Search Results

Search found 10 results on 1 pages for 'ketchup'.

Page 1/1 | 1 

  • Jquery Ketchup Form Validation not initializing required fields

    - by Aaron R
    We are trying to implement jquery ketchup demos.usejquery.com/ketchup-plugin/ and use required fields for the name, email and phone fields we have included all the markup and I think I have it setup properly but the form fields are not validating... You can see my sample here... thx for any assistance I have been staring at this for hours... http://c5.dealercontrol.net/service/service-appointment/

    Read the article

  • How can I get jQuery validation plugin Ketchup to stop an Ajax form submission when validation fails?

    - by Marshall Sontag
    I'm using Ruby on Rails, Formtastic gem, jQuery and ketchup to validate my form. I'm submitting the form created by Formtastic inside a modal box using ajax: <% semantic_form_remote_for @contact_form, :url => '/request/contact' do |f| %> I have a validation plugin verifying the fields on the form: $(document).ready(function() { $("#new_contact_form").ketchup(); }); The problem is that semantic_form_remote_for generates an onSubmit ajax request that the jQuery validation plugins won't prevent, since it's not a normal form submission. One question on stackoverflow suggests using :condition on the remote form declaration to fire a javascript function, but I can't do that since I'm not using a function, but rather relying on a jQuery handler. I also tried putting ketchup within a submit event handler: $(document).ready(function() { $("#new_contact_form").submit(function() { $('#new_contact_form').ketchup(); }); }); No luck. Form still submits. I also tried using the beforeSend option of jQuery.ajax: $(document).ready(function() { jQuery.ajax( { beforeSend: function(){ $('#new_contact_form').ketchup(); } }); }); Validation fires off, but form is still submitted. I switched to jQuery Validation plugin just to see if it was due to some limitation in Ketchup. It turns out that Validation has a submitHandler option: $(document).ready(function() { $('#new_contact_form').validate({ submitHandler: function(form) { jQuery.ajax({ data:jQuery.param(jQuery('#new_contact_form').serializeArray()), dataType:'script', type:'post', url:'/request/contact' }); return false; } }); }); This works when I use a regular semantic_form_for instead of semantic_form_remote_for, but alas, I would rather use Ketchup. Is Ketchup just woefully lacking? Am I forced to use jQuery Validation?

    Read the article

  • jquery lib conflicts

    - by Indranil Mutsuddy
    Hello friends, I am tryin to use jgrowl and jquery validation in the same page and each time either of them works. I ve gone through the jQuery.nonConflict but coulnt solve the problem my .cs code for jgrowl is string js = "$.jGrowl(' INVALID MEMBER ID, KINDLY TRY AGAIN ');"; Page.ClientScript.RegisterStartupScript(typeof(string), "jgrowlwarn", js, true); and in .aspx is the following libs <script src="../jquery.jgrowl.js" type="text/javascript"></script> <link href="../jquery.jgrowl.css" rel="stylesheet" type="text/css" /> whereas for validations the followin are the codes in .aspx page <link href="../ketchup.jquery.ketchup.css" rel="stylesheet" type="text/css" /> <script src="../JS/ketchup.jquery.min.js" type="text/javascript"></script> <script src="../JS/ketchup.jquery.ketchup.js" type="text/javascript"></script> <script src="../JS/ketchup.jquery.ketchup.messages.js" type="text/javascript"></script> <script src="../JS/ketchup.jquery.ketchup.validations.basic.js" type="text/javascript"></script> <script type ="text/javascript"> $(document).ready(function($) { $('#example1').ketchup(); }); </script> How to make this work? please help. Thanking you, Indranil

