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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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  • Wpf. Chart optimization. More than million points

    - by Evgeny
    I have custom control - chart with size, for example, 300x300 pixels and more than one million points (maybe less) in it. And its clear that now he works very slowly. I am searching for algoritm which will show only few points with minimal visual difference. I have link to component which have functionallity exactly what i need (2 million points demo): http://www.mindscape.co.nz/demo/SilverlightElements/demopage.html#/ChartOverviewPage I will be grateful for any matherials, links or thoughts how to realize such functionallity.

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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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