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  • ASP.NET MVC 2 Model Binding for a Collection

    - by nmarun
    Yes, my yet another post on Model Binding (previous one is here), but this one uses features presented in MVC 2. How I got to writing this blog? Well, I’m on a project where we’re doing some MVC things for a shopping cart. Let me show you what I was working with. Below are my model classes: 1: public class Product 2: { 3: public int Id { get; set; } 4: public string Name { get; set; } 5: public int Quantity { get; set; } 6: public decimal UnitPrice { get; set; } 7: } 8:   9: public class Totals 10: { 11: public decimal SubTotal { get; set; } 12: public decimal Tax { get; set; } 13: public decimal Total { get; set; } 14: } 15:   16: public class Basket 17: { 18: public List<Product> Products { get; set; } 19: public Totals Totals { get; set;} 20: } The view looks as below:  1: <h2>Shopping Cart</h2> 2:   3: <% using(Html.BeginForm()) { %> 4: 5: <h3>Products</h3> 6: <% for (int i = 0; i < Model.Products.Count; i++) 7: { %> 8: <div style="width: 100px;float:left;">Id</div> 9: <div style="width: 100px;float:left;"> 10: <%= Html.TextBox("ID", Model.Products[i].Id) %> 11: </div> 12: <div style="clear:both;"></div> 13: <div style="width: 100px;float:left;">Name</div> 14: <div style="width: 100px;float:left;"> 15: <%= Html.TextBox("Name", Model.Products[i].Name) %> 16: </div> 17: <div style="clear:both;"></div> 18: <div style="width: 100px;float:left;">Quantity</div> 19: <div style="width: 100px;float:left;"> 20: <%= Html.TextBox("Quantity", Model.Products[i].Quantity)%> 21: </div> 22: <div style="clear:both;"></div> 23: <div style="width: 100px;float:left;">Unit Price</div> 24: <div style="width: 100px;float:left;"> 25: <%= Html.TextBox("UnitPrice", Model.Products[i].UnitPrice)%> 26: </div> 27: <div style="clear:both;"><hr /></div> 28: <% } %> 29: 30: <h3>Totals</h3> 31: <div style="width: 100px;float:left;">Sub Total</div> 32: <div style="width: 100px;float:left;"> 33: <%= Html.TextBox("SubTotal", Model.Totals.SubTotal)%> 34: </div> 35: <div style="clear:both;"></div> 36: <div style="width: 100px;float:left;">Tax</div> 37: <div style="width: 100px;float:left;"> 38: <%= Html.TextBox("Tax", Model.Totals.Tax)%> 39: </div> 40: <div style="clear:both;"></div> 41: <div style="width: 100px;float:left;">Total</div> 42: <div style="width: 100px;float:left;"> 43: <%= Html.TextBox("Total", Model.Totals.Total)%> 44: </div> 45: <div style="clear:both;"></div> 46: <p /> 47: <input type="submit" name="Submit" value="Submit" /> 48: <% } %> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Nothing fancy, just a bunch of div’s containing textboxes and a submit button. Just make note that the textboxes have the same name as the property they are going to display. Yea, yea, I know. I’m displaying unit price as a textbox instead of a label, but that’s beside the point (and trust me, this will not be how it’ll look on the production site!!). The way my controller works is that initially two dummy products are added to the basked object and the Totals are calculated based on what products were added in what quantities and their respective unit price. So when the page loads in edit mode, where the user can change the quantity and hit the submit button. In the ‘post’ version of the action method, the Totals get recalculated and the new total will be displayed on the screen. Here’s the code: 1: public ActionResult Index() 2: { 3: Product product1 = new Product 4: { 5: Id = 1, 6: Name = "Product 1", 7: Quantity = 2, 8: UnitPrice = 200m 9: }; 10:   11: Product product2 = new Product 12: { 13: Id = 2, 14: Name = "Product 2", 15: Quantity = 1, 16: UnitPrice = 150m 17: }; 18:   19: List<Product> products = new List<Product> { product1, product2 }; 20:   21: Basket basket = new Basket 22: { 23: Products = products, 24: Totals = ComputeTotals(products) 25: }; 26: return View(basket); 27: } 28:   29: [HttpPost] 30: public ActionResult Index(Basket basket) 31: { 32: basket.Totals = ComputeTotals(basket.Products); 33: return View(basket); 34: } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } That’s that. Now I run the app, I see two products with the totals section below them. I look at the view source and I see that the input controls have the right ID, the right name and the right value as well. 1: <input id="ID" name="ID" type="text" value="1" /> 2: <input id="Name" name="Name" type="text" value="Product 1" /> 3: ... 4: <input id="ID" name="ID" type="text" value="2" /> 5: <input id="Name" name="Name" type="text" value="Product 2" /> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } So just as a regular user would do, I change the quantity value of one of the products and hit the submit button. The ‘post’ version of the Index method gets called and I had put a break-point on line 32 in the above snippet. When I hovered my mouse on the ‘basked’ object, happily assuming that the object would be all bound and ready for use, I was surprised to see both basket.Products and basket.Totals were null. Huh? A little research and I found out that the reason the DefaultModelBinder could not do its job is because of a naming mismatch on the input controls. What I mean is that when you have to bind to a custom .net type, you need more than just the property name. You need to pass a qualified name to the name property of the input control. I modified my view and the emitted code looked as below: 1: <input id="Product_Name" name="Product.Name" type="text" value="Product 1" /> 2: ... 3: <input id="Product_Name" name="Product.Name" type="text" value="Product 2" /> 4: ... 5: <input id="Totals_SubTotal" name="Totals.SubTotal" type="text" value="550" /> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Now, I update the quantity and hit the submit button and I see that the Totals object is populated, but the Products list is still null. Once again I went: ‘Hmm.. time for more research’. I found out that the way to do this is to provide the name as: 1: <%= Html.TextBox(string.Format("Products[{0}].ID", i), Model.Products[i].Id) %> 2: <!-- this will be rendered as --> 3: <input id="Products_0__ID" name="Products[0].ID" type="text" value="1" /> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } It was only now that I was able to see both the products and the totals being properly bound in the ‘post’ action method. Somehow, I feel this is kinda ‘clunky’ way of doing things. Seems like people at MS felt in a similar way and offered us a much cleaner way to solve this issue. The simple solution is that instead of using a Textbox, we can either use a TextboxFor or an EditorFor helper method. This one directly spits out the name of the input property as ‘Products[0].ID and so on. Cool right? I totally fell for this and changed my UI to contain EditorFor helper method. At this point, I ran the application, changed the quantity field and pressed the submit button. Of course my basket object parameter in my action method was correctly bound after these changes. I let the app complete the rest of the lines in the action method. When the page finally rendered, I did see that the quantity was changed to what I entered before the post. But, wait a minute, the totals section did not reflect the changes and showed the old values. My status: COMPLETELY PUZZLED! Just to recap, this is what my ‘post’ Index method looked like: 1: [HttpPost] 2: public ActionResult Index(Basket basket) 3: { 4: basket.Totals = ComputeTotals(basket.Products); 5: return View(basket); 6: } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } A careful debug confirmed that the basked.Products[0].Quantity showed the updated value and the ComputeTotals() method also returns the correct totals. But still when I passed this basket object, it ended up showing the old totals values only. I began playing a bit with the code and my first guess was that the input controls got their values from the ModelState object. For those who don’t know, the ModelState is a temporary storage area that ASP.NET MVC uses to retain incoming attempted values plus binding and validation errors. Also, the fact that input controls populate the values using data taken from: Previously attempted values recorded in the ModelState["name"].Value.AttemptedValue Explicitly provided value (<%= Html.TextBox("name", "Some value") %>) ViewData, by calling ViewData.Eval("name") FYI: ViewData dictionary takes precedence over ViewData's Model properties – read more here. These two indicators led to my guess. It took me quite some time, but finally I hit this post where Brad brilliantly explains why this is the preferred behavior. My guess was right and I, accordingly modified my code to reflect the following way: 1: [HttpPost] 2: public ActionResult Index(Basket basket) 3: { 4: // read the following posts to see why the ModelState 5: // needs to be cleared before passing it the view 6: // http://forums.asp.net/t/1535846.aspx 7: // http://forums.asp.net/p/1527149/3687407.aspx 8: if (ModelState.IsValid) 9: { 10: ModelState.Clear(); 11: } 12:   13: basket.Totals = ComputeTotals(basket.Products); 14: return View(basket); 15: } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } What this does is that in the case where your ModelState IS valid, it clears the dictionary. This enables the values to be read from the model directly and not from the ModelState. So the verdict is this: If you need to pass other parameters (like html attributes and the like) to your input control, use 1: <%= Html.TextBox(string.Format("Products[{0}].ID", i), Model.Products[i].Id) %> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Since, in EditorFor, there is no direct and simple way of passing this information to the input control. If you don’t have to pass any such ‘extra’ piece of information to the control, then go the EditorFor way. The code used in the post can be found here.

