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  • World Record Siebel PSPP Benchmark on SPARC T4 Servers

    - by Brian
    Oracle's SPARC T4 servers set a new World Record for Oracle's Siebel Platform Sizing and Performance Program (PSPP) benchmark suite. The result used Oracle's Siebel Customer Relationship Management (CRM) Industry Applications Release 8.1.1.4 and Oracle Database 11g Release 2 running Oracle Solaris on three SPARC T4-2 and two SPARC T4-1 servers. The SPARC T4 servers running the Siebel PSPP 8.1.1.4 workload which includes Siebel Call Center and Order Management System demonstrates impressive throughput performance of the SPARC T4 processor by achieving 29,000 users. This is the first Siebel PSPP 8.1.1.4 benchmark supporting 29,000 concurrent users with a rate of 239,748 Business Transactions/hour. The benchmark demonstrates vertical and horizontal scalability of Siebel CRM Release 8.1.1.4 on SPARC T4 servers. Performance Landscape Systems Txn/hr Users Call Center Order Management Response Times (sec) 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – Web 3 x SPARC T4-2 (2 x SPARC T4 2.85 GHz) – App/Gateway 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – DB 239,748 29,000 0.165 0.925 Oracle: Call Center + Order Management Transactions: 197,128 + 42,620 Users: 20300 + 8700 Configuration Summary Web Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 10 8/11 iPlanet Web Server 7 Application Server Configuration: 3 x SPARC T4-2 servers, each with 2 x SPARC T4 processor, 2.85 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 10 8/11 Siebel CRM 8.1.1.5 SIA Database Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.2) Storage Configuration: 1 x Sun Storage F5100 Flash Array 80 x 24 GB flash modules Benchmark Description Siebel 8.1 PSPP benchmark includes Call Center and Order Management: Siebel Financial Services Call Center – Provides the most complete solution for sales and service, allowing customer service and telesales representatives to provide superior customer support, improve customer loyalty, and increase revenues through cross-selling and up-selling. High-level description of the use cases tested: Incoming Call Creates Opportunity, Quote and Order and Incoming Call Creates Service Request . Three complex business transactions are executed simultaneously for specific number of concurrent users. The ratios of these 3 scenarios were 30%, 40%, 30% respectively, which together were totaling 70% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 10, 13, and 35 seconds respectively. Siebel Order Management – Oracle's Siebel Order Management allows employees such as salespeople and call center agents to create and manage quotes and orders through their entire life cycle. Siebel Order Management can be tightly integrated with back-office applications allowing users to perform tasks such as checking credit, confirming availability, and monitoring the fulfillment process. High-level description of the use cases tested: Order & Order Items Creation and Order Updates. Two complex Order Management transactions were executed simultaneously for specific number of concurrent users concurrently with aforementioned three Call Center scenarios above. The ratio of these 2 scenarios was 50% each, which together were totaling 30% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 20 and 67 seconds respectively. Key Points and Best Practices No processor cores or cache were activated or deactivated on the SPARC T-Series systems to achieve special benchmark effects. See Also Siebel White Papers SPARC T4-1 Server oracle.com OTN SPARC T4-2 Server oracle.com OTN Siebel CRM oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

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  • Get the last checked checkboxes...

    - by Sara
    Hi everyone, I'm not sure how to accomplish this issue which has been confusing me for a few days. I have a form that updates a user record in MySQL when a checkbox is checked. Now, this is how my form does this: if (isset($_POST['Update'])) { $paymentr = $_POST['paymentr']; //put checkboxes array into variable $paymentr2 = implode(', ', $paymentr); //implode array for mysql $query = "UPDATE transactions SET paymentreceived=NULL"; $result = mysql_query($query); $query = "UPDATE transactions SET paymentdate='0000-00-00'"; $result = mysql_query($query); $query = "UPDATE transactions SET paymentreceived='Yes' WHERE id IN ($paymentr2)"; $result = mysql_query($query); $query = "UPDATE transactions SET paymentdate=NOW() WHERE id IN ($paymentr2)"; $result = mysql_query($query); foreach ($paymentr as $v) { //should collect last updated records and put them into variable for emailing. $query = "SELECT id, refid, affid FROM transactions WHERE id = '$v'"; $result = mysql_query($query) or die("Query Failed: ".mysql_errno()." - ".mysql_error()."<BR>\n$query<BR>\n"); $trans = mysql_fetch_array($result, MYSQL_ASSOC); $transactions .= '<br>User ID:'.$trans['id'].' -- '.$trans['refid'].' -- '.$trans['affid'].'<br>'; } } Unfortunately, it then updates ALL the user records with the latest date which is not what I want it to do. The alternative I thought of was, via Javascript, giving the checkbox a value that would be dynamically updated when the user selected it. Then, only THOSE checkboxes would be put into the array. Is this possible? Is there a better solution? I'm not even sure I could wrap my brain around how to do that WITH Javascript. Does the answer perhaps lie in how my mysql code is written? Thanks - I sincerely appreciate it!!!

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  • Move Data into the grid for scalable, predictable response times

    - by JuergenKress
    CloudTran is pleased to introduce the availability of the CloudTran Transaction and Persistence Manager for creating scalable, reliable data services on the Oracle Coherence In-Memory Data Grid (IMDG). Use of IMDG architectures has been key to handling today’s web-scale loads because it eliminates database latency by storing important and frequently access data in memory instead of on disk. The CloudTran product lets developers easily use an IMDG for full ACID-compliant transactions without having to be concerned about the location or spread of data. The system has its own implementation of fast, scalable distributed transactions that does NOT depend on XA protocols but still guarantees all ACID properties. Plus, CloudTran asynchronously replicates data going into the IMDG to back-end datastores and back-up data centers, again ensuring ACID properties. CloudTran can be accessed through Java Persistence API (JPA via TopLink Grid) and now, through a new Low-Level API, or LLAPI. This is ideal for use in SOA applications that need data reliability, high availability, performance, and scalability. It is still in its limited beta release, the LLAPI gives developers the ability to use standard put/remove logic available in Coherence and then wrap logic with simple Spring annotations or XML+AspectJ to start transactions. An important feature of LLAPI is the ability to join transactions. This is a common outcome for SOA applications that need to reduce network traffic by aggregating data into single cache entries and then doing SOA service processing in the node holding the data. This results in the need to orchestrate transaction processing across multiple service calls. CloudTran has the capability to handle these “multi-client” transactions at speed with no loss in ACID properties. Developing software around an IMDG like Oracle Coherence is an important choice for today’s web-scale applications and services. But this introduces new architectural considerations to maintain scalability in light of increased network loads and data movement. Without using CloudTran, developers are faced with an incredibly difficult task to ensure data reliability, availability, performance, and scalability when working with an IMDG. Working with highly distributed data that is entirely volatile while stored in memory presents numerous edge cases where failures can result in data loss. The CloudTran product takes care of all of this, leaving developers with the confidence and peace of mind that all data is processed correctly. For those interested in evaluating the CloudTran product and IMDGs, take a look at this link for more information: http://www.CloudTran.com/downloadAPI.ph , or send your questions to [email protected]. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Technorati Tags: CloudTran,data grid,M,SOA Community,Oracle SOA,Oracle BPM,BPM,Community,OPN,Jürgen Kress

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  • Move Data into the Grid for Scalable, Predictable Response Times

