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  • Debian, CentOS, Slackware, FreeBSD, OpenSolaris and Ubuntu Server Edition: Which one to use for an http web server?

    - by Ako
    I am going to install and administrate a virtual server for a small university. The server should run inside a virtual machine (VirtualBox OSE). It is only used in the university network and is invisible to the outside world. It should run Apache web server for PHP, MySQL and probably a mail server. I don't know which OS to use. Main criteria for choosing include ease of administration and updating, package management and performance. I wonder if anyone has any suggestions? And candidate OSs are: Debian, Ubuntu, CentOS, Slackware, FreeBSD, OpenSolaris. Add any other OS if you know any better alternatives.

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  • unable to update gridview

    - by bhakti
    Please help ,i have added update/edit command button in gridview so to update data in my sql server database but am unable to do it. Data is not updated in database . ======code for onrowupdate======================================== protected void gRowUpdate(object sender, GridViewUpdateEventArgs e) { Books b = null; b = new Books(); DataTable dt=null; GridView g = (GridView)sender; try { dt=new DataTable(); b = new Books(); b.author = Convert.ToString(g.Rows[e.RowIndex].FindControl("Author")); b.bookID = Convert.ToInt32(g.Rows[e.RowIndex].FindControl("BookID")); b.title = Convert.ToString(g.Rows[e.RowIndex].FindControl("Title")); b.price = Convert.ToDouble(g.Rows[e.RowIndex].FindControl("Price")); // b.rec = Convert.ToString(g.Rows[e.RowIndex].FindControl("Date_of_reciept")); b.ed = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.bill = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.cre_by = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.src = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.pages = Convert.ToInt32(g.Rows[e.RowIndex].FindControl("Edition")); b.pub = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.mod_by = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.remark = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); // b.year = Convert.ToString(g.Rows[e.RowIndex].FindControl("Edition")); b.updatebook(b); g.EditIndex = -1; dt = b.GetAllBooks(); g.DataSource = dt; g.DataBind(); } catch (Exception ex) { throw (ex); } finally { b = null; } } ===================My stored procedure for update book able to update database by exec in sqlserver mgmt studio========================== set ANSI_NULLS ON set QUOTED_IDENTIFIER ON go ALTER PROCEDURE [dbo].[usp_updatebook] @bookid bigint, @author varchar(50), @title varchar(50), @price bigint, @src_equisition varchar(50), @bill_no varchar(50), @publisher varchar(50), @pages bigint, @remark varchar(50), @edition varchar(50), @created_by varchar(50), @modified_by varchar(50) /*@date_of_reciept datetime, @year_of_publication datetime*/ AS declare @modified_on datetime set @modified_on=getdate() UPDATE books SET author=@author, title=@title, price=@price, src_equisition=@src_equisition, bill_no=@bill_no, publisher=@publisher, /*Date_of_reciept=@date_of_reciept,*/ pages=@pages, remark=@remark, edition=@edition, /*Year_of_publication=@year_of_publication,*/ created_by=@created_by, modified_on=@modified_on, modified_by=@modified_by WHERE bookid=@bookid ========================class library function for update==================== public void updatebook(Books b) { DataAccess dbAccess = null; SqlCommand cmd = null; try { dbAccess = new DataAccess(); cmd = dbAccess.GetSQLCommand("usp_updatebook", CommandType.StoredProcedure); cmd.Parameters.Add("@bookid", SqlDbType.VarChar, 50).Value = b.bookID; cmd.Parameters.Add("@author", SqlDbType.VarChar, 50).Value = b.author; cmd.Parameters.Add("@title", SqlDbType.VarChar, 50).Value = b.title; cmd.Parameters.Add("@price", SqlDbType.Money).Value = b.price; cmd.Parameters.Add("@publisher", SqlDbType.VarChar, 50).Value = b.pub; // cmd.Parameters.Add("@year_of_publication", SqlDbType.DateTime).Value =Convert.ToDateTime( b.year); cmd.Parameters.Add("@src_equisition", SqlDbType.VarChar, 50).Value = b.src; cmd.Parameters.Add("@bill_no", SqlDbType.VarChar, 50).Value = b.bill; cmd.Parameters.Add("@remark", SqlDbType.VarChar, 50).Value = b.remark; cmd.Parameters.Add("@pages", SqlDbType.Int).Value = b.pages; cmd.Parameters.Add("@edition", SqlDbType.VarChar, 50).Value = b.ed; // cmd.Parameters.Add("@date_of_reciept", SqlDbType.DateTime).Value = Convert.ToDateTime(b.rec); // cmd.Parameters.Add("@created_on", SqlDbType.DateTime).Value = Convert.ToDateTime(b.cre_on); cmd.Parameters.Add("@created_by", SqlDbType.VarChar, 50).Value = b.cre_by; //cmd.Parameters.Add("@modified_on", SqlDbType.DateTime).Value = Convert.ToDateTime(b.mod_on); cmd.Parameters.Add("@modified_by", SqlDbType.VarChar, 50).Value = b.mod_by; cmd.ExecuteNonQuery(); } catch (Exception ex) { throw (ex); } finally { if (cmd.Connection != null && cmd.Connection.State == ConnectionState.Open) cmd.Connection.Close(); dbAccess = null; cmd = null; } } I have also tried to do update by following way protected void gv1_updating(object sender, GridViewUpdateEventArgs e) { GridView g = (GridView)sender; abc a = new abc(); DataTable dt = new DataTable(); try { a.cd_Id = Convert.ToInt32(g.DataKeys[e.RowIndex].Values[0].ToString()); //TextBox b = (TextBox)g.Rows[e.RowIndex].Cells[0].FindControl("cd_id"); TextBox c = (TextBox)g.Rows[e.RowIndex].Cells[2].FindControl("cd_name"); TextBox d = (TextBox)g.Rows[e.RowIndex].Cells[3].FindControl("version"); TextBox f = (TextBox)g.Rows[e.RowIndex].Cells[4].FindControl("company"); TextBox h = (TextBox)g.Rows[e.RowIndex].Cells[6].FindControl("created_by"); TextBox i = (TextBox)g.Rows[e.RowIndex].Cells[8].FindControl("modified_by"); //a.cd_Id = Convert.ToInt32(b.Text); a.cd_name = c.Text; a.ver = d.Text; a.comp = f.Text; a.cre_by = h.Text; a.mod_by = i.Text; a.updateDigi(a); g.EditIndex = -1; dt = a.GetAllDigi(); g.DataSource = dt; g.DataBind(); } catch(Exception ex) { throw (ex); } finally { dt = null; a = null; g = null; } } =================== but have error of Index out of range exception========= please do reply,thanxs in advance

