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  • "cloud architecture" concepts in a system architecture diagrams

    - by markus
    If you design a distributed application for easy scale-out, or you just want to make use of any of the new “cloud computing” offerings by Amazon, Google or Microsoft, there are some typical concepts or components you usually end up using: distributed blob storage (aka S3) asynchronous, durable message queues (aka SQS) non-Relational-/non-transactional databases (like SimpleDB, Google BigTable, Azure SQL Services) distributed background worker pool load-balanced, edge-service processes handling user requests (often virtualized) distributed caches (like memcached) CDN (content delivery network like Akamai) Now when it comes to design and sketch an architecture that makes use of such patterns, are there any commonly used symbols I could use? Or even a download with some cool Visio stencils? :) It doesn’t have to be a formal system like UML but I think it would be great if there were symbols that everyone knows and understands, like we have commonly used shapes for databases or a documents, for example. I think it would be important to not mix it up with traditional concepts like a normal file system (local or network server/SAN), or a relational database. Simply speaking, I want to be able to draw some conclusions about an application’s scalability or data consistency issues by just looking at the system architecture overview diagram. Update: Thank you very much for your answers. I like the idea of putting a small "cloud symbol" on the traditional symbols. However I leave this thread open just in case someone will find specific symbols (maybe in a book or so) - or uploaded some pimped up Visio stencils ;)

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  • What scalability problems have you solved using a NoSQL data store?

    - by knorv
    NoSQL refers to non-relational data stores that break with the history of relational databases and ACID guarantees. Popular open source NoSQL data stores include: Cassandra (tabular, written in Java, used by Facebook, Twitter, Digg, Rackspace, Mahalo and Reddit) CouchDB (document, written in Erlang, used by Engine Yard and BBC) Dynomite (key-value, written in C++, used by Powerset) HBase (key-value, written in Java, used by Bing) Hypertable (tabular, written in C++, used by Baidu) Kai (key-value, written in Erlang) MemcacheDB (key-value, written in C, used by Reddit) MongoDB (document, written in C++, used by Sourceforge, Github, Electronic Arts and NY Times) Neo4j (graph, written in Java, used by Swedish Universities) Project Voldemort (key-value, written in Java, used by LinkedIn) Redis (key-value, written in C, used by Engine Yard, Github and Craigslist) Riak (key-value, written in Erlang, used by Comcast and Mochi Media) Ringo (key-value, written in Erlang, used by Nokia) Scalaris (key-value, written in Erlang, used by OnScale) ThruDB (document, written in C++, used by JunkDepot.com) Tokyo Cabinet/Tokyo Tyrant (key-value, written in C, used by Mixi.jp (Japanese social networking site)) I'd like to know about specific problems you - the SO reader - have solved using data stores and what NoSQL data store you used. Questions: What scalability problems have you used NoSQL data stores to solve? What NoSQL data store did you use? What database did you use before switching to a NoSQL data store? I'm looking for first-hand experiences, so please do not answer unless you have that.

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  • Pros & Cons of Google App Engine

    - by Rishi
    Pros & Cons of Google App Engine [An Updated List 21st Aug 09] Help me Compile a List of all the Advantages & Disadvantages of Building an Application on the Google App Engine Pros: 1) No Need to buy Servers or Server Space (no maintenance). 2) Makes solving the problem of scaling much easier. Cons: 1) Locked into Google App Engine ?? 2)Developers have read-only access to the filesystem on App Engine. 3)App Engine can only execute code called from an HTTP request (except for scheduled background tasks). 4)Users may upload arbitrary Python modules, but only if they are pure-Python; C and Pyrex modules are not supported. 5)App Engine limits the maximum rows returned from an entity get to 1000 rows per Datastore call. 6)Java applications may only use a subset (The JRE Class White List) of the classes from the JRE standard edition. 7)Java applications cannot create new threads. Known Issues!! http://code.google.com/p/googleappengine/issues/list Hard limits Apps per developer - 10 Time per request - 30 sec Files per app - 3,000 HTTP response size - 10 MB Datastore item size - 1 MB Application code size - 150 MB Pro or Con? App Engine's infrastructure removes many of the system administration and development challenges of building applications to scale to millions of hits. Google handles deploying code to a cluster, monitoring, failover, and launching application instances as necessary. While other services let users install and configure nearly any *NIX compatible software, App Engine requires developers to use Python or Java as the programming language and a limited set of APIs. Current APIs allow storing and retrieving data from a BigTable non-relational database; making HTTP requests; sending e-mail; manipulating images; and caching. Most existing Web applications can't run on App Engine without modification, because they require a relational database.

