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  • SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

    - by Pinal Dave
    Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ 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, Technology Tagged: NuoDB

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  • MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

    - by Mat Keep
    0 0 1 1097 6254 Homework 52 14 7337 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication.  This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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  • Cloud Computing = Elasticity * Availability

    - by Herve Roggero
    What is cloud computing? Is hosting the same thing as cloud computing? Are you running a cloud if you already use virtual machines? What is the difference between Infrastructure as a Service (IaaS) and a cloud provider? And the list goes on… these questions keep coming up and all try to fundamentally explain what “cloud” means relative to other concepts. At the risk of over simplification, answering these questions becomes simpler once you understand the primary foundations of cloud computing: Elasticity and Availability.   Elasticity The basic value proposition of cloud computing is to pay as you go, and to pay for what you use. This implies that an application can expand and contract on demand, across all its tiers (presentation layer, services, database, security…).  This also implies that application components can grow independently from each other. So if you need more storage for your database, you should be able to grow that tier without affecting, reconfiguring or changing the other tiers. Basically, cloud applications behave like a sponge; when you add water to a sponge, it grows in size; in the application world, the more customers you add, the more it grows. Pure IaaS providers will provide certain benefits, specifically in terms of operating costs, but an IaaS provider will not help you in making your applications elastic; neither will Virtual Machines. The smallest elasticity unit of an IaaS provider and a Virtual Machine environment is a server (physical or virtual). While adding servers in a datacenter helps in achieving scale, it is hardly enough. The application has yet to use this hardware.  If the process of adding computing resources is not transparent to the application, the application is not elastic.   As you can see from the above description, designing for the cloud is not about more servers; it is about designing an application for elasticity regardless of the underlying server farm.   Availability The fact of the matter is that making applications highly available is hard. It requires highly specialized tools and trained staff. On top of it, it's expensive. Many companies are required to run multiple data centers due to high availability requirements. In some organizations, some data centers are simply on standby, waiting to be used in a case of a failover. Other organizations are able to achieve a certain level of success with active/active data centers, in which all available data centers serve incoming user requests. While achieving high availability for services is relatively simple, establishing a highly available database farm is far more complex. In fact it is so complex that many companies establish yearly tests to validate failover procedures.   To a certain degree certain IaaS provides can assist with complex disaster recovery planning and setting up data centers that can achieve successful failover. However the burden is still on the corporation to manage and maintain such an environment, including regular hardware and software upgrades. Cloud computing on the other hand removes most of the disaster recovery requirements by hiding many of the underlying complexities.   Cloud Providers A cloud provider is an infrastructure provider offering additional tools to achieve application elasticity and availability that are not usually available on-premise. For example Microsoft Azure provides a simple configuration screen that makes it possible to run 1 or 100 web sites by clicking a button or two on a screen (simplifying provisioning), and soon SQL Azure will offer Data Federation to allow database sharding (which allows you to scale the database tier seamlessly and automatically). Other cloud providers offer certain features that are not available on-premise as well, such as the Amazon SC3 (Simple Storage Service) which gives you virtually unlimited storage capabilities for simple data stores, which is somewhat equivalent to the Microsoft Azure Table offering (offering a server-independent data storage model). Unlike IaaS providers, cloud providers give you the necessary tools to adopt elasticity as part of your application architecture.    Some cloud providers offer built-in high availability that get you out of the business of configuring clustered solutions, or running multiple data centers. Some cloud providers will give you more control (which puts some of that burden back on the customers' shoulder) and others will tend to make high availability totally transparent. For example, SQL Azure provides high availability automatically which would be very difficult to achieve (and very costly) on premise.   Keep in mind that each cloud provider has its strengths and weaknesses; some are better at achieving transparent scalability and server independence than others.    Not for Everyone Note however that it is up to you to leverage the elasticity capabilities of a cloud provider, as discussed previously; if you build a website that does not need to scale, for which elasticity is not important, then you can use a traditional host provider unless you also need high availability. Leveraging the technologies of cloud providers can be difficult and can become a journey for companies that build their solutions in a scale up fashion. Cloud computing promises to address cost containment and scalability of applications with built-in high availability. If your application does not need to scale or you do not need high availability, then cloud computing may not be for you. In fact, you may pay a premium to run your applications with cloud providers due to the underlying technologies built specifically for scalability and availability requirements. And as such, the cloud is not for everyone.   Consistent Customer Experience, Predictable Cost With all its complexities, buzz and foggy definition, cloud computing boils down to a simple objective: consistent customer experience at a predictable cost.  The objective of a cloud solution is to provide the same user experience to your last customer than the first, while keeping your operating costs directly proportional to the number of customers you have. Making your applications elastic and highly available across all its tiers, with as much automation as possible, achieves the first objective of a consistent customer experience. And the ability to expand and contract the infrastructure footprint of your application dynamically achieves the cost containment objectives.     Herve Roggero is a SQL Azure MVP and co-author of Pro SQL Azure (APress).  He is the co-founder of Blue Syntax Consulting (www.bluesyntax.net), a company focusing on cloud computing technologies helping customers understand and adopt cloud computing technologies. For more information contact herve at hroggero @ bluesyntax.net .

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  • Guide to MySQL & NoSQL, Webinar Q&A

