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The Latest Integration Topics

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Building Microservices: Inter-Process Communication in a Microservices Architecture
In this article, learn how the different services within a system communicate with one another.
August 20, 2015
by Patrick Nommensen
· 27,517 Views · 8 Likes
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Designing REST APIs: Intent API Pattern
Learn more about the design and implementation of REST APIs, especially higher level APIs called Intent APIs.
August 19, 2015
by Chase Seibert
· 13,324 Views · 1 Like
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Spring Boot Example of Spring Integration and ActiveMQ
Learn to use Spring Boot to setup a Hello World example using Spring Integration and ActiveMQ.
August 19, 2015
by John Thompson
· 70,150 Views · 9 Likes
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Komodo 9.2 Released: Docker & Vagrant Integration, Package Installer, and More
The 9.2 release of Komodo IDE is live and includes new features such as Docker and Vagrant integration, collaboration improvements, a package installer, and UI changes.
August 10, 2015
by Kathy Thomas
· 1,662 Views · 2 Likes
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You Should Use JAXB Generated Classes for RESTful Web Services
Learn how to build RESTful web services in Spring that can utilize either JSON or XML.
August 10, 2015
by John Thompson
· 13,302 Views · 5 Likes
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How and Why to Serialize Lambdas
Serializing lambdas can be useful in a number of use cases such as persisting configuration, or as a visitor pattern to remote resources.
July 27, 2015
by Peter Lawrey
· 33,793 Views · 7 Likes
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RESTful Considered Harmful
RESTful APIs are common across the internet, but is this a good thing?
July 25, 2015
by Tomasz Nurkiewicz
· 68,591 Views · 31 Likes
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Solving "EJB Timer Service Not Available" Error in Glassfish Application Server
If you've encountered an EJB timer service error in Glassfish, Sam Sepassi explains how deleting a marker file may solve the issue.
July 23, 2015
by Sam Sepassi
· 26,462 Views · 1 Like
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Publishing Domain Events with Spring Integration EventBus
How to use Spring Integration to keep domain and integration concerns separate and simple for many Spring-based applications.
July 19, 2015
by Muhammad Noor
· 23,210 Views · 6 Likes
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JAX-RS and HTTP ‘OPTIONS’
The JAX-RS specification defines sensible defaults for the HTTP OPTIONS command. I actually stumbled upon this by chance!
July 13, 2015
by Abhishek Gupta DZone Core CORE
· 7,446 Views · 2 Likes
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Where Am I? Collecting GPS Data With Apache Camel
In this article I will tell you how Apache Camel can turn a full-stack Linux microcomputer (like Raspberry Pi) into a device collecting the GPS coordinates.
July 8, 2015
by Henryk Konsek
· 5,808 Views · 1 Like
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Microservices Design Principles
Get a crash course in understanding microservices and the difficulties in implementing them.
July 5, 2015
by Saravanan Subramanian
· 62,591 Views · 10 Likes
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Using Camel, CDI Inside Kubernetes With Fabric8
Learn about how to integrate Apache Camel and Fabric8 into an existing Kubernetes CDI service.
July 2, 2015
by Ioannis Canellos
· 19,743 Views · 1 Like
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Microservices = Death of the Enterprise Service Bus (ESB)? – Slide Deck and Video Recording
In 2015, the middleware world focuses on two buzzwords: Docker and Microservices. Software vendors still sell products such as an Enterprise Service Bus (ESB) or Complex Event Processing (CEP) engines. How is this related? Docker is a fascinating technology to deploy and distribute modules (middleware, applications, services) quickly and easily. Most people agree that Docker will change the future of software development in the next years. I will do another blog post about how Docker is related to TIBCO and how you can deploy and distribute Microservices with Docker and TIBCO products such as TIBCO EMS and BusinessWorks 6 easily. Microservices is NOT a technology, but a software architecture style. Many people say that Microservices kill the Enterprise Service Bus (ESB) because Microservices use smart endpoints and dumb pipes. I had a talk at the Microservices Meetup in Munich in June 2015. Most attendees were surprised, why TIBCO shall be relevant for Microservices. I heard that question in several customer meetings, too. This was the main motivation for this talk. I want to share the slide deck and video recording of the talk with you… Abstract: Why use TIBCO for Microservices? Microservices are the next step after SOA: Services implement a limited set of functions. Services are developed, deployed and scaled independently. Continuous Integration and Continuous Delivery control deployments. This way you get shorter time to results and increased flexibility. Microservices have to be independent regarding build, deployment, data management and business domains. A solid Microservices design requires single responsibility, loose coupling and a decentralized architecture. A Microservice can to be closed or open to partners and public via APIs. This session discusses the requirements, best practices and challenges for creating a good Microservices architecture, and if this spells the end of the Enterprise Service Bus (ESB). Key messages of the talk: Microservices = SOA done right Integration is key for success – the product name does not matter Real time event correlation is the game changer Slide Deck from Microservices Meetup in Munich, Germany Here is the slide deck: Microservices = Death of the Enterprise Service Bus (ESB)? from Kai Wähner Video Recording on Youtube The session was recorded (thanks to the guys from AutoScout24). Here is the Youtube upload: https://youtu.be/wMDHUTmUsKg Looking forward to your feedback… Is the ESB dead or not? If no, what kind of ESB (or better said in 2015: Service Delivery Platform) do you use? If yes, how to you implement “ESB features” in your projects? “Simple” REST services and server-code under the hood, or how else?
