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  • How does jQuery store data with .data()?

    - by TK
    I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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  • Load-balancer options

    - by toolkit
    I am looking at a number of possible options for load-balancing. So far, I am constrained to the following options: DNS server load-balancer, balancing to a cluster of tomcat servers, with terracotta for session replication. Pros - don't have to buy new kit. Cons - DNS lb can keep directing to a broken server. Hardware load-balancer, direct to cluster of tomcat servers. Pros - could have second box for failover lb. Cons - expense. Apache server load-balancer. Pros - apache's lb polls for broken servers. Cons - apache server is single point of failure, plus need to buy another server. Are there any other options I should consider? Thanks. Update: Thanks for all the answers so far +1's all round. Not accepting an answer yet, to keep more ideas coming.

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  • Performance of ClearCase servers on VMs?

    - by Garen
    Where I work, we are in need of upgrading our ClearCase servers and it's been proposed that we move them into a new (yet-to-be-deployed) VMmare system. In the past I've not noticed a significant problem with performance with most applications when running in VMs, but given that ClearCase "speed" (i.e. dynamic-view response times) is so latency sensitive I am concerned that this will not be a good idea. VMWare has numerous white-papers detailing performance related issues based on network traffic patterns that re-inforces my hypothesis, but nothing particularly concrete for this particular use case that I can see. What I can find are various forum posts online, but which are somewhat dated, e.g.: ClearCase clients are supported on VMWare, but not for performance issues. I would never put a production server on VM. It will work but will be slower. The more complex the slower it gets. accessing or building from a local snapshot view will be the fastest, building in a remote VM stored dynamic view using clearmake will be painful..... VMWare is best used for test environments (via http://www.cmcrossroads.com/forums?func=view&catid=31&id=44094&limit=10&start=10) and: VMware + ClearCase = works but SLUGGISH!!!!!! (windows)(not for production environment) My company tried to mandate that all new apps or app upgrades needed to be on/moved VMware instances. The VMware instance could not handle the demands of ClearCase. (come to find out that I was sharing a box with a database server) Will you know what else would be on that box besides ClearCase? Karl (via http://www.cmcrossroads.com/forums?func=view&id=44094&catid=31) and: ... are still finding we can't get the performance using dynamic views to below 2.5 times that of a physical machine. Interestingly, speaking to a few people with much VMWare experience and indeed from running builds, we are finding that typically, VMWare doesn't take that much longer for most applications and about 10-20% longer has been quoted. (via http://www.cmcrossroads.com/forums?func=view&catid=31&id=44094&limit=10&start=10) Which brings me to the more direct question: Does anyone have any more recent experience with ClearCase servers on VMware (if not any specific, relevant performance advice)?

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  • Load balance incoming traffic

    - by justin
    Dear All Please I have the following scenario. 3 servers voip / mail / terminal one load balancing router 2 internet connections (static ip`s) My concern is to load balance incoming traffic since the outgoing traffic is being taking care by the load balancing router. For instance all offices connect to the mail server via the internet same for voip and terminal services. The mail and voip clients are set up with one of the static ip`s and the router forwards the request to the appropriate server. But obviously like this there is no fail over nor load balancing cause all requests are being directed to one internet connection. Anyone has a suggestion was thing of a dns server, does this make sens ? or maybe a hosted option ? Thanks Justin

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  • Performance Tuning a High-Load Apache Server

