Tuesday, December 10, 2013

These 5 Tech Jobs Will See the Most Growth in 2014

These 5 Tech Jobs Will See the Most Growth in 2014 (via Dice News in Tech)

Mobile app developers top the list of Robert Half Technology’s top growth tech jobs for 2014. Given the high demand for mobile-dev skills and the difficulty finding people who have them, that’s no surprise. RHT compiles this list based on increases…

Saturday, December 7, 2013

Hottest Job in the Market: Software Developer

(via Dice News in Tech)

Software development is the most in-demand skill for technology jobs in the U.S., according to a study by Wanted Analytics. More than 232,000 jobs for software developers have been advertised online in the past 90 days, an increase of 3 percent over…

Wednesday, October 23, 2013

Software, Data Skills Key to Higher Pay

Software, Data Skills Key to Higher Pay (via Dice News in Tech)

Though few are on par with Twitter’s $10 million engineer, pay is on the upswing for IT occupations, according to a new Robert Half Technology salary survey. The report suggests that while salaries will rise an average of 3.7 percent in 2014 across…

Thursday, September 12, 2013

mdq.regex CLR Functions -- Part 3: Regex Check Constraints!


This is the third article in my series, mdq.regex CLR Functions. In my first two articles we reviewed mdq.RegexIsMatch and mdq.RegexMatches. In each article I demonstrated how to use these CLR functions to pass regular expressions (regex for short) to your T-SQL queries. Today I will show you how to create a couple tables with check constraints that use regex to evaluate input using mdq.RegexIsMatch.


Setting up mdq.RegexIsMatch is extremely quick and simple provided you have the right credentials. See this article for detailed instructions on how to setup mdq.RegexIsMatch.

Sample Regex Check Constraints

Creating check constraints to test for tricky string patterns such as a valid IP Address or E-mail address can be a headache using T-SQL. Luckily, regex is perfect for this sort of task; below are two examples. In the first example we create a table with a column that only accepts valid E-mail addresses, the second only accepts valid IP addresses. This is easiest to learn by example so let's get to it...

Valid E-mail Address


(      cust_name     varchar(100),

       cust_email    nvarchar(200)

              CHECK (





Valid IP Address (no leading zeros)


(      computer_name varchar(100),

       ip_address varchar(20)

              CHECK (






As you can see, these mdq.regex functions add a whole new world of possibilities to your SQL Server instance. Thanks for reading!


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Last Updated: 9/12/2013 (Posted)

Tuesday, May 28, 2013

mdq.regex CLR Functions -- Part 2: mdq.RegexMatches

Updated 12/7/2013

I updated this article on 12/7/2013 to include a link to instructions for enabling CLR Integration as and an updated link for the instructions to create the [Microsoft.MasterDataServices.DataQuality] assembly.


This is the second article in my series, mdq.regex CLR Functions. In my previous article about mdq.regex functions, mdq.regex CLR Functions -- Part 1 I introduced mdq.RegexIsMatch, a scalar CLR function that returns a bit based on if a regex pattern is matched. Today we will review mdq.RegexMatches.

mdq.RegexMatches is a Table Valued CLR function. Like mdq.RegexIsMatch, setup is fast, easy and this CLR was developed, tested, tuned and QA’d by Microsoft.


To create this function you will need:

  1. A schema named, “mdq” in your target DB
  2. CLR integration enabled
  3. The [Microsoft.MasterDataServices.DataQuality] assembly

See this article for details on enabling CLR integration and this article for the steps to create the assembly.

Run the following DDL to create mdq.RegexMatches:

CREATE FUNCTION mdq.[RegexMatches](@input [nvarchar](4000), @pattern [nvarchar](4000), @mask [tinyint] = 0)


(      [Sequence] [int] NULL,

       [Token] [nvarchar](4000) NULL)



EXTERNAL NAME [Microsoft.MasterDataServices.DataQuality].[Microsoft.MasterDataServices.DataQuality.SqlClr].[RegexMatches]


Using mdq.RegexMatches

mdq.RegexMatches searches an input string for all occurrences of a regular expression and returns all the successful matches. This function uses the regular expression functionality of the Matches method in the Microsoft .NET Framework.


mdq.RegexMatches (input,pattern,mask)



Is the input string for which to find matches. input is nvarchar(4000) with no default.