    - by JuergenKress
    CloudTran is pleased to introduce the availability of the CloudTran Transaction and Persistence Manager for creating scalable, reliable data services on the Oracle Coherence In-Memory Data Grid (IMDG). Use of IMDG architectures has been key to handling today’s web-scale loads because it eliminates database latency by storing important and frequently access data in memory instead of on disk. The CloudTran product lets developers easily use an IMDG for full ACID-compliant transactions without having to be concerned about the location or spread of data. The system has its own implementation of fast, scalable distributed transactions that does NOT depend on XA protocols but still guarantees all ACID properties. Plus, CloudTran asynchronously replicates data going into the IMDG to back-end datastores and back-up data centers, again ensuring ACID properties. CloudTran can be accessed through Java Persistence API (JPA via TopLink Grid) and now, through a new Low-Level API, or LLAPI. This is ideal for use in SOA applications that need data reliability, high availability, performance, and scalability. Still in limited beta release, the LLAPI gives developers the ability to use standard put/remove logic available in Coherence and then wrap logic with simple Spring annotations or XML+AspectJ to start transactions. An important feature of LLAPI is the ability to join transactions. This is a common outcome for SOA applications that need to reduce network traffic by aggregating data into single cache entries and then doing SOA service processing in the node holding the data. This results in the need to orchestrate transaction processing across multiple service calls. CloudTran has the capability to handle these “multi-client” transactions at speed with no loss in ACID properties. Developing software around an IMDG like Oracle Coherence is an important choice for today’s web-scale applications and services. But this introduces new architectural considerations to maintain scalability in light of increased network loads and data movement. Without using CloudTran, developers are faced with an incredibly difficult task to ensure data reliability, availability, performance, and scalability when working with an IMDG. Working with highly distributed data that is entirely volatile while stored in memory presents numerous edge cases where failures can result in data loss. The CloudTran product takes care of all of this, leaving developers with the confidence and peace of mind that all data is processed correctly. For those interested in evaluating the CloudTran product and IMDGs, take a look at this link for more information: http://www.CloudTran.com/downloadAPI.php, or, send your questions to [email protected]. WebLogic Partner Community For regular information become a member in the WebLogic Partner Community please visit: http://www.oracle.com/partners/goto/wls-emea ( OPN account required). If you need support with your account please contact the Oracle Partner Business Center. BlogTwitterLinkedInMixForumWiki Technorati Tags: Coherence,cloudtran,cache,WebLogic Community,Oracle,OPN,Jürgen Kress

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  • Paperclip: delete attachment and "can't convert nil into String" error

    - by snitko
    I'm using Paperclip and here's what I do in the model to delete attachments: def before_save self.avatar = nil if @delete_avatar == 1.to_s end Works fine unless @delete_avatar flag is set when the user is actually uploading the image (so the model receives both params[:user][:avatar] and params[:user][:delete_avatar]. This results in the following error: TypeError: can't convert nil into String from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:40:in `dirname' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:40:in `flush_writes' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:38:in `each' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:38:in `flush_writes' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/attachment.rb:144:in `save' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/attachment.rb:162:in `destroy' from /Work/project/src/app/models/user.rb:72:in `before_save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:347:in `send' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:347:in `callback' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:249:in `create_or_update' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/base.rb:2538:in `save_without_validation' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/validations.rb:1078:in `save_without_dirty' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/dirty.rb:79:in `save_without_transactions' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:229:in `send' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:229:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/connection_adapters/abstract/database_statements.rb:136:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:182:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:228:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:196:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:208:in `rollback_active_record_state!' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:196:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/base.rb:723:in `create' I assume it has something to do with the avatar.dirty? value because when it certainly is true when this happens. The question is, how do I totally reset the thing if there are changes to be saved and abort avatar upload when the flag is set?

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  • Paperclip: delete attachments and "can't convert nil into String" error

    - by snitko
    I'm using Paperclip and here's what I do in the model to delete attachments: def before_save self.avatar = nil if @delete_avatar == 1.to_s end Works fine unless @delete_avatar flag is set when the user is actually uploading the image (so the model receives both params[:user][:avatar] and params[:user][:delete_avatar]. This results in the following error: TypeError: can't convert nil into String from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:40:in `dirname' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:40:in `flush_writes' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:38:in `each' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/storage.rb:38:in `flush_writes' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/attachment.rb:144:in `save' from /Work/project/src/vendor/plugins/paperclip/lib/paperclip/attachment.rb:162:in `destroy' from /Work/project/src/app/models/user.rb:72:in `before_save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:347:in `send' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:347:in `callback' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/callbacks.rb:249:in `create_or_update' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/base.rb:2538:in `save_without_validation' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/validations.rb:1078:in `save_without_dirty' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/dirty.rb:79:in `save_without_transactions' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:229:in `send' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:229:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/connection_adapters/abstract/database_statements.rb:136:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:182:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:228:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:196:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:208:in `rollback_active_record_state!' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/transactions.rb:196:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.5/lib/active_record/base.rb:723:in `create' I assume it has something to do with the avatar.dirty? value because when it certainly is true when this happens. The question is, how do I totally reset the thing if there are changes to be saved and abort avatar upload when the flag is set?

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  • Optimizing tasks to reduce CPU in a trading application

    - by Joel
    Hello, I have designed a trading application that handles customers stocks investment portfolio. I am using two datastore kinds: Stocks - Contains unique stock name and its daily percent change. UserTransactions - Contains information regarding a specific purchase of a stock made by a user : the value of the purchase along with a reference to Stock for the current purchase. db.Model python modules: class Stocks (db.Model): stockname = db.StringProperty(multiline=True) dailyPercentChange=db.FloatProperty(default=1.0) class UserTransactions (db.Model): buyer = db.UserProperty() value=db.FloatProperty() stockref = db.ReferenceProperty(Stocks) Once an hour I need to update the database: update the daily percent change in Stocks and then update the value of all entities in UserTransactions that refer to that stock. The following python module iterates over all the stocks, update the dailyPercentChange property, and invoke a task to go over all UserTransactions entities which refer to the stock and update their value: Stocks.py # Iterate over all stocks in datastore for stock in Stocks.all(): # update daily percent change in datastore db.run_in_transaction(updateStockTxn, stock.key()) # create a task to update all user transactions entities referring to this stock taskqueue.add(url='/task', params={'stock_key': str(stock.key(), 'value' : self.request.get ('some_val_for_stock') }) def updateStockTxn(stock_key): #fetch the stock again - necessary to avoid concurrency updates stock = db.get(stock_key) stock.dailyPercentChange= data.get('some_val_for_stock') # I get this value from outside ... some more calculations here ... stock.put() Task.py (/task) # Amount of transaction per task amountPerCall=10 stock=db.get(self.request.get("stock_key")) # Get all user transactions which point to current stock user_transaction_query=stock.usertransactions_set cursor=self.request.get("cursor") if cursor: user_transaction_query.with_cursor(cursor) # Spawn another task if more than 10 transactions are in datastore transactions = user_transaction_query.fetch(amountPerCall) if len(transactions)==amountPerCall: taskqueue.add(url='/task', params={'stock_key': str(stock.key(), 'value' : self.request.get ('some_val_for_stock'), 'cursor': user_transaction_query.cursor() }) # Iterate over all transaction pointing to stock and update their value for transaction in transactions: db.run_in_transaction(updateUserTransactionTxn, transaction.key()) def updateUserTransactionTxn(transaction_key): #fetch the transaction again - necessary to avoid concurrency updates transaction = db.get(transaction_key) transaction.value= transaction.value* self.request.get ('some_val_for_stock') db.put(transaction) The problem: Currently the system works great, but the problem is that it is not scaling well… I have around 100 Stocks with 300 User Transactions, and I run the update every hour. In the dashboard, I see that the task.py takes around 65% of the CPU (Stock.py takes around 20%-30%) and I am using almost all of the 6.5 free CPU hours given to me by app engine. I have no problem to enable billing and pay for additional CPU, but the problem is the scaling of the system… Using 6.5 CPU hours for 100 stocks is very poor. I was wondering, given the requirements of the system as mentioned above, if there is a better and more efficient implementation (or just a small change that can help with the current implemntation) than the one presented here. Thanks!! Joel

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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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  • What's the difference between General Ledger Transfer Program, Create Accounting and Submit Accounting?

