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• The Data Scientist

  - by BuckWoody

  A new term - well, perhaps not that new - has come up and I’m actually very excited about it. The term is Data Scientist, and since it’s new, it’s fairly undefined. I’ll explain what I think it means, and why I’m excited about it. In general, I’ve found the term deals at its most basic with analyzing data. Of course, we all do that, and the term itself in that definition is redundant. There is no science that I know of that does not work with analyzing lots of data. But the term seems to refer to more than the common practices of looking at data visually, putting it in a spreadsheet or report, or even using simple coding to examine data sets. The term Data Scientist (as far as I can make out this early in it’s use) is someone who has a strong understanding of data sources, relevance (statistical and otherwise) and processing methods as well as front-end displays of large sets of complicated data. Some - but not all - Business Intelligence professionals have these skills. In other cases, senior developers, database architects or others fill these needs, but in my experience, many lack the strong mathematical skills needed to make these choices properly. I’ve divided the knowledge base for someone that would wear this title into three large segments. It remains to be seen if a given Data Scientist would be responsible for knowing all these areas or would specialize. There are pretty high requirements on the math side, specifically in graduate-degree level statistics, but in my experience a company will only have a few of these folks, so they are expected to know quite a bit in each of these areas. Persistence The first area is finding, cleaning and storing the data. In some cases, no cleaning is done prior to storage - it’s just identified and the cleansing is done in a later step. This area is where the professional would be able to tell if a particular data set should be stored in a Relational Database Management System (RDBMS), across a set of key/value pair storage (NoSQL) or in a file system like HDFS (part of the Hadoop landscape) or other methods. Or do you examine the stream of data without storing it in another system at all? This is an important decision - it’s a foundation choice that deals not only with a lot of expense of purchasing systems or even using Cloud Computing (PaaS, SaaS or IaaS) to source it, but also the skillsets and other resources needed to care and feed the system for a long time. The Data Scientist sets something into motion that will probably outlast his or her career at a company or organization. Often these choices are made by senior developers, database administrators or architects in a company. But sometimes each of these has a certain bias towards making a decision one way or another. The Data Scientist would examine these choices in light of the data itself, starting perhaps even before the business requirements are created. The business may not even be aware of all the strategic and tactical data sources that they have access to. Processing Once the decision is made to store the data, the next set of decisions are based around how to process the data. An RDBMS scales well to a certain level, and provides a high degree of ACID compliance as well as offering a well-known set-based language to work with this data. In other cases, scale should be spread among multiple nodes (as in the case of Hadoop landscapes or NoSQL offerings) or even across a Cloud provider like Windows Azure Table Storage. In fact, in many cases - most of the ones I’m dealing with lately - the data should be split among multiple types of processing environments. This is a newer idea. Many data professionals simply pick a methodology (RDBMS with Star Schemas, NoSQL, etc.) and put all data there, regardless of its shape, processing needs and so on. A Data Scientist is familiar not only with the various processing methods, but how they work, so that they can choose the right one for a given need. This is a huge time commitment, hence the need for a dedicated title like this one. Presentation This is where the need for a Data Scientist is most often already being filled, sometimes with more or less success. The latest Business Intelligence systems are quite good at allowing you to create amazing graphics - but it’s the data behind the graphics that are the most important component of truly effective displays. This is where the mathematics requirement of the Data Scientist title is the most unforgiving. In fact, someone without a good foundation in statistics is not a good candidate for creating reports. Even a basic level of statistics can be dangerous. Anyone who works in analyzing data will tell you that there are multiple errors possible when data just seems right - and basic statistics bears out that you’re on the right track - that are only solvable when you understanding why the statistical formula works the way it does. And there are lots of ways of presenting data. Sometimes all you need is a “yes” or “no” answer that can only come after heavy analysis work. In that case, a simple e-mail might be all the reporting you need. In others, complex relationships and multiple components require a deep understanding of the various graphical methods of presenting data. Knowing which kind of chart, color, graphic or shape conveys a particular datum best is essential knowledge for the Data Scientist. Why I’m excited I love this area of study. I like math, stats, and computing technologies, but it goes beyond that. I love what data can do - how it can help an organization. I’ve been fortunate enough in my professional career these past two decades to work with lots of folks who perform this role at companies from aerospace to medical firms, from manufacturing to retail. Interestingly, the size of the company really isn’t germane here. I worked with one very small bio-tech (cryogenics) company that worked deeply with analysis of complex interrelated data. So  watch this space. No, I’m not leaving Azure or distributed computing or Microsoft. In fact, I think I’m perfectly situated to investigate this role further. We have a huge set of tools, from RDBMS to Hadoop to allow me to explore. And I’m happy to share what I learn along the way.

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• Infinite loop using Spring Security - Login page is protected even though it should allow anonymous

  - by Tai Squared

  I have a Spring application (Spring version 2.5.6.SEC01, Spring Security version 2.0.5) with the following setup: web.xml <welcome-file-list> <welcome-file> index.jsp </welcome-file> </welcome-file-list> The index.jsp page is in the WebContent directory and simply contains a redirect: <c:redirect url="/login.htm"/> In the appname-servlet.xml, there is a view resolver to point to the jsp pages in WEB-INF/jsp <bean id="viewResolver" class="org.springframework.web.servlet.view.InternalResourceViewResolver"> <property name="viewClass" value="org.springframework.web.servlet.view.JstlView" /> <property name="prefix" value="/WEB-INF/jsp/" /> <property name="suffix" value=".jsp" /> </bean> In the security-config.xml file, I have the following configuration: <http> <!-- Restrict URLs based on role --> <intercept-url pattern="/WEB-INF/jsp/login.jsp*" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/WEB-INF/jsp/header.jsp*" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/WEB-INF/jsp/footer.jsp*" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/login*" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/index.jsp" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/logoutSuccess*" access="ROLE_ANONYMOUS" /> <intercept-url pattern="/css/**" filters="none" /> <intercept-url pattern="/images/**" filters="none" /> <intercept-url pattern="/**" access="ROLE_ANONYMOUS" /> <form-login login-page="/login.jsp"/> </http> <authentication-provider> <jdbc-user-service data-source-ref="dataSource" /> </authentication-provider> However, I can't even navigate to the login page and get the following error in the log: WARNING: The login page is being protected by the filter chain, but you don't appear to have anonymous authentication enabled. This is almost certainly an error. I've tried changing the ROLE_ANONYMOUS to IS_AUTHENTICATED_ANONYMOUSLY, changing the login-page to index.jsp, login.htm, and adding different intercept-url values, but I can't get it so the login page is accesible and security applies to the other pages. What do I have to change to avoid this loop?

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• How to expose an entity via alternate keys with spring data rest

  - by dan carter

  Spring-data-rest does a great job exposing entities via their primary key for GET, PUT and DELETE etc. operations. /myentityies/123 It also exposes search operations. /myentities/search/byMyOtherKey?myOtherKey=123 In my case the entities have a number of alternate keys. The systems calling us, will know the objects by these IDs, rather than our internal primary key. Is it possible to expose the objects via another URL and have the GET, PUT and DELETE handled by the built-in spring-data-rest controllers? /myentities/myotherkey/456 We'd like to avoid forcing the calling systems to have to make two requests for each update. I've tried playing with @RestResource path value, but there doesn't seem to be a way to add additional paths.