    - by Mat Keep
    0 0 1 959 5469 Homework 45 12 6416 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful. Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar. Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL: - On-Demand webinar (coming soon!) - Slides used during the webinar - Guide to MySQL and NoSQL whitepaper  - MySQL Cluster demo, including NoSQL interfaces, auto-sharing, high availability, etc.  So here is the Q&A from the event  Q. Where does MySQL Cluster fit in to the CAP theorem? A. MySQL Cluster is flexible. A single Cluster will prefer consistency over availability in the presence of network partitions. A pair of Clusters can be configured to prefer availability over consistency. A full explanation can be found on the MySQL Cluster & CAP Theorem blog post.  Q. Can you configure the number of replicas? (the slide used a replication factor of 1) Yes. A cluster is configured by an .ini file. The option NoOfReplicas sets the number of originals and replicas: 1 = no data redundancy, 2 = one copy etc. Usually there's no benefit in setting it >2. Q. Interestingly most (if not all) of the NoSQL databases recommend having 3 copies of data (the replication factor).    Yes, with configurable quorum based Reads and writes. MySQL Cluster does not need a quorum of replicas online to provide service. Systems that require a quorum need > 2 replicas to be able to tolerate a single failure. Additionally, many NoSQL systems take liberal inspiration from the original GFS paper which described a 3 replica configuration. MySQL Cluster avoids the need for a quorum by using a lightweight arbitrator. You can configure more than 2 replicas, but this is a tradeoff between incrementally improved availability, and linearly increased cost. Q. Can you have cross node group JOINS? Wouldn't that run into the risk of flooding the network? MySQL Cluster 7.2 supports cross nodegroup joins. A full cross-join can require a large amount of data transfer, which may bottleneck on network bandwidth. However, for more selective joins, typically seen with OLTP and light analytic applications, cross node-group joins give a great performance boost and network bandwidth saving over having the MySQL Server perform the join. Q. Are the details of the benchmark available anywhere? According to my calculations it results in approx. 350k ops/sec per processor which is the largest number I've seen lately The details are linked from Mikael Ronstrom's blog The benchmark uses a benchmarking tool we call flexAsynch which runs parallel asynchronous transactions. It involved 100 byte reads, of 25 columns each. Regarding the per-processor ops/s, MySQL Cluster is particularly efficient in terms of throughput/node. It uses lock-free minimal copy message passing internally, and maximizes ID cache reuse. Note also that these are in-memory tables, there is no need to read anything from disk. Q. Is access control (like table) planned to be supported for NoSQL access mode? Currently we have not seen much need for full SQL-like access control (which has always been overkill for web apps and telco apps). So we have no plans, though especially with memcached it is certainly possible to turn-on connection-level access control. But specifically table level controls are not planned. Q. How is the performance of memcached APi with MySQL against memcached+MySQL or any other Object Cache like Ecache with MySQL DB? With the memcache API we generally see a memcached response in less than 1 ms. and a small cluster with one memcached server can handle tens of thousands of operations per second. Q. Can .NET can access MemcachedAPI? Yes, just use a .Net memcache client such as the enyim or BeIT memcache libraries. Q. Is the row level locking applicable when you update a column through memcached API? An update that comes through memcached uses a row lock and then releases it immediately. Memcached operations like "INCREMENT" are actually pushed down to the data nodes. In most cases the locks are not even held long enough for a network round trip. Q. Has anyone published an example using something like PHP? I am assuming that you just use the PHP memcached extension to hook into the memcached API. Is that correct? Not that I'm aware of but absolutely you can use it with php or any of the other drivers Q. For beginner we need more examples. Take a look here for a fully worked example Q. Can I access MySQL using Cobol (Open Cobol) or C and if so where can I find the coding libraries etc? A. There is a cobol implementation that works well with MySQL, but I do not think it is Open Cobol. Also there is a MySQL C client library that is a standard part of every mysql distribution Q. Is there a place to go to find help when testing and/implementing the NoSQL access? If using Cluster then you can use the [email protected] alias or post on the MySQL Cluster forum Q. Are there any white papers on this?  Yes - there is more detail in the MySQL Guide to NoSQL whitepaper If you have further questions, please don’t hesitate to use the comments below!

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  • Clouds Everywhere But not a Drop of Rain – Part 3

    - by sxkumar
    I was sharing with you how a broad-based transformation such as cloud will increase agility and efficiency of an organization if process re-engineering is part of the plan.  I have also stressed on the key enterprise requirements such as “broad and deep solutions, “running your mission critical applications” and “automated and integrated set of capabilities”. Let me walk you through some key cloud attributes such as “elasticity” and “self-service” and what they mean for an enterprise class cloud. I will also talk about how we at Oracle have taken a very enterprise centric view to developing cloud solutions and how our products have been specifically engineered to address enterprise cloud needs. Cloud Elasticity and Enterprise Applications Requirements Easy and quick scalability for a short-period of time is the signature of cloud based solutions. It is this elasticity that allows you to dynamically redistribute your resources according to business priorities, helps increase your overall resource utilization, and reduces operational costs by allowing you to get the most out of your existing investment. Most public clouds are offering a instant provisioning mechanism of compute power (CPU, RAM, Disk), customer