    - by Oracle_EBS
    In Release 12, the General Ledger Transfer Program is no longer used. Use Create Accounting or Submit Accounting instead. Submit Accounting spawns the Revenue Recognition Process. The Create Accounting program does not. So if you create transactions with rules, then you would want to run Submit Accounting Process to spawn Revenue Recognition to create the distribution rows, which Create Accounting is then spawned to process to the GL. Create Accounting Submit Accounting Short Name for Concurrent Program XLAACCPB ARACCPB Specific to Receivables No Yes Runs Revenue Recognition automatically No Yes Can be run real-time for one Transaction/Receipt at a time Yes No Spawns the following Programs 1) XLAACCPB module: Create Accounting 2) XLAACCUP module: Accounting Program 3) GLLEZL module: Journal Import 1) ARTERRPM module: Revenue Recognition Master Program 2) ARTERRPW module: Revenue Recognition with parallel workers - could be numerous 3) ARREVSWP - Revenue Contingency Analyzer 4) XLAACCPB module: Create Accounting 5) XLAACCUP module: Accounting Program 5) GLLEZL module: Journal Import Keep in mind, Reports owned by application 'Subledger Accounting' cannot be seen when running the report from Receivables responsibility. You may want to request your sysadmin to attach the following SLA reports/programs to your AR responsibility as you will need these for your AR closing process: XLAPEXRPT : Subledger Period Close Exception Report - shows transactions in status final, incomplete and unprocessed. XLAGLTRN : Transfer Journal Entries to GL - transfers transactions in final status and manually created transactions to GL To add reports/programs owned by application 'Subledger Accounting' (Subledger Period Close Exception Report and Transfer Journal Entries to GL_ Add to the request group as follows: Let's use Subledger Accounting Report XLATBRPT: Open Account Balances Listing Report as an example. Responsibility: System Administrator Navigation: Security > Responsibility > Define Query the name of your Receivables Responsibility and note the Request Group (ie. Receivables All) Navigation: Security > Responsibility > Request Query the Request Group Go to Request Zone and Click on Add Record Enter the following: Type: Program Name: Open Account Balances Listing Save Responsibility: Receivables Manager Navigation: Control > Requests > Run In the list of values you should now see 'Open Account Balances Listing' report References: Note: 748999.1 How to add reports for application subledger accounting to receivables responsibiilty Note: 759534.1 R12 ARGLTP General Ledger Transfer Program Errors Out Note: 1121944.1 Understanding and Troubleshooting Revenue Recognition in Oracle Receivables

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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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  • Manager Self Service at your Fingertips

    - by Elaine Clement
    Last week we released new and improved Manager Self Service capabilities in PeopleSoft HCM 9.1. We delivered a new Manager Dashboard, streamlined many Manager Self Service transactions, provided new Pivot Grid capabilities, and implemented one-click Related Actions accessible from multiple places – all with the goal of improving every Manager’s self service experience. Manager Dashboard These new capabilities have the potential to significantly impact an organization’s bottom line, and here is why. Increased Efficiency The Manager Dashboard provides a ‘one-stop shop’ for your Managers with all of the key data they need consolidated into a single view. Alerts notifying managers of important tasks are immediately viewable and actionable. Administrators can configure the dashboard to include the most important pagelets needed for their organization, and Managers can personalize it to fit within their personal way of conducting their tasks. The Related Actions feature further improves the ease with which Managers get their work done by providing one-click access to Manager Self Service transactions.  Increased Job Satisfaction The streamlined Manager transactions, related actions, and the new Manager Dashboard provide an enhanced user experience. Managers are able to quickly get in, get the information they need, complete their transactions, and get out. Managers can spend their time focusing on getting the business results they need instead of their day to day HR tasks. Enhanced Decision Support Administrators can ensure the information and analytics they want their Managers to use are available from the Manager Dashboard, establishing best business practices. Additional pivot grids relevant to your own organization can be added to the Manager Dashboard. With this easy access to the relevant information in an easily understood format, Managers can make the right business decisions needed to improve their team and their team’s productivity. For more details on the Manager Dashboard and some of the other newly posted features, such as a new Talent Summary, check out this video and others: Oracle PeopleSoft Webcasts

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  • Committed JDO writes do not apply on local GAE HRD, or possibly reused transaction

    - by eeeeaaii
    I'm using JDO 2.3 on app engine. I was using the Master/Slave datastore for local testing and recently switched over to using the HRD datastore for local testing, and parts of my app are breaking (which is to be expected). One part of the app that's breaking is where it sends a lot of writes quickly - that is because of the 1-second limit thing, it's failing with a concurrent modification exception. Okay, so that's also to be expected, so I have the browser retry the writes again later when they fail (maybe not the best hack but I'm just trying to get it working quickly). But a weird thing is happening. Some of the writes which should be succeeding (the ones that DON'T get the concurrent modification exception) are also failing, even though the commit phase completes and the request returns my success code. I can see from the log that the retried requests are working okay, but these other requests that seem to have committed on the first try are, I guess, never "applied." But from what I read about the Apply phase, writing again to that same entity should force the apply... but it doesn't. Code follows. Some things to note: I am attempting to use automatic JDO caching. So this is where JDO uses memcache under the covers. This doesn't actually work unless you wrap everything in a transaction. all the requests are doing is reading a string out of an entity, modifying part of the string, and saving that string back to the entity. If these requests weren't in transactions, you'd of course have the "dirty read" problem. But with transactions, isolation is supposed to be at the level of "serializable" so I don't see what's happening here. the entity being modified is a root entity (not in a group) I have cross-group transactions enabled Another weird thing is happening. If the concurrent modification thing happens, and I subsequently edit more than 5 more entities (this is the max for cross-group transactions), then nothing happens right away, but when I stop and restart the server I get "IllegalArgumentException: operating on too many entity groups in a single transaction". Could it be possible that the PMF is returning the same PersistenceManager every time, or the PM is reusing the same transaction every time? I don't see how I could possibly get the above error otherwise. The code inside the transaction just edits one root entity. I can't think of any other way that GAE would give me the "too many entity groups" error. The relevant code (this is a simplified version) PersistenceManager pm = PMF.getManager(); Transaction tx = pm.currentTransaction(); String responsetext = ""; try { tx.begin(); // I have extra calls to "makePersistent" because I found that relying // on pm.close didn't always write the objects to cache, maybe that // was only a DataNucleus 1.x issue though Key userkey = obtainUserKeyFromCookie(); User u = pm.getObjectById(User.class, userkey); pm.makePersistent(u); // to make sure it gets cached for next time Key mapkey = obtainMapKeyFromQueryString(); // this is NOT a java.util.Map, just FYI Map currentmap = pm.getObjectById(Map.class, mapkey); Text mapData = currentmap.getMapData(); // mapData is JSON stored in the entity Text newMapData = parseModifyAndReturn(mapData); // transform the map currentmap.setMapData(newMapData); // mutate the Map object pm.makePersistent(currentmap); // make sure to persist so there is a cache hit tx.commit(); responsetext = "OK"; } catch (JDOCanRetryException jdoe) { // log jdoe responsetext = "RETRY"; } catch (Exception e) { // log e responsetext = "ERROR"; } finally { if (tx.isActive()) { tx.rollback(); } pm.close(); } resp.getWriter().println(responsetext); EDIT: so I have verified that it fails after exactly 5 transactions. Here's what I do: I create a Foo (root entity), do a bunch of concurrent operations on that Foo, and some fail and get retried, and some commit but don't apply (as described above). Then, I start creating more Foos, and do a few operations on those new Foos. If I only create four Foos, stopping and restarting app engine does NOT give me the IllegalArgumentException. However if I create five Foos (which is the limit for cross-group transactions), then when I stop and restart app engine, I do get the exception. So it seems that somehow these new Foos I am creating are counting toward the limit of 5 max entities per transaction, even though they are supposed to be handled by separate transactions. It's as if a transaction is still open and is being reused by the servlet when it handles the new requests for the 2nd through 5th Foos. EDIT2: it looks like the IllegalArgument thing is independent of the other bug. In other words, it always happens when I create five Foos, even if I don't get the concurrent modification exception. I don't know if it's a symptom of the same problem or if it's unrelated. EDIT3: I found out what was causing the (unrelated) IllegalArgumentException, it was a dumb mistake on my part. But the other issue is still happening. EDIT4: added pseudocode for the datastore access EDIT5: I am pretty sure I know why this is happening, but I will still award the bounty to anyone who can confirm it. Basically, I think the problem is that transactions are not really implemented in the local version of the datastore. References: https://groups.google.com/forum/?fromgroups=#!topic/google-appengine-java/gVMS1dFSpcU https://groups.google.com/forum/?fromgroups=#!topic/google-appengine-java/deGasFdIO-M https://groups.google.com/forum/?hl=en&fromgroups=#!msg/google-appengine-java/4YuNb6TVD6I/gSttMmHYwo0J Because transactions are not implemented, rollback is essentially a no-op. Therefore, I get a dirty read when two transactions try to modify the record at the same time. In other words, A reads the data and B reads the data at the same time. A attempts to modify the data, and B attempts to modify a different part of the data. A writes to the datastore, then B writes, obliterating A's changes. Then B is "rolled back" by app engine, but since rollbacks are a no-op when running on the local datastore, B's changes stay, and A's do not. Meanwhile, since B is the thread that threw the exception, the client retries B, but does not retry A (since A was supposedly the transaction that succeeded).