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• Fraud Detection with the SQL Server Suite Part 2

  - by Dejan Sarka

  This is the second part of the fraud detection whitepaper. You can find the first part in my previous blog post about this topic. My Approach to Data Mining Projects It is impossible to evaluate the time and money needed for a complete fraud detection infrastructure in advance. Personally, I do not know the customer’s data in advance. I don’t know whether there is already an existing infrastructure, like a data warehouse, in place, or whether we would need to build one from scratch. Therefore, I always suggest to start with a proof-of-concept (POC) project. A POC takes something between 5 and 10 working days, and involves personnel from the customer’s site – either employees or outsourced consultants. The team should include a subject matter expert (SME) and at least one information technology (IT) expert. The SME must be familiar with both the domain in question as well as the meaning of data at hand, while the IT expert should be familiar with the structure of data, how to access it, and have some programming (preferably Transact-SQL) knowledge. With more than one IT expert the most time consuming work, namely data preparation and overview, can be completed sooner. I assume that the relevant data is already extracted and available at the very beginning of the POC project. If a customer wants to have their people involved in the project directly and requests the transfer of knowledge, the project begins with training. I strongly advise this approach as it offers the establishment of a common background for all people involved, the understanding of how the algorithms work and the understanding of how the results should be interpreted, a way of becoming familiar with the SQL Server suite, and more. Once the data has been extracted, the customer’s SME (i.e. the analyst), and the IT expert assigned to the project will learn how to prepare the data in an efficient manner. Together with me, knowledge and expertise allow us to focus immediately on the most interesting attributes and identify any additional, calculated, ones soon after. By employing our programming knowledge, we can, for example, prepare tens of derived variables, detect outliers, identify the relationships between pairs of input variables, and more, in only two or three days, depending on the quantity and the quality of input data. I favor the customer’s decision of assigning additional personnel to the project. For example, I actually prefer to work with two teams simultaneously. I demonstrate and explain the subject matter by applying techniques directly on the data managed by each team, and then both teams continue to work on the data overview and data preparation under our supervision. I explain to the teams what kind of results we expect, the reasons why they are needed, and how to achieve them. Afterwards we review and explain the results, and continue with new instructions, until we resolve all known problems. Simultaneously with the data preparation the data overview is performed. The logic behind this task is the same – again I show to the teams involved the expected results, how to achieve them and what they mean. This is also done in multiple cycles as is the case with data preparation, because, quite frankly, both tasks are completely interleaved. A specific objective of the data overview is of principal importance – it is represented by a simple star schema and a simple OLAP cube that will first of all simplify data discovery and interpretation of the results, and will also prove useful in the following tasks. The presence of the customer’s SME is the key to resolving possible issues with the actual meaning of the data. We can always replace the IT part of the team with another database developer; however, we cannot conduct this kind of a project without the customer’s SME. After the data preparation and when the data overview is available, we begin the scientific part of the project. I assist the team in developing a variety of models, and in interpreting the results. The results are presented graphically, in an intuitive way. While it is possible to interpret the results on the fly, a much more appropriate alternative is possible if the initial training was also performed, because it allows the customer’s personnel to interpret the results by themselves, with only some guidance from me. The models are evaluated immediately by using several different techniques. One of the techniques includes evaluation over time, where we use an OLAP cube. After evaluating the models, we select the most appropriate model to be deployed for a production test; this allows the team to understand the deployment process. There are many possibilities of deploying data mining models into production; at the POC stage, we select the one that can be completed quickly. Typically, this means that we add the mining model as an additional dimension to an existing DW or OLAP cube, or to the OLAP cube developed during the data overview phase. Finally, we spend some time presenting the results of the POC project to the stakeholders and managers. Even from a POC, the customer will receive lots of benefits, all at the sole risk of spending money and time for a single 5 to 10 day project: The customer learns the basic patterns of frauds and fraud detection The customer learns how to do the entire cycle with their own people, only relying on me for the most complex problems The customer’s analysts learn how to perform much more in-depth analyses than they ever thought possible The customer’s IT experts learn how to perform data extraction and preparation much more efficiently than they did before All of the attendees of this training learn how to use their own creativity to implement further improvements of the process and procedures, even after the solution has been deployed to production The POC output for a smaller company or for a subsidiary of a larger company can actually be considered a finished, production-ready solution It is possible to utilize the results of the POC project at subsidiary level, as a finished POC project for the entire enterprise Typically, the project results in several important “side effects” Improved data quality Improved employee job satisfaction, as they are able to proactively contribute to the central knowledge about fraud patterns in the organization Because eventually more minds get to be involved in the enterprise, the company should expect more and better fraud detection patterns After the POC project is completed as described above, the actual project would not need months of engagement from my side. This is possible due to our preference to transfer the knowledge onto the customer’s employees: typically, the customer will use the results of the POC project for some time, and only engage me again to complete the project, or to ask for additional expertise if the complexity of the problem increases significantly. I usually expect to perform the following tasks: Establish the final infrastructure to measure the efficiency of the deployed models Deploy the models in additional scenarios Through reports By including Data Mining Extensions (DMX) queries in OLTP applications to support real-time early warnings Include data mining models as dimensions in OLAP cubes, if this was not done already during the POC project Create smart ETL applications that divert suspicious data for immediate or later inspection I would also offer to investigate how the outcome could be transferred automatically to the central system; for instance, if the POC project was performed in a subsidiary whereas a central system is available as well Of course, for the actual project, I would repeat the data and model preparation as needed It is virtually impossible to tell in advance how much time the deployment would take, before we decide together with customer what exactly the deployment process should cover. Without considering the deployment part, and with the POC project conducted as suggested above (including the transfer of knowledge), the actual project should still only take additional 5 to 10 days. The approximate timeline for the POC project is, as follows: 1-2 days of training 2-3 days for data preparation and data overview 2 days for creating and evaluating the models 1 day for initial preparation of the continuous learning infrastructure 1 day for presentation of the results and discussion of further actions Quite frequently I receive the following question: are we going to find the best possible model during the POC project, or during the actual project? My answer is always quite simple: I do not know. Maybe, if we would spend just one hour more for data preparation, or create just one more model, we could get better patterns and predictions. However, we simply must stop somewhere, and the best possible way to do this, according to my experience, is to restrict the time spent on the project in advance, after an agreement with the customer. You must also never forget that, because we build the complete learning infrastructure and transfer the knowledge, the customer will be capable of doing further investigations independently and improve the models and predictions over time without the need for a constant engagement with me.

