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  • PHP 5 functioning returning an array- interaction without assignment?

    - by Lee
    I'm wondering if this kind of thing will ever be possible in PHP (and whether it already is and I'm just missing something...) <?php function test() { return array( 'id'=>10, 'name'=>'John' ); } echo 'Your name is: '.test()['name']; ?> I'd really like to be able to use returned arrays directly instead of first assigning them to a var... possible?

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  • I want to copy all the files available in my TFS source server to a folder in a directory.I tried th

    - by deep
    PS> C:\Windows\System32> Get-TfsItemProperty $/MyFirstTFSProj -r ` -server xyzc011b| Where {$_.CheckinDate -gt (Get-Date).AddDays(-150)} | Copy-Item D:\john\application1 -Destination C:\Test -whatif Copy-Item : The input object cannot be bound to any parameters for the command either because the command does not take pipeline input or the input and its pr operties do not match any of the parameters that take pipeline input. At line:2 char:14 + Copy-Item <<<< D:\Deepu\SilverlightApplication5 -Destination C:\Test -w hatif

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  • How to use length indicator in a C++ program

    - by cj
    I want to make a program in C++ that reads a file where each field will have a number before it that indicates how long it is. The problem is I read every record in object of a class; how do I make the attributes of the class dynamic? For example if the field is "john" it will read it in a 4 char array. I don't want to make an array of 1000 elements as minimum memory usage is very important.

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  • Unfamiliar Javascript Syntax

    - by user1051643
    Long and short of the story is, whilst reading John Resig's blog (specifically http://ejohn.org/blog/javascript-trie-performance-analysis/) I came across a line which makes absolutely no sense to me whatsoever. Essentially it boils down to object = object[key] = something; (this can be found in the first code block of the article I've linked.) This has proven rather difficult to google, so if anyone can offer some insight / a good online resource for me to learn for myself, I'd much appreciate it.

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  • Get the subdomain from a URL

    - by jb
    Getting the subdomain from a URL sounds easy at first. http://www.domain.example Scan for the first period then return whatever came after the "http://" ... Then you remember http://super.duper.domain.example Oh. So then you think, okay, find the last period, go back a word and get everything before! Then you remember http://super.duper.domain.co.uk And you're back to square one. Anyone have any great ideas besides storing a list of all TLDs? John

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  • Unknown Column In Where Clause

    - by Corpo
    I have a simple query: SELECT u_name AS user_name FROM users WHERE user_name = "john"; I get "Unknown Column 'user_name' in where clause". Can I not refer to 'user_name' in other parts of the statement even after select 'u_name as user_name'?

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  • Ruby javascript unescape equivalent

    - by vise
    I want to unescape the following string: '\u00020\u0002Standard\u00023\u0002Doe John\u000169\u0002\u0010\u0002Lorem\u0002\u0011\u0002Ipsum\u0002\u0014\u0002' Javascripts unescape function works ok, however how can I unescape it in ruby? Take in mind that unescape(previousString) is 0Standard3Doe John69LoremIpsum.

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  • Problem with displaying usernames in my flash[:notice] - Agile Web Development With Rails - Chapter

    - by Lee
    I can't figure out what I'm doing wrong here. I can’t seem to get the #{@user.name} to work in my flash[:notice] Everything else works just fine I can add new users, but when I add a new user instead of saying “User John Doe was successfully created”, it says “User #{@user.name} was successfully created.” I'm at this point in the depot app: depot_p/app/controllers/users_controller.rb to work.

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  • how do I replace certain characters in a string?

    - by user296516
    Hi guys, Suppose I have a string like this SOMETHING [1000137c] SOMETHING = John Rogers III [SOMETHING] SOMETHING ELSE and I need to turn it into this SOMETHING [1000137c] SOMETHING = John_Rogers_III [SOMETHING] SOMETHING ELSE Therefor I need to replace spaces between words after "[1000137c] SOMETHING = " and before " [". How can I do that in php? Thanks!

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  • ESXi VM NTP Server

    - by jstorch
    Hello all. We need to setup an internal NTP server. Because this server will pretty much ONLY be a time server I was thinking of just creating a VM for it. However, Googling around it appears that there there might be serious clock drifting issues with VM servers. So, is running our NTP server in a VM a completely dumb idea? Thanks, John

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  • Ignore deleted files in git?

    - by matthavener
    Is it possible to ignore deleted files in git? git update-index --assume-unchanged allows me to ignore modifications, but it still tracks deletions. (This is similar, but I couldn't find where "John Doe" restated his question: http://stackoverflow.com/questions/655243/ignore-modified-but-not-committed-files-in-git)

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  • Help Desk Database Design

    - by user237244
    The company I work at has very specific and unique needs for a help desk system, so none of the open source systems will work for us. That being the case, I created a custom system using PHP and MySQL. It's far from perfect, but it's infinitely better than the last system they were using; trust me! It meets most of our needs quite nicely, but I have a question about the way I have the database set up. Here are the main tables: ClosedTickets ClosedTicketSolutions Locations OpenTickets OpenTicketSolutions Statuses Technicians When a user submits a help request, it goes in the "OpenTickets" table. As the technicians work on the problem, they submit entries with a description of what they've done. These entries go in the "OpenTicketSolutions" table. When the problem has been resolved, the last technician to work on the problem closes the ticket and it gets moved to the "ClosedTickets" table. All of the solution entries get moved to the "ClosedTicketSolutions" table as well. The other tables (Locations, Statuses, and Technicians) exist as a means of normalization (each location, status, and technician has an ID which is referenced). The problem I'm having now is this: When I want to view a list of all the open tickets, the SQL statement is somewhat complicated because I have to left join the "Locations", "Statuses", and "Technicians" tables. Fields from various tables need to be searchable as well. Check out how complicated the SQL statement is to search closed tickets for tickets submitted by anybody with a first name containing "John": SELECT ClosedTickets.*, date_format(ClosedTickets.EntryDate, '%c/%e/%y %l:%i %p') AS Formatted_Date, date_format(ClosedDate, '%c/%e/%y %l:%i %p') AS Formatted_ClosedDate, Concat(Technicians.LastName, ', ', Technicians.FirstName) AS TechFullName, Locations.LocationName, date_format(ClosedTicketSolutions.EntryDate, '%c/%e/%y') AS Formatted_Solution_EntryDate, ClosedTicketSolutions.HoursSpent AS SolutionHoursSpent, ClosedTicketSolutions.Tech_ID AS SolutionTech_ID, ClosedTicketSolutions.EntryText FROM ClosedTickets LEFT JOIN Technicians ON ClosedTickets.Tech_ID = Technicians.Tech_ID LEFT JOIN Locations ON ClosedTickets.Location_ID = Locations.Location_ID LEFT JOIN ClosedTicketSolutions ON ClosedTickets.TicketNum = ClosedTicketSolutions.TicketNum WHERE (ClosedTickets.FirstName LIKE '%John%') ORDER BY ClosedDate Desc, ClosedTicketSolutions.EntryDate, ClosedTicketSolutions.Entry_ID One thing that I'm not able to do right now is search both open and closed tickets at the same time. I don't think a union would work in my case. So I'm wondering if I should store the open and closed tickets in the same table and just have a field indicating whether or not the ticket is closed. The only problem I can forsee is that we have so many closed tickets already (nearly 30,000) so the whole system might perform slowly. Would it be a bad idea to combine the open and closed tickets?

