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  • How to configure Spring-DM OSGi service for new instance per call?

    - by Bhav
    I'm starting to delve into using Spring DM and OSGi services in an RCP application. I've created a service which is used by another bundle in the RCP application. It does a lookup of the service via calls to getBundleContext().getServiceReference() using the explicit bundle names and service class names. I'm not using DI anywhere yet. The issue I'm running into is that the service that is returned in the requesting bundle is a singleton. At times I notice a threading issue since it is a "stateful" service. How do I configure the application to get back a new service instance with each call? Here is my spring xml file contents which registers the service: <bean id="myServBean" class="com.xyz.ClassImpl"/> <osgi:service ref="myServBean" class="com.xyz.Class"/>

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  • SQL SERVER – Out of the Box – Activty and Performance Reports from SSSMS

    - by pinaldave
    SQL Server management Studio 2008 is wonderful tool and has many different features. Many times, an average user does not use them as they are not aware about these features. Today, we will learn one such feature. SSMS comes with many inbuilt performance and activity reports, but we do not use it to the full potential. Let us see how we can access these standard reports. Connect to SQL Server Node >> Right Click on it >> Go to Reports >> Click on Standard Reports >> Pick Any Report. Click to Enlarge You can see there are many reports, which an average users needs right away, are available there. Let me list all the reports available. Server Dashboard Configuration Changes History Schema Changes History Scheduler Health Memory Consumption Activity – All Blocking Transactions Activity – All Cursors Activity – All Sessions Activity – Top Sessions Activity – Dormant Sessions Activity -  Top Connections Top Transactions by Age Top Transactions by Blocked Transactions Count Top Transactions by Locks Count Performance – Batch Execution Statistics Performance – Object Execution Statistics Performance – Top Queries by Average CPU Time Performance – Top Queries by Average IO Performance – Top Queries by Total CPU Time Performance – Top Queries by Total IO Service Broker Statistics Transactions Log Shipping Status In fact, when you look at the above list, it is fairly clear that they are very thought out and commonly needed reports that are available in SQL Server 2008. Let us run a couple of reports and observe their result. Performance – Top Queries by Total CPU Time Click to Enlarge Memory Consumption Click to Enlarge There are options for custom reports as well, which we can configure. We will learn about them in some other post. Additionally, you can right click on the reports and export in Excel or PDF. I think this tool can really help those who are just looking for some quick details. Does any of you use this feature, or this feature has some limitations and You would like to see more features? Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology

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  • Fraud Detection with the SQL Server Suite Part 1

