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• Big Data&rsquo;s Killer App&hellip;

  - by jean-pierre.dijcks

  Recently Keith spent  some time talking about the cloud on this blog and I will spare you my thoughts on the whole thing. What I do want to write down is something about the Big Data movement and what I think is the killer app for Big Data... Where is this coming from, ok, I confess... I spent 3 days in cloud land at the Cloud Connect conference in Santa Clara and it was quite a lot of fun. One of the nice things at Cloud Connect was that there was a track dedicated to Big Data, which prompted me to some extend to write this post. What is Big Data anyways? The most valuable point made in the Big Data track was that Big Data in itself is not very cool. Doing something with Big Data is what makes all of this cool and interesting to a business user! The other good insight I got was that a lot of people think Big Data means a single gigantic monolithic system holding gazillions of bytes or documents or log files. Well turns out that most people in the Big Data track are talking about a lot of collections of smaller data sets. So rather than thinking "big = monolithic" you should be thinking "big = many data sets". This is more than just theoretical, it is actually relevant when thinking about big data and how to process it. It is important because it means that the platform that stores data will most likely consist out of multiple solutions. You may be storing logs on something like HDFS, you may store your customer information in Oracle and you may store distilled clickstream information in some distilled form in MySQL. The big question you will need to solve is not what lives where, but how to get it all together and get some value out of all that data. NoSQL and MapReduce Nope, sorry, this is not the killer app... and no I'm not saying this because my business card says Oracle and I'm therefore biased. I think language is important, but as with storage I think pragmatic is better. In other words, some questions can be answered with SQL very efficiently, others can be answered with PERL or TCL others with MR. History should teach us that anyone trying to solve a problem will use any and all tools around. For example, most data warehouses (Big Data 1.0?) get a lot of data in flat files. Everyone then runs a bunch of shell scripts to massage or verify those files and then shoves those files into the database. We've even built shell script support into external tables to allow for this. I think the Big Data projects will do the same. Some people will use MapReduce, although I would argue that things like Cascading are more interesting, some people will use Java. Some data is stored on HDFS making Cascading the way to go, some data is stored in Oracle and SQL does do a good job there. As with storage and with history, be pragmatic and use what fits and neither NoSQL nor MR will be the one and only. Also, a language, while important, does in itself not deliver business value. So while cool it is not a killer app... Vertical Behavioral Analytics This is the killer app! And you are now thinking: "what does that mean?" Let's decompose that heading. First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after collecting large volumes of specific data. That all important data is about behavior. What do my customers do? More importantly why do they behave like that? If you can figure that out, you can tailor web sites, stores, products etc. to that behavior and figure out how to be successful. Today's behavior that is somewhat easily tracked is web site clicks, search patterns and all of those things that a web site or web server tracks. that is where the Big Data lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about prediction churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who calls whom. I call you a lot, you switch provider, and I might/will switch too. And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical. The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example). But the gist of it all is that analytics that can predict customer behavior for a specific focused group of people in a specific industry is what makes Big Data interesting. Building a Vertical Behavioral Analysis System Well, that is going to be interesting. I have not seen much going on in that space and if I had to have some criticism on the cloud connect conference it would be the lack of concrete user cases on big data. The telco example, while a step into the vertical behavioral part is not really on big data. It used a sample of data from the customers' data warehouse. One thing I do think, and this is where I think parts of the NoSQL stuff come from, is that we will be doing this analysis where the data is. Over the past 10 years we at Oracle have called this in-database analytics. I guess we were (too) early? Now the entire market is going there including companies like SAS. In-place btw does not mean "no data movement at all", what it means that you will do this on data's permanent home. For SAS that is kind of the current problem. Most of the inputs live in a data warehouse. So why move it into SAS and back? That all worked with 1 TB data warehouses, but when we are looking at 100TB to 500 TB of distilled data... Comments? As it is still early days with these systems, I'm very interested in seeing reactions and thoughts to some of these thoughts...

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• Accelerate your SOA with Data Integration - Live Webinar Tuesday!

  - by dain.hansen

  Need to put wind in your SOA sails? Organizations are turning more and more to Real-time data integration to complement their Service Oriented Architecture. The benefit? Lowering costs through consolidating legacy systems, reducing risk of bad data polluting their applications, and shortening the time to deliver new service offerings. Join us on Tuesday April 13th, 11AM PST for our live webinar on the value of combining SOA and Data Integration together. In this webcast you'll learn how to innovate across your applications swiftly and at a lower cost using Oracle Data Integration technologies: Oracle Data Integrator Enterprise Edition, Oracle GoldenGate, and Oracle Data Quality. You'll also hear: Best practices for building re-usable data services that are high performing and scalable across the enterprise How real-time data integration can maximize SOA returns while providing continuous availability for your mission critical applications Architectural approaches to speed service implementation and delivery times, with pre-integrations to CRM, ERP, BI, and other packaged applications Register now for this live webinar!