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• No flow definition found. Spring web flow

  - by user184794

  Hi, I am new to Spring webflow and now I am trying the example in Spring recipes book and I know this is a basic question. I am getting the error as follows, org.springframework.webflow.definition.registry.NoSuchFlowDefinitionException: No flow definition '${flowExecutionUrl}&_eventId=next' found at org.springframework.webflow.definition.registry.FlowDefinitionRegistryImpl.getFlowDefinitionHolder(FlowDefinitionRegistryImpl.java:126) at org.springframework.webflow.definition.registry.FlowDefinitionRegistryImpl.getFlowDefinition(FlowDefinitionRegistryImpl.java:61) at org.springframework.webflow.executor.FlowExecutorImpl.launchExecution(FlowExecutorImpl.java:138) at org.springframework.webflow.mvc.servlet.FlowHandlerAdapter.handle(FlowHandlerAdapter.java:193).... Shown below is my configurations, <bean name="flowController" class="org.springframework.webflow.mvc.servlet.FlowController"> <property name="flowExecutor" ref="flowExecutor"></property> </bean> <webflow:flow-executor id="flowExecutor" /> <webflow:flow-registry id="flowRegistry" > <webflow:flow-location path="/WEB-INF/flows/welcome/welcome.xml"></webflow:flow-location> </webflow:flow-registry> /WEB-INF/flows/welcome/welcome.xml, <view-state id="welcome"> <transition on="next" to="introduction" /> <transition on="skip" to="menu" /> </view-state> <view-state id="introduction"> <on-render> <evaluate expression="libraryService.getHolidays()" result="requestScope.holidays" /> </on-render> <transition on="next" to="menu" /> </view-state> <view-state id="menu"></view-state> In welcome.jsp, <a href="${flowExecutionUrl}&_eventId=next">Next</a> <a href="${flowExecutionUrl}&_eventId=skip">Skip</a> Please let me know what is going wrong. I am using 2.0.9 Release. Thanks in advance, SD

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• Big Data – Beginning Big Data Series Next Month in 21 Parts

  - by Pinal Dave

  Big Data is the next big thing. There was a time when we used to talk in terms of MB and GB of the data. However, the industry is changing and we are now moving to a conversation where we discuss about data in Petabyte, Exabyte and Zettabyte. It seems that the world is now talking about increased Volume of the data. In simple world we all think that Big Data is nothing but plenty of volume. In reality Big Data is much more than just a huge volume of the data. When talking about the data we need to understand about variety and volume along with volume. Though Big data look like a simple concept, it is extremely complex subject when we attempt to start learning the same. My Journey I have recently presented on Big Data in quite a few organizations and I have received quite a few questions during this roadshow event. I have collected all the questions which I have received and decided to post about them on the blog. In the month of October 2013, on every weekday we will be learning something new about Big Data. Every day I will share a concept/question and in the same blog post we will learn the answer of the same. Big Data – Plenty of Questions I received quite a few questions during my road trip. Here are few of the questions. I want to learn Big Data – where should I start? Do I need to know SQL to learn Big Data? What is Hadoop? There are so many organizations talking about Big Data, and every one has a different approach. How to start with big Data? Do I need to know Java to learn about Big Data? What is different between various NoSQL languages. I will attempt to answer most of the questions during the month long series in the next month. Big Data – Big Subject Big Data is a very big subject and I no way claim that I will be covering every single big data concept in this series. However, I promise that I will be indeed sharing lots of basic concepts which are revolving around Big Data. We will discuss from fundamentals about Big Data and continue further learning about it. I will attempt to cover the concept so simple that many of you might have wondered about it but afraid to ask. Your Role! During this series next month, I need your one help. Please keep on posting questions you might have related to big data as blog post comments and on Facebook Page. I will monitor them closely and will try to answer them as well during this series. Now make sure that you do not miss any single blog post in this series as every blog post will be linked to each other. You can subscribe to my feed or like my Facebook page or subscribe via email (by entering email in the blog post). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Big Data, PostADay, SQL, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Spring security problem, Error creating bean with name 'org.springframework.web.servlet.mvc.annotati

  - by benaissa

  Hello; I'm developping a web application with spring mvc, i started by developping the web application after i'm trying to add spring security; but i have this message, and i don't find a solution, thanks 16-04-2010 12:10:22:296 6062 ERROR org.springframework.web.servlet.DispatcherServlet - Context initialization failed org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'org.springframework.web.servlet.mvc.annotation.DefaultAnnotationHandlerMapping': Initialization of bean failed; nested exception is java.lang.NoClassDefFoundError: org/springframework/beans/factory/generic/GenericBeanFactoryAccessor at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:527) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:456) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:286) at org.springframework.web.servlet.DispatcherServlet.createDefaultStrategy(DispatcherServlet.java:770) at org.springframework.web.servlet.DispatcherServlet.getDefaultStrategies(DispatcherServlet.java:737) at org.springframework.web.servlet.DispatcherServlet.initHandlerMappings(DispatcherServlet.java:518) at org.springframework.web.servlet.DispatcherServlet.initStrategies(DispatcherServlet.java:410) at org.springframework.web.servlet.DispatcherServlet.onRefresh(DispatcherServlet.java:398) at org.springframework.web.servlet.FrameworkServlet.onApplicationEvent(FrameworkServlet.java:474) at org.springframework.context.event.GenericApplicationListenerAdapter.onApplicationEvent(GenericApplicationListenerAdapter.java:51) at org.springframework.context.event.SourceFilteringListener.onApplicationEventInternal(SourceFilteringListener.java:97) at org.springframework.context.event.SourceFilteringListener.onApplicationEvent(SourceFilteringListener.java:68) at org.springframework.context.event.SimpleApplicationEventMulticaster.multicastEvent(SimpleApplicationEventMulticaster.java:97) at org.springframework.context.support.AbstractApplicationContext.publishEvent(AbstractApplicationContext.java:301) at org.springframework.context.support.AbstractApplicationContext.finishRefresh(AbstractApplicationContext.java:888) at org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:426) at org.springframework.web.servlet.FrameworkServlet.createWebApplicationContext(FrameworkServlet.java:402) at org.springframework.web.servlet.FrameworkServlet.initWebApplicationContext(FrameworkServlet.java:316) at org.springframework.web.servlet.FrameworkServlet.initServletBean(FrameworkServlet.java:282) at org.springframework.web.servlet.HttpServletBean.init(HttpServletBean.java:126) at javax.servlet.GenericServlet.init(GenericServlet.java:212) at org.apache.catalina.core.StandardWrapper.loadServlet(StandardWrapper.java:1173) at org.apache.catalina.core.StandardWrapper.allocate(StandardWrapper.java:809) at org.apache.catalina.core.StandardWrapperValve.invoke(StandardWrapperValve.java:129) at org.apache.catalina.core.StandardContextValve.invoke(StandardContextValve.java:191) at org.apache.catalina.core.StandardHostValve.invoke(StandardHostValve.java:127) at org.apache.catalina.valves.ErrorReportValve.invoke(ErrorReportValve.java:102) at org.apache.catalina.core.StandardEngineValve.invoke(StandardEngineValve.java:109) at org.apache.catalina.connector.CoyoteAdapter.service(CoyoteAdapter.java:298) at org.apache.coyote.http11.Http11Processor.process(Http11Processor.java:852) at org.apache.coyote.http11.Http11Protocol$Http11ConnectionHandler.process(Http11Protocol.java:588) at org.apache.tomcat.util.net.JIoEndpoint$Worker.run(JIoEndpoint.java:489) at java.lang.Thread.run(Thread.java:619) Caused by: java.lang.NoClassDefFoundError: org/springframework/beans/factory/generic/GenericBeanFactoryAccessor at org.springframework.web.servlet.mvc.annotation.DefaultAnnotationHandlerMapping.determineUrlsForHandler(DefaultAnnotationHandlerMapping.java:113) at org.springframework.web.servlet.handler.AbstractDetectingUrlHandlerMapping.detectHandlers(AbstractDetectingUrlHandlerMapping.java:79) at org.springframework.web.servlet.handler.AbstractDetectingUrlHandlerMapping.initApplicationContext(AbstractDetectingUrlHandlerMapping.java:57) at org.springframework.context.support.ApplicationObjectSupport.initApplicationContext(ApplicationObjectSupport.java:119) at org.springframework.web.context.support.WebApplicationObjectSupport.initApplicationContext(WebApplicationObjectSupport.java:69) at org.springframework.context.support.ApplicationObjectSupport.setApplicationContext(ApplicationObjectSupport.java:73) at org.springframework.context.support.ApplicationContextAwareProcessor.invokeAwareInterfaces(ApplicationContextAwareProcessor.java:99) at org.springframework.context.support.ApplicationContextAwareProcessor.postProcessBeforeInitialization(ApplicationContextAwareProcessor.java:82) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyBeanPostProcessorsBeforeInitialization(AbstractAutowireCapableBeanFactory.java:394) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1405) at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:519) ... 32 more Caused by: java.lang.ClassNotFoundException: org.springframework.beans.factory.generic.GenericBeanFactoryAccessor at org.apache.catalina.loader.WebappClassLoader.loadClass(WebappClassLoader.java:1516) at org.apache.catalina.loader.WebappClassLoader.loadClass(WebappClassLoader.java:1361) at java.lang.ClassLoader.loadClassInternal(ClassLoader.java:320) ... 43 more