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  • Why put a DAO layer over a persistence layer (like JDO or Hibernate)

    - by Todd Owen
    Data Access Objects (DAOs) are a common design pattern, and recommended by Sun. But the earliest examples of Java DAOs interacted directly with relational databases -- they were, in essence, doing object-relational mapping (ORM). Nowadays, I see DAOs on top of mature ORM frameworks like JDO and Hibernate, and I wonder if that is really a good idea. I am developing a web service using JDO as the persistence layer, and am considering whether or not to introduce DAOs. I foresee a problem when dealing with a particular class which contains a map of other objects: public class Book { // Book description in various languages, indexed by ISO language codes private Map<String,BookDescription> descriptions; } JDO is clever enough to map this to a foreign key constraint between the "BOOKS" and "BOOKDESCRIPTIONS" tables. It transparently loads the BookDescription objects (using lazy loading, I believe), and persists them when the Book object is persisted. If I was to introduce a "data access layer" and write a class like BookDao, and encapsulate all the JDO code within this, then wouldn't this JDO's transparent loading of the child objects be circumventing the data access layer? For consistency, shouldn't all the BookDescription objects be loaded and persisted via some BookDescriptionDao object (or BookDao.loadDescription method)? Yet refactoring in that way would make manipulating the model needlessly complicated. So my question is, what's wrong with calling JDO (or Hibernate, or whatever ORM you fancy) directly in the business layer? Its syntax is already quite concise, and it is datastore-agnostic. What is the advantage, if any, of encapsulating it in Data Access Objects?

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  • Is there an XML XQuery interface to existing XML files?

    - by xsaero00
    My company is in education industry and we use XML to store course content. We also store some course related information (mostly metainfo) in relational database. Right now we are in the process of switching from our proprietary XML Schema to DocBook 5. Along with the switch we want to move course related information from database to XML files. The reason for this is to have all course data in one place and to put it under Subversion. However, we would like to keep flexibility of the relational database and be able to easily extract specific information about a course from an XML document. XQuery seems to be up to the task so I was researching databases that supports it but so far could not find what I needed. What I basically want, is to have my XML files in a certain directory structure and then on top of this I would like to have a system that would index my files and let me select anything out of any file using XQuery. This way I can have "my cake and eat it too": I will have XQuery interface and still keep my files in plain text and versioned. Is there anything out there at least remotely resembling to what I want? If you think that what I an asking for is nonsense please make an alternative suggestion. On the related note: What XML Databases (preferably native and open source) do you have experience with and what would you recommend?

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  • Simple Database normalization question...

    - by user365531
    Hi all, I have a quick question regarding a database that I am designing and making sure it is normalized... I have a customer table, with a primary key of customerId. It has a StatusCode column that has a code which reflects the customers account status ie. 1 = Open, 2 = Closed, 3 = Suspended etc... Now I would like to have another field in the customer table that flags whether the account is allowed to be suspended or not... certain customers will be automatically suspended if they break there trading terms... others not... so the relevant table fields will be as so: Customers (CustomerId(PK):StatusCode:IsSuspensionAllowed) Now both fields are dependent on the primary key as you can not determine the status or whether suspensions are allowed on a particular customer unless you know the specific customer, except of course when the IsSuspensionAllowed field is set to YES, the the customer should never have a StatusCode of 3 (Suspended). It seems from the above table design it is possible for this to happen unless a check contraint is added to my table. I can't see how another table could be added to the relational design to enforce this though as it's only in the case where IsSuspensionAllowed is set to YES and StatusCode is set to 3 when the two have a dependence on each other. So after my long winded explanation my question is this: Is this a normalization problem and I'm not seeing a relational design that will enforce this... or is it actually just a business rule that should be enforced with a check contraint and the table is in fact still normalized. Cheers, Steve

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  • What database systems should an startup company consider?

    - by Am
    Right now I'm developing the prototype of a web application that aggregates large number of text entries from a large number of users. This data must be frequently displayed back and often updated. At the moment I store the content inside a MySQL database and use NHibernate ORM layer to interact with the DB. I've got a table defined for users, roles, submissions, tags, notifications and etc. I like this solution because it works well and my code looks nice and sane, but I'm also worried about how MySQL will perform once the size of our database reaches a significant number. I feel that it may struggle performing join operations fast enough. This has made me think about non-relational database system such as MongoDB, CouchDB, Cassandra or Hadoop. Unfortunately I have no experience with either. I've read some good reviews on MongoDB and it looks interesting. I'm happy to spend the time and learn if one turns out to be the way to go. I'd much appreciate any one offering points or issues to consider when going with none relational dbms?

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  • Implementation of MVC with SQLite and NSURLConnection, use cases?

    - by user324723
    I'm interested in knowing how others have implemented/designed database & web services in their iphone app and how they simplified it for the entire application. My application is dependent on these services and I can't figure out a efficient way to use them together due to the (semi)complexity of my requirements. My past attempts on combining them haven't been completely successful or at least optimal in my mind. I'm building a database driven iphone app that uses a relational database in sqlite and consumes web services based on missing content or user interaction. Like this hasn't been done before...right? Since I am using a relational database - any web services consumed requires normalization, parsing the result and persisting it to the database before it can be displayed in a table view controller. The applications UI consists of nested(nav controller) table views where a user can select a cell and be taken to the next table view where it attempts to populate the table views data source from the database. If nothing exists in the database then it will send a request via web services to download its content, thus download - parse - persist - query - display. Since the user has the ability to request a refresh of this data it still requires the same process. Quickly describing what I've implemented and tried to run with - 1st attempt - Used a singleton web service class that handled sending web service requests, parsing the result and returning it to the table view controller via delegate protocols. Once the controller received that data it would then be responsible for persisting it to the database and re-returning the result. I didn't like the idea of only preventing the case where the app delegate selector doesn't exists(released) causing the app to crash. 2nd attempt - Used NSNotificationCenter for easy access to both database and web services but later realized it was more complex due to adding and removing observers per view(which isn't advised anyways).

