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  • Search Engine Optimization For Beginners

    Learning about the SEO techniques can be scary and a bit overwhelming to say the least. If you do not know anything about SEO now is the time to learn, before trying to do it with just a little bit of knowledge, you will fail if you do it that way.

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  • Search Engine Optimization

    The best way a company can inform its public about itself is through its website. Most corporations and firms today have a website to their name. The internet has proved itself to be an open market for all kinds of products; the only problem being the trouble of attracting internet users.

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  • Search Engine Optimization Terms

    By the time you complete this multiple lesson tutorial, you'll know just what it takes to score top search engine positions for your Web sites. You'll understand how search engines crawl the Web, how they rank Web sites, and how they find previously undiscovered sites. You'll master the important HTML tags that are your key to getting your sites on a search engine's radar, and you'll see why it's important to amass as many potential keywords as possible.

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  • What is SEO (Search Engine Optimization)?

    SEO in its most basic form is a series of steps taken to make a web site search engine friendly and have it show up in the search engines. At a more advanced level, SEO can be implemented to allow the web site in question to rank high in the search engines, preferably in the first few positions.

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  • Why is WPO(whole-program optimization) not doing any improvements in my program size? (FPC 2.4.0)

    - by Gregory Smith
    I use FPC 2.4.0 for WinXP(binary from the official page), also tryed with same version but compiled from source on my comp. I put something like this: I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-1.wpo -OWsymbolliveness -CX -XX -Xs- -al -Os -oServer1.o Server I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-2.wpo -OWsymbolliveness -Fwserver-1.wpo -Owsymbolliveness -CX -XX -Xs- -al -Os -oServer2.o Server ..(up to 100 times) but always same .wpo files, and same .o sizes(.s, assembly files change intermittently) I also not(through compiler messages), that not used variables are still alive. Also tryed -OWall -owall What am i doing wrong?

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  • Pure Java open-source libraries for portfolio selection (= constrained, non-linear optimization)?

    - by __roland__
    Does anyone know or has experience with a pure Java library to select portfolios or do some similar kinds of quadratic programming with constraints? There seems to be a lot of tools, as already discussed elsewhere - but what I would like to use is a pure Java implementation. Since I want to call the library from within another open-source software with a BSD-ish license I would prefer LGPL over GPL. Any help is appreciated. If you don't know such libraries, which is the most simple algorithm you would suggest to implement? It has to cope with an inequality constraint (all x_i = 0) and an equality constraint (sum of all x_i = 1).

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  • Mysql optimization question - How to apply AND logic in search and limit on results in one query?

