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• MySQL Connect Only 10 Days Away - Focus on InnoDB Sessions

  - by Bertrand Matthelié

  Time flies and MySQL Connect is only 10 days away! You can check out the full program here as well as in the September edition of the MySQL newsletter. Mat recently blogged about the MySQL Cluster sessions you’ll have the opportunity to attend, and below are those focused on InnoDB. Remember you can plan your schedule with Schedule Builder. Saturday, 1.00 pm, Room Golden Gate 3: 10 Things You Should Know About InnoDB—Calvin Sun, Oracle InnoDB is the default storage engine for Oracle’s MySQL as of MySQL Release 5.5. It provides the standard ACID-compliant transactions, row-level locking, multiversion concurrency control, and referential integrity. InnoDB also implements several innovative technologies to improve its performance and reliability. This presentation gives a brief history of InnoDB; its main features; and some recent enhancements for better performance, scalability, and availability. Saturday, 5.30 pm, Room Golden Gate 4: Demystified MySQL/InnoDB Performance Tuning—Dimitri Kravtchuk, Oracle This session covers performance tuning with MySQL and the InnoDB storage engine for MySQL and explains the main improvements made in MySQL Release 5.5 and Release 5.6. Which setting for which workload? Which value will be better for my system? How can I avoid potential bottlenecks from the beginning? Do I need a purge thread? Is it true that InnoDB doesn't need thread concurrency anymore? These and many other questions are asked by DBAs and developers. Things are changing quickly and constantly, and there is no “silver bullet.” But understanding the configuration setting’s impact is already a huge step in performance improvement. Bring your ideas and problems to share them with others—the discussion is open, just moderated by a speaker. Sunday, 10.15 am, Room Golden Gate 4: Better Availability with InnoDB Online Operations—Calvin Sun, Oracle Many top Web properties rely on Oracle’s MySQL as a critical piece of infrastructure for serving millions of users. Database availability has become increasingly important. One way to enhance availability is to give users full access to the database during data definition language (DDL) operations. The online DDL operations in recent MySQL releases offer users the flexibility to perform schema changes while having full access to the database—that is, with minimal delay of operations on a table and without rebuilding the entire table. These enhancements provide better responsiveness and availability in busy production environments. This session covers these improvements in the InnoDB storage engine for MySQL for online DDL operations such as add index, drop foreign key, and rename column. Sunday, 11.45 am, Room Golden Gate 7: Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster—Andrew Morgan and John Duncan, Oracle Ever-increasing performance demands of Web-based services have generated significant interest in providing NoSQL access methods to MySQL (MySQL Cluster and the InnoDB storage engine of MySQL), enabling users to maintain all the advantages of their existing relational databases while providing blazing-fast performance for simple queries. Get the best of both worlds: persistence; consistency; rich SQL queries; high availability; scalability; and simple, flexible APIs and schemas for agile development. This session describes the memcached connectors and examines some use cases for how MySQL and memcached fit together in application architectures. It does the same for the newest MySQL Cluster native connector, an easy-to-use, fully asynchronous connector for Node.js. Sunday, 1.15 pm, Room Golden Gate 4: InnoDB Performance Tuning—Inaam Rana, Oracle The InnoDB storage engine has always been highly efficient and includes many unique architectural elements to ensure high performance and scalability. In MySQL 5.5 and MySQL 5.6, InnoDB includes many new features that take better advantage of recent advances in operating systems and hardware platforms than previous releases did. This session describes unique InnoDB architectural elements for performance, new features, and how to tune InnoDB to achieve better performance. Sunday, 4.15 pm, Room Golden Gate 3: InnoDB Compression for OLTP—Nizameddin Ordulu, Facebook and Inaam Rana, Oracle Data compression is an important capability of the InnoDB storage engine for Oracle’s MySQL. Compressed tables reduce the size of the database on disk, resulting in fewer reads and writes and better throughput by reducing the I/O workload. Facebook pushes the limit of InnoDB compression and has made several enhancements to InnoDB, making this technology ready for online transaction processing (OLTP). In this session, you will learn the fundamentals of InnoDB compression. You will also learn the enhancements the Facebook team has made to improve InnoDB compression, such as reducing compression failures, not logging compressed page images, and allowing changes of compression level. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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• How to Secure a Data Role by Multiple Business Units