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• Spring redirecting back to referrer

  - by Eqbal

  I have some resources in my application that require redirection to another resource (form) if some context information is not set. After the context gets set (requires two user steps), I need to redirect back to the requested resource. How do I achieve that. I am using annotation based controllers in Spring 3. Is org.springframework.security.web.savedrequest.HttpSessionRequestCache of any use.

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• Spring Web MVC: Use same request mapping for request parameter and path variable

  - by ngeek

  Good people: is there a way to express that my Spring Web MVC controller method should be matched either by a request handing in a ID as part of the URI path ... @RequestMapping(method=RequestMethod.GET, value="campaigns/{id}") public String getCampaignDetails(Model model, @PathVariable("id") Long id) { ... or if the client sends in the ID as a HTTP request parameter in the style ... @RequestMapping(method=RequestMethod.GET, value="campaigns") public String getCampaignDetails(Model model, @RequestParam("id") Long id) { This seems to me a quite common real-world URL scheme where I don't want to add duplicate code, but I wasn't able to find an answer yet. Any advice highly welcome.

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• Spring Security 3.0 and Active Directory LDAP: DOMAIN\user login

  - by Bernd Haug

  I would like to have users authenticate against an ActiveDirectory LDAP server using the DOMAIN\user.name syntax. I think that should be possible with SpringSec 3.0 since the docs mention an "alternative syntax" which I guess refers to the DOM\user syntax instead of a bind DN, but the docs don't elaborate further. Is there some way to configure Spring Sec 3 LDAP to use "the MS way" or do I have to write my own Authenticator implementation (against e.g. the java.naming.directory package, which I've tested to be able to use the MS syntax as its SECURITY_PRINCIPAL)?

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• Httpsession with Spring 3 MVC

  - by vipul12389

  I want to use httpsession in Spring 3 MVC..i have searched all the web and got this solution..at http://forum.springsource.org/showthread.php?98850-Adding-to-stuff-to-the-session-while-using-ResponseBody Basically, My application auto authenticates user by getting winId and authorizes through LDAP..(Its a intranet site) Here is the flow of the application, 1. User enters Aplication url (http://localhost:8082/eIA_Mock_5) it has a welcome page (index.jsp) Index.jsp gets winId through jQuery and hits login.html (through Ajax) and passes windowsId login.html (Controller) authenticates through LDAP and gives back 'Valid' String as a response javascript, upon getting the correct response, redirects/loads welcome page i.e. goes to localhost:8082/eIA_Mock_5/welcome.html Now, i have filter associated with it..which checks for is session valid for each incoming request..Now the problem is even though i set data on to httpsession, yet the filter or any other controller fails to get the data through session as a result it doesnt proceeds further.. here is the code..and could you suggest what is wrong actually ?? Home_Controller.java @Controller public class Home_Controller { public static Log logger = LogFactory.getLog(Home_Controller.class); @RequestMapping(value={"/welcome"}) public ModelAndView loadWelcomePage(HttpServletRequest request,HttpServletResponse response) { ModelAndView mdv = new ModelAndView(); try{ /*HttpSession session = request.getSession(); UserMasterBean userBean = (UserMasterBean)session.getAttribute("userBean"); String userName=userBean.getWindowsId(); if(userName==null || userName.equalsIgnoreCase("")) { mdv.setViewName("homePage"); System.out.println("Unable to authenticate user "); logger.debug("Unable to authenticate user "); } else { System.out.println("Welcome User "+userName); logger.debug("Welcome User "+userName); */ mdv.setViewName("homePage"); /*}*/ } catch(Exception e){ logger.debug("inside authenticateUser ",e); e.printStackTrace(); } return mdv; } @RequestMapping(value = "/login", method = RequestMethod.GET) public @ResponseBody String authenticateUser(@RequestParam String userName,HttpSession session) { logger.debug("inside authenticateUser"); String returnResponse=new String(); try{ logger.debug("userName for Authentication "+userName); System.out.println("userName for Authentication "+userName); //HttpSession session = request.getSession(); if(userName==null || userName.trim().equalsIgnoreCase("")) returnResponse="Invalid"; else { System.out.println("uname "+userName); String ldapResponse = LDAPConnectUtil.isValidActiveDirectoryUser(userName, ""); if(ldapResponse.equalsIgnoreCase("true")) { returnResponse="Valid"; System.out.println(userName+" Authenticated"); logger.debug(userName+" Authenticated"); UserMasterBean userBean = new UserMasterBean(); userBean.setWindowsId(userName); //if(session.getAttribute("userBean")==null) session.setAttribute("userBean", userBean); } else { returnResponse="Invalid"; //session.setAttribute("userBean", null); System.out.println("Unable to Authenticate the user through Ldap"); logger.debug("Unable to Authenticate the user through Ldap"); } System.out.println("ldapResponse "+ldapResponse); logger.debug("ldapResponse "+ldapResponse); System.out.println("returnResponse "+returnResponse); } UserMasterBean u = (UserMasterBean)session.getAttribute("userBean"); System.out.println("winId "+u.getWindowsId()); } catch(Exception e){ e.printStackTrace(); logger.debug("Exception in authenticateUser ",e); } return returnResponse; } Filter public void doFilter(ServletRequest request, ServletResponse response, FilterChain chain) { System.out.println("in PageFilter"); boolean flag = false; HttpServletRequest objHttpServletRequest = (HttpServletRequest)request; HttpServletResponse objHttpServletResponse = (HttpServletResponse)response; HttpSession session = objHttpServletRequest.getSession(); String contextPath = objHttpServletRequest.getContextPath(); String servletPath = objHttpServletRequest.getSession().getServletContext().getRealPath(objHttpServletRequest.getServletPath()); logger.debug("contextPath :" + contextPath); logger.debug("servletPath :" + servletPath); System.out.println("in PageFilter, contextPath :" + contextPath); System.out.println("in PageFilter, servletPath :" + servletPath); if (servletPath.endsWith("\\") || servletPath.endsWith("/") || servletPath.indexOf("css") > 0 || servletPath.indexOf("jsp") > 0 || servletPath.indexOf("images") > 0 || servletPath.indexOf("js") > 0 || servletPath.endsWith("index.jsp") || servletPath.indexOf("xls") > 0 || servletPath.indexOf("ini") > 0 || servletPath.indexOf("login.html") > 0 || /*servletPath.endsWith("welcome.html") ||*/ servletPath.endsWith("logout.do") ) { System.out.println("User is trying to access allowed pages like Login.jsp, errorPage.jsp, js, images, css"); logger.debug("User is trying to access allowed pages like Login.jsp, errorPage.jsp, js, images, css"); flag = true; } if (flag== false) { System.out.println("flag = false"); if(session.getAttribute("userBean") == null) System.out.println("yes session.userbean is null"); if ((session != null) && (session.getAttribute("userBean") != null)) { System.out.println("session!=null && session.getAttribute(userId)!=null"); logger.debug("IF Part"); UserMasterBean userBean = (UserMasterBean)session.getAttribute("userBean"); String windowsId = userBean.getWindowsId(); logger.debug("User Id " + windowsId + " allowed access"); System.out.println("User Id " + windowsId + " allowed access"); flag = true; } else { System.out.println("else .....session!=null && session.getAttribute(userId)!=null"); logger.debug("Else Part"); flag = false; } } if (flag == true) { try { System.out.println("before chain.doFilter(request, response)"); chain.doFilter(request, response); } catch (Exception e) { e.printStackTrace(); try { objHttpServletResponse.sendRedirect(contextPath + "/logout.do"); } catch (Exception ex) { ex.printStackTrace(); } } } else { try { System.out.println("before sendRedirect"); objHttpServletResponse.sendRedirect(contextPath + "/jsp/errorPage.jsp"); } catch (Exception ex) { ex.printStackTrace(); } } System.out.println("end of PageFilter"); } Index.jsp <script type="text/javascript"> //alert("inside s13"); var WinNetwork = new ActiveXObject("WScript.Network"); var userName=WinNetwork.UserName; alert(userName); $.ajax({ url : "login.html", data : "userName="+userName, success : function(result) { alert("result == "+result); if(result=="Valid") window.location = "http://10.160.118.200:8082/eIA_Mock_5/welcome.html"; } }); </script> web.xml has a filter entry with URL pattern as * I am using spring 3 mvc