July 2, 2015
by Kai Wähner DZone Core CORE
· 6,054 Views · 3 Likes
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Captains with Benefits
When it comes to teaching or learning, video streaming is something that still frightens people away. As a matter of fact that video chats and webinars have been around for a relatively long time, however; its still hard to encourage an individual or business to take part as such. And yet the benefits of CaptainLive can be substantial in both, short as well as long term. As we have already seen the benefits of video marketing therefore, we want to encourage you to use CaptainLive in order to take advantage of your potential whether it’s hidden in you or you are well aware of it. CaptainLive was launched in early 2015 with a mission to connect people in need of knowledge and skills with Captains with Benefits that are willing to share and give their expertise and mentor skills. CaptainLive’s integrated service now allows for text, video and audio conferencing. It’s been used by a variety of individuals with different backgrounds. At CaptainLive you can schedule an online live video stream with the experts in number topics ranging from counseling up to entertainment. Captains/Experts on the site charges from $5 USD up to $150 USD, most of which offer free 5 minute sessions with no obligation to book their session thereafter. Who knows you might end up registering as Captain yourself and start a part time business of your own to help others with your skills while making a healthy stream of income for yourself, it’s surely well worth your effort.
July 1, 2015
by Peter Watson
· 888 Views
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Choosing the Right SaaS for Your Business
In recent years, SaaS has become a popular delivery model for a wide range of business applications. Also known as on-demand software, because of the anytime, anywhere nature of Software as a Service, it’s easy to see why it has become so popular. Once you’ve decided you want to take the Software as a Service approach, you need to decide which SaaS solution you’re going to choose. Read on as we discuss the questions you should be asking your Software as a Service provider before signing up with them. How much does SaaS cost? Cost is likely to be your first question when considering Software as a Service, as you need to ensure that it fits within your budget. Software as a Service business intelligence costs less than traditional software packages, as there are limited or no upfront investments or overpriced license fees. Pricing for Software as a Service is typically based on measure of usage or by subscription. When choosing your SaaS provider, we suggest you look for any hidden usage charges to confirm that the costs of their service are transparent. Does a SaaS solution fit with your requirements? The platform you choose for your Software as a Service should solve your problems and help you to achieve your business objectives without disrupting the internal processes. The user interfaces of your SaaS software should be suitable for your team to utilize effectively. Does the provider’s software solve your key problems? Before purchasing your SaaS application, the provider should offer you an in-depth demo of the software to ensure that you can fully utilize it. Use this demo as an opportunity to discuss your problems with the demonstrator and make sure that they show you exactly how the software can help. If it can’t, it isn’t right for you. Does the provider offer training? One of the main problems with software purchased on a one-off basis is that you can be left with very limited support and training as to how to use the software. As a SaaS provider has a vested interest in you continually using the product, they should offer comprehensive support and training, including tutorials of how the software works so you and your team can feel confident using it. Make sure to ask about the training schemes and support available when signing up though, it will be an important part of your whole team adopting the system. Does the provider offer account management and system support? When implementing a SaaS application, the provider should give you best practice examples to follow to ensure your software operates efficiently. It’s also important that you know your provider will be on hand to ensure that you get the maximum value from the platform once it’s been implemented. This is also critical for resolving any conflicts or problems with Software as a Service. You should always check that your provider covers your hours of business so they are on hand to offer system support at all times, should you ever need it. How does SaaS compare to other providers? How does the service your Software as a Service provider offers meet peaks in demand for the service? Does the platform perform consistently when there are multiple users accessing it? Ask each provider about their page load times and response times, as this will allow you to collect and compare the performance of different SaaS providers. Ask about the security measures of the platform and how often the software is tested to check for vulnerabilities. Ultimately, SaaS solutions should put you in a better position to analyze your business intelligence and make better informed business decisions. The platform you choose should be the best fit for your own business model taking into account business goals, budget and usability. Learn more about finding the ideal SaaS solution for you at sales-i.