    - by futureal
    I am looking to understand some server performance problems I am seeing with a (for us) heavily loaded web server. The environment is as follows: Debian Lenny (all stable packages + patched to security updates) Apache 2.2.9 PHP 5.2.6 Amazon EC2 large instance The behavior we're seeing is that the web typically feels responsive, but with a slight delay to begin handling a request -- sometimes a fraction of a second, sometimes 2-3 seconds in our peak usage times. The actual load on the server is being reported as very high -- often 10.xx or 20.xx as reported by top. Further, running other things on the server during these times (even vi) is very slow, so the load is definitely up there. Oddly enough Apache remains very responsive, other than that initial delay. We have Apache configured as follows, using prefork: StartServers 5 MinSpareServers 5 MaxSpareServers 10 MaxClients 150 MaxRequestsPerChild 0 And KeepAlive as: KeepAlive On MaxKeepAliveRequests 100 KeepAliveTimeout 5 Looking at the server-status page, even at these times of heavy load we are rarely hitting the client cap, usually serving between 80-100 requests and many of those in the keepalive state. That tells me to rule out the initial request slowness as "waiting for a handler" but I may be wrong. Amazon's CloudWatch monitoring tells me that even when our OS is reporting a load of 15, our instance CPU utilization is between 75-80%. Example output from top: top - 15:47:06 up 31 days, 1:38, 8 users, load average: 11.46, 7.10, 6.56 Tasks: 221 total, 28 running, 193 sleeping, 0 stopped, 0 zombie Cpu(s): 66.9%us, 22.1%sy, 0.0%ni, 2.6%id, 3.1%wa, 0.0%hi, 0.7%si, 4.5%st Mem: 7871900k total, 7850624k used, 21276k free, 68728k buffers Swap: 0k total, 0k used, 0k free, 3750664k cached The majority of the processes look like: 24720 www-data 15 0 202m 26m 4412 S 9 0.3 0:02.97 apache2 24530 www-data 15 0 212m 35m 4544 S 7 0.5 0:03.05 apache2 24846 www-data 15 0 209m 33m 4420 S 7 0.4 0:01.03 apache2 24083 www-data 15 0 211m 35m 4484 S 7 0.5 0:07.14 apache2 24615 www-data 15 0 212m 35m 4404 S 7 0.5 0:02.89 apache2 Example output from vmstat at the same time as the above: procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu---- r b swpd free buff cache si so bi bo in cs us sy id wa 8 0 0 215084 68908 3774864 0 0 154 228 5 7 32 12 42 9 6 21 0 198948 68936 3775740 0 0 676 2363 4022 1047 56 16 9 15 23 0 0 169460 68936 3776356 0 0 432 1372 3762 835 76 21 0 0 23 1 0 140412 68936 3776648 0 0 280 0 3157 827 70 25 0 0 20 1 0 115892 68936 3776792 0 0 188 8 2802 532 68 24 0 0 6 1 0 133368 68936 3777780 0 0 752 71 3501 878 67 29 0 1 0 1 0 146656 68944 3778064 0 0 308 2052 3312 850 38 17 19 24 2 0 0 202104 68952 3778140 0 0 28 90 2617 700 44 13 33 5 9 0 0 188960 68956 3778200 0 0 8 0 2226 475 59 17 6 2 3 0 0 166364 68956 3778252 0 0 0 21 2288 386 65 19 1 0 And finally, output from Apache's server-status: Server uptime: 31 days 2 hours 18 minutes 31 seconds Total accesses: 60102946 - Total Traffic: 974.5 GB CPU Usage: u209.62 s75.19 cu0 cs0 - .0106% CPU load 22.4 requests/sec - 380.3 kB/second - 17.0 kB/request 107 requests currently being processed, 6 idle workers C.KKKW..KWWKKWKW.KKKCKK..KKK.KKKK.KK._WK.K.K.KKKKK.K.R.KK..C.C.K K.C.K..WK_K..KKW_CK.WK..W.KKKWKCKCKW.W_KKKKK.KKWKKKW._KKK.CKK... KK_KWKKKWKCKCWKK.KKKCK.......................................... ................................................................ From my limited experience I draw the following conclusions/questions: We may be allowing far too many KeepAlive requests I do see some time spent waiting for IO in the vmstat although not consistently and not a lot (I think?) so I am not sure this is a big concern or not, I am less experienced with vmstat Also in vmstat, I see in some iterations a number of processes waiting to be served, which is what I am attributing the initial page load delay on our web server to, possibly erroneously We serve a mixture of static content (75% or higher) and script content, and the script content is often fairly processor intensive, so finding the right balance between the two is important; long term we want to move statics elsewhere to optimize both servers but our software is not ready for that today I am happy to provide additional information if anybody has any ideas, the other note is that this is a high-availability production installation so I am wary of making tweak after tweak, and is why I haven't played with things like the KeepAlive value myself yet.