  - by Elie Wazen

  In this post we will see how a Role can be data secured by multiple Business Units (BUs).  Separate Data Roles are generally created for each BU if a corresponding data template generates roles on the basis of the BU dimension. The advantage of creating a policy with a rule that includes multiple BUs is that while mapping these roles in HCM Role Provisioning Rules, fewer number of entires need to be made. This could facilitate maintenance for enterprises with a large number of Business Units. Note: The example below applies as well if the securing entity is Inventory Organization. Let us take for example the case of a user provisioned with the "Accounts Payable Manager - Vision Operations" Data Role in Fusion Applications. This user will be able to access Invoices in Vision Operations but will not be able to see Invoices in Vision Germany. Figure 1. A User with a Data Role restricting them to Data from BU: Vision Operations With the role granted above, this is what the user will see when they attempt to select Business Units while searching for AP Invoices. Figure 2.The List Of Values of Business Units is limited to single one. This is the effect of the Data Role granted to that user as can be seen in Figure 1 In order to create a data role that secures by multiple BUs,  we need to start by creating a condition that groups those Business Units we want to include in that data role. This is accomplished by creating a new condition against the BU View .  That Condition will later be used to create a data policy for our newly created Role.  The BU View is a Database resource and  is accessed from APM as seen in the search below Figure 3.Viewing a Database Resource in APM The next step is create a new condition,  in which we define a sql predicate that includes 2 BUs ( The ids below refer to Vision Operations and Vision Germany).  At this point we have simply created a standalone condition.  We have not used this condition yet, and security is therefore not affected. Figure 4. Custom Role that inherits the Purchase Order Overview Duty We are now ready to create our Data Policy.  in APM, we search for our newly Created Role and Navigate to “Find Global Policies”.  we query the Role we want to secure and navigate to view its global policies. Figure 5. The Job Role we plan on securing We can see that the role was not defined with a Data Policy . So will create one that uses the condition we created earlier.   Figure 6. Creating a New Data Policy In the General Information tab, we have to specify the DB Resource that the Security Policy applies to:  In our case this is the BU View Figure 7. Data Policy Definition - Selection of the DB Resource we will secure by In the Rules Tab, we  make the rule applicable to multiple values of the DB Resource we selected in the previous tab.  This is where we associate the condition we created against the BU view to this data policy by entering the Condition name in the Condition field Figure 8. Data Policy Rule The last step of Defining the Data Policy, consists of  explicitly selecting  the Actions that are goverened by this Data Policy.  In this case for example we select the Actions displayed below in the right pane. Once the record is saved , we are ready to use our newly secured Data Role. Figure 9. Data Policy Actions We can now see a new Data Policy associated with our Role.  Figure 10. Role is now secured by a Data Policy We now Assign that new Role to the User.  Of course this does not have to be done in OIM and can be done using a Provisioning Rule in HCM. Figure 11. Role assigned to the User who previously was granted the Vision Ops secured role. Once that user accesses the Invoices Workarea this is what they see: In the image below the LOV of Business Unit returns the two values defined in our data policy namely: Vision Operations and Vision Germany Figure 12. The List Of Values of Business Units now includes the two we included in our data policy. This is the effect of the data role granted to that user as can be seen in Figure 11

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• Can an installation of SSRS be used for other reports if the SCOM Reporting Role is installed?

  - by Pete Davis

  I'm currently in the process of planing a SCOM 2007 R2 deployment and would like to deploy the OperationsManagerDW and Reporting Server to a shared SQL 2008 cluster which is used for reporting across multiple solutions. However in the in the deployment guide for SCOM 2007 R2 it says: Due to changes that the Operations Manager 2007 Reporting component makes to SQL Server Reporting Services security, no other applications that make use of SQL Server Reporting Services can be installed on this server. Which concerns me that it may interfere with existing or future (non SCOM) reports in some way even if deployed as a separate SSRS instance. Later in the same guide it states: Installing Operations Manager 2007 Reporting Services integrates the security of the instance of SQL Reporting Services with the Operations Manager role-based security. Do not install any other Reporting Services applications in this same instance of SQL Server. Does this mean that I can install a new SSRS instance and use this on the shared cluster for SCOM reporting or that I'd also need to create a whole new SQL Server instance as well as SSRS instance or I'd need a whole separate server for SCOM OperationsManagerDW and Reporitng Server?

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• CUPS basic auth error through web interface

  - by Inaimathi

  I'm trying to configure CUPS to allow remote administration through the web interface. There's enough documentation out there that I can figure out what to change in my cupsd.conf (changing Listen localhost:631 to Port 631, and adding Allow @LOCAL to the /, /admin and /admin/conf sections). I'm now at the point where I can see the CUPS interface from another machine on the same network. The trouble is, when I try to Add Printer, I'm asked for a username and password, but my response is rejected even when I know I've gotten it right (I assume it's asking for the username and password of someone in the lpadmin group on the server machine; I've sshed in with credentials its rejecting, and the user I'm using has been added to the lpadmin group). If I disable auth outright, by changing DefaultAuthType Basic to DefaultAuthType None, I get an "Unauthorized" error instead of a password request when I try to Add Printer. What am I doing wrong? Is there a way of letting users from the local network to administer the print server through the CUPS web interface? EDIT: By request, my complete cupsd.conf (spoiler: minimally edited default config file that comes with the edition of CUPS from the Debian wheezy repos): LogLevel warn MaxLogSize 0 SystemGroup lpadmin Port 631 # Listen localhost:631 Listen /var/run/cups/cups.sock Browsing On BrowseOrder allow,deny BrowseAllow all BrowseLocalProtocols CUPS dnssd # DefaultAuthType Basic DefaultAuthType None WebInterface Yes <Location /> Order allow,deny Allow @LOCAL </Location> <Location /admin> Order allow,deny Allow @LOCAL </Location> <Location /admin/conf> AuthType Default Require user @SYSTEM Order allow,deny Allow @LOCAL </Location> # Set the default printer/job policies... <Policy default> # Job/subscription privacy... JobPrivateAccess default JobPrivateValues default SubscriptionPrivateAccess default SubscriptionPrivateValues default # Job-related operations must be done by the owner or an administrator... <Limit Create-Job Print-Job Print-URI Validate-Job> Order deny,allow </Limit> <Limit Send-Document Send-URI Hold-Job Release-Job Restart-Job Purge-Jobs Set-Job-Attributes Create-Job-Subscription Renew-Subscription Cancel-Subscription Get-Notifications Reprocess-Job Cancel-Current-Job Suspend-Current-Job Resume-Job Cancel-My-Jobs Close-Job CUPS-Move-Job CUPS-Get-Document> Require user @OWNER @SYSTEM Order deny,allow </Limit> # All administration operations require an administrator to authenticate... <Limit CUPS-Add-Modify-Printer CUPS-Delete-Printer CUPS-Add-Modify-Class CUPS-Delete-Class CUPS-Set-Default CUPS-Get-Devices> AuthType Default Require user @SYSTEM Order deny,allow </Limit> # All printer operations require a printer operator to authenticate... <Limit Pause-Printer Resume-Printer Enable-Printer Disable-Printer Pause-Printer-After-Current-Job Hold-New-Jobs Release-Held-New-Jobs Deactivate-Printer Activate-Printer Restart-Printer Shutdown-Printer Startup-Printer Promote-Job Schedule-Job-After Cancel-Jobs CUPS-Accept-Jobs CUPS-Reject-Jobs> AuthType Default Require user @SYSTEM Order deny,allow </Limit> # Only the owner or an administrator can cancel or authenticate a job... <Limit Cancel-Job CUPS-Authenticate-Job> Require user @OWNER @SYSTEM Order deny,allow </Limit> <Limit All> Order deny,allow </Limit> </Policy> # Set the authenticated printer/job policies... <Policy authenticated> # Job/subscription privacy... JobPrivateAccess default JobPrivateValues default SubscriptionPrivateAccess default SubscriptionPrivateValues default # Job-related operations must be done by the owner or an administrator... <Limit Create-Job Print-Job Print-URI Validate-Job> AuthType Default Order deny,allow </Limit> <Limit Send-Document Send-URI Hold-Job Release-Job Restart-Job Purge-Jobs Set-Job-Attributes Create-Job-Subscription Renew-Subscription Cancel-Subscription Get-Notifications Reprocess-Job Cancel-Current-Job Suspend-Current-Job Resume-Job Cancel-My-Jobs Close-Job CUPS-Move-Job CUPS-Get-Document> AuthType Default Require user @OWNER @SYSTEM Order deny,allow </Limit> # All administration operations require an administrator to authenticate... <Limit CUPS-Add-Modify-Printer CUPS-Delete-Printer CUPS-Add-Modify-Class CUPS-Delete-Class CUPS-Set-Default> AuthType Default Require user @SYSTEM Order deny,allow </Limit> # All printer operations require a printer operator to authenticate... <Limit Pause-Printer Resume-Printer Enable-Printer Disable-Printer Pause-Printer-After-Current-Job Hold-New-Jobs Release-Held-New-Jobs Deactivate-Printer Activate-Printer Restart-Printer Shutdown-Printer Startup-Printer Promote-Job Schedule-Job-After Cancel-Jobs CUPS-Accept-Jobs CUPS-Reject-Jobs> AuthType Default Require user @SYSTEM Order deny,allow </Limit> # Only the owner or an administrator can cancel or authenticate a job... <Limit Cancel-Job CUPS-Authenticate-Job> AuthType Default Require user @OWNER @SYSTEM Order deny,allow </Limit> <Limit All> Order deny,allow </Limit> </Policy>