pay for the instance-hours(and bandwidth) they use, adding computing resources at peak times and removing them when they are no longer needed. This type of “just-in-time” serving of compute resources is well known for mid-tiers “state less” servers such as web application servers and web servers that just need another machine to start and run on it but what does it really mean for an enterprise application and its underlying data? Most enterprise applications are not as quite as “state less” and justifiably so. As such, how do you take advantage of cloud elasticity and make it relevant for your enterprise apps? This is where Cloud meets Grid Computing. At Oracle, we have invested enormous amount of time, energy and resources in creating enterprise grid solutions. All our technology products offer built-in elasticity via clustering and dynamic scaling. With products like Real Application Clusters (RAC), Automatic Storage Management, WebLogic Clustering, and Coherence In-Memory Grid, we allow all your enterprise applications to benefit from Cloud elasticity –both vertically and horizontally - without requiring any application changes. A number of technology vendors take a rather simplistic route of starting up additional or removing unneeded VM as the "Cloud Scale-Out" solution. While this may work for stateless mid-tier servers where load balancers can handle the addition and remove of instances transparently but following a similar approach for the database tier - often called as "database sharding" - requires significant application modification and typically does not work with off the shelf packaged applications. Technologies like Oracle Database Real Application Clusters, Automatic Storage Management, etc. on the other hand bring the benefits of incremental scalability and on-demand elasticity to ANY application by providing a simplified abstraction layers where the application does not need deal with data spread over multiple database instances. Rather they just talk to a single database and the database software takes care of aggregating resources across multiple hardware components. It is the technologies like these that truly make a cloud solution relevant for enterprises.  For customers who are looking for a next generation hardware consolidation platform, our engineered systems (e.g. Exadata, Exalogic) not only provide incredible amount of performance and capacity, they also reduce the data center complexity and simplify operations. Assemble, Deploy and Manage Enterprise Applications for Cloud Products like Oracle Virtual assembly builder (OVAB) resolve the complex problem of bringing the cloud speed to complex multi-tier applications. With assemblies, you can not only provision all components of a multi-tier application and wire them together by push of a button, other aspects of application lifecycle, such as real-time application testing, scale-up/scale-down, performance and availability monitoring, etc., are also automated using Oracle Enterprise Manager.  An essential criteria for an enterprise cloud to succeed is the ability to ensure business service levels especially when business users have either full visibility on the usage cost with a “show back” or a “charge back”. With Oracle Enterprise Manager 12c, we have created the most comprehensive cloud management solution in the industry that is capable of managing business service levels “applications-to-disk” in a enterprise private cloud – all from a single console. It is the only cloud management platform in the industry that allows you to deliver infrastructure, platform and application cloud services out of the box. Moreover, it offers integrated and complete lifecycle management of the cloud - including planning and set up, service delivery, operations management, metering and chargeback, etc .  Sounds unbelievable? Well, just watch this space for more details on how Oracle Enterprise Manager 12c is the nerve center of Oracle Cloud! Our cloud solution portfolio is also the broadest and most deep in the industry  - covering public, private, hybrid, Infrastructure, platform and applications clouds. It is no coincidence therefore that the Oracle Cloud today offers the most comprehensive set of public cloud services in the industry.  And to a large part, this has been made possible thanks to our years on investment in creating cloud enabling technologies.  Summary  But the intent of this blog post isn't to dwell on how great our solutions are (these are just some examples to illustrate how we at Oracle have approached this problem space). Rather it is to help you ask the right questions before you embark on your cloud journey.  So to summarize, here are the key takeaways.       It is critical that you are clear on why you are building the cloud. Successful organizations keep business benefits as the first and foremost cloud objective. On the other hand, those who approach this purely as a technology project are more likely to fail. Think about where you want to be in 3-5 years before you get started. Your long terms objectives should determine what your first step ought to be. As obvious as it may seem, more people than not make the first move without knowing where they are headed.  Don’t make the mistake of equating cloud to virtualization and Infrastructure-as-a-Service (IaaS). Spinning a VM on-demand will give some short term relief to your IT staff but is unlikely to solve your larger business problems. As such, even if IaaS is your first step towards a more comprehensive cloud, plan the roadmap around those higher level services before you begin. And ask your vendors on how they are going to be your partners in this journey. Capabilities like self-service access and chargeback/showback are absolutely critical if you really expect your cloud to be transformational. Your business won't see the full benefits of the cloud until it empowers them with same kind of control and transparency that they are used to while using a public cloud service.  Evaluate the benefits of integration, as opposed to blindly following the best-of-breed strategy. Integration is a huge challenge and more so in a cloud environment. There are enormous costs associated with stitching a solution out of disparate components and even more in maintaining it. Hope you found these ideas helpful. Looking forward to hearing your thoughts and experiences.