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  • How to enable caching on Apache2 (using as load balancer)

    - by csl
    I'm using Apache 2 as my load balancer (mod_jk). I've 2 Tomcat servers behind my load balancer. What I'm trying to do is to enable caching of my static pages in my load balancer using mod_cache but nothing seems to be working. I confirmed this by creating a simple JSP page that prints out current date time and I always get the latest date time (indicating that the JSP page is not cached). OS: Ubuntu

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  • Perform action based on load avg

    - by sfx
    I'm running some web applications on an debian server and have to struggle with ddos attacks sometimes. It's eating up all my resources and I can't ssh anymore into the server. An idea was to drop all connections if the load avg is too high, so there are still resources for me and accept new connections if the load avg is low enough. Since this has to work under heavy load I'm afraid a cronjob wouldn't be fast enough or take too much resources. tl;dr: Is there a way to configure the behavior if the load avg is above a specific threshold?

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  • No apparent reason for high load average

    - by Oz.
    We have several web servers running on Amazon (ec2) c1.xlarge, over Amazon AMI. The servers are duplicates of each other, running the exact same hardware and software. Each server spec is: 7 GB of memory 20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each) 1690 GB of instance storage 64-bit platform I/O Performance: High API name: c1.xlarge A couple of weeks ago we have run a yum upgrade on one of the servers. Starting on this upgrade the upgraded server started showing a high load average. Needless to say, we did not update the other servers and we can not do so until we understand the reason for this behavior. The strange thing is that when we compare the servers using top or iostat, we can not find the reason for the high load. Note that we have moved traffic from the "problematic" server to the others, which have made the "problematic" server less crowded in terms of requests, and still his load is higher. Do you have any idea what could it be, or where else can we check? Many thanks for the help! Oz. # # proper server # w command # 00:42:26 up 2 days, 19:54, 2 users, load average: 0.41, 0.48, 0.49 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT pts/1 82.80.137.29 00:28 14:05 0.01s 0.01s -bash pts/2 82.80.137.29 00:38 0.00s 0.02s 0.00s w # # proper server # iostat command # Linux 3.2.12-3.2.4.amzn1.x86_64 _x86_64_ (8 CPU) avg-cpu: %user %nice %system %iowait %steal %idle 9.03 0.02 4.26 0.17 0.13 86.39 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn xvdap1 1.63 1.50 55.00 367236 13444008 xvdfp1 4.41 45.93 70.48 11227226 17228552 xvdfp2 2.61 2.01 59.81 491890 14620104 xvdfp3 8.16 14.47 94.23 3536522 23034376 xvdfp4 0.98 0.79 45.86 192818 11209784 # # problematic server # w command # 00:43:26 up 2 days, 21:52, 2 users, load average: 1.35, 1.10, 1.17 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT pts/0 82.80.137.29 00:28 15:04 0.02s 0.02s -bash pts/1 82.80.137.29 00:38 0.00s 0.05s 0.00s w # # problematic server # iostat command # Linux 3.2.20-1.29.6.amzn1.x86_64 _x86_64_ (8 CPU) avg-cpu: %user %nice %system %iowait %steal %idle 7.97 0.04 3.43 0.19 0.07 88.30 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn xvdap1 2.10 1.49 76.54 374660 19253592 xvdfp1 5.64 40.98 85.92 10308946 21612112 xvdfp2 3.97 4.32 93.18 1087090 23439488 xvdfp3 10.87 30.30 115.14 7622474 28961720 xvdfp4 1.12 0.28 65.54 71034 16487112

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  • nginx proxy pass redirect through load balancer

    - by Brian
    I have several backend webservers that are load-balanced using LVS. These machines have only internal non-routable IPs on them. The load-balancer is the only machine with an external IP. This setup works great. I would like to add another webserver for image serving, but it will not be part of the load-balanced pool. Is it possible to proxy pass from the load-balanced web servers to the image server and have the response redirected to the client? Client--external LB--internal web server--internal image server I've gotten proxy pass working when I remove the LB from the equation, but no luck when trying to use it.

