Get all MS SQL Server stored procedure dependencies

 select distinct 'proc' =s7.name,  'name' = (s6.name+ '.' + o1.name),
    type = substring(v2.name, 5, 66) 
   from  sys.objects  o1
   ,master.dbo.spt_values v2
   ,sysdepends  d3
   ,master.dbo.spt_values u4
   ,master.dbo.spt_values w5 --11667
   ,sys.schemas  s6
   ,sys.procedures s7
   
  where  o1.object_id = d3.depid
  and  o1.type = substring(v2.name,1,2) collate database_default and v2.type = 'O9T'
  and  u4.type = 'B' and u4.number = d3.resultobj
  and  w5.type = 'B' and w5.number = d3.readobj|d3.selall
  and  d3.id = s7.object_id
  and  o1.schema_id = s6.schema_id
  and deptype < 2
 order by s7.name, s6.name + '.' +o1.name

Reading

I just finished reading the Dresden Files IX - White Night from Jim Butcher.
Nice book, not my preferred Dresden story but a nice one.
This is the last one I had.

Shuffling a LinkedList (c#)

Since I could not google a sample shuffle function for the LinkedList, here it goes one:

public static void Shuffle(LinkedList list)
{
   Random rand = new Random();

   for (LinkedListNode n = list.First; n != null; n = n.Next)
   {
       T v = n.Value;
       if (rand.Next(0, 2) == 1)
       {
           n.Value = list.Last.Value;
           list.Last.Value = v;
       }
       else
       {
           n.Value = list.First.Value;
           list.First.Value = v;
       }
   }
}

[TestMethod]
public void ShufleTest()
{
   LinkedList<string> list = new LinkedList<string>();
   list.AddLast("a");
   list.AddLast("b");
   list.AddLast("c");
   list.AddLast("d");
   list.AddLast("e");
   Shuffle(list);
   foreach(string s in list) {
       Console.WriteLine(s);
   }
}

Scalability podcast

I found this podcast some time ago while researching about garbage collection.

It is very interesting. I was listening it again and saw how it helps to understand some scalability issues that we are dealing in order to make our game scale.


Extreme Transaction Processing,
Low Latency and Performance

In this podcast, John, who has over 30 years of experience in investment banking and integration technology, John will cover several case studies of extreme transaction processing, low latency and high performance systems and offer insight into what we might expect to see in mainstream in the near future.

http://www.theserverside.com/tt/knowledgecenter/knowledgecenter.tss?l=PodcastJohnDavies


Podcast Slides
http://www.incept5.com/library/TSS%20EJS%202008%20-%20Extreme%20Transaction%20Processing%20-%20John%20Davies.pdf


Some links to read while watching the podcast.

Extreme Transaction Processing

• http://en.wikipedia.org/wiki/Extreme_Transaction_Processing

Extreme Transaction Processing (XTP) is an exceptionally demanding form of transaction processing. Transactions of 10,000 concurrent accesses (500 transaction per second) or more would require this form of processing.

500 seens a little, don't you think?

Apache Qpid

• http://qpid.apache.org/
• http://qpid.apache.org/faq.html#FAQ-Performance
• http://www.redhat.com/f/pdf/mrg/Reference_Architecture_MRG_Messaging_Throughput.pdf

"maximum repeatable ingress rate of ~760,000/2 = 380,000 messages
per second (for 256 byte messages). Thus, if doing OPRA (Options Price Reporting Authority)
with a pack factor of 16 in 256 bytes, that would allow for (16 x 380,000 =) 6,080,000 ingress
OPRA messages/ second to 60 consumers on shared queues."

Tangosol (mentioned in the pocast, bought by Oracle)

• http://www.oracle.com/tangosol/index.html

Oracle Coherence

• http://www.oracle.com/products/middleware/coherence/index.html

GigaSpaces (mentioned in the podcast)

• http://www.gigaspaces.com/

eXtreme Scale

• http://www-01.ibm.com/software/webservers/appserv/extremescale/
• http://www.soaflexibility.com/OG1/start.html?S_CMP=rnav (video)