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  • Load huge sql dump to mySql

    - by jonathan
    Hi I have a huge mysql dump file generated from phpmyAdmin (150 000 lines of create table, inserts....) The mySql query tool fails to open such a big file. As a result i can't insert all the records. Is there a way to do this ? Thanks John

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  • Python: Closing a for loop by reading stdout

    - by user1732102
    import os dictionaryfile = "/root/john.txt" pgpencryptedfile = "helloworld.txt.gpg" array = open(dictionaryfile).readlines() for x in array: x = x.rstrip('\n') newstring = "echo " + x + " | gpg --passphrase-fd 0 " + pgpencryptedfile os.popen(newstring) I need to create something inside the for loop that will read gpg's output. When gpg outputs this string gpg: WARNING: message was not integrity protected, I need the loop to close and print Success! How can I do this, and what is the reasoning behind it? Thanks Everyone!

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  • Game Design Dilemma

    - by Chris Williams
    I'm working on a 2d tilemapped RPG. I've actually made quite a fair amount of progress, but I'm at a point where I need to make a UI decision. I have the overland world completely mapped out, and I have several towns and special areas. I'm on the fence about how to integrate the two. Scenario 1: I have one ginormous map, where everything is the same scale. This means you can walk in and out of towns without having to load or wait and transition in any way. With everything the same scale, movement costs the same no matter where you are (in terms of time/turns/energy/hunger/whatever/etc...)  The potential downside to this is that it could take quite a long time to get anywhere on foot. Scenario 2: I have an overland map, a set of town maps, overland tactical maps, dungeon maps & special area maps. The overland map is at a different scale than the other maps. This means that time/turns/energy/hunger/whatever/etc is calculated at a different rate than on the other maps, which have a 1:1 scale. When entering a town, dungeon, special area or having a random encounter, you would effectively zoom in from the overland scale to the tactical scale. When you are done with combat, or exit a dungeon or town, it would zoom back out to the overland map. The downside to this is that at the zoomed out scale, the overland map isn't all that big (comparitively) and you can traverse it fairly quickly (in real time, not game world time.) Options: 1) Go with scenario 1, as is. 2) Go with scenario 1 and introduce a slightly speedier version of overland travel, such as a horse. 3) Go with scenario 1 and introduce "instant" travel, via portals or some kind of "click the big map" mechanism. This would only work with places you've already been, or somehow unlocked (perhaps via a quest.) 4) Go with Scenario 2, as is.   Thoughts, opinions, suggestions?  Feedback appreciated.

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  • How to find and fix performance problems in ORM powered applications