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  • Database for managing large volumes of (system) metrics

    - by symcbean
    Hi, I'm looking at building a system for managing and reporting stats on web page performance. I'll be collecting a lot more stats than are available in the standard log formats (approx 20 metrics) but compared to most types of database applications, the base data structure will be very simple. My problem is that I'll be accumulating a lot of data - in the region of 100,000 records (i.e. sets of metrics) per hour. Of course, resources are very limited! So that its possible to sensibly interact with the data, I'd need to consolidate each metric into one minute bins, broken down by URL, then for anything more than 1 day old, consolidated into 10 minute bins, then at 1 week, hourly bins. At the front end, I want to provide a view (prefereably as plots) of the last hour of data, with the facility for users to drill up/down through defined hierarchies of URLs (which do not always map directly to the hierarchy expressed in the path of the URL) and to view different time frames. Rather than coding all this myself and using a relational database, I was wondering if there were tools available which would facilitate both the management of the data and the reporting. I had a look at Mondrian however I can't see from the documentation I've looked at whether it's possible to drop the more granular information while maintaining the consolidated views of the data. RRDTool looks promising in terms of managing the data consolidation, but seems to be rather limited in terms of querying the dataset as a multi-dimensional/relational database. What else whould I be looking at?

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  • IPad SQLite Push and Pull Data from external MS SQL Server DB

    - by MattyD
    This carries on from my previous post (http://stackoverflow.com/questions/4182664/ipad-app-pull-and-push-relational-data). My plan is that when the ipad application starts I am going to pull data (config data i.e. Departments, Types etc etc relational data that is used across the system) from a webhosted MS SQL Server DB via a webservice and populate it into an SQL Lite DB on the IPad. Then when I load a listing I will pull the data over the line again via a webservice and populate it into the SQL Lite db on the ipad (than just run select commands to populate the listing). My questions are: 1. What is the most efficient way to transfer data across the line via the web? Everyone seems to do it a different way. My idea is that I will have a webService for each type of data pull (e.g. RetrieveContactListing) that will query the db and than convert that data into "something" to send across the line. My question really is what is the "something" that it should be converting into? 2. Everyone talks about odata services. Is this suited for applications where complex read and writes are needed? Ive created a simple iphone app before that talked to an sql server db (i just sent my own structured xml across the line) but now with this app the data calls are going to be a lot larger so efficiency is key.

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  • Storing large numbers of varying size objects on disk

    - by Foredecker
    I need to develop a system for storing large numbers (10's to 100's of thousands) of objects. Each object is email-like - there is a main text body, and several ancillary text fields of limited size. A body will be from a few bytes, to several KB in size. Each item will have a single unique ID (probably a GUID) that identifies it. The store will only be written to when an object is added to it. It will be read often. Deletions will be rare. The data is almost all human readable text so it will be readily compressible. A system that lets me issue the I/Os and mange the memory and caching would be ideal. I'm going to keep the indexes in memory, using it to map indexes to the single (and primary) key for the objects. Once I have the key, then I'll load it from disk, or the cache. The data management system needs to be part of my application - I do not want to depend on OS services. Or separately installed packages. Native (C++) would be best, but a manged (C#) thing would be ok. I believe that a database is an obvious choice, but this needs to be super-fast for look up and loading into memory of an object. I am not experienced with data base tech and I'm concerned that general relational systems will not handle all this variable sized data efficiently. (Note, this has nothing to do with my job - its a personal project.) In your experience, what are the viable alternatives to a traditional relational DB? Or would a DB work well for this?

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  • Oracle Data Integrator 11.1.1.5 Complex Files as Sources and Targets