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• Advantages of multiple SQL Server files with a single RAID array

  - by Dr Giles M

  Originally posted on stack overflow, but re-worded. Imagine the scenario : For a database I have RAID arrays R: (MDF) T: (transaction log) and of course shared transparent usage of X: (tempDB). I've been reading around and get the impression that if you are using RAID then adding multiple SQL Server NDF files sitting on R: within a filegroup won't yeild any more improvements. Of course, adding another raid array S: and putting an NDF file on that would. However, being a reasonably savvy software person, it's not unthinkable to hypothesise that, even for smaller MDFs sitting on one RAID array that SQL Server will perform growth and locking operations (for writes) on the MDF, so adding NDFs to the filegroup even if they sat on R: would distribute the locking operations and growth operations allowing more throughput? Or does the time taken to reconstruct the data from distributed filegroups outweigh the benefits of reduced locking? I'm also aware that the behaviour and benefits may be different for tables/indeces/log. Is there a good site that distinguishes the benefits of multiple files when RAID is already in place?

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• Adding operation in middle of complex sequence diagram in visio 2003

  - by James

  I am using Microsoft Visio 2003 to define static classes with operations/methods and a sequence diagrams referring to these classes. The sequence diagram is almost done, but i realized that i missed one operation in middle of the diagram. When i try to move rest of the sequences down by selecting it as a block, all the operations in the block loose link with static diagrams. ( Methods which were referred to static classes as fun(), became fun, which means that now they no longer refer to static diagrams and any future changes would not be reflected in dynamic sequence diagrams automatically.) The sequence diagrams have grown to A3 size paper and i have many of such diagrams which needs correction. Manually moving the operations one by one would involve lots of effort. Could someone kindly suggest a way to overcome this problem?

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• Why would an ext3 filsystem be rolled back on a Debian VM running in VirtualBox after loss of power to the host

  - by Sevas

  A Debian Virtual machine runs as a Guest VirtualBox VM. It's filesystem is EXT3. The host system loses power and after booting up the host system and guest VM, I find that the VM's filesystem has been rolled back to a previous state, losing changes made to the filesystem some time before losing power. The operations that were rolled back had been fully completed before the loss of power (files fully copied, file handles closed, etc.), but it's possible and even likely that other write operations were occuring on the VM at the point of the crash. So I am trying to figure out if it's the filesystem recovery process that rolls back filesystem operations after encountering corruption post power loss, or is it possibly related to VirtualBox and the way it ignores flush requests for performance gains by default (discussed here) Are there any other factors that would result in the filesystem being rolled back after losing power?

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• Token based Authentication for WCF HTTP/REST Services: Authorization

  - by Your DisplayName here!