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  • SQL SERVER – SSMS: Top Object and Batch Execution Statistics Reports

    - by Pinal Dave
    The month of June till mid of July has been the fever of sports. First, it was Wimbledon Tennis and then the Soccer fever was all over. There is a huge number of fan followers and it is great to see the level at which people sometimes worship these sports. Being an Indian, I cannot forget to mention the India tour of England later part of July. Following these sports and as the events unfold to the finals, there are a number of ways the statisticians can slice and dice the numbers. Cue from soccer I can surely say there is a team performance against another team and then there is individual member fairs against a particular opponent. Such statistics give us a fair idea to how a team in the past or in the recent past has fared against each other, head-to-head stats during World cup and during other neutral venue games. All these statistics are just pointers. In reality, they don’t reflect the calibre of the current team because the individuals who performed in each of these games are totally different (Typical example being the Brazil Vs Germany semi-final match in FIFA 2014). So at times these numbers are misleading. It is worth investigating and get the next level information. Similar to these statistics, SQL Server Management studio is also equipped with a number of reports like a) Object Execution Statistics report and b) Batch Execution Statistics reports. As discussed in the example, the team scorecard is like the Batch Execution statistics and individual stats is like Object Level statistics. The analogy can be taken only this far, trust me there is no correlation between SQL Server functioning and playing sports – It is like I think about diet all the time except while I am eating. Performance – Batch Execution Statistics Let us view the first report which can be invoked from Server Node -> Reports -> Standard Reports -> Performance – Batch Execution Statistics. Most of the values that are displayed in this report come from the DMVs sys.dm_exec_query_stats and sys.dm_exec_sql_text(sql_handle). This report contains 3 distinctive sections as outline below.   Section 1: This is a graphical bar graph representation of Average CPU Time, Average Logical reads and Average Logical Writes for individual batches. The Batch numbers are indicative and the details of individual batch is available in section 3 (detailed below). Section 2: This represents a Pie chart of all the batches by Total CPU Time (%) and Total Logical IO (%) by batches. This graphical representation tells us which batch consumed the highest CPU and IO since the server started, provided plan is available in the cache. Section 3: This is the section where we can find the SQL statements associated with each of the batch Numbers. This also gives us the details of Average CPU / Average Logical Reads and Average Logical Writes in the system for the given batch with object details. Expanding the rows, I will also get the # Executions and # Plans Generated for each of the queries. Performance – Object Execution Statistics The second report worth a look is Object Execution statistics. This is a similar report as the previous but turned on its head by SQL Server Objects. The report has 3 areas to look as above. Section 1 gives the Average CPU, Average IO bar charts for specific objects. The section 2 is a graphical representation of Total CPU by objects and Total Logical IO by objects. The final section details the various objects in detail with the Avg. CPU, IO and other details which are self-explanatory. At a high-level both the reports are based on queries on two DMVs (sys.dm_exec_query_stats and sys.dm_exec_sql_text) and it builds values based on calculations using columns in them: SELECT * FROM    sys.dm_exec_query_stats s1 CROSS APPLY sys.dm_exec_sql_text(sql_handle) AS s2 WHERE   s2.objectid IS NOT NULL AND DB_NAME(s2.dbid) IS NOT NULL ORDER BY  s1.sql_handle; This is one of the simplest form of reports and in future blogs we will look at more complex reports. I truly hope that these reports can give DBAs and developers a hint about what is the possible performance tuning area. As a closing point I must emphasize that all above reports pick up data from the plan cache. If a particular query has consumed a lot of resources earlier, but plan is not available in the cache, none of the above reports would show that bad query. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • Mysql performance problem & Failed DIMM

    - by murdoch
    Hi I have a dedicated mysql database server which has been having some performance problems recently, under normal load the server will be running fine, then suddenly out of the blue the performance will fall off a cliff. The server isn't using the swap file and there is 12GB of RAM in the server, more than enough for its needs. After contacting my hosting comapnies support they have discovered that there is a failed 2GB DIMM in the server and have scheduled to replace it tomorow morning. My question is could a failed DIMM result in the performance problems I am seeing or is this just coincidence? My worry is that they will replace the ram tomorrow but the problems will persist and I will still be lost of explanations so I am just trying to think ahead. The reason I ask is that there is plenty of RAM in the server, more than required and simply missing 2GB should be a problem, so if this failed DIMM is causing these performance problems then the OS must be trying to access the failed DIMM and slowing down as a result. Does that sound like a credible explanation? This is what DELLs omreport program says about the RAM, notice one dimm is "Critical" Memory Information Health : Critical Memory Operating Mode Fail Over State : Inactive Memory Operating Mode Configuration : Optimizer Attributes of Memory Array(s) Attributes : Location Memory Array 1 : System Board or Motherboard Attributes : Use Memory Array 1 : System Memory Attributes : Installed Capacity Memory Array 1 : 12288 MB Attributes : Maximum Capacity Memory Array 1 : 196608 MB Attributes : Slots Available Memory Array 1 : 18 Attributes : Slots Used Memory Array 1 : 6 Attributes : ECC Type Memory Array 1 : Multibit ECC Total of Memory Array(s) Attributes : Total Installed Capacity Value : 12288 MB Attributes : Total Installed Capacity Available to the OS Value : 12004 MB Attributes : Total Maximum Capacity Value : 196608 MB Details of Memory Array 1 Index : 0 Status : Ok Connector Name : DIMM_A1 Type : DDR3-Registered Size : 2048 MB Index : 1 Status : Ok Connector Name : DIMM_A2 Type : DDR3-Registered Size : 2048 MB Index : 2 Status : Ok Connector Name : DIMM_A3 Type : DDR3-Registered Size : 2048 MB Index : 3 Status : Critical Connector Name : DIMM_B1 Type : DDR3-Registered Size : 2048 MB Index : 4 Status : Ok Connector Name : DIMM_B2 Type : DDR3-Registered Size : 2048 MB Index : 5 Status : Ok Connector Name : DIMM_B3 Type : DDR3-Registered Size : 2048 MB the command free -m shows this, the server seems to be using more than 10GB of ram which would suggest it is trying to use the DIMM total used free shared buffers cached Mem: 12004 10766 1238 0 384 4809 -/+ buffers/cache: 5572 6432 Swap: 2047 0 2047 iostat output while problem is occuring avg-cpu: %user %nice %system %iowait %steal %idle 52.82 0.00 11.01 0.00 0.00 36.17 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 47.00 0.00 576.00 0 576 sda1 0.00 0.00 0.00 0 0 sda2 1.00 0.00 32.00 0 32 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 46.00 0.00 544.00 0 544 avg-cpu: %user %nice %system %iowait %steal %idle 53.12 0.00 7.81 0.00 0.00 39.06 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 49.00 0.00 592.00 0 592 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 49.00 0.00 592.00 0 592 avg-cpu: %user %nice %system %iowait %steal %idle 56.09 0.00 7.43 0.37 0.00 36.10 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 232.00 0.00 64520.00 0 64520 sda1 0.00 0.00 0.00 0 0 sda2 159.00 0.00 63728.00 0 63728 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 73.00 0.00 792.00 0 792 avg-cpu: %user %nice %system %iowait %steal %idle 52.18 0.00 9.24 0.06 0.00 38.51 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 49.00 0.00 600.00 0 600 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 49.00 0.00 600.00 0 600 avg-cpu: %user %nice %system %iowait %steal %idle 54.82 0.00 8.64 0.00 0.00 36.55 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 100.00 0.00 2168.00 0 2168 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 100.00 0.00 2168.00 0 2168 avg-cpu: %user %nice %system %iowait %steal %idle 54.78 0.00 6.75 0.00 0.00 38.48 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 84.00 0.00 896.00 0 896 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 84.00 0.00 896.00 0 896 avg-cpu: %user %nice %system %iowait %steal %idle 54.34 0.00 7.31 0.00 0.00 38.35 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 81.00 0.00 840.00 0 840 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 81.00 0.00 840.00 0 840 avg-cpu: %user %nice %system %iowait %steal %idle 55.18 0.00 5.81 0.44 0.00 38.58 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 317.00 0.00 105632.00 0 105632 sda1 0.00 0.00 0.00 0 0 sda2 224.00 0.00 104672.00 0 104672 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 93.00 0.00 960.00 0 960 avg-cpu: %user %nice %system %iowait %steal %idle 55.38 0.00 7.63 0.00 0.00 36.98 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 74.00 0.00 800.00 0 800 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 74.00 0.00 800.00 0 800 avg-cpu: %user %nice %system %iowait %steal %idle 56.43 0.00 7.80 0.00 0.00 35.77 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 72.00 0.00 784.00 0 784 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 72.00 0.00 784.00 0 784 avg-cpu: %user %nice %system %iowait %steal %idle 54.87 0.00 6.49 0.00 0.00 38.64 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 80.20 0.00 855.45 0 864 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 80.20 0.00 855.45 0 864 avg-cpu: %user %nice %system %iowait %steal %idle 57.22 0.00 5.69 0.00 0.00 37.09 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 33.00 0.00 432.00 0 432 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 33.00 0.00 432.00 0 432 avg-cpu: %user %nice %system %iowait %steal %idle 56.03 0.00 7.93 0.00 0.00 36.04 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 41.00 0.00 560.00 0 560 sda1 0.00 0.00 0.00 0 0 sda2 2.00 0.00 88.00 0 88 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 39.00 0.00 472.00 0 472 avg-cpu: %user %nice %system %iowait %steal %idle 55.78 0.00 5.13 0.00 0.00 39.09 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 29.00 0.00 392.00 0 392 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 29.00 0.00 392.00 0 392 avg-cpu: %user %nice %system %iowait %steal %idle 53.68 0.00 8.30 0.06 0.00 37.95 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 78.00 0.00 4280.00 0 4280 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 78.00 0.00 4280.00 0 4280

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  • Ranking Part III

    - by PointsToShare
    © 2011 By: Dov Trietsch. All rights reserved   Ranking Part III In a previous blogs “Ranking an Introduction” and  “Ranking Part II” , you have already praised me in “Rank the Author” and learned how to create a new element on a page and how to place it where you need it. For this installment, I just added code to keep the number of votes (you vote by clicking one of the stars) and the total vote. Using these two, we can compute the average rating. It’s a small step, but its purpose is to show that we do not need a detailed history in order to compute the average. A running total is sufficient. Please note that once you close the game, you will lose your previous total. In real life, we persist the totals in the list itself. We also keep a list of actual votes, but its purpose is to prevent double votes. If a person has already voted, his user id is already on the list and our program will check for it and bar the person from voting again. This is coded in an event receiver, which is a SharePoint server piece of code. I will show you how to do this part in a subsequent blog. Again, go to the page and look at the code. The gist of it is here. avg, votes, and stars are global variables that I defined before. function sendRate(sel){//I hate long line so I created pieces of the message in their own vars            var s1 = "Your Rating Was: ";            var s2 = ".. ";            var s3 = "\nVotes = ";            var s4 = "\nTotal Stars = ";            var s5 = "\nAverage = ";            var s;            s = parseInt(sel.id.replace("_", '')); // Get the selected star number            votes = parseInt(votes) + 1;            stars = parseInt(stars) + s;            avg = parseFloat(stars) / parseFloat(votes);            alert(s1 + sel.id + s2 +sel.title + s3 + votes + s4 + stars + s5 + avg);} Click on the link to play and examine “Ranking with Stats” That’s all folks!