    - by sandeepan-nath
    This is a little long but I have provided all the database structures and queries so that you can run it immediately and help me. Run the following queries:- CREATE TABLE IF NOT EXISTS `Tutor_Details` ( `id_tutor` int(10) NOT NULL auto_increment, `firstname` varchar(100) NOT NULL default '', `surname` varchar(155) NOT NULL default '', PRIMARY KEY (`id_tutor`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=41 ; INSERT INTO `Tutor_Details` (`id_tutor`,`firstname`, `surname`) VALUES (1, 'Sandeepan', 'Nath'), (2, 'Bob', 'Cratchit'); CREATE TABLE IF NOT EXISTS `Classes` ( `id_class` int(10) unsigned NOT NULL auto_increment, `id_tutor` int(10) unsigned NOT NULL default '0', `class_name` varchar(255) default NULL, PRIMARY KEY (`id_class`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=229 ; INSERT INTO `Classes` (`id_class`,`class_name`, `id_tutor`) VALUES (1, 'My Class', 1), (2, 'Sandeepan Class', 2); CREATE TABLE IF NOT EXISTS `Tags` ( `id_tag` int(10) unsigned NOT NULL auto_increment, `tag` varchar(255) default NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=18 ; INSERT INTO `Tags` (`id_tag`, `tag`) VALUES (1, 'Bob'), (6, 'Class'), (2, 'Cratchit'), (4, 'Nath'), (3, 'Sandeepan'), (5, 'My'); CREATE TABLE IF NOT EXISTS `Tutors_Tag_Relations` ( `id_tag` int(10) unsigned NOT NULL default '0', `id_tutor` int(10) default NULL, KEY `Tutors_Tag_Relations` (`id_tag`), KEY `id_tutor` (`id_tutor`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `Tutors_Tag_Relations` (`id_tag`, `id_tutor`) VALUES (3, 1), (4, 1), (1, 2), (2, 2); CREATE TABLE IF NOT EXISTS `Class_Tag_Relations` ( `id_tag` int(10) unsigned NOT NULL default '0', `id_class` int(10) default NULL, `id_tutor` int(10) NOT NULL, KEY `Class_Tag_Relations` (`id_tag`), KEY `id_class` (`id_class`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `Class_Tag_Relations` (`id_tag`, `id_class`, `id_tutor`) VALUES (5, 1, 1), (6, 1, 1), (3, 2, 2), (6, 2, 2); Following is about the tables:- There are tutors who create classes. Tutor_Details - Stores tutors Classes - Stores classes created by tutors And for searching we are using a tags based approach. All the keywords are stored in tags table (while classes/tutors are created) and tag relations are entered in Tutor_Tag_Relations and Class_Tag_Relations tables (for tutors and classes respectively)like this:- Tags - id_tag tag (this is a a unique field) Tutors_Tag_Relations - Stores tag relations while the tutors are created. Class_Tag_Relations - Stores tag relations while any tutor creates a class In the present data in database, tutor "Sandeepan Nath" has has created class "My Class" and "Bob Cratchit" has created "Sandeepan Class". 3.Requirement The requirement is to return tutor records from Tutor_Details table such that all the search terms (AND logic) are present in the union of these two sets - 1. Tutor_Details table 2. classes created by a tutor in Classes table) Example search and expected results:- Search Term Result "Sandeepan Class" Tutor Sandeepan Nath's record from Tutor Details table "Class" Both the tutors from ... Most importantly, there should be only one mysql query and a LIMIT applicable on the number of results. Following is a working query which I have so far written (It just applies OR logic of search key words instead of the desired AND logic). SELECT td . * FROM Tutor_Details AS td LEFT JOIN Tutors_Tag_Relations AS ttagrels ON td.id_tutor = ttagrels.id_tutor LEFT JOIN Classes AS wc ON td.id_tutor = wc.id_tutor INNER JOIN Class_Tag_Relations AS wtagrels ON td.id_tutor = wtagrels.id_tutor LEFT JOIN Tags AS t ON t.id_tag = ttagrels.id_tag OR t.id_tag = wtagrels.id_tag WHERE t.tag LIKE '%Sandeepan%' OR t.tag LIKE '%Nath%' GROUP BY td.id_tutor LIMIT 20 Please help me with anything you can. Thanks

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  • Some optimization about the code (computing ranks of a vector)?

    - by user1748356
    The following code is a function (performance-critical) to compute tied ranks of a vector: mergeSort(x,inds,ci); //a sort function to sort vector x of length ci, also returns keys (inds) of x. int tj=0; double xi=x[0]; for (int j = 1; j < ci; ++j) { if (x[j] > xi) { double rankvalue = 0.5 * (j - 1 + tj); for (int k = tj; k < j; ++k) { ranks[inds[k]]=rankvalue; }; tj = j; xi = x[j]; }; }; double rankvalue = 0.5 * (ci - 1 + tj); for (int k = tj; k < ci; ++k) { ranks[inds[k]]=rankvalue; }; The problem is, the supposed performance bottleneck mergeSort(), which is O(NlogN) is several times faster than the other part of codes (which is O(N)), which suggests there is room for huge improvment with the other part of the codes, any advices?

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  • R: Are there any alternatives to loops for subsetting from an optimization standpoint?

    - by Adam
    A recurring analysis paradigm I encounter in my research is the need to subset based on all different group id values, performing statistical analysis on each group in turn, and putting the results in an output matrix for further processing/summarizing. How I typically do this in R is something like the following: data.mat <- read.csv("...") groupids <- unique(data.mat$ID) #Assume there are then 100 unique groups results <- matrix(rep("NA",300),ncol=3,nrow=100) for(i in 1:100) { tempmat <- subset(data.mat,ID==groupids[i]) #Run various stats on tempmat (correlations, regressions, etc), checking to #make sure this specific group doesn't have NAs in the variables I'm using #and assign results to x, y, and z, for example. results[i,1] <- x results[i,2] <- y results[i,3] <- z } This ends up working for me, but depending on the size of the data and the number of groups I'm working with, this can take up to three days. Besides branching out into parallel processing, is there any "trick" for making something like this run faster? For instance, converting the loops into something else (something like an apply with a function containing the stats I want to run inside the loop), or eliminating the need to actually assign the subset of data to a variable?

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  • R optimization: How can I avoid a for loop in this situation?

