Search Results

Search found 21107 results on 845 pages for 'size optimization'.

Page 32/845 | < Previous Page | 28 29 30 31 32 33 34 35 36 37 38 39  | Next Page >

  • Working with Temporal Data in SQL Server

    - by Dejan Sarka
    My third Pluralsight course, Working with Temporal Data in SQL Server, is published. I am really proud on the second part of the course, where I discuss optimization of temporal queries. This was a nearly impossible task for decades. First solutions appeared only lately. I present all together six solutions (and one more that is not a solution), and I invented four of them. http://pluralsight.com/training/Courses/TableOfContents/working-with-temporal-data-sql-server

    Read the article

  • Research topics for starting and optimizing a high-traffic website

    - by user745434
    I bury a good deal of my ideas for fear that I don't know enough about scaling web applications and high-traffic websites. That said, I'd like to know of any general topics to research in order to ensure that your web app doesn't break / slow down when you start getting to Twitter-level traffic. I'm looking for research topics with, preferably, additional resources. For example: Make sure you optimize SQL queries (see High Performance MySQL Optimization)

    Read the article

  • SQL SERVER – Finding Size of a Columnstore Index Using DMVs

    - by pinaldave
    Columnstore Index is one of my favorite enhancement in SQL Server 2012. A columnstore index stores each column in a separate set of disk pages, rather than storing multiple rows per page as data traditionally has been stored. In case of the row store indexes multiple pages will contain multiple rows of the columns spanning across multiple pages. Whereas in case of column store indexes multiple pages will contain (multiple) single columns.  Columnstore Indexes are compressed by default and occupies much lesser space than regular row store index by default. One of the very common question I often see is need of the list of columnstore index along with their size and corresponding table name. I quickly re-wrote a script using DMVs sys.indexes and sys.dm_db_partition_stats. This script gives the size of the columnstore index on disk only. I am sure there will be advanced script to retrieve details related to components associated with the columnstore index. However, I believe following script is sufficient to start getting an idea of columnstore index size.  SELECT OBJECT_SCHEMA_NAME(i.OBJECT_ID) SchemaName, OBJECT_NAME(i.OBJECT_ID ) TableName, i.name IndexName, SUM(s.used_page_count) / 128.0 IndexSizeinMB FROM sys.indexes AS i INNER JOIN sys.dm_db_partition_stats AS S ON i.OBJECT_ID = S.OBJECT_ID AND I.index_id = S.index_id WHERE  i.type_desc = 'NONCLUSTERED COLUMNSTORE' GROUP BY i.OBJECT_ID, i.name Here is my introductory article written on SQL Server Fundamentals of Columnstore Index. Create a sample columnstore index based on the script described in the earlier article. It will give the following results. Please feel free to suggest improvement to script so I can further modify it to accommodate enhancements. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: ColumnStore Index

    Read the article

  • Optimal sprite size for rotations

    - by Panda Pajama
    I am making a sprite based game, and I have a bunch of images that I get in a ridiculously large resolution and I scale them to the desired sprite size (for example 64x64 pixels) before converting them to a game resource, so when draw my sprite inside the game, I don't have to scale it. However, if I rotate this small sprite inside the game (engine agnostically), some destination pixels will get interpolated, and the sprite will look smudged. This is of course dependent on the rotation angle as well as the interpolation algorithm, but regardless, there is not enough data to correctly sample a specific destination pixel. So there are two solutions I can think of. The first is to use the original huge image, rotate it to the desired angles, and then downscale all the reaulting variations, and put them in an atlas, which has the advantage of being quite simple to implement, but naively consumes twice as much sprite space for each rotation (each rotation must be inscribed in a circle whose diameter is the diagonal of the original sprite's rectangle, whose area is twice of that original rectangle, supposing square sprites). It also has the disadvantage of only having a predefined set of rotations available, which may be okay or not depending on the game. So the other choice would be to store a larger image, and rotate and downscale while rendering, which leads to my question. What is the optimal size for this sprite? Optimal meaning that a larger image will have no effect in the resulting image. This is definitely dependent on the image size, the amount of desired rotations without data loss down to 1/256, which is the minimum representable color difference. I am looking for a theoretical general answer to this problem, because trying a bunch of sizes may be okay, but is far from optimal.