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  • Ranking - an Introduction

    - by PointsToShare
    © 2011 By: Dov Trietsch. All rights reserved Ranking Ranking is quite common in the internet. Readers are asked to rank their latest reading by clicking on one of 5 (sometimes 10) stars. The number of stars is then converted to a number and the average number of stars as selected by all the readers is proudly (or shamefully) displayed for future readers. SharePoint 2007 lacked this feature altogether. SharePoint 2010 allows the users to rank items in a list or documents in a library (the two are actually the same because a library is actually a list). But in SP2010 the computation of the average is done later on a timer rather than on-the-spot as it should be. I suspect that the reason for this shortcoming is that they did not involve a mathematician! Let me explain. Ranking is kept in a related list. When a user rates a document the rank-list is added an item with the item id, the user name, and his number of stars. The fact that a user already ranked an item prevents him from ranking it again. This prevents the creator of the item from asking his mother to rank it a 5 and do it 753 times, thus stacking the ballot. Some systems will allow a user to change his rating and this will be done by updating the rank-list item. Now, when the timer kicks off, the list is spanned and for each item the rank-list items containing this id are summed up and divided by the number of votes thus yielding the new average. This is obviously very time consuming and very server intensive. In the 18th century an early actuary named James Dodson used what the great Augustus De Morgan (of De Morgan’s law) later named Commutation tables. The labor involved in computing a life insurance premium was staggering and also very error prone. Clerks with pencil and paper would multiply and add mountains of numbers to do the task. The more steps the greater the probability of error and the more expensive the process. Commutation tables created a “summary” of many steps and reduced the work 100 fold. So had Microsoft taken a lesson in the history of computation, they would have developed a much faster way for rating that may be done in real-time and is also 100 times faster and less CPU intensive. How do we do this? We use a form of commutation. We always keep the number of votes and the total of stars. One simple division gives us the average. So we write an event receiver. When a vote is added, we just add the stars to the total-stars and 1 to the number of votes. We then recomputed the average. When a vote is updated, we reduce the total by the old vote, increase it by the new vote and leave the number of votes the same. Again we do the division to get the new average. When a vote is deleted (highly unlikely and maybe even prohibited), we reduce the total by that vote and reduce the number of votes by 1… Gone are the days of spanning lists, counting items, and tallying votes and we have no need for a timer process to run it all. This is the first of a few treatises on ranking. Even though I discussed the math and the history thereof, in here I am only going to solve the presentation issue. I wanted to create the CSS and Jscript needed to display the stars, create the various effects like hovering and clicking (onmouseover, onmouseout, onclick, etc.) and I wanted to create a general solution with any number of stars. When I had it all done, I created the ranking game so that I could test it. The game is interesting in and on itself, so here it is (or go to the games page and select “rank the stars”). BTW, when you play it, look at the source code and see how it was all done.  Next, how the 5 stars are displayed in the New and Update forms. When the whole set of articles will be done, you’ll be able to create the complete solution. That’s all folks!

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  • Cannot add repository key

    - by William Anthony
    I just installed my new laptop with ubuntu 12.04 and when I'm trying to add key, there is a "network unreachable" error. william@ubuntu:~$ gpg --keyserver hkp://keys.gnupg.net --recv-keys 1C4CBDCDCD2EFD2A gpg: requesting key CD2EFD2A from hkp server keys.gnupg.net ?: keys.gnupg.net: Network is unreachable gpgkeys: HTTP fetch error 7: couldn't connect: Network is unreachable gpg: no valid OpenPGP data found. gpg: Total number processed: 0 I'm so sure the keyserver is not down, because I tried it again at my old laptop running ubuntu 11.04 william@william:~$ gpg --keyserver hkp://keys.gnupg.net --recv-keys 1C4CBDCDCD2EFD2A gpg: requesting key CD2EFD2A from hkp server keys.gnupg.net gpg: key CD2EFD2A: "Percona MySQL Development Team <[email protected]>" not changed gpg: Total number processed: 1 gpg: unchanged: 1 Is this a bug?

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  • Experience formula with javascript

    - by StealingMana
    I'm having trouble working out a formula using this experience curve to get the total exp after each level. I bet its easy and im just over thinking it. maxlvl = 10; increment = 28; baseexp = 100; function calc(){ for (i = 0;i<(maxlvl*increment);i+=increment){ expperlvl = baseexp + i; document.writeln(expperlvl); } } I figured it out. maxlvl=6; base=200; increment=56; function total(){ totalxp= (base*(maxlvl-1))+(increment*(maxlvl-2)*(maxlvl-1)/2); document.write(totalxp); }

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  • Data structure: sort and search effectively

    - by Jiten Shah
    I need to have a data structure with say 4 keys . I can sort on any of these keys. What data structure can I opt for? Sorting time should be very little. I thought of a tree, but it will be only help searching on one key. For other keys I'll have to remake the tree on that particular key and then find it. Is there any data structure that can take care of all 4 keys at the same time? these 4 fields are of total 12 bytes and total size for each record - 40 bytes.. have memory constraints too... operations are : insertion, deletion, sorting on different keys.

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  • Server Memory with Magento

    - by Mohamed Elgharabawy
    I have a cloud server with the following specifications: 2vCPUs 4G RAM 160GB Disk Space Network 400Mb/s System Image: Ubuntu 12.04 LTS I am only running Magento CE 1.7.0.2 on this server. Nothing else. Usually, the server has a loading time of 4-5 seconds. Recently, this has dropped to over 30 seconds and sometimes the server just goes away and I get HTTP error reports to my email stating that HTTP requests took more than 20000ms. Running top command and sorting them returns the following: top - 15:29:07 up 3:40, 1 user, load average: 28.59, 25.95, 22.91 Tasks: 112 total, 30 running, 82 sleeping, 0 stopped, 0 zombie Cpu(s): 90.2%us, 9.3%sy, 0.0%ni, 0.0%id, 0.0%wa, 0.0%hi, 0.3%si, 0.2%st PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 31901 www-data 20 0 360m 71m 5840 R 7 1.8 1:39.51 apache2 32084 www-data 20 0 362m 72m 5548 R 7 1.8 1:31.56 apache2 32089 www-data 20 0 348m 59m 5660 R 7 1.5 1:41.74 apache2 32295 www-data 20 0 343m 54m 5532 R 7 1.4 2:00.78 apache2 32303 www-data 20 0 354m 65m 5260 R 7 1.6 1:38.76 apache2 32304 www-data 20 0 346m 56m 5544 R 7 1.4 1:41.26 apache2 32305 www-data 20 0 348m 59m 5640 R 7 1.5 1:50.11 apache2 32291 www-data 20 0 358m 69m 5256 R 6 1.7 1:44.26 apache2 32517 www-data 20 0 345m 56m 5532 R 6 1.4 1:45.56 apache2 30473 www-data 20 0 355m 66m 5680 R 6 1.7 2:00.05 apache2 32093 www-data 20 0 352m 63m 5848 R 6 1.6 1:53.23 apache2 32302 www-data 20 0 345m 56m 5512 R 6 1.4 1:55.87 apache2 32433 www-data 20 0 346m 57m 5500 S 6 1.4 1:31.58 apache2 32638 www-data 20 0 354m 65m 5508 R 6 1.6 1:36.59 apache2 32230 www-data 20 0 347m 57m 5524 R 6 1.4 1:33.96 apache2 32231 www-data 20 0 355m 66m 5512 R 6 1.7 1:37.47 apache2 32233 www-data 20 0 354m 64m 6032 R 6 1.6 1:59.74 apache2 32300 www-data 20 0 355m 66m 5672 R 6 1.7 1:43.76 apache2 32510 www-data 20 0 347m 58m 5512 R 6 1.5 1:42.54 apache2 32521 www-data 20 0 348m 59m 5508 R 6 1.5 1:47.99 apache2 32639 www-data 20 0 344m 55m 5512 R 6 1.4 1:34.25 apache2 32083 www-data 20 0 345m 56m 5696 R 5 1.4 1:59.42 apache2 32085 www-data 20 0 347m 58m 5692 R 5 1.5 1:42.29 apache2 32293 www-data 20 0 353m 64m 5676 R 5 1.6 1:52.73 apache2 32301 www-data 20 0 348m 59m 5564 R 5 1.5 1:49.63 apache2 32528 www-data 20 0 351m 62m 5520 R 5 1.6 1:36.11 apache2 31523 mysql 20 0 3460m 576m 8288 S 5 14.4 2:06.91 mysqld 32002 www-data 20 0 345m 55m 5512 R 5 1.4 2:01.88 apache2 32080 www-data 20 0 357m 68m 5512 S 5 1.7 1:31.30 apache2 32163 www-data 20 0 347m 58m 5512 S 5 1.5 1:58.68 apache2 32509 www-data 20 0 345m 56m 5504 R 5 1.4 1:49.54 apache2 32306 www-data 20 0 358m 68m 5504 S 4 1.7 1:53.29 apache2 32165 www-data 20 0 344m 55m 5524 S 4 1.4 1:40.71 apache2 32640 www-data 20 0 345m 56m 5528 R 4 1.4 1:36.49 apache2 31888 www-data 20 0 359m 70m 5664 R 4 1.8 1:57.07 apache2 32511 www-data 20 0 357m 67m 5512 S 3 1.7 1:47.00 apache2 32054 www-data 20 0 357m 68m 5660 S 2 1.7 1:53.10 apache2 1 root 20 0 24452 2276 1232 S 0 0.1 0:01.58 init Moreover, running free -m returns the following: total used free shared buffers cached Mem: 4003 3919 83 0 118 901 -/+ buffers/cache: 2899 1103 Swap: 0 0 0 To investigate this further, I have installed apache buddy, it recommeneded that I need to reduce the maxclient connections. Which I did. I also installed MysqlTuner and it suggests that I need to set my innodb_buffer_pool_size to = 3.0G. However, I cannot do that, since the whole memory is 4G. Here is the output from apache buddy: ### GENERAL REPORT ### Settings considered for this report: Your server's physical RAM: 4003MB Apache's MaxClients directive: 40 Apache MPM Model: prefork Largest Apache process (by memory): 73.77MB [ OK ] Your MaxClients setting is within an acceptable range. Max potential memory usage: 2950.8 MB Percentage of RAM allocated to Apache 73.72 % And this is the output of MySQLTuner: -------- Performance Metrics ------------------------------------------------- [--] Up for: 47m 22s (675K q [237.552 qps], 12K conn, TX: 1B, RX: 300M) [--] Reads / Writes: 45% / 55% [--] Total buffers: 2.1G global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 2.5G (64% of installed RAM) [OK] Slow queries: 0% (0/675K) [OK] Highest usage of available connections: 26% (40/151) [OK] Key buffer size / total MyISAM indexes: 36.0M/18.7M [OK] Key buffer hit rate: 100.0% (245K cached / 105 reads) [OK] Query cache efficiency: 92.5% (500K cached / 541K selects) [!!] Query cache prunes per day: 302886 [OK] Sorts requiring temporary tables: 0% (1 temp sorts / 15K sorts) [!!] Joins performed without indexes: 12135 [OK] Temporary tables created on disk: 25% (8K on disk / 32K total) [OK] Thread cache hit rate: 90% (1K created / 12K connections) [!!] Table cache hit rate: 17% (400 open / 2K opened) [OK] Open file limit used: 12% (123/1K) [OK] Table locks acquired immediately: 100% (196K immediate / 196K locks) [!!] InnoDB buffer pool / data size: 2.0G/3.5G [OK] InnoDB log waits: 0 -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Read this before increasing table_cache over 64: http://bit.ly/1mi7c4C Variables to adjust: query_cache_size ( 64M) join_buffer_size ( 128.0K, or always use indexes with joins) table_cache ( 400) innodb_buffer_pool_size (= 3G) Last but not least, the server still has more than 60% of free disk space. Now, based on the above, I have few questions: Are these numbers normal? Do they make sense? Do I need to upgrade the server? If I don't need to upgrade and my configuration is not correct, how do I optimize it?