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  • Is the Unicode prefix N still needed in SQL Compact Edition?

    - by Dave
    At least in previous versions of SQL Server, you had to prefix Unicode string constants with an "N" to make them be treated as Unicode. Thus, select foo from bar where fizz = N'buzz' (See "Server-Side Programming with Unicode" for SQL Server 2005 "from the horse's mouth" documentation.) We have an application that is using SQL Compact Edition and I am wondering if that is still necessary. From the testing I am doing, it appears to be unneeded. That is, the following SQL statements both behave identically in SQL CE, but the second one fails in SQL Server 2005: select foo from bar where foo=N'???' select foo from bar where foo='???' (I hope I'm not swearing in some language I don't know about...) I'm wondering if that is because all strings are treated as Unicode in SQL CE, or if perhaps the default code page is now Unicode-aware. If anyone has seen any official documentation, either yea or nay, I'd appreciate it. I know I could go the safe route and just add the "N"'s, but there's a lot of code that will need changed, and if I don't need to, I don't want to! Thanks for your help!

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  • MySQL: SELECT highest column value when WHERE finds similar entries

    - by Ike
    My question is comparable to this one, but not quite the same. I have a database with a huge amount of books, with different editions of some of the same book titles. I'm looking for an SQL statement giving me the highest edition number of each of the titles I'm selecting with a WHERE clause (to find specific book series). Here's what the table looks like: |id|title |edition|year| |--|-------------------------|-------|----| |01|Serie One Title One |1 |2007| |02|Serie One Title One |2 |2008| |03|Serie One Title One |3 |2009| |04|Serie One Title Two |1 |2001| |05|Serie One Title Three |1 |2008| |06|Serie One Title Three |2 |2009| |07|Serie One Title Three |3 |2010| |08|Serie One Title Three |4 |2011| |--|-------------------------|-------|----| The result I'm looking for is this: |id|title |edition|year| |--|-------------------------|-------|----| |03|Serie One Title One |3 |2009| |04|Serie One Title Two |1 |2001| |08|Serie One Title Three |4 |2011| |--|-------------------------|-------|----| The closest I got was using this statement: select id, title, max(edition), max(year) from books where title like "serie one%" group by name; but it returns the highest edition and year and includes the first id it finds: |--|-----------------------|-------|----| |01|Serie One Title One |3 |2009| |04|Serie One Title Two |1 |2001| |05|Serie One Title Three |4 |2011| |--|-----------------------|-------|----| This fancy join also comes close, but doesn't give the right result: select b.id, b.title, b.edition, b.year from books b inner join (select name, max(edition) as maxedition from books group by title) g on b.edition = g.maxedition where b.title like "serie one%" group by title; Using this I'm getting unique titles, but mostly old editions.

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  • Can I use pdb files to step through a 3rd party assembly?

    - by Pure.Krome
    Hi folks, my friend has made a really helpful class library which I use all the time. I usually use Reflector to see what his code does. What I really wanted to do was to step through his code while I'm debugging. So he gave me his .pdb file. Foo.dll (release configuration, compile) Foo.pdb Now, I'm not sure how I can get it to auto break into his code when it throws an exception (his code, at various points, thorws exceptions .. like A first chance exception of type 'System.Web.HttpException' occurred in Foo.dll ... Can I do this? Do i need to setup something with the Symbol Server settings in Visual Studio ? Do i need to get the dll compiled into Debug Configuration and be passed the .dll and .pdb files? Or (and i'm really afraid of this one) .. do i need to have both the .dll, .pdb AND his source code ... I also had a look at this previous SO question, but it sorta didn't help (but proof I've tried to search before asking a question). Can someone help me please?

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  • How and Where do I learn about how to hook up my uncreated Database to a 3rd party API

    - by raln
    I want to create a database with information that I can send to a third party... they give their api on their website but they don't break it down for new / newbs like myself... I'm confused and was thinking of getting a developer to do this all for me but I DON'T want to get ripped off... and overpay All it is is a webapplication backed by a database onto their platform where they support different API's but I also need a function in my web app that can send various messages via XML, or SMPP to their webservice.. . hmm -Ken

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  • Upload images API on 3rd Party host .. Flickr ?

    - by Enatom
    I am building an Image Sharing feature for my website, where users can upload images and show it off on my website, through their own profile gallery. Except I dont want to physically host the uploaded images. Are there API's that can allow me to descretly save the uploaded images (from the users) to another Host, such as Flickr, Google etc.. I know Flickr has a good API, but could I use it for this? And does the Flickr Upload API only work with authorised users ? becuase I dont want them to upload to their Flickr account, but just host them with 1 big account so to speak thanks.