    - by Dejan Sarka
    While working on different fraud detection projects, I developed my own approach to the solution for this problem. In my PASS Summit 2013 session I am introducing this approach. I also wrote a whitepaper on the same topic, which was generously reviewed by my friend Matija Lah. In order to spread this knowledge faster, I am starting a series of blog posts which will at the end make the whole whitepaper. Abstract With the massive usage of credit cards and web applications for banking and payment processing, the number of fraudulent transactions is growing rapidly and on a global scale. Several fraud detection algorithms are available within a variety of different products. In this paper, we focus on using the Microsoft SQL Server suite for this purpose. In addition, we will explain our original approach to solving the problem by introducing a continuous learning procedure. Our preferred type of service is mentoring; it allows us to perform the work and consulting together with transferring the knowledge onto the customer, thus making it possible for a customer to continue to learn independently. This paper is based on practical experience with different projects covering online banking and credit card usage. Introduction A fraud is a criminal or deceptive activity with the intention of achieving financial or some other gain. Fraud can appear in multiple business areas. You can find a detailed overview of the business domains where fraud can take place in Sahin Y., & Duman E. (2011), Detecting Credit Card Fraud by Decision Trees and Support Vector Machines, Proceedings of the International MultiConference of Engineers and Computer Scientists 2011 Vol 1. Hong Kong: IMECS. Dealing with frauds includes fraud prevention and fraud detection. Fraud prevention is a proactive mechanism, which tries to disable frauds by using previous knowledge. Fraud detection is a reactive mechanism with the goal of detecting suspicious behavior when a fraudster surpasses the fraud prevention mechanism. A fraud detection mechanism checks every transaction and assigns a weight in terms of probability between 0 and 1 that represents a score for evaluating whether a transaction is fraudulent or not. A fraud detection mechanism cannot detect frauds with a probability of 100%; therefore, manual transaction checking must also be available. With fraud detection, this manual part can focus on the most suspicious transactions. This way, an unchanged number of supervisors can detect significantly more frauds than could be achieved with traditional methods of selecting which transactions to check, for example with random sampling. There are two principal data mining techniques available both in general data mining as well as in specific fraud detection techniques: supervised or directed and unsupervised or undirected. Supervised techniques or data mining models use previous knowledge. Typically, existing transactions are marked with a flag denoting whether a particular transaction is fraudulent or not. Customers at some point in time do report frauds, and the transactional system should be capable of accepting such a flag. Supervised data mining algorithms try to explain the value of this flag by using different input variables. When the patterns and rules that lead to frauds are learned through the model training process, they can be used for prediction of the fraud flag on new incoming transactions. Unsupervised techniques analyze data without prior knowledge, without the fraud flag; they try to find transactions which do not resemble other transactions, i.e. outliers. In both cases, there should be more frauds in the data set selected for checking by using the data mining knowledge compared to selecting the data set with simpler methods; this is known as the lift of a model. Typically, we compare the lift with random sampling. The supervised methods typically give a much better lift than the unsupervised ones. However, we must use the unsupervised ones when we do not have any previous knowledge. Furthermore, unsupervised methods are useful for controlling whether the supervised models are still efficient. Accuracy of the predictions drops over time. Patterns of credit card usage, for example, change over time. In addition, fraudsters continuously learn as well. Therefore, it is important to check the efficiency of the predictive models with the undirected ones. When the difference between the lift of the supervised models and the lift of the unsupervised models drops, it is time to refine the supervised models. However, the unsupervised models can become obsolete as well. It is also important to measure the overall efficiency of both, supervised and unsupervised models, over time. We can compare the number of predicted frauds with the total number of frauds that include predicted and reported occurrences. For measuring behavior across time, specific analytical databases called data warehouses (DW) and on-line analytical processing (OLAP) systems can be employed. By controlling the supervised models with unsupervised ones and by using an OLAP system or DW reports to control both, a continuous learning infrastructure can be established. There are many difficulties in developing a fraud detection system. As has already been mentioned, fraudsters continuously learn, and the patterns change. The exchange of experiences and ideas can be very limited due to privacy concerns. In addition, both data sets and results might be censored, as the companies generally do not want to publically expose actual fraudulent behaviors. Therefore it can be quite difficult if not impossible to cross-evaluate the models using data from different companies and different business areas. This fact stresses the importance of continuous learning even more. Finally, the number of frauds in the total number of transactions is small, typically much less than 1% of transactions is fraudulent. Some predictive data mining algorithms do not give good results when the target state is represented with a very low frequency. Data preparation techniques like oversampling and undersampling can help overcome the shortcomings of many algorithms. SQL Server suite includes all of the software required to create, deploy any maintain a fraud detection infrastructure. The Database Engine is the relational database management system (RDBMS), which supports all activity needed for data preparation and for data warehouses. SQL Server Analysis Services (SSAS) supports OLAP and data mining (in version 2012, you need to install SSAS in multidimensional and data mining mode; this was the only mode in previous versions of SSAS, while SSAS 2012 also supports the tabular mode, which does not include data mining). Additional products from the suite can be useful as well. SQL Server Integration Services (SSIS) is a tool for developing extract transform–load (ETL) applications. SSIS is typically used for loading a DW, and in addition, it can use SSAS data mining models for building intelligent data flows. SQL Server Reporting Services (SSRS) is useful for presenting the results in a variety of reports. Data Quality Services (DQS) mitigate the occasional data cleansing process by maintaining a knowledge base. Master Data Services is an application that helps companies maintaining a central, authoritative source of their master data, i.e. the most important data to any organization. For an overview of the SQL Server business intelligence (BI) part of the suite that includes Database Engine, SSAS and SSRS, please refer to Veerman E., Lachev T., & Sarka D. (2009). MCTS Self-Paced Training Kit (Exam 70-448): Microsoft® SQL Server® 2008 Business Intelligence Development and Maintenance. MS Press. For an overview of the enterprise information management (EIM) part that includes SSIS, DQS and MDS, please refer to Sarka D., Lah M., & Jerkic G. (2012). Training Kit (Exam 70-463): Implementing a Data Warehouse with Microsoft® SQL Server® 2012. O'Reilly. For details about SSAS data mining, please refer to MacLennan J., Tang Z., & Crivat B. (2009). Data Mining with Microsoft SQL Server 2008. Wiley. SQL Server Data Mining Add-ins for Office, a free download for Office versions 2007, 2010 and 2013, bring the power of data mining to Excel, enabling advanced analytics in Excel. Together with PowerPivot for Excel, which is also freely downloadable and can be used in Excel 2010, is already included in Excel 2013. It brings OLAP functionalities directly into Excel, making it possible for an advanced analyst to build a complete learning infrastructure using a familiar tool. This way, many more people, including employees in subsidiaries, can contribute to the learning process by examining local transactions and quickly identifying new patterns.