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  • Java Transaction Service without the application server

    - by johnny
    Is it possible to have a Java standalone application (no application server attached) that exposes some operations that a client can call and be the one to manage the transactions? I was thinking this application to expose JNDI resources and get a hold of a java:comp/UserTransaction from there, get also a bean from there and call methods A, B and C on it and coordinate the transaction from the client? The application I'm writing isn't complex enough so that I need a big application server around it so I'm thinking to have a standalone JTS inside it that the client could interact with from a transactions point of view. I don't have much experience with distributed transactions and don't really know how to tackle the issue. Is it even possible? Am I getting myself into something beyond what a mere mortal (programmer) can handle? How can I approach this?

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  • Oracle FLEXCUBE delivers 'Bank-in-a-Box' with Oracle Database Appliance

    - by margaret hamburger
    Another great example of how Oracle Database Appliance simplifies the deployment of high availability database solutions making it easy for Oracle Partners and ISVs to deliver value added solutions to customers on a simple, reliable and affordable database platform. Oracle FLEXCUBE Universal Banking recently announced that it runs on Oracle Database Appliance X3-2 to deliver mid-size banks a compelling banking-in-a-box solution. With this certification, banks can benefit from a low-IT-footprint, high-performance, full-scale banking technology that is engineered to support end-to-end business requirements. In a recent performance test of Oracle FLEXCUBE Universal Banking on Oracle Database Appliance X3-2, the system managed more than 2.6 million online transactions in 60 minutes. This equated to roughly 744 transactions per second with an average response time of 156 milliseconds for 98 percent of the transactions. Likewise, the solution completed end-of-month batch processing for 10 million customer accounts in 123 minutes during the performance test.  Learn more about Oracle Database Appliance Solution-in-a-Box.

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  • Developing web apps using ASP.NET MVC 3, Razor and EF Code First - Part 2

    - by shiju
    In my previous post Developing web apps using ASP.NET MVC 3, Razor and EF Code First - Part 1, we have discussed on how to work with ASP.NET MVC 3 and EF Code First for developing web apps. We have created generic repository and unit of work with EF Code First for our ASP.NET MVC 3 application and did basic CRUD operations against a simple domain entity. In this post, I will demonstrate on working with domain entity with deep object graph, Service Layer and View Models and will also complete the rest of the demo application. In the previous post, we have done CRUD operations against Category entity and this post will be focus on Expense entity those have an association with Category entity. You can download the source code from http://efmvc.codeplex.com . The following frameworks will be used for this step by step tutorial.    1. ASP.NET MVC 3 RTM    2. EF Code First CTP 5    3. Unity 2.0 Domain Model Category Entity public class Category   {       public int CategoryId { get; set; }       [Required(ErrorMessage = "Name Required")]       [StringLength(25, ErrorMessage = "Must be less than 25 characters")]       public string Name { get; set;}       public string Description { get; set; }       public virtual ICollection<Expense> Expenses { get; set; }   } Expense Entity public class Expense     {                public int ExpenseId { get; set; }                public string  Transaction { get; set; }         public DateTime Date { get; set; }         public double Amount { get; set; }         public int CategoryId { get; set; }         public virtual Category Category { get; set; }     } We have two domain entities - Category and Expense. A single category contains a list of expense transactions and every expense transaction should have a Category. Repository class for Expense Transaction Let’s create repository class for handling CRUD operations for Expense entity public class ExpenseRepository : RepositoryBase<Expense>, IExpenseRepository     {     public ExpenseRepository(IDatabaseFactory databaseFactory)         : base(databaseFactory)         {         }                } public interface IExpenseRepository : IRepository<Expense> { } Service Layer If you are new to Service Layer, checkout Martin Fowler's article Service Layer . According to Martin Fowler, Service Layer defines an application's boundary and its set of available operations from the perspective of interfacing client layers. It encapsulates the application's business logic, controlling transactions and coordinating responses in the implementation of its operations. Controller classes should be lightweight and do not put much of business logic onto it. We can use the service layer as the business logic layer and can encapsulate the rules of the application. Let’s create a Service class for coordinates the transaction for Expense public interface IExpenseService {     IEnumerable<Expense> GetExpenses(DateTime startDate, DateTime ednDate);     Expense GetExpense(int id);             void CreateExpense(Expense expense);     void DeleteExpense(int id);     void SaveExpense(); } public class ExpenseService : IExpenseService {     private readonly IExpenseRepository expenseRepository;            private readonly IUnitOfWork unitOfWork;     public ExpenseService(IExpenseRepository expenseRepository, IUnitOfWork unitOfWork)     {                  this.expenseRepository = expenseRepository;         this.unitOfWork = unitOfWork;     }     public IEnumerable<Expense> GetExpenses(DateTime startDate, DateTime endDate)     {         var expenses = expenseRepository.GetMany(exp => exp.Date >= startDate && exp.Date <= endDate);         return expenses;     }     public void CreateExpense(Expense expense)     {         expenseRepository.Add(expense);         unitOfWork.Commit();     }     public Expense GetExpense(int id)     {         var expense = expenseRepository.GetById(id);         return expense;     }     public void DeleteExpense(int id)     {         var expense = expenseRepository.GetById(id);         expenseRepository.Delete(expense);         unitOfWork.Commit();     }     public void SaveExpense()     {         unitOfWork.Commit();     } }   View Model for Expense Transactions In real world ASP.NET MVC applications, we need to design model objects especially for our views. Our domain objects are mainly designed for the needs for domain model and it is representing the domain of our applications. On the other hand, View Model objects are designed for our needs for views. We have an Expense domain entity that has an association with Category. While we are creating a new Expense, we have to specify that in which Category belongs with the new Expense transaction. The user interface for Expense transaction will have form fields for representing the Expense entity and a CategoryId for representing the Category. So let's create view model for representing the need for Expense transactions. public class ExpenseViewModel {     public int ExpenseId { get; set; }       [Required(ErrorMessage = "Category Required")]     public int CategoryId { get; set; }       [Required(ErrorMessage = "Transaction Required")]     public string Transaction { get; set; }       [Required(ErrorMessage = "Date Required")]     public DateTime Date { get; set; }       [Required(ErrorMessage = "Amount Required")]     public double Amount { get; set; }       public IEnumerable<SelectListItem> Category { get; set; } } The ExpenseViewModel is designed for the purpose of View template and contains the all validation rules. It has properties for mapping values to Expense entity and a property Category for binding values to a drop-down for list values of Category. Create Expense transaction Let’s create action methods in the ExpenseController for creating expense transactions public ActionResult Create() {     var expenseModel = new ExpenseViewModel();     var categories = categoryService.GetCategories();     expenseModel.Category = categories.ToSelectListItems(-1);     expenseModel.Date = DateTime.Today;     return View(expenseModel); } [HttpPost] public ActionResult Create(ExpenseViewModel expenseViewModel) {                      