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• Error while splitting application context file in spring

  - by Krupal

  I am trying to split the ApplicationContext file in Spring. For ex. the file is testproject-servlet.xml having all the entries. Now I want to split this single file into multiple files according to logical groups like : group1-services.xml, group2-services.xml I have created following entries in web.xml : <servlet> <servlet-name>testproject</servlet-name> <servlet-class> org.springframework.web.servlet.DispatcherServlet </servlet-class> <init-param> <param-name>contextConfigLocation</param-name> <param-value> /WEB-INF/group1-services.xml, /WEB-INF/group2-services.xml </param-value> </init-param> <load-on-startup>1</load-on-startup> </servlet> I am using SimpleUrlHandlerMapping as: RegisterController PayrollServicesController I also have the controller defined as : .. .. The problem is that I have splitted the ApplicationContext file "testproject-servlet.xml" into two different files and I have kept the above entries in "group1-services.xml". Is it fine? I want to group things logically based on their use in seperate .xml files. But I am getting the following error when I try to access a page inside the application : org.springframework.web.servlet.DispatcherServlet noHandlerFound WARNING: No mapping for [/TestProject/payroll_services.htm] in DispatcherServlet with name 'testproject' Please tell me how to resolve it. Thanks in Advance !

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• Spring Security 3.1 xsd and jars mismatch issue

  - by kmansoor

  I'm Trying to migrate from spring framework 3.0.5 to 3.1 and spring-security 3.0.5 to 3.1 (not to mention hibernate 3.6 to 4.1). Using Apache IVY. I'm getting the following error trying to start Tomcat 7.23 within Eclipse Helios (among a host of others, however this is the last in the console): org.springframework.beans.factory.BeanDefinitionStoreException: Line 7 in XML document from ServletContext resource [/WEB-INF/focus-security.xml] is invalid; nested exception is org.xml.sax.SAXParseException: Document root element "beans:beans", must match DOCTYPE root "null". org.xml.sax.SAXParseException: Document root element "beans:beans", must match DOCTYPE root "null". my security config file looks like this: <?xml version="1.0" encoding="UTF-8"?> <beans:beans xmlns="http://www.springframework.org/schema/security" xmlns:beans="http://www.springframework.org/schema/beans" xmlns:jdbc="http://www.springframework.org/schema/jdbc" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.1.xsd http://www.springframework.org/schema/security http://www.springframework.org/schema/security/spring-security-3.1.xsd http://www.springframework.org/schema/jdbc http://www.springframework.org/schema/jdbc/spring-jdbc-3.1.xsd"> Ivy.xml looks like this: <dependencies> <dependency org="org.hibernate" name="hibernate-core" rev="4.1.7.Final"/> <dependency org="org.hibernate" name="com.springsource.org.hibernate.validator" rev="4.2.0.Final" /> <dependency org="org.hibernate.javax.persistence" name="hibernate-jpa-2.0-api" rev="1.0.1.Final"/> <dependency org="org.hibernate" name="hibernate-entitymanager" rev="4.1.7.Final"/> <dependency org="org.hibernate" name="hibernate-validator" rev="4.3.0.Final"/> <dependency org="org.springframework" name="spring-context" rev="3.1.2.RELEASE"/> <dependency org="org.springframework" name="spring-web" rev="3.1.2.RELEASE"/> <dependency org="org.springframework" name="spring-tx" rev="3.1.2.RELEASE"/> <dependency org="org.springframework" name="spring-webmvc" rev="3.1.2.RELEASE"/> <dependency org="org.springframework" name="spring-test" rev="3.1.2.RELEASE"/> <dependency org="org.springframework.security" name="spring-security-core" rev="3.1.2.RELEASE"/> <dependency org="org.springframework.security" name="spring-security-web" rev="3.1.2.RELEASE"/> <dependency org="org.springframework.security" name="spring-security-config" rev="3.1.2.RELEASE"/> <dependency org="org.springframework.security" name="spring-security-taglibs" rev="3.1.2.RELEASE"/> <dependency org="net.sf.dozer" name="dozer" rev="5.3.2"/> <dependency org="org.apache.poi" name="poi" rev="3.8"/> <dependency org="commons-io" name="commons-io" rev="2.4"/> <dependency org="org.slf4j" name="slf4j-api" rev="1.6.6"/> <dependency org="org.slf4j" name="slf4j-log4j12" rev="1.6.6"/> <dependency org="org.slf4j" name="slf4j-ext" rev="1.6.6"/> <dependency org="log4j" name="log4j" rev="1.2.17"/> <dependency org="org.testng" name="testng" rev="6.8"/> <dependency org="org.dbunit" name="dbunit" rev="2.4.8"/> <dependency org="org.easymock" name="easymock" rev="3.1"/> </dependencies> I understand (hope) this error is due to a mismatch between the declared xsd and the jars on the classpath. Any pointers will be greatly appreciated.