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• Prevent Cross-Site Request Forgery in a Spring WebFlow Application

  - by Eric J.

  I'm looking for a (hopefully straightforward) way to add CSRF protection to an application build on Spring WebFlow 2. An approach that migrates well to Spring WebFlow 3 (when released) is preferred.

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• Howcan I get started with Spring Batch?

  - by C. Ross

  I'm trying to learn Spring Batch, but the startup guide is very confusing. Comments like You can get a pretty good idea about how to set up a job by examining the unit tests in the org.springframework.batch.sample package (in src/main/java) and the configuration in src/main/resources/jobs. aren't exactly helpful. Also I find the Sample project very complicated (17 non-empty Namespaces with 109 classes)! Is there a simpler place to get started with Spring Batch?

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• Can i use Spring on GAE?

  - by n002213f

  Can i use Spring Webflow/MVC and Spring Security and Hibernate on Google App Engine? Is there a list/summary of java frameworks that can be used on the GAE?

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• What are annotations and how do they actually work for frameworks like Spring?

  - by Rachel

  I am new to Spring and now a days I hear a lot about Spring Framework. I have two sets of very specific questions: Set No. 1: What are annotations in general ? How does annotations works specifically with Spring framework ? Can annotations be used outside Spring Framework or are they Framework specific ? Set No. 2: What module of Spring Framework is widely used in Industry ? I think it is Spring MVC but why it is the most used module, if am correct or correct me on this ? I am newbie to Spring and so feel free to edit this questions to make more sense.

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• What is annotations and how do it actually works for frameworks like Spring ?

  - by Rachel

  I am new to Spring and now a days I hear a lot about Spring Framework. I have two sets of very specific questions: Set No. 1: What are annotations in general ? How does annotations works specifically with Spring framework ? Can annotations be used outside Spring Framework or are they Framework specific ? Set No. 2: What module of Spring Framework is widely used in Industry ? I think it is Spring MVC but why it is the most used module, if am correct or correct me on this ? I am newbie to Spring and so feel free to edit this questions to make more sense.

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• Big Data – Basics of Big Data Analytics – Day 18 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the various components in Big Data Story. In this article we will understand what are the various analytics tasks we try to achieve with the Big Data and the list of the important tools in Big Data Story. When you have plenty of the data around you what is the first thing which comes to your mind? “What do all these data means?” Exactly – the same thought comes to my mind as well. I always wanted to know what all the data means and what meaningful information I can receive out of it. Most of the Big Data projects are built to retrieve various intelligence all this data contains within it. Let us take example of Facebook. When I look at my friends list of Facebook, I always want to ask many questions such as - On which date my maximum friends have a birthday? What is the most favorite film of my most of the friends so I can talk about it and engage them? What is the most liked placed to travel my friends? Which is the most disliked cousin for my friends in India and USA so when they travel, I do not take them there. There are many more questions I can think of. This illustrates that how important it is to have analysis of Big Data. Here are few of the kind of analysis listed which you can use with Big Data. Slicing and Dicing: This means breaking down your data into smaller set and understanding them one set at a time. This also helps to present various information in a variety of different user digestible ways. For example if you have data related to movies, you can use different slide and dice data in various formats like actors, movie length etc. Real Time Monitoring: This is very crucial in social media when there are any events happening and you wanted to measure the impact at the time when the event is happening. For example, if you are using twitter when there is a football match, you can watch what fans are talking about football match on twitter when the event is happening. Anomaly Predication and Modeling: If the business is running normal it is alright but if there are signs of trouble, everyone wants to know them early on the hand. Big Data analysis of various patterns can be very much helpful to predict future. Though it may not be always accurate but certain hints and signals can be very helpful. For example, lots of data can help conclude that if there is lots of rain it can increase the sell of umbrella. Text and Unstructured Data Analysis: unstructured data are now getting norm in the new world and they are a big part of the Big Data revolution. It is very important that we Extract, Transform and Load the unstructured data and make meaningful data out of it. For example, analysis of lots of images, one can predict that people like to use certain colors in certain months in their cloths. Big Data Analytics Solutions There are many different Big Data Analystics Solutions out in the market. It is impossible to list all of them so I will list a few of them over here. Tableau – This has to be one of the most popular visualization tools out in the big data market. SAS – A high performance analytics and infrastructure company IBM and Oracle – They have a range of tools for Big Data Analysis Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Data Scientist. 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 @PostConstruct function in a @Repository called multiple times

