Excel X64 driver and SQL Server 2008 R2 on cluster node [Fix]

As we continued with the execution of our migration plans from SQL Server 2005 to 2008 R2 X64, we found challenges than needed to be resolved pretty quickly. The latest issue we encountered was the Microsoft.ACE.OLEDB.12.0 provider in SQL Server 2008 R2 X64.

With that same provider, we were able to load Excel files directly into SQL Server 2005 X64 (SP3 and SP4), but had no luck in 2008 R2.

The prerequisites are to install the Microsoft Access Database Engine 2010 Redistributable, and to add the provider, with a couple of configuration changes:

Configuring:

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exec sp_configure 'show advanced options', 1;
reconfigure;
GO;
 
exec sp_configure 'Ad Hoc Distributed Queries', 1;
reconfigure;
GO;

EXEC master.dbo.sp_MSset_oledb_prop N'Microsoft.ACE.OLEDB.12.0', N'AllowInProcess', 1;
GO;

EXEC master.dbo.sp_MSset_oledb_prop N'Microsoft.ACE.OLEDB.12.0', N'DynamicParameters', 1;
GO;

Testing:

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SELECT *
FROM OPENROWSET('Microsoft.ACE.OLEDB.12.0',
'Excel 12.0;Database=M:\MSSQL10_50.MWTOOLS\MSSQL\DATA\dreambox.xlsx;HDR=Yes;IMEX=1',
'SELECT * FROM [Subsets & Ads$] WHERE Headline IS NOT NULL')

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)"

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)"

We had no luck with the provider until we pinpointed a workaround on a blog post using the MSDASQL provider instead

Workaround:

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SELECT * FROM OPENROWSET('MSDASQL',
'DRIVER=Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb);FIL=excel 12.0;DriverId=1046;DefaultDir=M:\MSSQL10_50.MWTOOLS\MSSQL\DATA\dreambox.xlsx', 'SELECT * FROM [Subsets & Ads$]')

After the change our application worked flawlessly.

Netflix on iPad/iPhone does not work when connected to a router running DD-WRT [Fix]

I was pretty frustrated when I realized that for firing up my new iPad I needed to install iTunes to my desktop. On top of that, I needed to add a credit card number to download a free application from the App Store. I worked it around by generating a one-time number from citicards.

I decided to install Netflix and did not work, even tried resintalling and changing SSIDs. The only way to make it work was by using a backup SSID from the U-Verse router.

After researching I found out that the DNSMasq package from DD-WRT thinks that the connection from Netflix on the iPad looks like a DNS Rebinding attack.

There are a couple of workarounds:

  1. Use a different DNS server in the iPad/iPhone wireless configuration, like the one provided by OpenDNS: 208.67.222.222
  2. Add a startup rule to DD-WRT to stop DNS rebinding:
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killall dnsmasq
sed -i -e 's/^stop-dns-rebinding/#&/' /tmp/dnsmasq.conf
dnsmasq --conf-file=/tmp/dnsmasq.conf

I pursued the second workaround as it allowed me to keep the wireless connection “stock”. Netflix is now working properly on my iPad.

Stop DNS rebinding

Stop DNS rebinding

Windowed Functions empowering analytics [#TSQL2sday]

T-SQL Tuesday #16

T-SQL Tuesday #16

This blog entry is participating in the T-SQL Tuesday #16 for the month of February, hosted by Jes Schultz Borland (Blog|Twitter).

Back in 2001 I was involved in a project migrating an e-commerce site to a new platform. We were mapping and moving data from an Oracle 8.1.5 to an Oracle 8.1.7 instance. The framework was the beloved Dynamo running on Sun Solaris. The Dynamo engineers decided to use sequencers on each entity (e.g. product, category, etc). I was trying to figure out the best reusable PL/SQL block to move the data creating the correct sequence until I was pointed out that Oracle 8.1.6 supported Analytical Functions. After reading and practicing I discovered the power of those functions.

For the purpose of this blog I will refer the Analytical Functions as Windowed Functions instead. They are very useful as it allows the user to crunch measures of subsets of data maintaining the “raw” detail level data. For example, it allows us to get the average price of a product category while also displaying the unit price of each product. It can also help us rank a product by its price and “window” it by category.

Examples

Basic Aggregation:

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-- Qty of products and average price
SELECT
    COUNT(productKey) AS [Quantity]
   ,AVG(StandardCost) AS [AverageCost]
FROM [dbo].[DimProduct]

Distribution of Data:

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-- Tier by Product Cost (4 tiers)
SELECT
    NTILE(4) OVER(ORDER BY [StandardCost]) AS [Tier]
   ,productKey
   ,StandardCost
FROM [dbo].[DimProduct]

Average per Category with raw data:

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-- Take the Average for each Product Subcategory and attach to the detail level data
SELECT
    AVG(StandardCost) OVER(PARTITION BY [ProductSubcategoryKey]) AS [AverageCostSubPerCat]
   ,productKey
   ,[ProductSubcategoryKey]
   ,StandardCost
FROM [dbo].[DimProduct]

Ranking:

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-- Rank Products based on the minimum and maximum cost per Product Subcategory
SELECT [ProductSubcategoryKey]
   ,RANK() OVER(PARTITION BY [ProductSubcategoryKey] ORDER BY StandardCost, [ProductKey]) AS sequence_min
   ,RANK() OVER(PARTITION BY [ProductSubcategoryKey] ORDER BY StandardCost DESC, [ProductKey] DESC) AS sequence_max
   ,[ProductKey]
   ,StandardCost
FROM [dbo].[DimProduct]
WHERE StandardCost IS NOT NULL

Averages excluding certain ranks:

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-- Get the Average and Qty. of the products per category excluding the minimum and maximum cost per Product Subcategory (above)
WITH CTE_sequence AS (
  SELECT [ProductSubcategoryKey]
     ,RANK() OVER(PARTITION BY [ProductSubcategoryKey] ORDER BY StandardCost, [ProductKey]) AS sequence_min
     ,RANK() OVER(PARTITION BY [ProductSubcategoryKey] ORDER BY StandardCost DESC, [ProductKey] DESC) AS sequence_max
     ,[ProductKey]
     ,StandardCost
  FROM [dbo].[DimProduct]
  WHERE StandardCost IS NOT NULL
)
SELECT [ProductSubcategoryKey]
  ,COUNT([ProductKey]) AS Quantity
  ,AVG(StandardCost) AS Average_Cost
FROM CTE_sequence
WHERE sequence_min > 0
  AND sequence_max > 0
GROUP BY [ProductSubcategoryKey]

There are more functions that can be used and the user even has the option to dice the data further by using HAVING and slicing with GROUP BY CUBE | ROLLUP which plots the data in “pivotable” format.