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• Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is HDFS. In this article we will take a quick look at the importance of the Relational Database in Big Data world. A Big Question? Here are a few questions I often received since the beginning of the Big Data Series - Does the relational database have no space in the story of the Big Data? Does relational database is no longer relevant as Big Data is evolving? Is relational database not capable to handle Big Data? Is it true that one no longer has to learn about relational data if Big Data is the final destination? Well, every single time when I hear that one person wants to learn about Big Data and is no longer interested in learning about relational database, I find it as a bit far stretched. I am not here to give ambiguous answers of It Depends. I am personally very clear that one who is aspiring to become Big Data Scientist or Big Data Expert they should learn about relational database. NoSQL Movement The reason for the NoSQL Movement in recent time was because of the two important advantages of the NoSQL databases. Performance Flexible Schema In personal experience I have found that when I use NoSQL I have found both of the above listed advantages when I use NoSQL database. There are instances when I found relational database too much restrictive when my data is unstructured as well as they have in the datatype which my Relational Database does not support. It is the same case when I have found that NoSQL solution performing much better than relational databases. I must say that I am a big fan of NoSQL solutions in the recent times but I have also seen occasions and situations where relational database is still perfect fit even though the database is growing increasingly as well have all the symptoms of the big data. Situations in Relational Database Outperforms Adhoc reporting is the one of the most common scenarios where NoSQL is does not have optimal solution. For example reporting queries often needs to aggregate based on the columns which are not indexed as well are built while the report is running, in this kind of scenario NoSQL databases (document database stores, distributed key value stores) database often does not perform well. In the case of the ad-hoc reporting I have often found it is much easier to work with relational databases. SQL is the most popular computer language of all the time. I have been using it for almost over 10 years and I feel that I will be using it for a long time in future. There are plenty of the tools, connectors and awareness of the SQL language in the industry. Pretty much every programming language has a written drivers for the SQL language and most of the developers have learned this language during their school/college time. In many cases, writing query based on SQL is much easier than writing queries in NoSQL supported languages. I believe this is the current situation but in the future this situation can reverse when No SQL query languages are equally popular. ACID (Atomicity Consistency Isolation Durability) – Not all the NoSQL solutions offers ACID compliant language. There are always situations (for example banking transactions, eCommerce shopping carts etc.) where if there is no ACID the operations can be invalid as well database integrity can be at risk. Even though the data volume indeed qualify as a Big Data there are always operations in the application which absolutely needs ACID compliance matured language. The Mixed Bag I have often heard argument that all the big social media sites now a days have moved away from Relational Database. Actually this is not entirely true. While researching about Big Data and Relational Database, I have found that many of the popular social media sites uses Big Data solutions along with Relational Database. Many are using relational databases to deliver the results to end user on the run time and many still uses a relational database as their major backbone. Here are a few examples: Facebook uses MySQL to display the timeline. (Reference Link) Twitter uses MySQL. (Reference Link) Tumblr uses Sharded MySQL (Reference Link) Wikipedia uses MySQL for data storage. (Reference Link) There are many for prominent organizations which are running large scale applications uses relational database along with various Big Data frameworks to satisfy their various business needs. Summary I believe that RDBMS is like a vanilla ice cream. Everybody loves it and everybody has it. NoSQL and other solutions are like chocolate ice cream or custom ice cream – there is a huge base which loves them and wants them but not every ice cream maker can make it just right  for everyone’s taste. No matter how fancy an ice cream store is there is always plain vanilla ice cream available there. Just like the same, there are always cases and situations in the Big Data’s story where traditional relational database is the part of the whole story. In the real world scenarios there will be always the case when there will be need of the relational database concepts and its ideology. It is extremely important to accept relational database as one of the key components of the Big Data instead of treating it as a substandard technology. Ray of Hope – NewSQL In this module we discussed that there are places where we need ACID compliance from our Big Data application and NoSQL will not support that out of box. There is a new termed coined for the application/tool which supports most of the properties of the traditional RDBMS and supports Big Data infrastructure – NewSQL. Tomorrow In tomorrow’s blog post we will discuss about NewSQL. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• To sample or not to sample...

  - by [email protected]

  Ideally, we would know the exact answer to every question. How many people support presidential candidate A vs. B? How many people suffer from H1N1 in a given state? Does this batch of manufactured widgets have any defective parts? Knowing exact answers is expensive in terms of time and money and, in most cases, is impractical if not impossible. Consider asking every person in a region for their candidate preference, testing every person with flu symptoms for H1N1 (assuming every person reported when they had flu symptoms), or destructively testing widgets to determine if they are "good" (leaving no product to sell). Knowing exact answers, fortunately, isn't necessary or even useful in many situations. Understanding the direction of a trend or statistically significant results may be sufficient to answer the underlying question: who is likely to win the election, have we likely reached a critical threshold for flu, or is this batch of widgets good enough to ship? Statistics help us to answer these questions with a certain degree of confidence. This focuses on how we collect data. In data mining, we focus on the use of data, that is data that has already been collected. In some cases, we may have all the data (all purchases made by all customers), in others the data may have been collected using sampling (voters, their demographics and candidate choice). Building data mining models on all of your data can be expensive in terms of time and hardware resources. Consider a company with 40 million customers. Do we need to mine all 40 million customers to get useful data mining models? The quality of models built on all data may be no better than models built on a relatively small sample. Determining how much is a reasonable amount of data involves experimentation. When starting the model building process on large datasets, it is often more efficient to begin with a small sample, perhaps 1000 - 10,000 cases (records) depending on the algorithm, source data, and hardware. This allows you to see quickly what issues might arise with choice of algorithm, algorithm settings, data quality, and need for further data preparation. Instead of waiting for a model on a large dataset to build only to find that the results don't meet expectations, once you are satisfied with the results on the initial sample, you can  take a larger sample to see if model quality improves, and to get a sense of how the algorithm scales to the particular dataset. If model accuracy or quality continues to improve, consider increasing the sample size. Sampling in data mining is also used to produce a held-aside or test dataset for assessing classification and regression model accuracy. Here, we reserve some of the build data (data that includes known target values) to be used for an honest estimate of model error using data the model has not seen before. This sampling transformation is often called a split because the build data is split into two randomly selected sets, often with 60% of the records being used for model building and 40% for testing. Sampling must be performed with care, as it can adversely affect model quality and usability. Even a truly random sample doesn't guarantee that all values are represented in a given attribute. This is particularly troublesome when the attribute with omitted values is the target. A predictive model that has not seen any examples for a particular target value can never predict that target value! For other attributes, values may consist of a single value (a constant attribute) or all unique values (an identifier attribute), each of which may be excluded during mining. Values from categorical predictor attributes that didn't appear in the training data are not used when testing or scoring datasets. In subsequent posts, we'll talk about three sampling techniques using Oracle Database: simple random sampling without replacement, stratified sampling, and simple random sampling with replacement.