    Read the article

  • User sumbitted top 5 and sort by popularity

    - by Bundy
    Hi, Database setup (MySQL) table: top_fives id, uid, first, second, third, fourth, fifth, creation_date 1, 1, cheese, eggs, ham, bacon, ketchup, 2010-03-17 2, 2, mayonaise, cheese, ketchup, eggs, bacon, 2010-03-17 Users can submit their top 5 of a certain subject. Now I would like a summary of the top fives ordered by popularity. Each column has it's own point value. column 'first' is rewarded 5 points, 'second' four points, 'third' three points, and so on... So, in my example it should be something like this: 1 Cheese (9 points = 5 + 4 -> 1 time in 'first' column and 1 time in 'second' column) 2 Eggs (6 points) 3 Mayonaise (5 points) 4 Ketchup (4 points) 5 Bacon (3 points) 6 Ham (3 points) What would be the easiest solution (PHP) for this kind of situation? Thanks in advance

    Read the article

  • Matching digits in Notepad++ extended search mode

    - by ketchup
    Notepad++'s manual is rather vague on the special character for numerical used in extended search mode. It says: \d### - Decimal value (between 000 and 255) but literally entering "\d###" doesn't match anything. What I am trying to do is to replace if VarA == 12 VarB = 1 with if VarA == 12 Var12=1 VarB=1

    Read the article

  • Back Up to Tape the Way You Shop For Groceries

    - by rickramsey
    Imagine if this was how you shopped for groceries: From the end of the aisle sprint to the point where you reach the ketchup. Pull a bottle from the shelf and yell at the top of your lungs, “Got it!” Sprint back to the end of the aisle. Start again and sprint down the same aisle to the mustard, pull a bottle from the shelf and again yell for the whole store to hear, “Got it!” Sprint back to the end of the aisle. Repeat this procedure for every item you need in the aisle. Proceed to the next aisle and follow the same steps for the list of items you need from that aisle. Sounds ridiculous, doesn’t it? Not only is it horribly inefficient, it’s exhausting and can lead to wear out failures on your grocery cart, or worse, yourself. This is essentially how NetApp and some other applications write NDMP backups to tape. In the analogy, the ketchup and mustard are the files to be written, yelling “Got it!” is the equivalent of a sync mark at the end of a file, and the sprint back to the end of an aisle is the process most commonly called a “backhitch” where the drive has to back up on a tape to start writing again. Writing to tape in this way results in very slow tape drive performance and imposes unnecessary wear on the tape drive and the media, especially when writing small files. The good news is not all tape drives behave this way when writing small files. Unlike midrange LTO drives, Oracle’s StorageTek T10000D tape drive is designed to handle this scenario efficiently. The difference between the two drive types is that the T10000D drive gives you the ability to write files in a NetApp NDMP backup environment the way you would normally shop for groceries. With grocery shopping, you essentially stream through aisles picking up items as you go, and then after checking out, yell, “Got it!”, though you might do that last step silently. With the T10000D, it has a feature called the Tape Application Accelerator, which prevents the drive from having to stop after each file is written to notify NetApp or another application that the write was successful. When enabled in the T10000D tape drive, Tape Application Accelerator causes the tape drive to respond to tape mark and file sync commands differently than when disabled: A tape mark received by the tape drive is treated as a buffered tape mark. A file sync received by the tape drive is treated as a no op command. Since buffered tape marks and no op commands do not cause the tape drive to empty the contents of its buffer to tape and backhitch, the data is written to tape in significantly less time. Oracle has emulated NetApp environments with a number of different file sizes and found the following when comparing the T10000D with the Tape Application Accelerator enabled versus LTO6 tape drives. Notice how the T10000D is not only monumentally faster, but also remarkably consistent? In addition, the writing of the 50 GB of files is done without a single backhitch. The LTO6 drive, meanwhile, will perform as many as 3,800 backhitches! At the end of writing the entire set of files, the T10000D tape drive reports back to the application, in this case NetApp, that the write was successful via a tape mark. So if the Tape Application Accelerator dramatically improves performance and reliability, why wouldn’t you always have it enabled? The reason is because tape drive buffers are meant to be just temporary data repositories so in the event of a power loss, there could be data loss in certain environments for the files that resided in the buffer. Fortunately, we do have best practices depending on your environment to avoid this from happening. I highly recommend reading Maximizing Tape Performance with StorageTek T10000 Tape Drives (pdf) to decide which best practice is right for you. The white paper also digs deeper into the benefits of the Tape Application Accelerator. The white paper is free, and after downloading it you can decide for yourself whether you want to yell “Got it!” out loud or just silently to yourself. Customer Advisory Panel One final link: Oracle has started up a Customer Advisory Panel program to collect feedback from customers on their current experiences with Oracle products, as well as desires for future product development. If you would like to participate in the program, go to this link at oracle.com. photo taken on Idaho's Sacajewea Historic Biway by Rick Ramsey - Brian Zents Follow OTN on Blog | Facebook | Twitter | YouTube

