negative number - Page 215

How to Add Your Gmail Account to Outlook 2013 Using IMAP

- by Lori Kaufman

If you use Outlook to check and manage your email, you can easily use it to check your Gmail account as well. You can setup your Gmail account to allow you to synchronize email across multiple machines using email clients instead of a browser. We will show you how to use IMAP in your Gmail account so you can synchronize your Gmail account across multiple machines, and then how to add your Gmail account to Outlook 2013. To setup your Gmail account to use IMAP, sign in to your Gmail account and go to Mail. Click the Settings button in the upper, right corner of the window and select Settings from the drop-down menu. On the Settings screen, click Forwarding and POP/IMAP. Scroll down to the IMAP Access section and select Enable IMAP. Click Save Changes at the bottom of the screen. Close your browser and open Outlook. To begin adding your Gmail account, click the File tab. On the Account Information screen, click Add Account. On the Add Account dialog box, you can choose the E-mail Account option which automatically sets up your Gmail account in Outlook. To do this enter your name, email address, and the password for your Gmail account twice. Click Next. The progress of the setup displays. The automatic process may or may not work. If the automatic process fails, select Manual setup or additional server types, instead of E-mail Account, and click Next. On the Choose Service screen, select POP or IMAP and click Next. On the POP and IMAP Account Settings enter the User, Server, and Logon Information. For the Server Information, select IMAP from the Account Type drop-down list and enter the following for the incoming and outgoing server information: Incoming mail server: imap.googlemail.com Outgoing mail server (SMTP): smtp.googlemail.com Make sure you enter your full email address for the User Name and select Remember password if you want Outlook to automatically log you in when checking email. Click More Settings. On the Internet E-mail Settings dialog box, click the Outgoing Server tab. Select the My outgoing server (SMTP) requires authentication and make sure the Use same settings as my incoming mail server option is selected. While still in the Internet E-mail Settings dialog box, click the Advanced tab. Enter the following information: Incoming server: 993 Incoming server encrypted connection: SSL Outgoing server encrypted connection TLS Outgoing server: 587 NOTE: You need to select the type of encrypted connection for the outgoing server before entering 587 for the Outgoing server (SMTP) port number. If you enter the port number first, the port number will revert back to port 25 when you change the type of encrypted connection. Click OK to accept your changes and close the Internet E-mail Settings dialog box. Click Next. Outlook tests the accounts settings by logging into the incoming mail server and sending a test email message. When the test is finished, click Close. You should see a screen saying “You’re all set!”. Click Finish. Your Gmail address displays in the account list on the left with any other email addresses you have added to Outlook. Click the Inbox to see what’s in your Inbox in your Gmail account. Because you’re using IMAP in your Gmail account and you used IMAP to add the account to Outlook, the messages and folders in Outlook reflect what’s in your Gmail account. Any changes you make to folders and any time you move email messages among folders in Outlook, the same changes are made in your Gmail account, as you will see when you log into your Gmail account in a browser. This works the other way as well. Any changes you make to the structure of your account (folders, etc.) in a browser will be reflected the next time you log into your Gmail account in Outlook.

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Anatomy of a .NET Assembly - Signature encodings

- by Simon Cooper

If you've just joined this series, I highly recommend you read the previous posts in this series, starting here, or at least these posts, covering the CLR metadata tables. Before we look at custom attribute encoding, we first need to have a brief look at how signatures are encoded in an assembly in general. Signature types There are several types of signatures in an assembly, all of which share a common base representation, and are all stored as binary blobs in the #Blob heap, referenced by an offset from various metadata tables. The types of signatures are: Method definition and method reference signatures. Field signatures Property signatures Method local variables. These are referenced from the StandAloneSig table, which is then referenced by method body headers. Generic type specifications. These represent a particular instantiation of a generic type. Generic method specifications. Similarly, these represent a particular instantiation of a generic method. All these signatures share the same underlying mechanism to represent a type Representing a type All metadata signatures are based around the ELEMENT_TYPE structure. This assigns a number to each 'built-in' type in the framework; for example, Uint16 is 0x07, String is 0x0e, and Object is 0x1c. Byte codes are also used to indicate SzArrays, multi-dimensional arrays, custom types, and generic type and method variables. However, these require some further information. Firstly, custom types (ie not one of the built-in types). These require you to specify the 4-byte TypeDefOrRef coded token after the CLASS (0x12) or VALUETYPE (0x11) element type. This 4-byte value is stored in a compressed format before being written out to disk (for more excruciating details, you can refer to the CLI specification). SzArrays simply have the array item type after the SZARRAY byte (0x1d). Multidimensional arrays follow the ARRAY element type with a series of compressed integers indicating the number of dimensions, and the size and lower bound of each dimension. Generic variables are simply followed by the index of the generic variable they refer to. There are other additions as well, for example, a specific byte value indicates a method parameter passed by reference (BYREF), and other values indicating custom modifiers. Some examples... To demonstrate, here's a few examples and what the resulting blobs in the #Blob heap will look like. Each name in capitals corresponds to a particular byte value in the ELEMENT_TYPE or CALLCONV structure, and coded tokens to custom types are represented by the type name in curly brackets. A simple field: int intField; FIELD I4 A field of an array of a generic type parameter (assuming T is the first generic parameter of the containing type): T[] genArrayField FIELD SZARRAY VAR 0 An instance method signature (note how the number of parameters does not include the return type): instance string MyMethod(MyType, int&, bool[][]); HASTHIS DEFAULT 3 STRING CLASS {MyType} BYREF I4 SZARRAY SZARRAY BOOLEAN A generic type instantiation: MyGenericType<MyType, MyStruct> GENERICINST CLASS {MyGenericType} 2 CLASS {MyType} VALUETYPE {MyStruct} For more complicated examples, in the following C# type declaration: GenericType<T> : GenericBaseType<object[], T, GenericType<T>> { ... } the Extends field of the TypeDef for GenericType will point to a TypeSpec with the following blob: GENERICINST CLASS {GenericBaseType} 3 SZARRAY OBJECT VAR 0 GENERICINST CLASS {GenericType} 1 VAR 0 And a static generic method signature (generic parameters on types are referenced using VAR, generic parameters on methods using MVAR): TResult[] GenericMethod<TInput, TResult>( TInput, System.Converter<TInput, TOutput>); GENERIC 2 2 SZARRAY MVAR 1 MVAR 0 GENERICINST CLASS {System.Converter} 2 MVAR 0 MVAR 1 As you can see, complicated signatures are recursively built up out of quite simple building blocks to represent all the possible variations in a .NET assembly. Now we've looked at the basics of normal method signatures, in my next post I'll look at custom attribute application signatures, and how they are different to normal signatures.

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Some Original Expressions

- by Phil Factor

Guest Editorial for Simple-Talk newsletterIn a guest editorial for the Simple-Talk Newsletter, Phil Factor wonders if we are still likely to find some more novel and unexpected ways of using the newer features of Transact SQL: or maybe in some features that have always been there! There can be a great deal of fun to be had in trying out recent features of SQL Expressions to see if they provide new functionality. It is surprisingly rare to find things that couldn’t be done before, but in a different and more cumbersome way; but it is great to experiment or to read of someone else making that discovery. One such recent feature is the ‘table value constructor’, or ‘VALUES constructor’, that managed to get into SQL Server 2008 from Standard SQL. This allows you to create derived tables of up to 1000 rows neatly within select statements that consist of lists of row values. E.g. SELECT Old_Welsh, number FROM (VALUES ('Un',1),('Dou',2),('Tri',3),('Petuar',4),('Pimp',5),('Chwech',6),('Seith',7),('Wyth',8),('Nau',9),('Dec',10)) AS WelshWordsToTen (Old_Welsh, number) These values can be expressions that return single values, including, surprisingly, subqueries. You can use this device to create views, or in the USING clause of a MERGE statement. Joe Celko covered this here and here. It can become extraordinarily handy to use once one gets into the way of thinking in these terms, and I’ve rewritten a lot of routines to use the constructor, but the old way of using UNION can be used the same way, but is a little slower and more long-winded. The use of scalar SQL subqueries as an expression in a VALUES constructor, and then applied to a MERGE, has got me thinking. It looks very clever, but what use could one put it to? I haven’t seen anything yet that couldn’t be done almost as simply in SQL Server 2000, but I’m hopeful that someone will come up with a way of solving a tricky problem, just in the same way that a freak of the XML syntax forever made the in-line production of delimited lists from an expression easy, or that a weird XML pirouette could do an elegant pivot-table rotation. It is in this sort of experimentation where the community of users can make a real contribution. The dissemination of techniques such as the Number, or Tally table, or the unconventional ways that the UPDATE statement can be used, has been rapid due to articles and blogs. However, there is plenty to be done to explore some of the less obvious features of Transact SQL. Even some of the features introduced into SQL Server 2000 are hardly well-known. Certain operations on data are still awkward to perform in Transact SQL, but we mustn’t, I think, be too ready to state that certain things can only be done in the application layer, or using a CLR routine. With the vast array of features in the product, and with the tools that surround it, I feel that there is generally a way of getting tricky things done. Or should we just stick to our lasts and push anything difficult out into procedural code? I’d love to know your views.