    - by chrisamiller
    I'm trying to do a simple genomic track intersection in R, and running into major performance problems, probably related to my use of for loops. In this situation, I have pre-defined windows at intervals of 100bp and I'm trying to calculate how much of each window is covered by the annotations in mylist. Graphically, it looks something like this: 0 100 200 300 400 500 600 windows: |-----|-----|-----|-----|-----|-----| mylist: |-| |-----------| So I wrote some code to do just that, but it's fairly slow and has become a bottleneck in my code: ##window for each 100-bp segment windows <- numeric(6) ##second track mylist = vector("list") mylist[[1]] = c(1,20) mylist[[2]] = c(120,320) ##do the intersection for(i in 1:length(mylist)){ st <- floor(mylist[[i]][1]/100)+1 sp <- floor(mylist[[i]][2]/100)+1 for(j in st:sp){ b <- max((j-1)*100, mylist[[i]][1]) e <- min(j*100, mylist[[i]][2]) windows[j] <- windows[j] + e - b + 1 } } print(windows) [1] 20 81 101 21 0 0 Naturally, this is being used on data sets that are much larger than the example I provide here. Through some profiling, I can see that the bottleneck is in the for loops, but my clumsy attempt to vectorize it using *apply functions resulted in code that runs an order of magnitude more slowly. I suppose I could write something in C, but I'd like to avoid that if possible. Can anyone suggest another approach that will speed this calculation up?

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  • Python2.7: How can I speed up this bit of code (loop/lists/tuple optimization)?

    - by user89
    I repeat the following idiom again and again. I read from a large file (sometimes, up to 1.2 million records!) and store the output into an SQLite databse. Putting stuff into the SQLite DB seems to be fairly fast. def readerFunction(recordSize, recordFormat, connection, outputDirectory, outputFile, numObjects): insertString = "insert into NODE_DISP_INFO(node, analysis, timeStep, H1_translation, H2_translation, V_translation, H1_rotation, H2_rotation, V_rotation) values (?, ?, ?, ?, ?, ?, ?, ?, ?)" analysisNumber = int(outputPath[-3:]) outputFileObject = open(os.path.join(outputDirectory, outputFile), "rb") outputFileObject, numberOfRecordsInFileObject = determineNumberOfRecordsInFileObjectGivenRecordSize(recordSize, outputFileObject) numberOfRecordsPerObject = (numberOfRecordsInFileObject//numberOfObjects) loop1StartTime = time.time() for i in range(numberOfRecordsPerObject ): processedRecords = [] loop2StartTime = time.time() for j in range(numberOfObjects): fout = outputFileObject .read(recordSize) processedRecords.append(tuple([j+1, analysisNumber, i] + [x for x in list(struct.unpack(recordFormat, fout))])) loop2EndTime = time.time() print "Time taken to finish loop2: {}".format(loop2EndTime-loop2StartTime) dbInsertStartTime = time.time() connection.executemany(insertString, processedRecords) dbInsertEndTime = time.time() loop1EndTime = time.time() print "Time taken to finish loop1: {}".format(loop1EndTime-loop1StartTime) outputFileObject.close() print "Finished reading output file for analysis {}...".format(analysisNumber) When I run the code, it seems that "loop 2" and "inserting into the database" is where most execution time is spent. Average "loop 2" time is 0.003s, but it is run up to 50,000 times, in some analyses. The time spent putting stuff into the database is about the same: 0.004s. Currently, I am inserting into the database every time after loop2 finishes so that I don't have to deal with running out RAM. What could I do to speed up "loop 2"?

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  • SQL SERVER – Out of the Box – Activty and Performance Reports from SSSMS