if (!ModelState.IsValid)         {             var categories = categoryService.GetCategories();             expenseViewModel.Category = categories.ToSelectListItems(expenseViewModel.CategoryId);             return View("Save", expenseViewModel);         }         Expense expense=new Expense();         ModelCopier.CopyModel(expenseViewModel,expense);         expenseService.CreateExpense(expense);         return RedirectToAction("Index");              } In the Create action method for HttpGet request, we have created an instance of our View Model ExpenseViewModel with Category information for the drop-down list and passing the Model object to View template. The extension method ToSelectListItems is shown below   public static IEnumerable<SelectListItem> ToSelectListItems(         this IEnumerable<Category> categories, int  selectedId) {     return           categories.OrderBy(category => category.Name)                 .Select(category =>                     new SelectListItem                     {                         Selected = (category.CategoryId == selectedId),                         Text = category.Name,                         Value = category.CategoryId.ToString()                     }); } In the Create action method for HttpPost, our view model object ExpenseViewModel will map with posted form input values. We need to create an instance of Expense for the persistence purpose. So we need to copy values from ExpenseViewModel object to Expense object. ASP.NET MVC futures assembly provides a static class ModelCopier that can use for copying values between Model objects. ModelCopier class has two static methods - CopyCollection and CopyModel.CopyCollection method will copy values between two collection objects and CopyModel will copy values between two model objects. We have used CopyModel method of ModelCopier class for copying values from expenseViewModel object to expense object. Finally we did a call to CreateExpense method of ExpenseService class for persisting new expense transaction. List Expense Transactions We want to list expense transactions based on a date range. So let’s create action method for filtering expense transactions with a specified date range. public ActionResult Index(DateTime? startDate, DateTime? endDate) {     //If date is not passed, take current month's first and last dte     DateTime dtNow;     dtNow = DateTime.Today;     if (!startDate.HasValue)     {         startDate = new DateTime(dtNow.Year, dtNow.Month, 1);         endDate = startDate.Value.AddMonths(1).AddDays(-1);     }     //take last date of start date's month, if end date is not passed     if (startDate.HasValue && !endDate.HasValue)     {         endDate = (new DateTime(startDate.Value.Year, startDate.Value.Month, 1)).AddMonths(1).AddDays(-1);     }     var expenses = expenseService.GetExpenses(startDate.Value ,endDate.Value);     //if request is Ajax will return partial view     if (Request.IsAjaxRequest())     {         return PartialView("ExpenseList", expenses);     }     //set start date and end date to ViewBag dictionary     ViewBag.StartDate = startDate.Value.ToShortDateString();     ViewBag.EndDate = endDate.Value.ToShortDateString();     //if request is not ajax     return View(expenses); } We are using the above Index Action method for both Ajax requests and normal requests. If there is a request for Ajax, we will call the PartialView ExpenseList. Razor Views for listing Expense information Let’s create view templates in Razor for showing list of Expense information ExpenseList.cshtml @model IEnumerable<MyFinance.Domain.Expense>   <table>         <tr>             <th>Actions</th>             <th>Category</th>             <th>                 Transaction             </th>             <th>                 Date             </th>             <th>                 Amount             </th>         </tr>       @foreach (var item in Model) {              <tr>             <td>                 @Html.ActionLink("Edit", "Edit",new { id = item.ExpenseId })                 @Ajax.ActionLink("Delete", "Delete", new { id = item.ExpenseId }, new AjaxOptions { Confirm = "Delete Expense?", HttpMethod = "Post", UpdateTargetId = "divExpenseList" })             </td>              <td>                 @item.Category.Name             </td>             <td>                 @item.Transaction             </td>             <td>                 @String.Format("{0:d}", item.Date)             </td>             <td>                 @String.Format("{0:F}", item.Amount)             </td>         </tr>          }       </table>     <p>         @Html.ActionLink("Create New Expense", "Create") |         @Html.ActionLink("Create New Category", "Create","Category")     </p> Index.cshtml @using MyFinance.Helpers; @model IEnumerable<MyFinance.Domain.Expense> @{     ViewBag.Title = "Index"; }    <h2>Expense List</h2>    <script src="@Url.Content("~/Scripts/jquery.unobtrusive-ajax.min.js")" type="text/javascript"></script> <script src="@Url.Content("~/Scripts/jquery-ui.js")" type="text/javascript"></script> <script src="@Url.Content("~/Scripts/jquery.ui.datepicker.js")" type="text/javascript"></script> <link href="@Url.Content("~/Content/jquery-ui-1.8.6.custom.css")" rel="stylesheet" type="text/css" />      @using (Ajax.BeginForm(new AjaxOptions{ UpdateTargetId="divExpenseList", HttpMethod="Get"})) {     <table>         <tr>         <td>         <div>           Start Date: @Html.TextBox("StartDate", Html.Encode(String.Format("{0:mm/dd/yyyy}", ViewData["StartDate"].ToString())), new { @class = "ui-datepicker" })         </div>         </td>         <td><div>            End Date: @Html.TextBox("EndDate", Html.Encode(String.Format("{0:mm/dd/yyyy}", ViewData["EndDate"].ToString())), new { @class = "ui-datepicker" })          </div></td>          <td> <input type="submit" value="Search By TransactionDate" /></td>         </tr>     </table>         }   <div id="divExpenseList">             @Html.Partial("ExpenseList", Model)     </div> <script type="text/javascript">     $().ready(function () {         $('.ui-datepicker').datepicker({             dateFormat: 'mm/dd/yy',             buttonImage: '@Url.Content("~/Content/calendar.gif")',             buttonImageOnly: true,             showOn: "button"         });     }); </script> Ajax search functionality using Ajax.BeginForm The search functionality of Index view is providing Ajax functionality using Ajax.BeginForm. The Ajax.BeginForm() method writes an opening <form> tag to the response. You can use this method in a using block. In that case, the method renders the closing </form> tag at the end of the using block and the form is submitted asynchronously by using JavaScript. The search functionality will call the Index Action method and this will return partial view ExpenseList for updating the search result. We want to update the response UI for the Ajax request onto divExpenseList element. So we have specified the UpdateTargetId as "divExpenseList" in the Ajax.BeginForm method. Add jQuery DatePicker Our search functionality is using a date range so we are providing two date pickers using jQuery datepicker. You need to add reference to the following JavaScript files to working with jQuery datepicker. jquery-ui.js jquery.ui.datepicker.js For theme support for datepicker, we can use a customized CSS class. In our example we have used a CSS file “jquery-ui-1.8.6.custom.css”. For more details about the datepicker component, visit jquery UI website at http://jqueryui.com/demos/datepicker . In the jQuery ready event, we have used following JavaScript function to initialize the UI element to show date picker. <script type="text/javascript">     $().ready(function () {         $('.ui-datepicker').datepicker({             dateFormat: 'mm/dd/yy',             buttonImage: '@Url.Content("~/Content/calendar.gif")',             buttonImageOnly: true,             showOn: "button"         });     }); </script>   Source Code You can download the source code from http://efmvc.codeplex.com/ . Summary In this two-part series, we have created a simple web application using ASP.NET MVC 3 RTM, Razor and EF Code First CTP 5. I have demonstrated patterns and practices  such as Dependency Injection, Repository pattern, Unit of Work, ViewModel and Service Layer. My primary objective was to demonstrate different practices and options for developing web apps using ASP.NET MVC 3 and EF Code First. You can implement these approaches in your own way for building web apps using ASP.NET MVC 3. I will refactor this demo app on later time.