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Enterprise Integration: Can Companies Afford It?

- by Ralph Wheaton

Each year, my company holds a global sales conference where employees and partners from around the world some together to collaborate, share knowledge and ideas and learn about future plans. As a member of the professional services division, several of us had been asked to make a presentation, an elevator pitch in 3 minutes or less that relates to a success we have worked on or directly relates to our tag (that is, our primary technology focus). Mine happens to be Enterprise Integration as it relates Business Intelligence. I found it rather difficult to present that pitch in a short amount of time and had to pare it down. At any rate, in just a little over 3 minutes, this is the presentation I submitted. Here is a link to the full presentation video in WMV format. Many companies today subscribe to a buy versus build mentality in an attempt to drive down costs and improve time to implementation. Sometimes this makes sense, especially as it relates to specialized software or software that performs a small number of tasks extremely well. However, if not carefully considered or planned out, this oftentimes leads to multiple disparate systems with silos of data or multiple versions of the same data. For instance, client data (contact information, addresses, phone numbers, opportunities, sales) stored in your CRM system may not play well with Accounts Receivables. Employee data may be stored across multiple systems such as HR, Time Entry and Payroll. Other data (such as member data) may not originate internally, but be provided by multiple outside sources in multiple formats. And to top it all off, some data may have to be manually entered into multiple systems to keep it all synchronized. When left to grow out of control like this, overall performance is lacking, stability is questionable and maintenance is frequent and costly. Worse yet, in many cases, this topology, this hodgepodge of data creates a reporting nightmare. Decision makers are forced to try to put together pieces of the puzzle attempting to find the information they need, wading through multiple systems to find what they think is the single version of the truth. More often than not, they find they are missing pieces, pieces that may be crucial to growing the business rather than closing the business. across applications. Master data owners are defined to establish single sources of data (such as the CRM system owns client data). Other systems subscribe to the master data and changes are replicated to subscribers as they are made. This can be one way (no changes are allowed on the subscriber systems) or bi-directional. But at all times, the master data owner is current or up to date. And all data, whether internal or external, use the same processes and methods to move data from one place to another, leveraging the same validations, lookups and transformations enterprise wide, eliminating inconsistencies and siloed data. Once implemented, an enterprise integration solution improves performance and stability by reducing the number of moving parts and eliminating inconsistent data. Overall maintenance costs are mitigated by reducing touch points or the number of places that require modification when a business rule is changed or another data element is added. Most importantly, however, now decision makers can easily extract and piece together the information they need to grow their business, improve customer satisfaction and so on. So, in implementing an enterprise integration solution, companies can position themselves for the future, allowing for easy transition to data marts, data warehousing and, ultimately, business intelligence. Along this path, companies can achieve growth in size, intelligence and complexity. Truly, the question is not can companies afford to implement an enterprise integration solution, but can they afford not to. Ralph Wheaton Microsoft Certified Technology Specialist Microsoft Certified Professional Developer Microsoft VTS-P BizTalk, .Net

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MPI Cluster Debugger launch integration in VS2010

Let's assume that you have all the HPC bits installed and that you have existing MPI code (or you created a "Hello World" project using the MPI project template). Of course, you create a single MPI application and at runtime it will correspond to multiple processes (of the same app) launched on multiple nodes (i.e. machines) on the cluster. So how do you debug such a situation by simply hitting the familiar "F5" keystroke (i.e. Debug - Start Debugging)?WATCH IT INSTEAD OF READING ABOUT ITIf you can't bear to read through all the details below, just watch this 19-minute screencast explaining this VS2010 feature. Alternatively, or even additionally, keep on reading.REQUIREMENTWhen you debug an MPI application, you would want the copying of resources from your client machine (where Visual Studio is installed) to each compute node (where Windows HPC Server is installed) to take place automatically for you. 'Resources' in the previous sentence includes your application binary, plus any binary or data dependencies it may have, plus PDBs if needed, plus the debug CRT of the correct bitness, plus msvsmon for remote debugging to work. You would also want, after copying is complete, to have your app and msvsmon launched and attached so that you can hit breakpoints back in Visual Studio on your client machine. All these thing that you would want are delivered in VS2010.STEPS TO F51. In your MPI project where you have placed a breakpoint go to Project Properties - Configuration Properties - Debugging. Ensure the "Debugger to launch" combo box value is set to MPI Cluster Debugger.2. There are a whole bunch of properties here and typically you can ignore all of them except one: Run Environment. By default it is set to run 1 process on your local machine and if you change the number after that to, for example, 4 it will launch 4 processes of your app on your local machine.You want this to run on your cluster though, so go to the dropdown arrow at the end of the Run Environment cell and open it to expose the "Edit Hpc node" menu which opens the Node Selector dialog:In this dialog you can enter (or pick from a list) the cluster head node name and then the number of processes you want to execute on the cluster and then hit OK and… you are done.3. Press F5 and watch your breakpoint get hit (after giving it some time for copying, remote execution, attachment and symbol resolution to take place).GOING DEEPERIn the MPI Cluster Debugger project properties above, you can see many additional properties to the Run Environment. They are all optional, but you may want to understand them in order to fine tune your cluster debugging. Read all about each one of these on the MSDN page Configuration Properties for the MPI Cluster Debugger.In the Node Selector dialog above you can see more options than just the Head Node name and Number of Process to run. They should be self-explanatory but I also cover them in depth in my screencast showing you an example of why you would choose to schedule processes per core versus per node. You can also read about these options on MSDN as part of the page How to: Configure and Launch the MPI Cluster Debugger.To read through an example that touches on MPI project creation, project properties, node selector, and also usage of MPI with OpenMP plus MPI with PPL, read the MSDN page Walkthrough: Launching the MPI Cluster Debugger in Visual Studio 2010.Happy MPI debugging! Comments about this post welcome at the original blog.

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Tuning Default WorkManager - Advantages and Disadvantages

- by Murali Veligeti

Before discussing on Tuning Default WorkManager, lets have a brief introduction on What is Default WorkManger Before Weblogic Server 9.0 release, we had the concept of Execute Queues. WebLogic Server (before WLS 9.0), processing was performed in multiple execute queues. Different classes of work were executed in different queues, based on priority and ordering requirements, and to avoid deadlocks. In addition to the default execute queue, weblogic.kernel.default, there were pre-configured queues dedicated to internal administrative traffic, such as weblogic.admin.HTTP and weblogic.admin.RMI.Users could control thread usage by altering the number of threads in the default queue, or configure custom execute queues to ensure that particular applications had access to a fixed number of execute threads, regardless of overall system load. From WLS 9.0 release onwards WebLogic Server uses is a single thread pool (single thread pool which is called Default WorkManager), in which all types of work are executed. WebLogic Server prioritizes work based on rules you define, and run-time metrics, including the actual time it takes to execute a request and the rate at which requests are entering and leaving the pool.The common thread pool changes its size automatically to maximize throughput. The queue monitors throughput over time and based on history, determines whether to adjust the thread count. For example, if historical throughput statistics indicate that a higher thread count increased throughput, WebLogic increases the thread count. Similarly, if statistics indicate that fewer threads did not reduce throughput, WebLogic decreases the thread count. This new strategy makes it easier for administrators to allocate processing resources and manage performance, avoiding the effort and complexity involved in configuring, monitoring, and tuning custom executes queues. The Default WorkManager is used to handle thread management and perform self-tuning.This Work Manager is used by an application when no other Work Managers are specified in the application’s deployment descriptors. In many situations, the default Work Manager may be sufficient for most application requirements. WebLogic Server’s thread-handling algorithms assign each application its own fair share by default. Applications are given equal priority for threads and are prevented from monopolizing them. The default work-manager, as its name tells, is the work-manager defined by default.Thus, all applications deployed on WLS will use it. But sometimes, when your application is already in production, it's obvious you can't take your EAR / WAR, update the deployment descriptor(s) and redeploy it.The default work-manager belongs to a thread-pool, as initial thread-pool comes with only five threads, that's not much. If your application has to face a large number of hits, you may want to start with more than that.Well, that's quite easy. You have two option to do so.1) Modify the config.xmlJust add the following line(s) in your server definition : <server> <name>AdminServer</name> <self-tuning-thread-pool-size-min>100</self-tuning-thread-pool-size-min> <self-tuning-thread-pool-size-max>200</self-tuning-thread-pool-size-max> [...] </server> 2) Adding some JVM parameters Add the following system property in setDomainEnv.sh/setDomainEnv.cmd or startWebLogic.sh/startWebLogic.cmd : -Dweblogic.threadpool.MinPoolSize=100 -Dweblogic.threadpool.MaxPoolSize=100 Reboot WLS and see the option has been taken into account . Disadvantage: So far its fine. But here there is an disadvantage in tuning Default WorkManager. Internally Weblogic Server has many work managers configured for different types of work. if we run out of threads in the self-tuning pool(because of system property -Dweblogic.threadpool.MaxPoolSize) due to being undersized, then important work that WLS might need to do could be starved. So, while limiting the self-tuning would limit the default WorkManager and internally it also limits all other internal WorkManagers which WLS uses.So the best alternative is to override the default WorkManager that means creating a WorkManager for the Application and assign the WorkManager for the application instead of tuning the Default WorkManager.

