Search Results

Search found 3874 results on 155 pages for 'nested transactions'.

Page 67/155 | < Previous Page | 63 64 65 66 67 68 69 70 71 72 73 74  | Next Page >

  • spring security : Failed to load ApplicationContext with pre-post-annotations="enabled"

    - by thogau
    I am using spring 3.0.1 + spring-security 3.0.2 and I am trying to use features like @PreAuthorize and @PostFilter annotations. When running in units tests using @RunWith(SpringJUnit4ClassRunner.class) or in a main(String[] args) method my application context fails to start if enable pre-post-annotations and use org.springframework.security.acls.AclPermissionEvaluator : <!-- Enable method level security--> <security:global-method-security pre-post-annotations="enabled"> <security:expression-handler ref="expressionHandler"/> </security:global-method-security> <bean id="expressionHandler" class="org.springframework.security.access.expression.method.DefaultMethodSecurityExpressionHandler"> <property name="permissionEvaluator" ref="aclPermissionEvaluator"/> </bean> <bean id="aclPermissionEvaluator" class="org.springframework.security.acls.AclPermissionEvaluator"> <constructor-arg ref="aclService"/> </bean> <!-- Enable stereotype support --> <context:annotation-config /> <context:component-scan base-package="com.rreps.core" /> <bean id="propertyConfigurer" class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer"> <property name="locations"> <list> <value>classpath:applicationContext.properties</value> </list> </property> </bean> <bean id="dataSource" class="com.mchange.v2.c3p0.ComboPooledDataSource"> <property name="driverClass" value="${jdbc.driver}" /> <property name="jdbcUrl" value="${jdbc.url}" /> <property name="user" value="${jdbc.username}" /> <property name="password" value="${jdbc.password}" /> <property name="initialPoolSize" value="10" /> <property name="minPoolSize" value="5" /> <property name="maxPoolSize" value="25" /> <property name="acquireRetryAttempts" value="10" /> <property name="acquireIncrement" value="5" /> <property name="idleConnectionTestPeriod" value="3600" /> <property name="maxIdleTime" value="10800" /> <property name="maxConnectionAge" value="14400" /> <property name="preferredTestQuery" value="SELECT 1;" /> <property name="testConnectionOnCheckin" value="false" /> </bean> <bean id="auditedSessionFactory" class="org.springframework.orm.hibernate3.annotation.AnnotationSessionFactoryBean"> <property name="dataSource" ref="dataSource" /> <property name="configLocation" value="classpath:hibernate.cfg.xml" /> <property name="hibernateProperties"> <value> hibernate.dialect=${hibernate.dialect} hibernate.query.substitutions=true 'Y', false 'N' hibernate.cache.use_second_level_cache=true hibernate.cache.provider_class=net.sf.ehcache.hibernate.SingletonEhCacheProvider hibernate.hbm2ddl.auto=update hibernate.c3p0.acquire_increment=5 hibernate.c3p0.idle_test_period=3600 hibernate.c3p0.timeout=10800 hibernate.c3p0.max_size=25 hibernate.c3p0.min_size=1 hibernate.show_sql=false hibernate.validator.autoregister_listeners=false </value> </property> <!-- validation is performed by "hand" (see http://opensource.atlassian.com/projects/hibernate/browse/HV-281) <property name="eventListeners"> <map> <entry key="pre-insert" value-ref="beanValidationEventListener" /> <entry key="pre-update" value-ref="beanValidationEventListener" /> </map> </property> --> <property name="entityInterceptor"> <bean class="com.rreps.core.dao.hibernate.interceptor.TrackingInterceptor" /> </property> </bean> <bean id="simpleSessionFactory" class="org.springframework.orm.hibernate3.annotation.AnnotationSessionFactoryBean"> <property name="dataSource" ref="dataSource" /> <property name="configLocation" value="classpath:hibernate.cfg.xml" /> <property name="hibernateProperties"> <value> hibernate.dialect=${hibernate.dialect} hibernate.query.substitutions=true 'Y', false 'N' hibernate.cache.use_second_level_cache=true hibernate.cache.provider_class=net.sf.ehcache.hibernate.SingletonEhCacheProvider hibernate.hbm2ddl.auto=update hibernate.c3p0.acquire_increment=5 hibernate.c3p0.idle_test_period=3600 hibernate.c3p0.timeout=10800 hibernate.c3p0.max_size=25 hibernate.c3p0.min_size=1 hibernate.show_sql=false hibernate.validator.autoregister_listeners=false </value> </property> <!-- property name="eventListeners"> <map> <entry key="pre-insert" value-ref="beanValidationEventListener" /> <entry key="pre-update" value-ref="beanValidationEventListener" /> </map> </property--> </bean> <bean id="sequenceSessionFactory" class="org.springframework.orm.hibernate3.annotation.AnnotationSessionFactoryBean"> <property name="dataSource" ref="dataSource" /> <property name="configLocation" value="classpath:hibernate.cfg.xml" /> <property name="hibernateProperties"> <value> hibernate.dialect=${hibernate.dialect} hibernate.query.substitutions=true 'Y', false 'N' hibernate.cache.use_second_level_cache=true hibernate.cache.provider_class=net.sf.ehcache.hibernate.SingletonEhCacheProvider hibernate.hbm2ddl.auto=update hibernate.c3p0.acquire_increment=5 hibernate.c3p0.idle_test_period=3600 hibernate.c3p0.timeout=10800 hibernate.c3p0.max_size=25 hibernate.c3p0.min_size=1 hibernate.show_sql=false hibernate.validator.autoregister_listeners=false </value> </property> </bean> <bean id="validationFactory" class="javax.validation.Validation" factory-method="buildDefaultValidatorFactory" /> <!-- bean id="beanValidationEventListener" class="org.hibernate.cfg.beanvalidation.BeanValidationEventListener"> <constructor-arg index="0" ref="validationFactory" /> <constructor-arg index="1"> <props/> </constructor-arg> </bean--> <!-- Enable @Transactional support --> <tx:annotation-driven transaction-manager="transactionManager"/> <bean id="transactionManager" class="org.springframework.orm.hibernate3.HibernateTransactionManager"> <property name="sessionFactory" ref="auditedSessionFactory" /> </bean> <security:authentication-manager alias="authenticationManager"> <security:authentication-provider user-service-ref="userDetailsService" /> </security:authentication-manager> <bean id="userDetailsService" class="com.rreps.core.service.impl.UserDetailsServiceImpl" /> <!