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  • ASP.NET MVC 3 Hosting :: How to Deploy Web Apps Using ASP.NET MVC 3, Razor and EF Code First - Part II

    - by mbridge
    In previous post, I have discussed on how to work with ASP.NET MVC 3 and EF Code First for developing web apps. In this post, I will demonstrate on working with domain entity with deep object graph, Service Layer and View Models and will also complete the rest of the demo application. In the previous post, we have done CRUD operations against Category entity and this post will be focus on Expense entity those have an association with Category entity. Domain Model Category Entity public class Category   {       public int CategoryId { get; set; }       [Required(ErrorMessage = "Name Required")]       [StringLength(25, ErrorMessage = "Must be less than 25 characters")]       public string Name { get; set;}       public string Description { get; set; }       public virtual ICollection<Expense> Expenses { get; set; }   } Expense Entity public class Expense     {                public int ExpenseId { get; set; }                public string  Transaction { get; set; }         public DateTime Date { get; set; }         public double Amount { get; set; }         public int CategoryId { get; set; }         public virtual Category Category { get; set; }     } We have two domain entities - Category and Expense. A single category contains a list of expense transactions and every expense transaction should have a Category. Repository class for Expense Transaction Let’s create repository class for handling CRUD operations for Expense entity public class ExpenseRepository : RepositoryBase<Expense>, IExpenseRepository     {     public ExpenseRepository(IDatabaseFactory databaseFactory)         : base(databaseFactory)         {         }                } public interface IExpenseRepository : IRepository<Expense> { } Service Layer If you are new to Service Layer, checkout Martin Fowler's article Service Layer . According to Martin Fowler, Service Layer defines an application's boundary and its set of available operations from the perspective of interfacing client layers. It encapsulates the application's business logic, controlling transactions and coordinating responses in the implementation of its operations. Controller classes should be lightweight and do not put much of business logic onto it. We can use the service layer as the business logic layer and can encapsulate the rules of the application. Let’s create a Service class for coordinates the transaction for Expense public interface IExpenseService {     IEnumerable<Expense> GetExpenses(DateTime startDate, DateTime ednDate);     Expense GetExpense(int id);             void CreateExpense(Expense expense);     void DeleteExpense(int id);     void SaveExpense(); } public class ExpenseService : IExpenseService {     private readonly IExpenseRepository expenseRepository;            private readonly IUnitOfWork unitOfWork;     public ExpenseService(IExpenseRepository expenseRepository, IUnitOfWork unitOfWork)     {                  this.expenseRepository = expenseRepository;         this.unitOfWork = unitOfWork;     }     public IEnumerable<Expense> GetExpenses(DateTime startDate, DateTime endDate)     {         var expenses = expenseRepository.GetMany(exp => exp.Date >= startDate && exp.Date <= endDate);         return expenses;     }     public void CreateExpense(Expense expense)     {         expenseRepository.Add(expense);         unitOfWork.Commit();     }     public Expense GetExpense(int id)     {         var expense = expenseRepository.GetById(id);         return expense;     }     public void DeleteExpense(int id)     {         var expense = expenseRepository.GetById(id);         expenseRepository.Delete(expense);         unitOfWork.Commit();     }     public void SaveExpense()     {         unitOfWork.Commit();     } } View Model for Expense Transactions In real world ASP.NET MVC applications, we need to design model objects especially for our views. Our domain objects are mainly designed for the needs for domain model and it is representing the domain of our applications. On the other hand, View Model objects are designed for our needs for views. We have an Expense domain entity that has an association with Category. While we are creating a new Expense, we have to specify that in which Category belongs with the new Expense transaction. The user interface for Expense transaction will have form fields for representing the Expense entity and a CategoryId for representing the Category. So let's create view model for representing the need for Expense transactions. public class ExpenseViewModel {     public int ExpenseId { get; set; }       [Required(ErrorMessage = "Category Required")]     public int CategoryId { get; set; }       [Required(ErrorMessage = "Transaction Required")]     public string Transaction { get; set; }       [Required(ErrorMessage = "Date Required")]     public DateTime Date { get; set; }       [Required(ErrorMessage = "Amount Required")]     public double Amount { get; set; }       public IEnumerable<SelectListItem> Category { get; set; } } The ExpenseViewModel is designed for the purpose of View template and contains the all validation rules. It has properties for mapping values to Expense entity and a property Category for binding values to a drop-down for list values of Category. Create Expense transaction Let’s create action methods in the ExpenseController for creating expense transactions public ActionResult Create() {     var expenseModel = new ExpenseViewModel();     var categories = categoryService.GetCategories();     expenseModel.Category = categories.ToSelectListItems(-1);     expenseModel.Date = DateTime.Today;     return View(expenseModel); } [HttpPost] public ActionResult Create(ExpenseViewModel expenseViewModel) {                      if (!ModelState.IsValid)         {             var categories = categoryService.GetCategories();             expenseViewModel.Category = categories.ToSelectListItems(expenseViewModel.CategoryId);             return View("Save", expenseViewModel);         }         Expense expense=new Expense();         ModelCopier.CopyModel(expenseViewModel,expense);         expenseService.CreateExpense(expense);         return RedirectToAction("Index");              } In the Create action method for HttpGet request, we have created an instance of our View Model ExpenseViewModel with Category information for the drop-down list and passing the Model object to View template. The extension method ToSelectListItems is shown below public static IEnumerable<SelectListItem> ToSelectListItems(         this IEnumerable<Category> categories, int  selectedId) {     return           categories.OrderBy(category => category.Name)                 .Select(category =>                     new SelectListItem                     {                         Selected = (category.CategoryId == selectedId),                         Text = category.Name,                         Value = category.CategoryId.ToString()                     }); } In the Create action method for HttpPost, our view model object ExpenseViewModel will map with posted form input values. We need to create an instance of Expense for the persistence purpose. So we need to copy values from ExpenseViewModel object to Expense object. ASP.NET MVC futures assembly provides a static class ModelCopier that can use for copying values between Model objects. ModelCopier class has two static methods - CopyCollection and CopyModel.CopyCollection method will copy values between two collection objects and CopyModel will copy values between two model objects. We have used CopyModel method of ModelCopier class for copying values from expenseViewModel object to expense object. Finally we did a call to CreateExpense method of ExpenseService class for persisting new expense transaction. List Expense Transactions We want to list expense transactions based on a date range. So let’s create action method for filtering expense transactions with a specified date range. public ActionResult Index(DateTime? startDate, DateTime? endDate) {     //If date is not passed, take current month's first and last dte     DateTime dtNow;     dtNow = DateTime.Today;     if (!startDate.HasValue)     {         startDate = new DateTime(dtNow.Year, dtNow.Month, 1);         endDate = startDate.Value.AddMonths(1).AddDays(-1);     }     //take last date of start date's month, if end date is not passed     if (startDate.HasValue && !endDate.HasValue)     {         endDate = (new DateTime(startDate.Value.Year, startDate.Value.Month, 1)).AddMonths(1).AddDays(-1);     }     var expenses = expenseService.GetExpenses(startDate.Value ,endDate.Value);     //if request is Ajax will return partial view     if (Request.IsAjaxRequest())     {         return PartialView("ExpenseList", expenses);     }     //set start date and end date to ViewBag dictionary     ViewBag.StartDate = startDate.Value.ToShortDateString();     ViewBag.EndDate = endDate.Value.ToShortDateString();     //if request is not ajax     return View(expenses); } We are using the above Index Action method for both Ajax requests and normal requests. If there is a request for Ajax, we will call the PartialView ExpenseList. Razor Views for listing Expense information Let’s create view templates in Razor for showing list of Expense information ExpenseList.cshtml @model IEnumerable<MyFinance.Domain.Expense>   <table>         <tr>             <th>Actions</th>             <th>Category</th>             <th>                 Transaction             </th>             <th>                 Date             </th>             <th>                 Amount             </th>         </tr>       @foreach (var item in Model) {              <tr>             <td>                 @Html.ActionLink("Edit", "Edit",new { id = item.ExpenseId })                 @Ajax.ActionLink("Delete", "Delete", new { id = item.ExpenseId }, new AjaxOptions { Confirm = "Delete Expense?", HttpMethod = "Post", UpdateTargetId = "divExpenseList" })             </td>              <td>                 @item.Category.Name             </td>             <td>                 @item.Transaction             </td>             <td>                 @String.Format("{0:d}", item.Date)             </td>             <td>                 @String.Format("{0:F}", item.Amount)             </td>         </tr>          }       </table>     <p>         @Html.ActionLink("Create New Expense", "Create") |         @Html.ActionLink("Create New Category", "Create","Category")     </p> Index.cshtml @using MyFinance.Helpers; @model IEnumerable<MyFinance.Domain.Expense> @{     ViewBag.Title = "Index"; }    <h2>Expense List</h2>    <script src="@Url.Content("~/Scripts/jquery.unobtrusive-ajax.min.js")" type="text/javascript"></script> <script src="@Url.Content("~/Scripts/jquery-ui.js")" type="text/javascript"></script> <script src="@Url.Content("~/Scripts/jquery.ui.datepicker.js")" type="text/javascript"></script> <link href="@Url.Content("~/Content/jquery-ui-1.8.6.custom.css")" rel="stylesheet" type="text/css" />      @using (Ajax.BeginForm(new AjaxOptions{ UpdateTargetId="divExpenseList", HttpMethod="Get"})) {     <table>         <tr>         <td>         <div>           Start Date: @Html.TextBox("StartDate", Html.Encode(String.Format("{0:mm/dd/yyyy}", ViewData["StartDate"].ToString())), new { @class = "ui-datepicker" })         </div>         </td>         <td><div>            End Date: @Html.TextBox("EndDate", Html.Encode(String.Format("{0:mm/dd/yyyy}", ViewData["EndDate"].ToString())), new { @class = "ui-datepicker" })          </div></td>          <td> <input type="submit" value="Search By TransactionDate" /></td>         </tr>     </table>         }   <div id="divExpenseList">             @Html.Partial("ExpenseList", Model)     </div> <script type="text/javascript">     $().ready(function () {         $('.ui-datepicker').datepicker({             dateFormat: 'mm/dd/yy',             buttonImage: '@Url.Content("~/Content/calendar.gif")',             buttonImageOnly: true,             showOn: "button"         });     }); </script> Ajax search functionality using Ajax.BeginForm The search functionality of Index view is providing Ajax functionality using Ajax.BeginForm. The Ajax.BeginForm() method writes an opening <form> tag to the response. You can use this method in a using block. In that case, the method renders the closing </form> tag at the end of the using block and the form is submitted asynchronously by using JavaScript. The search functionality will call the Index Action method and this will return partial view ExpenseList for updating the search result. We want to update the response UI for the Ajax request onto divExpenseList element. So we have specified the UpdateTargetId as "divExpenseList" in the Ajax.BeginForm method. Add jQuery DatePicker Our search functionality is using a date range so we are providing two date pickers using jQuery datepicker. You need to add reference to the following JavaScript files to working with jQuery datepicker. - jquery-ui.js - jquery.ui.datepicker.js For theme support for datepicker, we can use a customized CSS class. In our example we have used a CSS file “jquery-ui-1.8.6.custom.css”. For more details about the datepicker component, visit jquery UI website at http://jqueryui.com/demos/datepicker . In the jQuery ready event, we have used following JavaScript function to initialize the UI element to show date picker. <script type="text/javascript">     $().ready(function () {         $('.ui-datepicker').datepicker({             dateFormat: 'mm/dd/yy',             buttonImage: '@Url.Content("~/Content/calendar.gif")',             buttonImageOnly: true,             showOn: "button"         });     }); </script> Summary In this two-part series, we have created a simple web application using ASP.NET MVC 3 RTM, Razor and EF Code First CTP 5. I have demonstrated patterns and practices  such as Dependency Injection, Repository pattern, Unit of Work, ViewModel and Service Layer. My primary objective was to demonstrate different practices and options for developing web apps using ASP.NET MVC 3 and EF Code First. You can implement these approaches in your own way for building web apps using ASP.NET MVC 3. I will refactor this demo app on later time.