    - by FransBouma
    Once in a while we get requests about how to fix performance problems with our framework. As it comes down to following the same steps and looking into the same things every single time, I decided to write a blogpost about it instead, so more people can learn from this and solve performance problems in their O/R mapper powered applications. In some parts it's focused on LLBLGen Pro but it's also usable for other O/R mapping frameworks, as the vast majority of performance problems in O/R mapper powered applications are not specific for a certain O/R mapper framework. Too often, the developer looks at the wrong part of the application, trying to fix what isn't a problem in that part, and getting frustrated that 'things are so slow with <insert your favorite framework X here>'. I'm in the O/R mapper business for a long time now (almost 10 years, full time) and as it's a small world, we O/R mapper developers know almost all tricks to pull off by now: we all know what to do to make task ABC faster and what compromises (because there are almost always compromises) to deal with if we decide to make ABC faster that way. Some O/R mapper frameworks are faster in X, others in Y, but you can be sure the difference is mainly a result of a compromise some developers are willing to deal with and others aren't. That's why the O/R mapper frameworks on the market today are different in many ways, even though they all fetch and save entities from and to a database. I'm not suggesting there's no room for improvement in today's O/R mapper frameworks, there always is, but it's not a matter of 'the slowness of the application is caused by the O/R mapper' anymore. Perhaps query generation can be optimized a bit here, row materialization can be optimized a bit there, but it's mainly coming down to milliseconds. Still worth it if you're a framework developer, but it's not much compared to the time spend inside databases and in user code: if a complete fetch takes 40ms or 50ms (from call to entity object collection), it won't make a difference for your application as that 10ms difference won't be noticed. That's why it's very important to find the real locations of the problems so developers can fix them properly and don't get frustrated because their quest to get a fast, performing application failed. Performance tuning basics and rules Finding and fixing performance problems in any application is a strict procedure with four prescribed steps: isolate, analyze, interpret and fix, in that order. It's key that you don't skip a step nor make assumptions: these steps help you find the reason of a problem which seems to be there, and how to fix it or leave it as-is. Skipping a step, or when you assume things will be bad/slow without doing analysis will lead to the path of premature optimization and won't actually solve your problems, only create new ones. The most important rule of finding and fixing performance problems in software is that you have to understand what 'performance problem' actually means. Most developers will say "when a piece of software / code is slow, you have a performance problem". But is that actually the case? If I write a Linq query which will aggregate, group and sort 5 million rows from several tables to produce a resultset of 10 rows, it might take more than a couple of milliseconds before that resultset is ready to be consumed by other logic. If I solely look at the Linq query, the code consuming the resultset of the 10 rows and then look at the time it takes to complete the whole procedure, it will appear to me to be slow: all that time taken to produce and consume 10 rows? But if you look closer, if you analyze and interpret the situation, you'll see it does a tremendous amount of work, and in that light it might even be extremely fast. With every performance problem you encounter, always do realize that what you're trying to solve is perhaps not a technical problem at all, but a perception problem. The second most important rule you have to understand is based on the old saying "Penny wise, Pound Foolish": the part which takes e.g. 5% of the total time T for a given task isn't worth optimizing if you have another part which takes a much larger part of the total time T for that same given task. Optimizing parts which are relatively insignificant for the total time taken is not going to bring you better results overall, even if you totally optimize that part away. This is the core reason why analysis of the complete set of application parts which participate in a given task is key to being successful in solving performance problems: No analysis -> no problem -> no solution. One warning up front: hunting for performance will always include making compromises. Fast software can be made maintainable, but if you want to squeeze as much performance out of your software, you will inevitably be faced with the dilemma of compromising one or more from the group {readability, maintainability, features} for the extra performance you think you'll gain. It's then up to you to decide whether it's worth it. In almost all cases it's not. The reason for this is simple: the vast majority of performance problems can be solved by implementing the proper algorithms, the ones with proven Big O-characteristics so you know the performance you'll get plus you know the algorithm will work. The time taken by the algorithm implementing code is inevitable: you already implemented the best algorithm. You might find some optimizations on the technical level but in general these are minor. Let's look at the four steps to see how they guide us through the quest to find and fix performance problems. Isolate The first thing you need to do is to isolate the areas in your application which are assumed to be slow. For example, if your application is a web application and a given page is taking several seconds or even minutes to load, it's a good candidate to check out. It's important to start with the isolate step because it allows you to focus on a single code path per area with a clear begin and end and ignore the rest. The rest of the steps are taken per identified problematic area. Keep in mind that isolation focuses on tasks in an application, not code snippets. A task is something that's started in your application by either another task or the user, or another program, and has a beginning and an end. You can see a task as a piece of functionality offered by your application.  Analyze Once you've determined the problem areas, you have to perform analysis on the code paths of each area, to see where the performance problems occur and which areas are not the problem. This is a multi-layered effort: an application which uses an O/R mapper typically consists of multiple parts: there's likely some kind of interface (web, webservice, windows etc.), a part which controls the interface and business logic, the O/R mapper part and the RDBMS, all connected with either a network or inter-process connections provided by the OS or other means. Each of these parts, including the connectivity plumbing, eat up a part of the total time it takes to complete a task, e.g. load a webpage with all orders of a given customer X. To understand which parts participate in the task / area we're investigating and how much they contribute to the total time taken to complete the task, analysis of each participating task is essential. Start with the code you wrote which starts the task, analyze the code and track the path it follows through your application. What does the code do along the way, verify whether it's correct or not. Analyze whether you have implemented the right algorithms in your code for this particular area. Remember we're looking at one area at a time, which means we're ignoring all other code paths, just the code path of the current problematic area, from begin to end and back. Don't dig in and start optimizing at the code level just yet. We're just analyzing. If your analysis reveals big architectural stupidity, it's perhaps a good idea to rethink the architecture at this point. For the rest, we're analyzing which means we collect data about what could be wrong, for each participating part of the complete application. Reviewing the code you wrote is a good tool to get deeper understanding of what is going on for a given task but ultimately it lacks precision and overview what really happens: humans aren't good code interpreters, computers are. We therefore need to utilize tools to get deeper understanding about which parts contribute how much time to the total task, triggered by which other parts and for example how many times are they called. There are two different kind of tools which are necessary: .NET profilers and O/R mapper / RDBMS profilers. .NET profiling .NET profilers (e.g. dotTrace by JetBrains or Ants by Red Gate software) show exactly which pieces of code are called, how many times they're called, and the time it took to run that piece of code, at the method level and sometimes even at the line level. The .NET profilers are essential tools for understanding whether the time taken to complete a given task / area in your application is consumed by .NET code, where exactly in your code, the path to that code, how many times that code was called by other code and thus reveals where hotspots are located: the areas where a solution can be found. Importantly, they also reveal which areas can be left alone: remember our penny wise pound foolish saying: if a profiler reveals that a group of methods are fast, or don't contribute much to the total time taken for a given task, ignore them. Even if the code in them is perhaps complex and looks like a candidate for optimization: you can work all day on that, it won't matter.  As we're focusing on a single area of the application, it's best to start profiling right before you actually activate the task/area. Most .NET profilers support this by starting the application without starting the profiling procedure just yet. You navigate to the particular part which is slow, start profiling in the profiler, in your application you perform the actions which are considered slow, and afterwards you get a snapshot in the profiler. The snapshot contains the data collected by the profiler during the slow action, so most data is produced by code in the area to investigate. This is important, because it allows you to stay focused on a single area. O/R mapper and RDBMS profiling .NET profilers give you a good insight in the .NET side of things, but not in the RDBMS side of the application. As this article is about O/R mapper powered applications, we're also looking at databases, and the software making it possible to consume the database in your application: the O/R mapper. To understand which parts of the O/R mapper and database participate how much to the total time taken for task T, we need different tools. There are two kind of tools focusing on O/R mappers and database performance profiling: O/R mapper profilers and RDBMS profilers. For O/R mapper profilers, you can look at LLBLGen Prof by hibernating rhinos or the Linq to Sql/LLBLGen Pro profiler by Huagati. Hibernating rhinos also have profilers for other O/R mappers like NHibernate (NHProf) and Entity Framework (EFProf) and work the same as LLBLGen Prof. For RDBMS profilers, you have to look whether the RDBMS vendor has a profiler. For example for SQL Server, the profiler is shipped with SQL Server, for Oracle it's build into the RDBMS, however there are also 3rd party tools. Which tool you're using isn't really important, what's important is that you get insight in which queries are executed during the task / area we're currently focused on and how long they took. Here, the O/R mapper profilers have an advantage as they collect the time it took to execute the query from the application's perspective so they also collect the time it took to transport data across the network. This is important