-- ACL stuff --> <bean id="aclCache" class="org.springframework.security.acls.domain.EhCacheBasedAclCache"> <constructor-arg> <bean class="org.springframework.cache.ehcache.EhCacheFactoryBean"> <property name="cacheManager"> <bean class="org.springframework.cache.ehcache.EhCacheManagerFactoryBean"/> </property> <property name="cacheName" value="aclCache"/> </bean> </constructor-arg> </bean> <bean id="lookupStrategy" class="org.springframework.security.acls.jdbc.BasicLookupStrategy"> <constructor-arg ref="dataSource"/> <constructor-arg ref="aclCache"/> <constructor-arg> <bean class="org.springframework.security.acls.domain.AclAuthorizationStrategyImpl"> <constructor-arg> <list> <bean class="org.springframework.security.core.authority.GrantedAuthorityImpl"> <constructor-arg value="ROLE_ADMINISTRATEUR"/> </bean> <bean class="org.springframework.security.core.authority.GrantedAuthorityImpl"> <constructor-arg value="ROLE_ADMINISTRATEUR"/> </bean> <bean class="org.springframework.security.core.authority.GrantedAuthorityImpl"> <constructor-arg value="ROLE_ADMINISTRATEUR"/> </bean> </list> </constructor-arg> </bean> </constructor-arg> <constructor-arg> <bean class="org.springframework.security.acls.domain.ConsoleAuditLogger"/> </constructor-arg> </bean> <bean id="aclService" class="com.rreps.core.service.impl.MysqlJdbcMutableAclService"> <constructor-arg ref="dataSource"/> <constructor-arg ref="lookupStrategy"/> <constructor-arg ref="aclCache"/> </bean> The strange thing is that the context starts normally when deployed in a webapp and @PreAuthorize and @PostFilter annotations are working fine as well... Any idea what is wrong? Here is the end of the stacktrace : ... 55 more Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'dataSource' defined in class path resource [applicationContext-core.xml]: Initialization of bean failed; nested exception is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.transaction.config.internalTransactionAdvisor': Cannot resolve reference to bean 'org.springframework.transaction.annotation.AnnotationTransactionAttributeSource#0' while setting bean property 'transactionAttributeSource'; nested exception is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.transaction.annotation.AnnotationTransactionAttributeSource#0': Initialization of bean failed; nested exception is java.lang.NullPointerException at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:521) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:450) at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:290) at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:222) at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:287) at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:189) at org.springframework.beans.factory.support.BeanDefinitionValueResolver.resolveReference(BeanDefinitionValueResolver.java:322) ... 67 more Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.transaction.config.internalTransactionAdvisor': Cannot resolve reference to bean 'org.springframework.transaction.annotation.AnnotationTransactionAttributeSource#0' while setting bean property 'transactionAttributeSource'; nested exception is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.transaction.annotation.AnnotationTransactionAttributeSource#0': Initialization of bean failed; nested exception is java.lang.NullPointerException at org.springframework.beans.factory.support.BeanDefinitionValueResolver.resolveReference(BeanDefinitionValueResolver.java:328) at org.springframework.beans.factory.support.BeanDefinitionValueResolver.resolveValueIfNecessary(BeanDefinitionValueResolver.java:106) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyPropertyValues(AbstractAutowireCapableBeanFactory.java:1308) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1067) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:511) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:450) at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:290) at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:222) at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:287) at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:193) at org.springframework.aop.framework.autoproxy.BeanFactoryAdvisorRetrievalHelper.findAdvisorBeans(BeanFactoryAdvisorRetrievalHelper.java:86) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.findCandidateAdvisors(AbstractAdvisorAutoProxyCreator.java:100) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.findEligibleAdvisors(AbstractAdvisorAutoProxyCreator.java:86) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.getAdvicesAndAdvisorsForBean(AbstractAdvisorAutoProxyCreator.java:68) at org.springframework.aop.framework.autoproxy.AbstractAutoProxyCreator.wrapIfNecessary(AbstractAutoProxyCreator.java:359) at org.springframework.aop.framework.autoproxy.AbstractAutoProxyCreator.postProcessAfterInitialization(AbstractAutoProxyCreator.java:322) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyBeanPostProcessorsAfterInitialization(AbstractAutowireCapableBeanFactory.java:404) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1409) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:513) ... 73 more Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.transaction.annotation.AnnotationTransactionAttributeSource#0': Initialization of bean failed; nested exception is java.lang.NullPointerException at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:521) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:450) at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:290) at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:222) at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:287) at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:189) at org.springframework.beans.factory.support.BeanDefinitionValueResolver.resolveReference(BeanDefinitionValueResolver.java:322) ... 91 more Caused by: java.lang.NullPointerException at org.springframework.security.access.method.DelegatingMethodSecurityMetadataSource.getAttributes(DelegatingMethodSecurityMetadataSource.java:52) at org.springframework.security.access.intercept.aopalliance.MethodSecurityMetadataSourceAdvisor$MethodSecurityMetadataSourcePointcut.matches(MethodSecurityMetadataSourceAdvisor.java:129) at org.springframework.aop.support.AopUtils.canApply(AopUtils.java:215) at org.springframework.aop.support.AopUtils.canApply(AopUtils.java:252) at org.springframework.aop.support.AopUtils.findAdvisorsThatCanApply(AopUtils.java:284) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.findAdvisorsThatCanApply(AbstractAdvisorAutoProxyCreator.java:117) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.findEligibleAdvisors(AbstractAdvisorAutoProxyCreator.java:87) at org.springframework.aop.framework.autoproxy.AbstractAdvisorAutoProxyCreator.getAdvicesAndAdvisorsForBean(AbstractAdvisorAutoProxyCreator.java:68) at org.springframework.aop.framework.autoproxy.AbstractAutoProxyCreator.wrapIfNecessary(AbstractAutoProxyCreator.java:359) at org.springframework.aop.framework.autoproxy.AbstractAutoProxyCreator.postProcessAfterInitialization(AbstractAutoProxyCreator.java:322) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyBeanPostProcessorsAfterInitialization(AbstractAutowireCapableBeanFactory.java:404) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1409) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:513) ... 97 more