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Grid pathfinding with a lot of entities

- by Vee

I'd like to explain this problem with a screenshot from a released game, DROD: Gunthro's Epic Blunder, by Caravel Games. The game is turn-based and tile-based. I'm trying to create something very similar (a clone of the game), and I've got most of the fundamentals done, but I'm having trouble implementing pathfinding. Look at the screenshot. The guys in yellow are friendly, and want to kill the roaches. Every turn, every guy in yellow pathfinds to the closest roach, and every roach pathfinds to the closest guy in yellow. By closest I mean the target with the shortest path, not a simple distance calculation. All of this without any kind of slowdown when loading the level or when passing turns. And all of the entities change position every turn. Also (not shown in screenshot), there can be doors that open and close and change the level's layout. Impressive. I've tried implementing pathfinding in my clone. First attempt was making every roach find a path to a yellow guy every turn, using a breadth-first search algorithm. Obviously incredibly slow with more than a single roach, and would get exponentially slower with more than a single yellow guy. Second attempt was mas making every yellow guy generate a pathmap (still breadth-first search) every time he moved. Worked perfectly with multiple roaches and a single yellow guy, but adding more yellow guys made the game slow and unplayable. Last attempt was implementing JPS (jump point search). Every entity would individually calculate a path to its target. Fast, but with a limited number of entities. Having less than half the entities in the screenshot would make the game slow. And also, I had to get the "closest" enemy by calculating distance, not shortest path. I've asked on the DROD forums how they did it, and a user replied that it was breadth-first search. The game is open source, and I took a look at the source code, but it's C++ (I'm using C#) and I found it confusing. I don't know how to do it. Every approach I tried isn't good enough. And I believe that DROD generates global pathmaps, somehow, but I can't understand how every entity find the best individual path to other entities that move every turn. What's the trick? This is a reply I just got on the DROD forums: Without having looked at the code I'd wager it's two (or so) pathmaps for the whole room: One to the nearest enemy, and one to the nearest friendly for every tile. There's no need to make a separate pathmap for every entity when the overall goal is "move towards nearest enemy/friendly"... just mark every tile with the number of moves it takes to the nearest target and have the entity chose the move that takes it to the tile with the lowest number. To be honest, I don't understand it that well.

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Exploring TCP throughput with DTrace

- by user12820842

One key measure to use when assessing TCP throughput is assessing the amount of unacknowledged data in the pipe. This is sometimes termed the Bandwidth Delay Product (BDP) (note that BDP is often used more generally as the product of the link capacity and the end-to-end delay). In DTrace terms, the amount of unacknowledged data in bytes for the connection is the different between the next sequence number to send and the lowest unacknoweldged sequence number (tcps_snxt - tcps_suna). According to the theory, when the number of unacknowledged bytes for the connection is less than the receive window of the peer, the path bandwidth is the limiting factor for throughput. In other words, if we can fill the pipe without the peer TCP complaining (by virtue of its window size reaching 0), we are purely bandwidth-limited. If the peer's receive window is too small however, the sending TCP has to wait for acknowledgements before it can send more data. In this case the round-trip time (RTT) limits throughput. In such cases the effective throughput limit is the window size divided by the RTT, e.g. if the window size is 64K and the RTT is 0.5sec, the throughput is 128K/s. So a neat way to visually determine if the receive window of clients may be too small should be to compare the distribution of BDP values for the server versus the client's advertised receive window. If the BDP distribution overlaps the send window distribution such that it is to the right (or lower down in DTrace since quantizations are displayed vertically), it indicates that the amount of unacknowledged data regularly exceeds the client's receive window, so that it is possible that the sender may have more data to send but is blocked by a zero-window on the client side. In the following example, we compare the distribution of BDP values to the receive window advertised by the receiver (10.175.96.92) for a large file download via http. # dtrace -s tcp_tput.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 6 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 9 4096 | 14 8192 | 27 16384 | 67 32768 |@@ 1464 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 32396 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 16384 | 0 32768 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 17067 65536 | 0 Here we have a puzzle. We can see that the receiver's advertised window is in the 32768-65535 range, while the amount of unacknowledged data in the pipe is largely in the 65536-131071 range. What's going on here? Surely in a case like this we should see zero-window events, since the amount of data in the pipe regularly exceeds the window size of the receiver. We can see that we don't see any zero-window events since the SWND distribution displays no 0 values - it stays within the 32768-65535 range. The explanation is straightforward enough. TCP Window scaling is in operation for this connection - the Window Scale TCP option is used on connection setup to allow a connection to advertise (and have advertised to it) a window greater than 65536 bytes. In this case the scaling shift is 1, so this explains why the SWND values are clustered in the 32768-65535 range rather than the 65536-131071 range - the SWND value needs to be multiplied by two since the reciever is also scaling its window by a shift factor of 1. Here's the simple script that compares BDP and SWND distributions, fixed to take account of window scaling. #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::send / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @bdp["BDP(bytes)", args[2]-ip_daddr, args[4]-tcp_sport] = quantize(args[3]-tcps_snxt - args[3]-tcps_suna); } tcp:::receive / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @swnd["SWND(bytes)", args[2]-ip_saddr, args[4]-tcp_dport] = quantize((args[4]-tcp_window)*(1 tcps_snd_ws)); } And here's the fixed output. # dtrace -s tcp_tput_scaled.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 39 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 4 4096 | 9 8192 | 22 16384 | 37 32768 |@ 99 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 3858 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 512 | 0 1024 | 1 2048 | 0 4096 | 2 8192 | 4 16384 | 7 32768 | 14 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1956 131072 | 0

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Attending a Career Fair: “Don’t be shy – Be prepared”

- by jessica.ebbelaar

There are a large number of ways to interact with companies nowadays. The career fair is a very effective and personal way to interact with a number of different companies in a very short period of time. Here are some simple tips to help you perform during a career fair. Do research The key to being successful at a career fair is to do research before you go. Make a first selection of the companies you feel could be interesting for you. Include many types of employers. Once you have decided on the list of companies you want to visit, go to their career portal. Inform yourself about what the company does, i.e what roles there are available, how the company culture is described, what impression the testimonials give you. The question that you still have after reviewing this information, are the ones you can discuss with the company on the fair. Sell yourself Visit the companies you have on your top 5 list first, so you will be at your highest energy level to make that first impression. Think in advance about what you are going to tell the recruiter. Prepare a 30-second introduction (including degree, strengths, skills & experience) Be confident when you talk about your experience. Remember to start the conversation with a smile, make good eye contact and give a firm handshake. You could be speaking to your next manager, so be professional! If you already know what jobs you are interested in, relate your skills and experience to the roles that the company has available. If you are not yet sure gather as much information as you can about employment and/or hiring procedures, specific skills necessary for different jobs, training and career paths. Stand out As career fairs are very crowded and the attending companies meet with a lot of potential candidates on one day, you have to make sure you are noticed in a positive way. A good preparation and asking questions that show you have a good understanding of the industry, organization and roles will help you. Be aware of time demands on employers. Do not monopolize an employer's time. Dress appropriately to make a good first impression. Bring your resume Do not forget to bring your resume in print or on a USB-stick to the fair. If you are searching for different types of jobs, bring different versions of your resume. Your resume should be short and professional on white paper that is free of graphics or fancy print styles and containing larger margins for interviewer notes. Follow up After each conversation ask who you can contact for follow-up discussions about the specific roles. Use the back of a business card to record notes that help you remember important details and follow-up instructions. If no card is available, record the contact information and your comments in your notepad or phone. Last but not least, thank everyone you talk to for their time. Follow up as soon as possible with thank you notes that address the companies’ hiring needs, your qualifications, and express your desire for a second interview. What not to do… Do not visit a company with a group of friends. Interact with the companies on your own, to make your own positive impression. Do not walk up to a recruiter and interrupt a current conversation; wait your turn and be polite. What you should absolutely avoid is a grab and run on freebies! Take the time to speak to the company and ask for a freebie at the end of the conversation in case they are not offered to you. Good luck with the preparations for the career fair you will attend. Oracle recruiters look forward to meet you! They will be present on a large number of fairs in the region. For an overview of the fairs go to the Events & Calendar page on http://campus.oracle.com If you have any questions related to this article feel free to contact [email protected].