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  • FTP Load Balancer on EC2

    - by inakiabt
    I need an EC2 instance to balance all incoming FTP connections to a list of FTP servers (EC2 instances too). This list will be changed dynamically due to the load of the FTP servers (launch a new FTP server when the FTP servers are overloaded or shutdown a FTP server when the load is low). What you recommend? a FTP proxy? DNS server? Load balancer? Note: The FTP servers must support Passive Mode

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  • nginx proxy pass redirect through load balancer

    - by Brian
    I have several backend webservers that are load-balanced using LVS. These machines have only internal non-routable IPs on them. The load-balancer is the only machine with an external IP. This setup works great. I would like to add another webserver for image serving, but it will not be part of the load-balanced pool. Is it possible to proxy pass from the load-balanced web servers to the image server and have the response redirected to the client? Client--external LB--internal web server--internal image server I've gotten proxy pass working when I remove the LB from the equation, but no luck when trying to use it.

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  • FTP Load Balancer

    - by inakiabt
    I need an EC2 instance to balance all incoming FTP connections to a list of FTP servers (EC2 instances too). This list will be changed dynamically due to the load of the FTP servers (launch a new FTP server when the FTP servers are overloaded or shutdown a FTP server when the load is low). What you recommend? a FTP proxy? DNS server? Load balancer? Note: The FTP servers must support Passive Mode

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  • Load Balancing Linux Web Services and Change Config Without Restart

    - by Eric J.
    What options are available to load balance web service traffic on Linux with the ability to add or remove servers from the server pool without restarting the load balancer? This post: http://serverfault.com/questions/71437/mod-proxy-change-without-restart looks like a very promising way to switch between two servers, but I don't know enough about mod_proxy and mod_rewrite to understand how/if I can use an external file to specify the BalancerMember entries for a section. Are there other open source load balancers that support reconfiguration without restart?

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  • Apache load balancer with https real servers and client certificates

    - by Jack Scheible
    Our network requirements state that ALL network traffic must be encrypted. The network configuration looks like this: ------------ /-- https --> | server 1 | / ------------ |------------| |---------------|/ ------------ | Client | --- https --> | Load Balancer | ---- https --> | server 2 | |------------| |---------------|\ ------------ \ ------------ \-- https --> | server 3 | ------------ And it has to pass client certificates. I've got a config that can do load balancing with in-the-clear real servers: <VirtualHost *:8666> DocumentRoot "/usr/local/apache/ssl_html" ServerName vmbigip1 ServerAdmin [email protected] DirectoryIndex index.html <Proxy *> Order deny,allow Allow from all </Proxy> SSLEngine on SSLProxyEngine On SSLCertificateFile /usr/local/apache/conf/server.crt SSLCertificateKeyFile /usr/local/apache/conf/server.key <Proxy balancer://mycluster> BalancerMember http://1.2.3.1:80 BalancerMember http://1.2.3.2:80 # technically we aren't blocking anyone, but could here Order Deny,Allow Deny from none Allow from all # Load Balancer Settings # A simple Round Robin load balancer. ProxySet lbmethod=byrequests </Proxy> # balancer-manager # This tool is built into the mod_proxy_balancer module allows you # to do simple mods to the balanced group via a gui web interface. <Location /balancer-manager> SetHandler balancer-manager Order deny,allow Allow from all </Location> ProxyRequests Off ProxyPreserveHost On # Point of Balance # Allows you to explicitly name the location in the site to be # balanced, here we will balance "/" or everything in the site. ProxyPass /balancer-manager ! ProxyPass / balancer://mycluster/ stickysession=JSESSIONID </VirtualHost> What I need is for the servers in my load balancer to be BalancerMember https://1.2.3.1:443 BalancerMember https://1.2.3.2:443 But that does not work. I get SSL negotiation errors. Even when I do get that to work, I will need to pass client certificates. Any help would be appreciated.