    Read the article

  • Javascript Isometric draw optimization

    - by hustlerinc
    I'm having trouble with isometric tiles drawing. At the moment I got an array with the tiles i want to draw. And it all works fine until i increase the size of the array. Since I draw ALL tiles on the map it really affects the game performance (obviously) :D. My problem is I'm no genius when it comes to javascript and I haven't managed to just draw what is in viewport. Should be fairly simple for an expert though because its fixed sizes etc. Canvas is 960x480 pixels, each tile 64x32. This gives 16 tiles on first row, 15 on the next etc. for a total of 16 rows. Tile 0,0 is in the top-right corner. And draws X up to down and Y right to left. Going through the tiles on the first row from left to right as +X -Y. Here is the relevant part of my drawMap() function drawMap(){ var tileW = 64; // Tile Width var tileH = 32; // Tile Height var mapX = 960-32; var mapY = -16; for(i=0;i<map.length;i++){ for(j=0;j<map[i].length;j++){ var drawTile = map[i][j]; var drawObj = objectMap[i][j]; var xpos = (i-j)*tileH + mapX; var ypos = (i+j)*tileH/2 + mapY; // Place the tiles isometric. ctx.drawImage(tileImg[drawTile],xpos,ypos); if(drawObj){ ctx.drawImage(objectImg[drawObj-1],xpos,ypos-(objectImg[drawObj- 1])); } } } } Could anyone please help me how to translate this to just draw the relevant tiles? It would be deeply appreciated.

    Read the article

  • YouTube SEO: Video Optimization

    - by Mike Stiles
    SEO optimization is still regarded as one of the primary tools in the digital marketing kit. However and wherever a potential customer is conducting a search, brands want their content to surface in the top results. Makes sense. But without a regular flow of good, relevant content, your SEO opportunities run shallow. We know from several studies video is one of the most engaging forms of content, so why not make sure that in addition to being cool, your videos are helping you win the SEO game? Keywords:-Decide what search phrases make the most sense for your video. Don’t dare use phrases that have nothing to do with the content. You’ll make people mad.-Research those keywords to see how competitive they are. Adjust them so there are still lots of people searching for it, but there are not as many links showing up for it.-Search your potential keywords and phrases to see what comes up. It’s amazing how many people forget to do that. Video Title: -Try to start and/or end with your keyword.-When you search on YouTube, visual action words tend to come up as suggested searches. So try to use action words. Video Description: -Lead with a link to your site (include http://). -Don’t stuff this with your keyword. It leads to bad writing and it won’t work anyway. This is where you convince people to watch, so write for humans. Use some showmanship. -At the end, do a call to action (subscribe, see the whole playlist, visit our social channels, etc.) Video Tags:-Don’t over-tag. 5-10 tags per video is plenty. -If you’re compelled to have more than 10, that means you should probably make more videos specifically targeting all those keywords. Find Linking Pals:-45% of videos are discovered on video sites. But 44% are found through links on blogs and sites.-Write a blog about your video’s content, then link to the video in it. -A good site for finding places to guest blog is myblogguest.com-Once you find good linking partners, they’ll link to your future videos (as long as they’re good and you’re returning the favor). Tap the Power of Similar Videos:-Use Video Reply to associate your video with other topic-related videos. That’s when you make a video responding to or referencing a video made by someone else. Content:-Again, build up a portfolio of videos, not just one that goes after 30 keywords.-Create shorter, sequential videos that pull them deeper into the content and closer to a desired final action.-Organize your video topics separately using Playlists. Playlists show up as a whole in search results like individual videos, so optimize playlists the same as you would for a video. Meta Data:-Too much importance is placed on it. It accounts for only 15% of search success.-YouTube reads Captions or Transcripts to determine what a video is about. If you’re not using them, you’re missing out.-You get the SEO benefit of captions and transcripts whether the viewers has them toggled on or not. Promotion:-This accounts for 25% of search success.-Promote the daylights out of your videos using your social channels and digital assets. Don’t assume it’s going to magically get discovered. -You can pay to promote your video. This could surface it on the YouTube home page, YouTube search results, YouTube related videos, and across the Google content network. Community:-Accounts for 10% of search success.-Make sure your YouTube home page is a fun place to spend time. Carefully pick your featured video, and make sure your Playlists are featured. -Participate in discussions so users will see you’re present. The volume of ratings/comments is as important as the number of views when it comes to where you surface on search. Video Sitemaps:-As with a web site, a video sitemap helps Google quickly index your video.-Google wants to know title, description, play page URL, the URL of the thumbnail image you want, and raw video file location.-Sitemaps are xml files you host or dynamically generate on your site. Once you’ve made your sitemap, sign in and submit it using Google webmaster tools. Just as with the broadcast and cable TV channels, putting a video out there is only step one. You also have to make sure everybody knows it’s there so the largest audience possible can see it. Here’s hoping you get great ratings. @mikestiles

