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  • NetBackup-pal is muködik az Oracle Database 11gR2 mentés Exadata V2 környezetben

    - by Fekete Zoltán
    A Veritas NetBackup szoftverrel is menthetok az Oracle 11gR2 adatbázisok az Oracle Enterprise Linux-on is (RMAN-t használva), 64-bites környezetben. A dokumentumokban a Red Hat-re vonatkozó infót kell keresnünk, mivel http://seer.entsupport.symantec.com/docs/337048.htm szerint "Oracle Enterprise Linux (OEL)" Supported based on NetBackup Red Hat Enterprise Linux 4.x/5.x Client, Server, and Oracle Agent support. BMR is not supported. NetBackup compatibility listák: http://seer.entsupport.symantec.com/docs/303344.htm - A NetBackup 7 kompatibilis az Oracle Exadata V2-vel: http://seer.entsupport.symantec.com/docs/340295.htm - A NetBackup 6.x verziókra telepíteni kell a következo patch-et: NB_6.5.5_ET1940073_1_347227.zip is a NetBackup 6.5.5 EEB (Emergency Engineering Binary) for Oracle Clients. http://seer.entsupport.symantec.com/docs/347227.htm és http://support.veritas.com/docs/279048.

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  • Sun Fire X4800 M2 Delivers World Record TPC-C for x86 Systems

    - by Brian
    Oracle's Sun Fire X4800 M2 server equipped with eight 2.4 GHz Intel Xeon Processor E7-8870 chips obtained a result of 5,055,888 tpmC on the TPC-C benchmark. This result is a world record for x86 servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning. The Sun Fire X4800 M2 server delivered a new x86 TPC-C world record of 5,055,888 tpmC with a price performance of $0.89/tpmC using Oracle Database 11g Release 2. This configuration is available 06/26/12. The Sun Fire X4800 M2 server delivers 3.0x times better performance than the next 8-processor result, an IBM System p 570 equipped with POWER6 processors. The Sun Fire X4800 M2 server has 3.1x times better price/performance than the 8-processor 4.7GHz POWER6 IBM System p 570. The Sun Fire X4800 M2 server has 1.6x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors. This is the first TPC-C result on any system using eight Intel Xeon Processor E7-8800 Series chips. The Sun Fire X4800 M2 server is the first x86 system to get over 5 million tpmC. The Oracle solution utilized Oracle Linux operating system and Oracle Database 11g Enterprise Edition Release 2 with Partitioning to produce the x86 world record TPC-C benchmark performance. Performance Landscape Select TPC-C results (sorted by tpmC, bigger is better) System p/c/t tpmC Price/tpmC Avail Database MemorySize Sun Fire X4800 M2 8/80/160 5,055,888 0.89 USD 6/26/2012 Oracle 11g R2 4 TB IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 DB2 ESE 9.7 3 TB IBM x3850 X5 4/32/64 2,308,099 0.60 USD 5/20/2011 DB2 ESE 9.7 1.5 TB IBM System p 570 8/16/32 1,616,162 3.54 USD 11/21/2007 DB2 9.0 2 TB p/c/t - processors, cores, threads Avail - availability date Oracle and IBM TPC-C Response times System tpmC Response Time (sec) New Order 90th% Response Time (sec) New Order Average Sun Fire X4800 M2 5,055,888 0.210 0.166 IBM x3850 X5 3,014,684 0.500 0.272 Ratios - Oracle Better 1.6x 1.4x 1.3x Oracle uses average new order response time for comparison between Oracle and IBM. Graphs of Oracle's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page. Configuration Summary and Results Hardware Configuration: Server Sun Fire X4800 M2 server 8 x 2.4 GHz Intel Xeon Processor E7-8870 4 TB memory 8 x 300 GB 10K RPM SAS internal disks 8 x Dual port 8 Gbs FC HBA Data Storage 10 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 10 x 2 TB 7.2K RPM 3.5" SAS disks 2 x Sun Storage F5100 Flash Array storage (1.92 TB each) 1 x Brocade 5300 switches Redo Storage 2 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 11 x 2 TB 7.2K RPM 3.5" SAS disks Clients 8 x Sun Fire X4170 M2 servers, each with 2 x 3.06 GHz Intel Xeon X5675 processors 48 GB memory 2 x 300 GB 10K RPM SAS disks Software Configuration: Oracle Linux (Sun Fire 4800 M2) Oracle Solaris 11 Express (COMSTAR for Sun Fire X4270 M2) Oracle Solaris 10 9/10 (Sun Fire X4170 M2) Oracle Database 11g Release 2 Enterprise Edition with Partitioning Oracle iPlanet Web Server 7.0 U5 Tuxedo CFS-R Tier 1 Results: System: Sun Fire X4800 M2 tpmC: 5,055,888 Price/tpmC: 0.89 USD Available: 6/26/2012 Database: Oracle Database 11g Cluster: no New Order Average Response: 0.166 seconds Benchmark Description TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses. Key Points and Best Practices Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance. COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules. Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark. See Also Oracle Press Release -- Sun Fire X4800 M2 TPC-C Executive Summary tpc.org Complete Sun Fire X4800 M2 TPC-C Full Disclosure Report tpc.org Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page Sun Fire X4800 M2 Server oracle.com OTN Oracle Linux oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage F5100 Flash Array oracle.com OTN Disclosure Statement TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). Sun Fire X4800 M2 (8/80/160) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 5,055,888 tpmC, $0.89 USD/tpmC, available 6/26/2012. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM System p 570 (8/16/32) with DB2 9.0, 1,616,162 tpmC, $3.54 USD/tpmC, available 11/21/2007. Source: http://www.tpc.org/tpcc, results as of 7/15/2011.