Is the regular expression pattern to use for matching. pattern is nvarchar(4000) with no default.


Is the RegexOptions mask that specifies the behavior of the regular expression. For more information, see mdq.RegexMask (Transact-SQL).

mdq.RegexMatches Code Samples

In the first example below I am searching for numeric patterns. For the second example I will demonstrate how to search for records based on a word pattern. We will conclude with a technique for querying a table for valid and invalid EMail addresses.

mdq.regexMatches to find numeric patterns

-- (1) Let's find this pattern: (one or more numbers)-(one or more numbers)-(one or more numbers) [e.g. 222-111-9999]

SELECT Token AS pattern

FROM clr.RegexMatches(N'XYXYXYXYYX11-222-333XYXYXYXYXY', N'\d+-\d+-\d+', 0);



-- (2) Let's find patterns of one or more numbers

DECLARE @text varchar(1000)='1 is one, 2 is two and 3 makes three',

        @find_cons_digits varchar(20)='\d+';

SELECT Sequence, Token AS value

FROM clr.RegexMatches(@text, @find_cons_digits, 0);




-- (3) Let's find sequenses of two consecutive numbers

DECLARE @text varchar(1000)='1 is one, 2 is two and 3 makes three',

        @find_cons_digits varchar(20)='\d+';


SELECT  @text='1 is zero, 11 is one, 22 is two... 345678 makes three, four and five',



SELECT Sequence, Token AS value

FROM clr.RegexMatches(@text, @find_cons_digits, 0);


mdq.regexMatches to find word patterns

-- (4) Let's perform a word count

DECLARE @quote varchar(1000)='The world is a dangerous place to live; not because of the people who are evil, but because of the people who dont do anything about it. --Albert Einstein',

                @quote2 varchar(100)='apple orange orange pear',

                @word_count varchar(20)='\b(\w+)',

                @ab_count varchar(20)='\b([ab]\S+)',

                @find_duplicates varchar(50)='\b(\w+?)\s\1\b';


SELECT COUNT(*) AS [word count]

FROM clr.RegexMatches(@quote,@word_count,0);



-- (5) Let's find how many words begin with A or B

SELECT COUNT(*) AS [words that begin with A or B]

FROM clr.RegexMatches(@quote, @ab_count,0);


-- (6) Let's find repeated words

SELECT @quote2 AS quote, Token AS [repeated words]

FROM clr.RegexMatches(@quote2,@find_duplicates,0);


-- (7) Let's normalize a string, a series of numbers or both:

SELECT Sequence, Token AS val

FROM clr.RegexMatches(N'NormalizeMe', N'([a-zA-z])', ''); --string


SELECT Sequence, Token AS val

FROM clr.RegexMatches(N'54321', N'\d', ''); --series of numbers


SELECT Sequence, Token AS val

FROM clr.RegexMatches(N'text1234', N'([a-zA-z0-9])', ''); --text and numbers

Query that returns valid Email addresses and one that only returns invalid addresses:

IF OBJECT_ID('tempdb..#customer_email') IS NOT NULL

        DROP TABLE #customer_email;


CREATE TABLE #customer_email

(       email_id int identity primary key,

        cust_id int NOT NULL,

        email nvarchar(100) unique NOT NULL);


INSERT INTO #customer_email (cust_id, email)

        SELECT  1,'john.doe@a+++cme. com'       UNION ALL

        SELECT  1,'JohnDoe@somewhere.com'   UNION ALL

        SELECT  2,'Sally.Smith@Microsoft'   UNION ALL

        SELECT  3,'AlChurch@turning.net'    UNION ALL

        SELECT  4,'JaneDoe@aol.com';



DECLARE @validEmail nvarchar(1000);

SET @validEmail='^(([a-zA-Z0-9!#\$%\^&\*\{\}''`\+=-_\|/\?]+(\.[a-zA-Z0-9!#\$%\^&\*\{\}''`\+=-_\|/\?]+)*){1,64}@(([A-Za-z0-9]+[A-Za-z0-9-_]*){1,63}\.)*(([A-Za-z0-9]+[A-Za-z0-9-_]*){3,63}\.)+([A-Za-z0-9]{2,4}\.?)+){1,255}$';