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  • Load balancers, multiple data centers and url based routing

    - by kunkunur
    There is one data center - dc1. There is a business need to setup another data center - dc2 in another geography and there might be more in the future say dc3. Within the data center dc1: There are two web servers say WS1 and WS2. These two webservers do not share anything currently. There isnt any necessity foreseen to have more webservers within each dc. dc1 also has a local load balancer which has been setup with session stickiness. So if a user say u1 lands on dc1 and if the load balancer decides to route his first request to WS1 then from there on all u1's requests will get routed to WS1. Local load balancer and webservers are invisible to the user. Local load balancer listens to the traffic on a virtual ip which is assigned to the virtual cluster of webservers ws1 and ws2. Virtual ip is the ip to which the host name is resolved to in the DNS. There are no client specific subdomains as of now instead there is a client specific url(context). ex: www.example.com/client1 and www.example.com/client2. Given above when dc2 is onboarded I want to route the traffic between dc1 and dc2 based on the client. The options that I have found so far are. Have client specific subdomains e.g. client1.example.com and client2.example.com and assign each of them with the virtual ip of the data center to which I want to route them. or Assign www.example.com and www1.example.com to first dc i.e. dc1 and assign www2.example.com to dc2. All requests will first get routed to dc1 where WS1 and WS2 will redirect the user to www1.example.com or www2.example.com based on whether the url ends with /client1 or /client2. I need help in the following If I setup a global load balancer between dc1 and dc2 do I have any alternative solutions. That is, can a global load balancer route the traffic based on the url ? Are there drawbacks to subdomain based solutions compared to www1 solution? With www1 solution I am worried that it creates a dependency on dc1 atleast for the first request and the user will see that he is getting redirected to a different url.

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  • What other ways can I load balance EC2 servers without using Elastic Load Balancing?

    - by undefined
    I have a web application that consists of a web server managed by a web hosting firm, a set of EC2 instances in amazons cloud and a MySQL database (hosted on the webserver). MySQL is behind a firewall and is set to allow access from Localhost and from a single IP address which is an Amazon Elastic IP address that is attached to the EC2 instance I have been running up to now. The problem is that I want to look at my scaling up and load balancing strategy for my EC2 instance. To this end I have been investigating the Elastic Load Balancers and Autoscaling tools that Amazon provides and have managed to set this up fine but for one thing - connecting to the MySQL database running on my webserver. I realised (thanks to answers on Serverfault) that I needed to check firewall settings and add the IP address for the load balancer, however Elastic Load Balancers provide you with a DNS name, not an IP address and infact the IP addresses change over time so this will not work. I have been told by the company hosting the database that the way the firewall works is to look up the IP address of the DNS name and store the IP rather than the DNS name. so basically this will not work and the only way to allow access would be to open up the SQL port to allow access from anyone! Is this a viable idea? Should I look at moving my database into the cloud? Is there another firewall that the server company can use? Should I find another way of load balancing (if so what?) tricky one eh? any help appreciated!

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  • Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

    Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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  • SQLAuthority News – Fast Track Data Warehouse 3.0 Reference Guide

    - by pinaldave
    http://msdn.microsoft.com/en-us/library/gg605238.aspx I am very excited that Fast Track Data Warehouse 3.0 reference guide has been announced. As a consultant I have always enjoyed working with Fast Track Data Warehouse project as it truly expresses the potential of the SQL Server Engine. Here is few details of the enhancement of the Fast Track Data Warehouse 3.0 reference architecture. The SQL Server Fast Track Data Warehouse initiative provides a basic methodology and concrete examples for the deployment of balanced hardware and database configuration for a data warehousing workload. Balance is measured across the key components of a SQL Server installation; storage, server, application settings, and configuration settings for each component are evaluated. Description Note FTDW 3.0 Architecture Basic component architecture for FT 3.0 based systems. New Memory Guidelines Minimum and maximum tested memory configurations by server socket count. Additional Startup Options Notes for T-834 and setting for Lock Pages in Memory. Storage Configuration RAID1+0 now standard (RAID1 was used in FT 2.0). Evaluating Fragmentation Query provided for evaluating logical fragmentation. Loading Data Additional options for CI table loads. MCR Additional detail and explanation of FTDW MCR Rating. Read white paper on fast track data warehousing. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • Importing data from text file to specific columns using BULK INSERT