  In the previous post I showed how token based authentication can be implemented for WCF HTTP based services. Authentication is the process of finding out who the user is – this includes anonymous users. Then it is up to the service to decide under which circumstances the client has access to the service as a whole or individual operations. This is called authorization. By default – my framework does not allow anonymous users and will deny access right in the service authorization manager. You can however turn anonymous access on – that means technically, that instead of denying access, an anonymous principal is placed on Thread.CurrentPrincipal. You can flip that switch in the configuration class that you can pass into the service host/factory. var configuration = new WebTokenWebServiceHostConfiguration {     AllowAnonymousAccess = true }; But this is not enough, in addition you also need to decorate the individual operations to allow anonymous access as well, e.g.: [AllowAnonymousAccess] public string GetInfo() {     ... } Inside these operations you might have an authenticated or an anonymous principal on Thread.CurrentPrincipal, and it is up to your code to decide what to do. Side note: Being a security guy, I like this opt-in approach to anonymous access much better that all those opt-out approaches out there (like the Authorize attribute – or this.). Claims-based Authorization Since there is a ClaimsPrincipal available, you can use the standard WIF claims authorization manager infrastructure – either declaratively via ClaimsPrincipalPermission or programmatically (see also here). [ClaimsPrincipalPermission(SecurityAction.Demand,     Resource = "Claims",     Operation = "View")] public ViewClaims GetClientIdentity() {     return new ServiceLogic().GetClaims(); }   In addition you can also turn off per-request authorization (see here for background) via the config and just use the “domain specific” instrumentation. While the code is not 100% done – you can download the current solution here. HTH (Wanna learn more about federation, WIF, claims, tokens etc.? Click here.)

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• SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

  - by pinaldave

  This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions from SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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• Reminder: True WCF Asynchronous Operation

  - by Sean Feldman

  A true asynchronous service operation is not the one that returns void, but the one that is marked as IsOneWay=true using BeginX/EndX asynchronous operations (thanks Krzysztof). To support this sort of fire-and-forget invocation, Windows Communication Foundation offers one-way operations. After the client issues the call, Windows Communication Foundation generates a request message, but no correlated reply message will ever return to the client. As a result, one-way operations can't return values, and any exception thrown on the service side will not make its way to the client. One-way calls do not equate to asynchronous calls. When one-way calls reach the service, they may not be dispatched all at once and may be queued up on the service side to be dispatched one at a time, all according to the service configured concurrency mode behavior and session mode. How many messages (whether one-way or request-reply) the service is willing to queue up is a product of the configured channel and the reliability mode. If the number of queued messages has exceeded the queue's capacity, then the client will block, even when issuing a one-way call. However, once the call is queued, the client is unblocked and can continue executing while the service processes the operation in the background. This usually gives the appearance of asynchronous calls.

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• Flexible cloud file storage for a web.py app?

  - by benwad

  I'm creating a web app using web.py (although I may later rewrite it for Tornado) which involves a lot of file manipulation. One example, the app will have a git-style 'commit' operation, in which some files are sent to the server and placed in a new folder along with the unchanged files from the last version. This will involve copying the old folder to the new folder, replacing/adding/deleting the files in the commit to the new folder, then deleting all unchanged files in the old folder (as they are now in the new folder). I've decided on Heroku for the app hosting environment, and I am currently looking at cloud storage options that are built with these kinds of operations in mind. I was thinking of Amazon S3, however I'm not sure if that lets you carry out these kinds of file operations in-place. I was thinking I may have to load these files into the server's RAM and then re-insert them into the bucket, costing me a fortune. I was also thinking of Progstr Filer (http://filer.progstr.com/index.html) but that seems to only integrate with Rails apps. Can anyone help with this? Basically I want file operations to be as cheap as possible.

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• Flash Technology Can Revolutionize your IT Infrastructure

  - by kimberly.billings

  A recent article in the Data Center Journal written by Mark Teter outlines how flash is becoming a disruptive technology in the data center and how it will soon replace HDDs in the storage hierarchy. As Teter explains, the drivers behind this trend are lower cost/performance and power savings; flash is over 100x faster for reads than the fastest HDD, and while it is expensive, it can produce dramatic reductions in the cost of performance as measured in Input/Outputs per second (IOPS). What's more, flash consumes 1/5th the power of HDD, so it's faster AND greener. Teter writes, "when appropriately used, flash turns the current economics of IT performance on its head. That's disruptive." Exadata Smart Flash Cache in the Sun Oracle Database Machine makes intelligent use of flash storage to deliver extreme performance for OLTP and mixed workloads. It intelligently caches data from the Oracle Database replacing slow mechanical I/O operations to disk with very rapid flash memory operations. Exadata Smart Flash Cache is the fundamental technology of the Sun Oracle Database Machine that enables the processing of up to 1 million random I/O operations per second (IOPS), and the scanning of data within Exadata storage at up to 50 GB/second. Are you incorporating flash into your storage strategy? Let us know! Read more: "Flash technology can revolutionize your IT infrastructure", The Data Center Journal, March 30, 2010. Exadata Smart Flash Cache and the Sun Oracle Database Machine white paper var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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• Database Web Service using Toplink DB Provider

  - by Vishal Jain

  With JDeveloper 11gR2 you can now create database based web services using JAX-WS Provider. The key differences between this and the already existing PL/SQL Web Services support is:Based on JAX-WS ProviderSupports SQL Queries for creating Web ServicesSupports Table CRUD OperationsThis is present as a new option in the New Gallery under 'Web Services'When you invoke the New Gallery option, it present you with three options to choose from:In this entry I will explain the options of creating service based on SQL queries and Table CRUD operations.SQL Query based Service When you select this option, on 'Next' page it asks you for the DB Conn details. You can also choose if you want SOAP 1.1 or 1.2 format. For this example, I will proceed with SOAP 1.1, the default option.On the Next page, you can give the SQL query. The wizard support Bind Variables, so you can parametrize your queries. Give "?" as a input parameter you want to give at runtime, and the "Bind Variables" button will get enabled. Here you can specify the name and type of the variable.Finish the wizard. Now you can test your service in Analyzer:See that the bind variable specified comes as a input parameter in the Analyzer Input Form:CRUD OperationsFor this, At Step 2 of Wizard, select the radio button "Generate Table CRUD Service Provider"At the next step, select the DB Connection and the table for which you want to generate the default set of operations:Finish the Wizard. Now, run the service in Analyzer for a quick check.See that all the basic operations are exposed:

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• New Enhancements for InnoDB Memcached