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  • TOTD #166: Using NoSQL database in your Java EE 6 Applications on GlassFish - MongoDB for now!

    - by arungupta
    The Java EE 6 platform includes Java Persistence API to work with RDBMS. The JPA specification defines a comprehensive API that includes, but not restricted to, how a database table can be mapped to a POJO and vice versa, provides mechanisms how a PersistenceContext can be injected in a @Stateless bean and then be used for performing different operations on the database table and write typesafe queries. There are several well known advantages of RDBMS but the NoSQL movement has gained traction over past couple of years. The NoSQL databases are not intended to be a replacement for the mainstream RDBMS. As Philosophy of NoSQL explains, NoSQL database was designed for casual use where all the features typically provided by an RDBMS are not required. The name "NoSQL" is more of a category of databases that is more known for what it is not rather than what it is. The basic principles of NoSQL database are: No need to have a pre-defined schema and that makes them a schema-less database. Addition of new properties to existing objects is easy and does not require ALTER TABLE. The unstructured data gives flexibility to change the format of data any time without downtime or reduced service levels. Also there are no joins happening on the server because there is no structure and thus no relation between them. Scalability and performance is more important than the entire set of functionality typically provided by an RDBMS. This set of databases provide eventual consistency and/or transactions restricted to single items but more focus on CRUD. Not be restricted to SQL to access the information stored in the backing database. Designed to scale-out (horizontal) instead of scale-up (vertical). This is important knowing that databases, and everything else as well, is moving into the cloud. RBDMS can scale-out using sharding but requires complex management and not for the faint of heart. Unlike RBDMS which require a separate caching tier, most of the NoSQL databases comes with integrated caching. Designed for less management and simpler data models lead to lower administration as well. There are primarily three types of NoSQL databases: Key-Value stores (e.g. Cassandra and Riak) Document databases (MongoDB or CouchDB) Graph databases (Neo4J) You may think NoSQL is panacea but as I mentioned above they are not meant to replace the mainstream databases and here is why: RDBMS have been around for many years, very stable, and functionally rich. This is something CIOs and CTOs can bet their money on without much worry. There is a reason 98% of Fortune 100 companies run Oracle :-) NoSQL is cutting edge, brings excitement to developers, but enterprises are cautious about them. Commercial databases like Oracle are well supported by the backing enterprises in terms of providing support resources on a global scale. There is a full ecosystem built around these commercial databases providing training, performance tuning, architecture guidance, and everything else. NoSQL is fairly new and typically backed by a single company not able to meet the scale of these big enterprises. NoSQL databases are good for CRUDing operations but business intelligence is extremely important for enterprises to stay competitive. RDBMS provide extensive tooling to generate this data but that was not the original intention of NoSQL databases and is lacking in that area. Generating any meaningful information other than CRUDing require extensive programming. Not suited for complex transactions such as banking systems or other highly transactional applications requiring 2-phase commit. SQL cannot be used with NoSQL databases and writing simple queries can be involving. Enough talking, lets take a look at some code. This blog has published multiple blogs on how to access a RDBMS using JPA in a Java EE 6 application. This Tip Of The Day (TOTD) will show you can use MongoDB (a document-oriented database) with a typical 3-tier Java EE 6 application. Lets get started! The complete source code of this project can be downloaded here. Download MongoDB for your platform from here (1.8.2 as of this writing) and start the server as: arun@ArunUbuntu:~/tools/mongodb-linux-x86_64-1.8.2/bin$./mongod./mongod --help for help and startup optionsSun Jun 26 20:41:11 [initandlisten] MongoDB starting : pid=11210port=27017 dbpath=/data/db/ 64-bit Sun Jun 26 20:41:11 [initandlisten] db version v1.8.2, pdfile version4.5Sun Jun 26 20:41:11 [initandlisten] git version:433bbaa14aaba6860da15bd4de8edf600f56501bSun Jun 26 20:41:11 [initandlisten] build sys info: Linuxbs-linux64.10gen.cc 2.6.21.7-2.ec2.v1.2.fc8xen #1 SMP Fri Nov 2017:48:28 EST 2009 x86_64 BOOST_LIB_VERSION=1_41Sun Jun 26 20:41:11 [initandlisten] waiting for connections on port 27017Sun Jun 26 20:41:11 [websvr] web admin interface listening on port 28017 The default directory for the database is /data/db and needs to be created as: sudo mkdir -p /data/db/sudo chown `id -u` /data/db You can specify a different directory using "--dbpath" option. Refer to Quickstart for your specific platform. Using NetBeans, create a Java EE 6 project and make sure to enable CDI and add JavaServer Faces framework. Download MongoDB Java Driver (2.6.3 of this writing) and add it to the project library by selecting "Properties", "LIbraries", "Add Library...", creating a new library by specifying the location of the JAR file, and adding the library to the created project. Edit the generated "index.xhtml" such that it looks like: <h1>Add a new movie</h1><h:form> Name: <h:inputText value="#{movie.name}" size="20"/><br/> Year: <h:inputText value="#{movie.year}" size="6"/><br/> Language: <h:inputText value="#{movie.language}" size="20"/><br/> <h:commandButton actionListener="#{movieSessionBean.createMovie}" action="show" title="Add" value="submit"/></h:form> This page has a simple HTML form with three text boxes and a submit button. The text boxes take name, year, and language of a movie and the submit button invokes the "createMovie" method of "movieSessionBean" and then render "show.xhtml". Create "show.xhtml" ("New" -> "Other..." -> "Other" -> "XHTML File") such that it looks like: <head> <title><h1>List of movies</h1></title> </head> <body> <h:form> <h:dataTable value="#{movieSessionBean.movies}" var="m" > <h:column><f:facet name="header">Name</f:facet>#{m.name}</h:column> <h:column><f:facet name="header">Year</f:facet>#{m.year}</h:column> <h:column><f:facet name="header">Language</f:facet>#{m.language}</h:column> </h:dataTable> </h:form> This page shows the name, year, and language of all movies stored in the database so far. The list of movies is returned by "movieSessionBean.movies" property. Now create the "Movie" class such that it looks like: import com.mongodb.BasicDBObject;import com.mongodb.BasicDBObject;import com.mongodb.DBObject;import javax.enterprise.inject.Model;import javax.validation.constraints.Size;/** * @author arun */@Modelpublic class Movie { @Size(min=1, max=20) private String name; @Size(min=1, max=20) private String language; private int year; // getters and setters for "name", "year", "language" public BasicDBObject toDBObject() { BasicDBObject doc = new BasicDBObject(); doc.put("name", name); doc.put("year", year); doc.put("language", language); return doc; } public static Movie fromDBObject(DBObject doc) { Movie m = new Movie(); m.name = (String)doc.get("name"); m.year = (int)doc.get("year"); m.language = (String)doc.get("language"); return m; } @Override public String toString() { return name + ", " + year + ", " + language; }} Other than the usual boilerplate code, the key methods here are "toDBObject" and "fromDBObject". These methods provide a conversion from "Movie" -> "DBObject" and vice versa. The "DBObject" is a MongoDB class that comes as part of the mongo-2.6.3.jar file and which we added to our project earlier.  The complete javadoc for 2.6.3 can be seen here. Notice, this class also uses Bean Validation constraints and will be honored by the JSF layer. Finally, create "MovieSessionBean" stateless EJB with all the business logic such that it looks like: package org.glassfish.samples;import com.mongodb.BasicDBObject;import com.mongodb.DB;import com.mongodb.DBCollection;import com.mongodb.DBCursor;import com.mongodb.DBObject;import com.mongodb.Mongo;import java.net.UnknownHostException;import java.util.ArrayList;import java.util.List;import javax.annotation.PostConstruct;import javax.ejb.Stateless;import javax.inject.Inject;import javax.inject.Named;/** * @author arun */@Stateless@Namedpublic class MovieSessionBean { @Inject Movie movie; DBCollection movieColl; @PostConstruct private void initDB() throws UnknownHostException { Mongo m = new Mongo(); DB db = m.getDB("movieDB"); movieColl = db.getCollection("movies"); if (movieColl == null) { movieColl = db.createCollection("movies", null); } } public void createMovie() { BasicDBObject doc = movie.toDBObject(); movieColl.insert(doc); } public List<Movie> getMovies() { List<Movie> movies = new ArrayList(); DBCursor cur = movieColl.find(); System.out.println("getMovies: Found " + cur.size() + " movie(s)"); for (DBObject dbo : cur.toArray()) { movies.add(Movie.fromDBObject(dbo)); } return movies; }} The database is initialized in @PostConstruct. Instead of a working with a database table, NoSQL databases work with a schema-less document. The "Movie" class is the document in our case and stored in the collection "movies". The collection allows us to perform query functions on all movies. The "getMovies" method invokes "find" method on the collection which is equivalent to the SQL query "select * from movies" and then returns a List<Movie>. Also notice that there is no "persistence.xml" in the project. Right-click and run the project to see the output as: Enter some values in the text box and click on enter to see the result as: If you reached here then you've successfully used MongoDB in your Java EE 6 application, congratulations! Some food for thought and further play ... SQL to MongoDB mapping shows mapping between traditional SQL -> Mongo query language. Tutorial shows fun things you can do with MongoDB. Try the interactive online shell  The cookbook provides common ways of using MongoDB In terms of this project, here are some tasks that can be tried: Encapsulate database management in a JPA persistence provider. Is it even worth it because the capabilities are going to be very different ? MongoDB uses "BSonObject" class for JSON representation, add @XmlRootElement on a POJO and how a compatible JSON representation can be generated. This will make the fromXXX and toXXX methods redundant.