    Read the article

  • JMX Based Monitoring - Part Four - Business App Server Monitoring

    - by Anthony Shorten
    In the last blog entry I talked about the Oracle Utilities Application Framework V4 feature for monitoring and managing aspects of the Web Application Server using JMX. In this blog entry I am going to discuss a similar new feature that allows JMX to be used for management and monitoring the Oracle Utilities business application server component. This feature is primarily focussed on performance tracking of the product. In first release of Oracle Utilities Customer Care And Billing (V1.x I am talking about), we used to use Oracle Tuxedo as part of the architecture. In Oracle Utilities Application Framework V2.0 and above, we removed Tuxedo from the architecture. One of the features that some customers used within Tuxedo was the performance tracking ability. The idea was that you enabled performance logging on the individual Tuxedo servers and then used a utility named txrpt to produce a performance report. This report would list every service called, the number of times it was called and the average response time. When I worked a performance consultant, I used this report to identify badly performing services and also gauge the overall performance characteristics of a site. When Tuxedo was removed from the architecture this information was also lost. While you can get some information from access.log and some Mbeans supplied by the Web Application Server it was not at the same granularity as txrpt or as useful. I am happy to say we have not only reintroduced this facility in Oracle Utilities Application Framework but it is now accessible via JMX and also we have added more detail into the performance tracking. Most of this new design was working with customers around the world to make sure we introduced a new feature that not only satisfied their performance tracking needs but allowed for finer grained performance analysis. As with the Web Application Server, the Business Application Server JMX monitoring is enabled by specifying a JMX port number in RMI Port number for JMX Business and initial credentials in the JMX Enablement System User ID and JMX Enablement System Password configuration options. These options are available using the configureEnv[.sh] -a utility. These credentials are shared across the Web Application Server and Business Application Server for authorization purposes. Once this is information is supplied a number of configuration files are built (by the initialSetup[.sh] utility) to configure the facility: spl.properties - contains the JMX URL, the security configuration and the mbeans that are enabled. For example, on my demonstration machine: spl.runtime.management.rmi.port=6750 spl.runtime.management.connector.url.default=service:jmx:rmi:///jndi/rmi://localhost:6750/oracle/ouaf/ejbAppConnector jmx.remote.x.password.file=scripts/ouaf.jmx.password.file jmx.remote.x.access.file=scripts/ouaf.jmx.access.file ouaf.jmx.com.splwg.ejb.service.management.PerformanceStatistics=enabled ouaf.jmx.* files - contain the userid and password. The default configuration uses the JMX default configuration. You can use additional security features by altering the spl.properties file manually or using a custom template. For more security options see JMX Security for more details. Once it has been configured and the changes reflected in the product using the initialSetup[.sh] utility the JMX facility can be used. For illustrative purposes I will use jconsole but any JSR160 complaint browser or client can be used (with the appropriate configuration). Once you start jconsole (ensure that splenviron[.sh] is executed prior to execution to set the environment variables or for remote connection, ensure java is in your path and jconsole.jar in your classpath) you specify the URL in the spl.runtime.management.connnector.url.default entry. For example: You are then able to track performance of the product using the PerformanceStatistics Mbean. The attributes of the PerformanceStatistics Mbean are counts of each object type. This is where this facility differs from txrpt. The information that is collected includes the following: The Service Type is captured so you can filter the results in terms of the type of service. For maintenance type services you can even see the transaction type (ADD, CHANGE etc) so you can see the performance of updates against read transactions. The Minimum and Maximum are also collected to give you an idea of the spread of performance. The last call is recorded. The date, time and user of the last call are recorded to give you an idea of the timeliness of the data. The Mbean maintains a set of counters per Service Type to give you a summary of the types of transactions being executed. This gives you an overall picture of the types of transactions and volumes at your site. There are a number of interesting operations that can also be performed: reset - This resets the statistics back to zero. This is an important operation. For example, txrpt is restricted to collecting statistics per hour, which is ok for most people. But what if you wanted to be more granular? This operation allows to set the collection period to anything you wish. The statistics collected will represent values since the last restart or last reset. completeExecutionDump - This is the operation that produces a CSV in memory to allow extraction of the data. All the statistics are extracted (see the Server Administration Guide for a full list). This can be then loaded into a database, a tool or simply into your favourite spreadsheet for analysis. Here is an extract of an execution dump from my demonstration environment to give you an idea of the format: ServiceName, ServiceType, MinTime, MaxTime, Avg Time, # of Calls, Latest Time, Latest Date, Latest User ... CFLZLOUL, EXECUTE_LIST, 15.0, 64.0, 22.2, 10, 16.0, 2009-12-16::11-25-36-932, ASHORTEN CILBBLLP, READ, 106.0, 1184.0, 466.3333333333333, 6, 106.0, 2009-12-16::11-39-01-645, BOBAMA CILBBLLP, DELETE, 70.0, 146.0, 108.0, 2, 70.0, 2009-12-15::12-53-58-280, BPAYS CILBBLLP, ADD, 860.0, 4903.0, 2243.5, 8, 860.0, 2009-12-16::17-54-23-862, LELLISON CILBBLLP, CHANGE, 112.0, 3410.0, 815.1666666666666, 12, 112.0, 2009-12-16::11-40-01-103, ASHORTEN CILBCBAL, EXECUTE_LIST, 8.0, 84.0, 26.0, 22, 23.0, 2009-12-16::17-54-01-643, LJACKMAN InitializeUserInfoService, READ_SYSTEM, 49.0, 962.0, 70.83777777777777, 450, 63.0, 2010-02-25::11-21-21-667, ASHORTEN InitializeUserService, READ_SYSTEM, 130.0, 2835.0, 234.85777777777778, 450, 216.0, 2010-02-25::11-21-21-446, ASHORTEN MenuLoginService, READ_SYSTEM, 530.0, 1186.0, 703.3333333333334, 9, 530.0, 2009-12-16::16-39-31-172, ASHORTEN NavigationOptionDescriptionService, READ_SYSTEM, 2.0, 7.0, 4.0, 8, 2.0, 2009-12-21::09-46-46-892, ASHORTEN ... There are other operations and attributes available. Refer to the Server Administration Guide provided with your product to understand the full et of operations and attributes. This is one of the many features I am proud that we implemented as it allows flexible monitoring of the performance of the product.