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  • Oracle TimesTen In-Memory Database Performance on SPARC T4-2

    - by Brian
    The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11: On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms: Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%. Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor. Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with: 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system. 10x more performance per processor than the SPARC T2+ 1.4 GHz server. 1.6x better performance per processor than the SPARC T3 1.65 GHz based server. In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems. Performance Landscape Mobile Call Processing Test Performance System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 218,400 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 162,900 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 80,400 TimesTen Performance Throughput Benchmark (TPTBM) Read-Only System Processor Sockets/Cores/Threads Tps SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 7.9M SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 6.5M M4000 SPARC64 VII+, 2.66 GHz 4 16 32 3.1M T5440 SPARC T2+, 1.4 GHz 4 32 256 3.1M TimesTen Performance Throughput Benchmark (TPTBM) Update-Only System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 547,800 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 363,800 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 240,500 TimesTen Replication Tests System Processor Sockets/Cores/Threads Asynchronous 2-Safe SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 38,024 13,701 SPARC T5440 SPARC T2+, 1.4 GHz 4 32 256 11,621 4,615 Configuration Summary Hardware Configurations: SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 4 x 300 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head SPARC T3-4 server 4 x SPARC T3 processors, 1.6 GHz 512 GB memory 1 x 8 Gbs FC Qlogic HBA 8 x 146 GB internal disks 1 x Sun Fire X4275 server configured as COMSTAR head SPARC Enterprise M4000 server 4 x SPARC64 VII+ processors, 2.66 GHz 128 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 2 x 146 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head Software Configuration: Oracle Solaris 11 11/11 Oracle TimesTen 11.2.2.4 Benchmark Descriptions TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required. Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources. Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes. See Also SPARC T4-2 Server oracle.com OTN Oracle TimesTen In-Memory Database oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • General questions regarding open-source licensing

    - by ndg
    I'm looking to release an open-source iOS software project but I'm very new to the licensing side of the things. While I'm aware that the majority of answers here will not lawyers, I'd appreciate it if anyone could steer me in the right direction. With the exception of the following requirements I'm happy for developers to largely do whatever they want with the projects source code. I'm not interested in any copyleft licensing schemes, and while I'd like to encourage attribution in derivative works it is not required. As such, my requirements are as follows: Original source can be distributed and re-distributed (verbatim) both commercially and non-commercially as long as the original copyright information, website link and license is maintained. I wish to retain rights to any of the multi-media distributed as part of the project (sound effects, graphics, logo marks, etc). Such assets will be included to allow other developers to easily execute the project, but cannot be re-distributed in any manner. I wish to retain rights to the applications name and branding. Futher to selecting an applicable license, I have the following questions: The project makes use of a number of third-party libraries (all licensed under variants of the MIT license). I've included individual licenses within the source (and application) and believe I've met all requirements expressed in these licenses, but is there anything else that needs to be done before distributing them as part of my open-source project? Also included in my project is a single proprietary, close-sourced library that's used to power a small part of the application. I'm obviously unable to include this in the source release, but what's the best way of handling this? Should I simply weak-link the project and exclude it entirely from the Git project?

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  • Seamless STP with Oracle SOA Suite

    - by user12339860
    STP stands for “Straight Through Processing”. Wikipedia describes STP as a solution that enables “the entire trade process for capital markets and payment transactions to be conducted electronically without the need for re-keying or manual intervention, subject to legal and regulatory restrictions” .I will deal with the later part of the definition i.e “payment transactions without manual intervention” in this article. The STP that I am writing about involves the interaction between a Bank and its’ corporate customers,to that extent this business case is also called “Corporate Payments”.Simply put a  Corporate Payment-STP solution needs to connect the payment transaction right from the Corporate ERP into the Bank’s Payment Hub. A SOA based STP solution can do a lot more than just process transaction. But before I get to the solution let me describe the perspectives of the two primary parties in this interaction. The Corporate customer and the Bank. Corporate's Interaction with Bank:  Typically it is the treasury department of an enterprise which interacts with the Bank on a daily basis. Here is how a day of interaction would look like from the treasury department of a corp. Corporate Cash Retrieve Beginning of day totals Monitor Cash Accounts Send or receive cash between accounts Supply chain payments Payment Settlements Calculate settlement positions Retrieve End of Day totals Assess Transaction Financial Impact Short Term Investment Desk Retrieve Current Account information Conduct Investment activities Bank’s Interaction with the Corporate :  From the Bank’s perspective, the interaction starts from the point of on boarding a corporate customer to billing the corporate for the value added services it provides. Once the corporate is on-boarded the daily interaction involves Handle the various formats of data arriving from customers Process Beginning of Day & End of Day reporting request from customers Meet compliance requirements Process Payments Transmit Payment Status Challenges with this Interaction :  Both the Bank & the Corporate face many challenges from these interactions. Some of the challenges include Keeping a consistent view of transaction data for various LOBs of the corporate & the Bank Corporate customers use different ERPs, hence the data formats are bound to be different Can the Bank’s IT systems convert the data formats that can be easily mapped to the corporate ERP How does the Bank manage the communication profiles of these customers?  Corporate customers are demanding near real time visibility on their corporate accounts Corporate customers can make better cash management decisions if they can analyse the impact. Can the Bank create opportunities to sell its products to the investment desks at corporate houses & manage their orders? How will the Bank bill the corporate customer for the value added services it provides. What does a SOA based Seamless STP solution bring to the table? Highlights of Oracle SOA based STP solution For the Corporate Customer: No Manual or Paper based banking transactions Secure Delivery of Payment data to the Bank from multiple ERPs without customization Single Portal for monitoring & administering payment transactions Rule based validation of payments Customer has data necessary for more effective handling of payment and cash management decisions  Business measurements track progress toward payment cost goals  For the Bank: Reduces time & complexity of transactions Simplifies the process of introducing new products to corporate customers Single Payment hub for all corporate ERP payments across multiple instruments New Revenue sources by delivering value added services to customers Leverages existing payment infrastructure Remove Inconsistent data formats and interchange between bank and corporate systems  Compliance and many other benefits

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  • Implementing Service Level Agreements in Enterprise Manager 12c for Oracle Packaged Applications