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  • SQL query mixing aggregated results and single values

    - by Paul Flowerdew
    I have a table with transactions. Each transaction has a transaction ID, and accounting period (AP), and a posting value (PV), as well as other fields. Some of the IDs are duplicated, usually because the transaction was done in error. To give an example, part of the table might look like: ID PV AP 123 100 2 123 -100 5 In this case the transaction was added in AP2 then removed in AP5. Another example would be: ID PV AP 456 100 2 456 -100 5 456 100 8 In the first example, the problem is that if I am analyzing what was spent in AP2, there is a transaction in there which actually shouldn't be taken into account because it was taken out again in AP5. In the second example, the second two transactions shouldn't be taken into account because they cancel each other out. I want to label as many transactions as possible which shouldn't be taken into account as erroneous. To identify these transactions, I want to find the ones with duplicate IDs whose PVs sum to zero (like ID 123 above) or transactions where the PV of the earliest one is equal to sum(PV), as in the second example. This second condition is what is causing me grief. So far I have SELECT * FROM table WHERE table.ID IN (SELECT table.ID FROM table GROUP BY table.ID HAVING COUNT(*) > 1 AND (SUM(table.PV) = 0 OR SUM(table.PV) = <PV of first transaction in each group>)) ORDER BY table.ID; The bit in chevrons is what I'm trying to do and I'm stuck. Can I do it like this or is there some other method I can use in SQL to do this? Edit 1: Btw I forgot to say that I'm using SQL Compact 3.5, in case it matters. Edit 2: I think the code snippet above is a bit misleading. I still want to mark out transactions with duplicate IDs where sum(PV) = 0, as in the first example. But where the PV of the earliest transaction = sum(PV), as in the second example, what I actually want is to keep the earliest transaction and mark out all the others with the same ID. Sorry if that caused confusion. Edit 3: I've been playing with Clodoaldo's solution and have made some progress, but still can't get quite what I want. I'm trying to get the transactions I know for certain to be erroneous. Suppose the following transactions are also in the table: ID PV AP 789 100 2 789 200 5 789 -100 8 In this example sum(PV) < 0 and the earliest PV < sum(PV) so I don't want to mark any of these out. If I modify Clodoaldo's query as follows: select t.* from t left join ( select id, min(ap) as ap, sum(pv) as sum_pv from t group by id having sum(pv) <> 0 ) s on t.id = s.id and t.ap = s.ap and t.pv = s.sum_pv where s.id is null This gives the result ID PV AP 123 100 2 123 -100 5 456 -100 5 456 100 8 789 100 3 789 200 5 789 -100 8 Whilst the first 4 transactions are ok (they would be marked out), the 789 transactions are also there, and I don't want them. But I can't figure out how to modify the query so that they're not included. Any ideas?

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  • Saving child collections with NHibernate

    - by Ben
    Hi, I am in the process or learning NHibernate so bare with me. I have an Order class and a Transaction class. Order has a one to many association with transaction. The transaction table in my database has a not null constraint on the OrderId foreign key. Order class: public class Order { public virtual Guid Id { get; set; } public virtual DateTime CreatedOn { get; set; } public virtual decimal Total { get; set; } public virtual ICollection<Transaction> Transactions { get; set; } public Order() { Transactions = new HashSet<Transaction>(); } } Order Mapping: <class name="Order" table="Orders"> <cache usage="read-write"/> <id name="Id"> <generator class="guid"/> </id> <property name="CreatedOn" type="datetime"/> <property name="Total" type="decimal"/> <set name="Transactions" table="Transactions" lazy="false" inverse="true"> <key column="OrderId"/> <one-to-many class="Transaction"/> </set> Transaction Class: public class Transaction { public virtual Guid Id { get; set; } public virtual DateTime ExecutedOn { get; set; } public virtual bool Success { get; set; } public virtual Order Order { get; set; } } Transaction Mapping: <class name="Transaction" table="Transactions"> <cache usage="read-write"/> <id name="Id" column="Id" type="Guid"> <generator class="guid"/> </id> <property name="ExecutedOn" type="datetime"/> <property name="Success" type="bool"/> <many-to-one name="Order" class="Order" column="OrderId" not-null="true"/> Really I don't want a bidirectional association. There is no need for my transaction objects to reference their order object directly (I just need to access the transactions of an order). However, I had to add this so that Order.Transactions is persisted to the database: Repository: public void Update(Order entity) { using (ISession session = NHibernateHelper.OpenSession()) { using (ITransaction transaction = session.BeginTransaction()) { session.Update(entity); foreach (var tx in entity.Transactions) { tx.Order = entity; session.SaveOrUpdate(tx); } transaction.Commit(); } } } My problem is that this will then issue an update for every transaction on the order collection (regardless of whether it has changed or not). What I was trying to get around was having to explicitly save the transaction before saving the order and instead just add the transactions to the order and then save the order: public void Can_add_transaction_to_existing_order() { var orderRepo = new OrderRepository(); var order = orderRepo.GetById(new Guid("aa3b5d04-c5c8-4ad9-9b3e-9ce73e488a9f")); Transaction tx = new Transaction(); tx.ExecutedOn = DateTime.Now; tx.Success = true; order.Transactions.Add(tx); orderRepo.Update(order); } Although I have found quite a few articles covering the set up of a one-to-many association, most of these discuss retrieving of data and not persisting back. Many thanks, Ben

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  • JPA Entity (in multiple persistence-unit) in OSGi (Spring DM) Environnement is confusing me.