    Read the article

  • Four Emerging Payment Stories

    - by David Dorf
    The world of alternate payments has been moving fast of late.  Innovation in this area will help both consumers and retailers, but probably hurt the banks (at least that's the plan).  Here are four recent news items in this area: Dwolla, a start-up in Iowa, is trying to make credit cards obsolete.  Twelve guys in Des Moines are using $1.3M they raised to allow businesses to skip the credit card networks and avoid the fees.  Today they move about $1M a day across their network with an average transaction size of $500. Instead of charging merchants 2.9% plus $.30 per transaction, Dwolla charges a quarter -- yep, that coin featuring George Washington. Dwolla (Web + Dollar = Dwolla) avoids the credit networks and connects directly to bank accounts using the bank's ACH network.  They are signing up banks and merchants targeting both B2B and C2B as well as P2P payments.  They leverage social networks to notify people they have a money transfer, and also have a mobile app that uses GPS location. However, all is not rosy.  There have been complaints about unexpected chargebacks and with debit fees being reduced by the big banks, the need is not as pronounced.  The big banks are working on their own network called clearXchange that could provide stiff competition. VeriFone just bought European payment processor Point for around $1B.  By itself this would not have caught my attention except for the fact that VeriFone also announced the acquisition of GlobalBay earlier this month.  In addition to their core business of selling stand-beside payment terminals, with GlobalBay they get employee-operated mobile selling tools and with Point they get a very big payment processing platform. MasterCard and Intel announced a partnership around payments, starting with PayPass, MasterCard's new payment technology.  Intel will lend its expertise to add additional levels of security, which seems to be the biggest barrier for consumer adoption.  Everyone is scrambling to get their piece of cash transactions, which still represents 85% of all transactions. Apple was awarded another mobile payment patent further cementing the rumors that the iPhone 5 will support NFC payments.  As usual, Apple is upsetting the apple cart (sorry) by moving control of key data from the carriers to Apple.  With Apple's vast number of iTunes accounts, they have a ready-made customer base to use the payment infrastructure, which I bet will slowly transition people away from credit cards and toward cheaper ACH.  Gary Schwartz explains the three step process Apple is taking to become a payment processor. Below is a picture I drew representing payments in the retail industry. There's certainly a lot of innovation happening.

    Read the article

  • Need to Know

    - by Tony Davis
    Sometimes, I wonder whether writers of documentation, tutorials and articles stop to ask themselves one very important question: Does the reader really need to know this? I recently took on the task of writing a concise series of articles about the transaction log, what is it, how it works and why it's important. It was an enjoyable task; rather like peering inside a giant, complex clock mechanism. Initially, one sees only the basic components, which work to guarantee the integrity of database transactions, and preserve these transactions so that data can be restored to a previous point in time. On closer inspection, one notices all of small, arcane mechanisms that are necessary to make this happen; LSNs, virtual log files, log chains, database checkpoints, and so on. It was engrossing, escapist, stuff; what I'd written looked weighty and steeped in mysterious significance. Suddenly, however, I jolted myself back to reality with the awful thought "does anyone really need to know all this?" The driver of a car needs only to be dimly aware of what goes on under the hood, however exciting the mechanism is to the engineer. Similarly, while everyone who uses SQL Server ought to be aware of the transaction log, its role in guaranteeing the ACID properties, and how to control its growth, the intricate mechanisms ticking away under its clock face are a world away from the daily work of the harassed developer. The DBA needs to know more, such as the correct rituals for ensuring optimal performance and data integrity, setting the appropriate growth characteristics, backup routines, restore procedures, and so on. However, even then, the average DBA only needs to understand enough about the arcane processes to spot problems and react appropriately, or to know how to Google for the best way of dealing with it. The art of technical writing is tied up in intimate knowledge of your audience and what they need to know at any point. It means serving up just enough at each point to help the reader in a practical way, but not to overcook it, or stuff the reader with information that does them no good. When I think of the books and articles that have helped me the most, they have been full of brief, practical, and well-informed guidance, based on experience. This seems far-removed from the 900-page "beginner's guides" that one now sees everywhere. The more I write and edit, the more I become convinced that the real art of technical communication lies in knowing what to leave out. In what areas do the SQL Server technical materials suffer from "information overload"? Where else does it seem that concise, practical advice is drowned out by endless discussion of the "clock mechanisms"? Cheers, Tony.

    Read the article

  • MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

    - by Pinal Dave
    Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

    Read the article

  • An Introduction to Cash Till

    Cash till is a machine that can tabulate the amount of sales transactions and usually prints receipt for the customers. It can also make a permanent and cumulative record of the day’s sales. Al... [Author: Alan Wisdom - Computers and Internet - April 05, 2010]

    Read the article

  • SQL SERVER Find Largest Supported DML Operation Question to You

    SQL Server is very big and it is not possible to know everything in SQL Server but we all keep learning. Recently I was going over the best practices of transactions log and I come across following statement. The log size must be at least twice the size of largest supported DML operation (using uncompressed [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

    Read the article

  • Don’t miss the Receiving Webcast on November 20th

    - by user793553
    This one-hour session is recommended for technical and functional users who are interested to know about the Receiving transactions and its debugging techniques. TOPICS WILL INCLUDE: Using generic diagnostic scripts. How to read debug logs in receiving. Data flow for various document types (PO, RMA, ISO, IOT) to help debug issues Receiving Transaction processor Generic datafixes.  See DocID 1456150.1 to sign up now!

    Read the article

  • Minimal set of critical database operations

    - by Juan Carlos Coto
    In designing the data layer code for an application, I'm trying to determine if there is a minimal set of database operations (both single and combined) that are essential for proper application function (i.e. the database is left in an expected state after every data access call). Is there a way to determine the minimal set of database operations (functions, transactions, etc.) that are critical for an application to function correctly? How do I find it? Thanks very much!

    Read the article

  • Don’t Miss The Top Exastack ISV Headlines – Week Of May 26

    - by Roxana Babiciu
    Calypso Technology announced that Calypso version 14 has achieved Oracle Exadata Optimized status through OPN. In simulations of data-intensive straight through-processing tasks, Calypso achieved performance gains of up to 500% using Exadata hardware – Read more Infosys achieves Oracle SuperCluster Optimized status with Finacle, a core banking solution. Finacle can process 6x the volume of transactions currently processed by the entire US banking system – Read more

    Read the article

  • Incremental Statistics Maintenance – what statistics will be gathered after DML occurs on the table?

    - by Maria Colgan
    Incremental statistics maintenance was introduced in Oracle Database 11g to improve the performance of gathering statistics on large partitioned table. When incremental statistics maintenance is enabled for a partitioned table, oracle accurately generated global level  statistics by aggregating partition level statistics. As more people begin to adopt this functionality we have gotten more questions around how they expected incremental statistics to behave in a given scenario. For example, last week we got a question around what partitions should have statistics gathered on them after DML has occurred on the table? The person who asked the question assumed that statistics would only be gathered on partitions that had stale statistics (10% of the rows in the partition had changed). However, what they actually saw when they did a DBMS_STATS.GATHER_TABLE_STATS was all of the partitions that had been affected by the DML had statistics re-gathered on them. This is the expected behavior, incremental statistics maintenance is suppose to yield the same statistics as gathering table statistics from scratch, just faster. This means incremental statistics maintenance needs to gather statistics on any partition that will change the global or table level statistics. For instance, the min or max value for a column could change after just one row is inserted or updated in the table. It might easier to demonstrate this using an example. Let’s take the ORDERS2 table, which is partitioned by month on order_date.  We will begin by enabling incremental statistics for the table and gathering statistics on the table. After the statistics gather the last_analyzed date for the table and all of the partitions now show 13-Mar-12. And we now have the following column statistics for the ORDERS2 table. We can also confirm that we really did use incremental statistics by querying the dictionary table sys.HIST_HEAD$, which should have an entry for each column in the ORDERS2 table. So, now that we have established a good baseline, let’s move on to the DML. Information is loaded into the latest partition of the ORDERS2 table once a month. Existing orders maybe also be update to reflect changes in their status. Let’s assume the following transactions take place on the ORDERS2 table this month. After these transactions have occurred we need to re-gather statistic since the partition ORDERS_MAR_2012 now has rows in it and the number of distinct values and the maximum value for the STATUS column have also changed. Now if we look at the last_analyzed date for the table and the partitions, we will see that the global statistics and the statistics on the partitions where rows have changed due to the update (ORDERS_FEB_2012) and the data load (ORDERS_MAR_2012) have been updated. The column statistics also reflect the changes with the number of distinct values in the status column increase to reflect the update. So, incremental statistics maintenance will gather statistics on any partition, whose data has changed and that change will impact the global level statistics.