    - by pinaldave
    SQL Server management Studio 2008 is wonderful tool and has many different features. Many times, an average user does not use them as they are not aware about these features. Today, we will learn one such feature. SSMS comes with many inbuilt performance and activity reports, but we do not use it to the full potential. Let us see how we can access these standard reports. Connect to SQL Server Node >> Right Click on it >> Go to Reports >> Click on Standard Reports >> Pick Any Report. Click to Enlarge You can see there are many reports, which an average users needs right away, are available there. Let me list all the reports available. Server Dashboard Configuration Changes History Schema Changes History Scheduler Health Memory Consumption Activity – All Blocking Transactions Activity – All Cursors Activity – All Sessions Activity – Top Sessions Activity – Dormant Sessions Activity -  Top Connections Top Transactions by Age Top Transactions by Blocked Transactions Count Top Transactions by Locks Count Performance – Batch Execution Statistics Performance – Object Execution Statistics Performance – Top Queries by Average CPU Time Performance – Top Queries by Average IO Performance – Top Queries by Total CPU Time Performance – Top Queries by Total IO Service Broker Statistics Transactions Log Shipping Status In fact, when you look at the above list, it is fairly clear that they are very thought out and commonly needed reports that are available in SQL Server 2008. Let us run a couple of reports and observe their result. Performance – Top Queries by Total CPU Time Click to Enlarge Memory Consumption Click to Enlarge There are options for custom reports as well, which we can configure. We will learn about them in some other post. Additionally, you can right click on the reports and export in Excel or PDF. I think this tool can really help those who are just looking for some quick details. Does any of you use this feature, or this feature has some limitations and You would like to see more features? Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Summary of Month – Wait Type – Day 28 of 28

    - by pinaldave
    I am glad to announce that the month of Wait Types and Queues very successful. I am glad that it was very well received and there was great amount of participation from community. I am fortunate to have some of the excellent comments throughout the series. I want to dedicate this series to all the guest blogger – Jonathan, Jacob, Glenn, and Feodor for their kindness to take a participation in this series. Here is the complete list of the blog posts in this series. I enjoyed writing the series and I plan to continue writing similar series. Please offer your opinion. SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28 SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28 SQL SERVER – DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28 SQL SERVER – Capturing Wait Types and Wait Stats Information at Interval – Wait Type – Day 5 of 28 SQL SERVER – CXPACKET – Parallelism – Usual Solution – Wait Type – Day 6 of 28 SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28 SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28 SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28 SQL SERVER – IO_COMPLETION – Wait Type – Day 10 of 28 SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28 SQL SERVER – PAGELATCH_DT, PAGELATCH_EX, PAGELATCH_KP, PAGELATCH_SH, PAGELATCH_UP – Wait Type – Day 12 of 28 SQL SERVER – FT_IFTS_SCHEDULER_IDLE_WAIT – Full Text – Wait Type – Day 13 of 28 SQL SERVER – BACKUPIO, BACKUPBUFFER – Wait Type – Day 14 of 28 SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28 SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28 SQL SERVER – WRITELOG – Wait Type – Day 17 of 28 SQL SERVER – LOGBUFFER – Wait Type – Day 18 of 28 SQL SERVER – PREEMPTIVE and Non-PREEMPTIVE – Wait Type – Day 19 of 28 SQL SERVER – MSQL_XP – Wait Type – Day 20 of 28 SQL SERVER – Guest Posts – Feodor Georgiev – The Context of Our Database Environment – Going Beyond the Internal SQL Server Waits – Wait Type – Day 21 of 28 SQL SERVER – Guest Post – Jacob Sebastian – Filestream – Wait Types – Wait Queues – Day 22 of 28 SQL SERVER – OLEDB – Link Server – Wait Type – Day 23 of 28 SQL SERVER – 2000 – DBCC SQLPERF(waitstats) – Wait Type – Day 24 of 28 SQL SERVER – 2011 – Wait Type – Day 25 of 28 SQL SERVER – Guest Post – Glenn Berry – Wait Type – Day 26 of 28 SQL SERVER – Best Reference – Wait Type – Day 27 of 28 SQL SERVER – Summary of Month – Wait Type – Day 28 of 28 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, SQLServer, T SQL, Technology

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  • SQL SERVER – Difference Between DATETIME and DATETIME2