    - by Alex Kotopoulis
    Overview ODI 11.1.1.5 adds the new Complex File technology for use with file sources and targets. The goal is to read or write file structures that are too complex to be parsed using the existing ODI File technology. This includes: Different record types in one list that use different parsing rules Hierarchical lists, for example customers with nested orders Parsing instructions in the file data, such as delimiter types, field lengths, type identifiers Complex headers such as multiple header lines or parseable information in header Skipping of lines  Conditional or choice fields Similar to the ODI File and XML File technologies, the complex file parsing is done through a JDBC driver that exposes the flat file as relational table structures. Complex files are mapped to one or more table structures, as opposed to the (simple) file technology, which always has a one-to-one relationship between file and table. The resulting set of tables follows the same concept as the ODI XML driver, table rows have additional PK-FK relationships to express hierarchy as well as order values to maintain the file order in the resulting table.   The parsing instruction format used for complex files is the nXSD (native XSD) format that is already in use with Oracle BPEL. This format extends the XML Schema standard by adding additional parsing instructions to each element. Using nXSD parsing technology, the native file is converted into an internal XML format. It is important to understand that the XML is streamed to improve performance; there is no size limitation of the native file based on memory size, the XML data is never fully materialized.  The internal XML is then converted to relational schema using the same mapping rules as the ODI XML driver. How to Create an nXSD file Complex file models depend on the nXSD schema for the given file. This nXSD file has to be created using a text editor or the Native Format Builder Wizard that is part of Oracle BPEL. BPEL is included in the ODI Suite, but not in standalone ODI Enterprise Edition. The nXSD format extends the standard XSD format through nxsd attributes. NXSD is a valid XML Schema, since the XSD standard allows extra attributes with their own namespaces. The following is a sample NXSD schema: <?xml version="1.0"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:nxsd="http://xmlns.oracle.com/pcbpel/nxsd" elementFormDefault="qualified" xmlns:tns="http://xmlns.oracle.com/pcbpel/demoSchema/csv" targetNamespace="http://xmlns.oracle.com/pcbpel/demoSchema/csv" attributeFormDefault="unqualified" nxsd:encoding="US-ASCII" nxsd:stream="chars" nxsd:version="NXSD"> <xsd:element name="Root">         <xsd:complexType><xsd:sequence>       <xsd:element name="Header">                 <xsd:complexType><xsd:sequence>                         <xsd:element name="Branch" type="xsd:string" nxsd:style="terminated" nxsd:terminatedBy=","/>                         <xsd:element name="ListDate" type="xsd:string" nxsd:style="terminated" nxsd:terminatedBy="${eol}"/>                         </xsd:sequence></xsd:complexType>                         </xsd:element>                 </xsd:sequence></xsd:complexType>         <xsd:element name="Customer" maxOccurs="unbounded">                 <xsd:complexType><xsd:sequence>                 <xsd:element name="Name" type="xsd:string" nxsd:style="terminated" nxsd:terminatedBy=","/>                         <xsd:element name="Street" type="xsd:string" nxsd:style="terminated" nxsd:terminatedBy="," />                         <xsd:element name="City" type="xsd:string" nxsd:style="terminated" nxsd:terminatedBy="${eol}" />                         </xsd:sequence></xsd:complexType>                         </xsd:element>                 </xsd:sequence></xsd:complexType> </xsd:element> </xsd:schema> The nXSD schema annotates elements to describe their position and delimiters within the flat text file. The schema above uses almost exclusively the nxsd:terminatedBy instruction to look for the next terminator chars. There are various constructs in nXSD to parse fixed length fields, look ahead in the document for string occurences, perform conditional logic, use variables to remember state, and many more. nXSD files can either be written manually using an XML Schema Editor or created using the Native Format Builder Wizard. Both Native Format Builder Wizard as well as the nXSD language are described in the Application Server Adapter Users Guide. The way to start the Native Format Builder in BPEL is to create a new File Adapter; in step 8 of the Adapter Configuration Wizard a new Schema for Native Format can be created:   The Native Format Builder guides through a number of steps to generate the nXSD based on a sample native file. If the format is complex, it is often a good idea to “approximate” it with a similar simple format and then add the complex components manually.  The resulting *.xsd file can be copied and used as the format for ODI, other BPEL constructs such as the file adapter definition are not relevant for ODI. Using this technique it is also possible to parse the same file format in SOA Suite and ODI, for example using SOA for small real-time messages, and ODI for large batches. This nXSD schema in this example describes a file with a header row containing data and 3 string fields per row delimited by commas, for example: Redwood City Downtown Branch, 06/01/2011 Ebeneezer Scrooge, Sandy Lane, Atherton Tiny Tim, Winton Terrace, Menlo Park The ODI Complex File JDBC driver exposes the file structure through a set of relational tables with PK-FK relationships. The tables for this example are: Table ROOT (1 row): ROOTPK Primary Key for root element SNPSFILENAME Name of the file SNPSFILEPATH Path of the file SNPSLOADDATE Date of load Table HEADER (1 row): ROOTFK Foreign Key to ROOT record ROWORDER Order of row in native document BRANCH Data BRANCHORDER Order of Branch within row LISTDATE Data LISTDATEORDER Order of ListDate within row Table ADDRESS (2 rows): ROOTFK