-- (1) This will return records with only valid EMail addresses


FROM #customer_email e

CROSS APPLY clr.RegexMatches(e.email,@validEmail, 0);


-- (2) This will return records with only invalid EMail addresses

SELECT e.email_id, e.cust_id, e.email

FROM #customer_email e


SELECT ex.email_id, ex.cust_id, ex.email

FROM #customer_email ex

CROSS APPLY clr.RegexMatches(ex.email, @validEmail, 0);


DROP TABLE #customer_email;


... EMail Query results:


Today we reviewed the steps for setting up and using mdq.RegexMatches. Thanks for reading!


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Last Updated: 12/7/2013 (minor updates, repaired broken links)

Monday, May 27, 2013

5 Career Killers You Must Absolutely Avoid

5 Career Killers You Must Absolutely Avoid

(via Dice News in Tech)

Here are a couple of obvious ways to get yourself in trouble: Insult your boss on Facebook, and look for a new job on company time. But as annoyed as your boss might get over those, they’re usually survivable mistakes, at least as long as you don’t repeat them. The real dangers that could lead…

Tuesday, May 21, 2013

Reading XML Data


In this post I will demonstrate how to query XML data. This is one of those things that is much easier to learn by example so I provided five examples. I won't get into how to get the data in or out of SQL Server because that topic is outside the scope of this article. All you need to know is that it's easy if you know a little WMI scripting, powershell or .NET.


In the examples below I will read XML data from:

  1. An XML fragment from a MS Word Doc
  2. An XML fragment from an SSRS Report
  3. An event from the Windows Event Viewer
  4. An XML fragment from an SSIS package
  5. An XML fragment from a SQL trace

For these examples I will not include the entire XML document because the XML can be quite verbose. Instead I am using XML fragments (a portion of the entire XML document). This way you can get the general idea without having to copy/paste a ton of XML.

Setting up the sample data

Use this code:


(0) Create some sample data


Note: For simplicity I am only including XML fragments and

I removed the namespaces, namespace declarations, etc.


IF OBJECT_ID('tempdb..#data') IS NOT NULL

       DROP TABLE #data;


CREATE TABLE #data (id int primary key, xmldesc varchar(100) not null, doc xml not null);


DECLARE @worddoc xml='



       <p><r><t>1:  Paragraph 1...</t></r></p>

       <p><r><t>2:  Paragraph 2...</t></r></p>

       <p><r><t>3:  Paragraph 3...</t></r></p>



DECLARE @ssrs_report xml=




              <DataSource Name="QuestNTDev">







              <DataSet Name="ds_p_major_region"/>

              <DataSet Name="ds_p_country_code"/>

              <DataSet Name="ds_p_acct_group"/>

              <DataSet Name="ds_p_currency_code"/>

              <DataSet Name="ds_p_profit_center"/>

              <DataSet Name="ds_p_office_id"/>

              <DataSet Name="ds_p_total_by_office"/>

              <DataSet Name="ds_p_subtotal_on_summary"/>

              <DataSet Name="ds_get_spid"/>

              <DataSet Name="ds_output"/>


</Report>' AS varchar(1000)),'rd:','');

DECLARE @events xml='




                     <Provider Name="MSSQL$SQL2012"/>

                     <EventID Qualifiers="16384">17137</EventID>

                     <TimeCreated SystemTime="2012-05-10T16:18:53.000000000Z"/>












                     <Provider Name="MSSQL$SQL2012"/>

                     <EventID Qualifiers="19999">1000225</EventID>

                     <TimeCreated SystemTime="2013-05-6T16:18:53.000000000Z"/>











DECLARE @ssis_package xml=


'<DTS:Executable DTS:ExecutableType="SSIS.Package.2">

  <DTS:Property DTS:Name="PackageFormatVersion">2</DTS:Property>

  <DTS:Property DTS:Name="VersionComments"></DTS:Property>

  <DTS:Property DTS:Name="CreatorName">DOMAIN\username</DTS:Property>

  <DTS:Property DTS:Name="CreatorComputerName">AJBTEST</DTS:Property>

  <DTS:Property DTS:Name="CreationDate"