because a query which returns a massive resultset or a resultset with large blob/clob/ntext/image fields takes more time to get transported across the network than a small resultset and a database profiler doesn't take this into account most of the time. Another tool to use in this case, which is more low level and not all O/R mappers support it (though LLBLGen Pro and NHibernate as well do) is tracing: most O/R mappers offer some form of tracing or logging system which you can use to collect the SQL generated and executed and often also other activity behind the scenes. While tracing can produce a tremendous amount of data in some cases, it also gives insight in what's going on. Interpret After we've completed the analysis step it's time to look at the data we've collected. We've done code reviews to see whether we've done anything stupid and which parts actually take place and if the proper algorithms have been implemented. We've done .NET profiling to see which parts are choke points and how much time they contribute to the total time taken to complete the task we're investigating. We've performed O/R mapper profiling and RDBMS profiling to see which queries were executed during the task, how many queries were generated and executed and how long they took to complete, including network transportation. All this data reveals two things: which parts are big contributors to the total time taken and which parts are irrelevant. Both aspects are very important. The parts which are irrelevant (i.e. don't contribute significantly to the total time taken) can be ignored from now on, we won't look at them. The parts which contribute a lot to the total time taken are important to look at. We now have to first look at the .NET profiler results, to see whether the time taken is consumed in our own code, in .NET framework code, in the O/R mapper itself or somewhere else. For example if most of the time is consumed by DbCommand.ExecuteReader, the time it took to complete the task is depending on the time the data is fetched from the database. If there was just 1 query executed, according to tracing or O/R mapper profilers / RDBMS profilers, check whether that query is optimal, uses indexes or has to deal with a lot of data. Interpret means that you follow the path from begin to end through the data collected and determine where, along the path, the most time is contributed. It also means that you have to check whether this was expected or is totally unexpected. My previous example of the 10 row resultset of a query which groups millions of rows will likely reveal that a long time is spend inside the database and almost no time is spend in the .NET code, meaning the RDBMS part contributes the most to the total time taken, the rest is compared to that time, irrelevant. Considering the vastness of the source data set, it's expected this will take some time. However, does it need tweaking? Perhaps all possible tweaks are already in place. In the interpret step you then have to decide that further action in this area is necessary or not, based on what the analysis results show: if the analysis results were unexpected and in the area where the most time is contributed to the total time taken is room for improvement, action should be taken. If not, you can only accept the situation and move on. In all cases, document your decision together with the analysis you've done. If you decide that the perceived performance problem is actually expected due to the nature of the task performed, it's essential that in the future when someone else looks at the application and starts asking questions you can answer them properly and new analysis is only necessary if situations changed. Fix After interpreting the analysis results you've concluded that some areas need adjustment. This is the fix step: you're actively correcting the performance problem with proper action targeted at the real cause. In many cases related to O/R mapper powered applications it means you'll use different features of the O/R mapper to achieve the same goal, or apply optimizations at the RDBMS level. It could also mean you apply caching inside your application (compromise memory consumption over performance) to avoid unnecessary re-querying data and re-consuming the results. After applying a change, it's key you re-do the analysis and interpretation steps: compare the results and expectations with what you had before, to see whether your actions had any effect or whether it moved the problem to a different part of the application. Don't fall into the trap to do partly analysis: do the full analysis again: .NET profiling and O/R mapper / RDBMS profiling. It might very well be that the changes you've made make one part faster but another part significantly slower, in such a way that the overall problem hasn't changed at all. Performance tuning is dealing with compromises and making choices: to use one feature over the other, to accept a higher memory footprint, to go away from the strict-OO path and execute queries directly onto the RDBMS, these are choices and compromises which will cross your path if you want to fix performance problems with respect to O/R mappers or data-access and databases in general. In most cases it's not a big issue: alternatives are often good choices too and the compromises aren't that hard to deal with. What is important is that you document why you made a choice, a compromise: which analysis data, which interpretation led you to the choice made. This is key for good maintainability in the years to come. Most common performance problems with O/R mappers Below is an incomplete list of common performance problems related to data-access / O/R mappers / RDBMS code. It will help you with fixing the hotspots you found in the interpretation step. SELECT N+1: (Lazy-loading specific). Lazy loading triggered performance bottlenecks. Consider a list of Orders bound to a grid. You have a Field mapped onto a related field in Order, Customer.CompanyName. Showing this column in the grid will make the grid fetch (indirectly) for each row the Customer row. This means you'll get for the single list not 1 query (for the orders) but 1+(the number of orders shown) queries. To solve this: use eager loading using a prefetch path to fetch the customers with the orders. SELECT N+1 is easy to spot with an O/R mapper profiler or RDBMS profiler: if you see a lot of identical queries executed at once, you have this problem. Prefetch paths using many path nodes or sorting, or limiting. Eager loading problem. Prefetch paths can help with performance, but as 1 query is fetched per node, it can be the number of data fetched in a child node is bigger than you think. Also consider that data in every node is merged on the client within the parent. This is fast, but it also can take some time if you fetch massive amounts of entities. If you keep fetches small, you can use tuning parameters like the ParameterizedPrefetchPathThreshold setting to get more optimal queries. Deep inheritance hierarchies of type Target Per Entity/Type. If you use inheritance of type Target per Entity / Type (each type in the inheritance hierarchy is mapped onto its own table/view), fetches will join subtype- and supertype tables in many cases, which can lead to a lot of performance problems if the hierarchy has many types. With this problem, keep inheritance to a minimum if possible, or switch to a hierarchy of type Target Per Hierarchy, which means all entities in the inheritance hierarchy are mapped onto the same table/view. Of course this has its own set of drawbacks, but it's a compromise you might want to take. Fetching massive amounts of data by fetching large lists of entities. LLBLGen Pro supports paging (and limiting the # of rows returned), which is often key to process through large sets of data. Use paging on the RDBMS if possible (so a query is executed which returns only the rows in the page requested). When using paging in a web application, be sure that you switch server-side paging on on the datasourcecontrol used. In this case, paging on the grid alone is not enough: this can lead to fetching a lot of data which is then loaded into the grid and paged there. Keep note that analyzing queries for paging could lead to the false assumption that paging doesn't occur, e.g. when the query contains a field of type ntext/image/clob/blob and DISTINCT can't be applied while it should have (e.g. due to a join): the datareader will do DISTINCT filtering on the client. this is a little slower but it does perform paging functionality on the data-reader so it won't fetch all rows even if the query suggests it does. Fetch massive amounts of data because blob/clob/ntext/image fields aren't excluded. LLBLGen Pro supports field exclusion for queries. You can exclude fields (also in prefetch paths) per query to avoid fetching all fields of an entity, e.g. when you don't need them for the logic consuming the resultset. Excluding fields can greatly reduce the amount of time spend on data-transport across the network. Use this optimization if you see that there's a big difference between query execution time on the RDBMS and the time reported by the .NET profiler for the ExecuteReader method call. Doing client-side aggregates/scalar calculations by consuming a lot of data. If possible, try to formulate a scalar query or group by query using the projection system or GetScalar functionality of LLBLGen Pro to do data consumption on the RDBMS server. It's far more efficient to process data on the RDBMS server than to first load it all in memory, then traverse the data in-memory to calculate a value. Using .ToList() constructs inside linq queries. It might be you use .ToList() somewhere in a Linq query which makes the query be run partially in-memory. Example: var q = from c in metaData.Customers.ToList() where c.Country=="Norway" select c; This will actually fetch all customers in-memory and do an in-memory filtering, as the linq query is defined on an IEnumerable<T>, and not on the IQueryable<T>. Linq is nice, but it can often be a bit unclear where some parts of a Linq query might run. Fetching all entities to delete into memory first. To delete a set of entities it's rather inefficient to first fetch them all into memory and then delete them one by one. It's more efficient to execute a DELETE FROM ... WHERE query on the database directly to delete the entities in one go. LLBLGen Pro supports this feature, and so do some other O/R mappers. It's not always possible to do this operation in the context of an O/R mapper however: if an O/R mapper relies on a cache, these kind of operations are likely not supported because they make it impossible to track whether an entity is actually removed from the DB and thus can be removed from the cache. Fetching all entities to update with an expression into memory first. Similar to the previous point: it is more efficient to update a set of entities directly with a single UPDATE query using an expression instead of fetching the entities into memory first and then updating the entities in a loop, and afterwards saving them. It might however be a compromise you don't want to take as it is working around the idea of having an object graph in memory which is manipulated and instead makes the code fully aware there's a RDBMS somewhere. Conclusion Performance tuning is almost always about compromises and making choices. It's also about knowing where to look and how the systems in play behave and should behave. The four steps I provided should help you stay focused on the real problem and lead you towards the solution. Knowing how to optimally use the systems participating in your own code (.NET framework, O/R mapper, RDBMS, network/services) is key for success as well as knowing what's going on inside the application you built. I hope you'll find this guide useful in tracking down performance problems and dealing with them in a useful way.  

