages indispensable in these complicated situations proving query languages unique usefulness in structured data processing. One such complex data structure processing requiring query processing are multipath queries. These require complicated coordination between multiple paths of a hierarchical data structure such as when a query selects data from one path based on data from another path.
An amazing thing happened unnoticed and unplanned in the ANSI SQL-92 standard. In this standard, the LEFT Outer Join was introduced along with other outer join capabilities. The LEFT Outer Join is a one-sided join that is hierarchical by nature. It always preserves the left side of the outer join operation allowing, for example, employee data that has no dependent data to always be preserved. A new ON clause operation allows specification of hierarchical join criteria at each join point to replace the single use SQL WHERE clause. This prevents any ambiguity in defining hierarchical data structures that occurred when using the older WHERE clause. This combination of new SQL features unexpectedly turned out to support complete hierarchical multipath data structure definition and hierarchical processing even though there was no prior design performed or coding added in ANSI SQL to support full hierarchical processing.
These powerful hierarchical data structures can also be naturally defined in SQL views which can be dynamically joined in multiple ways creating larger variable structures and perform their hierarchical processing on the fly. This concept for processing dynamically created structured data is new and opens up many powerful capabilities in structured data. It utilizes a new Dynamic Metadata Maintenance operation that allows the metadata to be transparently processed. This eliminates any metadata operation by the user to process dynamic structured data. The ANSI SQL query language is in a position to take advantage of these new dynamic structured data capabilities such as for use in peer-to-peer data collaboration.
As stated in the very beginning of this article, Dart is a programming language. This gives it great user control that requires the user to have programming experience and knowledge. But what is not generally recognized, is that some problems are just too complicated to solve under user control. They require automatic processing to handle. These can be performed by a query processor. This automatic processing also means that the user does not need programming experience to specify the query. ANSI SQL's natural hierarchical structured data processing described above places it in a good position to be a complementary language for Google's Dart processor because each has their strong and weak points. Documentation describing the technology used by ANSI SQL hierarchical structured data processing follows:
SQL Dynamic Structured Data Processing Collaboration Article at:
ANSI SQL Transparent Hierarchical Processing User Guide at:
ANSI SQL Transparent Hierarchical Processing Technology Slide Presentation at:
Online Interactive ANSI SQL Transparent Hierarchical Processing Prototype at:
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