Foreign Key to ROOT record ROWORDER Order of row in native document NAME Data NAMEORDER Oder of Name within row STREET Data STREETORDER Order of Street within row CITY Data CITYORDER Order of City within row Every table has PK and/or FK fields to reflect the document hierarchy through relationships. In this example this is trivial since the HEADER and all CUSTOMER records point back to the PK of ROOT. Deeper nested documents require this to identify parent elements. All tables also have a ROWORDER field to define the order of rows, as well as order fields for each column, in case the order of columns varies in the original document and needs to be maintained. If order is not relevant, these fields can be ignored. How to Create an Complex File Data Server in ODI After creating the nXSD file and a test data file, and storing it on the local file system accessible to ODI, you can go to the ODI Topology Navigator to create a Data Server and Physical Schema under the Complex File technology. This technology follows the conventions of other ODI technologies and is very similar to the XML technology. The parsing settings such as the source native file, the nXSD schema file, the root element, as well as the external database can be set in the JDBC URL: The use of an external database defined by dbprops is optional, but is strongly recommended for production use. Ideally, the staging database should be used for this. Also, when using a complex file exclusively for read purposes, it is recommended to use the ro=true property to ensure the file is not unnecessarily synchronized back from the database when the connection is closed. A data file is always required to be present  at the filename path during design-time. Without this file, operations like testing the connection, reading the model data, or reverse engineering the model will fail.  All properties of the Complex File JDBC Driver are documented in the Oracle Fusion Middleware Connectivity and Knowledge Modules Guide for Oracle Data Integrator in Appendix C: Oracle Data Integrator Driver for Complex Files Reference. David Allan has created a great viewlet Complex File Processing - 0 to 60 which shows the creation of a Complex File data server as well as a model based on this server. How to Create Models based on an Complex File Schema Once physical schema and logical schema have been created, the Complex File can be used to create a Model as if it were based on a database. When reverse-engineering the Model, data stores(tables) for each XSD element of complex type will be created. Use of complex files as sources is straightforward; when using them as targets it has to be made sure that all dependent tables have matching PK-FK pairs; the same applies to the XML driver as well. Debugging and Error Handling There are different ways to test an nXSD file. The Native Format Builder Wizard can be used even if the nXSD wasn’t created in it; it will show issues related to the schema and/or test data. In ODI, the nXSD  will be parsed and run against the existing test XML file when testing a connection in the Dataserver. If either the nXSD has an error or the data is non-compliant to the schema, an error will be displayed. Sample error message: Error while reading native data. [Line=1, Col=5] Not enough data available in the input, when trying to read data of length "19" for "element with name D1" from the specified position, using "style" as "fixedLength" and "length" as "". Ensure that there is enough data from the specified position in the input. Complex File FAQ Is the size of the native file limited by available memory? No, since the native data is streamed through the driver, only the available space in the staging database limits the size of the data. There are limits on individual field sizes, though; a single large object field needs to fit in memory. Should I always use the complex file driver instead of the file driver in ODI now? No, use the file technology for all simple file parsing tasks, for example any fixed-length or delimited files that just have one row format and can be mapped into a simple table. Because of its narrow assumptions the ODI file driver is easy to configure within ODI and can stream file data without writing it into a database. The complex file driver should be used whenever the use case cannot be handled through the file driver. Are we generating XML out of flat files before we write it into a database? We don’t materialize any XML as part of parsing a flat file, either in memory or on disk. The data produced by the XML parser is streamed in Java objects that just use XSD-derived nXSD schema as its type system. We use the nXSD schema because is the standard for describing complex flat file metadata in Oracle Fusion Middleware, and enables users to share schemas across products. Is the nXSD file interchangeable with SOA Suite? Yes, ODI can use the same nXSD files as SOA Suite, allowing mixed use cases with the same data format. Can I start the Native Format Builder from the ODI Studio? No, the Native Format Builder has to be started from a JDeveloper with BPEL instance. You can get BPEL as part of the SOA Suite bundle. Users without SOA Suite can manually develop nXSD files using XSD editors. When is the database data written back to the native file? Data is synchronized using the SYNCHRONIZE and CREATE FILE commands, and when the JDBC connection is closed. It is recommended to set the ro or read_only property to true when a file is exclusively used for reading so that no unnecessary write-backs occur. Is the nXSD metadata part of the ODI Master or Work Repository? No, the data server definition in the master repository only contains the JDBC URL with file paths; the nXSD files have to be accessible on the file systems where the JDBC driver is executed during production, either by copying or by using a network file system. Where can I find sample nXSD files? The Application Server Adapter Users Guide contains nXSD samples for various different use cases.