    - by pinaldave
    Yesterday I have written a very quick blog post on SQL SERVER – Difference Between GETDATE and SYSDATETIME and I got tremendous response for the same. I suggest you read that blog post before continuing this blog post today. I had asked people to honestly take part and share their view about above two system function. There are few emails as well few comments on the blog post asking question how did I come to know the difference between the same. The answer is real world issues. I was called in for performance tuning consultancy where I was asked very strange question by one developer. Here is the situation he was facing. System had a single table with two different column of datetime. One column was datelastmodified and second column was datefirstmodified. One of the column was DATETIME and another was DATETIME2. Developer was populating them with SYSDATETIME respectively. He was always thinking that the value inserted in the table will be the same. This table was only accessed by INSERT statement and there was no updates done over it in application.One fine day he ran distinct on both of this column and was in for surprise. He always thought that both of the table will have same data, but in fact they had very different data. He presented this scenario to me. I said this can not be possible but when looked at the resultset, I had to agree with him. Here is the simple script generated to demonstrate the problem he was facing. This is just a sample of original table. DECLARE @Intveral INT SET @Intveral = 10000 CREATE TABLE #TimeTable (FirstDate DATETIME, LastDate DATETIME2) WHILE (@Intveral > 0) BEGIN INSERT #TimeTable (FirstDate, LastDate) VALUES (SYSDATETIME(), SYSDATETIME()) SET @Intveral = @Intveral - 1 END GO SELECT COUNT(DISTINCT FirstDate) D_GETDATE, COUNT(DISTINCT LastDate) D_SYSGETDATE FROM #TimeTable GO SELECT DISTINCT a.FirstDate, b.LastDate FROM #TimeTable a INNER JOIN #TimeTable b ON a.FirstDate = b.LastDate GO SELECT * FROM #TimeTable GO DROP TABLE #TimeTable GO Let us see the resultset. You can clearly see from result that SYSDATETIME() does not populate the same value in the both of the field. In fact the value is either rounded down or rounded up in the field which is DATETIME. Event though we are populating the same value, the values are totally different in both the column resulting the SELF JOIN fail and display different DISTINCT values. The best policy is if you are using DATETIME use GETDATE() and if you are suing DATETIME2 use SYSDATETIME() to populate them with current date and time to accurately address the precision. As DATETIME2 is introduced in SQL Server 2008, above script will only work with SQL SErver 2008 and later versions. I hope I have answered few questions asked yesterday. Reference: Pinal Dave (http://www.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL DateTime, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Index Created on View not Used Often – Observation of the View – Part 2

    - by pinaldave
    Earlier, I have written an article about SQL SERVER – Index Created on View not Used Often – Observation of the View. I received an email from one of the readers, asking if there would no problems when we create the Index on the base table. Well, we need to discuss this situation in two different cases. Before proceeding to the discussion, I strongly suggest you read my earlier articles. To avoid the duplication, I am not going to repeat the code and explanation over here. In all the earlier cases, I have explained in detail how Index created on the View is not utilized. SQL SERVER – Index Created on View not Used Often – Limitation of the View 12 SQL SERVER – Index Created on View not Used Often – Observation of the View SQL SERVER – Indexed View always Use Index on Table As per earlier blog posts, so far we have done the following: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View However, the blog reader who emailed me suggests the extension of the said logic, which is as follows: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View Create Index on the Base Table Write SELECT with ORDER BY on View After doing the last two steps, the question is “Will the query on the View utilize the Index on the View, or will it still use the Index of the base table?“ Let us first run the Create example. USE tempdb GO IF EXISTS (SELECT * FROM sys.views WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[SampleView]')) DROP VIEW [dbo].[SampleView] GO IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[mySampleTable]') AND TYPE IN (N'U')) DROP TABLE [dbo].[mySampleTable] GO -- Create SampleTable CREATE TABLE mySampleTable (ID1 INT, ID2 INT, SomeData VARCHAR(100)) INSERT INTO mySampleTable (ID1,ID2,SomeData) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY o1.name), ROW_NUMBER() OVER (ORDER BY o2.name), o2.name FROM sys.all_objects o1 CROSS JOIN sys.all_objects o2 GO -- Create View CREATE VIEW SampleView WITH SCHEMABINDING AS SELECT ID1,ID2,SomeData FROM dbo.mySampleTable GO -- Create Index on View CREATE UNIQUE CLUSTERED INDEX [IX_ViewSample] ON [dbo].[SampleView] ( ID2 ASC ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO -- Create Index on Original Table -- On Column ID1 CREATE UNIQUE CLUSTERED INDEX [IX_OriginalTable] ON mySampleTable ( ID1 ASC ) GO -- On Column ID2 CREATE UNIQUE NONCLUSTERED INDEX [IX_OriginalTable_ID2] ON mySampleTable ( ID2 ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO Now let us see the execution plans for both of the SELECT statement. Before Index on Base Table (with Index on View): After Index on Base Table (with Index on View): Looking at both executions, it is very clear that with or without, the View is using Indexes. Alright, I have written 11 disadvantages of the Views. Now I have written one case where the View is using Indexes. Anybody who says that I am being harsh on Views can say now that I found one place where Index on View can be helpful. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL View, SQLServer, T SQL, Technology

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  • SQL SERVER – Index Created on View not Used Often – Observation of the View