    Read the article

  • Generalize, or Fix The Problem?

    - by Droogans
    Which of these two programmers is "better", from a managerial standpoint? The first programmer is Albert. You tell Al to make a system that will pass you the salt at the dinner table. He does it in less than a day. It works fine. The second programmer is Ben. Ben is told to make a program to pass the salt, and after two days, he's still working on it. It will save time in the long run...if you need pepper, ketchup, etc. There isn't any clear indication that there will be a need for this, but it's not improbable. Who's the better programmer to have working under you, as a manager?

    Read the article

  • Option Trading: Getting the most out of the event session options

    - by extended_events
    You can control different aspects of how an event session behaves by setting the event session options as part of the CREATE EVENT SESSION DDL. The default settings for the event session options are designed to handle most of the common event collection situations so I generally recommend that you just use the defaults. Like everything in the real world though, there are going to be a handful of “special cases” that require something different. This post focuses on identifying the special cases and the correct use of the options to accommodate those cases. There is a reason it’s called Default The default session options specify a total event buffer size of 4 MB with a 30 second latency. Translating this into human terms; this means that our default behavior is that the system will start processing events from the event buffer when we reach about 1.3 MB of events or after 30 seconds, which ever comes first. Aside: What’s up with the 1.3 MB, I thought you said the buffer was 4 MB?The Extended Events engine takes the total buffer size specified by MAX_MEMORY (4MB by default) and divides it into 3 equally sized buffers. This is done so that a session can be publishing events to one buffer while other buffers are being processed. There are always at least three buffers; how to get more than three is covered later. Using this configuration, the Extended Events engine can “keep up” with most event sessions on standard workloads. Why is this? The fact is that most events are small, really small; on the order of a couple hundred bytes. Even when you start considering events that carry dynamically sized data (eg. binary, text, etc.) or adding actions that collect additional data, the total size of the event is still likely to be pretty small. This means that each buffer can likely hold thousands of events before it has to be processed. When the event buffers are finally processed there is an economy of scale achieved since most targets support bulk processing of the events so they are processed at the buffer level rather than the individual event level. When all this is working together it’s more likely that a full buffer will be processed and put back into the ready queue before the remaining buffers (remember, there are at least three) are full. I know what you’re going to say: “My server is exceptional! My workload is so massive it defies categorization!” OK, maybe you weren’t going to say that exactly, but you were probably thinking it. The point is that there are situations that won’t be covered by the Default, but that’s a good place to start and this post assumes you’ve started there so that you have something to look at in order to determine if you do have a special case that needs different settings. So let’s get to the special cases… What event just fired?! How about now?! Now?! If you believe the commercial adage from Heinz Ketchup (Heinz Slow Good Ketchup ad on You Tube), some things are worth the wait. This is not a belief held by most DBAs, particularly DBAs who are looking for an answer to a troubleshooting question fast. If you’re one of these anxious DBAs, or maybe just a Program Manager doing a demo, then 30 seconds might be longer than you’re comfortable waiting. If you find yourself in this situation then consider changing the MAX_DISPATCH_LATENCY option for your event session. This option will force the event buffers to be processed based on your time schedule. This option only makes sense for the asynchronous targets since those are the ones where we allow events to build up in the event buffer – if you’re using one of the synchronous targets this option isn’t relevant. Avoid forgotten events by increasing your memory Have you ever had one of those days where you keep forgetting things? That can happen in Extended Events too; we call it dropped events. In order to optimizes for server performance and help ensure that the Extended Events doesn’t block the server if to drop events that can’t be published to a buffer because the buffer is full. You can determine if events are being dropped from a session by querying the dm_xe_sessions DMV and looking at the dropped_event_count field. Aside: Should you care if you’re dropping events?Maybe not – think about why you’re collecting data in the first place and whether you’re really going to miss a few dropped events. For example, if you’re collecting query duration stats over thousands of executions of a query it won’t make a huge difference to miss a couple executions. Use your best judgment. If you find that your session is dropping events it means that the event buffer is not large enough to handle the volume of events that are being published. There are two ways to address this problem. First, you could collect fewer events – examine you session to see if you are over collecting. Do you need all the actions you’ve specified? Could you apply a predicate to be more specific about when you fire the event? Assuming the session is defined correctly, the next option is to change the MAX_MEMORY option to a larger number. Picking the right event buffer size might take some trial and error, but a good place to start is with the number of dropped events compared to the number you’ve