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  • PTLQueue : a scalable bounded-capacity MPMC queue

    - by Dave
    Title: Fast concurrent MPMC queue -- I've used the following concurrent queue algorithm enough that it warrants a blog entry. I'll sketch out the design of a fast and scalable multiple-producer multiple-consumer (MPSC) concurrent queue called PTLQueue. The queue has bounded capacity and is implemented via a circular array. Bounded capacity can be a useful property if there's a mismatch between producer rates and consumer rates where an unbounded queue might otherwise result in excessive memory consumption by virtue of the container nodes that -- in some queue implementations -- are used to hold values. A bounded-capacity queue can provide flow control between components. Beware, however, that bounded collections can also result in resource deadlock if abused. The put() and take() operators are partial and wait for the collection to become non-full or non-empty, respectively. Put() and take() do not allocate memory, and are not vulnerable to the ABA pathologies. The PTLQueue algorithm can be implemented equally well in C/C++ and Java. Partial operators are often more convenient than total methods. In many use cases if the preconditions aren't met, there's nothing else useful the thread can do, so it may as well wait via a partial method. An exception is in the case of work-stealing queues where a thief might scan a set of queues from which it could potentially steal. Total methods return ASAP with a success-failure indication. (It's tempting to describe a queue or API as blocking or non-blocking instead of partial or total, but non-blocking is already an overloaded concurrency term. Perhaps waiting/non-waiting or patient/impatient might be better terms). It's also trivial to construct partial operators by busy-waiting via total operators, but such constructs may be less efficient than an operator explicitly and intentionally designed to wait. A PTLQueue instance contains an array of slots, where each slot has volatile Turn and MailBox fields. The array has power-of-two length allowing mod/div operations to be replaced by masking. We assume sensible padding and alignment to reduce the impact of false sharing. (On x86 I recommend 128-byte alignment and padding because of the adjacent-sector prefetch facility). Each queue also has PutCursor and TakeCursor cursor variables, each of which should be sequestered as the sole occupant of a cache line or sector. You can opt to use 64-bit integers if concerned about wrap-around aliasing in the cursor variables. Put(null) is considered illegal, but the caller or implementation can easily check for and convert null to a distinguished non-null proxy value if null happens to be a value you'd like to pass. Take() will accordingly convert the proxy value back to null. An advantage of PTLQueue is that you can use atomic fetch-and-increment for the partial methods. We initialize each slot at index I with (Turn=I, MailBox=null). Both cursors are initially 0. All shared variables are considered "volatile" and atomics such as CAS and AtomicFetchAndIncrement are presumed to have bidirectional fence semantics. Finally T is the templated type. I've sketched out a total tryTake() method below that allows the caller to poll the queue. tryPut() has an analogous construction. Zebra stripping : alternating row colors for nice-looking code listings. See also google code "prettify" : https://code.google.com/p/google-code-prettify/ Prettify is a javascript module that yields the HTML/CSS/JS equivalent of pretty-print. -- pre:nth-child(odd) { background-color:#ff0000; } pre:nth-child(even) { background-color:#0000ff; } border-left: 11px solid #ccc; margin: 1.7em 0 1.7em 0.3em; background-color:#BFB; font-size:12px; line-height:65%; " // PTLQueue : Put(v) : // producer : partial method - waits as necessary assert v != null assert Mask = 1 && (Mask & (Mask+1)) == 0 // Document invariants // doorway step // Obtain a sequence number -- ticket // As a practical concern the ticket value is temporally unique // The ticket also identifies and selects a slot auto tkt = AtomicFetchIncrement (&PutCursor, 1) slot * s = &Slots[tkt & Mask] // waiting phase : // wait for slot's generation to match the tkt value assigned to this put() invocation. // The "generation" is implicitly encoded as the upper bits in the cursor // above those used to specify the index : tkt div (Mask+1) // The generation serves as an epoch number to identify a cohort of threads // accessing disjoint slots while s-Turn != tkt : Pause assert s-MailBox == null s-MailBox = v // deposit and pass message Take() : // consumer : partial method - waits as necessary auto tkt = AtomicFetchIncrement (&TakeCursor,1) slot * s = &Slots[tkt & Mask] // 2-stage waiting : // First wait for turn for our generation // Acquire exclusive "take" access to slot's MailBox field // Then wait for the slot to become occupied while s-Turn != tkt : Pause // Concurrency in this section of code is now reduced to just 1 producer thread // vs 1 consumer thread. // For a given queue and slot, there will be most one Take() operation running // in this section. // Consumer waits for producer to arrive and make slot non-empty // Extract message; clear mailbox; advance Turn indicator // We have an obvious happens-before relation : // Put(m) happens-before corresponding Take() that returns that same "m" for T v = s-MailBox if v != null : s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 // unlock slot to admit next producer and consumer return v Pause tryTake() : // total method - returns ASAP with failure indication for auto tkt = TakeCursor slot * s = &Slots[tkt & Mask] if s-Turn != tkt : return null T v = s-MailBox // presumptive return value if v == null : return null // ratify tkt and v values and commit by advancing cursor if CAS (&TakeCursor, tkt, tkt+1) != tkt : continue s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 return v The basic idea derives from the Partitioned Ticket Lock "PTL" (US20120240126-A1) and the MultiLane Concurrent Bag (US8689237). The latter is essentially a circular ring-buffer where the elements themselves are queues or concurrent collections. You can think of the PTLQueue as a partitioned ticket lock "PTL" augmented to pass values from lock to unlock via the slots. Alternatively, you could conceptualize of PTLQueue as a degenerate MultiLane bag where each slot or "lane" consists of a simple single-word MailBox instead of a general queue. Each lane in PTLQueue also has a private Turn field which acts like the Turn (Grant) variables found in PTL. Turn enforces strict FIFO ordering and restricts concurrency on the slot mailbox field to at most one simultaneous put() and take() operation. PTL uses a single "ticket" variable and per-slot Turn (grant) fields while MultiLane has distinct PutCursor and TakeCursor cursors and abstract per-slot sub-queues. Both PTL and MultiLane advance their cursor and ticket variables with atomic fetch-and-increment. PTLQueue borrows from both PTL and MultiLane and has distinct put and take cursors and per-slot Turn fields. Instead of a per-slot queues, PTLQueue uses a simple single-word MailBox field. PutCursor and TakeCursor act like a pair of ticket locks, conferring "put" and "take" access to a given slot. PutCursor, for instance, assigns an incoming put() request to a slot and serves as a PTL "Ticket" to acquire "put" permission to that slot's MailBox field. To better explain the operation of PTLQueue we deconstruct the operation of put() and take() as follows. Put() first increments PutCursor obtaining a new unique ticket. That ticket value also identifies a slot. Put() next waits for that slot's Turn field to match that ticket value. This is tantamount to using a PTL to acquire "put" permission on the slot's MailBox field. Finally, having obtained exclusive "put" permission on the slot, put() stores the message value into the slot's MailBox. Take() similarly advances TakeCursor, identifying a slot, and then acquires and secures "take" permission on a slot by waiting for Turn. Take() then waits for the slot's MailBox to become non-empty, extracts the message, and clears MailBox. Finally, take() advances the slot's Turn field, which releases both "put" and "take" access to the slot's MailBox. Note the asymmetry : put() acquires "put" access to the slot, but take() releases that lock. At any given time, for a given slot in a PTLQueue, at most one thread has "put" access and at most one thread has "take" access. This restricts concurrency from general MPMC to 1-vs-1. We have 2 ticket locks -- one for put() and one for take() -- each with its own "ticket" variable in the form of the corresponding cursor, but they share a single "Grant" egress variable in the form of the slot's Turn variable. Advancing the PutCursor, for instance, serves two purposes. First, we obtain a unique ticket which identifies a slot. Second, incrementing the cursor is the doorway protocol step to acquire the per-slot mutual exclusion "put" lock. The cursors and operations to increment those cursors serve double-duty : slot-selection and ticket assignment for locking the slot's MailBox field. At any given time