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  • TOTD #166: Using NoSQL database in your Java EE 6 Applications on GlassFish - MongoDB for now!

    - by arungupta
    The Java EE 6 platform includes Java Persistence API to work with RDBMS. The JPA specification defines a comprehensive API that includes, but not restricted to, how a database table can be mapped to a POJO and vice versa, provides mechanisms how a PersistenceContext can be injected in a @Stateless bean and then be used for performing different operations on the database table and write typesafe queries. There are several well known advantages of RDBMS but the NoSQL movement has gained traction over past couple of years. The NoSQL databases are not intended to be a replacement for the mainstream RDBMS. As Philosophy of NoSQL explains, NoSQL database was designed for casual use where all the features typically provided by an RDBMS are not required. The name "NoSQL" is more of a category of databases that is more known for what it is not rather than what it is. The basic principles of NoSQL database are: No need to have a pre-defined schema and that makes them a schema-less database. Addition of new properties to existing objects is easy and does not require ALTER TABLE. The unstructured data gives flexibility to change the format of data any time without downtime or reduced service levels. Also there are no joins happening on the server because there is no structure and thus no relation between them. Scalability and performance is more important than the entire set of functionality typically provided by an RDBMS. This set of databases provide eventual consistency and/or transactions restricted to single items but more focus on CRUD. Not be restricted to SQL to access the information stored in the backing database. Designed to scale-out (horizontal) instead of scale-up (vertical). This is important knowing that databases, and everything else as well, is moving into the cloud. RBDMS can scale-out using sharding but requires complex management and not for the faint of heart. Unlike RBDMS which require a separate caching tier, most of the NoSQL databases comes with integrated caching. Designed for less management and simpler data models lead to lower administration as well. There are primarily three types of NoSQL databases: Key-Value stores (e.g. Cassandra and Riak) Document databases (MongoDB or CouchDB) Graph databases (Neo4J) You may think NoSQL is panacea but as I mentioned above they are not meant to replace the mainstream databases and here is why: RDBMS have been around for many years, very stable, and functionally rich. This is something CIOs and CTOs can bet their money on without much worry. There is a reason 98% of Fortune 100 companies run Oracle :-) NoSQL is cutting edge, brings excitement to developers, but enterprises are cautious about them. Commercial databases like Oracle are well supported by the backing enterprises in terms of providing support resources on a global scale. There is a full ecosystem built around these commercial databases providing training, performance tuning, architecture guidance, and everything else. NoSQL is fairly new and typically backed by a single company not able to meet the scale of these big enterprises. NoSQL databases are good for CRUDing operations but business intelligence is extremely important for enterprises to stay competitive. RDBMS provide extensive tooling to generate this data but that was not the original intention of NoSQL databases and is lacking in that area. Generating any meaningful information other than CRUDing require extensive programming. Not suited for complex transactions such as banking systems or other highly transactional applications requiring 2-phase commit. SQL cannot be used with NoSQL databases and writing simple queries can be involving. Enough talking, lets take a look at some code. This blog has published multiple blogs on how to access a RDBMS using JPA in a Java EE 6 application. This Tip Of The Day (TOTD) will show you can use MongoDB (a document-oriented database) with a typical 3-tier Java EE 6 application. Lets get started! The complete source code of this project can be downloaded here. Download MongoDB for your platform from here (1.8.2 as of this writing) and start the server as: arun@ArunUbuntu:~/tools/mongodb-linux-x86_64-1.8.2/bin$./mongod./mongod --help for help and startup optionsSun Jun 26 20:41:11 [initandlisten] MongoDB starting : pid=11210port=27017 dbpath=/data/db/ 64-bit Sun Jun 26 20:41:11 [initandlisten] db version v1.8.2, pdfile version4.5Sun Jun 26 20:41:11 [initandlisten] git version:433bbaa14aaba6860da15bd4de8edf600f56501bSun Jun 26 20:41:11 [initandlisten] build sys info: Linuxbs-linux64.10gen.cc 2.6.21.7-2.ec2.v1.2.fc8xen #1 SMP Fri Nov 2017:48:28 EST 2009 x86_64 BOOST_LIB_VERSION=1_41Sun Jun 26 20:41:11 [initandlisten] waiting for connections on port 27017Sun Jun 26 20:41:11 [websvr] web admin interface listening on port 28017 The default directory for the database is /data/db and needs to be created as: sudo mkdir -p /data/db/sudo chown `id -u` /data/db You can specify a different directory using "--dbpath" option. Refer to Quickstart for your specific platform. Using NetBeans, create a Java EE 6 project and make sure to enable CDI and add JavaServer Faces framework. Download MongoDB Java Driver (2.6.3 of this writing) and add it to the project library by selecting "Properties", "LIbraries", "Add Library...", creating a new library by specifying the location of the JAR file, and adding the library to the created project. Edit the generated "index.xhtml" such that it looks like: <h1>Add a new movie</h1><h:form> Name: <h:inputText value="#{movie.name}" size="20"/><br/> Year: <h:inputText value="#{movie.year}" size="6"/><br/> Language: <h:inputText value="#{movie.language}" size="20"/><br/> <h:commandButton actionListener="#{movieSessionBean.createMovie}" action="show" title="Add" value="submit"/></h:form> This page has a simple HTML form with three text boxes and a submit button. The text boxes take name, year, and language of a movie and the submit button invokes the "createMovie" method of "movieSessionBean" and then render "show.xhtml". Create "show.xhtml" ("New" -> "Other..." -> "Other" -> "XHTML File") such that it looks like: <head> <title><h1>List of movies</h1></title> </head> <body> <h:form> <h:dataTable value="#{movieSessionBean.movies}" var="m" > <h:column><f:facet name="header">Name</f:facet>#{m.name}</h:column> <h:column><f:facet name="header">Year</f:facet>#{m.year}</h:column> <h:column><f:facet name="header">Language</f:facet>#{m.language}</h:column> </h:dataTable> </h:form> This page shows the name, year, and language of all movies stored in the database so far. The list of movies is returned by "movieSessionBean.movies" property. Now create the "Movie" class such that it looks like: import com.mongodb.BasicDBObject;import com.mongodb.BasicDBObject;import com.mongodb.DBObject;import javax.enterprise.inject.Model;import javax.validation.constraints.Size;/** * @author arun */@Modelpublic class Movie { @Size(min=1, max=20) private String name; @Size(min=1, max=20) private String language; private int year; // getters and setters for "name", "year", "language" public BasicDBObject toDBObject() { BasicDBObject doc = new BasicDBObject(); doc.put("name", name); doc.put("year", year); doc.put("language", language); return doc; } public static Movie fromDBObject(DBObject doc) { Movie m = new Movie(); m.name = (String)doc.get("name"); m.year = (int)doc.get("year"); m.language = (String)doc.get("language"); return m; } @Override public String toString() { return name + ", " + year + ", " + language; }} Other than the usual boilerplate code, the key methods here are "toDBObject" and "fromDBObject". These methods provide a conversion from "Movie" -> "DBObject" and vice versa. The "DBObject" is a MongoDB class that comes as part of the mongo-2.6.3.jar file and which we added to our project earlier.  The complete javadoc for 2.6.3 can be seen here. Notice, this class also uses Bean Validation constraints and will be honored by the JSF layer. Finally, create "MovieSessionBean" stateless EJB with all the business logic such that it looks like: package org.glassfish.samples;import com.mongodb.BasicDBObject;import com.mongodb.DB;import com.mongodb.DBCollection;import com.mongodb.DBCursor;import com.mongodb.DBObject;import com.mongodb.Mongo;import java.net.UnknownHostException;import java.util.ArrayList;import java.util.List;import javax.annotation.PostConstruct;import javax.ejb.Stateless;import javax.inject.Inject;import javax.inject.Named;/** * @author arun */@Stateless@Namedpublic class MovieSessionBean { @Inject Movie movie; DBCollection movieColl; @PostConstruct private void initDB() throws UnknownHostException { Mongo m = new Mongo(); DB db = m.getDB("movieDB"); movieColl = db.getCollection("movies"); if (movieColl == null) { movieColl = db.createCollection("movies", null); } } public void createMovie() { BasicDBObject doc = movie.toDBObject(); movieColl.insert(doc); } public List<Movie> getMovies() { List<Movie> movies = new ArrayList(); DBCursor cur = movieColl.find(); System.out.println("getMovies: Found " + cur.size() + " movie(s)"); for (DBObject dbo : cur.toArray()) { movies.add(Movie.fromDBObject(dbo)); } return movies; }} The database is initialized in @PostConstruct. Instead of a working with a database table, NoSQL databases work with a schema-less document. The "Movie" class is the document in our case and stored in the collection "movies". The collection allows us to perform query functions on all movies. The "getMovies" method invokes "find" method on the collection which is equivalent to the SQL query "select * from movies" and then returns a List<Movie>. Also notice that there is no "persistence.xml" in the project. Right-click and run the project to see the output as: Enter some values in the text box and click on enter to see the result as: If you reached here then you've successfully used MongoDB in your Java EE 6 application, congratulations! Some food for thought and further play ... SQL to MongoDB mapping shows mapping between traditional SQL -> Mongo query language. Tutorial shows fun things you can do with MongoDB. Try the interactive online shell  The cookbook provides common ways of using MongoDB In terms of this project, here are some tasks that can be tried: Encapsulate database management in a JPA persistence provider. Is it even worth it because the capabilities are going to be very different ? MongoDB uses "BSonObject" class for JSON representation, add @XmlRootElement on a POJO and how a compatible JSON representation can be generated. This will make the fromXXX and toXXX methods redundant.