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• Kipróbálható az ingyenes új Oracle Data Miner 11gR2 grafikus workflow-val

  - by Fekete Zoltán

  Oracle Data Mining technológiai információs oldal. Oracle Data Miner 11g Release 2 - Early Adopter oldal. Megjelent, letöltheto és kipróbálható az Oracle Data Mining, az Oracle adatbányászat új grafikus felülete, az Oracle Data Miner 11gR2. Az Oracle Data Minerhez egyszeruen az SQL Developer-t kell letöltenünk, mivel az adatbányászati felület abból indítható. Az Oracle Data Mining az Oracle adatbáziskezelobe ágyazott adatbányászati motor, ami az Oracle Database Enterprise Edition opciója. Az adatbányászat az adattárházak elemzésének kifinomult eszköze és folyamata. Az Oracle Data Mining in-database-mining elonyeit felvonultatja: - nincs felesleges adatmozgatás, a teljes adatbányászati folyamatban az adatbázisban maradnak az adatok - az adatbányászati modellek is az Oracle adatbázisban vannak - az adatbányászati eredmények, cluster adatok, döntések, valószínuségek, stb. szintén az adatbázisban keletkeznek, és ott közvetlenül elemezhetoek Az új ingyenes Data Miner felület "hatalmas gazdagodáson" ment keresztül az elozo verzióhoz képest. - grafikus adatbányászati workflow szerkesztés és futtatás jelent meg! - továbbra is ingyenes - kibovült a felület - új elemzési lehetoségekkel bovült - az SQL Developer 3.0 felületrol indítható, ez megkönnyíti az adatbányászati funkciók meghívását az adatbázisból, ha épp nem a grafikus felületetet szeretnénk erre használni Az ingyenes Data Miner felület az Oracle SQL Developer kiterjesztéseként érheto el, így az elemzok közvetlenül dolgozhatnak az adatokkal az adatbázisban és a Data Miner grafikus felülettel is, építhetnek és kiértékelhetnek, futtathatnak modelleket, predikciókat tehetnek és elemezhetnek, támogatást kapva az adatbányászati módszertan megvalósítására. A korábbi Oracle Data Miner felület a Data Miner Classic néven fut és továbbra is letöltheto az OTN-rol. Az új Data Miner GUI-ból egy képernyokép: Milyen feladatokra ad megoldási lehetoséget az Oracle Data Mining: - ügyfél viselkedés megjövendölése, prediktálása - a "legjobb" ügyfelek eredményes megcélzása - ügyfél megtartás, elvándorlás kezelés (churn) - ügyfél szegmensek, klaszterek, profilok keresése és vizsgálata - anomáliák, visszaélések felderítése - stb.

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• Spring Data Neo4J @Indexed(unique = true) not working

  - by Markus Lamm

  I'm new to Neo4J and I have, probably an easy question. There're NodeEntitys in my application, a property (name) is annotated with @Indexed(unique = true) to achieve the uniqueness like I do in JPA with @Column(unique = true). My problem is, that when I persist an entity with a name that already exists in my graph, it works fine anyway. But I expected some kind of exception here...?! Here' s an overview over basic my code: @NodeEntity public abstract class BaseEntity implements Identifiable { @GraphId private Long entityId; ... } public class Role extends BaseEntity { @Indexed(unique = true) private String name; ... } public interface RoleRepository extends GraphRepository<Role> { Role findByName(String name); } @Service public class RoleServiceImpl extends BaseEntityServiceImpl<Role> implements { private RoleRepository repository; @Override @Transactional public T save(final T entity) { return getRepository().save(entity); } } And this is my test: @Test public void testNameUniqueIndex() { final List<Role> roles = Lists.newLinkedList(service.findAll()); final String existingName = roles.get(0).getName(); Role newRole = new Role.Builder(existingName).build(); newRole = service.save(newRole); } That's the point where I expect something to go wrong! How can I ensure the uniqueness of a property, without checking it for myself?? THANKS IN ADVANCE FOR ANY IDEAS!! P.S.: I'm using neo4j 1.8.M07, spring-data-neo4j 2.1.0.BUILD-SNAPSHOT and Spring 3.1.2.RELEASE.

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• accessing HttpServletRequest object in Spring WebFlow

  - by user198530

  I am using WebFlow and would like to add the current Locale into the flow. I already have a resolveLocale method that does this with this signature: public Locale resolveLocale (HttpServletRequest request); I would like to add something like this in my WebFlow XML: <on-start> <evaluate expression="localeService.resolveLocale(???)" result="flowScope.locale"/> </on-start> Now, I don't know what to put in the ??? parameter part. Any ideas? Thanks for reading.

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• How to configure Spring Security PasswordComparisonAuthenticator

  - by denlab

  I can bind to an embedded ldap server on my local machine with the following bean: <b:bean id="secondLdapProvider" class="org.springframework.security.ldap.authentication.LdapAuthenticationProvider"> <b:constructor-arg> <b:bean class="org.springframework.security.ldap.authentication.BindAuthenticator"> <b:constructor-arg ref="contextSource" /> <b:property name="userSearch"> <b:bean id="userSearch" class="org.springframework.security.ldap.search.FilterBasedLdapUserSearch"> <b:constructor-arg index="0" value="ou=people"/> <b:constructor-arg index="1" value="(uid={0})"/> <b:constructor-arg index="2" ref="contextSource" /> </b:bean> </b:property> </b:bean> </b:constructor-arg> <b:constructor-arg> <b:bean class="com.company.security.ldap.BookinLdapAuthoritiesPopulator"> </b:bean> </b:constructor-arg> </b:bean> however, when I try to authenticate with a PasswordComparisonAuthenticator it repeatedly fails on a bad credentials event: <b:bean id="ldapAuthProvider" class="org.springframework.security.ldap.authentication.LdapAuthenticationProvider"> <b:constructor-arg> <b:bean class="org.springframework.security.ldap.authentication.PasswordComparisonAuthenticator"> <b:constructor-arg ref="contextSource" /> <b:property name="userDnPatterns"> <b:list> <b:value>uid={0},ou=people</b:value> </b:list> </b:property> </b:bean> </b:constructor-arg> <b:constructor-arg> <b:bean class="com.company.security.ldap.BookinLdapAuthoritiesPopulator"> </b:bean> </b:constructor-arg> </b:bean> Through debugging, I can see that the authenticate method picks up the DN from the ldif file, but then tries to compare the passwords, however, it's using the LdapShaPasswordEncoder (the default one) where the password is stored in plaintext in the file, and this is where the authentication fails. Here's the authentication manager bean referencing the preferred authentication bean: <authentication-manager> <authentication-provider ref="ldapAuthProvider"/> <authentication-provider user-service-ref="userDetailsService"> <password-encoder hash="md5" base64="true"> <salt-source system-wide="secret"/> </password-encoder> </authentication-provider> </authentication-manager> On a side note, whether I set the password-encoder on ldapAuthProvider to plaintext or just leave it blank, doesn't seem to make a difference. Any help would be greatly appreciated. Thanks

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• how to retrive pK using spring security