  - by Seth

  I have a DAO that I'm trying to inject into a couple different places: @Repository public class FooDAO { @Autowired private HibernateManager sessionFactory; @PostConstruct public void doSomeDatabaseStuff() throws DataAccessException { ... } } And my application-context.xml is a fairly simple context:component-scan: <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-2.0.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-2.5.xsd" default-init-method="init" default-destroy-method="destroy"> <context:component-scan base-package="top.level"/> </beans> The DAO is accessed from a couple servlets in my application server through @Autowired properties. As far as I understand, anything annotated with @Repository should default to being a singleton and thus doSomeDatabaseStuff() should only be called once (as is my intention). The problem is that I'm seeing doSomeDatabaseStuff() called multiple times. What's going on here? Have I set something up incorrectly? I'm using spring 3.0.0. Thanks for the help.

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• Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21

  - by Pinal Dave

  Data is forever. Think about it – it is indeed true. Are you using any application as it is which was built 10 years ago? Are you using any piece of hardware which was built 10 years ago? The answer is most certainly No. However, if I ask you – are you using any data which were captured 50 years ago, the answer is most certainly Yes. For example, look at the history of our nation. I am from India and we have documented history which goes back as over 1000s of year. Well, just look at our birthday data – atleast we are using it till today. Data never gets old and it is going to stay there forever.  Application which interprets and analysis data got changed but the data remained in its purest format in most cases. As organizations have grown the data associated with them also grew exponentially and today there are lots of complexity to their data. Most of the big organizations have data in multiple applications and in different formats. The data is also spread out so much that it is hard to categorize with a single algorithm or logic. The mobile revolution which we are experimenting right now has completely changed how we capture the data and build intelligent systems.  Big organizations are indeed facing challenges to keep all the data on a platform which give them a  single consistent view of their data. This unique challenge to make sense of all the data coming in from different sources and deriving the useful actionable information out of is the revolution Big Data world is facing. Defining Big Data The 3Vs that define Big Data are Variety, Velocity and Volume. Volume We currently see the exponential growth in the data storage as the data is now more than text data. We can find data in the format of videos, musics and large images on our social media channels. It is very common to have Terabytes and Petabytes of the storage system for enterprises. As the database grows the applications and architecture built to support the data needs to be reevaluated quite often. Sometimes the same data is re-evaluated with multiple angles and even though the original data is the same the new found intelligence creates explosion of the data. The big volume indeed represents Big Data. Velocity The data growth and social media explosion have changed how we look at the data. There was a time when we used to believe that data of yesterday is recent. The matter of the fact newspapers is still following that logic. However, news channels and radios have changed how fast we receive the news. Today, people reply on social media to update them with the latest happening. On social media sometimes a few seconds old messages (a tweet, status updates etc.) is not something interests users. They often discard old messages and pay attention to recent updates. The data movement is now almost real time and the update window has reduced to fractions of the seconds. This high velocity data represent Big Data. Variety Data can be stored in multiple format. For example database, excel, csv, access or for the matter of the fact, it can be stored in a simple text file. Sometimes the data is not even in the traditional format as we assume, it may be in the form of video, SMS, pdf or something we might have not thought about it. It is the need of the organization to arrange it and make it meaningful. It will be easy to do so if we have data in the same format, however it is not the case most of the time. The real world have data in many different formats and that is the challenge we need to overcome with the Big Data. This variety of the data represent  represent Big Data. Big Data in Simple Words Big Data is not just about lots of data, it is actually a concept providing an opportunity to find new insight into your existing data as well guidelines to capture and analysis your future data. It makes any business more agile and robust so it can adapt and overcome business challenges. Tomorrow In tomorrow’s blog post we will try to answer discuss Evolution of 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 - Reach users ID without passing it through every controller