a slot MailBox field can be in one of the following states: empty with no pending operations -- neutral state; empty with one or more waiting take() operations pending -- deficit; occupied with no pending operations; occupied with one or more waiting put() operations -- surplus; empty with a pending put() or pending put() and take() operations -- transitional; or occupied with a pending take() or pending put() and take() operations -- transitional. The partial put() and take() operators can be implemented with an atomic fetch-and-increment operation, which may confer a performance advantage over a CAS-based loop. In addition we have independent PutCursor and TakeCursor cursors. Critically, a put() operation modifies PutCursor but does not access the TakeCursor and a take() operation modifies the TakeCursor cursor but does not access the PutCursor. This acts to reduce coherence traffic relative to some other queue designs. It's worth noting that slow threads or obstruction in one slot (or "lane") does not impede or obstruct operations in other slots -- this gives us some degree of obstruction isolation. PTLQueue is not lock-free, however. The implementation above is expressed with polite busy-waiting (Pause) but it's trivial to implement per-slot parking and unparking to deschedule waiting threads. It's also easy to convert the queue to a more general deque by replacing the PutCursor and TakeCursor cursors with Left/Front and Right/Back cursors that can move either direction. Specifically, to push and pop from the "left" side of the deque we would decrement and increment the Left cursor, respectively, and to push and pop from the "right" side of the deque we would increment and decrement the Right cursor, respectively. We used a variation of PTLQueue for message passing in our recent OPODIS 2013 paper. ul { list-style:none; padding-left:0; padding:0; margin:0; margin-left:0; } ul#myTagID { padding: 0px; margin: 0px; list-style:none; margin-left:0;} -- -- There's quite a bit of related literature in this area. I'll call out a few relevant references: Wilson's NYU Courant Institute UltraComputer dissertation from 1988 is classic and the canonical starting point : Operating System Data Structures for Shared-Memory MIMD Machines with Fetch-and-Add. Regarding provenance and priority, I think PTLQueue or queues effectively equivalent to PTLQueue have been independently rediscovered a number of times. See CB-Queue and BNPBV, below, for instance. But Wilson's dissertation anticipates the basic idea and seems to predate all the others. Gottlieb et al : Basic Techniques for the Efficient Coordination of Very Large Numbers of Cooperating Sequential Processors Orozco et al : CB-Queue in Toward high-throughput algorithms on many-core architectures which appeared in TACO 2012. Meneghin et al : BNPVB family in Performance evaluation of inter-thread communication mechanisms on multicore/multithreaded architecture Dmitry Vyukov : bounded MPMC queue (highly recommended) Alex Otenko : US8607249 (highly related). John Mellor-Crummey : Concurrent queues: Practical fetch-and-phi algorithms. Technical Report 229, Department of Computer Science, University of Rochester Thomasson : FIFO Distributed Bakery Algorithm (very similar to PTLQueue). Scott and Scherer : Dual Data Structures I'll propose an optimization left as an exercise for the reader. Say we wanted to reduce memory usage by eliminating inter-slot padding. Such padding is usually "dark" memory and otherwise unused and wasted. But eliminating the padding leaves us at risk of increased false sharing. Furthermore lets say it was usually the case that the PutCursor and TakeCursor were numerically close to each other. (That's true in some use cases). We might still reduce false sharing by incrementing the cursors by some value other than 1 that is not trivially small and is coprime with the number of slots. Alternatively, we might increment the cursor by one and mask as usual, resulting in a logical index. We then use that logical index value to index into a permutation table, yielding an effective index for use in the slot array. The permutation table would be constructed so that nearby logical indices would map to more distant effective indices. (Open question: what should that permutation look like? Possibly some perversion of a Gray code or De Bruijn sequence might be suitable). As an aside, say we need to busy-wait for some condition as follows : "while C == 0 : Pause". Lets say that C is usually non-zero, so we typically don't wait. But when C happens to be 0 we'll have to spin for some period, possibly brief. We can arrange for the code to be more machine-friendly with respect to the branch predictors by transforming the loop into : "if C == 0 : for { Pause; if C != 0 : break; }". Critically, we want to restructure the loop so there's one branch that controls entry and another that controls loop exit. A concern is that your compiler or JIT might be clever enough to transform this back to "while C == 0 : Pause". You can sometimes avoid this by inserting a call to a some type of very cheap "opaque" method that the compiler can't elide or reorder. On Solaris, for instance, you could use :"if C == 0 : { gethrtime(); for { Pause; if C != 0 : break; }}". It's worth noting the obvious duality between locks and queues. If you have strict FIFO lock implementation with local spinning and succession by direct handoff such as MCS or CLH,then you can usually transform that lock into a queue. Hidden commentary and annotations - invisible : * And of course there's a well-known duality between queues and locks, but I'll leave that topic for another blog post. * Compare and contrast : PTLQ vs PTL and MultiLane * Equivalent : Turn; seq; sequence; pos; position; ticket * Put = Lock; Deposit Take = identify and reserve slot; wait; extract & clear; unlock * conceptualize : Distinct PutLock and TakeLock implemented as ticket lock or PTL Distinct arrival cursors but share per-slot "Turn" variable provides exclusive role-based access to slot's mailbox field put() acquires exclusive access to a slot for purposes of "deposit" assigns slot round-robin and then acquires deposit access rights/perms to that slot take() acquires exclusive access to slot for purposes of "withdrawal" assigns slot round-robin and then acquires withdrawal access rights/perms to that slot At any given time, only one thread can have withdrawal access to a slot at any given time, only one thread can have deposit access to a slot Permissible for T1 to have deposit access and T2 to simultaneously have withdrawal access * round-robin for the purposes of; role-based; access mode; access role mailslot; mailbox; allocate/assign/identify slot rights; permission; license; access permission; * PTL/Ticket hybrid Asymmetric usage ; owner oblivious lock-unlock pairing K-exclusion add Grant cursor pass message m from lock to unlock via Slots[] array Cursor performs 2 functions : + PTL ticket + Assigns request to slot in round-robin fashion Deconstruct protocol : explication put() : allocate slot in round-robin fashion acquire PTL for "put" access store message into slot associated with PTL index take() : Acquire PTL for "take" access // doorway step seq = fetchAdd (&Grant, 1) s = &Slots[seq & Mask] // waiting phase while s-Turn != seq : pause Extract : wait for s-mailbox to be full v = s-mailbox s-mailbox = null Release PTL for both "put" and "take" access s-Turn = seq + Mask + 1 * Slot round-robin assignment and lock "doorway" protocol leverage the same cursor and FetchAdd operation on that cursor FetchAdd (&Cursor,1) + round-robin slot assignment and dispersal + PTL/ticket lock "doorway" step waiting phase is via "Turn" field in slot * PTLQueue uses 2 cursors -- put and take. Acquire "put" access to slot via PTL-like lock Acquire "take" access to slot via PTL-like lock 2 locks : put and take -- at most one thread can access slot's mailbox Both locks use same "turn" field Like multilane : 2 cursors : put and take slot is simple 1-capacity mailbox instead of queue Borrow per-slot turn/grant from PTL Provides strict FIFO Lock slot : put-vs-put take-vs-take at most one put accesses slot at any one time at most one put accesses take at any one time reduction to 1-vs-1 instead of N-vs-M concurrency Per slot locks for put/take Release put/take by advancing turn * is instrumental in ... * P-V Semaphore vs lock vs K-exclusion * See also : FastQueues-excerpt.java dice-etc/queue-mpmc-bounded-blocking-circular-xadd/ * PTLQueue is the same as PTLQB - identical * Expedient return; ASAP; prompt; immediately * Lamport's Bakery algorithm : doorway step then waiting phase Threads arriving at doorway obtain a unique ticket number Threads enter in ticket order * In the terminology of Reed and Kanodia a ticket lock corresponds to the busy-wait implementation of a semaphore using an eventcount and a sequencer It can also be thought of as an optimization of Lamport's bakery lock was designed for fault-tolerance rather than performance Instead of spinning on the release counter, processors using a bakery lock repeatedly examine the tickets of their peers --

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  • Performance Enhancement in Full-Text Search Query