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  • how is this jquery app validating the username? (3rd party script)

    - by SarmenHB
    The tutorial that I'm trying to figure out is this: http://www.position-absolute.com/articles/jquery-form-validator-because-form-validation-is-a-mess/ The username field looks like this: <input value="" class="validate[required,custom[noSpecialCaracters],length[0,20],ajax[ajaxUser]]" type="text" name="user" id="user" /> That <input> field has a class item named ajax[ajaxUser] which has its rules contained in this script (jquery.validationEngine-en.js). The snippet for that item looks like this: "ajaxUser":{ "file":"validateUser.php", "extraData":"name=eric", "alertTextOk":"* This user is available", "alertTextLoad":"* Loading, please wait", "alertText":"* This user is already taken"}, What I can't figure out at all is how its PHP page is working which is validateUser.php. Where are all those post fields coming from? I looked around and can't find a field with those names. Thanks

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  • How to cope with developing against a poor 3rd party API/application?

    - by wsanville
    I'm a web developer, and my organization has recently started to use a proprietary ASP.NET CMS for our web sites. I was excited to get started using the CMS, thinking it would bring a lot of value to our end users and be fun to work with, since my skills are a good match for the types of projects we're using it for. That was about a year ago. Since then, we've ran into all kinds of issues, from blatant bugs in the product, to nasty edge cases in the APIs, to extremely poor documentation for developers. On about a weekly basis, we are forced to pursue workarounds and rewrite some of the out of the box functionality, and even find some of the basic features unusable. In many cases, since this is a closed source application (and obfuscated of course), there's nothing we can do as developers to solve these issues. So my question is, how does one attempt to develop a good application in such a scenario? The application mostly works when using the the exact out of the box behavior, or using one of the company's starter sites. However, my attempts to use the underlying APIs to implement slightly different, yet reasonable behavior has proved to be extremely time consuming (not to mention just as buggy), given the lack of good information about the APIs. I've given this a lot of thought, and my conflicting viewpoints are the following: Strongly advise against any customization to the CMS, as development time will rise exponentially, or even have an extremely high chance of failing. While this is accurate, I do not want to give the impression that I am not willing to code my own solutions to problems and take the initiative to implement something difficult or complex. I don't want to be perceived as someone who is not motivated, lazy, or not knowledgeable to do anything complex, because this is simply not the case. I love coding my own solutions, trying new/difficult things, I just dislike the vendor app we're using. Continue on the path I'm on now, which is hacking my way past all issues I encounter and try my best to deliver an application that meets the needs and specs exactly. My goals are to make it as seamless and easy to use as possible to the end user, even when integrating the CMS with our other applications internally. The problem I'm finding with this approach is it is very time consuming. I open support cases with the vendor on a regular basis to solve issues and to gain knowledge of their APIs, but this is extremely time consuming, and in some cases it leads to dead ends. I post on the vendors forums on a regular basis but have become frustrated as most of my posts get 0 replies. So, what would you, a reasonable developer, do in this case? How can I make the best of the situation? And just for fun, here are some of the code smells and anti-patterns I've dealt with using the product (aside from their own code blatantly failing): Use of StringBuilder to concatenate a giant string that is hard coded and does not change. They use it to concatenate their Javascript and write it out into the body tags of their pages. Methods that accept object or Microsoft.VisualBasic.Collection as the parameters. In the case of the VB Collection, the data is not a list of any kind, it's used instead of making a class. Methods that return a Hashtable of VB Collections Method names of the form MethodName_v45, MethodName_v20, etc... Multiple classes with the same name in different namespaces with different functionality/behavior. Intellisense that reads "Note: this parameter is non functional" Complete lack of coding standards, API is filled with magic numbers and magic strings. Properties with a getter of type object that accepts totally different things, like enum or strings, and throw exceptions at runtime when you pass in something not supported. And much, much, more...

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  • What is the best way to mock a 3rd party object in ruby?