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  • Java Spotlight Episode 139: Mark Heckler and José Pereda on JES based Energy Monitoring @MkHeck @JPeredaDnr

    - by Roger Brinkley
    Interview with Mark Heckler and José Pereda on using JavaSE Embedded with the Java Embedded Suite on a RaspberryPI along with a JavaFX client to monitor an energy production system and their JavaOne Tutorial- Java Embedded EXTREME MASHUPS: Building self-powering sensor nets for the IoT Right-click or Control-click to download this MP3 file. You can also subscribe to the Java Spotlight Podcast Feed to get the latest podcast automatically. If you use iTunes you can open iTunes and subscribe with this link: Java Spotlight Podcast in iTunes. Show Notes News Java Virtual Developer Day Session Videos Available JavaFX Maven Plugin 2.0 Released JavaFX Scene Builder 1.1 build b28 FXForm 2 release 0.2.2 OpenJDK8/Zero cross compile build for Foundation model HSAIL-based GPU offload: the Quest for Java Performance Begins Progress on Moving to Gradle Java EE 7 Launch Keynote Replay Java EE 7 Technical Breakouts Replay Java EE 7 support in NetBeans 7.3.1 Java EE 7 support in Eclipse 4.3 Java Magazine - May/June Events Jul 16-19, Uberconf, Denver, USA Jul 22-24, JavaOne Shanghai, China Jul 29-31, JVM Language Summit, Santa Clara Sep 11-12, JavaZone, Oslo, Norway Sep 19-20, Strange Loop, St. Louis Sep 22-26 JavaOne San Francisco 2013, USA Feature Interview Mark Heckler is an Oracle Corporation Java/Middleware/Core Tech Engineer with development experience in numerous environments. He has worked for and with key players in the manufacturing, emerging markets, retail, medical, telecom, and financial industries to develop and deliver critical capabilities on time and on budget. Currently, he works primarily with large government customers using Java throughout the stack and across the enterprise. He also participates in open-source development at every opportunity, being a JFXtras project committer and developer of DialogFX, MonologFX, and various other projects. When Mark isn't working with Java, he enjoys writing about his experiences at the Java Jungle website (https://blogs.oracle.com/javajungle/) and on Twitter (@MkHeck). José Pereda is a Structural Engineer working in the School of Engineers in the University of Valladolid in Spain for more than 15 years, and his passion is related to applying programming to solve real problems. Being involved with Java since 1999, José shares his time between JavaFX and the Embedded world, developing commercial applications and open source projects (https://github.com/jperedadnr), and blogging (http://jperedadnr.blogspot.com.es/) or tweeting (@JPeredaDnr) of both. What’s Cool AquaFX 0.1 - Mac OS X skin for JavaFX by Claudine Zillmann DromblerFX adds a docking framework Part 2 of Gerrit’s taming the Nashorn for writing JavaFX apps in Javascript Tool from mihosoft called JSelect for quickly switching JDKs Apache Maven Javadoc Plugin 2.9.1 Released Proposal: Java Concurrency Stress tests (jcstress) Slide-free Code-driven session at SV JUG JavaOne approvals/rejects gone out

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  • Global Cache CR Requested But Current Block Received