    Read the article

  • SQL SERVER – Move Database Files MDF and LDF to Another Location

    - by pinaldave
    When a novice DBA or Developer create a database they use SQL Server Management Studio to create new database. Additionally, the T-SQL script to create a database is very easy as well. You can just write CREATE DATABASE DatabaseName and it will create new database for you. The point to remember here is that it will create the database at the default location specified for SQL Server Instance (this default instance can be changed and we will see that in future blog posts). Now, once the database goes in production it will start to grow. It is not common to keep the Database on the same location where OS is installed. Usually Database files are on SAN, Separate Disk Array or on SSDs. This is done usually for performance reason and manageability perspective. Now the challenges comes up when database which was installed at not preferred default location and needs to move to a different location. Here is the quick tutorial how you can do it. Let us assume we have two folders loc1 and loc2. We want to move database files from loc1 to loc2. USE MASTER; GO -- Take database in single user mode -- if you are facing errors -- This may terminate your active transactions for database ALTER DATABASE TestDB SET SINGLE_USER WITH ROLLBACK IMMEDIATE; GO -- Detach DB EXEC MASTER.dbo.sp_detach_db @dbname = N'TestDB' GO Now move the files from loc1 to loc2. You can now reattach the files with new locations. -- Move MDF File from Loc1 to Loc 2 -- Re-Attached DB CREATE DATABASE [TestDB] ON ( FILENAME = N'F:\loc2\TestDB.mdf' ), ( FILENAME = N'F:\loc2\TestDB_log.ldf' ) FOR ATTACH GO Well, we are done. There is little warning here for you: If you do ROLLBACK IMMEDIATE you may terminate your active transactions so do not use it randomly. Do it if you are confident that they are not needed or due to any reason there is a connection to the database which you are not able to kill manually after review. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

    Read the article

  • How to archive data from a table to a local or remote database in SQL 2005 and SQL 2008

    - by simonsabin
    Often you have the need to archive data from a table. This leads to a number of challenges 1. How can you do it without impacting users 2. How can I make it transactionally consistent, i.e. the data I put in the archive is the data I remove from the main table 3. How can I get it to perform well Points 1 is very much tied to point 3. If it doesn't perform well then the delete of data is going to cause lots of locks and thus potentially blocking. For points 1 and 3 refer to my previous posts DELETE-TOP-x-rows-avoiding-a-table-scan and UPDATE-and-DELETE-TOP-and-ORDER-BY---Part2. In essence you need to be removing small chunks of data from your table and you want to do that avoiding a table scan. So that deals with the delete approach but archiving is about inserting that data somewhere else. Well in SQL 2008 they introduced a new feature INSERT over DML (Data Manipulation Language, i.e. SQL statements that change data), or composable DML. The ability to nest DML statements within themselves, so you can past the results of an insert to an update to a merge. I've mentioned this before here SQL-Server-2008---MERGE-and-optimistic-concurrency. This feature is currently limited to being able to consume the results of a DML statement in an INSERT statement. There are many restrictions which you can find here http://msdn.microsoft.com/en-us/library/ms177564.aspx look for the section "Inserting Data Returned From an OUTPUT Clause Into a Table" Even with the restrictions what we can do is consume the OUTPUT from a DELETE and INSERT the results into a table in another database. Note that in BOL it refers to not being able to use a remote table, remote means a table on another SQL instance. To show this working use this SQL to setup two databases foo and fooArchive create database foo go --create the source table fred in database foo select * into foo..fred from sys.objects go create database fooArchive go if object_id('fredarchive',DB_ID('fooArchive')) is null begin     select getdate() ArchiveDate,* into fooArchive..FredArchive from sys.objects where 1=2       end go And then we can use this simple statement to archive the data insert into fooArchive..FredArchive select getdate(),d.* from (delete top (1)         from foo..Fred         output deleted.*) d         go In this statement the delete can be any delete statement you wish so if you are deleting by ids or a range of values then you can do that. Refer to the DELETE-TOP-x-rows-avoiding-a-table-scan post to ensure that your delete is going to perform. The last thing you want to do is to perform 100 deletes each with 5000 records for each of those deletes to do a table scan. For a solution that works for SQL2005 or if you want to archive to a different server then you can use linked servers or SSIS. This example shows how to do it with linked servers. [ONARC-LAP03] is the source server. begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d commit transaction and to prove the transactions work try, you should get the same number of records before and after. select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d rollback transaction   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive The transactions are very important with this solution. Look what happens when you don't have transactions and an error occurs   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*                     raiserror (''Oh doo doo'',15,15)') d                     select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive Before running this think what the result would be. I got it wrong. What seems to happen is that the remote query is executed as a transaction, the error causes that to rollback. However the results have already been sent to the client and so get inserted into the

    Read the article

  • Web Based CRM For Banks.

    Banks have to make several transactions in a day; buyers have to give their email, phone numbers, address, names, social security number and credit card information. Huge amount of information is pro... [Author: James Wong - Computers and Internet - March 29, 2010]

    Read the article

  • SQL SERVER – Rollback TRUNCATE Command in Transaction

    - by pinaldave
    This is very common concept that truncate can not be rolled back. I always hear conversation between developer if truncate can be rolled back or not. If you use TRANSACTIONS in your code, TRUNCATE can be rolled back. If there is no transaction is used and TRUNCATE operation is committed, it can not be retrieved from [...]