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Advanced Record-Level Business Intelligence with Inner Queries

- by gt0084e1

While business intelligence is generally applied at an aggregate level to large data sets, it's often useful to provide a more streamlined insight into an individual records or to be able to sort and rank them. For instance, a salesperson looking at a specific customer could benefit from basic stats on that account. A marketer trying to define an ideal customer could pull the top entries and look for insights or patterns. Inner queries let you do sophisticated analysis without the overhead of traditional BI or OLAP technologies like Analysis Services. Example - Order History Constancy Let's assume that management has realized that the best thing for our business is to have customers ordering every month. We'll need to identify and rank customers based on how consistently they buy and when their last purchase was so sales & marketing can respond accordingly. Our current application may not be able to provide this and adding an OLAP server like SSAS may be overkill for our needs. Luckily, SQL Server provides the ability to do relatively sophisticated analytics via inner queries. Here's the kind of output we'd like to see. Creating the Queries Before you create a view, you need to create the SQL query that does the calculations. Here we are calculating the total number of orders as well as the number of months since the last order. These fields might be very useful to sort by but may not be available in the app. This approach provides a very streamlined and high performance method of delivering actionable information without radically changing the application. It's also works very well with self-service reporting tools like Izenda. SELECT CustomerID,CompanyName, ( SELECT COUNT(OrderID) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID ) As Orders, DATEDIFF(mm, ( SELECT Max(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) ,getdate() ) AS MonthsSinceLastOrder FROM Customers Creating Views To turn this or any query into a view, just put CREATE VIEW AS before it. If you want to change it use the statement ALTER VIEW AS. Creating Computed Columns If you'd prefer not to create a view, inner queries can also be applied by using computed columns. Place you SQL in the (Formula) field of the Computed Column Specification or check out this article here. Advanced Scoring and Ranking One of the best uses for this approach is to score leads based on multiple fields. For instance, you may be in a business where customers that don't order every month require more persistent follow up. You could devise a simple formula that shows the continuity of an account. If they ordered every month since their first order, they would be at 100 indicating that they have been ordering 100% of the time. Here's the query that would calculate that. It uses a few SQL tricks to make this happen. We are extracting the count of unique months and then dividing by the months since initial order. This query will give you the following information which can be used to help sales and marketing now where to focus. You could sort by this percentage to know where to start calling or to find patterns describing your best customers. Number of orders First Order Date Last Order Date Percentage of months order was placed since last order. SELECT CustomerID, (SELECT COUNT(OrderID) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) As Orders, (SELECT Max(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) AS LastOrder, (SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) AS FirstOrder, DATEDIFF(mm,(SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID),getdate()) AS MonthsSinceFirstOrder, 100*(SELECT COUNT(DISTINCT 100*DATEPART(yy,OrderDate) + DATEPART(mm,OrderDate)) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) / DATEDIFF(mm,(SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID),getdate()) As OrderPercent FROM Customers

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How do you formulate the Domain Model in Domain Driven Design properly (Bounded Contexts, Domains)?

- by lko

Say you have a few applications which deal with a few different Core Domains. The examples are made up and it's hard to put a real example with meaningful data together (concisely). In Domain Driven Design (DDD) when you start looking at Bounded Contexts and Domains/Sub Domains, it says that a Bounded Context is a "phase" in a lifecycle. An example of Context here would be within an ecommerce system. Although you could model this as a single system, it would also warrant splitting into separate Contexts. Each of these areas within the application have their own Ubiquitous Language, their own Model, and a way to talk to other Bounded Contexts to obtain the information they need. The Core, Sub, and Generic Domains are the area of expertise and can be numerous in complex applications. Say there is a long process dealing with an Entity for example a Book in a core domain. Now looking at the Bounded Contexts there can be a number of phases in the books life-cycle. Say outline, creation, correction, publish, sale phases. Now imagine a second core domain, perhaps a store domain. The publisher has its own branch of stores to sell books. The store can have a number of Bounded Contexts (life-cycle phases) for example a "Stock" or "Inventory" context. In the first domain there is probably a Book database table with basically just an ID to track the different book Entities in the different life-cycles. Now suppose you have 10+ supporting domains e.g. Users, Catalogs, Inventory, .. (hard to think of relevant examples). For example a DomainModel for the Book Outline phase, the Creation phase, Correction phase, Publish phase, Sale phase. Then for the Store core domain it probably has a number of life-cycle phases. public class BookId : Entity { public long Id { get; set; } } In the creation phase (Bounded Context) the book could be a simple class. public class Book : BookId { public string Title { get; set; } public List<string> Chapters { get; set; } //... } Whereas in the publish phase (Bounded Context) it would have all the text, release date etc. public class Book : BookId { public DateTime ReleaseDate { get; set; } //... } The immediate benefit I can see in separating by "life-cycle phase" is that it's a great way to separate business logic so there aren't mammoth all-encompassing Entities nor Domain Services. A problem I have is figuring out how to concretely define the rules to the physical layout of the Domain Model. A. Does the Domain Model get "modeled" so there are as many bounded contexts (separate projects etc.) as there are life-cycle phases across the core domains in a complex application? Edit: Answer to A. Yes, according to the answer by Alexey Zimarev there should be an entire "Domain" for each bounded context. B. Is the Domain Model typically arranged by Bounded Contexts (or Domains, or both)? Edit: Answer to B. Each Bounded Context should have its own complete "Domain" (Service/Entities/VO's/Repositories) C. Does it mean there can easily be 10's of "segregated" Domain Models and multiple projects can use it (the Entities/Value Objects)? Edit: Answer to C. There is a complete "Domain" for each Bounded Context and the Domain Model (Entity/VO layer/project) isn't "used" by the other Bounded Contexts directly, only via chosen paths (i.e. via Domain Events). The part that I am trying to figure out is how the Domain Model is actually implemented once you start to figure out your Bounded Contexts and Core/Sub Domains, particularly in complex applications. The goal is to establish the definitions which can help to separate Entities between the Bounded Contexts and Domains.

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MPI Cluster Debugger launch integration in VS2010

Let's assume that you have all the HPC bits installed and that you have existing MPI code (or you created a "Hello World" project using the MPI project template). Of course, you create a single MPI application and at runtime it will correspond to multiple processes (of the same app) launched on multiple nodes (i.e. machines) on the cluster. So how do you debug such a situation by simply hitting the familiar "F5" keystroke (i.e. Debug - Start Debugging)?WATCH IT INSTEAD OF READING ABOUT ITIf you can't bear to read through all the details below, just watch this 19-minute screencast explaining this VS2010 feature. Alternatively, or even additionally, keep on reading.REQUIREMENTWhen you debug an MPI application, you would want the copying of resources from your client machine (where Visual Studio is installed) to each compute node (where Windows HPC Server is installed) to take place automatically for you. 'Resources' in the previous sentence includes your application binary, plus any binary or data dependencies it may have, plus PDBs if needed, plus the debug CRT of the correct bitness, plus msvsmon for remote debugging to work. You would also want, after copying is complete, to have your app and msvsmon launched and attached so that you can hit breakpoints back in Visual Studio on your client machine. All these thing that you would want are delivered in VS2010.STEPS TO F51. In your MPI project where you have placed a breakpoint go to Project Properties - Configuration Properties - Debugging. Ensure the "Debugger to launch" combo box value is set to MPI Cluster Debugger.2. There are a whole bunch of properties here and typically you can ignore all of them except one: Run Environment. By default it is set to run 1 process on your local machine and if you change the number after that to, for example, 4 it will launch 4 processes of your app on your local machine.You want this to run on your cluster though, so go to the dropdown arrow at the end of the Run Environment cell and open it to expose the "Edit Hpc node" menu which opens the Node Selector dialog:In this dialog you can enter (or pick from a list) the cluster head node name and then the number of processes you want to execute on the cluster and then hit OK and… you are done.3. Press F5 and watch your breakpoint get hit (after giving it some time for copying, remote execution, attachment and symbol resolution to take place).GOING DEEPERIn the MPI Cluster Debugger project properties above, you can see many additional properties to the Run Environment. They are all optional, but you may want to understand them in order to fine tune your cluster debugging. Read all about each one of these on the MSDN page Configuration Properties for the MPI Cluster Debugger.In the Node Selector dialog above you can see more options than just the Head Node name and Number of Process to run. They should be self-explanatory but I also cover them in depth in my screencast showing you an example of why you would choose to schedule processes per core versus per node. You can also read about these options on MSDN as part of the page How to: Configure and Launch the MPI Cluster Debugger.To read through an example that touches on MPI project creation, project properties, node selector, and also usage of MPI with OpenMP plus MPI with PPL, read the MSDN page Walkthrough: Launching the MPI Cluster Debugger in Visual Studio 2010.Happy MPI debugging! Comments about this post welcome at the original blog.