    - by Dinesh Asanka
    Bulk insert is much faster than using other techniques such as  SSIS. However, when you are using bulk insert you can’t insert to specific columns. If, for example, there are five columns in a table you should have five values for each record in the text file you are importing from. This is an issue when you are expecting default values to be inserted into tables. Let us say you have table as below: In this table, you are expecting ID, Status and CreatedDate to be updated automatically, so your text file may only have   FirstName  LastName  values as below: Dinesh,Asanka Saman,Liyanage Ruwan,Silva Susantha,Bathige Jude,Peires Sanjeewa,Jayawickrama If you use bulk insert to this table like follows, You will be returned an error: Bulk load data conversion error (type mismatch or invalid character for the specified codepage) for row 1, column 1 (ID). To avoid this you will need to create a view with the columns you are expecting to fill and use bulk insert against it. If you check the table now, you will see table with values in the text file and the default values.

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  • Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

    Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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  • extjs data store load data on fly

    - by CKeven
    I'm trying to create a data store that will load the data schema and records on fly. Here is the current code i have and I'm not sure how to setup the array reader properly since i don't have the schema before query returns. ds = new Ext.data.Store({ url: 'http://10.10.97.83/cgi-bin/cgiip.exe/WService=wsdev/majax/jsbrdgx.p', baseParams: { cr: Ext.util.JSON.encode(omgtobxParms) }, reader: new Ext.data.ArrayReader({ //root:data.value.records }, col_names) }); {"name": "tmp_buy_book", "schema": [ { "name": "a", "type": "C"}, { "name": "b", "type": "C"} "records": [["1", ""], ["1",""]]}

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  • Big Data – Buzz Words: What is MapReduce – Day 7 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL Developer Data Modeler v3.3 Early Adopter: Search

    - by thatjeffsmith
    photo: Stuck in Customs via photopin cc The next version of Oracle SQL Developer Data Modeler is now available as an Early Adopter (read, beta) release. There are many new major feature enhancements to talk about, but today’s focus will be on the brand new Search mechanism. Data, data, data – SO MUCH data Google has made countless billions of dollars around a very efficient and intelligent search business. People have become accustomed to having their data accessible AND searchable. Data models can have thousands of entities or tables, each having dozens of attributes or columns. Imagine how hard it could be to find what you’re looking for here. This is the challenge we have tackled head-on in v3.3. Same location as the Search toolbar in Oracle SQL Developer (and most web browsers) Here’s how it works: Search as you type – wicked fast as the entire model is loaded into memory Supports regular expressions (regex) Results loaded to a new panel below Search across designs, models Search EVERYTHING, or filter by type Save your frequent searches Save your search results as a report Open common properties of object in search results and edit basic properties on-the-fly Want to just watch the video? We have a new Oracle Learning Library resource available now which introduces the new and improved Search mechanism in SQL Developer Data Modeler. Go watch the video and then come back. Some Screenshots This will be a pretty easy feature to pick up. Search is intuitive – we’ve already learned how to do search. Now we just have a better interface for it in SQL Developer Data Modeler. But just in case you need a couple of pointers… The SYS data dictionary in model form with Search Results If I type ‘translation’ in the search dialog, then the results will come up as hits are ‘resolved.’ By default, everything is searched, although I can filter the results after-the-fact. You can see where the search finds a match in the ‘Content’ column Save the Results as a Report If you limit the search results to a category and a model, then you can save the results as a report. All of the usual suspects You can optionally include the search string, which displays in the top of of the report as ‘PATTERN.’ You can save you common reporting setups as a template and reuse those as well. Here’s a sample HTML report: Yes, I like to search my search results report! Two More Ways to Search You can search ‘in context’ by opening the ‘Find’ dialog from an active design. You can do this using the ‘Search’ toolbar button or from a model context menu. Searching a specific model Instead of bringing up the old modal Find dialog, you now get to use the new and improved Search panel. Notice there’s no ‘Model’ drop-down to select and that the active Search form is now in the Search panel versus the search toolbar up top. What else is new in SQL Developer Data Modeler version 3.3? All kinds of goodies. You can send your model to Excel for quick edits/reviews and suck the changes back into your model, you can share objects between models, and much much more. You’ll find new videos and blog posts on the subject in the new few days and weeks. Enjoy! If you have any feedback or want to report bugs, please visit our forums.