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  • Designing a web application to scale

    - by Fahim Akhter
    Hi, While designing a web application facebook application to be precise. Which can spike and increase rapidly because of it vitality and is right intensive. What point should one keep in mind while designing the DB. For example what things should I leave room for if I need to shard or have a Master/Slave combination later (with memcache) Considering I use Relational Database with mySQL

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  • High availability for databases (DRBD + GFS)?

    - by EvanAlm
    Does it work to have like an MySQL (or any other relational database) on the GFS (with DRBD) and have multiple nodes reading and writing to it? Is that the "best" way of providing a HA database/application setup if so? Is RHEL (cluster suite) a good way to set up this? (or centos)

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  • MySQL for SQL Server DBAs

    - by SQL3D
    I've been tasked with taking over the administration of a MySQL installation (running on Red Hat Linux) that will become fairly critical to our business in the near future. I was wondering if anyone could recommend some resources in regards to administering MySQL for DBAs already experienced with other relational database (SQL Server and some Oracle in my case). Specifically I'm looking for information around disaster recovery as well as high availability to start with, but I do want to get well rounded with the entire system. Thanks in advance, Dan

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  • SQLAuthority News – Best Practices for Data Warehousing with SQL Server 2008 R2

    - by pinaldave
    An integral part of any BI system is the data warehouse—a central repository of data that is regularly refreshed from the source systems. The new data is transferred at regular intervals  by extract, transform, and load (ETL) processes. This whitepaper talks about what are best practices for Data Warehousing. This whitepaper discusses ETL, Analysis, Reporting as well relational database. The main focus of this whitepaper is on mainly ‘architecture’ and ‘performance’. Download Best Practices for Data Warehousing with SQL Server 2008 R2 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • 100,000 complex structures that are accessed frequently by 100,000 users

    - by Saad
    If you are required to store 100,000 complex structures that are accessed frequently by 100,000 users, which of the following solutions would you use and why? Memcached, In-code python objects, Redis, or a relational database (MySQL). With the little knowledge that I have I think that memcached and In-code python object will not store permanent persistent data. so they don't qualify as the right answer for such a problem. And for complex data structures its best to use Redis. Please correct me if I am wrong.

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  • Top 10 Tips & Tricks for Oracle SQL Developer

    - by thatjeffsmith
    Being a short week due to the holiday, and with everyone enjoying their Summer vacations (apologies Southern Hemispherians), I reckoned it was a great time to do one of those lazy recap-Top 10-Reader’s Digest type posts. I’ve been sharing 1-3 tips or ‘tricks’ a week since I started blogging about SQL Developer, and I have more than enough content to write a book. But since I’m lazy, I’m just going to compile a list of my favorite ‘must know’ tips instead. I always have to leave out a few tips when I do my presentations, so now I can refer back to this list to make sure I’m not forgetting anything. So without further ado… 1. Configure Your Preferences Yes, there are a LOT of options. But you don’t need to worry about all of them just yet. I do recommend you take a quick look at these ones in particular. Whether you’re new to the tool or have been using it for 5 years, don’t overlook these settings! 2. Disable Extensions You Aren’t Using If you’re not using Data Miner, or if you’re not working on a Migration – disable those extensions! SQL Developer will run leaner & meaner, plus the user interface will be a bit more simplified making the tool easier to navigate as well. 3. SQL Recall via Keyboard Access your history via the keyboard! Cycle through your recent SQL statements just using these magic key strokes! Ctrl+Up or Ctrl+Down. 4. Format Your Query Output Directly to CSV, XML, HTML, etc Have the query results pre-formatted in the format of your choice! Too lazy to run the Export wizard for your query result sets? Just add the SQL Developer output hints to your statement and have the output auto-magically formatted to the style of your choice! 5. Drag & Drop Multiple Tables to the Worksheet SQL Developer will auto-join the related objects. You can then toggle over to the Query Builder to toggle off the columns you don’t want to query. I guarantee this tip will save you time if you’re joining 3 or more tables! 6. Drag & Drop Multiple Tables to a Relational Model A pretty picture is worth a few dozen DDL scripts? SQL Developer does data modeling! If you ctrl-drag a table to a model, it will take that table and any related tables and reverse engineer them to a relational model! You can then print it out or export it to HTML, PDF, etc. 7. View Your PL/SQL Execution Output Automatically Function returns a refcursor? Procedure had 3 out parameters? When you run these programs via the Procedure Editor, we automatically capture the output and place them into one or more data grids for you to browse. 8. Disable Automatic Code Insight and Use It On-Demand Code Editor – Completion Insight – Enable Completion Auto-Popup (Keyword being Auto) Some folks really don’t like it when their IDEs or word-processors try to do ‘too much’ for them. Thankfully SQL Developer allows you to either increase the delay before it attempts to auto-complete your text OR to disable the automatic bit. Instead, you can invoke it on-demand. 9. Interactive Debugging – Change Your Variable Values as You Step Through Your PLSQL Watches aren’t just for watching. You can actually interact with your programs and ‘see what happens’ when X = 256 instead of 1. 10. Ditch the Tree View for the Schema Browser There’s nothing wrong with the Connection tree for browsing your database objects. But some folks just can’t seem to get comfortable with it. So, we built them a Schema Browser that uses a drop down control instead for changing up your schema and object types. Already Know This Stuff, Want More? Just check out my SQL Developer resource page, it’s one of the main links on the top of this page. Or if you can’t find something, just drop me a note in the form of a comment on this page and I’ll do my best to find it or write it for you.