    - by pinaldave
    I always enjoy writing about concepts on Views. Views are frequently used concepts, and so it’s not surprising that I have seen so many misconceptions about this subject. To clear such misconceptions, I have previously written the article SQL SERVER – The Limitations of the Views – Eleven and more…. I also wrote a follow up article wherein I demonstrated that without even creating index on the basic table, the query on the View will not use the View. You can read about this demonstration over here: SQL SERVER – Index Created on View not Used Often – Limitation of the View 12. I promised in that post that I would also write an article where I would demonstrate the condition where the Index will be used. I got many responses suggesting that I can do that with using NOEXPAND; I agree. I have already written about this in my original summary article. Here is a way for you to see how Index created on View can be utilized. We will do the following steps on this exercise: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View USE tempdb GO IF EXISTS (SELECT * FROM sys.views WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[SampleView]')) DROP VIEW [dbo].[SampleView] GO IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[mySampleTable]') AND TYPE IN (N'U')) DROP TABLE [dbo].[mySampleTable] GO -- Create SampleTable CREATE TABLE mySampleTable (ID1 INT, ID2 INT, SomeData VARCHAR(100)) INSERT INTO mySampleTable (ID1,ID2,SomeData) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY o1.name), ROW_NUMBER() OVER (ORDER BY o2.name), o2.name FROM sys.all_objects o1 CROSS JOIN sys.all_objects o2 GO -- Create View CREATE VIEW SampleView WITH SCHEMABINDING AS SELECT ID1,ID2,SomeData FROM dbo.mySampleTable GO -- Create Index on View CREATE UNIQUE CLUSTERED INDEX [IX_ViewSample] ON [dbo].[SampleView] ( ID2 ASC ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO When we check the execution plan for this , we find it clearly that the Index created on the View is utilized. ORDER BY clause uses the Index created on the View. I hope this makes the puzzle simpler on how the Index is used on the View. Again, I strongly recommend reading my earlier series about the limitations of the Views found here: SQL SERVER – The Limitations of the Views – Eleven and more…. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL View, T SQL, Technology

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  • SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer

    - by pinaldave
    Incredibly, SQL Server has so much information to share with us. Every single day, I am amazed with this SQL Server technology. Sometimes I find several interesting information by just querying few of the DMV. And when I present this info in front of my client during performance tuning consultancy, they are surprised with my findings. Today, I am going to share one of the hidden gems of DMV with you, the one which I frequently use to understand what’s going on under the hood of SQL Server. SQL Server keeps the record of most of the operations of the Query Optimizer. We can learn many interesting details about the optimizer which can be utilized to improve the performance of server. SELECT * FROM sys.dm_exec_query_optimizer_info WHERE counter IN ('optimizations', 'elapsed time','final cost', 'insert stmt','delete stmt','update stmt', 'merge stmt','contains subquery','tables', 'hints','order hint','join hint', 'view reference','remote query','maximum DOP', 'maximum recursion level','indexed views loaded', 'indexed views matched','indexed views used', 'indexed views updated','dynamic cursor request', 'fast forward cursor request') All occurrence values are cumulative and are set to 0 at system restart. All values for value fields are set to NULL at system restart. I have removed a few of the internal counters from the script above, and kept only documented details. Let us check the result of the above query. As you can see, there is so much vital information that is revealed in above query. I can easily say so many things about how many times Optimizer was triggered and what the average time taken by it to optimize my queries was. Additionally, I can also determine how many times update, insert or delete statements were optimized. I was able to quickly figure out that my client was overusing the Query Hints using this dynamic management view. If you have been reading my blog, I am sure you are aware of my series related to SQL Server Views SQL SERVER – The Limitations of the Views – Eleven and more…. With this, I can take a quick look and figure out how many times Views were used in various solutions within the query. Moreover, you can easily know what fraction of the optimizations has been involved in tuning server. For example, the following query would tell me, in total optimizations, what the fraction of time View was “reference“. As this View also includes system Views and DMVs, the number is a bit higher on my machine. SELECT (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'view reference') / (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'optimizations') AS ViewReferencedFraction Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – Public Training and Private Training – Differences and Similarities