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Rotating WebLogic Server logs to avoid large files using WLST.

- by adejuanc

By default, when WebLogic Server instances are started in development mode, the server automatically renames (rotates) its local server log file as SERVER_NAME.log.n. For the remainder of the server session, log messages accumulate in SERVER_NAME.log until the file grows to a size of 500 kilobytes.Each time the server log file reaches this size, the server renames the log file and creates a new SERVER_NAME.log to store new messages. By default, the rotated log files are numbered in order of creation filenamennnnn, where filename is the name configured for the log file. You can configure a server instance to include a time and date stamp in the file name of rotated log files; for example, server-name-%yyyy%-%mm%-%dd%-%hh%-%mm%.log.By default, when server instances are started in production mode, the server rotates its server log file whenever the file grows to 5000 kilobytes in size. It does not rotate the local server log file when the server is started. For more information about changing the mode in which a server starts, see Change to production mode in the Administration Console Online Help.You can change these default settings for log file rotation. For example, you can change the file size at which the server rotates the log file or you can configure a server to rotate log files based on a time interval. You can also specify the maximum number of rotated files that can accumulate. After the number of log files reaches this number, subsequent file rotations delete the oldest log file and create a new log file with the latest suffix. Note: WebLogic Server sets a threshold size limit of 500 MB before it forces a hard rotation to prevent excessive log file growth. To Rotate via WLST : #invoke WLSTC:\>java weblogic.WLST#connect WLST to an Administration Serverawls:/offline> connect('username','password')#navigate to the ServerRuntime MBean hierarchywls:/mydomain/serverConfig> serverRuntime()wls:/mydomain/serverRuntime>ls()#navigate to the server LogRuntimeMBeanwls:/mydomain/serverRuntime> cd('LogRuntime/myserver')wls:/mydomain/serverRuntime/LogRuntime/myserver> ls()-r-- Name myserver-r-- Type LogRuntime-r-x forceLogRotation java.lang.Void :#force the immediate rotation of the server log filewls:/mydomain/serverRuntime/LogRuntime/myserver> cmo.forceLogRotation()wls:/mydomain/serverRuntime/LogRuntime/myserver> The server immediately rotates the file and prints the following message: <Mar 2, 2012 3:23:01 PM EST> <Info> <Log Management> <BEA-170017> <The log file C:\diablodomain\servers\myserver\logs\myserver.log will be rotated. Reopen the log file if tailing has stopped. This can happen on some platforms like Windows.><Mar 2, 2012 3:23:01 PM EST> <Info> <Log Management> <BEA-170018> <The log file has been rotated to C:\diablodomain\servers\myserver\logs\myserver.log00001. Log messages will continue to be logged in C:\diablodomain\servers\myserver\logs\myserver.log.> To specify the Location of the archived Log Files The following command specifies the directory location for the archived log files using the -Dweblogic.log.LogFileRotationDir Java startup option: java -Dweblogic.log.LogFileRotationDir=c:\foo-Dweblogic.management.username=installadministrator-Dweblogic.management.password=installadministrator weblogic.Server For more information read the following documentation ; Using the WebLogic Scripting Tool http://download.oracle.com/docs/cd/E13222_01/wls/docs103/config_scripting/using_WLST.html Configuring WebLogic Logging Services http://download.oracle.com/docs/cd/E12840_01/wls/docs103/logging/config_logs.html

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Know your Data Lineage

- by Simon Elliston Ball

An academic paper without the footnotes isn’t an academic paper. Journalists wouldn’t base a news article on facts that they can’t verify. So why would anyone publish reports without being able to say where the data has come from and be confident of its quality, in other words, without knowing its lineage. (sometimes referred to as ‘provenance’ or ‘pedigree’) The number and variety of data sources, both traditional and new, increases inexorably. Data comes clean or dirty, processed or raw, unimpeachable or entirely fabricated. On its journey to our report, from its source, the data can travel through a network of interconnected pipes, passing through numerous distinct systems, each managed by different people. At each point along the pipeline, it can be changed, filtered, aggregated and combined. When the data finally emerges, how can we be sure that it is right? How can we be certain that no part of the data collection was based on incorrect assumptions, that key data points haven’t been left out, or that the sources are good? Even when we’re using data science to give us an approximate or probable answer, we cannot have any confidence in the results without confidence in the data from which it came. You need to know what has been done to your data, where it came from, and who is responsible for each stage of the analysis. This information represents your data lineage; it is your stack-trace. If you’re an analyst, suspicious of a number, it tells you why the number is there and how it got there. If you’re a developer, working on a pipeline, it provides the context you need to track down the bug. If you’re a manager, or an auditor, it lets you know the right things are being done. Lineage tracking is part of good data governance. Most audit and lineage systems require you to buy into their whole structure. If you are using Hadoop for your data storage and processing, then tools like Falcon allow you to track lineage, as long as you are using Falcon to write and run the pipeline. It can mean learning a new way of running your jobs (or using some sort of proxy), and even a distinct way of writing your queries. Other Hadoop tools provide a lot of operational and audit information, spread throughout the many logs produced by Hive, Sqoop, MapReduce and all the various moving parts that make up the eco-system. To get a full picture of what’s going on in your Hadoop system you need to capture both Falcon lineage and the data-exhaust of other tools that Falcon can’t orchestrate. However, the problem is bigger even that that. Often, Hadoop is just one piece in a larger processing workflow. The next step of the challenge is how you bind together the lineage metadata describing what happened before and after Hadoop, where ‘after’ could be a data analysis environment like R, an application, or even directly into an end-user tool such as Tableau or Excel. One possibility is to push as much as you can of your key analytics into Hadoop, but would you give up the power, and familiarity of your existing tools in return for a reliable way of tracking lineage? Lineage and auditing should work consistently, automatically and quietly, allowing users to access their data with any tool they require to use. The real solution, therefore, is to create a consistent method by which to bring lineage data from these data various disparate sources into the data analysis platform that you use, rather than being forced to use the tool that manages the pipeline for the lineage and a different tool for the data analysis. The key is to keep your logs, keep your audit data, from every source, bring them together and use the data analysis tools to trace the paths from raw data to the answer that data analysis provides.

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Numbers not adding up? (What am I not understanding here?) [closed]

- by Milo

I have the following output: Short version: The last numbers on the S= lines increase by H and SHOULD theoretically be linearly decreasing, ex: -285,-290,-295...but the fourth one jumps to -252. Yet, every other number is linearly increasing. Why is that and how could I fix that? To explain the numbers, it comes from slider value changed. I have a slider whose value is used to generate the float on the next line. Everything should be growing linearly here. This value is used to determine the size of a flow layout and it is also used in conjunction with a scrollbar. But basically I have a background for the flow layout and that number is the start location for rendering it. The numbers should linearly change to create a smooth transition but when that one jumps, it looks weird on screen and I dont understand why the numbers are jumping every X slider value changes. Mathematically what could be causing this? Here is the code for rendering the background and the function that is called when value changes: void LobbyTableManager::renderBG( GraphicsContext* g, agui::Rectangle& absRect, agui::Rectangle& childRect ) { float scale = 0.35f; int w = m_bgSprite->getWidth() * getTableScale() * scale; int h = m_bgSprite->getHeight() * getTableScale() * scale; int numX = ceil(absRect.getWidth() / (float)w) + 2; int numY = ceil(absRect.getHeight() / (float)h) + 2; int startY = childRect.getY(); int numAttempts = 0; while(startY + h < absRect.getY() && numAttempts < 1000) { startY += h; if(moo) { std::cout << startY << ","; } numAttempts++; } g->holdDrawing(); for(int i = 0; i < numX; ++i) { for(int j = 0; j < numY; ++j) { g->drawScaledSprite(m_bgSprite,0,0,m_bgSprite->getWidth(),m_bgSprite->getHeight(), absRect.getX() + (i * w) + (offsetX),absRect.getY() + (j * h) + startY,w,h,0); } } g->unholdDrawing(); g->setClippingRect(cx,cy,cw,ch); } void LobbyTableManager::setTableScale( float scale ) { scale += 0.3f; scale *= 2.0f; float scrollRel = m_vScroll->getRelativeValue(); setScale(scale); rescaleTables(); resizeFlow(); updateScrollBars(); float newVal = scrollRel * m_vScroll->getMaxValue(); m_vScroll->setValue(newVal); } void LobbyTableManager::valueChanged( agui::VScrollBar* source,int val ) { m_flow->setLocation(0,-val); } Any insight on mathematically why the anomaly might happen every Nth time would be helpful. I just dont understand why if every number linearly increates it jumps from -295 to -252! Thanks