    Read the article

  • Why is heap size fixed on JVMs?

    - by themel
    Can anyone explain to me why JVMs (I didn't check too many, but I've never seen one that didn't do it that way) need to run on a fixed heap size? I know it's easier to implement on a simple contiguous heap, but the Sun JVM is now over a decade old, so I'd expect them to have had time to improve this. Needing to define the maximum memory size of your program at startup time seems such a 1960s thing to do, and then there are the bad interactions with OS virtual memory management (GC retrieving swapped out data, inability to determine how much memory the Java process is really using from the OS side, huge amounts of VM space wasted (I know, you don't care on your fancy 48bit machines...)). I also guess that the various sad attempts to build small operating systems inside the JVM (EE application servers, OSGi) are at least partially to blame on this circumstance, because running multiple Java processes on a system invariably leads to wasted resources because you have to give each of them the memory it might have to use at peak. Surprisingly, Google didn't yield the storms of outrage over this that I would expect, but they may just have been buried under the millions of people finding out about fixed heap size and just accepting it for a fact.

    Read the article

  • 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.

    Read the article

  • How would I instruct extconf.rb to use additional g++ optimization flags, and which are advisable?

    - by mohawkjohn
    I'm using Rice to write a C++ extension for a Ruby gem. The extension is in the form of a shared object (.so) file. This requires 'mkmf-rice' instead of 'mkmf', but the two (AFAIK) are pretty similar. By default, the compiler uses the flags -g -O2. Personally, I find this kind of silly, since it's hard to debug with any optimization enabled. I've resorted to editing the Makefile to take out the flags I don't like (e.g., removing -fPIC -shared when I need to debug using main() instead of Ruby's hooks). But I figure there's got to be a better way. I know I can just do $CPPFLAGS += " -DRICE" to add additional flags. But how do I remove things without editing the Makefile directly? A secondary question: what optimizations are safe for shared objects loaded by Ruby? Can I do things like -funroll-loops? What do you all recommend? It's a scientific computing project, so the faster the better. Memory is not much of an issue. Many thanks!

    Read the article

  • What's the steps for SQL optimization and changes without reflect live system ?

    - by Space Cracker
    we have a big portal that build using SharePoint 2007 , asp.net 3.5 , SQL Server 2005 .. many developers work in it since 01/2008 and we are now doing huge analysis for current SQL Databases [not share-point DB ] to optimize and enhance it. The main db have about 330 table and 1720 stored procedure (SP) created from 01/2008 till now Many table names / Columns is very long and we want to short it we found SP names is written in 25 format :( , some of them are very complex and also we want to rename many SP parameters need to be renamed one of the biggest table is Registered user table, that will be spitted in more than one table for some optimization, many columns name will be changed I searched for the way that i can rename table names ,columns and i found SQL refactor tool but i still trying it .. my questions : Is SQl Refactor is the best tool for renaming ? or is there any other one ? if i want to make it manually, is there any references or best practice for that ? How can i do such changes in fast and stable way .. i search for recommendations and case studies if exist ?

    Read the article

  • Alternate User select interface in django admin to reduce page size on large site?

    - by David Eyk
    I have a Django-based site with roughly 300,000 User objects. Admin pages for objects with a ForeignKey field to User take a very long time to load as the resulting form is about 6MB in size. Of course, the resulting dropdown isn't particularly useful, either. Are there any off-the-shelf replacements for handling this case? I've been googling for a snippet or a blog entry, but haven't found anything yet. I'd like to have a smaller download size and a more usable interface.