July 1, 2015
by Chris Bourne
· 8,931 Views
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Restify Commands with the Request Pattern
REST is all the rage. It provides a networked approach to exposing data and services, both internally within a company and to partners. Here, we explore a novel approach to providing a RESTful API to a set of existing commands. Business Problem: expose Commands via REST Many organizations have made considerable software available through Unix-like commands. Imagine an Enterprise, well, the Enterprise, that wishes to provide RESTful APIs to commands like: OrderSickLeave , IncreaseSpeed , SelfDestruct … hundreds of them… Each of these commands is backed by some software, say a Java Class of some sort. They’d like to publish this functionality, as follows: Restify – provide a RESTful API for each command. The REST attributes are the command arguments, above Validate – before the commands is issued, validate the arguments (does exist, is the a positive number, etc) Secure – ensure the commands are available as appropriate Background: Espresso creates RESTful API for SQL data Espresso creates RESTful APIs, principally for SQL data. Some key functionality is described below. API Creation You connect Espresso to a database, and it creates a RESTful endpoint for each table, view and Stored Procedure. The API supports the usual RESTful operations of Get (including filters based on HTTP arguments), and update (Put, Post and Delete). Validation Rules You can specify validation rule expressions that are automatically executed on update requests. For example, you might specify a rule that balance <= creditLimit. Validation rules are part of the larger notion of business logic, which includes computations (the balance is the sum of the unpaid order amounts). Computations can chain, and validations work over computed data, so you can solve remarkably complicated problems with a few simple rules. Extensibility Espresso creates a server-side JavaScript Domain Object for each table, providing access to attributes (customer.balance), and persistence (customer.save()). The objects encapsulate their integrity in two ways: Rule Invocation – update requests trigger the relevant validation / computation rules Events – you can also associate server-side JavaScript event handlers with a table. These fire as update requests are processed The Event handlers can invoke anything in the JVM, such as jar file code you can load into Espresso, other RESTful services, etc. Background: Command Pattern Imagine a word processor, providing functionality to make a string of selected text bold, another bit of functionality for italics, and so forth. Now imagine we wish to provide Undo functionality. Not possible unless we save the commands. So, the Command Pattern emerged: create a class for each Command creating an instance “does” the command (e.g., make text bold), where the constructor arguments provide the necessary information (text start, length) maintain an ordered list of commands (object instances) require the Command Classes to provide an Undo method to reverse the effects of the constructor (e.g., remove the bold) Database Adaption: insert logic on a Request Table We can see this same pattern in database applications, where we wish to keep a record of transactions. For example, instead of just changing a salary (and forgetting who, when, old values etc), we create a SalaryAction(employeeId, raisePercent). We can think of this as a Request Table. The logic on the SalaryAction table might give the raise, but also validate (is the percent too big? is the resultant salary out of range?), and record who, when etc. Restify Commands with Request Tables So we can combine these notions: Create a database with table for each Command (OrderSickLeave, IncreaseSpeed, etc), with columns for command arguments. We can also provide columns for admin data (date executed, etc) Leverage Espresso to Restify these Declare Validation Logic JavaScript table events execute the command We can now use this approach to Restify our Enterprise commands, as described below. Command Requests Database The lower 3 tables are the Request Tables. They each have Foreign Keys to the Crew table, simply identifying the source of the request (this is optional). Load into Espresso We next connect Espresso, which discovers these tables and creates a Default RESTful API to them. We can view it in a test tool immediately: We can also define a Custom API, exposing just the elements we wish: Validate Command Parameters The following rules apply to Posts against our Command Request tables. Here we ensure that the IncreaseSpeed request has a argument (attribute) for warpFactor, that it be between 0 and 10, and that the optional emergencyReason parameter is supplied if the warpFactorexceeds 8 Live Browser – view, post data You can use the API tool, or this automatically constructed app: Invoke existing code Finally, we add server-side JavaScript logic (stubbed here) to execute our command. This would execute existing code in a loadable jar. Conclusion: 4 hour project This project was completed in about a half a day.