    Read the article

  • Framework 4 Features: User Propogation to the Database

    - by Anthony Shorten
    Once of the features I mentioned in a previous entry was the ability for Oracle Utilities Application Framework V4 to automatically propogate the end user to the database connection. This bears more explanation. In the past releases of the Oracle Utilities Application Framework, all database connections are pooled and shared within a channel of access. So for example, the online connections on the Business Application Server share a common pool of connections and the batch in a thread pool shares a seperate pool of connections. The connections are pooled for performance reasons (the most expensive part of a typical transaction is opening and closing connections so we save time by having them ready beforehand). The idea is that when a business function needs some SQL to be execute it takes a spare connection from the pool, executes the SQL and then returns the connection back to the pool for reuse. Unfortunelty to support the pool being started and ready before the transactions arrives means that you need to have a shared userid (as you dont know the users who need them beforehand). Therefore each connection uses the same database user to execute the SQL it needs. This is acceptable for executing transactions, generally but does not allow the DBA or other tools to ascertain which end user is actually running the transaction. In Oracle Utilities Application Framework V4, we now set the CLIENT_IDENTIFIER to the end userid (not the Login Id) when the connection is taken from the pool and used and reset it back to blank when returned to the pool. The CLIENT_IDENTIFIER is a feature that is present in the Oracle Database connection information. From a monitoring perspective, when a connection to the database is actively running SQL, the end user is now able to be determined by querying the CLIENT_IDENTIFIER on the session object within the database. This can be done in the DBA's favorite monitoring tool (even just some SQL on the v$session table is enough). This has other implications as well. Oracle sells a lot of other security addons to the database and so do third parties. If a site wants to have additional levels of security or auditing in the database then the CLIENT_IDENTIFIER, if supported, is now available to be recorded or used by those products to provide additional levels of security. This facility was one of the highly "nice to haves" that customers would ask us about so we now allow it to be used to allow finer grained monitoring and additional security facilities. Note: This facility is only available for customers using the Oracle Database versions of our products.

    Read the article

  • Network Security Risk Assessment

    - by Chandra Vennapoosa
    Information that is gathered everyday regarding client and business transactions are either stored on servers or on user computers. These stored information are considered important and sensitive in the company's interest and hence they need to be protected from network attacks and other unknown circumstances. Network administrator manage and protect the network through a series of passwords and data encryption. Topics First Step for Risk Assessment Identifying Essential Data/System/Hardware Identifying External Blocks Measuring the Risk to Your Enterprise Calculating the Assets Value The Liquid Financial Assets Value Getting Everything Together

    Read the article

  • World Record Oracle E-Business Consolidated Workload on SPARC T4-2

    - by Brian
    Oracle set a World Record for the Oracle E-Business Suite Standard Medium multiple-online module benchmark using Oracle's SPARC T4-2 and SPARC T4-4 servers which ran the application and database. Oracle's SPARC T4 servers demonstrate performance leadership and world-record results on Oracle E-Business Suite Applications R12 OLTP benchmark by publishing the first result using multiple concurrent online application modules with Oracle Database 11g Release 2 running Solaris.   This results shows that a multi-tier configuration of SPARC T4 servers running the Oracle E-Business Suite R12.1.2 application and Oracle Database 11g Release 2 is capable of supporting 4,100 online users with outstanding response-times, executing a mix of complex transactions consolidating 4 Oracle E-Business modules (iProcurement, Order Management, Customer Service and HR Self-Service).   The SPARC T4-2 server in the application tier utilized about 65% and the SPARC T4-4 server in the database tier utilized about 30%, providing significant headroom for additional Oracle E-Business Suite R12.1.2 processing modules, more online users, and future growth.   Oracle E-Business Suite Applications were run in Oracle Solaris Containers on SPARC T4 servers and provides a consolidation platform for multiple E-Business instances.   Performance Landscape Multiple Online Modules (Self-Service, Order-Management, iProcurement, Customer-Service) Medium Configuration System Users AverageResponse Time 90th PercentileResponse Time SPARC T4-2 4,100 2.08 sec 2.52 sec Configuration Summary Application Tier Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 3 x 300 GB internal disks Oracle Solaris 10 Oracle E-Business Suite 12.1.2 Database Tier Configuration: 1 x SPARC T4-4 server 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 2 x 300 GB internal disks Oracle Solaris 10 Oracle Solaris Containers Oracle Database 11g Release 2 Storage Configuration: 1 x Sun Storage F5100 Flash Array (80 x 24 GB flash modules) Benchmark Description The Oracle R12 E-Business Suite Standard Benchmark combines online transaction execution by simulated users with multiple online concurrent modules to model a typical scenario for a global enterprise. The online component exercises the common UI flows which are most frequently used by a majority of our customers. This benchmark utilized four concurrent flows of OLTP transactions, for Order to Cash, iProcurement, Customer Service and HR Self-Service and measured the response times. The selected flows model simultaneous business activities inclusive of managing customers, services, products and employees. See Also Oracle R12 E-Business Suite Standard Benchmark Results Oracle R12 E-Business Suite Standard Benchmark Overview Oracle R12 E-Business Benchmark Description E-Business Suite Applications R2 (R12.1.2) Online Benchmark - Using Oracle Database 11g on Oracle's SPARC T4-2 and Oracle's SPARC T4-4 Servers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle E-Business Suite oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle E-Business Suite R12 medium multiple-online module benchmark, SPARC T4-2, SPARC T4, 2.85 GHz, 2 chips, 16 cores, 128 threads, 256 GB memory, SPARC T4-4, SPARC T4, 3.0 GHz, 4 chips, 32 cores, 256 threads, 256 GB memory, average response time 2.08 sec, 90th percentile response time 2.52 sec, Oracle Solaris 10, Oracle Solaris Containers, Oracle E-Business Suite 12.1.2, Oracle Database 11g Release 2, Results as of 9/30/2012.