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E-Business Suite : Role of CHUNK_SIZE in Oracle Payroll

- by Giri Mandalika

Different batch processes in Oracle Payroll flow have the ability to spawn multiple child processes (or threads) to complete the work in hand. The number of child processes to fork is controlled by the THREADS parameter in APPS.PAY_ACTION_PARAMETERS view. THREADS parameter The default value for THREADS parameter is 1, which is fine for a single-processor system but not optimal for the modern multi-core multi-processor systems. Setting the THREADS parameter to a value equal to or less than the total number of [virtual] processors available on the system may improve the performance of payroll processing. However on the down side, since multiple child processes operate against the same set of payroll tables in HR schema, database may experience undesired consequences such as buffer busy waits and index contention, which results in giving up some of the gains achieved by using multiple child processes/threads to process the work. Couple of other action parameters, CHUNK_SIZE and CHUNK_SHUFFLE, help alleviate the database contention. eg., Set a value for THREADS parameter as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'THREADS'; COMMIT; (I am not aware of any maximum value for THREADS parameter) CHUNK_SIZE parameter The size of each commit unit for the batch process is controlled by the CHUNK_SIZE action parameter. In other words, chunking is the act of splitting the assignment actions into commit groups of desired size represented by the CHUNK_SIZE parameter. The default value is 20, and each thread processes one chunk at a time -- which means each child process inserts or processes 20 assignment actions at any time. When multiple threads are configured, each thread picks up a chunk to process, completes the assignment actions and then picks up another chunk. This is repeated until all the chunks are exhausted. It is possible to use different chunk sizes in different batch processes. During the initial phase of processing, CHUNK_SIZE number of assignment actions are inserted into relevant table(s). When multiple child processes are inserting data at the same time into the same set of tables, as explained earlier, database may experience contention. The default value of 20 is mostly optimal in such a case. Experiment with different values for the initial phase by +/-10 for CHUNK_SIZE parameter and observe the performance impact. A larger value may make sense during the main processing phase. Again experimentation is the key in finding the suitable value for your environment. Start with a large value such as 2000 for the chunk size, then increment or decrement the size by 500 at a time until an optimal value is found. eg., Set a value for CHUNK_SIZE parameter as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'CHUNK_SIZE'; COMMIT; CHUNK_SIZE action parameter accepts a value that is as low as 1 or as high as 16000. CHUNK SHUFFLE parameter By default, chunks of assignment actions are processed sequentially by all threads - which may not be a good thing especially given that all child processes/threads performing similar actions against the same set of tables almost at the same time. By saying not a good thing, I mean to say that the default behavior leads to contention in the database (in data blocks, for example). It is possible to relieve some of that database contention by randomizing the processing order of chunks of assignment actions. This behavior is controlled by the CHUNK SHUFFLE action parameter. Chunk processing is not randomized unless explicitly configured. eg., Set chunk shuffling as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = 'Y' WHERE PARAMETER_NAME = 'CHUNK SHUFFLE'; COMMIT; Finally I recommend checking the following document out for additional details and additional pay action tunable parameters that may speed up the processing of Oracle Payroll. My Oracle Support Doc ID: 226987.1 Oracle 11i & R12 Human Resources (HRMS) & Benefits (BEN) Tuning & System Health Checks Also experiment with different combinations of parameters and values until the right set of action parameters and values are found for your deployment.

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Ops Center 12c - Update - Provisioning Solaris on x86 Using a Card-Based NIC

- by scottdickson

Last week, I posted a blog describing how to use Ops Center to provision Solaris over the network via a NIC on a card rather than the built-in NIC. Really, that was all about how to install Solaris on a SPARC system. This week, we'll look at how to do the same thing for an x86-based server. Really, the overall process is exactly the same, at least for Solaris 11, with only minor updates. We will focus on Solaris 11 for this blog. Once I verify that the same approach works for Solaris 10, I will provide another update. Booting Solaris 11 on x86 Just as before, in order to configure the server for network boot across a card-based NIC, it is necessary to declare the asset to associate the additional MACs with the server. You likely will need to access the server console via the ILOM to figure out the MAC and to get a good idea of the network instance number. The simplest way to find both of these is to start a network boot using the desired NIC and see where it appears in the list of network interfaces and what MAC is used when it tries to boot. Go to the ILOM for the server. Reset the server and start the console. When the BIOS loads, select the boot menu, usually with Ctrl-P. This will give you a menu of devices to boot from, including all of the NICs. Select the NIC you want to boot from. Its position in the list is a good indication of what network number Solaris will give the device. In this case, we want to boot from the 5th interface (GB_4, net4). Pick it and start the boot processes. When it starts to boot, you will see the MAC address for the interface Once you have the network instance and the MAC, go through the same process of declaring the asset as in the SPARC case. This associates the additional network interface with the server.. Creating an OS Provisioning Plan The simplest way to do the boot via an alternate interface on an x86 system is to do a manual boot. Update the OS provisioning profile as in the SPARC case to reflect the fact that we are booting from a different interface. Update, in this case, the network boot device to be GB_4/net4, or the device corresponding to your network instance number. Configure the profile to support manual network boot by checking the box for manual boot in the OS Provisioning profile. Booting the System Once you have created a profile and plan to support booting from the additional NIC, we are ready to install the server. Again, from the ILOM, reset the system and start the console. When the BIOS loads, select boot from the Boot Menu as above. Select the network interface from the list as before and start the boot process. When the grub bootloader loads, the default boot image is the Solaris Text Installer. On the grub menu, select Automated Installer and Ops Center takes over from there. Lessons The key lesson from all of this is that Ops Center is a valuable tool for provisioning servers whether they are connected via built-in network interfaces or via high-speed NICs on cards. This is great news for modern datacenters using converged network infrastructures. The process works for both SPARC and x86 Solaris installations. And it's easy and repeatable.

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Creating a voxel world with 3D arrays using threads

- by Sean M.

I am making a voxel game (a bit like Minecraft) in C++(11), and I've come across an issue with creating a world efficiently. In my program, I have a World class, which holds a 3D array of Region class pointers. When I initialize the world, I give it a width, height, and depth so it knows how large of a world to create. Each Region is split up into a 32x32x32 area of blocks, so as you may guess, it takes a while to initialize the world once the world gets to be above 8x4x8 Regions. In order to alleviate this issue, I thought that using threads to generate different levels of the world concurrently would make it go faster. Having not used threads much before this, and being still relatively new to C++, I'm not entirely sure how to go about implementing one thread per level (level being a xz plane with a height of 1), when there is a variable number of levels. I tried this: for(int i = 0; i < height; i++) { std::thread th(std::bind(&World::load, this, width, height, depth)); th.join(); } Where load() just loads all Regions at height "height". But that executes the threads one at a time (which makes sense, looking back), and that of course takes as long as generating all Regions in one loop. I then tried: std::thread t1(std::bind(&World::load, this, w, h1, h2 - 1, d)); std::thread t2(std::bind(&World::load, this, w, h2, h3 - 1, d)); std::thread t3(std::bind(&World::load, this, w, h3, h4 - 1, d)); std::thread t4(std::bind(&World::load, this, w, h4, h - 1, d)); t1.join(); t2.join(); t3.join(); t4.join(); This works in that the world loads about 3-3.5 times faster, but this forces the height to be a multiple of 4, and it also gives the same exact VAO object to every single Region, which need individual VAOs in order to render properly. The VAO of each Region is set in the constructor, so I'm assuming that somehow the VAO number is not thread safe or something (again, unfamiliar with threads). So basically, my question is two one-part: How to I implement a variable number of threads that all execute at the same time, and force the main thread to wait for them using join() without stopping the other threads? How do I make the VAO objects thread safe, so when a bunch of Regions are being created at the same time across multiple threads, they don't all get the exact same VAO? Turns out it has to do with GL contexts not working across multiple threads. I moved the VAO/VBO creation back to the main thread. Fixed! Here is the code for block.h/.cpp, region.h/.cpp, and CVBObject.h/.cpp which controls VBOs and VAOs, in case you need it. If you need to see anything else just ask. EDIT: Also, I'd prefer not to have answers that are like "you should have used boost". I'm trying to do this without boost to get used to threads before moving onto other libraries.