    - by Vincent Demeester
    Hi, I'm a bit confused about a strange behavior of my JPA's related objects. I have three bundle : The User bundle does contain some user-related objects, but mainly the User object. The Energy bundle does contain some energy-related objects, and particularly a ConsumptionTerminal which contains a List of User. The Index bundle does contain an Index object that has no dependency at all. My OSGi environment is the following : A DataSource bundle that provide 2 services : dataSource and jpaVendorAdapter. The three bundles. They consume dataSource and jpaVendorAdapter. Their module-context.xml file look like : And they all have a persistence.xml file : User <?xml version="1.0" encoding="UTF-8"?> <persistence> <persistence-unit name="securityPU" transaction-type="JTA"> <jta-data-source>java:/securityDataSourceService</jta-data-source> <class>net.nextep.amundsen.security.domain.User</class> <!-- [...] --> <exclude-unlisted-classes>true</exclude-unlisted-classes> <properties> <property name="eclipselink.logging.level" value="INFO" /> <property name="eclipselink.ddl-generation" value="create-tables" /> <property name="eclipselink.ddl-generation.output-mode" value="database" /> <property name="eclipselink.orm.throw.exceptions" value="true" /> </properties> </persistence-unit> </persistence> Energy <?xml version="1.0" encoding="UTF-8"?> <persistence> <persistence-unit name="energyPU" transaction-type="JTA"> <jta-data-source>java:/securityDataSourceService</jta-data-source> <class>net.nextep.amundsen.security.domain.User</class> <class>net.nextep.amundsen.energy.domain.User</class> <!-- [...] --> <exclude-unlisted-classes>true</exclude-unlisted-classes> <properties> <property name="eclipselink.logging.level" value="INFO" /> <property name="eclipselink.ddl-generation" value="create-tables" /> <property name="eclipselink.ddl-generation.output-mode" value="database" /> <property name="eclipselink.orm.throw.exceptions" value="true" /> </properties> </persistence-unit> </persistence> Index : This one has the most simple persistence.xml with just the Index class (no shared Class). I'm using named @PersistenceUnit annotation like @PersitenceUnit(name = 'securityPU') (for the User bundle). And finally, I'm using EclipseLink as Jpa provider and Spring DM (+ Spring DM Server in the development process) The problem is the following : When the User bundle is deployed, I'm able to persist User objects. When the User bundle and Energy bundles are both deployed, I'm not able to persist User objects (neither the Energy object). But I don't have any exception at all ! There is no problem at all with the Index bundle. The bug is dataSource independent (I tried with PostgreSQL and MySQL so far). My first conclusion was that the <class>net.nextep.amundsen.security.domain.User</class> in both persistence unit was causing the trouble. I tried without it (and hiding the User dependent object in the Energy bundle) but it failed too. I'm a bit confused about that bug. I'm also not quite sure about the transaction management in this context. I wasn't the one who designed this architecture (but I tell my intern OK without testing it.. shame on me) but if I could understand this bug and maybe fix it without rewrite the bundle (and break my intern work), I would appreciate. Am I doing something wrong ? (it's obvious, but what..) Did I miss something while reading documentation ? By the way, I'm also looking for some best practices or advices when it comes to JPA, EclipseLink (or whatever JPA Provider) and Spring DM (and OSGi in general). I found interesting slides from Mike Keith about this topic (by browsing Stackoverflow).

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  • Defines JEE 5 the handling of commit error using bean managed transactions?