  - by Calvin Sun

  In MySQL 5.6, we continued our development on InnoDB Memcached and completed a few widely desirable features that make InnoDB Memcached a competitive feature in more scenario. Notablely, they are 1) Support multiple table mapping 2) Added background thread to auto-commit long running transactions 3) Enhancement in binlog performance  Let’s go over each of these features one by one. And in the last section, we will go over a couple of internally performed performance tests. Support multiple table mapping In our earlier release, all InnoDB Memcached operations are mapped to a single InnoDB table. In the real life, user might want to use this InnoDB Memcached features on different tables. Thus being able to support access to different table at run time, and having different mapping for different connections becomes a very desirable feature. And in this GA release, we allow user just be able to do both. We will discuss the key concepts and key steps in using this feature. 1) "mapping name" in the "get" and "set" command In order to allow InnoDB Memcached map to a new table, the user (DBA) would still require to "pre-register" table(s) in InnoDB Memcached “containers” table (there is security consideration for this requirement). If you would like to know about “containers” table, please refer to my earlier blogs in blogs.innodb.com. Once registered, the InnoDB Memcached will then be able to look for such table when they are referred. Each of such registered table will have a unique "registration name" (or mapping_name) corresponding to the “name” field in the “containers” table.. To access these tables, user will include such "registration name" in their get or set commands, in the form of "get @@new_mapping_name.key", prefix "@@" is required for signaling a mapped table change. The key and the "mapping name" are separated by a configurable delimiter, by default, it is ".". So the syntax is: get [@@mapping_name.]key_name set [@@mapping_name.]key_name  or  get @@mapping_name set @@mapping_name Here is an example: Let's set up three tables in the "containers" table: The first is a map to InnoDB table "test/demo_test" table with mapping name "setup_1" INSERT INTO containers VALUES ("setup_1", "test", "demo_test", "c1", "c2", "c3", "c4", "c5", "PRIMARY");  Similarly, we set up table mappings for table "test/new_demo" with name "setup_2" and that to table "mydatabase/my_demo" with name "setup_3": INSERT INTO containers VALUES ("setup_2", "test", "new_demo", "c1", "c2", "c3", "c4", "c5", "secondary_index_x"); INSERT INTO containers VALUES ("setup_3", "my_database", "my_demo", "c1", "c2", "c3", "c4", "c5", "idx"); To switch to table "my_database/my_demo", and get the value corresponding to “key_a”, user will do: get @@setup_3.key_a (this will also output the value that corresponding to key "key_a" or simply get @@setup_3 Once this is done, this connection will switch to "my_database/my_demo" table until another table mapping switch is requested. so it can continue issue regular command like: get key_b  set key_c 0 0 7 These DMLs will all be directed to "my_database/my_demo" table. And this also implies that different connections can have different bindings (to different table). 2) Delimiter: For the delimiter "." that separates the "mapping name" and key value, we also added a configure option in the "config_options" system table with name of "table_map_delimiter": INSERT INTO config_options VALUES("table_map_delimiter", "."); So if user wants to change to a different delimiter, they can change it in the config_option table. 3) Default mapping: Once we have multiple table mapping, there should be always a "default" map setting. For this, we decided if there exists a mapping name of "default", then this will be chosen as default mapping. Otherwise, the first row of the containers table will chosen as default setting. Please note, user tables can be repeated in the "containers" table (for example, user wants to access different columns of the table in different settings), as long as they are using different mapping/configure names in the first column, which is enforced by a unique index. 4) bind command In addition, we also extend the protocol and added a bind command, its usage is fairly straightforward. To switch to "setup_3" mapping above, you simply issue: bind setup_3 This will switch this connection's InnoDB table to "my_database/my_demo" In summary, with this feature, you now can direct access to difference tables with difference session. And even a single connection, you can query into difference tables. Background thread to auto-commit long running transactions This is a feature related to the “batch” concept we discussed in earlier blogs. This “batch” feature allows us batch the read and write operations, and commit them only after certain calls. The “batch” size is controlled by the configure parameter “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size”. This could significantly boost performance. However, it also comes with some disadvantages, for example, you will not be able to view “uncommitted” operations from SQL end unless you set transaction isolation level to read_uncommitted, and in addition, this will held certain row locks for extend period of time that might reduce the concurrency. To deal with this, we introduce a background thread that “auto-commits” the transaction if they are idle for certain amount of time (default is 5 seconds). The background thread will wake up every second and loop through every “connections” opened by Memcached, and check for idle transactions. And if such transaction is idle longer than certain limit and not being used, it will commit such transactions. This limit is configurable by change “innodb_api_bk_commit_interval”. Its default value is 5 seconds, and minimum is 1 second, and maximum is 1073741824 seconds. With the help of such background thread, you will not need to worry about long running uncommitted transactions when set daemon_memcached_w_batch_size and daemon_memcached_r_batch_size to a large number. This also reduces the number of locks that could be held due to long running transactions, and thus further increase the concurrency. Enhancement in binlog performance As you might all know, binlog operation is not done by InnoDB storage engine, rather it is handled in the MySQL layer. In order to support binlog operation through InnoDB Memcached, we would have to artificially create some MySQL constructs in order to access binlog handler APIs. In previous lab release, for simplicity consideration, we open and destroy these MySQL constructs (such as THD) for each operations. This required us to set the “batch” size always to 1 when binlog is on, no matter what “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size” are configured to. This put a big restriction on our capability to scale, and also there are quite a bit overhead in creating destroying such constructs that bogs the performance down. With this release, we made necessary change that would keep MySQL constructs as long as they are valid for a particular connection. So there will not be repeated and redundant open and close (table) calls. And now even with binlog option is enabled (with innodb_api_enable_binlog,), we still can batch the transactions with daemon_memcached_w_batch_size and daemon_memcached_r_batch_size, thus scale the write/read performance. Although there are still overheads that makes InnoDB Memcached cannot perform as fast as when binlog is turned off. It is much better off comparing to previous release. And we are continuing optimize the solution is this area to improve the performance as much as possible. Performance Study: Amerandra of our System QA team have conducted some performance studies on queries through our InnoDB Memcached connection and plain SQL end. And it shows some interesting results. The test is conducted on a “Linux 2.6.32-300.7.1.el6uek.x86_64 ix86 (64)” machine with 16 GB Memory, Intel Xeon 2.0 GHz CPU X86_64 2 CPUs- 4 Core Each, 2 RAID DISKS (1027 GB,733.9GB). Results are described in following tables: Table 1: Performance comparison on Set operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8*** 5.6.7-RC* X faster Set (QPS) Set** 8 30,000 5,600 5.36 32 59,000 13,000 4.54 128 68,000 8,000 8.50 512 63,000 6.800 9.23 * mysql-5.6.7-rc-linux2.6-x86_64 ** The “set” operation when implemented in InnoDB Memcached involves a couple of DMLs: it first query the table to see whether the “key” exists, if it does not, the new key/value pair will be inserted. If it does exist, the “value” field of matching row (by key) will be updated. So when used in above query, it is a precompiled store procedure, and query will just execute such procedures. *** added “–daemon_memcached_option=-t8” (default is 4 threads) So we can see with this “set” query, InnoDB Memcached can run 4.5 to 9 time faster than MySQL server. Table 2: Performance comparison on Get operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8 5.6.7-RC* X faster Get (QPS) Get 8 42,000 27,000 1.56 32 101,000 55.000 1.83 128 117,000 52,000 2.25 512 109,000 52,000 2.10 With the “get” query (or the select query), memcached performs 1.5 to 2 times faster than normal SQL. Summary: In summary, we added several much-desired features to InnoDB Memcached in this release, allowing user to operate on different tables with this Memcached interface. We also now provide a background commit thread to commit long running idle transactions, thus allow user to configure large batch write/read without worrying about large number of rows held or not being able to see (uncommit) data. We also greatly enhanced the performance when Binlog is enabled. We will continue making efforts in both performance enhancement and functionality areas to make InnoDB Memcached a good demo case for our InnoDB APIs. Jimmy Yang, September 29, 2012

