Manipulating data directly in a table isn’t always practical. On occasion, performance requirements may dictate that the revised or replacement data set first be assembled in a separate table (a staging table) then switched in to replace the currently live data. Continue reading
I like to expose myself to programming languages rooted in different paradigms so that I can expand my skill set, broaden my thinking and learn new ways to solve problems. Lately, I’ve been exploring the world of pure functional programming by studying Haskell.
My object-oriented mind finds the following fascinating:
naturalNumbers = [1..] -- [1,2,3,4,5,…]
This simple statement defines a list starting with 1 and increasing by 1 each step all the way to infinity. The result is not a range that can be enumerated to infinity (for example,
1..1.0/0 using Ruby’s Range class); it’s an actual list that goes to infinity. Continue reading
At the core, both Microsoft Access and Microsoft SQL Server are relational database management systems (RDBMS), yet each uses a separate file format and code base. These differences add friction to the process of integrating the two technologies. Developers interacting with both back ends need to learn the idiosyncrasies of two systems. For administrators, the fact that each uses a different driver requires maintaining multiple driver configurations on systems that need to communicate with both. Power users are faced with the pain of figuring out how to cross this technology divide when growth dictates switching a home-grown Access application to a SQL Server backend. Continue reading
Since a view is a saved query and queries can specify ordering, adding ORDER BY a view definition might seem a reasonable proposition. Try it and Microsoft SQL Server chokes. Then you learn the trick: include a TOP clause and SQL Server will be a-ok with ordering clauses in views. You want all rows returned so you add “TOP 100 PERCENT” to your definition and SQL Server is happy!
Yet you notice something strange. Sometimes the rows returned aren’t sorted according to the view’s ORDER BY clause. As you ponder this puzzlement, your mind wonders back to the roundabout syntax required to finagle ORDER BY into the view definition. Is something funny going on? But the answer eludes you. Continue reading
Did you know that IDENTITY columns can count downward?! According to MSDN, IDENTITY’s second argument, named increment, “is the incremental value that is added to the identity value of the previous row that was loaded.” No constraint is given that increment must be positive (remember from Algebra that both positive and negative numbers can be added). Set increment to a negative number and IDENTITY will generate a descending sequence of numbers. Continue reading
“If I query a table that has a clustered index without specifying an ORDER BY clause, the resultset will be sorted according to the clustered index” may sound reasonable. After all, since “a clustered index determines the physical order of data in a table” (per TechNet), isn’t it logical to assume that a query with no ORDER BY clause returns data sorted this way? Continue reading
The versatility of T-SQL’s object_id() function, which accepts one-part (object_name), two-part (schema.object_name) and three-part (database.schema.object_name) object names as its first argument, could seem to imply that object identification numbers (object IDs) are global across a Microsoft SQL Server instance. After all, if object_id() accepts a multi-part object name which uniquely identifies the specified object relative to the server instance, wouldn’t the object ID returned by that function also uniquely identify the same object across the server instance? Continue reading
Pass in a query and a column name (or a column list) and receive an unpivoted result set back. Specify either the columns to unpivot or the columns to leave unpivoted (i.e. unpivot all but the specified columns). Behind the scenes, this stored proc casts value columns to a common data type of your choosing, eliminating “the type of column ‘x’ conflicts with the type of other columns specified in the UNPIVOT list” errors. It can also be used as a SQL generator, outputting the dynamically-built query’s text instead of executing it. Continue reading
SELECT returns all relevant rows from the database.
GROUP BY applies aggregate functions, condensing
SELECTed data into one summary row per grouping. What if mixing the two approaches is desired—what if data rows need to be combined with aggregate totals in the same result set?
OVER clause allows several kinds of functions to be applied to non-
BY rows. Using
OVER, a simple
SELECT returning data rows can be expanded to include columns containing summary statistics. Traditionally, aggregate functions can only be used in conjunction with
GROUP BY or to produce a single row summary result set; when used with
OVER, these limitations are removed. Continue reading
Learning about how SSIS’s MaximumErrorCount property works can be challenging. There’s not much documentation describing this property and the behavior it controls. Here’s my attempt to help remedy this.
When the number of errors occurring inside a container during execution reaches its MaximumErrorCount, the container’s ExecutionResult is changed to Failure if it is not already set to that state. A value of zero sets the error count threshold to infinity, disabling this functionality. Continue reading