    - by pinaldave
    Earlier this year, I was on Road SQL Server Seminars. I did many SQL Server Performance Trainings and SQL Server Performance Consultations throughout the year but I feel the most rewarding exercise is always the one when instructor learns something from students, too. I was just talking to my wife, Nupur – she manages my logistics and administration related activities – and she pointed out that this year I have done 62% consultations and 38% trainings. I was bit surprised as I thought the numbers would be reversed. Every time I review the year, I think of training done at organizations. Well, I cannot argue with reality, I have done more consultations (some would call them projects) than training. I told my wife that I enjoy consultations more than training. She promptly asked me a question which was not directly related but made me think for long time, and in the end resulted in this blog post. Nupur asked me: what do I enjoy the most, public training or private training? I had a long conversation with her on this subject. I am not going to write long blog post which can change your life here. This is rather a small post condensing my one hour discussion into 200 words. Public Training is fun because… There are lots of different kinds of attendees There are always vivid questions Lots of questions on questions Less interest in theory and more interest in demos Good opportunity of future business Private Training is fun because… There is a focused interest One question is discussed deeply because of existing company issues More interest in “how it happened” concepts – under the hood operations Good connection with attendees This is also a good opportunity of future business Here I will stop my monologue and I want to open up this question to all of you: Question to Attendees - Which one do you enjoy the most – Public Training or Private Training? Question to Trainers - What do you enjoy the most – Public Training or Private Training? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLAuthority News, T SQL, Technology

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  • Correct way to handle path-finding collision matrix

    - by Xander Lamkins
    Here is an example of me utilizing path finding. The red grid represents the grid utilized by my A* library to locate a distance. This picture is only an example, currently it is all calculated on the 1x1 pixel level (pretty darn laggy). I want to make it so that the farther I click, the less accurate it will be (split the map into larger grid pieces). Edit: as mentioned by Eric, this is not a required game mechanic. I am perfectly fine with any method that allows me to make this accurate while still fast. This isn't the really the topic of this question though. The problem I have is, my current library uses a two dimensional grid of integers. The higher the number in a cell, the more resistance for that grid tile. Currently I'm setting all unwalkable spots to Integer Max. Here is an example of what I want: I'm just not sure how I should set up the arrays of integers of the grid. Every time an element is added/removed to/from the game, it's collision details are updated in the table. Here is a picture of what the map looks like on my collision layer: I probably shouldn't be creating new arrays every time I have to do a path find because my game needs to support tons of PF at the same time. Should I have multiple arrays that are all updated when the dynamic elements are updated (a building is built/a building is destroyed). The problem I see with this is that it will probably make the creation and destruction of buildings a little more laggy than I would want because it would be setting the collision grid for each built in accuracy level. I would also have to add more/remove some arrays if I ever in the future changed the map size. Should I generate the new array based on an accuracy value every time I need to PF? The problem I see with this is that it will probably make any form of PF just as laggy because it will have to search through a MapWidth x MapHeight number of cells to shrink it all down. Or is there a better way? I'm certainly not the best at optimizing really anything. I've just started dealing with XNA so I'm not used to having optimization code really doing much of an affect until now... :( If you need code examples, please ask. I'll add it as an edit. EDIT: While this doesn't directly relate to the question, I figure the more information I provide, the better. To keep your units from moving as accurately to the players desired position, I've decided that once the unit PFs over to the less accurate grid piece, it will then PF on a more accurate level to the exact position requested.

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  • Does OO, TDD, and Refactoring to Smaller Functions affect Speed of Code?

    - by Dennis
    In Computer Science field, I have noticed a notable shift in thinking when it comes to programming. The advice as it stands now is write smaller, more testable code refactor existing code into smaller and smaller chunks of code until most of your methods/functions are just a few lines long write functions that only do one thing (which makes them smaller again) This is a change compared to the "old" or "bad" code practices where you have methods spanning 2500 lines, and big classes doing everything. My question is this: when it call comes down to machine code, to 1s and 0s, to assembly instructions, should I be at all concerned that my class-separated code with variety of small-to-tiny functions generates too much extra overhead? While I am not exactly familiar with how OO code and function calls are handled in ASM in the end, I do have some idea. I assume that each extra function call, object call, or include call (in some languages), generate an extra set of instructions, thereby increasing code's volume and adding various overhead, without adding actual "useful" code. I also imagine that good optimizations can be done to ASM before it is actually ran on the hardware, but that optimization can only do so much too. Hence, my question -- how much overhead (in space and speed) does well-separated code (split up across hundreds of files, classes, and methods) actually introduce compared to having "one big method that contains everything", due to this overhead? UPDATE for clarity: I am assuming that adding more and more functions and more and more objects and classes in a code will result in more and more parameter passing between smaller code pieces. It was said somewhere (quote TBD) that up to 70% of all code is made up of ASM's MOV instruction - loading CPU registers with proper variables, not the actual computation being done. In my case, you load up CPU's time with PUSH/POP instructions to provide linkage and parameter passing between various pieces of code. The smaller you make your pieces of code, the more overhead "linkage" is required. I am concerned that this linkage adds to software bloat and slow-down and I am wondering if I should be concerned about this, and how much, if any at all, because current and future generations of programmers who are building software for the next century, will have to live with and consume software built using these practices. UPDATE: Multiple files I am writing new code now that is slowly replacing old code. In particular I've noted that one of the old classes was a ~3000 line file (as mentioned earlier). Now it is becoming a set of 15-20 files located across various directories, including test files and not including PHP framework I am using to bind some things together. More files are coming as well. When it comes to disk I/O, loading multiple files is slower than loading one large file. Of course not all files are loaded, they are loaded as needed, and disk caching and memory caching options exist, and yet still I believe that loading multiple files takes more processing than loading a single file into memory. I am adding that to my concern.