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• Windows Live SkyDrive: How To Move or Copy Files Between Folders

  - by Gopinath

  Microsoft has very simple and easy to use interface to move files between folders in Windows Operating system. But their own cloud storage service,Windows Live SkyDrive, complicated these simple and daily used operations. We need a guide to figure out how to perform basic copy/move operations. Couple of years ago we wrote about moving files between folders in old version of SkyDrive but the guide does not hold good today as SkyDrive has gone through many user interface changes in the recent past. Today one of our readers asked us how to move/copy files in the latest version of SkyDrive and here are the steps to be followed 1. Login to your Windows Live SkyDrive 2. Select the file you want to Move or Copy by clicking on the information icon (see 2 in below image) 3. After selecting the information icon, expand Information section displayed on the right side panel to access Move and Copy options (see 3 in the below image). 4. To move the selected file to another folder, select Move option and Sky Drive will guide you through folder selection user interface for choosing the target folder. 5. Once you navigate to the target folder where you want to move the file click on “Move this file into <<Target Folder>>”. 6. You are done. Dear Microsoft, SkyDrive provides us tonnes of free storage but please make it’s user interface a bit better so that we don’t need to write guides to perform basic operations. Hope you listen to your customers. This article titled,Windows Live SkyDrive: How To Move or Copy Files Between Folders, was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

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• need explanation on amortization in algorithm

  - by Pradeep

  I am a learning algorithm analysis and came across a analysis tool for understanding the running time of an algorithm with widely varying performance which is called as amortization. The autor quotes " An array with upper bound of n elements, with a fixed bound N, on it size. Operation clear takes O(n) time, since we should dereference all the elements in the array in order to really empty it. " The above statement is clear and valid. Now consider the next content: "Now consider a series of n operations on an initially empty array. if we take the worst case viewpoint, the running time is O(n^2), since the worst case of a sigle clear operation in the series is O(n) and there may be as many as O(n) clear operations in the series." From the above statement how is the time complexity O(n^2)? I did not understand the logic behind it. if 'n' operations are performed how is it O(n ^2)? Please explain what the autor is trying to convey..

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• Short Look at Frends Helium 2.0 Beta

  - by mipsen

  Pekka from Frends gave me the opportunity to have a look at the beta-version of their Helium 2.0. For all of you, who don't know the tool: Helium is a web-application that collects management-data from BizTalk which you usually have to tediously collect yourself, like performance-data (throttling, throughput (like completed Orchestrations/hour), other perfomance-counters) and data about the state of BTS-Applications and presents the data in clearly structured diagrams and overviews which (often) even allow drill-down.  Installing Helium 2 was quite easy. It comes as an msi-file which creates the web-application on IIS. Aditionally a windows-service is deployt which acts as an agent for sending alert-e-mails and collecting data. What I missed during installation was a link to the created web-app at the end, but the link can be found under Program Files/Frends... On the start-page Helium shows two sections: An overview about the BTS-Apps (Running?, suspended messages?) Basic perfomance-data You can drill-down into the BTS-Apps further, to see ReceiveLocations, Orchestrations and SendPorts. And then a very nice feature can be activated: You can set a monitor to each of the ports and/or orchestrations and have an e-mail sent when a threshold of executions/day or hour is not met. I think this is a great idea. The following screeshot shows the configuration of this option. Conclusion: Helium is a useful monitoring  tool for BTS-operations that might save a lot of time for collecting data, writing a tool yourself or documentation for the operations-staff where to find the data. Pros: Simple installation Most important data for BTS-operations in one place Monitor for alerts, if throughput is not met Nice Web-UI Reasonable price Cons: Additional Perormance-counters cannot be added Im am not sure when the final version is to be shipped, but you can see that on Frend's homepage soon, I guess... A trial version is available here