  - by aditya

  i implement this method of the UserDetailService interface, public UserDetails loadUserByUsername(final String username) throws UsernameNotFoundException, DataAccessException { final EmailCredential userDetails = persistentEmailCredential .getUniqueEmailCredential(username); if (userDetails == null) { throw new UsernameNotFoundException(username + "is not registered"); } final HashSet<GrantedAuthority> authorities = new HashSet<GrantedAuthority>(); authorities.add(new GrantedAuthorityImpl("ROLE_USER")); for (UserRole role:userDetails.getAccount().getRoles()) { authorities.add(new GrantedAuthorityImpl(role.getRole())); } return new User(userDetails.getEmailAddress(), userDetails .getPassword(), true, true, true, true, authorities); } in the security context i do some thing like this <!-- Login Info --> <form-login default-target-url='/dashboard.htm' login-page="/login.htm" authentication-failure-url="/login.htm?authfailed=true" always-use-default-target='false' /> <logout logout-success-url="/login.htm" invalidate-session="true" /> <remember-me user-service-ref="emailAccountService" key="fuellingsport" /> <session-management> <concurrency-control max-sessions="1" /> </session-management> </http> now i want to pop out the Pk of the logged in user, how can i show it in my jsp pages, any idea thanks in advance

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• Spring @RequestMapping and trailing slash problem

  - by Eqbal

  I am trying to map a method in a Controller using the annotation with URI template: @RequestMapping(value="/select/{customerNumber}/{resource}", method=RequestMethod.GET) It appears that this does not get mapped if there is a trailing slash at the end of "resource".

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• Spring annotation mvc - request and response

  - by Eqbal

  I am using annotation based mvc and I am trying to get access to request and response objects using this method declaration in my controller. @RequestMapping(method=RequestMethod.GET) public String checkRequest(Model model, HttpServletRequest request, HttpServletResponse response) But I get an error saying GET method not supported. I need the request and response to pass it to another API call.

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• Getting rejected value null spring validation

  - by Shabarinath

  Hi in my project when I am trying to validate my form its not showing any error messages even if validation fails (Event Form is not submitted and enters into validation fail block) Here is my code /****************** Post Method *************/ @RequestMapping(value="/property", method = RequestMethod.POST) public String saveOrUpdateProperty(@ModelAttribute("property") Property property, BindingResult result, Model model, HttpServletRequest request) throws Exception { try { if(validateFormData(property, result)) { model.addAttribute("property", new Property()); return "property/postProperty"; } } /********* Validate Block *************/ private boolean validateFormData(Property property, BindingResult result) throws DaoException { if (property.getPropertyType() == null || property.getPropertyType().equals("")) { result.rejectValue("propertyType", "Cannot Be Empty !", "Cannot Be Empty !"); } if (property.getTitle() == null || property.getTitle().equals("")) { result.rejectValue("title", "Cannot Be Empty !", "Cannot Be Empty !"); } return (result.hasFieldErrors() || result.hasErrors()); } But when i debug i can see below one org.springframework.validation.BeanPropertyBindingResult: 1 errors Field error in object 'property' on field 'title': rejected value [null]; codes [Cannot Be Empty !.property.title,Cannot Be Empty !.title,Cannot Be Empty !.java.lang.String,Cannot Be Empty !]; arguments []; default message [Cannot Be Empty !] and this is how i am displaying in jsp file <div class="control-group"> <div class="controls"> <label class="control-label"><span class="required">* </span>Property Type</label> <div class="controls"> <form:input path="title" placeholder="Pin Code" cssClass="form-control border-radius-4 textField"/> <form:errors path="title" style="color:red;"/> </div> </div> </div> Event though when i see the below one when i debug (1 Error its correct) org.springframework.validation.BeanPropertyBindingResult: 1 errors Why it is not displayed in jsp can any one hep me?

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• Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the Cloud in the Big Data Story. In this article we will understand the role of Operational Databases Supporting Big Data Story. Even though we keep on talking about Big Data architecture, it is extremely crucial to understand that Big Data system can’t just exist in the isolation of itself. There are many needs of the business can only be fully filled with the help of the operational databases. Just having a system which can analysis big data may not solve every single data problem. Real World Example Think about this way, you are using Facebook and you have just updated your information about the current relationship status. In the next few seconds the same information is also reflected in the timeline of your partner as well as a few of the immediate friends. After a while you will notice that the same information is now also available to your remote friends. Later on when someone searches for all the relationship changes with their friends your change of the relationship will also show up in the same list. Now here is the question – do you think Big Data architecture is doing every single of these changes? Do you think that the immediate reflection of your relationship changes with your family member is also because of the technology used in Big Data. Actually the answer is Facebook uses MySQL to do various updates in the timeline as well as various events we do on their homepage. It is really difficult to part from the operational databases in any real world business. Now we will see a few of the examples of the operational databases. Relational Databases (This blog post) NoSQL Databases (This blog post) Key-Value Pair Databases (Tomorrow’s post) Document Databases (Tomorrow’s post) Columnar Databases (The Day After’s post) Graph Databases (The Day After’s post) Spatial Databases (The Day After’s post) Relational Databases We have earlier discussed about the RDBMS role in the Big Data’s story in detail so we will not cover it extensively over here. Relational Database is pretty much everywhere in most of the businesses which are here for many years. The importance and existence of the relational database are always going to be there as long as there are meaningful structured data around. There are many different kinds of relational databases for example Oracle, SQL Server, MySQL and many others. If you are looking for Open Source and widely accepted database, I suggest to try MySQL as that has been very popular in the last few years. I also suggest you to try out PostgreSQL as well. Besides many other essential qualities PostgreeSQL have very interesting licensing policies. PostgreSQL licenses allow modifications and distribution of the application in open or closed (source) form. One can make any modifications and can keep it private as well as well contribute to the community. I believe this one quality makes it much more interesting to use as well it will play very important role in future. Nonrelational Databases (NOSQL) We have also covered Nonrelational Dabases in earlier blog posts. NoSQL actually stands for Not Only SQL Databases. There are plenty of NoSQL databases out in the market and selecting the right one is always very challenging. Here are few of the properties which are very essential to consider when selecting the right NoSQL database for operational purpose. Data and Query Model Persistence of Data and Design Eventual Consistency Scalability Though above all of the properties are interesting to have in any NoSQL database but the one which most attracts to me is Eventual Consistency. Eventual Consistency RDBMS uses ACID (Atomicity, Consistency, Isolation, Durability) as a key mechanism for ensuring the data consistency, whereas NonRelational DBMS uses BASE for the same purpose. Base stands for Basically Available, Soft state and Eventual consistency. Eventual consistency is widely deployed in distributed systems. It is a consistency model used in distributed computing which expects unexpected often. In large distributed system, there are always various nodes joining and various nodes being removed as they are often using commodity servers. This happens either intentionally or accidentally. Even though one or more nodes are down, it is expected that entire system still functions normally. Applications should be able to do various updates as well as retrieval of the data successfully without any issue. Additionally, this also means that system is expected to return the same updated data anytime from all the functioning nodes. Irrespective of when any node is joining the system, if it is marked to hold some data it should contain the same updated data eventually. As per Wikipedia - Eventual consistency is a consistency model used in distributed computing that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value. In other words -  Informally, if no additional updates are made to a given data item, all reads to that item will eventually return the same value. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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