    - by marabol
    I'm using glassfish 2.1 and 2.1.1. If I've a bean method annotated by @TransactionAttribute(value = TransactionAttributeType.REQUIRES_NEW). After doing some JPA stuff the commit fails in the afterCompletion-Phase of JTS. GlassFish logs this failure only. And the caller of this bean method has no chance to know something goes wrong. So I wonder, if there is any definition how a jee 5 server has to handle exceptions while commiting. I would expect any runtime exception. I'm using stateless beans. With SessionSynchronisation I could get the commit failue, if I use statefull beans. Is it possible to intercept, so I can throw an exception, that I've declared in my interface? This is the whole exception stacktrace: [#|2010-05-06T12:15:54.840+0000|WARNING|sun-appserver2.1|oracle.toplink.essentials.session.file:/C:/glassfish/domains/domain1/applications/j2ee-apps/my-ear-1.0.0-SNAPSHOT/my-jar-1.1.8_jar/-myPu.transaction|_ThreadID=25;_ThreadName=p: thread-pool-1; w: 15;_RequestID=67a475a1-25c3-4416-abea-0d159f715373;| java.lang.RuntimeException: Got exception during XAResource.end: oracle.jdbc.xa.OracleXAException at com.sun.enterprise.distributedtx.J2EETransactionManagerOpt.delistResource(J2EETransactionManagerOpt.java:224) at com.sun.enterprise.resource.ResourceManagerImpl.unregisterResource(ResourceManagerImpl.java:265) at com.sun.enterprise.resource.ResourceManagerImpl.delistResource(ResourceManagerImpl.java:223) at com.sun.enterprise.resource.PoolManagerImpl.resourceClosed(PoolManagerImpl.java:400) at com.sun.enterprise.resource.ConnectorAllocator$ConnectionListenerImpl.connectionClosed(ConnectorAllocator.java:72) at com.sun.gjc.spi.ManagedConnection.connectionClosed(ManagedConnection.java:639) at com.sun.gjc.spi.base.ConnectionHolder.close(ConnectionHolder.java:201) at com.sun.gjc.spi.jdbc40.ConnectionHolder40.close(ConnectionHolder40.java:519) at oracle.toplink.essentials.internal.databaseaccess.DatabaseAccessor.closeDatasourceConnection(DatabaseAccessor.java:394) at oracle.toplink.essentials.internal.databaseaccess.DatasourceAccessor.closeConnection(DatasourceAccessor.java:382) at oracle.toplink.essentials.internal.databaseaccess.DatabaseAccessor.closeConnection(DatabaseAccessor.java:417) at oracle.toplink.essentials.internal.databaseaccess.DatasourceAccessor.afterJTSTransaction(DatasourceAccessor.java:115) at oracle.toplink.essentials.threetier.ClientSession.afterTransaction(ClientSession.java:119) at oracle.toplink.essentials.internal.sessions.UnitOfWorkImpl.afterTransaction(UnitOfWorkImpl.java:1841) at oracle.toplink.essentials.transaction.AbstractSynchronizationListener.afterCompletion(AbstractSynchronizationListener.java:170) at oracle.toplink.essentials.transaction.JTASynchronizationListener.afterCompletion(JTASynchronizationListener.java:102) at com.sun.jts.jta.SynchronizationImpl.after_completion(SynchronizationImpl.java:154) at com.sun.jts.CosTransactions.RegisteredSyncs.distributeAfter(RegisteredSyncs.java:210) at com.sun.jts.CosTransactions.TopCoordinator.afterCompletion(TopCoordinator.java:2585) at com.sun.jts.CosTransactions.CoordinatorTerm.commit(CoordinatorTerm.java:433) at com.sun.jts.CosTransactions.TerminatorImpl.commit(TerminatorImpl.java:250) at com.sun.jts.CosTransactions.CurrentImpl.commit(CurrentImpl.java:623) at com.sun.jts.jta.TransactionManagerImpl.commit(TransactionManagerImpl.java:309) at com.sun.enterprise.distributedtx.J2EETransactionManagerImpl.commit(J2EETransactionManagerImpl.java:1029) at com.sun.enterprise.distributedtx.J2EETransactionManagerOpt.commit(J2EETransactionManagerOpt.java:398) at com.sun.ejb.containers.BaseContainer.completeNewTx(BaseContainer.java:3817) at com.sun.ejb.containers.BaseContainer.postInvokeTx(BaseContainer.java:3610) at com.sun.ejb.containers.BaseContainer.postInvoke(BaseContainer.java:1379) at com.sun.ejb.containers.BaseContainer.postInvoke(BaseContainer.java:1316) at com.sun.ejb.containers.EJBLocalObjectInvocationHandler.invoke(EJBLocalObjectInvocationHandler.java:205) at com.sun.ejb.containers.EJBLocalObjectInvocationHandlerDelegate.invoke(EJBLocalObjectInvocationHandlerDelegate.java:127) at $Proxy127.myNewTxMethod(Unknown Source) at mypackage.MyBean2.myMethod(MyBean2.java:197) at mypackage.MyBean2.myMethod2(MyBean2.java:166) at mypackage.MyBean2.myMethod3(MyBean2.java:105) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at com.sun.enterprise.security.application.EJBSecurityManager.runMethod(EJBSecurityManager.java:1011) at com.sun.enterprise.security.SecurityUtil.invoke(SecurityUtil.java:175) at com.sun.ejb.containers.BaseContainer.invokeTargetBeanMethod(BaseContainer.java:2920) at com.sun.ejb.containers.BaseContainer.intercept(BaseContainer.java:4011) at com.sun.ejb.containers.EJBLocalObjectInvocationHandler.invoke(EJBLocalObjectInvocationHandler.java:197) at com.sun.ejb.containers.EJBLocalObjectInvocationHandlerDelegate.invoke(EJBLocalObjectInvocationHandlerDelegate.java:127) at $Proxy158.myMethod3(Unknown Source) at mypackage.MyBean3.myMethod4(MyBean3.java:94) at mypackage.MyBean3.onMessage(MyBean3.java:85) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at com.sun.enterprise.security.SecurityUtil$2.run(SecurityUtil.java:181) at java.security.AccessController.doPrivileged(Native Method) at com.sun.enterprise.security.application.EJBSecurityManager.doAsPrivileged(EJBSecurityManager.java:985) at com.sun.enterprise.security.SecurityUtil.invoke(SecurityUtil.java:186) at com.sun.ejb.containers.BaseContainer.invokeTargetBeanMethod(BaseContainer.java:2920) at com.sun.ejb.containers.BaseContainer.intercept(BaseContainer.java:4011) at com.sun.ejb.containers.MessageBeanContainer.deliverMessage(MessageBeanContainer.java:1111) at com.sun.ejb.containers.MessageBeanListenerImpl.deliverMessage(MessageBeanListenerImpl.java:74) at com.sun.enterprise.connectors.inflow.MessageEndpointInvocationHandler.invoke(MessageEndpointInvocationHandler.java:179) at $Proxy192.onMessage(Unknown Source) at com.sun.messaging.jms.ra.OnMessageRunner.run(OnMessageRunner.java:258) at com.sun.enterprise.connectors.work.OneWork.doWork(OneWork.java:76) at com.sun.corba.ee.impl.orbutil.threadpool.ThreadPoolImpl$WorkerThread.run(ThreadPoolImpl.java:555) |#]

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  • What is a simple way to get ACID transactions with persistence on the local file system (in Java)?