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• Out-of-the-Box Integration Links Primavera Solutions with PeopleSoft Projects Applications

  - by Sylvie MacKenzie, PMP

  In a move that brings best-in-class enterprise project portfolio management to Oracle’s PeopleSoft enterprise resource planning customers, Oracle announced the integration of Oracle’s PeopleSoft projects applications and Oracle’s Primavera P6 Enterprise Project Portfolio Management. The combination of PeopleSoft financial controls and Primavera portfolio management capabilities brings greater oversight of end-to-end processes to help organizations improve the planning and execution efforts needed to deliver projects on time and within budget. “As an organization with many high-value, project-driven initiatives, we are very pleased to see Oracle’s investment in this important integration,” says Janardhanan Sankar, senior vice president for technology and quality at ITC Infotech India Ltd. Oracle’s PeopleSoft projects applications enable project-centric organizations and departments to establish core operational processes for full project lifecycle management across operations and finance. The integration with Primavera P6 Enterprise Project Portfolio Management means organizations can eliminate costly and difficult-to-maintain proprietary integrations. Organizations can also standardize on the Oracle technologies to Align back-office budgets and costs with project operations to help ensure accurate forecasting of costs, resources, and schedules Provide an accurate single source of truth to financial managers and analysts using Oracle’s PeopleSoft projects applications, and to project managers using Primavera P6 Enterprise Project Portfolio Management  Enhance project collaboration and execution by having all users utilizing common solutions to communicate, plan, and deliver projects “By bringing together Oracle’s PeopleSoft projects applications and Oracle’s Primavera P6 Enterprise Project Portfolio Management, we are able to provide customers with the infrastructure they need to achieve a single source of truth on the projects they are managing,” says Paco Aubrejuan, Oracle’s group vice president and general manager, PeopleSoft. “This real-time visibility drives profitability, increases productivity, and improves operations.” For more information, view the on-demand Webcast, “Bridging Business Processes for Optimal Portfolio Performance,” or read about the new integration.

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• Explicitly pass context object versus injecting with IoC

  - by SonOfPirate

  I have a layered service application where the service layer delegates operations into the domain layer for execution. Many of these operations need to know the context under which they are operation. (The context included the identity of the current user, culture information, etc. received from the caller.) For example, I have an API method that returns a list of announcements. The list is based on the current user's role and each announcement is localized to their culture. The API is a thin-facade that delegates to an Application Service in my domain layer. The Application Service method obviously needs to know the context of the current request/operation as another call to the same API from another user should result in a different list. Within this method, we also have logging that uses some of the context information so we a clear understanding of the context when the operation was performed (this is especially useful if something goes wrong.) While this is a contrived example, in the real world, my Application Services will coordinate operations with many collaborative components, any number of them also needing the context information. My choice is to pass the context to the Application Service which would then pass it with any calls to collaborators or have the IoC container satisfy the dependency the Application Service and any collaborators have on the context. I am wondering if it is considered good/bad, best practices/code smell, etc. if I pass the context object as a parameter to the domain methods or if injecting the context via an IoC container is preferred. (EDIT: I should mention that the context object is instantiated per-request.)

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• Which Graphics/Geometry abstraction to choose?

  - by Robz

  I've been thinking about the design for a browser app on the HTML5 canvas that simulates a 2D robot zooming around, sensing the world around it. I decided to do this from scratch just for fun. I need shapes, like polygons, circles, and lines in order to model the robot and the world it lives in. These shapes need to be drawn with different appearance attributes, like border/fill style/width/color. I also need to have geometry functions to detect intersections and containment for the robot's sensors and so that the robot doesn't go inside stuff. One idea for functions is to have two totally separate libraries, one to implement graphics (like drawShape(context, shape)) and one for geometry operations (like shapeIntersectsShape(shape1, shape2)). Or, in a more object-oriented approach, the shape objects themselves could implement methods to do their own graphics (shape.draw(context)) and geometry operations (shape1.intersects(shape2)). Then there is the data itself: whether the data to draw a shape and the data to do geometric operations on that shape should be encapsulated within the same object, or be separate structures (where one would contain the other, or both be contained inside another structure). How do existing applications that do graphics/geometry stuff deal with this? Is there one model that is best, or is each good for certain applications? Should the fact that I'm using Javascript instead of a more classical language change how I approach the design?

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• What is logical cohesion, and why is it bad or undesirable?

  - by Matt Fenwick

  From the c2wiki page on coupling & cohesion: Cohesion (interdependency within module) strength/level names : (from worse to better, high cohesion is good) Coincidental Cohesion : (Worst) Module elements are unrelated Logical Cohesion : Elements perform similar activities as selected from outside module, i.e. by a flag that selects operation to perform (see also CommandObject). i.e. body of function is one huge if-else/switch on operation flag Temporal Cohesion : operations related only by general time performed (i.e. initialization() or FatalErrorShutdown?()) Procedural Cohesion : Elements involved in different but sequential activities, each on different data (usually could be trivially split into multiple modules along linear sequence boundaries) Communicational Cohesion : unrelated operations except need same data or input Sequential Cohesion : operations on same data in significant order; output from one function is input to next (pipeline) Informational Cohesion: a module performs a number of actions, each with its own entry point, with independent code for each action, all performed on the same data structure. Essentially an implementation of an abstract data type. i.e. define structure of sales_region_table and its operators: init_table(), update_table(), print_table() Functional Cohesion : all elements contribute to a single, well-defined task, i.e. a function that performs exactly one operation get_engine_temperature(), add_sales_tax() (emphasis mine). I don't fully understand the definition of logical cohesion. My questions are: what is logical cohesion? Why does it get such a bad rap (2nd worst kind of cohesion)?