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  • Design Book–Dimensional or No Dimensional, that is..the question

    - by drsql
    So, it is right there in the title of the book “Relational Database Design” etc (the title is kinda long :)  But as I consider what to cover and, conversely, what not to cover, dimensional design inevitably pops up. So I am considering including it in the book. One thing I try to do is to cover topics to a level where you can start using it immediately, and I am not sure that I could get a deep enough coverage of the subject to do that. I don’t really feel like it has to be the definitive source...(read more)

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  • To ORM or Not to ORM. That is the question&hellip;

    - by Patrick Liekhus
    UPDATE:  Thanks for the feedback and comments.  I have adjusted my table below with your recommendations.  I had missed a point or two. I wanted to do a series on creating an entire project using the EDMX XAF code generation and the SpecFlow BDD Easy Test tools discussed in my earlier posts, but I thought it would be appropriate to start with a simple comparison and reasoning on why I choose to use these tools. Let’s start by defining the term ORM, or Object-Relational Mapping.  According to Wikipedia it is defined as the following: Object-relational mapping (ORM, O/RM, and O/R mapping) in computer software is a programming technique for converting data between incompatible type systems in object-oriented programming languages. This creates, in effect, a "virtual object database" that can be used from within the programming language. Why should you care?  Basically it allows you to map your business objects in code to their persistence layer behind them. And better yet, why would you want to do this?  Let me outline it in the following points: Development speed.  No more need to map repetitive tasks query results to object members.  Once the map is created the code is rendered for you. Persistence portability.  The ORM knows how to map SQL specific syntax for the persistence engine you choose.  It does not matter if it is SQL Server, Oracle and another database of your choosing. Standard/Boilerplate code is simplified.  The basic CRUD operations are consistent and case use database metadata for basic operations. So how does this help?  Well, let’s compare some of the ORM tools that I have used and/or researched.  I have been interested in ORM for some time now.  My ORM of choice for a long time was NHibernate and I still believe it has a strong case in some business situations.  However, you have to take business considerations into account and the law of diminishing returns.  Because of these two factors, my recent activity and experience has been around DevExpress eXpress Persistence Objects (XPO).  The primary reason for this is because they have the DevExpress eXpress Application Framework (XAF) that sits on top of XPO.  With this added value, the data model can be created (either database first of code first) and the Web and Windows client can be created from these maps.  While out of the box they provide some simple list and detail screens, you can verify easily extend and modify these to your liking.  DevExpress has done a tremendous job of providing enough framework while also staying out of the way when you need to extend it.  This sounds worse than it really is.  What I mean by this is that if you choose to follow DevExpress coding style and recommendations, the hooks and extension points provided allow you to do some pretty heavy lifting while also not worrying about the basics. I have put together a list of the top features that I have used to compare the limited list of ORM’s that I have exposure with.  Again, the biggest selling point in my opinion is that XPO is just a solid as any of the other ORM’s but with the added layer of XAF they become unstoppable.  And then couple that with the EDMX modeling tools and code generation, it becomes a no brainer. Designer Features Entity Framework NHibernate Fluent w/ Nhibernate Telerik OpenAccess DevExpress XPO DevExpress XPO/XAF plus Liekhus Tools Uses XML to map relationships - Yes - - -   Visual class designer interface Yes - - - - Yes Management integrated w/ Visual Studio Yes - - Yes - Yes Supports schema first approach Yes - - Yes - Yes Supports model first approach Yes - - Yes Yes Yes Supports code first approach Yes Yes Yes Yes Yes Yes Attribute driven coding style Yes - Yes - Yes Yes                 I have a very small team and limited resources with a lot of responsibilities.  In order to keep up with our customers, we must rely on tools like these.  We use the EDMX tool so that we can create a visual representation of the applications with our customers.  Second, we rely on the code generation so that we can focus on the business problems at hand and not whether a field is mapped correctly.  This keeps us from requiring as many junior level developers on our team.  I have also worked on multiple teams where they believed in writing their own “framework”.  In my experiences and opinion this is not the route to take unless you have a team dedicated to supporting just the framework.  Each time that I have worked on custom frameworks, the framework eventually becomes old, out dated and full of “performance” enhancements specific to one or two requirements.  With an ORM, there are a lot smarter people than me working on the bigger issue of persistence and performance.  Again, my recommendation would be to use an available framework and get to working on your business domain problems.  If your coding is not making money for you, why are you working on it?  Do you really need to be writing query to object member code again and again? Thanks

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  • Design Book–Fourth(last) Section (Physical Abstraction Optimization)

    - by drsql
    In this last section of the book, we will shift focus to the physical abstraction layer optimization. By this I mean the little bits and pieces of the design that is specifically there for performance and are actually part of the relational engine (read: the part of the SQL Server experience that ideally is hidden from you completely, but in 2010 reality it isn’t quite so yet.  This includes all of the data structures like database, files, etc; the optimizer; some coding, etc. In my mind, this...(read more)

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  • SQLAuthority News – Download Whitepaper Using SharePoint List Data in PowerPivot

    - by pinaldave
    One of the many features of Microsoft SQL Server PowerPivot is the range of data sources that can be used to import data. Anything, from Microsoft SQL Server relational databases, Oracle databases, and Microsoft Access databases, to text documents, can be used as data sources in PowerPivot. In this paper, I explain one of the new and upcoming data sources that people are excited about – SharePoint list data in the form of Atom feeds. This white paper goes on to explain the different ways you can import SharePoint list data into PowerPivot, what types of lists are supported, various components that need to be installed to use this feature, and where to get those components. Download and read this whitepaper. Note: Abstract is taken from MSDN Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • NoSQL Memcached API for MySQL: Latest Updates