June 30, 2015
by Val Huber DZone Core CORE
· 5,808 Views
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Instant Enterprise REST Accelerates the Software Driven Business
Software Driven Business is a consensus goal. But real challenges exist: the time, cost and complexity of building such apps is substantial. Business Agility – and strategic business advantage – is lost. We need another revolution – Instant Enterprise REST – that provides Business Agility using business-level specifications rather than low-level code, and delivers Enterprise-class scalability, integration, enforcement and extensibility. It’s now a reality with Instant Enterprise REST. Software Driven Business: Consensus Vision Businesses have seen the value in providing mobile and tablet apps that bring the business into the hands of customers and employees. They provide information at their finger tips – wherever they are. Industry Leaders like CA have pioneered the vision of a Software Driven Business. They argue persuasively that strategic business advantage lies in Time to Market and Time to Decision: “reveal the need for speed in the application economy. As companies transform into software-driven enterprises, bringing high-quality applications to market faster becomes one of the most critical differentiators.” The Business Agility Gap While there is consensus around this vision, there is a substantial gap in realizing the Software Driven Business. It centers around Agility – time to market. As CA argues, this drives strategic business advantage. This problem manifests both to Business Users and IT, although differently. You might have been party to a discussion like this: Business Users are frustrated about how long it takes to create systems, and revise them. They see problems that look nearly as simple as a spreadsheet take weeks… to months. How can it months for IT to build a system that takes days on a spreadsheet? IT is no less frustrated. They understand the deep technology it takes to build Enterprise-class systems: We’re working 90 hours a week. And falling behind. Gap Analysis For apps about critical corporate data, there’s general consensus that the time and cost for such systems are about evenly split between backends and front ends. And there’s nearly universal consensus that, independent of the UI technology, that RESTful APIs deliver the backend data. But the backend is far more than basic data access. A “SQL Pass-through” – simply restifying SQL data – does not meet Enterprise-class requirements to scale, integrate and enforce: Scale – APIs require Pagination to address large result sets, Nested Documents to reduce latency, Optimistic Locking to ensure concurrency. These are not provided in a simple SQL Pass-through – you must program them, by hand. Integrate – a wizard can produce an API from schema objects, but it cannot address multiple databases, or integrate non-SQL data sources such as ERP, other RESTful services, or NoSQL. Enforce – an API needs to enforce our security (down to the row level), and the integrity of the data. These are significant tasks, which are sadly often placed in client buttons where they cannot be shared. Providing these Enterprise class services takes significant time, expertise and expense. Business Agility is reduced. IT is essentially being forced to cover inadequate technology infrastructure. The Business Users are right: if the Business Specification is clear, then that ought to be enough: A clear business specification should be sufficient. Everything else is just friction. The vision of the Software Driven Business requires Business Driven Software that pre-supplies the infrastructure. We are not seeking 10 or 15%. We are looking for orders of magnitude. Our vision must be: We should be able to create RESTful APIs (mainly) from business specifications, not low level code. It should be no more difficult to create a system than it is toimagine it. Business-Driven Software: Instant Enterprise REST Business Driven Software is more than just a clever play on words. It’s a real implementation that delivers this vision, and we call it Instant Enterprise REST. It consists of 3 core technologies: Enterprise Pattern Automation – creates APIs that with Enterprise-class scalability built-in (pagination, nested documents, optimistic locking, etc) Declarative – specify your API, integration and enforcement policies with spreadsheet-like rules in a simple point-and-click UI Extensibility – enables the RESTful APIs to invoke your existing logic, inside or outside the JVM, via standard server-side JavaScript. The combination of these 3 technologies enables you to create RESTful APIs for database backends – half your system – 10 times faster. Let’s briefly examine them below. Technology 1: Enterprise Pattern Automation There are well known patterns in the data domain, describing data structure and access via SQL. There are also well-known patterns for managing SQL data in the context of RESTful services. Well known patterns can be automated. Let’s imagine a service (say, a server accessed via a browser) that automates these patterns, as described below, just by connecting the service to a database: Schema Discovery – tables, views, stored procedures: The system creates a complete (default) API for each schema object. Note this includes Stored Procedures, which often represent a significant investment. Enterprise Pattern Automation: the resultant