  - by nilsi

  I have a design issue that I don't know how to solve. I'm using Spring 3.2.4 and Spring security 3.1.4. I have a Account table in my database that looks like this: create table Account (id identity, username varchar unique, password varchar not null, firstName varchar not null, lastName varchar not null, university varchar not null, primary key (id)); Until recently my username was just only a username but I changed it to be the email address instead since many users want to login with that instead. I have a header that I include on all my pages which got a link to the users profile like this: <a href="/project/users/<%= request.getUserPrincipal().getName()%>" class="navbar-link"><strong><%= request.getUserPrincipal().getName()%></strong></a> The problem is that <%= request.getUserPrincipal().getName()%> returns the email now, I don't want to link the user's with thier emails. Instead I want to use the id every user have to link to the profile. How do I reach the users id's from every page? I have been thinking of two solutions but I'm not sure: Change the principal to contain the id as well, don't know how to do this and having problem finding good information on the topic. Add a model attribute to all my controllers that contain the whole user but this would be really ugly, like this. Account account = entityManager.find(Account.class, email); model.addAttribute("account", account); There are more way's as well and I have no clue which one is to prefer. I hope it's clear enough and thank you for any help on this. ====== Edit according to answer ======= I edited Account to implement UserDetails, it now looks like this (will fix the auto generated stuff later): @Entity @Table(name="Account") public class Account implements UserDetails { @Id private int id; private String username; private String password; private String firstName; private String lastName; @ManyToOne private University university; public Account() { } public Account(String username, String password, String firstName, String lastName, University university) { this.username = username; this.password = password; this.firstName = firstName; this.lastName = lastName; this.university = university; } public String getUsername() { return username; } public String getPassword() { return password; } public String getFirstName() { return firstName; } public String getLastName() { return lastName; } public void setUsername(String username) { this.username = username; } public void setPassword(String password) { this.password = password; } public void setFirstName(String firstName) { this.firstName = firstName; } public void setLastName(String lastName) { this.lastName = lastName; } public University getUniversity() { return university; } public void setUniversity(University university) { this.university = university; } public int getId() { return id; } public void setId(int id) { this.id = id; } @Override public Collection<? extends GrantedAuthority> getAuthorities() { // TODO Auto-generated method stub return null; } @Override public boolean isAccountNonExpired() { // TODO Auto-generated method stub return false; } @Override public boolean isAccountNonLocked() { // TODO Auto-generated method stub return false; } @Override public boolean isCredentialsNonExpired() { // TODO Auto-generated method stub return false; } @Override public boolean isEnabled() { // TODO Auto-generated method stub return true; } } I also added <%@ taglib prefix="sec" uri="http://www.springframework.org/security/tags" %> To my jsp files and trying to reach the id by <sec:authentication property="principal.id" /> This gives me the following org.springframework.beans.NotReadablePropertyException: Invalid property 'principal.id' of bean class [org.springframework.security.authentication.UsernamePasswordAuthenticationToken]: Bean property 'principal.id' is not readable or has an invalid getter method: Does the return type of the getter match the parameter type of the setter? ====== Edit 2 according to answer ======= I based my application on spring social samples and I never had to change anything until now. This are the files I think are relevant, please tell me if theres something you need to see besides this. AccountRepository.java public interface AccountRepository { void createAccount(Account account) throws UsernameAlreadyInUseException; Account findAccountByUsername(String username); } JdbcAccountRepository.java @Repository public class JdbcAccountRepository implements AccountRepository { private final JdbcTemplate jdbcTemplate; private final PasswordEncoder passwordEncoder; @Inject public JdbcAccountRepository(JdbcTemplate jdbcTemplate, PasswordEncoder passwordEncoder) { this.jdbcTemplate = jdbcTemplate; this.passwordEncoder = passwordEncoder; } @Transactional public void createAccount(Account user) throws UsernameAlreadyInUseException { try { jdbcTemplate.update( "insert into Account (firstName, lastName, username, university, password) values (?, ?, ?, ?, ?)", user.getFirstName(), user.getLastName(), user.getUsername(), user.getUniversity(), passwordEncoder.encode(user.getPassword())); } catch (DuplicateKeyException e) { throw new UsernameAlreadyInUseException(user.getUsername()); } } public Account findAccountByUsername(String username) { return jdbcTemplate.queryForObject("select username, firstName, lastName, university from Account where username = ?", new RowMapper<Account>() { public Account mapRow(ResultSet rs, int rowNum) throws SQLException { return new Account(rs.getString("username"), null, rs.getString("firstName"), rs.getString("lastName"), new University("test")); } }, username); } } security.xml <?xml version="1.0" encoding="UTF-8"?> <beans:beans xmlns="http://www.springframework.org/schema/security" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:beans="http://www.springframework.org/schema/beans" xsi:schemaLocation="http://www.springframework.org/schema/security http://www.springframework.org/schema/security/spring-security-3.1.xsd http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.1.xsd"> <http pattern="/resources/**" security="none" /> <http pattern="/project/" security="none" /> <http use-expressions="true"> <!-- Authentication policy --> <form-login login-page="/signin" login-processing-url="/signin/authenticate" authentication-failure-url="/signin?error=bad_credentials" /> <logout logout-url="/signout" delete-cookies="JSESSIONID" /> <intercept-url pattern="/addcourse" access="isAuthenticated()" /> <intercept-url pattern="/courses/**/**/edit" access="isAuthenticated()" /> <intercept-url pattern="/users/**/edit" access="isAuthenticated()" /> </http> <authentication-manager alias="authenticationManager"> <authentication-provider> <password-encoder ref="passwordEncoder" /> <jdbc-user-service data-source-ref="dataSource" users-by-username-query="select username, password, true from Account where username = ?" authorities-by-username-query="select username, 'ROLE_USER' from Account where username = ?"/> </authentication-provider> <authentication-provider> <user-service> <user name="admin" password="admin" authorities="ROLE_USER, ROLE_ADMIN" /> </user-service> </authentication-provider> </authentication-manager> </beans:beans> And this is my try of implementing a UserDetailsService public class RepositoryUserDetailsService implements UserDetailsService { private final AccountRepository accountRepository; @Autowired public RepositoryUserDetailsService(AccountRepository repository) { this.accountRepository = repository; } @Override public UserDetails loadUserByUsername(String username) throws UsernameNotFoundException { Account user = accountRepository.findAccountByUsername(username); if (user == null) { throw new UsernameNotFoundException("No user found with username: " + username); } return user; } } Still gives me the same error, do I need to add the UserDetailsService somewhere? This is starting to be something else compared to my initial question, I should maybe start another question. Sorry for my lack of experience in this. I have to read up.