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  • Of transactions and Mongo

    - by Nuri Halperin
    Originally posted on: http://geekswithblogs.net/nuri/archive/2014/05/20/of-transactions-and-mongo-again.aspxWhat's the first thing you hear about NoSQL databases? That they lose your data? That there's no transactions? No joins? No hope for "real" applications? Well, you *should* be wondering whether a certain of database is the right one for your job. But if you do so, you should be wondering that about "traditional" databases as well! In the spirit of exploration let's take a look at a common challenge: You are a bank. You have customers with accounts. Customer A wants to pay B. You want to allow that only if A can cover the amount being transferred. Let's looks at the problem without any context of any database engine in mind. What would you do? How would you ensure that the amount transfer is done "properly"? Would you prevent a "transaction" from taking place unless A can cover the amount? There are several options: Prevent any change to A's account while the transfer is taking place. That boils down to locking. Apply the change, and allow A's balance to go below zero. Charge person A some interest on the negative balance. Not friendly, but certainly a choice. Don't do either. Options 1 and 2 are difficult to attain in the NoSQL world. Mongo won't save you headaches here either. Option 3 looks a bit harsh. But here's where this can go: ledger. See, and account doesn't need to be represented by a single row in a table of all accounts with only the current balance on it. More often than not, accounting systems use ledgers. And entries in ledgers - as it turns out – don't actually get updated. Once a ledger entry is written, it is not removed or altered. A transaction is represented by an entry in the ledger stating and amount withdrawn from A's account and an entry in the ledger stating an addition of said amount to B's account. For sake of space-saving, that entry in the ledger can happen using one entry. Think {Timestamp, FromAccountId, ToAccountId, Amount}. The implication of the original question – "how do you enforce non-negative balance rule" then boils down to: Insert entry in ledger Run validation of recent entries Insert reverse entry to roll back transaction if validation failed. What is validation? Sum up the transactions that A's account has (all deposits and debits), and ensure the balance is positive. For sake of efficiency, one can roll up transactions and "close the book" on transactions with a pseudo entry stating balance as of midnight or something. This lets you avoid doing math on the fly on too many transactions. You simply run from the latest "approved balance" marker to date. But that's an optimization, and premature optimizations are the root of (some? most?) evil.. Back to some nagging questions though: "But mongo is only eventually consistent!" Well, yes, kind of. It's not actually true that Mongo has not transactions. It would be more descriptive to say that Mongo's transaction scope is a single document in a single collection. A write to a Mongo document happens completely or not at all. So although it is true that you can't update more than one documents "at the same time" under a "transaction" umbrella as an atomic update, it is NOT true that there' is no isolation. So a competition between two concurrent updates is completely coherent and the writes will be serialized. They will not scribble on the same document at the same time. In our case - in choosing a ledger approach - we're not even trying to "update" a document, we're simply adding a document to a collection. So there goes the "no transaction" issue. Now let's turn our attention to consistency. What you should know about mongo is that at any given moment, only on member of a replica set is writable. This means that the writable instance in a set of replicated instances always has "the truth". There could be a replication lag such that a reader going to one of the replicas still sees "old" state of a collection or document. But in our ledger case, things fall nicely into place: Run your validation against the writable instance. It is guaranteed to have a ledger either with (after) or without (before) the ledger entry got written. No funky states. Again, the ledger writing *adds* a document, so there's no inconsistent document state to be had either way. Next, we might worry about data loss. Here, mongo offers several write-concerns. Write-concern in Mongo is a mode that marshals how uptight you want the db engine to be about actually persisting a document write to disk before it reports to the application that it is "done". The most volatile, is to say you don't care. In that case, mongo would just accept your write command and say back "thanks" with no guarantee of persistence. If the server loses power at the wrong moment, it may have said "ok" but actually no written the data to disk. That's kind of bad. Don't do that with data you care about. It may be good for votes on a pole regarding how cute a furry animal is, but not so good for business. There are several other write-concerns varying from flushing the write to the disk of the writable instance, flushing to disk on several members of the replica set, a majority of the replica set or all of the members of a replica set. The former choice is the quickest, as no network coordination is required besides the main writable instance. The others impose extra network and time cost. Depending on your tolerance for latency and read-lag, you will face a choice of what works for you. It's really important to understand that no data loss occurs once a document is flushed to an instance. The record is on disk at that point. From that point on, backup strategies and disaster recovery are your worry, not loss of power to the writable machine. This scenario is not different from a relational database at that point. Where does this leave us? Oh, yes. Eventual consistency. By now, we ensured that the "source of truth" instance has the correct data, persisted and coherent. But because of lag, the app may have gone to the writable instance, performed the update and then gone to a replica and looked at the ledger there before the transaction replicated. Here are 2 options to deal with this. Similar to write concerns, mongo support read preferences. An app may choose to read only from the writable instance. This is not an awesome choice to make for every ready, because it just burdens the one instance, and doesn't make use of the other read-only servers. But this choice can be made on a query by query basis. So for the app that our person A is using, we can have person A issue the transfer command to B, and then if that same app is going to immediately as "are we there yet?" we'll query that same writable instance. But B and anyone else in the world can just chill and read from the read-only instance. They have no basis to expect that the ledger has just been written to. So as far as they know, the transaction hasn't happened until they see it appear later. We can further relax the demand by creating application UI that reacts to a write command with "thank you, we will post it shortly" instead of "thank you, we just did everything and here's the new balance". This is a very powerful thing. UI design for highly scalable systems can't insist that the all databases be locked just to paint an "all done" on screen. People understand. They were trained by many online businesses already that your placing of an order does not mean that your product is already outside your door waiting (yes, I know, large retailers are working on it... but were' not there yet). The second thing we can do, is add some artificial delay to a transaction's visibility on the ledger. The way that works is simply adding some logic such that the query against the ledger never nets a transaction for customers newer than say 15 minutes and who's validation flag is not set. This buys us time 2 ways: Replication can catch up to all instances by then, and validation rules can run and determine if this transaction should be "negated" with a compensating transaction. In case we do need to "roll back" the transaction, the backend system can place the timestamp of the compensating transaction at the exact same time or 1ms after the original one. Effectively, once A or B visits their ledger, both transactions would be visible and the overall balance "as of now" would reflect no change.  The 2 transactions (attempted/ reverted) would be visible , since we do actually account for the attempt. Hold on a second. There's a hole in the story: what if several transfers from A to some accounts are registered, and 2 independent validators attempt to compute the balance concurrently? Is there a chance that both would conclude non-sufficient-funds even though rolling back transaction 100 would free up enough for transaction 117 (some random later transaction)? Yes. there is that chance. But the integrity of the business rule is not compromised, since the prime rule is don't dispense money you don't have. To minimize or eliminate this scenario, we can also assign a single validation process per origin account. This may seem non-scalable, but it can easily be done as a "sharded" distribution. Say we have 11 validation threads (or processing nodes etc.). We divide the account number space such that each validator is exclusively responsible for a certain range of account numbers. Sounds cunningly similar to Mongo's sharding strategy, doesn't it? Each validator then works in isolation. More capacity needed? Chop the account space into more chunks. So where  are we now with the nagging questions? "No joins": Huh? What are those for? "No transactions": You mean no cross-collection and no cross-document transactions? Granted - but don't always need them either. "No hope for real applications": well... There are more issues and edge cases to slog through, I'm sure. But hopefully this gives you some ideas of how to solve common problems without distributed locking and relational databases. But then again, you can choose relational databases if they suit your problem.