    - by Liu Maclean(???)
    ????????«MINSCN?Cache Fusion Read Consistent» ????,???????????? ??????????????????: SQL> select * from V$version; BANNER -------------------------------------------------------------------------------- Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit Production PL/SQL Release 11.2.0.3.0 - Production CORE 11.2.0.3.0 Production TNS for Linux: Version 11.2.0.3.0 - Production NLSRTL Version 11.2.0.3.0 - Production SQL> select count(*) from gv$instance; COUNT(*) ---------- 2 SQL> select * from global_name; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com ?11gR2 2??RAC??????????status???XG,????Xcurrent block???INSTANCE 2?hold?,?????INSTANCE 1?????????,?????: SQL> select * from test; ID ---------- 1 2 SQL> select dbms_rowid.rowid_block_number(rowid),dbms_rowid.rowid_relative_fno(rowid) from test; DBMS_ROWID.ROWID_BLOCK_NUMBER(ROWID) DBMS_ROWID.ROWID_RELATIVE_FNO(ROWID) ------------------------------------ ------------------------------------ 89233 1 89233 1 SQL> alter system flush buffer_cache; System altered. INSTANCE 1 Session A: SQL> update test set id=id+1 where id=1; 1 row updated. INSTANCE 1 Session B: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1755287 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD1/trace/VPROD1_ora_19111.trc GLOBAL CACHE ELEMENT DUMP (address: 0xa4ff3080): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: X rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kdswh11: kdst_fetch' bscn: 0x0.146e20 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0xa9f6a6f8,0xa9f6a6f8] seq: 32 hist: 58 145:0 118 66 144:0 192 352 197 48 121 113 424 180 58 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x02000001 lflg: 0x1 state: XCURRENT tsn: 0 tsh: 2 addr: 0xa9f6a5c8 obj: 76896 cls: DATA bscn: 0x0.1ac898 BH (0xa9f6a5c8) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0xa9e56000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 3 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x91f4e970,0xbae9d5b8] lru: [0x91f58848,0xa9f6a828] lru-flags: debug_dump obj-flags: object_ckpt_list ckptq: [0x9df6d1d8,0xa9f6a740] fileq: [0xa2ece670,0xbdf4ed68] objq: [0xb4964e00,0xb4964e00] objaq: [0xb4964de0,0xb4964de0] st: XCURRENT md: NULL fpin: 'kdswh11: kdst_fetch' tch: 2 le: 0xa4ff3080 flags: buffer_dirty redo_since_read LRBA: [0x19.5671.0] LSCN: [0x0.1ac898] HSCN: [0x0.1ac898] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001ac898 seq: 0x01 flg: 0x00 tail: 0xc8980601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data ??????block: (1/89233)?GLOBAL CACHE ELEMENT DUMP?LOCK????X ??XG , ??????Current Block????Instance??modify???,????????????? ????Instance 2 ????: Instance 2 Session C: SQL> update test set id=id+1 where id=2; 1 row updated. Instance 2 Session D: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1756658 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_ora_13038.trc GLOBAL CACHE ELEMENT DUMP (address: 0x89fb25a0): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: XG rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kduwh01: kdusru' bscn: 0x0.1acdf3 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0x96f4cf80,0x96f4cf80] seq: 61 hist: 324 21 143:0 19 16 352 329 144:6 14 7 352 197 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x0a000001 state: XCURRENT tsn: 0 tsh: 1 addr: 0x96f4ce50 obj: 76896 cls: DATA bscn: 0x0.1acdf6 BH (0x96f4ce50) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0x96bd4000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 2 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x96ee1fe8,0xbae9d5b8] lru: [0x96f4d0b0,0x96f4cdc0] obj-flags: object_ckpt_list ckptq: [0xbdf519b8,0x96f4d5a8] fileq: [0xbdf519d8,0xbdf519d8] objq: [0xb4a47b90,0xb4a47b90] objaq: [0x96f4d0e8,0xb4a47b70] st: XCURRENT md: NULL fpin: 'kduwh01: kdusru' tch: 1 le: 0x89fb25a0 flags: buffer_dirty redo_since_read remote_transfered LRBA: [0x11.9e18.0] LSCN: [0x0.1acdf6] HSCN: [0x0.1acdf6] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001acdf6 seq: 0x01 flg: 0x00 tail: 0xcdf60601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data GCS CLIENT 0x89fb2618,6 resp[(nil),0x15c91.1] pkey 76896.0 grant 2 cvt 0 mdrole 0x42 st 0x100 lst 0x20 GRANTQ rl G0 master 1 owner 2 sid 0 remote[(nil),0] hist 0x94121c601163423c history 0x3c.0x4.0xd.0xb.0x1.0xc.0x7.0x9.0x14.0x1. cflag 0x0 sender 1 flags 0x0 replay# 0 abast (nil).x0.1 dbmap (nil) disk: 0x0000.00000000 write request: 0x0000.00000000 pi scn: 0x0000.00000000 sq[(nil),(nil)] msgseq 0x1 updseq 0x0 reqids[6,0,0] infop (nil) lockseq x2b8 pkey 76896.0 hv 93 [stat 0x0, 1->1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 ?Instance 2??????block: (1/89233)? GLOBAL CACHE ELEMENT Lock Convert?lock: XG ????GC_ELEMENTS DUMP???XCUR Cache Fusion?,???????X$ VIEW,??? X$LE X$KJBR X$KJBL, ???X$ VIEW???????????????????: INSTANCE 2 Session D: SELECT * FROM x$le WHERE le_addr IN (SELECT le_addr FROM x$bh WHERE obj IN (SELECT data_object_id FROM dba_objects WHERE owner = 'SYS' AND object_name = 'TEST') AND class = 1 AND state != 3); ADDR INDX INST_ID LE_ADDR LE_ID1 LE_ID2 ---------------- ---------- ---------- ---------------- ---------- ---------- LE_RLS LE_ACQ LE_FLAGS LE_MODE LE_WRITE LE_LOCAL LE_RECOVERY ---------- ---------- ---------- ---------- ---------- ---------- ----------- LE_BLKS LE_TIME LE_KJBL ---------- ---------- ---------------- 00007F94CA14CF60 7003 2 0000000089FB25A0 89233 1 0 0 32 2 0 1 0 1 0 0000000089FB2618 PCM Resource NAME?[ID1][ID2],[BL]???, ID1?ID2 ??blockno? fileno????, ??????????GC_elements dump?? id1: 0x15c91 id2: 0×1 pkey: OBJ#76896 block: (1/89233)?? ,?  kjblname ? kjbrname ??”[0x15c91][0x1],[BL]” ??: INSTANCE 2 Session D: SQL> set linesize 80 pagesize 1400 SQL> SELECT * 2 FROM x$kjbl l 3 WHERE l.kjblname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBLLOCKP KJBLGRANT KJBLREQUE ---------------- ---------- ---------- ---------------- --------- --------- KJBLROLE KJBLRESP KJBLNAME ---------- ---------------- ------------------------------ KJBLNAME2 KJBLQUEUE ------------------------------ ---------- KJBLLOCKST KJBLWRITING ---------------------------------------------------------------- ----------- KJBLREQWRITE KJBLOWNER KJBLMASTER KJBLBLOCKED KJBLBLOCKER KJBLSID KJBLRDOMID ------------ ---------- ---------- ----------- ----------- ---------- ---------- KJBLPKEY ---------- 00007F94CA22A288 451 2 0000000089FB2618 KJUSEREX KJUSERNL 0 00 [0x15c91][0x1],[BL][ext 0x0,0x 89233,1,BL 0 GRANTED 0 0 1 0 0 0 0 0 76896 SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; no rows selected Instance 1 session B: SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBRRESP KJBRGRANT KJBRNCVL ---------------- ---------- ---------- ---------------- --------- --------- KJBRROLE KJBRNAME KJBRMASTER KJBRGRANTQ ---------- ------------------------------ ---------- ---------------- KJBRCVTQ KJBRWRITER KJBRSID KJBRRDOMID KJBRPKEY ---------------- ---------------- ---------- ---------- ---------- 00007F801ACA68F8 1355 1 00000000B5A62AE0 KJUSEREX KJUSERNL 0 [0x15c91][0x1],[BL][ext 0x0,0x 0 00000000B48BB330 00 00 0 0 76896 ??????Instance 1???block: (1/89233),??????Instance 2 build cr block ????Instance 1, ?????????? ????? Instance 1? Foreground Process ? Instance 2?LMS??????RAC  TRACE: Instance 2: [oracle@vrh2 ~]$ ps -ef|grep ora_lms|grep -v grep oracle 23364 1 0 Apr29 ? 00:33:15 ora_lms0_VPROD2 SQL> oradebug setospid 23364 Oracle pid: 13, Unix process pid: 23364, image: [email protected] (LMS0) SQL> oradebug event 10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high; Statement processed. SQL> oradebug tracefile_name /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_lms0_23364.trc Instance 1 session B : SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1756658 3 1756661 3 1755287 Instance 1 session A : SQL> alter session set events '10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high'; Session altered. SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761520 ?x$BH?????,???????Instance 1???build??CR block,????? TRACE ??: Instance 1 foreground Process: PARSING IN CURSOR #140336527348792 len=18 dep=0 uid=0 oct=3 lid=0 tim=1335939136125254 hv=1689401402 ad='b1a4c828' sqlid='c99yw1xkb4f1u' select * from test END OF STMT PARSE #140336527348792:c=2999,e=2860,p=0,cr=0,cu=0,mis=1,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125253 EXEC #140336527348792:c=0,e=40,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125373 WAIT #140336527348792: nam='SQL*Net message to client' ela= 6 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939136125420 *** 2012-05-02 02:12:16.125 kclscrs: req=0 block=1/89233 2012-05-02 02:12:16.125574 : kjbcro[0x15c91.1 76896.0][4] *** 2012-05-02 02:12:16.125 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:12:16.125 kclscrs: bid=1:3:1:0:f:1e:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1c:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:14:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:12:16.125718 : kjbcro[0x15c91.1 76896.0][4] 2012-05-02 02:12:16.125751 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:12:16.125780 : kjbsentscn[0x0.1ae0f0][to 2] 2012-05-02 02:12:16.125806 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177740 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:12:16.125918 : kjbmscr(0x15c91.1)reqid=0x8(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:12:16.126959 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:12:16.127 kclwcrs: wait=0 tm=1233 *** 2012-05-02 02:12:16.127 kclwcrs: got 1 blocks from ksxprcv WAIT #140336527348792: nam='gc cr block 2-way' ela= 1233 p1=1 p2=89233 p3=1 obj#=76896 tim=1335939136127199 2012-05-02 02:12:16.127272 : kjbcrcomplete[0x15c91.1 76896.0][0] 2012-05-02 02:12:16.127309 : kjbrcvdscn[0x0.1ae0f0][from 2][idx 2012-05-02 02:12:16.127329 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f0][from 2] ???? kjbcro[0x15c91.1 76896.0][4] kjbsentscn[0x0.1ae0f0][to 2] ?Instance 