    - by T.R.
    I'm working on a small (java) project where a website needs to maintain a (preferably comma-separated) list of registered e-mail addresses, nothing else, and be able to check if an address is in the list. I have no control over the hosting or the server's lack of database support. Prevayler seemed a good solution, but the website is a ghost town, with example code missing from just about everywhere it's supposed to be, so I'm a little wary. What other options are recommended for such a task?

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  • How to handle request-wise DB transactions in ASP.NET MVC?

    - by Dario Solera
    I'm using SubSonic 3.0 (SimpleRepository) to handle database access in my ASP.NET MVC 1.0 application. It would be nice to handle a transaction for every web request, committing if everything went smooth and rolling back in case of exception. Is this possible? If so, how? I know this topic has been discussed many times, but I just couldn't find a satisfactory answer. I have built my own solution (create a TransactionScope in the controller, then commit/rollback in OnActionExecuted), but it turns out to be very unreliable.

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  • Paypal development. encrypt transactions. php p12

    - by ninchen
    when i take a look at the paypal documentation, they say "Note that the PayPal SDK for PHP does not require SSL encryption". https://developer.paypal.com/docs/classic/api/apiCredentials/#encrypting-your-certificate Is the statement of this phrase, that i don't have to create a p12 certificate when working with php, but use the public_key.pem and paypal_public_key.pem? If yes: Is it secure enough to create the encrypted form input elements without p12 certificate? If no: What do they mean? :-) Before this question came up, i've tested this little programm. http://www.softarea51.com/blog/how-to-integrate-your-custom-shopping-cart-with-paypal-website-payments-standard-using-php/ There is a config file paypal-wps-config.inc.php where i can define the paths to my certificates. // tryed to use // 'paypal_cert.p12 '; $config['private_key_path'] = '/home/folder/.cert/pp/prvkey.pem'; // must match the one you set when you created the private key $config['private_key_password'] = ''; //'my_password'; When i try to use the p12 certificate, openssl_error_string() returns "Could not sign data: error:0906D06C:PEM routines:PEM_read_bio:no start line openssl_pkcs7_sign When i instead use the prvkey.pem without password all works fine. Here is the function, which signs and encrypt the data. function signAndEncrypt($dataStr_, $ewpCertPath_, $ewpPrivateKeyPath_, $ewpPrivateKeyPwd_, $paypalCertPath_) { $dataStrFile = realpath(tempnam('/tmp', 'pp_')); $fd = fopen($dataStrFile, 'w'); if(!$fd) { $error = "Could not open temporary file $dataStrFile."; return array("status" => false, "error_msg" => $error, "error_no" => 0); } fwrite($fd, $dataStr_); fclose($fd); $signedDataFile = realpath(tempnam('/tmp', 'pp_')); **// here the error came from** if(!@openssl_pkcs7_sign( $dataStrFile, $signedDataFile, "file://$ewpCertPath_", array("file://$ewpPrivateKeyPath_", $ewpPrivateKeyPwd_), array(), PKCS7_BINARY)) { unlink($dataStrFile); unlink($signedDataFile); $error = "Could not sign data: ".openssl_error_string(); return array("status" => false, "error_msg" => $error, "error_no" => 0); } unlink($dataStrFile); $signedData = file_get_contents($signedDataFile); $signedDataArray = explode("\n\n", $signedData); $signedData = $signedDataArray[1]; $signedData = base64_decode($signedData); unlink($signedDataFile); $decodedSignedDataFile = realpath(tempnam('/tmp', 'pp_')); $fd = fopen($decodedSignedDataFile, 'w'); if(!$fd) { $error = "Could not open temporary file $decodedSignedDataFile."; return array("status" => false, "error_msg" => $error, "error_no" => 0); } fwrite($fd, $signedData); fclose($fd); $encryptedDataFile = realpath(tempnam('/tmp', 'pp_')); if(!@openssl_pkcs7_encrypt( $decodedSignedDataFile, $encryptedDataFile, file_get_contents($paypalCertPath_), array(), PKCS7_BINARY)) { unlink($decodedSignedDataFile); unlink($encryptedDataFile); $error = "Could not encrypt data: ".openssl_error_string(); return array("status" => false, "error_msg" => $error, "error_no" => 0); } unlink($decodedSignedDataFile); $encryptedData = file_get_contents($encryptedDataFile); if(!$encryptedData) { $error = "Encryption and signature of data failed."; return array("status" => false, "error_msg" => $error, "error_no" => 0); } unlink($encryptedDataFile); $encryptedDataArray = explode("\n\n", $encryptedData); $encryptedData = trim(str_replace("\n", '', $encryptedDataArray[1])); return array("status" => true, "encryptedData" => $encryptedData); } // signAndEncrypt } // PPCrypto The main questions: 1. Is it possible to use p12 cert with php, or is it secure enough to work without it? 2. Why i become an error when using openssl_pkcs7_sign Please help. Greetings ninchen