    Read the article

  • How to select random image of specific size using Django / Python?

    - by Jonathan
    I've been using this little snippet to select random images. However I would like to change it to select only images of a certain size. I'm running into trouble checking against image size. If I use get_image_dimensions() I need to use a conditional statement, which then requires that I allow exceptions. So, I guess I need some pointers on just limiting by image dimensions. Thanks. import os import random import posixpath from django import template from django.conf import settings register = template.Library() def is_image_file(filename): """Does `filename` appear to be an image file?""" img_types = [".jpg", ".jpeg", ".png", ".gif"] ext = os.path.splitext(filename)[1] return ext in img_types @register.simple_tag def random_image(path): """ Select a random image file from the provided directory and return its href. `path` should be relative to MEDIA_ROOT. Usage: <img src='{% random_image "images/whatever/" %}'> """ fullpath = os.path.join(settings.MEDIA_ROOT, path) filenames = [f for f in os.listdir(fullpath) if is_image_file(f)] pick = random.choice(filenames) return posixpath.join(settings.MEDIA_URL, path, pick)

    Read the article

  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

    Read the article

  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

    Read the article

  • Task Manager: VM Size smaller than Mem usage?

    - by shoosh
    The windows XP tasks manager can show two different columns regarding the memory usage of the processes. One is called Mem Usage and the other is VM Size (not on by default, you need to activate it) From what I've gathered, VM size is the size of the entire memory space occupied by the process and Mem Usage is the amount of memory currently committed and used. This assumption is verified by most processes when the VM Size is only slightly larger than Mem Usage for instance my Outlook currently has 79,724 K in VM Size and 56,600 K in Mem Usage But it fails for other processes such as Firefox which currently has 171,900 K for Mem Usage and only 156,440 K in VM Size. How can a process use more memory than the amount of virtual memory allocated to it? So Maybe my interpretation of these columns is wrong. What do they actually mean?

    Read the article

  • SIFR 3.0 - Font Size

    - by Nick
    I have been working with SIFR 3.0 for some time now and the font-size never seems to work correctly. I understand the most basic concepts behind SIFR. SIFR runs when you load the page. It does some calculations one the size of the HTML rendered font and then replaces it with a flash movie that is roughly equal to that size. Because of this, you want to style your HTML font to match the size of your SIFR font as close as possible. My problem always comes up when trying to style these two font sizes to match. Let's say I want to use a SIFR font of Helvetica Neue Lt at about 32px. The HTML equivalent is something like Arial Narrow at about 36px with some negative letter spacing. So here is what I do. In sifr.css I'll write: @media screen { .sIFR-active h1 { visibility: hidden; z-index: 0 !important; font-size: 36px; } } Great, that gets the default HTML font the size I need. Now I need to update the flash SIFR font size. So I go into sifr-config.js and write something like this: sIFR.replace(HelveticaNeueThinCond, { selector: 'h1', css: '.sIFR-root { color: #762123; font-size: 32px; line-height: 1em; }', transparent: true }); So right now everything is working great. That is until my h1 text wraps more than one line. For some reason, when the text wraps it only shows the first line. It seems calculates the height wrong. This is very weird because I ran some tests. I took "visibility: hidden" off of "sIFR-active h1" to make sure that the HTML rendered text was the right size. It is, it takes up two lines. However, when the Flash replaces this text it gives it a min-height of one line of text. Odd. The only way I could find to fix this wrapping problem was to remove "font-size: 32px;" from "sIFR.replace(HelveticaNeueThinCond" in sifr-config. The problem I run into then is that it inherits the font-size set in sifr.css. Now the problem is that my HTML text is bigger then the SIFR text. So occasional my HTML text will wrap to a new line before my SIFR text leaving a big white space. So, how do I set two different font-size (one for my HTML text and one for my SIFR) without losing the wrapping. The only time I have been able to use the successfully is when I have a SIFR font that is so similar to a web safe font that they can share the same font-size attribute. Thanks

    Read the article

  • SQL SERVER – What is Spatial Database? – Developing with SQL Server Spatial and Deep Dive into Spati