2??SCN=1ae0f0=1761520? block: (1/89233),???’gc cr block 2-way’ ??,?????????CR block? Instance 2 LMS TRACE 2012-05-02 02:12:15.634057 : GSIPC:RCVD: ksxp msg 0x7f16e1598588 sndr 1 seq 0.177740 type 36 tkts 0 2012-05-02 02:12:15.634094 : GSIPC:RCVD: watq msg 0x7f16e1598588 sndr 1, seq 177740, type 36, tkts 0 2012-05-02 02:12:15.634108 : GSIPC:TKT: collect msg 0x7f16e1598588 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.634162 : kjbrcvdscn[0x0.1ae0f0][from 1][idx 2012-05-02 02:12:15.634186 : kjbrcvdscn[no bscn1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 GCS CLIENT END 2012-05-02 02:12:15.635211 : kjbdowncvt[0x15c91.1 76896.0][1][options x0] 2012-05-02 02:12:15.635230 : GSIPC:AMBUF: rcv buff 0x7f16e1c56420, pool rcvbuf, rqlen 1103 2012-05-02 02:12:15.635308 : GSIPC:GPBMSG: new bmsg 0x7f16e1c56490 mb 0x7f16e1c56420 msg 0x7f16e1c564b0 mlen 152 dest x101 flushsz -1 2012-05-02 02:12:15.635334 : kjbmslset(0x15c91.1)) seq 0x4 reqid=0x6 (shadow 0xb48bb330.xb)(rsn 2)(mas@1) 2012-05-02 02:12:15.635355 : GSIPC:SPBMSG: send bmsg 0x7f16e1c56490 blen 184 msg 0x7f16e1c564b0 mtype 33 attr|dest x30101 bsz|fsz x1ffff 2012-05-02 02:12:15.635377 : GSIPC:SNDQ: enq msg 0x7f16e1c56490, type 65521 seq 118669, inst 1, receiver 1, queued 1 *** 2012-05-02 02:12:15.635 kclccctx: cleanup copy 0x7f16e1d94798 2012-05-02 02:12:15.635479 : [kjmpmsgi:compl][type 36][msg 0x7f16e1598588][seq 177740.0][qtime 0][ptime 1257] 2012-05-02 02:12:15.635511 : GSIPC:BSEND: flushing sndq 0xb491dd28, id 1, dcx 0xbc516778, inst 1, rcvr 1 qlen 0 1 2012-05-02 02:12:15.635536 : GSIPC:BSEND: no batch1 msg 0x7f16e1c56490 type 65521 len 184 dest (1:1) 2012-05-02 02:12:15.635557 : kjbsentscn[0x0.1ae0f1][to 1] 2012-05-02 02:12:15.635578 : GSIPC:SENDM: send msg 0x7f16e1c56490 dest x10001 seq 118669 type 65521 tkts x10002 mlen xb800e8 WAIT #0: nam='gcs remote message' ela= 180 waittime=1 poll=0 event=0 obj#=0 tim=1335939135635819 2012-05-02 02:12:15.635853 : GSIPC:RCVD: ksxp msg 0x7f16e167e0b0 sndr 1 seq 0.177741 type 32 tkts 0 2012-05-02 02:12:15.635875 : GSIPC:RCVD: watq msg 0x7f16e167e0b0 sndr 1, seq 177741, type 32, tkts 0 2012-05-02 02:12:15.636012 : GSIPC:TKT: collect msg 0x7f16e167e0b0 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.636040 : kjbrcvdscn[0x0.1ae0f1][from 1][idx 2012-05-02 02:12:15.636060 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f1][from 1] 2012-05-02 02:12:15.636082 : GSIPC:TKT: dest (1:1) rtkt not acked 1  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:12:15.636102 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:12:15.636125 : [kjmxmpm][type 32][seq 0.177741][msg 0x7f16e167e0b0][from 1] 2012-05-02 02:12:15.636146 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23a,(client 0x9fff7b58,0x1)(from 1)(lseq xdf0) 2????LMS????????? ??gcs remote message GSIPC ????SCN=[0x0.1ae0f0] block=1/89233???,??BAST kjbmpbast(0x15c91.1),?? block=1/89233??????? ??fairness??(?11.2.0.3???_fairness_threshold=2),?current block?KCL: F156: fairness downconvert,?Xcurrent DownConvert? Scurrent: Instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 2 0 3 1756658 ??Instance 2 LMS ?cr block??? kjbmslset(0x15c91.1)) ????SEND QUEUE GSIPC:SNDQ: enq msg 0x7f16e1c56490? ???????Instance 1???? block: (1/89233)??? ??????: Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29273 437 Instance 1 session A: SQL> SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761942 3 1761932 1 0 3 1761520 Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29274 437 select * from test END OF STMT PARSE #140336529675592:c=0,e=337,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940051 EXEC #140336529675592:c=0,e=96,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940204 WAIT #140336529675592: nam='SQL*Net message to client' ela= 5 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939668940348 *** 2012-05-02 02:21:08.940 kclscrs: req=0 block=1/89233 2012-05-02 02:21:08.940676 : kjbcro[0x15c91.1 76896.0][5] *** 2012-05-02 02:21:08.940 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:21:08.940 kclscrs: bid=1:3:1:0:f:21:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1f:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:17:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:21:08.940799 : kjbcro[0x15c91.1 76896.0][5] 2012-05-02 02:21:08.940833 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:21:08.940859 : kjbsentscn[0x0.1ae28c][to 2] 2012-05-02 02:21:08.940870 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177810 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:21:08.940976 : kjbmscr(0x15c91.1)reqid=0xa(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:21:08.941314 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:21:08.941 kclwcrs: wait=0 tm=707 *** 2012-05-02 02:21:08.941 kclwcrs: got 1 blocks from ksxprcv 2012-05-02 02:21:08.941818 : kjbassume[0x15c91.1][sender 2][mymode x1][myrole x0][srole x0][flgs x0][spiscn 0x0.0][swscn 0x0.0] 2012-05-02 02:21:08.941852 : kjbrcvdscn[0x0.1ae28d][from 2][idx 2012-05-02 02:21:08.941871 : kjbrcvdscn[no bscn ??????????????SCN=[0x0.1ae28c]=1761932 Version?CR block, ????receive????Xcurrent Block??SCN=1ae28d=1761933,Instance 1???Xcurrent Block???build????????SCN=1761932?CR BLOCK, ????????Current block,?????????'gc current block 2-way'? ?????????????request current block,?????kjbcro;?????Instance 2?LMS???????Current Block: Instance 2 LMS trace: 2012-05-02 02:21:08.448743 : GSIPC:RCVD: ksxp msg 0x7f16e14a4398 sndr 1 seq 0.177810 type 36 tkts 0 2012-05-02 02:21:08.448778 : GSIPC:RCVD: watq msg 0x7f16e14a4398 sndr 1, seq 177810, type 36, tkts 0 2012-05-02 02:21:08.448798 : GSIPC:TKT: collect msg 0x7f16e14a4398 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.448816 : kjbrcvdscn[0x0.1ae28c][from 1][idx 2012-05-02 02:21:08.448834 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28c][from 1] 2012-05-02 02:21:08.448857 : GSIPC:TKT: dest (1:1) rtkt not acked 2  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.448875 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.448970 : [kjmxmpm][type 36][seq 0.177810][msg 0x7f16e14a4398][from 1] 2012-05-02 02:21:08.448993 : kjbmpbast(0x15c91.1) reqid=0x6 (req 0xa4ff30f8)(reqinst 1)(reqid 10)(flags x0) *** 2012-05-02 02:21:08.449 kclcrrf: req=48054 block=1/89233 *** 2012-05-02 02:21:08.449 kcl_compress_block: compressed: 6 free space: 7680 2012-05-02 02:21:08.449085 : kjbsentscn[0x0.1ae28d][to 1] 2012-05-02 02:21:08.449142 : kjbdeliver[to 1][0xa4ff30f8][10][current 1] 2012-05-02 02:21:08.449164 : kjbmssch(reqlock 0xa4ff30f8,10)(to 1)(bsz 344) 2012-05-02 02:21:08.449183 : GSIPC:AMBUF: rcv buff 0x7f16e18bcec8, pool rcvbuf, rqlen 1102 *** 2012-05-02 02:21:08.449 kclccctx: cleanup copy 0x7f16e1d94838 *** 2012-05-02 02:21:08.449 kcltouched: touch seconds 3271 *** 2012-05-02 02:21:08.449 kclgrantlk: req=48054 2012-05-02 02:21:08.449347 : [kjmpmsgi:compl][type 36][msg 0x7f16e14a4398][seq 177810.0][qtime 0][ptime 1119] WAIT #0: nam='gcs remote message' ela= 568 waittime=1 poll=0 event=0 obj#=0 tim=1335939668449962 2012-05-02 02:21:08.450001 : GSIPC:RCVD: ksxp msg 0x7f16e1bb22a0 sndr 1 seq 0.177811 type 32 tkts 0 2012-05-02 02:21:08.450024 : GSIPC:RCVD: watq msg 0x7f16e1bb22a0 sndr 1, seq 177811, type 32, tkts 0 2012-05-02 02:21:08.450043 : GSIPC:TKT: collect msg 0x7f16e1bb22a0 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.450060 : kjbrcvdscn[0x0.1ae28e][from 1][idx 2012-05-02 02:21:08.450078 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28e][from 1] 2012-05-02 02:21:08.450097 : GSIPC:TKT: dest (1:1) rtkt not acked 3  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.450116 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.450136 : [kjmxmpm][type 32][seq 0.177811][msg 0x7f16e1bb22a0][from 1] 2012-05-02 02:21:08.450155 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23e,(client 0x9fff7b58,0x1)(from 1)(lseq xdf4) ???Instance 2??LMS???,???build cr block,??????Instance 1?????Current Block??????Instance 2??v$cr_block_server??????LIGHT_WORKS?????current block transfer??????,??????? CR server? Light Work Rule(Light Work Rule?8i Cr Server?????????,?Remote LMS?? build CR????????,resource holder?LMS???????block,????CR build If creating the consistent read version block involves too much work (such as reading blocks from disk), then the holder sends the block to the requestor, and the requestor completes the CR fabrication. The holder maintains a fairness counter of CR requests. After the fairness threshold is reached, the holder downgrades it to lock mode.)? ??????? CR Request ????Current Block?? ???:??????class?block,CR server??????? ??undo block?? undo header block?CR quest, LMS????Current Block, ????? ???? ??????? block cleanout? CR  Version??????? ???????? data blocks, ??????? CR quest  & CR received?(???????Light Work Rule,LMS"??"), ??Current Block??DownConvert???S lock,??LMS???????ship??current version?block? ??????? , ?????? ,???????DownConvert?????”_fairness_threshold“???200,????Xcurrent Block?????Scurrent, ????LMS?????Current Version?Data Block: SQL> show parameter fair NAME TYPE VALUE ------------------------------------ ----------- ------------------------------ _fairness_threshold integer 200 Instance 1: SQL> update test set id=id+1 where id=4; 1 row updated. Instance 2: SQL> update test set id=id+1 where id=2; 1 row updated. SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1838166 ?Instance 1? ????,? ??instance 2? v$cr_block_server?? instance 1 SQL> select * from test; ID ---------- 10 3 instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 SQL> select * from test; ID ---------- 10 3 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 ................... SQL> / STATE CR_SCN_BAS ---------- ---------- 2 0 3 1883707 3 1883695 repeat cr request on Instance 1 SQL> / STATE CR_SCN_BAS ---------- ---------- 8 0 3 1883707 3 1883695 ??????_fairness_threshold????????,?????200 ????????CR serve??Downgrade?lock, ????data block? CR Request????Receive? Current Block?