API provides well-known services for Filter, Sort, Pagination, Optimistic Locking, handling Generated Keys and so forth. So, the service has provided a default Enterprise-class API, instantly. So, literally seconds into your project, you can test your running API: Not enough, not done, but a great start. Technology 2: Declarative Declarative is the key (“what, not how”). It has had striking impacts on domains where there are well-understood underlying patterns. Max Tardiveau has put it well: Whatever can be declarative, will be declarative. For example, spreadsheets are declarative – and they gave birth to the PC industry. And SQL is declarative – itself an industry. Two game-changers. So, the challenge is to apply the spirit of declarative to REST integration and enforcement. The stakes are high – success can deliver breathtaking agility. Declarative Integration: Multi-Database Custom API, Point and Click Enterprise Pattern Automation provides a good start, but the API is not rich. It is a flat, single-table API, really just “restified” SQL. What we really need is Nested Documents – returning multiple types (e.g., an Order, a list of Items, and a list of contact names) in a single call can reduce latency (vs. a separate call for each type). REST is perfect for this. Multi-database APIs – a RESTful server provides the opportunity to integrate multiple databases in single call, shielding clients from underlying complexity. Nested Documents are easy: define them by simply selecting tables (via a User Interface or Command Line). Foreign Keys are used to default the joins. Add the ability to choose / alias columns, and we’re on the way to a pretty good API. But what about databases that have no Foreign Keys? Or multi-database APIs? Leveraging the schema does not mean we are limited to it. All we need to do is: Provide a means to define “Virtual” Foreign Keys for the service (i.e., stored outside the schema) Extend this to Foreign Keys between databases We now have a rich, multi-database API. Defined declaratively as shown below, no code required, running in minutes, ready for client development: Declarative Enforcement: Integrity Logic, with spreadsheet-like rules So now consider enforcement, specifically database integrity. A very significant portion of any project is the multi-table validations and computations that define how the data is processed. “Your code goes here” means, well, a lot of code. We need a more powerful, more declarative, paradigm. In a spreadsheet, you assign expressions to cells. Whenever the referenced data is changed, the cell is updated. Since the cells references can chain, a series of simple expressions can solve remarkably complex problems. What if we did the same for database data? We could assign derivation expressions to columns, and validation expressions to tables. Then, the API could “watch” for requests that change the referenced column, and recompute (efficiently) the calculated column. Just as in a spreadsheet, support for chaining and proper ordering is required and implicit. To address multi-table logic, such expressions would need to address references to related tables. It’s only at this point that the logic becomes seriously powerful. Let’s take an example. To check credit in a Customer / Purchaseorder / Lineitem application, we could define spreadsheet-like expressions such as: There is actually a sub-branch of declarative that addresses this: Reactive Programming. Here it’s declarative,since you don’t need to code a Observer handler. The result is that the logic above can be fully executable. No need to code Change Detection / Change Dependency – it’s invoked and enforced automatically by the API in reaction to RESTful updates. SQL handling is also implicit, including underlying optimizations (caching, pruning etc). The impact is massive – the 5 expressions above express the same logic as hundreds of lines of code. That’s a massive 40X more concise. Game changer. And quality goes up, since the rules are applied automatically. Declarative Enforcement: Security, filter expressions for role/table We can provide an analogous approach to security: define filter expressions for roles (like SalesRep), so that when a table is accessed by the role, the API adds the filter. That way, a user with that role sees only the rows for which they are authorized. Technology 3: Standards-based Extensibility Declarative is great, but you’re probably thinking “ok, but you can’t solve every problem declaratively”. And you’re dead right. Business Value requires that we integrate a declarative approach with a procedural one that is familiar, standards-based, and enables us to integrate existing software. Automatic JavaScript Object Model The first phase of many projects is to build an ORM for natural programmatic access to data: JPA, Hibernate, Entity Framework. It’s not a small project, and cumbersome to maintain as changes occur. In fact, the Object Model can be created directly from the schema. So, you’d have an object type for Purchaseorder, for Lineitem, and so forth. The model provides access to attributes and related data, and persistence services. You could then use it as shown below. JavaScript seems like the best language choice: reasonable across technology bases (everybody uses JavaScript), and its dynamic nature eliminates code generation hassles. JavaScript Events In addition to accessors and persistence, the JavaScript objects