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  • CodePlex Daily Summary for Sunday, November 21, 2010

    CodePlex Daily Summary for Sunday, November 21, 2010Popular ReleasesMDownloader: MDownloader-0.15.24.6966: Fixed Updater; Fixed minor bugs;Smith Html Editor: Smith Html Editor V0.75: The first public release.MiniTwitter: 1.59: MiniTwitter 1.59 ???? ?? User Streams ????????????????? ?? ?????????????? ???????? ?????????????.NET Extensions - Extension Methods Library for C# and VB.NET: Release 2011.01: Added new extensions for - object.CountLoopsToNull Added new extensions for DateTime: - DateTime.IsWeekend - DateTime.AddWeeks Added new extensions for string: - string.Repeat - string.IsNumeric - string.ExtractDigits - string.ConcatWith - string.ToGuid - string.ToGuidSave Added new extensions for Exception: - Exception.GetOriginalException Added new extensions for Stream: - Stream.Write (overload) And other new methods ... Release as of dotnetpro 01/2011Code Sample from Microsoft: Visual Studio 2010 Code Samples 2010-11-19: Code samples for Visual Studio 2010Prism Training Kit: Prism Training Kit 4.0: Release NotesThis is an updated version of the Prism training Kit that targets Prism 4.0 and added labs for some of the new features of Prism 4.0. This release consists of a Training Kit with Labs on the following topics Modularity Dependency Injection Bootstrapper UI Composition Communication MEF Navigation Note: Take into account that this is a Beta version. If you find any bugs please report them in the Issue Tracker PrerequisitesVisual Studio 2010 Microsoft Word 2...Free language translator and file converter: Free Language Translator 2.2: Starting with version 2.0, the translator encountered a major redesign that uses MEF based plugins and .net 4.0. I've also fixed some bugs and added support for translating subtitles that can show up in video media players. Version 2.1 shows the context menu 'Translate' in Windows Explorer on right click. Version 2.2 has links to start the media file with its associated subtitle. Download the zip file and expand it in a temporary location on your local disk. At a minimum , you should uninstal...Free Silverlight & WPF Chart Control - Visifire: Visifire SL and WPF Charts v3.6.4 Released: Hi, Today we are releasing Visifire 3.6.4 with few bug fixes: * Multi-line Labels were getting clipped while exploding last DataPoint in Funnel and Pyramid chart. * ClosestPlotDistance property in Axis was not behaving as expected. * In DateTime Axis, Chart threw exception on mouse click over PlotArea if there were no DataPoints present in Chart. * ToolTip was not disappearing while changing the DataSource property of the DataSeries at real-time. * Chart threw exception ...Microsoft SQL Server Product Samples: Database: AdventureWorks 2008R2 SR1: Sample Databases for Microsoft SQL Server 2008R2 (SR1)This release is dedicated to the sample databases that ship for Microsoft SQL Server 2008R2. See Database Prerequisites for SQL Server 2008R2 for feature configurations required for installing the sample databases. See Installing SQL Server 2008R2 Databases for step by step installation instructions. The SR1 release contains minor bug fixes to the installer used to create the sample databases. There are no changes to the databases them...VidCoder: 0.7.2: Fixed duplicated subtitles when running multiple encodes off of the same title.Craig's Utility Library: Craig's Utility Library Code 2.0: This update contains a number of changes, added functionality, and bug fixes: Added transaction support to SQLHelper. Added linked/embedded resource ability to EmailSender. Updated List to take into account new functions. Added better support for MAC address in WMI classes. Fixed Parsing in Reflection class when dealing with sub classes. Fixed bug in SQLHelper when replacing the Command that is a select after doing a select. Fixed issue in SQL Server helper with regard to generati...MFCMAPI: November 2010 Release: Build: 6.0.0.1023 Full release notes at SGriffin's blog. If you just want to run the tool, get the executable. If you want to debug it, get the symbol file and the source. The 64 bit build will only work on a machine with Outlook 2010 64 bit installed. All other machines should use the 32 bit build, regardless of the operating system. Facebook BadgeDotNetNuke® Community Edition: 05.06.00: Major HighlightsAdded automatic portal alias creation for single portal installs Updated the file manager upload page to allow user to upload multiple files without returning to the file manager page. Fixed issue with Event Log Email Notifications. Fixed issue where Telerik HTML Editor was unable to upload files to secure or database folder. Fixed issue where registration page is not set correctly during an upgrade. Fixed issue where Sendmail stripped HTML and Links from emails...mVu Mobile Viewer: mVu Mobile Viewer 0.7.10.0: Tube8 fix.EPPlus-Create advanced Excel 2007 spreadsheets on the server: EPPlus 2.8.0.1: EPPlus-Create advanced Excel 2007 spreadsheets on the serverNew Features Improved chart support Different chart-types series on the same chart Support for secondary axis and a lot of new properties Better styling Encryption and Workbook protection Table support Import csv files Array formulas ...and a lot of bugfixesAutoLoL: AutoLoL v1.4.2: Added support for more clients (French and Russian) Settings are now stored sepperatly for each user on a computer Auto Login is much faster now Auto Login detects and handles caps lock state properly nowTailspinSpyworks - WebForms Sample Application: TailspinSpyworks-v0.9: Contains a number of bug fixes and additional tutorial steps as well as complete database implementation details.ASP.NET MVC Project Awesome (jQuery Ajax helpers): 1.3 and demos: It contains a rich set of helpers (controls) that you can use to build highly responsive and interactive Ajax-enabled Web applications. These helpers include Autocomplete, AjaxDropdown, Lookup, Confirm Dialog, Popup Form and Pager tested on mozilla, safari, chrome, opera, ie 9b/8/7/6 new stuff in 1.3 Autocomplete helper Autocomplete and AjaxDropdown can have parentId and be filled with data depending on the