    - by pinaldave
    What is Spatial Database? A spatial database is a database that is optimized to store and query data related to objects in space, including points, lines and polygons. While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types. (Source: Wikipedia) Today I will be talking about the same subject at Microsoft TechEd India. If you want to learn about how to spatial aspect of data and how to integrate them with SQL Server this is the perfect session for you. Spatial is very special concept of SQL Server and I really like how it is implemented in SQL Server. In general Performance Tuning and Query Optimization is something I always have enjoyed in my professional life. Index are my best friends and many time, by implementing and many time by removing I have improved the performance of the system. In this session, I will be talking about Index along with Spatial Data. As Spatial Database is very interesting concept, I will cover super short but very interesting 10 quick slides about this subject. I will make sure in very first 20 mins, you will understand following topics Introduction to Spatial Database One line definition Understanding Spatial Indexing Index Internals Query/Performance Tuning Query Hinting/Cost Analysis Spatial Index Catalog Views Performance Troubleshooting Finding Optimal Index using Spatial Index SP Common Errors Index Maintenance This slides decks will be followed by around 30 mins demo which will have story of geometry, geography, index internals and performance tuning. If you are interested in learning how GIS works and how SQL Server out of the box supports this wonderful tools, you will really like how the story is told. I am sure all people who attend the event will know how the Bangalore is positioned on the map of India. I will take example of Bangalore and Hyderabad and demonstrate how index can improve the performance. Well there are lots of story to tell in the session, and I will be opening this session with the beautiful script of Botticelli’s Birth of Venus created by Michael J. Swart. I will also demonstrate few real life scenario where I will be talking about Spatial Database and its usage. Do not miss this session. At the end of session there will be book awarded to best participant. My session details: Session 3: Developing with SQL Server Spatial and Deep Dive into Spatial Indexing Date: April 14, 2010 Time: 5:00pm-6:00pm Microsoft SQL Server 2008 delivers new spatial data types that enable you to consume, use, and extend location-based data through spatial-enabled applications. Attend this session to learn how to use spatial functionality in next version of SQL Server to build and optimize spatial queries. This session outlines the new geography data type to store geodetic spatial data and perform operations on it, use the new geometry data type to store planar spatial data and perform operations on it, take advantage of new spatial indexes for high performance queries, use the new spatial results tab to quickly and easily view spatial query results directly from within Management Studio, extend spatial data capabilities by building or integrating location-enabled applications through support for spatial standards and specifications and much more. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology Tagged: Spatial Database

    Read the article

  • CSS optimization - extra classes in dom or preprocessor-repetitive styling in css file?

    - by anna.mi
    I'm starting on a fairly large project and I'm considering the option of using LESS for pre-processing my css. the useful thing about LESS is that you can define a mixin that contains for example: .border-radius(@radius) { -webkit-border-radius: @radius; -moz-border-radius: @radius; -o-border-radius: @radius; -ms-border-radius: @radius; border-radius: @radius; } and then use it in a class declaration as .rounded-div { .border-radius(10px); } to get the outputted css as: .rounded-div { -webkit-border-radius: 10px; -moz-border-radius: 10px; -o-border-radius: 10px; -ms-border-radius: 10px; border-radius: 10px; } this is extremely useful in the case of browser prefixes. However this same concept could be used to encapsulate commonly-used css, for example: .column-container { overflow: hidden; display: block; width: 100%; } .column(@width) { float: left; width: @width; } and then use this mixin whenever i need columns in my design: .my-column-outer { .column-container(); background: red; } .my-column-inner { .column(50%); font-color: yellow; } (of course, using the preprocessor we could easily expand this to be much more useful, eg. pass the number of columns and the container width as variables and have LESS determine the width of each column depending on the number of columns and container width!) the problem with this is that when compliled, my final css file would have 100 such declarations, copy&pasted, making the file huge and bloated and repetitive. The alternative to this would be to use a grid system which has predefined classes for each column-layout option, eg .c-50 ( with a "float: left; width:50%;" definition ), .c-33, .c-25 to accomodate for a 2-column, 3-column and 4-column layout and then use these classes to my dom. i really mislike the idea of the extra classes, from experience it results to bloated dom (creating extra divs just to attach the grid classes to). Also the most basic tutorial for html/css would tell you that the dom should be separated from the styling - grid classes are styling related! to me, its the same as attaching a "border-radius-10" class to the .rounded-div example above! on the other hand, the large css file that would result from the repetitive code is also a disadvantage so i guess my question is, which one would you recommend? and which do you use? and, which solution is best for optimization? apart from the larger file size, has there even been any research on whether browser renders multiple classes faster than a large css file, or the other way round? tnx! i'd love to hear your opinion!