are Logic Aware. That is, the save operation above executes any rules associated with OrderAudit (e.g., updated-by), and JavaScript Events. Here is a sample event for the PurchaseOrder object, where you access the JavaScript Object Model via the system-supplied row variable: Extensible Logic Auditing is a common pattern. It should be possible to solve this once in a genericmanner, then re-use it (e.g, to audit employees, orders and so forth). So, Instant Enterprise REST should enable you to provide Extensible Logic – load your own JavaScript code, and invoke it. So, the code above could become: MyLibrary.auditFromTo(orderRow,"OrderAudit"); where auditFromTo creates an instance of OrderAudit, sets the foreign key, sets like-named attributes, and saves it. Pluggable Authentication Most organizations have existing data stores that identify users and their roles, such as Active Directory, LDAP, OAuth, etc. Security should integrate with such systems as a function of enforcing row/column access. Standard deployment Finally, the system should deploy in a familiar manner: available on the cloud, or an on-premise virtual appliance or war file. Standards also enable integration with related critical infrastructure, such as API Management, ERP Systems, etc. See a project in 3 minutes To see how it all fits together, you can view this video to see a full project built: from concept, through initial implementation, and an iteration cycle. Actual project time was about half an hour. Instant Enterprise REST: Business Agility Instant Enterprise REST enables us to close the Agility Gap in realizing the Software Driven Business vision. We can now create important portions of our software in largely business terms, rather than technical terms. This offers major advantages: Time to Market: spreadsheet-like rules are 40X more concise. Instant REST eliminates all the SQL / REST / JSON boilerplate. Simplicity: team members can learn the basics of Espresso in days, and be as productive as rocket scientists using alternative technologies Leverage Expertise and Software: Espresso is built on standards like REST, JavaScript, and Event Oriented Programming. You can call out to existing software, and extend the rule types by identifying your own patterns and loading their implementations into Espresso. Quality: at the defect level, automatic invocation and ordering eliminate large classes of bugs. At the architectural level, centralized enforcement factors logic out of the client buttons where it can be shared, audited for compliances, etc
June 30, 2015
by Val Huber DZone Core CORE
· 1,462 Views
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Persistence and DAO Testing Made Simple (with Exparity-Stub and Hamcrest-Bean)
Persistence of model objects is a part of many Java projects and a part which deserves, and often gets, high test coverage as one of the key layer integration points in the code. However, I've often felt the testing paradigms for this can be cumbersome, often involving a large amount of setup with an equivalent amount of validation. This can be tedious to both create and maintain. As a solution to this I've been testing persistence with a different pattern; by combining both the exparity-stub and the hamcrest-bean library you can thoroughly test model persistence in a few lines of test code as per the snippet below; .. User user = aRandomInstanceOf(User.class); User saved = dao.save(user); assertThat(dao.getUserById(saved.getId()), theSameBeanAs(saved)); The test snippet above is small but in those few lines will thoroughly test that all fields in a graph can be persisted and retrieved without loss, that any JPA or other mapping is valid, and that your queries are valid. For a complete example we'll work through testing a simple DAO for storing and retrieving User objects using the in-memory H2 database for simplicity. The same example will work for any persistence mechanism. Before we get started with an example lets briefly outline what the libraries are and what they do. The Exparity-Stub Library The exparity-stub libraries provides a set of static methods for creating stubs of model objects, object graphs, collections, types, and primitive types. For our example we'll be creating random stubs because we want to completely fill the graph with junk data and check it can be written down. exparity-stub offers two approaches to this, the RandomBuilder or the BeanBuilder. The RandomBuilder provides a terser notation to create random objects with less code. For example: User user = RandomBuilder.aRandomInstanceOf(User.class); List users = RandomBuilder.aRandomListOf(User.class); String anyString = RandomBuilder.aRandomString(); Whereas the BeanBuilder provides a fluent interface with finer control for building individual objects and graphs, for example; User user = BeanBuilder.aRandomInstanceOf(User.class) .excludeProperty("Id").build(); For this example i'm going to use the BeanBuilder so I can exclude the User.Id property from being populated by the random builder. The Hamcrest-Bean Library The hamcrest-bean library is an extension library to the Java Hamcrest library. The hamcrest-bean library provides a set of matchers specifically for testing Java objects and object graphs and performs deep inspections of those objects. It supports exclusions and overrides to allow fine control, if required, of how matching of any property, path, or type is handled, for example: User expected = new User("Jane", "Doe"); assertThat(new User("John", "Doe"), BeanMatchers.theSameAs(expected).excludeProperty("FirstName")); A Sample Project The sample project I'll work through is persistence of a simple User object with a child list of UserComment objects. This simple graph will be persisted to a H2 database with hibernate handling the Object-Relational Mapping (ORM) mapping, and Java Persistence Annotation (JPA) used to mark-up the model. The Model Below are the two model classes; first the User class. package org.exparity.hamcrest.bean.sample.dao; import java.util.