                DTS:DataType="7">11/25/2012 3:35:28 PM</DTS:Property>


' AS varchar(1000)),'DTS:','');

DECLARE @sqlTrace xml='



    <Event id="65534" name="Trace Start">

      <Column id="14" name="StartTime">2013-05-10T17:21:28.007-05:00</Column>


    <Event id="13" name="SQL:BatchStarting">

      <Column id="1" name="TextData">SELECT 1</Column>

      <Column id="3" name="DatabaseID">7</Column>

      <Column id="35" name="DatabaseName">ajbTest</Column>

      <Column id="12" name="SPID">60</Column>

      <Column id="14" name="StartTime">2013-05-10T17:21:48.917-05:00</Column>

      <Column id="26" name="ServerName">MYSERVER\SQL2012Express</Column>


    <Event id="65533" name="Trace Stop">

      <Column id="14" name="StartTime">2013-05-10T17:21:54.46-05:00</Column>






       SELECT 1, 'An XML fragment from a MS Word Doc', @worddoc UNION ALL

       SELECT 2, 'An XML fragment from an SSRS Report', @ssrs_report UNION ALL

       SELECT 3, 'An event from the Event Viewer',            @events UNION ALL

       SELECT 4, 'An XML fragment from an SSIS pkg',   @ssis_package UNION ALL

       SELECT 5, 'An XML fragment from a SQL trace',   @sqlTrace;

The contents of #data will look like this:

Reading XML data

Note my comments in the code


(1) Reading from a word doc


SELECT p.value('(r/t/text())[1]', 'varchar(20)') AS p_num

FROM #data

CROSS APPLY doc.nodes('wordDocument/body/p') AS doc(p)

WHERE id=1;



(2) Reading from an SSRS Report


SELECT datasource.value('(DataSourceReference/text())[1]', 'varchar(20)') AS DataSource,

              dataset.value('(@Name)', 'varchar(20)') AS DataSet

FROM #data

CROSS APPLY doc.nodes('Report/DataSources/DataSource') AS datasources(datasource)

CROSS APPLY doc.nodes('Report/DataSets/DataSet') AS datasets(dataset)

WHERE id=2;



(3) Reading from extracted event viewer data


SELECT [System].value('(Computer/text())[1]', 'varchar(20)') AS SQLBox,

              [System].value('(../EventData/Data/text())[1]', 'varchar(50)') AS DB,

              [System].value('(TimeCreated/@SystemTime)[1]', 'varchar(20)') AS StartupTime

FROM #data

CROSS APPLY doc.nodes('Events/Event/System') AS events([System])

WHERE id=3

AND [System].value('(EventRecordID/text())[1]', 'int')=16563

AND [System].value('(Channel/text())[1]', 'varchar(20)')='Application';




(4) Reading from a SSIS package


SELECT x.value('(@ExecutableType)[1]', 'varchar(100)') AS PkgType,

              x.value('(Property[@Name="CreatorName"])[1]', 'varchar(100)') AS Creator,

              x.value('(Property[@Name="CreationDate"])[1]', 'varchar(100)') AS CreatedOn,

              x.value('(Property[@Name="CreatorComputerName"])[1]', 'varchar(100)') AS Computer

FROM #data

CROSS APPLY doc.nodes('Executable') AS ex(x)

WHERE id=4;




(5) Reading from an SQL trace (XML format)


SELECT  e.value('(@name)[1]', 'varchar(100)') AS [event],

              e.value('(Column[@name="StartTime"]/text())[1]', 'varchar(100)') AS StartTime,

              e.value('(Column[@id="1"]/text())[1]', 'varchar(100)') AS Command

FROM #data

CROSS APPLY doc.nodes('TraceData/Events/Event') AS events(e)

WHERE id=5;

... and the results:


Today I demonstrated how to use T-SQL to read from different XML data structures. Thanks for reading!


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Last Updated: 5/21/2013 (Posted)