Databases Reference
In-Depth Information
legitimately deleted (legitimately because the data had success-
fully made it to the next downstream point), then we may have
to go all the way back to the original point at which the data
was first acquired or created. This can impose significant delays
in getting the data to its consumers, and significant costs in
reacquiring or recreating it and in moving it, for a second time,
down the pipeline. And this risk is quite real because, prior to
making it into the database, the backups and logfiles which pro-
tect data once it has reached the DBMS are not yet available.
By internalizing these datasets within the production tables
whose data they contain, we eliminate the costs of managing
them, including the costs of recovering from mistakes made in
managing them. We now turn to the task of re-presenting what
were physically distinct managed objects, external to production
tables. We re-present them as queryable objects, showing how
queries can produce result sets containing exactly the data that
would have been in those physical datasets, had we not
internalized them.
Pipeline Datasets as Queryable Objects
We emphasize once more that most business queries for
temporal data will not focusondatafromasingleoneofthese
eight internalized pipeline datasets. Together with currently
asserted current data, these eight other categories of temporal
data constitute a partitioning of all bi-temporal data. Like the
Allen relationship queries we will discuss in the next chapter,
we focus on these queries in spite of thefactthattheyare
not real-world business queries. We focus on them because,
as a set, they are guaranteed to be complete. If these eight
categories of pipeline datasets can be internalized, then we
can be certain that any real-world business dataset—one des-
tined to update a production table, or one derived from a pro-
duction table—can also be internalized. In the next chapter,
once we have seen that any Allen relationship against asserted
version data can be expressed in a query, we will be similarly
certain that any query whatsoever can be expressed against
asserted version tables.
In each case, we will illustrate these queries in the context
of CREATE VIEW statements. From the point of view of the
semantics involved, there is no difference between direct queries
and SQL VIEW statements. But actual VIEW statements lend a
little more substance to the notion of re-presenting internalized
pipeline datasets as queryable objects.