*; import javax.persistence.*; @Entity @Table public class User { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) private Long id; private Date createTs; private String username, firstName, surname; @OneToMany(cascade = CascadeType.ALL, fetch = FetchType.EAGER) private List comments = new ArrayList<>(); public Long getId() { return id; } public void setId(Long id) { this.id = id; } public Date getCreateTs() { return createTs; } public void setCreateTs(Date createTs) { this.createTs = createTs; } public String getUsername() { return username; } public void setUsername(String username) { this.username = username; } public String getFirstName() { return firstName; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getSurname() { return surname; } public void setSurname(String surname) { this.surname = surname; } public List getComments() { return comments; } public void setComments(List comments) { this.comments = comments; } } Followed by the UserComment class. package org.exparity.hamcrest.bean.sample.dao; import java.util.Date; import javax.persistence.*; @Table @Entity public class UserComment { private Long id; private Date timestamp; @Transient private String text; private String title; public Date getTimestamp() { return timestamp; } public void setTimestamp(Date timestamp) { this.timestamp = timestamp; } public String getText() { return text; } public void setText(String text) { this.text = text; } public String getTitle() { return title; } public void setTitle(String title) { this.title = title; } } Followed by the UserComment class. package org.exparity.hamcrest.bean.sample.dao; import java.util.Date; import javax.persistence.*; @Table @Entity public class UserComment { private Long id; private Date timestamp; @Transient private String text; private String title; public Date getTimestamp() { return timestamp; } public void setTimestamp(Date timestamp) { this.timestamp = timestamp; } public String getText() { return text; } public void setText(String text) { this.text = text; } public String getTitle() { return title; } public void setTitle(String title) { this.title = title; } } The Data Access Object (DAO) Next up we write our DAO layer. I've excluded the UserDAO interface from this post but it is available in the sample project ongithub .The full, if somewhat crude, implementation of the UserDAO is below. package org.exparity.hamcrest.bean.sample.dao; import org.hibernate.boot.registry.StandardServiceRegistryBuilder; import org.hibernate.cfg.Configuration; import org.hibernate.*; public class UserDAOHibernateImpl implements UserDAO { private final SessionFactory factory; public UserDAOHibernateImpl(final String resourceFile) { this.factory = new Configuration() .addAnnotatedClass(User.class) .addAnnotatedClass(UserComment.class) .buildSessionFactory( new StandardServiceRegistryBuilder() .loadProperties(resourceFile) .build()); } @Override public User save(final User user) { Session session = factory.getCurrentSession(); Transaction txn = session.beginTransaction(); try { session.save(user); txn.commit(); } catch (final Exception e) { txn.rollback(); } return user; } @Override public User getUserById(Long userId) { Session session = factory.getCurrentSession(); Transaction txn = session.beginTransaction(); try { return (User) session.get(User.class, userId); } finally { txn.rollback(); } } } Integration Test And finally, onto our integration test. The hibernate.properties will create an instance of an in-memory database and create the necessary tables on instantiation of the DAO. hibernate.dialect=org.hibernate.dialect.H2Dialect hibernate.connection.username=sa hibernate.connection.password= hibernate.connection.driver_class=org.h2.Driver hibernate.connection.url=jdbc:h2:mem:test hibernate.current_session_context_class=thread hibernate.cache.provider_class=org.hibernate.cache.internal.NoCacheProvider hibernate.show_sql=true hibernate.hbm2ddl.auto=update The integration test is below. package org.exparity.hamcrest.bean.sample.dao; import static org.exparity.hamcrest.BeanMatchers.theSameBeanAs; import static org.exparity.stub.bean.BeanBuilder.aRandomInstanceOf; import static org.hamcrest.MatcherAssert.assertThat; import static org.hamcrest.Matchers.*; import org.junit.Test; public class UserDAOHibernateImplTest { @Test public void canSaveAUser() { User user = aRandomInstanceOf(User.class).excludeProperty("Id").build(); UserDAOHibernateImpl dao = new UserDAOHibernateImpl("hibernate.properties"); User saved = dao.save(user); User loaded = dao.getUserById(saved.getId()); assertThat(loaded, not(sameInstance(user))); assertThat(loaded, theSameBeanAs(user)); } } Let's break the test down step by step to see what each step is doing and why the test is put together this way. 1) Model Setup User user = aRandomInstanceOf(User.class).excludeProperty("Id").build(); Create a random instance of the User class and it's associates using exparity-stub. The instance will be populated with random data with the exception of the Id property. I've excluded the Id property so that is left null to test that the id is being generated in the database. 