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Cannot get ATI Drivers installed

- by bittoast67

I am trying to install the Catalyst driver. The best I can get is a strange resolution problem and firefox acts all wonkt. The worst I have gotten is low graphics mode in which I just reinstall Ubuntu. I have a HP Pavilion Dv7 laptop. With Radeon 3200 HD. I plan to try again with a fresh install of Ubuntu 12.4.3 as I have heard its the most compatible. This is what I have done: I have tried just the easy way of going to synaptic and installing the drivers that way. the fglrx package (not the fglrx update). And if memory serves I think that boots me into low graphics mode. So, fresh install of Ubuntu and tried again. I have done everything a couple times from this site (http://wiki.cchtml.com/index.php/Ubuntu_Precise_Installation_Guide) following every instruction to a T. That gets me something, such as a lowered fan speed and a much cooler computer, but I also lose most of my resolution. And displays says its the best resolution I can get. I also have a very screwy firefox. Using this method I can see AMD Catalyst Control Center in my dash (two of them really one administrator and one not) but when I try to open it it says no amd driver detected. So again, ubuntu reinstall. I have tried the GUI method from the Legacy driver I got from AMD's site. It runs through smoothly and at the very end after I exit the installer it gives me an error. I have also tried various other methods using terminal, as well as various different drivers (the one from the amd's site and the one suggested in the above link for my graphics card) both to no avail. When I try the method in the link on number 2, and I get the super low res and screwy fire fox. I type in, fglrxinfo ,and get a badrequest error. I have yet to type in fglrxinfo and get anything like what I am supposed to. UPDATE: I am now currently reinstalling Ubuntu 12.4. I tried the above mentioned link - thank you very much!- just to see on the previously failed driver attempt by following the purge commands. And to no avail when typing fglrxinfo I still get the badrequest thing. I will update again after a try with a true fresh install. Thanks again!! UPDATE: Alright everyone. Still no go. I have done everything word per word in the provided tutorial. I have rebooted my computer again to a fucked up resolution and this is what I get when typing fglrxinfo: $ fglrxinfo X Error of failed request: BadRequest (invalid request code or no such operation) Major opcode of failed request: 153 (GLX) Minor opcode of failed request: 19 (X_GLXQueryServerString) Serial number of failed request: 12 Current serial number in output stream: 12 I would like to add that when installing this file: fglrx_8.970-0ubuntu1_amd64.deb I got this: Building initial module for 3.8.0-29-generic Error! Bad return status for module build on kernel: 3.8.0-29-generic (x86_64) Consult /var/lib/dkms/fglrx/8.970/build/make.log for more information. update-initramfs: deferring update (trigger activated) Processing triggers for ureadahead ... Processing triggers for bamfdaemon ... Rebuilding /usr/share/applications/bamf.index... Processing triggers for initramfs-tools ... update-initramfs: Generating /boot/initrd.img-3.8.0-29-generic Processing triggers for libc-bin ... ldconfig deferred processing now taking place Any ideas? Anyone? I cant for the life of me figure out what I am doing wrong.

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Faster Memory Allocation Using vmtasks

- by Steve Sistare

You may have noticed a new system process called "vmtasks" on Solaris 11 systems: % pgrep vmtasks 8 % prstat -p 8 PID USERNAME SIZE RSS STATE PRI NICE TIME CPU PROCESS/NLWP 8 root 0K 0K sleep 99 -20 9:10:59 0.0% vmtasks/32 What is vmtasks, and why should you care? In a nutshell, vmtasks accelerates creation, locking, and destruction of pages in shared memory segments. This is particularly helpful for locked memory, as creating a page of physical memory is much more expensive than creating a page of virtual memory. For example, an ISM segment (shmflag & SHM_SHARE_MMU) is locked in memory on the first shmat() call, and a DISM segment (shmflg & SHM_PAGEABLE) is locked using mlock() or memcntl(). Segment operations such as creation and locking are typically single threaded, performed by the thread making the system call. In many applications, the size of a shared memory segment is a large fraction of total physical memory, and the single-threaded initialization is a scalability bottleneck which increases application startup time. To break the bottleneck, we apply parallel processing, harnessing the power of the additional CPUs that are always present on modern platforms. For sufficiently large segments, as many of 16 threads of vmtasks are employed to assist an application thread during creation, locking, and destruction operations. The segment is implicitly divided at page boundaries, and each thread is given a chunk of pages to process. The per-page processing time can vary, so for dynamic load balancing, the number of chunks is greater than the number of threads, and threads grab chunks dynamically as they finish their work. Because the threads modify a single application address space in compressed time interval, contention on locks protecting VM data structures locks was a problem, and we had to re-scale a number of VM locks to get good parallel efficiency. The vmtasks process has 1 thread per CPU and may accelerate multiple segment operations simultaneously, but each operation gets at most 16 helper threads to avoid monopolizing CPU resources. We may reconsider this limit in the future. Acceleration using vmtasks is enabled out of the box, with no tuning required, and works for all Solaris platform architectures (SPARC sun4u, SPARC sun4v, x86). The following tables show the time to create + lock + destroy a large segment, normalized as milliseconds per gigabyte, before and after the introduction of vmtasks: ISM system ncpu before after speedup ------ ---- ------ ----- ------- x4600 32 1386 245 6X X7560 64 1016 153 7X M9000 512 1196 206 6X T5240 128 2506 234 11X T4-2 128 1197 107 11x DISM system ncpu before after speedup ------ ---- ------ ----- ------- x4600 32 1582 265 6X X7560 64 1116 158 7X M9000 512 1165 152 8X T5240 128 2796 198 14X (I am missing the data for T4 DISM, for no good reason; it works fine). The following table separates the creation and destruction times: ISM, T4-2 before after ------ ----- create 702 64 destroy 495 43 To put this in perspective, consider creating a 512 GB ISM segment on T4-2. Creating the segment would take 6 minutes with the old code, and only 33 seconds with the new. If this is your Oracle SGA, you save over 5 minutes when starting the database, and you also save when shutting it down prior to a restart. Those minutes go directly to your bottom line for service availability.

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Using WKA in Large Coherence Clusters (Disabling Multicast)

- by jpurdy

Disabling hardware multicast (by configuring well-known addresses aka WKA) will place significant stress on the network. For messages that must be sent to multiple servers, rather than having a server send a single packet to the switch and having the switch broadcast that packet to the rest of the cluster, the server must send a packet to each of the other servers. While hardware varies significantly, consider that a server with a single gigabit connection can send at most ~70,000 packets per second. To continue with some concrete numbers, in a cluster with 500 members, that means that each server can send at most 140 cluster-wide messages per second. And if there are 10 cluster members on each physical machine, that number shrinks to 14 cluster-wide messages per second (or with only mild hyperbole, roughly zero). It is also important to keep in mind that network I/O is not only expensive in terms of the network itself, but also the consumption of CPU required to send (or receive) a message (due to things like copying the packet bytes, processing a interrupt, etc). Fortunately, Coherence is designed to rely primarily on point-to-point messages, but there are some features that are inherently one-to-many: Announcing the arrival or departure of a member Updating partition assignment maps across the cluster Creating or destroying a NamedCache Invalidating a cache entry from a large number of client-side near caches Distributing a filter-based request across the full set of cache servers (e.g. queries, aggregators and entry processors) Invoking clear() on a NamedCache The first few of these are operations that are primarily routed through a single senior member, and also occur infrequently, so they usually are not a primary consideration. There are cases, however, where the load from introducing new members can be substantial (to the point of destabilizing the cluster). Consider the case where cluster in the first paragraph grows from 500 members to 1000 members (holding the number of physical machines constant). During this period, there will be 500 new member introductions, each of which may consist of several cluster-wide operations (for the cluster membership itself as well as the partitioned cache services, replicated cache services, invocation services, management services, etc). Note that all of these introductions will route through that one senior member, which is sharing its network bandwidth with several other members (which will be communicating to a lesser degree with other members throughout this process). While each service may have a distinct senior member, there's a good chance during initial startup that a single member will be the senior for all services (if those services start on the senior before the second member joins the cluster). It's obvious that this could cause CPU and/or network starvation. In the current release of Coherence (3.7.1.3 as of this writing), the pure unicast code path also has less sophisticated flow-control for cluster-wide messages (compared to the multicast-enabled code path), which may also result in significant heap consumption on the senior member's JVM (from the message backlog). This is almost never a problem in practice, but with sufficient CPU or network starvation, it could become critical. For the non-operational concerns (near caches, queries, etc), the application itself will determine how much load is placed on the cluster. Applications intended for deployment in a pure unicast environment should be careful to avoid excessive dependence on these features. Even in an environment with multicast support, these operations may scale poorly since even with a constant request rate, the underlying workload will increase at roughly the same rate as the underlying resources are added. Unless there is an infrastructural requirement to the contrary, multicast should be enabled. If it can't be enabled, care should be taken to ensure the added overhead doesn't lead to performance or stability issues. This is particularly crucial in large clusters.