    Read the article

  • 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?

    Read the article

  • SQL SERVER – Quick Look at SQL Server Configuration for Performance Indications

    - by pinaldave
    Earlier I wrote SQL SERVER – Beginning SQL Server: One Step at a Time – SQL Server Magazine. That was the first article on the series of my real world experience of Performance Tuning experience. I have written second part the same series over here. Read second part over here: Quick Look at SQL Server Configuration for Performance Indications. In this second part I talk about two types of my clients. 1) Those who want instant results 2) Those who want the right results It is really fun to work with both the clients. I talk about various configuration options which I look at when I try to give very early opinion about SQL Server Performance. There are various eight configurations, I give quick look and start talking about performance. Head over to original article over here: Quick Look at SQL Server Configuration for Performance Indications. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28

    - by pinaldave
    This blog post will have running account of the all the blog post I will be doing in this month related to SQL Server Wait Types and Wait Queues. 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 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

    Read the article

  • SQL SERVER – Convert IN to EXISTS – Performance Talk

    - by pinaldave
    In recent training one of the attendee asked if I can show simple method to convert IN clause to EXISTS clause. Here is the simple example. USE AdventureWorks GO -- use of = SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID = ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of exists SELECT * FROM HumanResources.Employee E WHERE EXISTS ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO It is NOT necessary that every time when IN is replaced by EXISTS it gives better performance. However, in our case listed above it does for sure give better performance. Click on below image to see the execution plan. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • Fast Fashion Freshness

    - by David Dorf
    Fashion retailers such as H&M, Zara, and Wet Seal have perfected the fast fashion retailing model. The concept requires no replenishment in order to maintain assortment freshness and to create a sense of urgency for the consumer to purchase now. However, maintaining assortment freshness results in high product turnover, making markdown optimization a necessity. Wet Seal, for instance, needed to move from ad-hoc markdowns and dealing with surplus inventory to handling markdowns methodically across 8,000 SKUs with only 12-15 week lifecycle (from DC receipt to exit). By optimizing and automating markdowns, Wet Seal is reaching their goal of assortment freshness, which in turn increases sales. If you're interested in learning more, register for a free webinar occurring on May 13th featuring Join Daniel Ryu, Vice President of Planning and Allocation at Wet Seal. He'll be discussing how the fast fashion retailer maintains their goal of assortment freshness.

    Read the article

  • JIT compiler for C, C++, and the likes

    - by Ebrahim
    Is there any just-in-time compiler out there for compiled languages, such as C and C++? (The first names that come to mind are Clang and LLVM! But I don't think they currently support it.) Explanation: I think the software could benefit from runtime profiling feedback and aggressively optimized recompilation of hotspots at runtime, even for compiled-to-machine languages like C and C++. Profile-guided optimization does a similar job, but with the difference a JIT would be more flexible in different environments. In PGO you run your binary prior to releasing it. After you released it, it would use no environment/input feedbacks collected at runtime. So if the input pattern is changed, it is probe to performance penalty. But JIT works well even in that conditions. However I think it is controversial wether the JIT compiling performance benefit outweights its own overhead. Edit: Grammar

    Read the article

  • Single click handler for all buttons in Javascript? Is it a pattern? Whats the benefit?

    - by Hasan Khan
    I have been told that when there are multiple buttons on the page for same purpose but targeting different item e.g. delete item on a grid of items, they say it is recommended to just register for click handler only on the top most element like 'body' and check what was clicked instead of hooking up click with every delete button. Whats the benefit of this? Creating more handlers causes problems? Is it an optimization of some sort? Is it a pattern? Does it have anything to do with performance? Where can I read more about it?

    Read the article

< Previous Page | 28 29 30 31 32 33 34 35 36 37 38 39  | Next Page >