2) DAO Setup UserDAOHibernateImpl dao = new UserDAOHibernateImpl("hibernate.properties") Instantiate the DAO ready to be tested, passing in the property file to use for the test. The hibernate properties used will configure an in-memory instance of H2 and create the schema automatically. 3) Exercise the DAO User saved = dao.save(user); User loaded = dao.getUserById(saved.getId()); Save the random instance of the model set up in step (1) and then query the object back out again. 4) Verify the results assertThat(loaded, not(sameInstance(user))); assertThat(loaded, theSameBeanAs(user)); The first line verifies that the loaded User instance is not the same instance as the originally saved User. This prevents false positive results when the loaded instance is returned directly from a cache. The second line uses hamcrest-bean to perform a deep comparison of the loaded User instance against the original user instance. Running the Test The first run of the test yields an error; specifically a hibernate warning because a @Id annotation has been missed on UserComment. org.hibernate.AnnotationException: No identifier specified for entity: org.exparity.hamcrest.bean.sample.dao.UserComment at org.hibernate.cfg.InheritanceState.determineDefaultAccessType(InheritanceState.java:277) at org.hibernate.cfg.InheritanceState.getElementsToProcess(InheritanceState.java:224) at org.hibernate.cfg.AnnotationBinder.bindClass(AnnotationBinder.java:775) at org.hibernate.cfg.Configuration$MetadataSourceQueue.processAnnotatedClassesQueue(Configuration.java:3845) at org.hibernate.cfg.Configuration$MetadataSourceQueue.processMetadata(Configuration.java:3799) at org.hibernate.cfg.Configuration.secondPassCompile(Configuration.java:1412) at org.hibernate.cfg.Configuration.buildSessionFactory(Configuration.java:1846) at org.exparity.hamcrest.bean.sample.dao.UserDAOHibernateImpl.(UserDAOHibernateImpl.java:15) at org.exparity.hamcrest.bean.sample.dao.UserDAOHibernateImplTest.canSaveAUser(UserDAOHibernateImplTest.java:18) A fix to the UserComment object and we can run the test again. @Table @Entity public class UserComment { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) private Long id; private Date timestamp; @Transient private String text; private String title; ... After running the test again we get another failure. The presence of the @Transient annotation on the UserComment.text property is preventing the value being persisted java.lang.AssertionError: Expected: the same as but: User.Comments[0].Text is null instead of "mDAWDJXbheIHbbHLR1NNVJqAki49RvaVwQtKD38r79u0y3MTDD" at org.hamcrest.MatcherAssert.assertThat(MatcherAssert.java:20) at org.hamcrest.MatcherAssert.assertThat(MatcherAssert.java:8) at org.exparity.hamcrest.bean.sample.dao.UserDAOHibernateImplTest.canSaveAUser(UserDAOHibernateImplTest.java:19) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:483) at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:47) Another change to the UserComment object to remove the @Transient annotation and we can run the test again. @Table @Entity public class UserComment { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) private Long id; private Date timestamp; private String text; private String title; ... After running the test again it all passes. Try It Out To try hamcrest-bean and exparity-stub out for yourself include the dependency in your maven pom or other dependency manager. org.exparity hamcrest-bean 1.0.10 test org.exparity exparity-stub 1.1.5 test
June 29, 2015
by Stewart Bissett
· 3,287 Views
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The Cloudcast #198 - Architecting Cloud Foundry
Download the MP3 Date: June 19, 2015 By: Aaron Delp and Brian Gracely Description: Aaron and Brian talk to Chip Childers (@chipchilders, VP of Technology @CloudFoundryOrg) about the current status of Cloud Foundry projects, how Microsoft .NET will be integrated, IaaS vs. PaaS, and the CF.org thinking about overall interoperability Interested in the O'Reilly OSCON? Want to register for OSCON now? Use promo code 20CLOUD for 20% off Details to win an OSCON pass coming soon! Check out the OSCON Schedule Free eBook from O'Reilly Media for Cloudcast Listeners! Check out an excerpt from the upcoming Docker Cookbook Topic 1 - From an overall project perspective, what grades would you give Cloud Foundry in terms of stability, core functionality, security, operations, etc? Topic 2 - You were previously involved (directly/indirectly)with CloudStack. As you talk to people in the marketplace, how is it different discussing IaaS vs. PaaS. Topic 3 - How much ability will you have to drive prioritization within sub-projects or new projects? (eg. Security vs. new Languages vs. Interop, etc.) Topic 4 - What’s the CF.org way of thinking about interoperability? Topic 5 - What guidance are you giving the teams in terms of expandability of Cloud Foundry? Architecturally, are there certain places you recommend over other places? Topic 6 - Is there a place for integrating SaaS applications (monitoring, logging, etc.) into Cloud Foundry?
June 29, 2015
by Brian Gracely
· 1,175 Views
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