    - by spinlock
    I'm writing a test app using the twitter gem and I'd like to write an integration test but I can't figure out how to mock the objects in the Twitter namespace. Here's the function that I want to test: def build_twitter(omniauth) Twitter.configure do |config| config.consumer_key = TWITTER_KEY config.consumer_secret = TWITTER_SECRET config.oauth_token = omniauth['credentials']['token'] config.oauth_token_secret = omniauth['credentials']['secret'] end client = Twitter::Client.new user = client.current_user self.name = user.name end and here's the rspec test that I'm trying to write: feature 'testing oauth' do before(:each) do @twitter = double("Twitter") @twitter.stub!(:configure).and_return true @client = double("Twitter::Client") @client.stub!(:current_user).and_return(@user) @user = double("Twitter::User") @user.stub!(:name).and_return("Tester") end scenario 'twitter' do visit root_path login_with_oauth page.should have_content("Pages#home") end end But, I'm getting this error: 1) testing oauth twitter Failure/Error: login_with_oauth Twitter::Error::Unauthorized: GET https://api.twitter.com/1/account/verify_credentials.json: 401: Invalid / expired Token # ./app/models/user.rb:40:in `build_twitter' # ./app/models/user.rb:16:in `build_authentication' # ./app/controllers/authentications_controller.rb:47:in `create' # ./spec/support/integration_spec_helper.rb:3:in `login_with_oauth' # ./spec/integration/twit_test.rb:16:in `block (2 levels) in <top (required)>' The mocks above are using rspec but I'm open to trying mocha too. Any help would be greatly appreciated.

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  • Can we find out the difference between 2 RGb colors to find out a 3rd color?

    - by AK
    2 colors are mixed together. If i have the RGB for the resultant color and RGB for one of the colors mixed, then somehow i could calculate the 2nd color? I will try to explain visually what i am trying to say. Here is a flickr link http://www.flickr.com/photos/48150615@N08/4407414157 I know that the circle in the middle has an opacity of 20% Is there any way to know the color value of the circle so that i can deduct that to get the same color value as the background color.

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  • jQuery how to add class to a parent div which has a 3rd level child div with a specific class name.

    - by Vikram
    Hello friends I have an issue adding a special class to a couple of my divs. My layout is like this. <div class="container"> <div class="grid-6 push-3 equal" style="height: 999px;"> <div class="block"> <div id="mainbody"> <!-- Body content here --> </div> </div> </div> <div class="grid-2 equal" style="height: 999px;"> <div class="block"> <div id="sidebar-a"> <!-- Sidebar-a content here --> </div> </div> </div> <div class="grid-2 equal" style="height: 999px;"> <div class="block"> <div id="sidebar-b"> <!-- Sidebar-b content here --> </div> </div> </div> <div class="grid-2 equal" style="height: 999px;"> <div class="block"> <div id="sidebar-b"> <!-- Sidebar-c content here --> </div> </div> </div> </div> I want to add a different background color to each of my sidebars via CSS and when I code like: #mainbody { background : #fff; } #sidebar-a { background : #eee; } #sidebar-b { background : #ddd; } #sidebar-c { background : #ccc; } It is applying the background only to that specific class but that specific class is not of equal height. I actually need to apply to this <div class="grid-2 equal" style="height: 999px;"> div. Now the issue is that in this <div class="grid-6 push-3 equal" style="height: 999px;"> and class="grid-2 equal" style="height: 999px;"> the class names grid-6 and grid-2 are generated dynamically by my PHP of 960 Grid System and also the style="height: 999px; is generated by a jQuery script for Equal-Columns. What I want is to add a unique class name like this...... Look for a div with a class of .equal which has a child div with a class of .block and which further has a child div with an ID of sidebar-a. IF TRUE then add a class of .sidebar-a to the maindiv which has a class of .equal So that the result looks like this: <div class="grid-6 equal push-3 mainbody" style="height: 999px;"> <div class="grid-2 equal sidebar-a" style="height: 999px;"> <div class="grid-2 equal sidebar-b" style="height: 999px;"> <div class="grid-2 equal sidebar-c" style="height: 999px;"> Then I'll be able to style it like this: .mainbody { background : #fff; } .sidebar-a { background : #eee; } .sidebar-b { background : #ddd; } .sidebar-c { background : #ccc; } Hence I thought since I am anyway using jQuery in my Template, why not use it to deal with this issue. Please feel free to suggest a better way if you have something else in mind.