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• Design Pattern for Skipping Steps in a Wizard

  - by Eric J.

  I'm designing a flexible Wizard system that presents a number of screens to complete a task. Some screens may need to be skipped based on answers to prompts on one or more previous screens. The conditions to skip a given screen need to be editable by a non-technical user via a UI. Multiple conditions need only be combined with and. I have an initial design in mind, but it feels inelegant. I wonder if there's a better way to approach this class of problem. Initial Design UI where The first column allows the user to select a question from a previous screen. The second column allows the user to select an operator applicable to the type of question asked. The third column allows the user to enter one or more values depending on the selected operator. Object Model public enum Operations { ... } public class Condition { int QuestionId { get; set; } Operations Operation { get; set; } List<object> Parameters { get; private set; } } List<Condition> pageSkipConditions; Controller Logic bool allConditionsTrue = pageSkipConditions.Count > 0; foreach (Condition c in pageSkipConditions) { allConditionsTrue &= Evaluate(previousAnswers, c); } // ... private bool Evaluate(List<Answers> previousAnswers, Condition c) { switch (c.Operation) { case Operations.StartsWith: // logic for this operation // etc. } }

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• Uralelektrostroy Improves Turnaround Times for Engineering and Construction Projects by Approximately 50% with Better Project Data Management

  - by Melissa Centurio Lopes

  LLC Uralelektrostroy was established in 1998, to meet the growing demand for reliable energy supply, which included the deployment and operation of a modern power grid system for Russia’s booming economy and industrial sector. To rise to the challenge, the country required a company with a strong reputation and the ability to strategically operate energy production and distribution facilities. As a renowned energy expert, Uralelektrostroy successfully embarked on the mission—focusing on the design, construction, and operation of power grids, transmission lines, and generation facilities. Today, Uralelektrostroy leads the Russian utilities industry with operations across the country, particularly in the Ural, Western Siberia, and Moscow regions. Challenges: Track work progress through all engineering project development stages with ease—from planning and start-up operations, to onsite construction and quality assurance—to enhance visibility into complex projects, such as power grid and power-transmission-line construction Implement and execute engineering projects faster—for example, designing and building power generation and distribution facilities—by better monitoring numerous local subcontractors Improve alignment of project schedules with project owners’ requirements—awarding federal and regional authorities—to avoid incurring fines for missing deadlines Solutions: Used Oracle’s Primavera P6 Enterprise Project Portfolio Management 8.1 to streamline communication with customers and subcontractors through better data management and harmonized reporting, reducing construction project implementation and turnaround times by approximately 50%, on average Enabled fast generation of work-in-progress reports that track project schedules, budgets, materials, and staffing—from approval and material procurement, to construction and delivery Reduced the number of construction sites by nearly 30% (from 35 to 25) by identifying unprofitable sites—streamlining operations at the company’s construction site network and increasing profitability Improved project visibility by enabling managers to efficiently track project status, ensuring on-time reporting and punctual project deliveries to federal customers to reduce delay penalties to zero “Oracle’s Primavera P6 Enterprise Project Portfolio Management 8.1 drastically changed the way we run our business. We’ve reduced the number of redundant assets, streamlined project implementation and execution, and improved collaboration with our customers and contractors. Overall, the Oracle deployment helped to increase our profitability.” – Roman Aleksandrovich Naumenko, Head of Information Technology, LLC Uralelektrostroy Read the complete customer snapshot here.

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• What is a Relational Database Management System (RDBMS)?

  A Relational Database Management System (RDBMS)  can also be called a traditional database that uses a Structured Query Language (SQL) to provide access to stored data while insuring the integrity of the data. The data is stored in a collection of tables that is defined by relationships between data items. In addition, data permitted to be joined in new relationships. Traditional databases primarily process data through transactions called transaction processing. Transaction processing is the methodology of grouping related business operations based predefined business events. An example of this can be seen when a person attempts to purchase an item from an online e-tailor. The business must execute specific operations for a related  business event. In this case, a business must store the following information: Customer Info, Order Info, Order Item Info, Customer Payment Data, Payment Results, and Current Order Status. Example: Pseudo SQL Operations needed for processing an online e-tailor sale. Insert Customer into Customers Insert New Order into Orders Insert Each New Order Item into OrderItems Insert Customer Payment Info into PaymentInfo Insert Payment Processing Result into PaymentDetails Update Customer for Current Order Status Common Relational Database Management System Microsoft SQL Server Microsoft Access Oracle MySQL DB2 It is important to note that no current RDBMS has fully implemented all of the Relational Principles. Common RDBMS Traits Volatile Data Supports Transaction Processing Optimized for Updates and Simple Queries 

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• C programming multiple storage backends

  - by ahjmorton

  I am starting a side project in C which requires multiple storage backends to be driven by a particular piece of logic. These storage backends would each be linked with the decision of which one to use specified at runtime. So for example if I invoke my program with one set of parameters it will perform the operations in memory but if I change the program configuration it would write to disk. The underlying idea is that each storage backend should implement the same protocol. In other words the logic for performing operations should need to know which backend it is operating on. Currently the way I have thought to provide this indirection is to have a struct of function pointers with the logic calling these function pointers. Essentially the struct would contain all the operations needed to implement the higher level logic E.g. struct Context { void (* doPartOfDoOp)(void) int (* getResult)(void); } //logic.h void doOp(Context * context) { //bunch of stuff context->doPartOfDoOp(); } int getResult(Context * context) { //bunch of stuff return context->getResult(); } My questions is if this way of solving the problem is one a C programmer would understand? I am a Java developer by trade but enjoy using C/++. Essentially the Context struct provides an interface like level of indirection. However I would like to know if there is a more idiomatic way of achieving this.

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