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  • SQL SERVER – Update Statistics are Sampled By Default

    - by pinaldave
    After reading my earlier post SQL SERVER – Create Primary Key with Specific Name when Creating Table on Statistics, I have received another question by a blog reader. The question is as follows: Question: Are the statistics sampled by default? Answer: Yes. The sampling rate can be specified by the user and it can be anywhere between a very low value to 100%. Let us do a small experiment to verify if the auto update on statistics is left on. Also, let’s examine a very large table that is created and statistics by default- whether the statistics are sampled or not. USE [AdventureWorks] GO -- Create Table CREATE TABLE [dbo].[StatsTest]( [ID] [int] IDENTITY(1,1) NOT NULL, [FirstName] [varchar](100) NULL, [LastName] [varchar](100) NULL, [City] [varchar](100) NULL, CONSTRAINT [PK_StatsTest] PRIMARY KEY CLUSTERED ([ID] ASC) ) ON [PRIMARY] GO -- Insert 1 Million Rows INSERT INTO [dbo].[StatsTest] (FirstName,LastName,City) SELECT TOP 1000000 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Update the statistics UPDATE STATISTICS [dbo].[StatsTest] GO -- Shows the statistics DBCC SHOW_STATISTICS ("StatsTest"PK_StatsTest) GO -- Clean up DROP TABLE [dbo].[StatsTest] GO Now let us observe the result of the DBCC SHOW_STATISTICS. The result shows that Resultset is for sure sampling for a large dataset. The percentage of sampling is based on data distribution as well as the kind of data in the table. Before dropping the table, let us check first the size of the table. The size of the table is 35 MB. Now, let us run the above code with lesser number of the rows. USE [AdventureWorks] GO -- Create Table CREATE TABLE [dbo].[StatsTest]( [ID] [int] IDENTITY(1,1) NOT NULL, [FirstName] [varchar](100) NULL, [LastName] [varchar](100) NULL, [City] [varchar](100) NULL, CONSTRAINT [PK_StatsTest] PRIMARY KEY CLUSTERED ([ID] ASC) ) ON [PRIMARY] GO -- Insert 1 Hundred Thousand Rows INSERT INTO [dbo].[StatsTest] (FirstName,LastName,City) SELECT TOP 100000 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Update the statistics UPDATE STATISTICS [dbo].[StatsTest] GO -- Shows the statistics DBCC SHOW_STATISTICS ("StatsTest"PK_StatsTest) GO -- Clean up DROP TABLE [dbo].[StatsTest] GO You can see that Rows Sampled is just the same as Rows of the table. In this case, the sample rate is 100%. Before dropping the table, let us also check the size of the table. The size of the table is less than 4 MB. Let us compare the Result set just for a valid reference. Test 1: Total Rows: 1000000, Rows Sampled: 255420, Size of the Table: 35.516 MB Test 2: Total Rows: 100000, Rows Sampled: 100000, Size of the Table: 3.555 MB The reason behind the sample in the Test1 is that the data space is larger than 8 MB, and therefore it uses more than 1024 data pages. If the data space is smaller than 8 MB and uses less than 1024 data pages, then the sampling does not happen. Sampling aids in reducing excessive data scan; however, sometimes it reduces the accuracy of the data as well. Please note that this is just a sample test and there is no way it can be claimed as a benchmark test. The result can be dissimilar on different machines. There are lots of other information can be included when talking about this subject. I will write detail post covering all the subject very soon. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics

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