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  • Paying by Cash

    - by David Dorf
    I'll grant you paying by cash in the context of stores isn't particularly interesting, but in my quest to try new payment methods I decided to pay by cash at an online store. Using a credit card means I have to hoist myself off the couch, find the card, and enter all those digits. Google Checkout certainly makes that task easier by storing my credit card information, but what happens to all those people that don't have a credit card? What about the ones that are afraid to use credit cards over the internet. There are three main options for cash payment, not all of which are accepted by every merchant. The most popular is PayPal. The issue I have with them is that returns and disputes have to be handled with PayPal, not the merchant. I once used PayPal at a shady online store and lost my money. Yeah, my bad but they wouldn't help me at all. PayPal was purchased by eBay in 2002. BillMeLater is best for larger purchases, because at checkout they actually run a credit check to make sure you're credit worthy. Assuming you are, they pay the merchant on your behalf and mail you a bill, which you better pay quickly or interest will start to accrue. That's nice for the merchant because they get paid right away, and I presume there's no charge-backs. BillMeLater was purchased by eBay in 2008. Last night I tried eBillMe for the first time. After checkout, they send you a bill via email and expect you to pay either via online banking (they provide the instructions to set everything up) or walk-in locations across the US (typically banks). The process was quick and easy. The merchant doesn't ship the product until the bill is paid, so there's a day or two delay. For the merchant there are no charge-backs, and the fees are less than credit cards. For the shopper, they provide buyer protection similar to that offered by credit cards, and 1% cashback on purchases. Once the online bill-pay is setup, its easy to reuse in the future. Seems like a win-win for merchants and shoppers.

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