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  • Commit in SQL

    - by PRajkumar
    SQL Transaction Control Language Commands (TCL)                                           (COMMIT) Commit Transaction As a SQL language we use transaction control language very frequently. Committing a transaction means making permanent the changes performed by the SQL statements within the transaction. A transaction is a sequence of SQL statements that Oracle Database treats as a single unit. This statement also erases all save points in the transaction and releases transaction locks. Oracle Database issues an implicit COMMIT before and after any data definition language (DDL) statement. Oracle recommends that you explicitly end every transaction in your application programs with a COMMIT or ROLLBACK statement, including the last transaction, before disconnecting from Oracle Database. If you do not explicitly commit the transaction and the program terminates abnormally, then the last uncommitted transaction is automatically rolled back.   Until you commit a transaction: ·         You can see any changes you have made during the transaction by querying the modified tables, but other users cannot see the changes. After you commit the transaction, the changes are visible to other users' statements that execute after the commit ·         You can roll back (undo) any changes made during the transaction with the ROLLBACK statement   Note: Most of the people think that when we type commit data or changes of what you have made has been written to data files, but this is wrong when you type commit it means that you are saying that your job has been completed and respective verification will be done by oracle engine that means it checks whether your transaction achieved consistency when it finds ok it sends a commit message to the user from log buffer but not from data buffer, so after writing data in log buffer it insists data buffer to write data in to data files, this is how it works.   Before a transaction that modifies data is committed, the following has occurred: ·         Oracle has generated undo information. The undo information contains the old data values changed by the SQL statements of the transaction ·         Oracle has generated redo log entries in the redo log buffer of the System Global Area (SGA). The redo log record contains the change to the data block and the change to the rollback block. These changes may go to disk before a transaction is committed ·         The changes have been made to the database buffers of the SGA. These changes may go to disk before a transaction is committed   Note:   The data changes for a committed transaction, stored in the database buffers of the SGA, are not necessarily written immediately to the data files by the database writer (DBWn) background process. This writing takes place when it is most efficient for the database to do so. It can happen before the transaction commits or, alternatively, it can happen some times after the transaction commits.   When a transaction is committed, the following occurs: 1.      The internal transaction table for the associated undo table space records that the transaction has committed, and the corresponding unique system change number (SCN) of the transaction is assigned and recorded in the table 2.      The log writer process (LGWR) writes redo log entries in the SGA's redo log buffers to the redo log file. It also writes the transaction's SCN to the redo log file. This atomic event constitutes the commit of the transaction 3.      Oracle releases locks held on rows and tables 4.      Oracle marks the transaction complete   Note:   The default behavior is for LGWR to write redo to the online redo log files synchronously and for transactions to wait for the redo to go to disk before returning a commit to the user. However, for lower transaction commit latency application developers can specify that redo be written asynchronously and that transaction do not need to wait for the redo to be on disk.   The syntax of Commit Statement is   COMMIT [WORK] [COMMENT ‘your comment’]; ·         WORK is optional. The WORK keyword is supported for compliance with standard SQL. The statements COMMIT and COMMIT WORK are equivalent. Examples Committing an Insert INSERT INTO table_name VALUES (val1, val2); COMMIT WORK; ·         COMMENT Comment is also optional. This clause is supported for backward compatibility. Oracle recommends that you used named transactions instead of commit comments. Specify a comment to be associated with the current transaction. The 'text' is a quoted literal of up to 255 bytes that Oracle Database stores in the data dictionary view DBA_2PC_PENDING along with the transaction ID if a distributed transaction becomes in doubt. This comment can help you diagnose the failure of a distributed transaction. Examples The following statement commits the current transaction and associates a comment with it: COMMIT     COMMENT 'In-doubt transaction Code 36, Call (415) 555-2637'; ·         WRITE Clause Use this clause to specify the priority with which the redo information generated by the commit operation is written to the redo log. This clause can improve performance by reducing latency, thus eliminating the wait for an I/O to the redo log. Use this clause to improve response time in environments with stringent response time requirements where the following conditions apply: The volume of update transactions is large, requiring that the redo log be written to disk frequently. The application can tolerate the loss of an asynchronously committed transaction. The latency contributed by waiting for the redo log write to occur contributes significantly to overall response time. You can specify the WAIT | NOWAIT and IMMEDIATE | BATCH clauses in any order. Examples To commit the same insert operation and instruct the database to buffer the change to the redo log, without initiating disk I/O, use the following COMMIT statement: COMMIT WRITE BATCH; Note: If you omit this clause, then the behavior of the commit operation is controlled by the COMMIT_WRITE initialization parameter, if it has been set. The default value of the parameter is the same as the default for this clause. Therefore, if the parameter has not been set and you omit this clause, then commit records are written to disk before control is returned to the user. WAIT | NOWAIT Use these clauses to specify when control returns to the user. The WAIT parameter ensures that the commit will return only after the corresponding redo is persistent in the online redo log. Whether in BATCH or IMMEDIATE mode, when the client receives a successful return from this COMMIT statement, the transaction has been committed to durable media. A crash occurring after a successful write to the log can prevent the success message from returning to the client. In this case the client cannot tell whether or not the transaction committed. The NOWAIT parameter causes the commit to return to the client whether or not the write to the redo log has completed. This behavior can increase transaction throughput. With the WAIT parameter, if the commit message is received, then you can be sure that no data has been lost. Caution: With NOWAIT, a crash occurring after the commit message is received, but before the redo log record(s) are written, can falsely indicate to a transaction that its changes are persistent. If you omit this clause, then the transaction commits with the WAIT behavior. IMMEDIATE | BATCH Use these clauses to specify when the redo is written to the log. The IMMEDIATE parameter causes the log writer process (LGWR) to write the transaction's redo information to the log. This operation option forces a disk I/O, so it can reduce transaction throughput. The BATCH parameter causes the redo to be buffered to the redo log, along with other concurrently executing transactions. When sufficient redo information is collected, a disk write of the redo log is initiated. This behavior is called "group commit", as redo for multiple transactions is written to the log in a single I/O operation. If you omit this clause, then the transaction commits with the IMMEDIATE behavior. ·         FORCE Clause Use this clause to manually commit an in-doubt distributed transaction or a corrupt transaction. ·         In a distributed database system, the FORCE string [, integer] clause lets you manually commit an in-doubt distributed transaction. The transaction is identified by the 'string' containing its local or global transaction ID. To find the IDs of such transactions, query the data dictionary view DBA_2PC_PENDING. You can use integer to specifically assign the transaction a system change number (SCN). If you omit integer, then the transaction is committed using the current SCN. ·         The FORCE CORRUPT_XID 'string' clause lets you manually commit a single corrupt transaction, where string is the ID of the corrupt transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to specify this clause. ·         Specify FORCE CORRUPT_XID_ALL to manually commit all corrupt transactions. You must have DBA privileges to specify this clause. Examples Forcing an in doubt transaction. Example The following statement manually commits a hypothetical in-doubt distributed transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to issue this statement. COMMIT FORCE '22.57.53';