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  • UserID is returned as 0 and Token has the 3rd part missing for a Canvas Facebook Application!

    - by Nader Rahimizad
    Hi Guys, Do you know what could cause this as a return for a Facebook Canvas app. It works for most users of our site but some users, it generates this and i cant figure out what would cause this. The userID is returned as 0 and the Token seems to be missing something. there is no other way for the users to reach the site other than visiting the Facebook App page... Please let me know what i can do to prevent this from happening UserID: 0 Token: 104743107829|b8bbc20eac6127d8a9a85451490a0663 Quesrty String:signed_request=W13Y8eiSHTyyqBnyJjll8WngPFeQqabhVBkJaHnXYb4.eyJhbGdvcml0aG0iOiJITUFDLVNIQTI1NiIsImlzc3VlZF9hdCI6MTI5NDU5NjIwMywidXNlciI6eyJsb2NhbGUiOiJpdF9JVCIsImNvdW50cnkiOiJpdCJ9fQ

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  • Capturing clicks even when stopPropagation has been called (ie by 3rd party code)?

    - by josh
    I want to detect any click that happens on a page (to close a custom context menu). I'm using jQuery and trying to do $(document).click(function(){ ...close my context menu ... }); However, I'm using some code that calls evt.stopPropagation() in the click handlers for certain elements on the page, and those clicks aren't making it up to my top-level handler. Is there any way of capturing those clicks? Can be jQuery or not jQuery, as long as it works cross-browser.

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  • Distributed development staff needing a common IP range

    - by bakasan
    I work on a development staff that is geographically distributed, mostly all throughout the state of CA, but several key members also must travel frequently. We rely quite heavily on a 3rd party provider API for a great deal of our subsystems (can't get into who it is or what they do). The 3rd party however is quite stringent on network access and have no notion of a development sandbox. Access is restricted to 2, 3 IP numbers and that's about it. Once we account for our production servers, that leaves us with an IP or two to spare for our dev team--which is still problematic as people's home IP changes, people travel, we have more than 2 devs, etc. Wide IP blocks are not permitted by the 3rd party. Nor will they allow dynamic DNS type services. There is no simple console to swap IPs on the fly either (e.g. if a dev's IP at home changes or they are on the road). As none of us are deep network experts, I'm wondering what our viable options are? Are there such things as 3rd party hosts to VPNs? Generally I think of a VPN as a mechanism to gain access to a home office, but the notion would be a 3rd party VPN that we'd all connect to and we'd register this as an IP origin w/ our 3rd party. We've considered using Amazon EC2 to effectively host a dev environment for each dev and using that to connect. Amazon only gives you so many static IPs however (I believe 5?) so this would only be a stop gap solution until our team size out strips our IP count at Amazon. Those were the only viable thoughts that I had, but again, I'm far from a networking guy. Tried searching for similar threads, but I'm not even sure I know the right vernacular to look around for.

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  • Using R to Analyze G1GC Log Files

    - by user12620111
    Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { 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  Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

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  • JÖN JÖN JÖN!!! Oracle BI EE 11g Launch júliusban

    - by Fekete Zoltán
    A bejelentésre már nem kell sokat várni. Minden rajongó mélyet lélegezhet. JÖN JÖN JÖN az Oracle Business Intelligence Enterprise Edition 11g! Az Oracle INFORMATION INDEPTH NEWSLETTERS, Enterprise Performance Management and Business Intelligence Edition, June 2010 számában is olvashatunk a témáról: Oracle Readies for Oracle Business Intelligence Enterprise Edition 11g Launch . Ki tudja pontosan megmondani, hányat kell addig aludni a bejelentésig? :) A válaszokat comment formájában kérem! Mind funkciókban, mind külalakban és használhatóságban nagy lépés lesz az új verzió. A bejelentés: London: Oracle Business Intelligence Enterprise Edition 11g Launch Miért is NAGY UGRÁS ez? Még visszatérek a témára. Addig is várom a kommenteket.

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