collected. Aside: There are three different behaviors for dropping events that you specify using the EVENT_RETENTION_MODE option. The default is to allow single event loss and you should stick with this setting since it is the best choice for keeping the impact on server performance low.You’ll be tempted to use the setting to not lose any events (NO_EVENT_LOSS) – resist this urge since it can result in blocking on the server. If you’re worried that you’re losing events you should be increasing your event buffer memory as described in this section. Some events are too big to fail A less common reason for dropping an event is when an event is so large that it can’t fit into the event buffer. Even though most events are going to be small, you might find a condition that occasionally generates a very large event. You can determine if your session is dropping large events by looking at the dm_xe_sessions DMV once again, this time check the largest_event_dropped_size. If this value is larger than the size of your event buffer [remember, the size of your event buffer, by default, is max_memory / 3] then you need a large event buffer. To specify a large event buffer you set the MAX_EVENT_SIZE option to a value large enough to fit the largest event dropped based on data from the DMV. When you set this option the Extended Events engine will create two buffers of this size to accommodate these large events. As an added bonus (no extra charge) the large event buffer will also be used to store normal events in the cases where the normal event buffers are all full and waiting to be processed. (Note: This is just a side-effect, not the intended use. If you’re dropping many normal events then you should increase your normal event buffer size.) Partitioning: moving your events to a sub-division Earlier I alluded to the fact that you can configure your event session to use more than the standard three event buffers – this is called partitioning and is controlled by the MEMORY_PARTITION_MODE option. The result of setting this option is fairly easy to explain, but knowing when to use it is a bit more art than science. First the science… You can configure partitioning in three ways: None, Per NUMA Node & Per CPU. This specifies the location where sets of event buffers are created with fairly obvious implication. There are rules we follow for sub-dividing the total memory (specified by MAX_MEMORY) between all the event buffers that are specific to the mode used: None: 3 buffers (fixed)Node: 3 * number_of_nodesCPU: 2.5 * number_of_cpus Here are some examples of what this means for different Node/CPU counts: Configuration None Node CPU 2 CPUs, 1 Node 3 buffers 3 buffers 5 buffers 6 CPUs, 2 Node 3 buffers 6 buffers 15 buffers 40 CPUs, 5 Nodes 3 buffers 15 buffers 100 buffers   Aside: Buffer size on multi-processor computersAs the number of Nodes or CPUs increases, the size of the event buffer gets smaller because the total memory is sub-divided into more pieces. The defaults will hold up to this for a while since each buffer set is holding events only from the Node or CPU that it is associated with, but at some point the buffers will get too small and you’ll either see events being dropped or you’ll get an error when you create your session because you’re below the minimum buffer size. Increase the MAX_MEMORY setting to an appropriate number for the configuration. The most likely reason to start partitioning is going to be related to performance. If you notice that running an event session is impacting the performance of your server beyond a reasonably expected level [Yes, there is a reasonably expected level of work required to collect events.] then partitioning might be an answer. Before you partition you might want to check a few other things: Is your event retention set to NO_EVENT_LOSS and causing blocking? (I told you not to do this.) Consider changing your event loss mode or increasing memory. Are you over collecting and causing more work than necessary? Consider adding predicates to events or removing unnecessary events and actions from your session. Are you writing the file target to the same slow disk that you use for TempDB and your other high activity databases? <kidding> <not really> It’s always worth considering the end to end picture – if you’re writing events to a file you can be impacted by I/O, network; all the usual stuff. Assuming you’ve ruled out the obvious (and not so obvious) issues, there are performance conditions that will be addressed by partitioning. For example, it’s possible to have a successful event session (eg. no dropped events) but still see a performance impact because you have many CPUs all attempting to write to the same free buffer and having to wait in line to finish their work. This is a case where partitioning would relieve the contention between the different CPUs and likely reduce the performance impact cause by the event session. There is no DMV you can check to find these conditions – sorry – that’s where the art comes in. This is  largely a matter of experimentation. On the bright side you probably won’t need to to worry about this level of detail all that often. The performance impact of Extended Events is significantly lower than what you may be used to with SQL Trace. You will likely only care about the impact if you are trying to set up a long running event session that will be part of your everyday workload – sessions used for short term troubleshooting will likely fall into the “reasonably expected impact” category. Hey buddy – I think you forgot something OK, there are two options I didn’t cover: STARTUP_STATE & TRACK_CAUSALITY. If you want your event sessions to start automatically when the server starts, set the STARTUP_STATE option to ON. (Now there is only one option I didn’t cover.) I’m going to leave causality for another post since it’s not really related to session behavior, it’s more about event analysis. - Mike Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