    - by Calvin Sun
    Ever since its first release, we are continuing consolidating and developing InnoDB Full-Text Search feature. There is one recent improvement that worth blogging about. It is an effort with MySQL Optimizer team that simplifies some common queries’ Query Plans and dramatically shorted the query time. I will describe the issue, our solution and the end result by some performance numbers to demonstrate our efforts in continuing enhancement the Full-Text Search capability. The Issue: As we had discussed in previous Blogs, InnoDB implements Full-Text index as reversed auxiliary tables. The query once parsed will be reinterpreted into several queries into related auxiliary tables and then results are merged and consolidated to come up with the final result. So at the end of the query, we’ll have all matching records on hand, sorted by their ranking or by their Doc IDs. Unfortunately, MySQL’s optimizer and query processing had been initially designed for MyISAM Full-Text index, and sometimes did not fully utilize the complete result package from InnoDB. Here are a couple examples: Case 1: Query result ordered by Rank with only top N results: mysql> SELECT FTS_DOC_ID, MATCH (title, body) AGAINST ('database') AS SCORE FROM articles ORDER BY score DESC LIMIT 1; In this query, user tries to retrieve a single record with highest ranking. It should have a quick answer once we have all the matching documents on hand, especially if there are ranked. However, before this change, MySQL would almost retrieve rankings for almost every row in the table, sort them and them come with the top rank result. This whole retrieve and sort is quite unnecessary given the InnoDB already have the answer. In a real life case, user could have millions of rows, so in the old scheme, it would retrieve millions of rows' ranking and sort them, even if our FTS already found there are two 3 matched rows. Apparently, the million ranking retrieve is done in vain. In above case, it should just ask for 3 matched rows' ranking, all other rows' ranking are 0. If it want the top ranking, then it can just get the first record from our already sorted result. Case 2: Select Count(*) on matching records: mysql> SELECT COUNT(*) FROM articles WHERE MATCH (title,body) AGAINST ('database' IN NATURAL LANGUAGE MODE); In this case, InnoDB search can find matching rows quickly and will have all matching rows. However, before our change, in the old scheme, every row in the table was requested by MySQL one by one, just to check whether its ranking is larger than 0, and later comes up a count. In fact, there is no need for MySQL to fetch all rows, instead InnoDB already had all the matching records. The only thing need is to call an InnoDB API to retrieve the count The difference can be huge. Following query output shows how big the difference can be: mysql> select count(*) from searchindex_inno where match(si_title, si_text) against ('people')  +----------+ | count(*) | +----------+ | 666877 | +----------+ 1 row in set (16 min 17.37 sec) So the query took almost 16 minutes. Let’s see how long the InnoDB can come up the result. In InnoDB, you can obtain extra diagnostic printout by turning on “innodb_ft_enable_diag_print”, this will print out extra query info: Error log: keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 2 secs: row(s) 666877: error: 10 ft_init() ft_init_ext() keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 3 secs: row(s) 666877: error: 10 Output shows it only took InnoDB only 3 seconds to get the result, while the whole query took 16 minutes to finish. So large amount of time has been wasted on the un-needed row fetching. The Solution: The solution is obvious. MySQL can skip some of its steps, optimize its plan and obtain useful information directly from InnoDB. Some of savings from doing this include: 1) Avoid redundant sorting. Since InnoDB already sorted the result according to ranking. MySQL Query Processing layer does not need to sort to get top matching results. 2) Avoid row by row fetching to get the matching count. InnoDB provides all the matching records. All those not in the result list should all have ranking of 0, and no need to be retrieved. And InnoDB has a count of total matching records on hand. No need to recount. 3) Covered index scan. InnoDB results always contains the matching records' Document ID and their ranking. So if only the Document ID and ranking is needed, there is no need to go to user table to fetch the record itself. 4) Narrow the search result early, reduce the user table access. If the user wants to get top N matching records, we do not need to fetch all matching records from user table. We should be able to first select TOP N matching DOC IDs, and then only fetch corresponding records with these Doc IDs. Performance Results and comparison with MyISAM The result by this change is very obvious. I includes six testing result performed by Alexander Rubin just to demonstrate how fast the InnoDB query now becomes when comparing MyISAM Full-Text Search. These tests are base on the English Wikipedia data of 5.4 Million rows and approximately 16G table. The test was performed on a machine with 1 CPU Dual Core, SSD drive, 8G of RAM and InnoDB_buffer_pool is set to 8 GB. Table 1: SELECT with LIMIT CLAUSE mysql> SELECT si_title, match(si_title, si_text) against('family') as rel FROM si WHERE match(si_title, si_text) against('family') ORDER BY rel desc LIMIT 10; InnoDB MyISAM Times Faster Time for the query 1.63 sec 3 min 26.31 sec 127 You can see for this particular query (retrieve top 10 records), InnoDB Full-Text Search is now approximately 127 times faster than MyISAM. Table 2: SELECT COUNT QUERY mysql>select count(*) from si where match(si_title, si_text) against('family‘); +----------+ | count(*) | +----------+ | 293955 | +----------+ InnoDB MyISAM Times Faster Time for the query 1.35 sec 28 min 59.59 sec 1289 In this particular case, where there are 293k matching results, InnoDB took only 1.35 second to get all of them, while take MyISAM almost half an hour, that is about 1289 times faster!. Table 3: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county California 0.93 sec 32.03 sec 34.4 President united states of America 2.5 sec 36.98 sec 14.8 Table 4: SELECT title and text with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, si_title, si_text, ... as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.61 sec 41.65 sec 68.3 family film 1.15 sec 47.17 sec 41.0 Pizza restaurant orange county california 1.03 sec 48.2 sec 46.8 President united states of america 2.49 sec 44.61 sec 17.9 Table 5: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel  FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county califormia 0.93 sec 32.03 sec 34.4 President united states of america 2.5 sec 36.98 sec 14.8 Table 6: SELECT COUNT(*) mysql> SELECT count(*) FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.47 sec 82 sec 174.5 family film 0.83 sec 131 sec 157.8 Pizza restaurant orange county califormia 0.74 sec 106 sec 143.2 President united states of america 1.96 sec 220 sec 112.2  Again, table 3 to table 6 all showing InnoDB consistently outperform MyISAM in these queries by a large margin. It becomes obvious the InnoDB has great advantage over MyISAM in handling large data search. Summary: These results demonstrate the great performance we could achieve by making MySQL optimizer and InnoDB Full-Text Search more tightly coupled. I think there are still many cases that InnoDB’s result info have not been fully taken advantage of, which means we still have great room to improve. And we will continuously explore the area, and get more dramatic results for InnoDB full-text searches. Jimmy Yang, September 29, 2012

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  • July, the 31 Days of SQL Server DMO’s – Day 26 (sys.dm_db_log_space_usage)

    - by Tamarick Hill
    The sys.dm_db_log_space_usage DMV is a new DMV for SQL Server 2012. It returns Total Size, Used Size, and Used Percent size for a transaction log file of a given database. To illustrate this DMV, I will query the DMV against my AdventureWorks2012 database. SELECT * FROM sys.dm_db_log_space_usage As mentioned above, the result set gives us the total size of the transaction log in bytes, the used size of the log in bytes, and the percent of the log that has been used. This is a very simplistic DMV but returns valuable information. Being able to detect when a transaction log is close to being full is always a valuable thing to alert on, and this DMV just provided an additional method for acquiring the necessary information. Follow me on Twitter @PrimeTimeDBA

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  • Measure load of ubuntu server

    - by user84471
    I have Ubuntu server and apache2 installed on it. I want to benchmark it using ab tool from another machine. I want to know how measure load of this program. In top is showing this: top - 06:02:19 up 3 min, 2 users, load average: 0.28, 0.26, 0.12 Tasks: 94 total, 2 running, 92 sleeping, 0 stopped, 0 zombie Cpu(s): 67.2%us, 5.5%sy, 0.0%ni, 26.3%id, 0.5%wa, 0.0%hi, 0.5%si, 0.0%st Mem: 499320k total, 342028k used, 157292k free, 42504k buffers Swap: 514044k total, 0k used, 514044k free, 71388k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 1521 www-data 20 0 49180 22m 4144 S 23 4.6 0:00.68 apache2 1520 www-data 20 0 49180 22m 4152 S 22 4.6 0:00.66 apache2 1124 www-data 20 0 49180 22m 4152 S 22 4.6 0:00.70 apache2 1519 www-data 20 0 49180 22m 4152 S 20 4.6 0:00.70 apache2 1525 www-data 20 0 49180 22m 4144 S 16 4.6 0:00.47 apache2 1123 www-data 20 0 49168 22m 4152 S 9 4.6 0:00.78 apache2 1125 www-data 20 0 49168 22m 4152 S 9 4.6 0:00.77 apache2 1126 www-data 20 0 49168 22m 4152 S 9 4.6 0:00.73 apache2 1127 www-data 20 0 49168 22m 4152 S 9 4.6 0:00.74 apache2 1523 www-data 20 0 42896 14m 3388 R 5 3.1 0:00.14 apache2 1038 whoopsie 20 0 24476 3720 2856 S 0 0.7 0:00.01 whoopsie 1089 root 20 0 34060 6988 3640 S 0 1.4 0:00.05 apache2 1338 ubuntu 20 0 2832 1192 944 S 0 0.2 0:00.30 top 1417 ubuntu 20 0 9652 1456 824 S 0 0.3 0:00.02 sshd 1 root 20 0 3540 1876 1248 S 0 0.4 0:00.83 init 2 root 20 0 0 0 0 S 0 0.0 0:00.00 kthreadd 3 root 20 0 0 0 0 S 0 0.0 0:00.03 ksoftirqd/0 4 root 20 0 0 0 0 S 0 0.0 0:00.00 kworker/0:0 5 root 20 0 0 0 0 S 0 0.0 0:00.48 kworker/u:0 6 root RT 0 0 0 0 S 0 0.0 0:00.00 migration/0 7 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/0 8 root RT 0 0 0 0 S 0 0.0 0:00.00 migration/1 9 root 20 0 0 0 0 S 0 0.0 0:00.00 kworker/1:0 10 root 20 0 0 0 0 S 0 0.0 0:00.01 ksoftirqd/1 11 root 20 0 0 0 0 S 0 0.0 0:00.17 kworker/0:1 12 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/1 13 root 0 -20 0 0 0 S 0 0.0 0:00.00 cpuset 14 root 0 -20 0 0 0 S 0 0.0 0:00.00 khelper 15 root 20 0 0 0 0 S 0 0.0 0:00.00 kdevtmpfs 16 root 0 -20 0 0 0 S 0 0.0 0:00.00 netns 17 root 20 0 0 0 0 S 0 0.0 0:00.32 kworker/u:1 18 root 20 0 0 0 0 S 0 0.0 0:00.00 sync_supers 19 root 20 0 0 0 0 S 0 0.0 0:00.00 bdi-default 20 root 0 -20 0 0 0 S 0 0.0 0:00.00 kintegrityd 21 root 0 -20 0 0 0 S 0 0.0 0:00.00 kblockd 22 root 0 -20 0 0 0 S 0 0.0 0:00.00 ata_sff 23 root 20 0 0 0 0 S 0 0.0 0:00.00 khubd So its difficult to do it without any script or program. How can I do this?