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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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• Setting up MongoDB in High Performance Computing LSF linux cluster

  - by Dnaiel

  I am trying to run mongo in a LSF cluster computing environment where I have no admin control. Our sysadmin installed mongodb, but it is not running. Any ideas on what should I ask the server admin to do for it to run? Or if I could run it locally? [node1382]allelix> mongod --dbpath /users/dnaiel/ma/mongodb/ Tue Oct 2 21:33:48 [initandlisten] MongoDB starting : pid=22436 port=27017 dbpath=/seq/epigenome01/allelix/ma/mongodb/ 64-bit host=node1382 Tue Oct 2 21:33:48 [initandlisten] Tue Oct 2 21:33:48 [initandlisten] ** WARNING: You are running on a NUMA machine. Tue Oct 2 21:33:48 [initandlisten] ** We suggest launching mongod like this to avoid performance problems: Tue Oct 2 21:33:48 [initandlisten] ** numactl --interleave=all mongod [other options] Tue Oct 2 21:33:48 [initandlisten] Tue Oct 2 21:33:48 [initandlisten] db version v2.2.0, pdfile version 4.5 Tue Oct 2 21:33:48 [initandlisten] git version: f5e83eae9cfbec7fb7a071321928f00d1b0c5207 Tue Oct 2 21:33:48 [initandlisten] build info: Linux ip-10-2-29-40 2.6.21.7-2.ec2.v1.2.fc8xen #1 SMP Fri Nov 20 17:48:28 EST 2009 x86_64 BOOST_LIB_VERSION=1_49 Tue Oct 2 21:33:48 [initandlisten] options: { dbpath: "/users/dnaiel/ma/mongodb/" } Tue Oct 2 21:33:48 [initandlisten] journal dir=users/dnaiel/ma/mongodb/journal Tue Oct 2 21:33:48 [initandlisten] recover begin Tue Oct 2 21:33:48 [initandlisten] info no lsn file in journal/ directory Tue Oct 2 21:33:48 [initandlisten] recover lsn: 0 Tue Oct 2 21:33:48 [initandlisten] recover /seq/epigenome01/allelix/ma/mongodb/journal/j._0 Tue Oct 2 21:33:48 [initandlisten] recover cleaning up Tue Oct 2 21:33:48 [initandlisten] removeJournalFiles Tue Oct 2 21:33:48 [initandlisten] recover done Tue Oct 2 21:33:48 [websvr] admin web console waiting for connections on port 28017 Tue Oct 2 21:33:48 [initandlisten] waiting for connections on port 27017 It basically waits forever and cannot start mongodb. These servers are not webservers but they do have network access, it's a cloud computing LSF environment system. Any advice would be welcome, thanks in advance.

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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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