Stairway to Biml Level 3: Building an Incremental Load Package
The Stairway to BIML continues, with a lesson on how you might build a more complex package: an incremental load package.
Stairway to Biml Level 4: Using Biml as an SSIS Design Patterns Engine
In this level, we make a large leap forward, showing you how to use BIML to script a large number of packages using C#.
Stairway to Columnstore Indexes Level 10: Optimizing Queries For Batch Mode (Part 1)
In this level, Hugo Kornelis looks at how to rewrite your queries to best take advantage of batch mode.
Stairway to Columnstore Indexes Level 11: Optimizing Queries For Batch Mode (Part 2)
Hugo Kornelis continues his exploration of the types of queries that can end up running in row mode when accessing columnstore indexes. He demonstrates how careful rewriting can often yield a logically equivalent query that runs in batch mode instead, and therefore gains the best possible performance benefit.
Stairway to Columnstore Indexes Level 5: Adding New Data To Columnstore Indexes
Earlier levels have shown how Columnstore Indexes work effectively with static data. In most tables however, data is hardly ever static. We are constantly inserting new rows, and updating or deleting existing rows. If you think about what this means for a columnstore index, you will realize that this comes with some unique challenges.
Stairway to ColumnStore Indexes Level 8: Optimizing Clustered Columnstore Indexes
In Level 7, we looked at optimizing rowgroup elimination for a nonclustered columnstore index. For a clustered columnstore index, the same technique can be used but the steps and syntax change a bit. This will be covered later – but first, let’s take a look at another significant difference between nonclustered and clustered columnstore indexes, […]
Stairway to Columnstore Indexes Level 9: Batch Mode Execution
In this level, Hugo explains what batch mode execution is, how it differs from row mode execution, and what its limitations are.
Stairway to Data, Level 1: The Basics
A great deal of the confusion that occurs when a database application is developed comes from a poor understanding of the basics of data. Here, Joe Celko gives a broad coverage of the difficulties you're likely to meet when handling data in databases.
Stairway to Data, Level 2: Numerics
A confusion about the nature of numbers can lead to a number of problems in database applications. Joe Celko gives a simple guide to the subject
Stairway to Data, Level 3: Strings
Character-handling in SQL is not particularly straightforward, and confusion about collation and character encoding is a common cause of problems with searching, joining, and sorting.
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Question of the Day
Using OPENJSON
I have some data in a table that looks like this:
BeerID BeerName brewer beerdescription 1 Becks Interbrew Beck's is a German-style pilsner beer 2 Fat Tire New Belgium Toasty malt, gentle sweetness, flash of fresh hop bitterness. 3 Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste 4 Alaskan Amber Alaskan Brewing Alaskan Brewing Amber Ale is an "alt" style beer 8 Kirin Kirin Brewing Kirin Ichiban is a Lager-type beerIf I run this, what is returned?
select t1.[key]
from openjson((select t.* FROM Beer AS t for json path)) t1 See possible answers