    - by Mat Keep
    With data volumes exploding, it is vital to be able to ingest and query data at high speed. For this reason, MySQL has implemented NoSQL interfaces directly to the InnoDB and MySQL Cluster (NDB) storage engines, which bypass the SQL layer completely. Without SQL parsing and optimization, Key-Value data can be written directly to MySQL tables up to 9x faster, while maintaining ACID guarantees. In addition, users can continue to run complex queries with SQL across the same data set, providing real-time analytics to the business or anonymizing sensitive data before loading to big data platforms such as Hadoop, while still maintaining all of the advantages of their existing relational database infrastructure. This and more is discussed in the latest Guide to MySQL and NoSQL where you can learn more about using the APIs to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database The native Memcached API is part of the MySQL 5.6 Release Candidate, and is already available in the GA release of MySQL Cluster. By using the ubiquitous Memcached API for writing and reading data, developers can preserve their investments in Memcached infrastructure by re-using existing Memcached clients, while also eliminating the need for application changes. Speed, when combined with flexibility, is essential in the world of growing data volumes and variability. Complementing NoSQL access, support for on-line DDL (Data Definition Language) operations in MySQL 5.6 and MySQL Cluster enables DevOps teams to dynamically update their database schema to accommodate rapidly changing requirements, such as the need to capture additional data generated by their applications. These changes can be made without database downtime. Using the Memcached interface, developers do not need to define a schema at all when using MySQL Cluster. Lets look a little more closely at the Memcached implementations for both InnoDB and MySQL Cluster. Memcached Implementation for InnoDB The Memcached API for InnoDB is previewed as part of the MySQL 5.6 Release Candidate. As illustrated in the following figure, Memcached for InnoDB is implemented via a Memcached daemon plug-in to the mysqld process, with the Memcached protocol mapped to the native InnoDB API. Figure 1: Memcached API Implementation for InnoDB With the Memcached daemon running in the same process space, users get very low latency access to their data while also leveraging the scalability enhancements delivered with InnoDB and a simple deployment and management model. Multiple web / application servers can remotely access the Memcached / InnoDB server to get direct access to a shared data set. With simultaneous SQL access, users can maintain all the advanced functionality offered by InnoDB including support for Foreign Keys, XA transactions and complex JOIN operations. Benchmarks demonstrate that the NoSQL Memcached API for InnoDB delivers up to 9x higher performance than the SQL interface when inserting new key/value pairs, with a single low-end commodity server supporting nearly 70,000 Transactions per Second. Figure 2: Over 9x Faster INSERT Operations The delivered performance demonstrates MySQL with the native Memcached NoSQL interface is well suited for high-speed inserts with the added assurance of transactional guarantees. You can check out the latest Memcached / InnoDB developments and benchmarks here You can learn how to configure the Memcached API for InnoDB here Memcached Implementation for MySQL Cluster Memcached API support for MySQL Cluster was introduced with General Availability (GA) of the 7.2 release, and joins an extensive range of NoSQL interfaces that are already available for MySQL Cluster Like Memcached, MySQL Cluster provides a distributed hash table with in-memory performance. MySQL Cluster extends Memcached functionality by adding support for write-intensive workloads, a full relational model with ACID compliance (including persistence), rich query support, auto-sharding and 99.999% availability, with extensive management and monitoring capabilities. All writes are committed directly to MySQL Cluster, eliminating cache invalidation and the overhead of data consistency checking to ensure complete synchronization between the database and cache. Figure 3: Memcached API Implementation with MySQL Cluster Implementation is simple: 1. The application sends reads and writes to the Memcached process (using the standard Memcached API). 2. This invokes the Memcached Driver for NDB (which is part of the same process) 3. The NDB API is called, providing for very quick access to the data held in MySQL Cluster’s data nodes. The solution has been designed to be very flexible, allowing the application architect to find a configuration that best fits their needs. It is possible to co-locate the Memcached API in either the data nodes or application nodes, or alternatively within a dedicated Memcached layer. The benefit of this flexible approach to deployment is that users can configure behavior on a per-key-prefix basis (through tables in MySQL Cluster) and the application doesn’t have to care – it just uses the Memcached API and relies on the software to store data in the right place(s) and to keep everything synchronized. Using Memcached for Schema-less Data By default, every Key / Value is written to the same table with each Key / Value pair stored in a single row – thus allowing schema-less data storage. Alternatively, the developer can define a key-prefix so that each value is linked to a pre-defined column in a specific table. Of course if the application needs to access the same data through SQL then developers can map key prefixes to existing table columns, enabling Memcached access to schema-structured data already stored in MySQL Cluster. Conclusion Download the Guide to MySQL and NoSQL to learn more about NoSQL APIs and how you can use them to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database See how to build a social app with MySQL Cluster and the Memcached API from our on-demand webinar or take a look at the docs Don't hesitate to use the comments section below for any questions you may have 

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