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  • Chromium/Chrome tabs crashes on Ubuntu/Edubuntu 12.04.3

    - by Joakim Waern
    For some reason the tabs of Chromium and Chrome have started to crash (He's dead Jim) when running on Ubuntu or Edubuntu 12.04.3. It seems to happen only when I log in. I tried the browsers on Ubuntu 13.10 and everything worked fine. Any suggestions? Ps. The browser doesn't crash, just the tabs, and I can open new ones (but they also crash after a while). Here's the output command free on the terminal after a tab crash: total used free shared buffers cached Mem: 2041116 1722740 318376 0 2868 267256 -/+ buffers/cache: 1452616 588500 Swap: 2085884 104 2085780 Compared to the output before the crash: total used free shared buffers cached Mem: 2041116 1967108 74008 0 14632 253036 -/+ buffers/cache: 1699440 341676 Swap: 2085884 40 2085844

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  • Integrating application ad-support - best practice

    - by Jarede
    Considering the review that came out in March: Researchers from Purdue University in collaboration with Microsoft claim that third-party advertising in free smartphone apps can be responsible for as much as 65 percent to 75 percent of an app's energy consumption. Is there a best practice for integrating advert support into mobile applications, so as to not drain user battery too much. When you fire up Angry Birds on your Android phone, the researchers found that the core gaming component only consumes about 18 percent of total app energy. The biggest battery suck comes from the software powering third-party ads and analytics accounting for 45 percent of total app energy, according to the study. Has anyone invoked better ways of keeping away from the "3G Tail", as the report puts it. Is it better/possible to download a large set of adverts that are cached for a few hours, and using them to populate your ad space, to avoid constant use of the wifi/3g radios. Are there any best practices for the inclusion of adverts in mobile apps?

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  • ubuntu is very slow

    - by johnny smithens
    Hello all. I am new with Ubuntu, and it is very slow(even in Ubuntu 2D). The performance is degraded for almost any task. I just reinstalled with amd64, and tried updating the Nvidia drivers with Nvidia Xserver. but it made no difference. This is the output of free -m: total used free shared buffers cached Mem: 3006 1318 1688 0 61 699 -/+ buffers/cache: 556 2449 Swap: 3064 0 3064 tl;dr - total: 3006, used: 1318 When I see the virtual console with Ctrl+Alt+F2, I see constantly: Assuming Drive Cache: write through; asking for cache data failed; It is very frustrating. Thanks in advance!

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  • Linux server apache httpd processes take i/o wait to close to 100% and lock down server

    - by user3682065
    For about 5 days now, and seemingly out of the blue, my linux server has started locking up from time to time. The pattern is always the same as far as I can tell from top and iotop commands around the time it starts happening: One or more httpd processes (usually one) hang and start using up 100% of CPU power, the %wa goes close to 100% and in the iotop I see several httpd processes with 99.99% in the IO column. I'm also running an SVN server on this machine through apache and the one way that I've been consistently able to reproduce this is to do an SVN commit of new files or an SVN update from the repository on this server (I am the only one using this SVN repository). This will always reproduce this scenario successfully, but until very recently I had no problems at all checking in/out of SVN. But sometimes it just happens for no detectable reason at all it seems. So it seems like there is some issue with my Apache that leads it to have processes use up a lot of read/write upon certain triggers. I was wondering if anyone could help me uncover that issue. EDIT: OK now it's happening again: This is top: [root@server ~]# top top - 10:56:54 up 2:59, 5 users, load average: 171.46, 70.35, 27.01 Tasks: 328 total, 2 running, 326 sleeping, 0 stopped, 0 zombie Cpu(s): 1.9%us, 2.0%sy, 0.0%ni, 0.0%id, 96.1%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 2021144k total, 1968192k used, 52952k free, 2500k buffers Swap: 4194288k total, 2938584k used, 1255704k free, 39008k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 10390 apache 20 0 2774m 936m 6200 D 2.0 47.4 1:52.27 httpd 2149 root 20 0 927m 13m 1040 S 0.7 0.7 1:50.46 namecoind 11 root 20 0 0 0 0 R 0.3 0.0 0:30.10 events/0 23 root 20 0 0 0 0 S 0.3 0.0 0:17.88 kblockd/1 2049 root 20 0 382m 4932 2880 D 0.3 0.2 0:03.67 httpd 2144 root 20 0 1702m 69m 1164 S 0.3 3.5 5:19.68 bitcoind 6325 root 20 0 15164 1100 656 R 0.3 0.1 0:11.09 top 10311 apache 20 0 387m 9496 7320 D 0.3 0.5 0:01.89 httpd 10313 apache 20 0 391m 10m 7364 D 0.3 0.5 0:02.40 httpd 10466 apache 20 0 399m 12m 7392 D 0.3 0.7 0:02.41 httpd 10599 apache 20 0 391m 9324 7340 D 0.3 0.5 0:00.15 httpd 10628 apache 20 0 384m 7620 4052 D 0.3 0.4 0:00.01 httpd 10633 apache 20 0 384m 7048 3504 D 0.3 0.3 0:00.01 httpd 10634 apache 20 0 384m 8012 4048 D 0.3 0.4 0:00.02 httpd 10638 apache 20 0 400m 22m 9.8m D 0.3 1.1 0:01.93 httpd 10640 apache 20 0 385m 8288 4028 D 0.3 0.4 0:00.03 httpd 10641 apache 20 0 401m 21m 6376 D 0.3 1.1 0:01.45 httpd 10759 apache 20 0 385m 8816 3480 D 0.3 0.4 0:01.45 httpd 10773 apache 20 0 384m 8044 3464 D 0.3 0.4 0:00.02 httpd This is an iotop snapshot: Total DISK READ: 5.93 M/s | Total DISK WRITE: 0.00 B/s TID PRIO USER DISK READ DISK WRITE SWAPIN IO> COMMAND 10732 be/4 apache 3.76 K/s 0.00 B/s 0.00 % 58.48 % httpd 876 be/3 root 0.00 B/s 52.68 K/s 0.00 % 52.98 % [jbd2/dm-1-8] 10906 be/4 root 124.17 K/s 0.00 B/s 0.00 % 23.03 % sh -c [ -x /usr/local/psa/admin/sbin/backupmng ] && /usr/local/psa/admin/sbin/backupmng >/dev/null 2>&1 2156 be/4 root 206.94 K/s 0.00 B/s 0.00 % 21.15 % bitcoind 10904 be/4 mysql 0.00 B/s 0.00 B/s 0.00 % 18.94 % mysqld --basedir=/usr --datadir=/var/lib/mysql --user=mysql --log-error=/var/log/mysqld.log --pid-file=/var/run/mysqld/mysqld.pid --socket=/var/lib/mysql/mysql.sock 10773 be/4 apache 7.53 K/s 0.00 B/s 0.00 % 14.77 % httpd 10641 be/4 apache 15.05 K/s 0.00 B/s 0.00 % 11.57 % httpd 10399 be/4 apache 1057.29 K/s 0.00 B/s 43.16 % 10.56 % httpd 10682 be/4 sw-cp-se 158.03 K/s 0.00 B/s 0.00 % 7.45 % sw-engine-cgi -c /usr/local/psa/admin/conf/php.ini -d auto_prepend_file=auth.php3 -u psaadm 10774 be/4 apache 3.76 K/s 0.00 B/s 0.00 % 6.53 % httpd 10624 be/4 apache 0.00 B/s 0.00 B/s 0.00 % 5.53 % httpd 10356 be/4 apache 899.26 K/s 0.00 B/s 35.52 % 4.01 % httpd 10795 be/4 apache 0.00 B/s 0.00 B/s 0.00 % 3.93 % httpd 10804 be/4 apache 7.53 K/s 0.00 B/s 0.00 % 3.08 % httpd 4379 be/4 root 2.89 M/s 0.00 B/s 99.99 % 0.00 % namecoind 10619 be/4 apache 462.80 K/s 0.00 B/s 7.80 % 0.00 % httpd 10636 be/4 apache 3.76 K/s 0.00 B/s 0.00 % 0.00 % httpd 10716 be/4 mysql 105.35 K/s 0.00 B/s 5.92 % 0.00 % mysqld --basedir=/usr --datadir=/var/lib/mysql --user=mysql --log-error=/var/log/mysqld.log --pid-file=/var/run/mysqld/mysqld.pid --socket=/var/lib/mysql/mysql.sock 1988 be/4 root 18.81 K/s 0.00 B/s 0.00 % 0.00 % spamd_full.sock I also ran lsof -p for pid 10390 which was way up top under the top command and this is the bottom line where I can sort of see what request this was and it says CLOSE_WAIT: httpd 10390 apache 34u IPv6 315879 0t0 TCP default-domain.com:https->crawl-66-249-65-91.googlebot.com:42907 (CLOSE_WAIT) I'm still not sure what exactly is causing this all to happen though? I killed that service but %wa and load average remain high, I also stopped mysqld and other services. It really only goes down once I stop httpd altogether, and even then I can't start it without finding remaining hanging httpd processes via "netstat -tulpn", killing those or doing "killall -9 httpd" and after waiting a while for it to cycle through all those then doing /etc/init.d/httpd start

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  • Ubuntu 12.04.1 LTS USB not being detected after formatting with Startup Disk Creator

    - by Zach
    sudo fdisk -l lists the drive, however, I cannot find it in the file explorer. Disk /dev/sda: 250.1 GB, 250059350016 bytes 255 heads, 63 sectors/track, 30401 cylinders, total 488397168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x000d871e Device Boot Start End Blocks Id System /dev/sda1 * 2048 486322175 243160064 83 Linux /dev/sda2 486324222 488396799 1036289 5 Extended /dev/sda5 486324224 488396799 1036288 82 Linux swap / Solaris Disk /dev/sdb: 8195 MB, 8195480064 bytes 253 heads, 62 sectors/track, 1020 cylinders, total 16006797 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x00027ae4 Device Boot Start End Blocks Id System /dev/sdb1 * 62 15999719 M 7999829 c W95 FAT32 (LBA) Manually mounting it produces this error message :~$ sudo mount -t vfat /dev/sdb1 /media/external -ouiduid=1000,gid=1000,utf8,dmask=027,fmask=137 mount: wrong fs type, bad option, bad superblock on /dev/sdb1, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so Is the usb toast?