    Read the article

  • Option Trading: Getting the most out of the event session options

    - by extended_events
    You can control different aspects of how an event session behaves by setting the event session options as part of the CREATE EVENT SESSION DDL. The default settings for the event session options are designed to handle most of the common event collection situations so I generally recommend that you just use the defaults. Like everything in the real world though, there are going to be a handful of “special cases” that require something different. This post focuses on identifying the special cases and the correct use of the options to accommodate those cases. There is a reason it’s called Default The default session options specify a total event buffer size of 4 MB with a 30 second latency. Translating this into human terms; this means that our default behavior is that the system will start processing events from the event buffer when we reach about 1.3 MB of events or after 30 seconds, which ever comes first. Aside: What’s up with the 1.3 MB, I thought you said the buffer was 4 MB?The Extended Events engine takes the total buffer size specified by MAX_MEMORY (4MB by default) and divides it into 3 equally sized buffers. This is done so that a session can be publishing events to one buffer while other buffers are being processed. There are always at least three buffers; how to get more than three is covered later. Using this configuration, the Extended Events engine can “keep up” with most event sessions on standard workloads. Why is this? The fact is that most events are small, really small; on the order of a couple hundred bytes. Even when you start considering events that carry dynamically sized data (eg. binary, text, etc.) or adding actions that collect additional data, the total size of the event is still likely to be pretty small. This means that each buffer can likely hold thousands of events before it has to be processed. When the event buffers are finally processed there is an economy of scale achieved since most targets support bulk processing of the events so they are processed at the buffer level rather than the individual event level. When all this is working together it’s more likely that a full buffer will be processed and put back into the ready queue before the remaining buffers (remember, there are at least three) are full. I know what you’re going to say: “My server is exceptional! My workload is so massive it defies categorization!” OK, maybe you weren’t going to say that exactly, but you were probably thinking it. The point is that there are situations that won’t be covered by the Default, but that’s a good place to start and this post assumes you’ve started there so that you have something to look at in order to determine if you do have a special case that needs different settings. So let’s get to the special cases… What event just fired?! How about now?! Now?! If you believe the commercial adage from Heinz Ketchup (Heinz Slow Good Ketchup ad on You Tube), some things are worth the wait. This is not a belief held by most DBAs, particularly DBAs who are looking for an answer to a troubleshooting question fast. If you’re one of these anxious DBAs, or maybe just a Program Manager doing a demo, then 30 seconds might be longer than you’re comfortable waiting. If you find yourself in this situation then consider changing the MAX_DISPATCH_LATENCY option for your event session. This option will force the event buffers to be processed based on your time schedule. This option only makes sense for the asynchronous targets since those are the ones where we allow events to build up in the event buffer – if you’re using one of the synchronous targets this option isn’t relevant. Avoid forgotten events by increasing your memory Have you ever had one of those days where you keep forgetting things? That can happen in Extended Events too; we call it dropped events. In order to optimizes for server performance and help ensure that the Extended Events doesn’t block the server if to drop events that can’t be published to a buffer because the buffer is full. You can determine if events are being dropped from a session by querying