    Read the article

  • SOA &amp; Application Grid Specialization step 2 of 6 &ndash; References &amp; Marketing Kits

    - by Jürgen Kress
    In our fist step to become SOA Specialized & Application Grid Specialized we highlighted our OMM to register your opportunities. We continue our path to specialization with our marketing offerings to create your reference cases and run joint marketing campaigns. References: Be Recognized Through Partner Success Stories Oracle delivers a wide variety of services and solutions through our partners and we believe that those successes should be recognized and promoted. References are also required to become specialized. We showcase our partners’ capabilities in Oracle products and industries through partner success stories that are published on Oracle.com. For significant implementations, we may invite partners to participate in a press release or be interviewed in a podcast. To participate and take a further step to become specialized, please take a minute to complete the form and tell us about the successful project you have implemented. If your story is selected, we will contact you for an interview. Create your references The partner reference program Enables partners to be recognized by both Oracle and our customers Provides an opportunity for partners to showcase successes with their customers on Oracle solutions Helps raise awareness of our partners’ capabilities, elevating them above their competition Time to submit a SOA and Application Grid reference request today To learn more about partner references, check out the following resources: Judson Althoff’s YouTube Video: Be Recognized with OPN Specialized Reference Program OPN PartnerCast: Be Recognized…Your Reference Matters!!! (MP3) Partner/Customer Reference Brochure (PDF) Marketing Kits We have created OFM 11g marketing kit http://tinyurl.com/soamarketing (OPN account required) The marketing kit includes all the ppts and demos from our launch event. Oracle package includes: • Event templates like invitation, agenda ,confirmation follow up templates • OFM 11g presentations • Free usage of the Oracle Customer Visit Center • Condition: mandatory lead registration in the Oracle Open Market Model (OMM) To download the material, please make sure that you select the campaign “Enterprise: Fusion Middleware 11g”: OFM 11g Oracle Marketing 4 Partners Package http://tinyurl.com/soamarketing (OPN account required)   For more information on Specialization please visit our OPN Specialized Webcast Series And become a member in our SOA Partner Community for registration please visit www.oracle.com/goto/ema/soa Jürgen Kress, SOA Partner Adoption EMEA SOA Specialized Application Grid Specialized Proof 2 transactions with OMM Proof 2 transactions with OMM Create your 2 references Create your 2 references SOA Sales assessment 3, Oracle Application Grid Sales Specialist  SOA Pre-Sales assessment 3 Oracle Application Grid PreSales Specialist Support assessment 1 Support assessment 2 SOA Implementation assessment 4 Application Gridplementation assessment 4

    Read the article

  • Oracle Flashback Technologies - Overview

    - by Sridhar_R-Oracle
    Oracle Flashback Technologies - IntroductionIn his May 29th 2014 blog, my colleague Joe Meeks introduced Oracle Maximum Availability Architecture (MAA) and discussed both planned and unplanned outages. Let’s take a closer look at unplanned outages. These can be caused by physical failures (e.g., server, storage, network, file deletion, physical corruption, site failures) or by logical failures – cases where all components and files are physically available, but data is incorrect or corrupt. These logical failures are usually caused by human errors or application logic errors. This blog series focuses on these logical errors – what causes them and how to address and recover from them using Oracle Database Flashback. In this introductory blog post, I’ll provide an overview of the Oracle Database Flashback technologies and will discuss the features in detail in future blog posts. Let’s get started. We are all human beings (unless a machine is reading this), and making mistakes is a part of what we do…often what we do best!  We “fat finger”, we spill drinks on keyboards, unplug the wrong cables, etc.  In addition, many of us, in our lives as DBAs or developers, must have observed, caused, or corrected one or more of the following unpleasant events: Accidentally updated a table with wrong values !! Performed a batch update that went wrong - due to logical errors in the code !! Dropped a table !! How do DBAs typically recover from these types of errors? First, data needs to be restored and recovered to the point-in-time when the error occurred (incomplete or point-in-time recovery).  Moreover, depending on the type of fault, it’s possible that some services – or even the entire database – would have to be taken down during the recovery process.Apart from error conditions, there are other questions that need to be addressed as part of the investigation. For example, what did the data look like in the morning, prior to the error? What were the various changes to the row(s) between two timestamps? Who performed the transaction and how can it be reversed?  Oracle Database includes built-in Flashback technologies, with features that address these challenges and questions, and enable you to perform faster, easier, and convenient recovery from logical corruptions. HistoryFlashback Query, the first Flashback Technology, was introduced in Oracle 9i. It provides a simple, powerful and completely non-disruptive mechanism for data verification and recovery from logical errors, and enables users to view the state of data at a previous point in time.Flashback Technologies were further enhanced in Oracle 10g, to provide fast, easy recovery at the database, table, row, and even at a transaction level.Oracle Database 11g introduced an innovative method to manage and query long-term historical data with Flashback Data Archive. The 11g release also introduced Flashback Transaction, which provides an easy, one-step operation to back out a transaction. Oracle Database versions 11.2.0.2 and beyond further enhanced the performance of these features. Note that all the features listed here work without requiring any kind of restore operation.In addition, Flashback features are fully supported with the new multi-tenant capabilities introduced with Oracle Database 12c, Flashback Features Oracle Flashback Database enables point-in-time-recovery of the entire database without requiring a traditional restore and recovery operation. It rewinds the entire database to a specified point in time in the past by undoing all the changes that were made since that time.Oracle Flashback Table enables an entire table or a set of tables to be recovered to a point in time in the past.Oracle Flashback Drop enables accidentally dropped tables and all dependent objects to be restored.Oracle Flashback Query enables data to be viewed at a point-in-time in the past. This feature can be used to view and reconstruct data that was lost due to unintentional change(s) or deletion(s). This feature can also be used to build self-service error correction into applications, empowering end-users to undo and correct their errors.Oracle Flashback Version Query offers the ability to query the historical changes to data between two points in time or system change numbers (SCN) Oracle Flashback Transaction Query enables changes to be examined at the transaction level. This capability can be used to diagnose problems, perform analysis, audit transactions, and even revert the transaction by undoing SQLOracle Flashback Transaction is a procedure used to back-out a transaction and its dependent transactions.Flashback technologies eliminate the need for a traditional restore and recovery process to fix logical corruptions or make enquiries. Using these technologies, you can recover from the error in the same amount of time it took to generate the error. All the Flashback features can be accessed either via SQL command line (or) via Enterprise Manager.  Most of the Flashback technologies depend on the available UNDO to retrieve older data. The following table describes the various Flashback technologies: their purpose, dependencies and situations where each individual technology can be used.   Example Syntax Error investigation related:The purpose is to investigate what went wrong and what the values were at certain points in timeFlashback Queries  ( select .. as of SCN | Timestamp )   - Helps to see the value of a row/set of rows at a point in timeFlashback Version Queries  ( select .. versions between SCN | Timestamp and SCN | Timestamp)  - Helps determine how the value evolved between certain SCNs or between timestamps Flashback Transaction Queries (select .. XID=)   - Helps to understand how the transaction caused the changes.Error correction related:The purpose is to fix the error and correct the problems,Flashback Table  (flashback table .. to SCN | Timestamp)  - To rewind the table to a particular timestamp or SCN to reverse unwanted updates Flashback Drop (flashback table ..  to before drop )  - To undrop or undelete a table Flashback Database (flashback database to SCN  | Restore Point )  - This is the rewind button for Oracle databases. You can revert the entire database to a particular point in time. It is a fast way to perform a PITR (point-in-time recovery). Flashback Transaction (DBMS_FLASHBACK.TRANSACTION_BACKOUT(XID..))  - To reverse a transaction and its related transactions Advanced use cases Flashback technology is integrated into Oracle Recovery Manager (RMAN) and Oracle Data Guard. So, apart from the basic use cases mentioned above, the following use cases are addressed using Oracle Flashback. Block Media recovery by RMAN - to perform block level recovery Snapshot Standby - where the standby is temporarily converted to a read/write environment for testing, backup, or migration purposes Re-instate old primary in a Data Guard environment – this avoids the need to restore an old backup and perform a recovery to make it a new standby. Guaranteed Restore Points - to bring back the entire database to an older point-in-time in a guaranteed way. and so on..I hope this introductory overview helps you understand how Flashback features can be used to investigate and recover from logical errors.  As mentioned earlier, I will take a deeper-dive into to some of the critical Flashback features in my upcoming blogs and address common use cases.