value of the parent PopupForm besides Content("ok") on success can also return J...Nearforums - ASP.NET MVC forum engine: Nearforums v4.1: Version 4.1 of the ASP.NET MVC forum engine, with great improvements: TinyMCE added as visual editor for messages (removed CKEditor). Integrated AntiSamy for cleaner html user post and add more prevention to potential injections. Admin status page: a page for the site admin to check the current status of the configuration / db / etc. View Roadmap for more details.UltimateJB: UltimateJB 2.01 PL3 KakaRoto + PSNYes by EvilSperm: Voici une version attendu avec impatience pour beaucoup : - La Version PSNYes pour pouvoir jouer sur le PSN avec une PS3 Jailbreaker. - Pour l'instant le PSNYes n'est disponible qu'avec les PS3 en firmwares 3.41 !!! - La version PL3 KAKAROTO intégre ses dernières modification et prépare a l'intégration du Firmware 3.30 !!! Conclusion : - UltimateJB PSNYes => Valide l'utilisation du PSN : Uniquement compatible avec les 3.41 - ultimateJB DEFAULT => Pas de PSN mais disponible pour les PS3 sui...New Projects1600hours: 1600hours project made in C++.aoleDownload: Aole Series DownloadBills and Cash Flow: Bills and Cash Flow is a simple multi-tenant application to track bills and view cash flowCUDAagrep: CUDAagrep, a fast CUDA implementation of agrep algorithm for approximate DNA/RNA sequence matching.DNN5 Simple Ticketing Module: This is a simple DNN module that accepts trouble tickets and creates a knowledge base for a company.EntityOH: Dynamic Entities ORMFxcop ASP.NET Security Rules: Fxcop ASP.NET security rules This is a set of code analysis rules aiming at analyzing ASP.NET and ASP.NET MVC security against best practices. The rules can be used by Visual Studio 10 Ultimate or FxCop v10 standalone.Head First Design Patterns - Code Examples in C#: This project consists of ported code examples from the book Head First Design Patterns by Eric and Elizabeth Freeman into C#.HTML5 Media Player (Video / Audio): A .NET implementation of the VideoJS and AudioJS open source projects with video and audio support for HTML5. Excellent for use with iPod, iPad, iPhone, etc.Keyword Auction Simulator: This is the project for simulating the keyword auction like Adwords.mAdcOW Office Add-Ins: A collection of handy Office 2010 add-ins.Manga to Epub: Manga to Epub allow you to convert a bunch of images to a single "epub" file, readable on your reader. It handles most of the image types as well as several archives. You have multiple customization options, such as trimming the images in order to remove white borders.Mapua Career Ramp Up: A joint endeavor with the Philippine IT industry leaders and with Mapua School of Information Technology to build an online collaborative database system to Ramp-Up graduating students on their career as future IT Professionals. minami: Minami is a Project what focuse the work on Stability and Features. Is Development in C++minami-dev: Comes later the Description.Mobile RPG: Mobile RPG is five ATtiny85 microcontrollers playing their own RPG characters with a primary MCU acting as GM. Its a fun exercise in autonomous role playing.NetSnoop: Netsnoop allows everyone to get a quick overview over alle the current connections on their workstation.nGso: GSO algorithm implementation based on http://www.springerlink.com/content/y065470472612847/fulltext.pdf Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions K.N. Krishnanand · D. GhoseOpenID Starter Kit for ASP.NET MVC: OpenID Starter Kit for ASP.NET MVC is used to jump start building your web application with ASP.NET MVC with OpenID login system. It is also a good education resource if you want to learn how to implement OpenID into a ASP.NET MVC.Orchard Contact Us Module: Add a contact us page to your Orchard site using this module.Persian Scheduler and Calendar Control: This is a Jalali (Persian or shamsi) calendar and scheduler control in silverlight. Choosing the name 'Jalali' is in honor of 'Hakim omar khayyam' the founder of Jalali calendar. This is under the lisence of 'Barid New Systems' company.Popfly Metadata Generator: Creates Metadata for New project.PurpleStoat: A modular, extensible Silverlight application shell using Prism, Unity and the Enterprise Library, and written in C#. It includes a WCF service which provides AuthZ and logging services to the shell, which are also available to the modules.QL Config Compare Tool: The QL Config Compare Tool enables you to compare two QuakeLive configs. It creates a detailed overview of the differences and is able to save statistics.SQL PHI Identifier: SQL PHI Identifier is an auditing tool for DBA's in a healthcare environment to be able to help identify which databases/tables might hold protected health information (PHI). Using this information a DBA can then take the necessary steps to secure that data adequately.Sqlite ORM: Sqlite ORM is at present a simple Class to Table mapper for Sqlite databases. Tables are created on demand, and designed to future proof for Sharding. Code has 100% unit test coverage.Test shop: Test shopVarMerger - ??????? ????????? ??? ???????? ????????????.: VarMerger - ?????????? (Add-In) ??? MS Word 2007, ??????? ????????? ??????????? ???????? ???????? ??????? ?? ??????, ?????????? ????????? ?????? ? ??????. Visual Studio Add-In For creating Vista Gadget: The absence of tools in Visual Studio that can help developers to create Vista gadgets is strange and disappointing, in my opinion., I want to show you some tools that can help you to develop Vista gadgets using only Visual Studio 2008 or 2010 IDE.Vocal Remover - VST Plugin: VST Plugin Removes vocal form songs using M/S system trick with EQ on mid signal. source in C++ IDE: Visual Studio 2010 Express Edition LIB: Steinberg VST SDK 2.4Windows Phone 7 To Go: A project with demos for Windows Phone 7 FeaturesWinware: Winware is not only an Entity Framework, but beyond.XTengine: Xtengine makes it easier for XNA developers to develop in a compositional manner. You'll no longer have to write specific game classes with deep hierarchies or hardcode to load levels. It's developed in C# with XNA 4.0, with WP7 in mind.

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