the dm_xe_sessions DMV and looking at the dropped_event_count field. Aside: Should you care if you’re dropping events?Maybe not – think about why you’re collecting data in the first place and whether you’re really going to miss a few dropped events. For example, if you’re collecting query duration stats over thousands of executions of a query it won’t make a huge difference to miss a couple executions. Use your best judgment. If you find that your session is dropping events it means that the event buffer is not large enough to handle the volume of events that are being published. There are two ways to address this problem. First, you could collect fewer events – examine you session to see if you are over collecting. Do you need all the actions you’ve specified? Could you apply a predicate to be more specific about when you fire the event? Assuming the session is defined correctly, the next option is to change the MAX_MEMORY option to a larger number. Picking the right event buffer size might take some trial and error, but a good place to start is with the number of dropped events compared to the number you’ve collected. Aside: There are three different behaviors for dropping events that you specify using the EVENT_RETENTION_MODE option. The default is to allow single event loss and you should stick with this setting since it is the best choice for keeping the impact on server performance low.You’ll be tempted to use the setting to not lose any events (NO_EVENT_LOSS) – resist this urge since it can result in blocking on the server. If you’re worried that you’re losing events you should be increasing your event buffer memory as described in this section. Some events are too big to fail A less common reason for dropping an event is when an event is so large that it can’t fit into the event buffer. Even though most events are going to be small, you might find a condition that occasionally generates a very large event. You can determine if your session is dropping large events by looking at the dm_xe_sessions DMV once again, this time check the largest_event_dropped_size. If this value is larger than the size of your event buffer [remember, the size of your event buffer, by default, is max_memory / 3] then you need a large event buffer. To specify a large event buffer you set the MAX_EVENT_SIZE option to a value large enough to fit the largest event dropped based on data from the DMV. When you set this option the Extended Events engine will create two buffers of this size to accommodate these large events. As an added bonus (no extra charge) the large event buffer will also be used to store normal events in the cases where the normal event buffers are all full and waiting to be processed. (Note: This is just a side-effect, not the intended use. If you’re dropping many normal events then you should increase your normal event buffer size.) Partitioning: moving your events to a sub-division Earlier I alluded to the fact that you can configure your event session to use more than the standard three event buffers – this is called partitioning and is controlled by the MEMORY_PARTITION_MODE option. The result of setting this option is fairly easy to explain, but knowing when to use it is a bit more art than science. First the science… You can configure partitioning in three ways: None, Per NUMA Node & Per CPU. This specifies the location where sets of event buffers are created with fairly obvious implication. There are rules we follow for sub-dividing the total memory (specified by MAX_MEMORY) between all the event buffers that are specific to the mode used: None: 3 buffers (fixed)Node: 3 * number_of_nodesCPU: 2.5 * number_of_cpus Here are some examples of what this means for different Node/CPU counts: Configuration None Node CPU 2 CPUs, 1 Node 3 buffers 3 buffers 5 buffers 6 CPUs, 2 Node 3 buffers 6 buffers 15 buffers 40 CPUs, 5 Nodes 3 buffers 15 buffers 100 buffers   Aside: Buffer size on multi-processor computersAs the number of Nodes or CPUs increases, the size of the event buffer gets smaller because the total memory is sub-divided into more pieces. The defaults will hold up to this for a while since each buffer set is holding events only from