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  • Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Squid on windows loadbalancing only to one server

    - by Martin L.
    After thousands of googles and trying days i cant get the load balancer/failover in squid on windows to work. Iam using squid 2.7. My webservers are 2 single NIC lighttpd and one dual nic lighttpd. server1 in this example is running squid on port 80 and lighttpd on port 8080 (just to test) Requirements: All 3 webservers running lighttpd should be balanced two option for load balancing: Best would be if server1 is busy server2 takes over, if server2 is busy server3 takes over, etc.. Round robin style evenly distributed load. Eg server1 takes first call, server2 second etc.. All requests should be treated the same way (no url rewriting or so on) Sent host headers have to be redirected to every server as http host header, speaking of "server1", "server1.company.internal" and "10.211.1.1". My approach: acl all src all acl manager proto cache_object http_port 80 accel defaultsite=server1.company.internal vhost #reverse proxy entries cache_peer 10.211.2.1 parent 8080 0 no-query originserver round-robin login=PASS name=server1_nic1 cache_peer 10.211.1.2 parent 80 0 no-query originserver round-robin login=PASS name=server2_nic1 cache_peer 10.211.2.3 parent 8080 0 no-query originserver round-robin login=PASS name=server3_nic1 cache_peer 10.211.2.4 parent 8080 0 no-query originserver round-robin login=PASS name=server3_nic2 #decl of names of squid host acl registered_name_hostdomain dstdomain server1.company.internal acl registered_name_host dstdomain server1 #ip of squid host acl registered_name_ip dstdomain 10.211.2.1 # access: redirects the correct squid hostname http_access allow registered_name_hostdomain http_access allow registered_name_host http_access allow registered_name_ip http_access deny all cache_peer_access server1_nic1 allow registered_name_hostdomain cache_peer_access server1_nic1 allow registered_name_host cache_peer_access server1_nic1 allow registered_name_ip cache_peer_access server2_nic1 allow registered_name_hostdomain cache_peer_access server2_nic1 allow registered_name_host cache_peer_access server2_nic1 allow registered_name_ip cache_peer_access server3_nic1 allow registered_name_hostdomain cache_peer_access server3_nic1 allow registered_name_host cache_peer_access server3_nic1 allow registered_name_ip cache_peer_access server3_nic2 allow registered_name_hostdomain cache_peer_access server3_nic2 allow registered_name_host cache_peer_access server3_nic2 allow registered_name_ip cache_peer_access server1_nic1 deny all cache_peer_access server2_nic1 deny all cache_peer_access server3_nic1 deny all cache_peer_access server3_nic2 deny all never_direct allow all Problems: Load balancer does not load balance other than to first server. Only if the first server is killed in any way the second will take over. I have seen the others working at some point, but definitely not as the intended load balancing described above. If the cache_peer_access is not defined sometimes the wrong hostname is sent to the backend webserver and this always depends on the defaultsite= parameter. Probably because the host header on the request to squid is not set and its replaced by defaultsite. Leaving out defaultsite didnt solve the problem. The only workaround i found for this is the current approach with cache_peer_access. Questions: Does the cache_peer_access influence the round-robin? Is there a better workaround to pass the host header to the backed webservers? Which parameters do increase the speed of load balancing or does anyone have a better approach? -Martin

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