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  • Why are the custom campaign parameters in Google Analytics so long?

    - by Baumr
    Adding several Google Analytics custom campaign parameters can make URLs very long. For example, in Google's own examples: http://www.example.com/?utm_campaign=spring&utm_medium=referral&utm_source=exampleblog http://www.example.com/?utm_campaign=spring&utm_medium=email&utm_source=newsletter1 http://www.example.com/?utm_campaign=spring&utm_medium=email&utm_source=newsletter1&utm_content=toplink Is there shorter alternatives that GA will pick up?

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  • ADF vs. EJB/Spring: Where should I invest my time?

    - by Arthur Huxley
    I am a junior Java SE developer, planning to become a Java Standard Edition professional. Which technologies/frameworks will be the smartest thing for me to learn? I will invest a lot of time and energy on the technologies that I eventually choose and it will be the basis for my carreer. I need to choose carefully. I have one question in particular regarding Oracle ADF: How can it be better than Spring or EJB 3.x? No offense to the ADF developers - and please excuse my ignorance - but is there a reason for using ADF other than locking customers to Oracle products? If ADF is an inferior technology I fear I will be making a mistake choosing to specialize in ADF.

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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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  • How can you connect to a password protected MS Access Database from a Spring JdbcTemplate?

    - by Tim Visher
    I need to connect to a password protected MS Access 2003 DB using the JDBC-ODBC bridge. I can't find out how to specify the password in the connect string, or even if that is the correct method of connecting. It would probably be relevant to mention that this is a Spring App which is accessing the database through a JdbcTemplate configured as a datasource bean in our application context file. Some relevant snippets: from application-context.xml <bean id="jdbcTemplate" class="org.springframework.jdbc.core.JdbcTemplate"> <property name="dataSource" ref="legacyDataSource" /> </bean> <bean id="jobsheetLocation" class="java.lang.String"> <constructor-arg value="${jobsheet.location}"/> </bean> <bean id="legacyDataSource" class="org.springframework.jdbc.datasource.DriverManagerDataSource"> <property name="driverClassName" value="${jdbc.legacy.driverClassName}" /> <property name="url" value="${jdbc.legacy.url}"/> <property name="password" value="-------------" /> </bean> from our build properties jdbc.legacy.driverClassName=sun.jdbc.odbc.JdbcOdbcDriver jdbc.legacy.url=jdbc:odbc:Driver\={Microsoft Access Driver (*.mdb)};Dbq\=@LegacyDbPath@;DriverID\=22;READONLY\=true Any thoughts?

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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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