    Read the article

  • PayPal India Problems Continues

    - by Ravish
    Reserve Bank of India has been giving hard time to PayPal and its users in India. RBI had previously blocked PayPal transactions in India a few times, and they made it difficult to withdraw payments by enforcing exports and forex related compliance. Here is yet another bad news for Indian PayPal users. With effect from March 1st, Indian users cannot receive payments of more than $500 in your PayPal account. Moreover, you cannot keep or use any funds in your PayPal account. You can use your PayPal balance to make send money for any goods or services, and must withdraw it to your bank account within 7 days of the receipt. These changes have rendered PayPal almost useless for small business, webmasters and publishers. Most webmasters and publishers rely on PayPal to receive payments from advertisers and clients. It has also made it impossible to buy anything online with PayPal. Sending payments abroad via other channels is already a pain, sending a bank wire requires too many formalities, documentation and time. Moreover, you are even required to deduct TDS on payments you make for any products or services. The restrictions will take effect on March 1st, so you have 30 days to complete any pending transactions you may have. This step by RBI is yet another gimmick by corrupt Indian Government to make life difficult of entrepreneurs, kill innovation, slap more taxes and create more channels to take bribes. Following is the notification from PayPal about this issue: As part of our commitment to provide a high level of customer service, we would like to give you a 30-day advance notice on changes to our user agreement for India. With effect from 1 March 2011, you are required to comply with the requirements set out in the notification of the Reserve Bank of India governing the processing and settlement of export-related receipts facilitated by online payment gateways (“RBI Guidelines”). In order to comply with the RBI Guidelines, our user agreement in India will be amended for the following services as follows: Any balance in and all future payments into your PayPal account may not be used to buy goods or services and must be transferred to your bank account in India within 7 days from the receipt of confirmation from the buyer in respect of the goods or services; and Export-related payments for goods and services into your PayPal account may not exceed US$500 per transaction. We seek your understanding as we continue to employ our best efforts to comply with the RBI Guidelines in a timely manner. Related posts:WordCamp India Ends On a High Note Silicon WordPress Theme Accord WordPress Theme

    Read the article

  • Payment Gateway options other than Paypal, for sending out mass payments

    - by Rishav Rastogi
    We were using Paypal Payment pro earlier for the same thing, but for some reason Paypal has been given some new guideline which kinda hinder with the way we need to send out payments at the moment. We receive payments from clients and then send out payments back to vendors on a weekly basis ( deducting our cut ). Can you let me know what options are available to for such transactions other than paypal ? which is the best in terms cost of setup etc. Thanks

    Read the article

  • WebCenter Customer Spotlight: Los Angeles Department of Water and Power

    - by me
    Author: Peter Reiser - Social Business Evangelist, Oracle WebCenter  Solution Summary Los Angeles Department of Water and Power (LADWP) is the largest public utility company in the United States with over 1.6 million customers. LADWP provides water and power for millions of residential & commercial customers in Southern California. The goal of the project was to implement a newly designed web portal to increase customer self-service while reducing transactions via IVR and automate many of the paper based processes to web based workflows for their 1.6 million customers. LADWP implemented a Self Service Portal using Oracle WebCenter Portal & Oracle WebCenter Content and Oracle SOA Suite for the integration of their complex back-end systems infrastructure. The new portal has received extremely positive feedback from not only the customers and users of the portal, but also other utilities. At Oracle OpenWorld 2012, LADWP won the prestigious WebCenter innovation award for their innovative solution. Company OverviewLos Angeles Department of Water and Power (LADWP) is the largest public utility company in the United States with over 1.6 million customers. LADWP provides water and power for millions of residential & commercial customers in Southern California. LADWP also bills most of these customers for sanitation services provided by another department in the city of Los Angeles.  Business ChallengesThe goal of the project was to implement a newly designed web portal that is easy to navigate from a web browser and mobile devices, as well as be the platform for surfacing internet and intranet applications at LADWP. The primary objective of the new portal was to increase customer self-service while reducing the transactions via IVR and walk-up and to automate many of the paper based processes to web based workflows for customers. This includes automation of Self Service implemented through My Account (Bill Pay, Payment History, Bill History, Usage analysis, Service Request Management) Financial Assistance Programs Customer Rebate Programs Turn Off/Turn On/Transfer of Services Outage Reporting eNotification (SMS, email) Solution DeployedLADWP implemented a Self Service Portal using Oracle WebCenter Portal & Oracle WebCenter Content. Using Oracle SOA Suite they integrated various back-end systems including Oracle Siebel CRM IBM Mainframe based CIS FILENET for document management EBP Eletronic Bill Payment System HP Imprint System for BillXML data Other systems including outage reporting systems, SMS service, etc. The new portal’s features include: Complete Graphical redesign based on best practices in UI Design for high usability Customer Self Service implemented through MyAccount (Bill Pay, Payment History, Bill History, Usage Analysis, Service Request Management) Financial Assistance Programs (CRM, WebCenter) Customer Rebate Programs (CRM, WebCenter) Turn On/Off/Transfer of services (Commercial & Residential) Outage Reporting eNotification (SMS, email) Multilingual (English & Spanish) – using WebCenter multi-language support Section 508 (ADA) Compliant Search – Using WebCenter SES (Secured Enterprise Search) Distributed Authorship in WebCenter Content Mobile Access (any Mobile Browser) Business ResultsThe new portal has received extremely positive feedback from not only customers and users of the portal, but also other utilities. At Oracle OpenWorld 2012, LADWP won the prestigious WebCenter innovation award for their innovative solution. Additional Information LADWP OpenWorld presentation Oracle WebCenter Portal Oracle WebCenter Content Oracle SOA Suite

    Read the article

< Previous Page | 63 64 65 66 67 68 69 70 71 72 73 74  | Next Page >