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Concurrent Affairs

- by Tony Davis

I once wrote an editorial, multi-core mania, on the conundrum of ever-increasing numbers of processor cores, but without the concurrent programming techniques to get anywhere near exploiting their performance potential. I came to the.controversial.conclusion that, while the problem loomed for all procedural languages, it was not a big issue for the vast majority of programmers. Two years later, I still think most programmers don't concern themselves overly with this issue, but I do think that's a bigger problem than I originally implied. Firstly, is the performance boost from writing code that can fully exploit all available cores worth the cost of the additional programming complexity? Right now, with quad-core processors that, at best, can make our programs four times faster, the answer is still no for many applications. But what happens in a few years, as the number of cores grows to 100 or even 1000? At this point, it becomes very hard to ignore the potential gains from exploiting concurrency. Possibly, I was optimistic to assume that, by the time we have 100-core processors, and most applications really needed to exploit them, some technology would be around to allow us to do so with relative ease. The ideal solution would be one that allows programmers to forget about the problem, in much the same way that garbage collection removed the need to worry too much about memory allocation. From all I can find on the topic, though, there is only a remote likelihood that we'll ever have a compiler that takes a program written in a single-threaded style and "auto-magically" converts it into an efficient, correct, multi-threaded program. At the same time, it seems clear that what is currently the most common solution, multi-threaded programming with shared memory, is unsustainable. As soon as a piece of state can be changed by a different thread of execution, the potential number of execution paths through your program grows exponentially with the number of threads. If you have two threads, each executing n instructions, then there are 2^n possible "interleavings" of those instructions. Of course, many of those interleavings will have identical behavior, but several won't. Not only does this make understanding how a program works an order of magnitude harder, but it will also result in irreproducible, non-deterministic, bugs. And of course, the problem will be many times worse when you have a hundred or a thousand threads. So what is the answer? All of the possible alternatives require a change in the way we write programs and, currently, seem to be plagued by performance issues. Software transactional memory (STM) applies the ideas of database transactions, and optimistic concurrency control, to memory. However, working out how to break down your program into sufficiently small transactions, so as to avoid contention issues, isn't easy. Another approach is concurrency with actors, where instead of having threads share memory, each thread runs in complete isolation, and communicates with others by passing messages. It simplifies concurrent programs but still has performance issues, if the threads need to operate on the same large piece of data. There are doubtless other possible solutions that I haven't mentioned, and I would love to know to what extent you, as a developer, are considering the problem of multi-core concurrency, what solution you currently favor, and why. Cheers, Tony.

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I thought the new AUTO_SAMPLE_SIZE in Oracle Database 11g looked at all the rows in a table so why do I see a very small sample size on some tables?

- by Maria Colgan

I recently got asked this question and thought it was worth a quick blog post to explain in a little more detail what is going on with the new AUTO_SAMPLE_SIZE in Oracle Database 11g and what you should expect to see in the dictionary views. Let’s take the SH.CUSTOMERS table as an example. There are 55,500 rows in the SH.CUSTOMERS tables. If we gather statistics on the SH.CUSTOMERS using the new AUTO_SAMPLE_SIZE but without collecting histogram we can check what sample size was used by looking in the USER_TABLES and USER_TAB_COL_STATISTICS dictionary views. The sample sized shown in the USER_TABLES is 55,500 rows or the entire table as expected. In USER_TAB_COL_STATISTICS most columns show 55,500 rows as the sample size except for four columns (CUST_SRC_ID, CUST_EFF_TO, CUST_MARTIAL_STATUS, CUST_INCOME_LEVEL ). The CUST_SRC_ID and CUST_EFF_TO columns have no sample size listed because there are only NULL values in these columns and the statistics gathering procedure skips NULL values. The CUST_MARTIAL_STATUS (38,072) and the CUST_INCOME_LEVEL (55,459) columns show less than 55,500 rows as their sample size because of the presence of NULL values in these columns. In the SH.CUSTOMERS table 17,428 rows have a NULL as the value for CUST_MARTIAL_STATUS column (17428+38072 = 55500), while 41 rows have a NULL values for the CUST_INCOME_LEVEL column (41+55459 = 55500). So we can confirm that the new AUTO_SAMPLE_SIZE algorithm will use all non-NULL values when gathering basic table and column level statistics. Now we have clear understanding of what sample size to expect lets include histogram creation as part of the statistics gathering. Again we can look in the USER_TABLES and USER_TAB_COL_STATISTICS dictionary views to find the sample size used. The sample size seen in USER_TABLES is 55,500 rows but if we look at the column statistics we see that it is same as in previous case except for columns CUST_POSTAL_CODE and CUST_CITY_ID. You will also notice that these columns now have histograms created on them. The sample size shown for these columns is not the sample size used to gather the basic column statistics. AUTO_SAMPLE_SIZE still uses all the rows in the table - the NULL rows to gather the basic column statistics (55,500 rows in this case). The size shown is the sample size used to create the histogram on the column. When we create a histogram we try to build it on a sample that has approximately 5,500 non-null values for the column. Typically all of the histograms required for a table are built from the same sample. In our example the histograms created on CUST_POSTAL_CODE and the CUST_CITY_ID were built on a single sample of ~5,500 (5,450 rows) as these columns contained only non-null values. However, if one or more of the columns that requires a histogram has null values then the sample size maybe increased in order to achieve a sample of 5,500 non-null values for those columns. n addition, if the difference between the number of nulls in the columns varies greatly, we may create multiple samples, one for the columns that have a low number of null values and one for the columns with a high number of null values. This scheme enables us to get close to 5,500 non-null values for each column. +Maria Colgan

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?12c database ????Adaptive Execution Plans ????????

- by Liu Maclean(???)

12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ??????? ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only. The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | | | 7 (100)| | |* 1 | HASH JOIN | | 4 | 128 | 7 (0)| 00:00:01 | |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???; ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization??????????????? ? ??????????????? ???????????????????????????????? ???????????,??????????????, ???????????????????? ??????????? Re-optimization??, ????????????????????? Re-optimization????dynamic plan?????????? dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are: Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM orders o, ( SELECT order_id, product_name FROM order_items o, product_information p WHERE p.product_id = o.product_id AND list_price < 50 AND min_price < 40 ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 269 |00:00:00.02 | 1336 | 18 | | | | | 1 | NESTED LOOPS | | 1 | 1 | 269 |00:00:00.02 | 1336 | 18 | | | | | 2 | MERGE JOIN CARTESIAN| | 1 | 4 | 9135 |00:00:00.02 | 34 | 15 | | | | |* 3 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 1 | 87 |00:00:00.01 | 33 | 14 | | | | | 4 | BUFFER SORT | | 87 | 105 | 9135 |00:00:00.01 | 1 | 1 | 4096 | 4096 | 4096 (0)| | 5 | INDEX FULL SCAN | ORDER_PK | 1 | 105 | 105 |00:00:00.01 | 1 | 1 | | | | |* 6 | INDEX UNIQUE SCAN | ORDER_ITEMS_UK | 9135 | 1 | 269 |00:00:00.01 | 1302 | 3 | | | | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50)) 6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM orders o, ( SELECT order_id, product_name FROM order_items o, product_information p WHERE p.product_id = o.product_id AND list_price < 50 AND min_price < 40 ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 269 |00:00:00.01 | 63 | 3 | | | | | 1 | NESTED LOOPS | | 1 | 269 | 269 |00:00:00.01 | 63 | 3 | | | | |* 2 | HASH JOIN | | 1 | 313 | 269 |00:00:00.01 | 42 | 3 | 1321K| 1321K| 1234K (0)| |* 3 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 87 | 87 |00:00:00.01 | 16 | 0 | | | | | 4 | INDEX FAST FULL SCAN| ORDER_ITEMS_UK | 1 | 665 | 665 |00:00:00.01 | 26 | 3 | | | | |* 5 | INDEX UNIQUE SCAN | ORDER_PK | 269 | 1 | 269 |00:00:00.01 | 21 | 0 | | | | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50)) 5 - access("O"."ORDER_ID"="ORDER_ID") Note ----- - statistics feedback used for this statement SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y 0 N 1 1* select child_number,other_xml From v$SQL_PLAN where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ -------------------------------------------------------------------------------- 1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1 2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_ hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></ hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]> </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7 4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[ LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$ F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml> 0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]> </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]> </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[ INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1 " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@" SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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