    - by Anand Akela
    Contributed by Eunjoo Lee, Product Manager, Oracle Enterprise Manager. Service Level Management, or SLM, is a key tool in the proactive management of any Oracle Packaged Application (e.g., E-Business Suite, Siebel, PeopleSoft, JD Edwards E1, Fusion Apps, etc.). The benefits of SLM are that administrators can utilize representative Application transactions, which are constantly and automatically running behind the scenes, to verify that all of the key application and technology components of an Application are available and performing to expectations. A single transaction can verify the availability and performance of the underlying Application Tech Stack in a much more efficient manner than by monitoring the same underlying targets individually. In this article, we’ll be demonstrating SLM using Siebel Applications, but the same tools and processes apply to any of the Package Applications mentioned above. In this demonstration, we will log into the Siebel Application, navigate to the Contacts View, update a contact phone record, and then log-out. This transaction exposes availability and performance metrics of multiple Siebel Servers, multiple Components and Component Groups, and the Siebel Database - in a single unified manner. We can then monitor and manage these transactions like any other target in EM 12c, including placing pro-active alerts on them if the transaction is either unavailable or is not performing to required levels. The first step in the SLM process is recording the Siebel transaction. The following screenwatch demonstrates how to record Siebel transaction using an EM tool called “OpenScript”. A completed recording is called a “Synthetic Transaction”. The second step in the SLM process is uploading the Synthetic Transaction into EM 12c, and creating Generic Service Tests. We can create a Generic Service Test to execute our synthetic transactions at regular intervals to evaluate the performance of various business flows. As these transactions are running periodically, it is possible to monitor the performance of the Siebel Application by evaluating the performance of the synthetic transactions. The process of creating a Generic Service Test is detailed in the next screenwatch. EM 12c provides a guided workflow for all of the key creation steps, including configuring the Service Test, uploading of the Synthetic Test, determining the frequency of the Service Test, establishing beacons, and selecting performance and usage metrics, just to name a few. The third and final step in the SLM process is the creation of Service Level Agreements (SLA). Service Level Agreements allow Administrators to utilize the previously created Service Tests to specify expected service levels for Application availability, performance, and usage. SLAs can be created for different time periods and for different Service Tests. This last screenwatch demonstrates the process of creating an SLA, as well as highlights the Dashboards and Reports that Administrators can use to monitor Service Test results. Hopefully, this article provides you with a good start point for creating Service Level Agreements for your E-Business Suite, Siebel, PeopleSoft, JD Edwards E1, or Fusion Applications. Enterprise Manager Cloud Control 12c, with the Application Management Suites, represents a quick and easy way to implement Service Level Management capabilities at customer sites. Stay Connected: Twitter |  Face book |  You Tube |  Linked in |  Google+ |  Newsletter

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  • TransactionScope won't work with DB2 provider

    - by Florin
    Hi Everyone, I've been trying to use TransactionScope with a DB2 database (using DB2 .Net provider v 9.0.0.2 and c# 2.0) which SHOULD be supported according to IBM. I have tried all the advice i could find on the IBM forums (such as here) to no avail. I have enabled XA transactions on my XP Sp2 machine, tried also from a Win 2003 Server machine but i consistently get the infamous error: ERROR [58005] [IBM][DB2/NT] SQL0998N Error occurred during transaction or heuristic processing. Reason Code = "16". Subcode = "2-80004005". SQLSTATE=58005 The windows event log says: The XA Transaction Manager attempted to load the XA resource manager DLL. The call to LOADLIBRARY for the XA resource manager DLL failed: DLL=C:\APPS\IBM\DB2v95fp2\SQLLIB\BIN\DB2APP.DLL File=d:\comxp_sp2\com\com1x\dtc\dtc\xatm\src\xarmconn.cpp Line=2467. Also, granted the NETWORK SERVICE user full rights to the folder and dll. Here's the MSDTC startup message MS DTC started with the following settings: Security Configuration (OFF = 0 and ON = 1): Network Administration of Transactions = 0, Network Clients = 0, Inbound Distributed Transactions using Native MSDTC Protocol = 0, Outbound Distributed Transactions using Native MSDTC Protocol = 0, Transaction Internet Protocol (TIP) = 0, XA Transactions = 1 Any help would be much appreciated! Thanks, Florin

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  • Crypted_password is null when using Authlogic to save a user

    - by kareem
    i'm getting a strange error on my production install when i try and create a new user using AL: ActiveRecord::StatementInvalid: Mysql::Error: Column 'crypted_password' cannot be null: INSERT INTO users especially strange b/c it works as expected on my local box. RUnning Rails 2.3.2 and ruby 1.8.7 on both boxes. user.rb: class User < ActiveRecord::Base before_create :set_username acts_as_authentic do |c| c.require_password_confirmation = false c.login_field = "email" c.validates_length_of_password_field_options = {:minimum => 4} c.validate_login_field = false #don't validate email field with additional validations end end Here's output from my production console: >> u = User.new => #<User id: nil, username: nil, email: nil, crypted_password: nil, password_salt: nil, persistence_token: nil, single_access_token: nil, perishable_token: nil, login_count: 0, failed_login_count: 0, last_request_at: nil, current_login_at: nil, last_login_at: nil, current_login_ip: nil, last_login_ip: nil, created_at: nil, updated_at: nil, is_admin: 0, first_name: nil, last_name: nil> >> u.full_name = 'john smith' => "john smith" >> u.password = 'test' => "test" >> u.email = '[email protected]' => "[email protected]" >> u.valid? => true >> u.save ActiveRecord::StatementInvalid: Mysql::Error: Column 'crypted_password' cannot be null: INSERT INTO `users` (`single_access_token`, `last_request_at`, `created_at`, `crypted_password`, `perishable_token`, `updated_at`, `username`, `failed_login_count`, `current_login_ip`, `password_salt`, `current_login_at`, `is_admin`, `persistence_token`, `login_count`, `last_name`, `last_login_ip`, `last_login_at`, `email`, `first_name`) VALUES('B-XSXwhO7hkbtISIOyEq', NULL, '2009-07-31 01:10:44', NULL, 'FK3mYS2Tp5Tzeq5IXE1z', '2009-07-31 01:10:44', 'john', 0, NULL, NULL, NULL, 0, '2c76b645f761eb3509353290e93874cecdb68a63caa165812ab1b126d63660757090ecf69995caef9e78f93d070b524e2542b3fec4ee050726088c2a9fdb0c9f', 0, 'smith', NULL, NULL, '[email protected]', 'john') from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/abstract_adapter.rb:212:in `log' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/mysql_adapter.rb:320:in `execute' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/abstract/database_statements.rb: 259:in `insert_sql' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/mysql_adapter.rb:330:in `insert_sql' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/abstract/database_statements.rb: 44:in `insert_without_query_dirty' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/abstract/query_cache.rb:18:in `insert' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/base.rb:2902:in `create_without_timestamps' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/timestamp.rb:29:in `create_without_callbacks' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/callbacks.rb:266:in `create' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/base.rb:2868:in `create_or_update_without_callbacks' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/callbacks.rb:250:in `create_or_update' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/base.rb:2539:in `save_without_validation' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/validations.rb:1009:in `save_without_dirty' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/dirty.rb:79:in `save_without_transactions' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:229:in `send' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:229:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/connection_adapters/abstract/database_statements.rb: 136:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:182:in `transaction' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:228:in `with_transaction_returning_status' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:196:in `save' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:208:in `rollback_active_record_state!' from /usr/lib/ruby/gems/1.8/gems/activerecord-2.3.2/lib/ active_record/transactions.rb:196:in `save' No idea why this is happening, and especially why this saves a new user on dev but not on production. Any help is much appreciated, thanks! edit: using Apache & Passenger 2.2.4

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  • Using Rails, problem testing has_many relationship

    - by east
    The summary is that I've code that works when manually testing, but isn't doing what I would think it should when trying to build an automated test. Here are the details: I've two models: Payment and PaymentTranscation. class Payment ... has_many :transactions, :class_name => 'PaymentTransaction' class PaymentTranscation ... belongs_to payment The PaymentTransaction is only created in a Payment model method, like so: def pay_up ... transactions.create!(params...) ... end I've manually tested this code, inspected the database, and everything works well. The failing automated test looks like this: def test_pay_up purchase = Payment.new(...) assert purchase.save assert_equal purchase.state, :initialized.to_s assert purchase.pay_up # this should create a new PaymentTransaction... assert_equal purchase.state, :succeeded.to_s assert_equal purchase.transactions.count, 1 # FAILS HERE; transactions is an empty array end If I step through the code, it's clear that the PaymentTransaction is getting created correctly (though I can't see it in the database because everything is in a testing transaction). What I can't figure out is why transactions is returning an empty array in the test when I know a valid PaymentTransaction is getting created. Anybody have some suggestions? Thanks in advance, east

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  • How to remove/hide Atomikos startup error message?

    - by HDave
    When Atomikos is configured via Spring, a jta.properties or transactions.properties file is not needed. Nonetheless, Atomikos starts up with the follow messages printed to stderr: No properties path set - looking for transactions.properties in classpath... transactions.properties not found - looking for jta.properties in classpath... Failed to open transactions properties file - using default values It makes it look like the Spring configuration didn't take -- although apparently everything is fine. Does anyone know how to get rid of this so I don't end up getting asked about it 1.000 times?

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