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  • GParted detects entire disk as UNALLOCATED SPACE + hd0 out of disk

    - by msPeachy
    Good day to everyone. I hope someone can help me with my problem. I have a dual boot Windows and Ubuntu system. I recently encountered an hd0 out of disk error and wasn't able to boot Ubuntu. So I booted into Windows. After 2 to 3 times of booting and rebooting Windows, I tried booting Ubuntu again but still I get the same hd0 out of disk error. I decided to run Ubuntu from LIVEUSB to try to fix my Ubuntu partition using GParted, but when I run GParted, it shows my entire disk as UNALLOCATED SPACE! The strange thing is that Nautilus still shows and mounts my partitions. Also every time I boot into Windows , my partitions exists and I am able to read and write to them. I have no idea what is wrong. Please help! I can't stand using Windows since most of the tools I use are in Ubuntu. I don't mind reinstalling Ubuntu. In fact I already tried reinstalling using the LIVEUSB but since GParted or the Ubuntu installer itself does not recognize my partitions and shows the entire disk as unallocated space, I decided not to continue. I am currently running Ubuntu from LIVEUSB. Here's the outpuf of sudo fdisk -l Disk /dev/sda: 320.1 GB, 320072933376 bytes 255 heads, 63 sectors/track, 38913 cylinders, total 625142448 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0xb30ab30a Device Boot Start End Blocks Id System /dev/sda1 * 2048 104869887 52433920 83 Linux /dev/sda2 104869888 105074687 102400 7 HPFS/NTFS/exFAT /dev/sda3 105074688 156149759 25537536 7 HPFS/NTFS/exFAT /dev/sda4 156151800 625153409 234500805 f W95 Ext'd (LBA) /dev/sda5 156151808 169156591 6502392 82 Linux swap / Solaris /dev/sda6 169158656 294991871 62916608 7 HPFS/NTFS/exFAT /dev/sda7 294993920 471037944 88022012+ 7 HPFS/NTFS/exFAT /dev/sda8 471041928 625121152 77039612+ 7 HPFS/NTFS/exFAT When I run, sudo parted -l, I got this error message: ubuntu@ubuntu:~$ sudo parted -l Error: Can't have a partition outside the disk! UPDATE I think I might know the problem. The total sectors of sda is 625142448 but the extended partition (sda4) ends at 625153409. Now, my question is, how do I fix this or modify the extended partition (sda4) to matched the total number of sectors? Anyone, please??? UPDATE I was able to fix the unallocated space issue with the help of Rod Smith's tool called fixparts I am now able to view my partitions via GParted in LiveUSB. But the error: hd0 out of disk. Press any key to continue... still persists on reboot. I still can't boot into Ubuntu. Can someone help me please???

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  • Identify memory leak in Java app

    - by Vincent Ma
    One important advantage of java is programer don't care memory management and GC handle it well. Maybe this is one reason why java is more popular. As Java programer you real dont care it? After you meet Out of memory you will realize it it’s not true. Java GC and memory is big topic you can get some information in here Today just let me show how to identify memory leak quickly. Let quickly review demo java code, it’s one kind of memory leak in our code, using static collection and always add some object. import java.util.ArrayList;import java.util.List; public class MemoryTest { public static void main(String[] args) { new Thread(new MemoryLeak(), "MemoryLeak").start(); }} class MemoryLeak implements Runnable { public static List<Integer> leakList = new ArrayList<Integer>(); public void run() { int num =0; while(true) { try { Thread.sleep(1); } catch (InterruptedException e) { } num++; Integer i = new Integer(num); leakList.add(i); } }} run it with java -verbose:gc -XX:+PrintGCDetails -Xmx60m -XX:MaxPermSize=160m MemoryTest after about some minuts you will get Exception in thread "MemoryLeak" java.lang.OutOfMemoryError: Java heap space at java.util.Arrays.copyOf(Arrays.java:2760) at java.util.Arrays.copyOf(Arrays.java:2734) at java.util.ArrayList.ensureCapacity(ArrayList.java:167) at java.util.ArrayList.add(ArrayList.java:351) at MemoryLeak.run(MemoryTest.java:25) at java.lang.Thread.run(Thread.java:619)Heap def new generation total 18432K, used 3703K [0x045e0000, 0x059e0000, 0x059e0000) eden space 16384K, 22% used [0x045e0000, 0x0497dde0, 0x055e0000) from space 2048K, 0% used [0x055e0000, 0x055e0000, 0x057e0000) to space 2048K, 0% used [0x057e0000, 0x057e0000, 0x059e0000) tenured generation total 40960K, used 40959K [0x059e0000, 0x081e0000, 0x081e0000) the space 40960K, 99% used [0x059e0000, 0x081dfff8, 0x081e0000, 0x081e0000) compacting perm gen total 12288K, used 2083K [0x081e0000, 0x08de0000, 0x10de0000) the space 12288K, 16% used [0x081e0000, 0x083e8c50, 0x083e8e00, 0x08de0000)No shared spaces configured. OK let us quickly identify it using JProfile Download JProfile in here  Run JProfile and attach MemoryTest get largest size of  Objects in Memory View in here is Integer then select Integer and go to Heap Walker. get GC Graph for this object  Then you get detail code raise this issue quickly now.  That is enjoy it.

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  • Why do large IT projects tend to fail or have big cost/schedule overruns?

    - by Pratik
    I always read about large scale transformation or integration project that are total or almost total disaster. Even if they somehow manage to succeed the cost and schedule blow out is enormous. What is the real reason behind large projects being more prone to failure. Can agile be used in these sort of projects or traditional approach is still the best. One example from Australia is the Queensland Payroll project where they changed test success criteria to deliver the project. See some more failed projects in this SO question Have you got any personal experience to share?

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  • Could not apply stored configuration for monitors

    - by Hernantz
    Well this happened when I upgraded to Natty. Not only seems I can't change my resolution to higher than 1024x768 but it appears at the left and using only 70% of the monitor's width. I tried logging in but in ubuntu classic mode, and i was able to change it, but that trick did not work anymore. (May this be a compiz problem?) Anyways, here is my /var/log/Xorg.0.log http://pastebin.com/Ew4wwLab and lspci -nn | grep VGA: 00:02.0 VGA compatible controller [0300]: Intel Corporation Mobile 945GM/GMS, 943/940GML Express Integrated Graphics Controller [8086:27a2] (rev 03) I tried using xrandr for adding manually a resolution of 1280x1768 but without luck. Here is the xrandr output Screen 0: minimum 320 x 200, current 1024 x 768, maximum 4096 x 4096 LVDS1 connected 1024x768+0+0 (normal left inverted right x axis y axis) 0mm x 0mm 1024x768 60.0*+ 800x600 60.3 56.2 640x480 59.9 VGA1 disconnected (normal left inverted right x axis y axis) TV1 disconnected (normal left inverted right x axis y axis) 1280x1024 (0xc6) 109.0MHz h: width 1280 start 1368 end 1496 total 1712 skew 0 clock 63.7KHz v: height 1024 start 1027 end 1034 total 1063 clock 59.9Hz

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  • How to make "xrandr" work with GMA500?

    - by Nwbie
    Is it error at driver of graphic chip or Xorg or kernel? I am Asus T91mt with GMA500, Ubuntu 12.04.1. I would like too see only a notice of connection at least. A log of xrandr: $ lspci | grep VGA 00:02.0 VGA compatible controller: Intel Corporation System Corporation System Controller Hub (SCH Poulcbo) Graphics Controller (rev 07) vp@vc:~$ xrandr --verbose xrandr: Failed to get size of gamma for output default Screen 0: minimum 1024 x 600, current 1024 x 600, maximum 1024 x 600 default connected 1024x600+0+0 (0x138) normal (normal) 0mm x 0mm Identifier: 0x137 Timestamp: 26863 Subpixel: unknown Clones: CRTC: 0 CRTCs: 0 Transform: 1.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 1.000000 filter: 1024x600 (0x138) 0.0MHz *current h: width 1024 start 0 end 0 total 1024 skew 0 clock 0.0KHz v: height 600 start 0 end 0 total 600 clock 0.0Hz vp@vc:~$ xrandr --prop xrandr: Failed to get size of gamma for output default Screen 0: minimum 1024 x 600, current 1024 x 600, maximum 1024 x 600 default connected 1024x600+0+0 0mm x 0mm 1024x600 0.0* vp@vc:~$ Please help, i am linux newbie and i am tired ;/

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  • Playing with F#

    - by mroberts
    Project Euler is a awesome site.   When working with a new language it can be tricky to find problems that need solving, that are more complex than "Hello World" and simpler than a full blown application. Project Euler gives use just that, cool and thought provoking problems that usually don't take days to solve.  I've solved a number of questions with C# and some with Java.  BTW, I used Java because it had BigInteger support before .Net. A couple weeks ago, back when winter had a firm grip on Columbus, OH, I began playing (researching) with F#.  I began with Problem #1 from Project Euler.  I started by looking at my solution in C#. Here is my solution in C#. 1: using System; 2: using System.Collections.Generic; 3:   4: namespace Problem001 5: { 6: class Program 7: { 8: static void Main(string[] args) 9: { 10: List<int> values = new List<int>(); 11:   12: for (int i = 1; i < 1000; i++) 13: { 14: if (i % 3 == 0 || i % 5 == 0) 15: values.Add(i); 16: } 17: int total = 0; 18:   19: values.ForEach(v => total += v); 20:   21: Console.WriteLine(total); 22: Console.ReadKey(); 23: } 24: } 25: }   Now, after much tweaking and learning, here is my solution in F#.   1: open System 2:   3: let calc n = 4: [1..n] 5: |> List.map (fun x -> if (x % 3 = 0 || x % 5 = 0) then x else 0) 6: |> List.sum 7:   8: let main() = 9: calc 999 10: |> printfn "result = %d" 11: Console.ReadKey(true) |> ignore 12:   13: main() Just this little example highlights some cool things about F#. Type inference. F# infers the type of a value.  In the C# code above we declare a number of variables, the list, and a couple ints.  F# does not require this, it infers the calc (a function) accepts a int and returns a int. Great built in functionality for Lists.  List.map for example. BTW, I don’t think I’m spilling the beans by giving away the code for Problem 1.  It by far is the easiest question, IMHO, solved by 92,000+ people. Next I’ll look into writing a class library with F#.

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