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Delightful Database Diversion

Fair warning, this one is a bit harder than the last few!

Answer key will be posted in the comments in a day or two.

Across

5. Run this before upgrading to SQL 2017

8. Copy of the database but not backwards.

11. Instead of INSERT

13. Rerun a trace against multiple locations

15. Uses hypothetical indexes

16. Evaporate data into the blue

17. Default default schema

19. UNMASK

20. Not normal

22. Update here, insert there

24. Free Enterprise SQL

26. Picture of the database.

Down

1. This data needs a bath.

2. It's not a fact

3. Window into the server

4. Ignores logon triggers

6. Used to edit SSIS

7. Delete a database

9. After ALTER

10. We are never going to get out of this one on our own.

12. Replication limbo

14. OLAP DB

18. Comma

21. Watch out for Bobby!

22. Go deeper into a report

23. Consistency Checker

25. Information

Kenneth Fisher from SQLServerCentral.com

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When you build applications that store data in SQL Server you will most likely have to store dates and times, and you’ll call functions to do date manipulations. It is important to understand the different date and time data types, and when to use one data type over another. In this level I will be exploring the different date and time data types and discussing when each type is appropriate. More »

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Today's Question (by Steve Jones):

I have a CSV with a number of rows and columns that looks like this:

I want to read this into a dataframe in R. What command should I use? Assume the filename is c:\nfl\2016qbstats.csv.

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Yesterday's Question of the Day

Yesterday's Question (by Steve Jones):

I've got a table of integers only and I want to put one trillion rows in the table for some testing. However, I'm worried about space. Which table should I create to use the minimal space?

Answer: CREATE TABLE dbo.LotsofIntegers (ID BIGINT, INDEX LotsofIntCDX CLUSTERED COLUMNSTORE) ;

Explanation:

One trillion integers won't fit in an INT column so a BIGINT type is needed. However, with rowstore data, this will be around 10TB. With a clustered columnstore, this will be under a GB.

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