the Node or CPU that it is associated with, but at some point the buffers will get too small and you’ll either see events being dropped or you’ll get an error when you create your session because you’re below the minimum buffer size. Increase the MAX_MEMORY setting to an appropriate number for the configuration. The most likely reason to start partitioning is going to be related to performance. If you notice that running an event session is impacting the performance of your server beyond a reasonably expected level [Yes, there is a reasonably expected level of work required to collect events.] then partitioning might be an answer. Before you partition you might want to check a few other things: Is your event retention set to NO_EVENT_LOSS and causing blocking? (I told you not to do this.) Consider changing your event loss mode or increasing memory. Are you over collecting and causing more work than necessary? Consider adding predicates to events or removing unnecessary events and actions from your session. Are you writing the file target to the same slow disk that you use for TempDB and your other high activity databases? <kidding> <not really> It’s always worth considering the end to end picture – if you’re writing events to a file you can be impacted by I/O, network; all the usual stuff. Assuming you’ve ruled out the obvious (and not so obvious) issues, there are performance conditions that will be addressed by partitioning. For example, it’s possible to have a successful event session (eg. no dropped events) but still see a performance impact because you have many CPUs all attempting to write to the same free buffer and having to wait in line to finish their work. This is a case where partitioning would relieve the contention between the different CPUs and likely reduce the performance impact cause by the event session. There is no DMV you can check to find these conditions – sorry – that’s where the art comes in. This is  largely a matter of experimentation. On the bright side you probably won’t need to to worry about this level of detail all that often. The performance impact of Extended Events is significantly lower than what you may be used to with SQL Trace. You will likely only care about the impact if you are trying to set up a long running event session that will be part of your everyday workload – sessions used for short term troubleshooting will likely fall into the “reasonably expected impact” category. Hey buddy – I think you forgot something OK, there are two options I didn’t cover: STARTUP_STATE & TRACK_CAUSALITY. If you want your event sessions to start automatically when the server starts, set the STARTUP_STATE option to ON. (Now there is only one option I didn’t cover.) I’m going to leave causality for another post since it’s not really related to session behavior, it’s more about event analysis. - Mike Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

    Read the article

  • Session Variable Not Being Updated? ASP.NET

    - by davemackey
    I have a three step wizard. On the first step I use a repeater to create a series of buttons that an individual can select from. When the user selects one of the buttons the value of the button is saved to session state. They are taken to the next step and shown a similar list of buttons that are based on what they previously selected. Thus, if you choose "Hamburger" you might receive the options of "onion", "lettuce", "tomato" while if you choose "Hot Dog" you might receive "sauerkraut" and "ketchup". Lets say an individual chooses Hamburger. This is saved into session state like so: Public Sub Button_ItemCommand(ByVal Sender As Object, ByVal e As RepeaterCommandEventArgs) ' ******** Lets pass on the results of our query in LinqDataSource1_Selecting. Session("food_select") = RTrim(e.CommandName) Wizard1.ActiveStepIndex = 1 End Sub Now, this works fine and dandy. But lets say I select hamburger and then realize I'm really hankering for a hot dog. I go back to the first wizard step and click on the hot dog button - but when the wizard progresses to the next step I still see the options for hamburgers! The session variable has not been updated. Why? Thanks!

    Read the article

1