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  • Visual Database Design Application

    - by tshauck
    Hi, I'm getting to the point where the applications I write need a little more structure during the planning phase. So I'd like to use some sort of visual tool to design the tables and relationships. I'm on a mac and have tried mysql workbench, but I find it buggy and a bit bloated for my intended use. Is something that I could design in that has a nice interface and is primarily a tool for visual design? Thanks

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  • Protect Data and Save Money? Learn How Best-in-Class Organizations do Both

    - by roxana.bradescu
    Databases contain nearly two-thirds of the sensitive information that must be protected as part of any organization's overall approach to security, risk management, and compliance. Solutions for protecting data housed in databases vary from encrypting data at the application level to defense-in-depth protection of the database itself. So is there a difference? Absolutely! According to new research from the Aberdeen Group, Best-in-Class organizations experience fewer data breaches and audit deficiencies - at lower cost -- by deploying database security solutions. And the results are dramatic: Aberdeen found that organizations encrypting data within their databases achieved 30% fewer data breaches and 15% greater audit efficiency with 34% less total cost when compared to organizations encrypting data within applications. Join us for a live webcast with Derek Brink, Vice President and Research Fellow at the Aberdeen Group, next week to learn how your organization can become Best-in-Class.

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  • Is data integrity possible without normalization?

    - by shuniar
    I am working on an application that requires the storage of location information such as city, state, zip code, latitude, and longitude. I would like to ensure: Location data is accurate Detroit, CA Detroit IS NOT in California Detroit, MI Detroit IS in Michigan Cities and states are spelled correctly California not Calefornia Detroit not Detriot Cities and states are named consistently Valid: CA Detroit Invalid: Cali california DET d-town The D Also, since city/zip data is not guaranteed to be static, updating this data in a normalized fashion could be difficult, whereas it could be implemented as a de facto location if it is denormalized. A couple thoughts that come to mind: A collection of reference tables that store a list of all states and the most common cities and zip codes that can grow over time. It would search the database for an exact or similar match and recommend corrections. Use some sort of service to validate the location data before it is stored in the database. Is it possible to fulfill these requirements without normalization, and if so, should I denormalize this data?

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  • Geek City: Clearing Plans for a Single Database

    - by Kalen Delaney
    I know Friday afternoon isn't the best time for blogging, as everyone is going home now, and by Monday morning, this post will be old news. But I'm not shutting down just yet, and a something came up this week that I just realized not everybody knew about, so I decided to blog it. Many (or most?) of you are aware that you can clear all cached plans using DBCC FREEPROCCACHE. In addition, there are certain configuration options, for which changing their values will cause all plans in cache to be removed....(read more)

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  • Here Comes the FY11 Earmarks Database

    - by Mike C
    I'm really interested in politics (don't worry, I'm not going to start bashing politicians and hammering you with political rage). The point is when the U.S. FY11 Omnibus Spending Bill (the bill to fund the U.S. Government for another year) was announced it piqued my interest. I'm fascinated by " earmarks " (also affectionally known as " pork "). For those who aren't familiar with U.S. politics, "earmark" is a slang term for "Congressionally Directed Spending". It's basically the set of provisions...(read more)

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  • Geek City: Clearing Plans for a Single Database

    - by Kalen Delaney
    I know Friday afternoon isn't the best time for blogging, as everyone is going home now, and by Monday morning, this post will be old news. But I'm not shutting down just yet, and a something came up this week that I just realized not everybody knew about, so I decided to blog it. Many (or most?) of you are aware that you can clear all cached plans using DBCC FREEPROCCACHE. In addition, there are certain configuration options, for which changing their values will cause all plans in cache to be removed....(read more)

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  • Storing Attendance Data in database

    - by Ali Abbas
    So i have to store daily attendance of employees of my organisation from my application . The part where I need some help is, the efficient way to store attendance data. After some research and brain storming I came up with some approaches . Could you point me out which one is the best and any unobvious ill effects of the mentioned approaches. The approaches are as follows Create a single table for whole organisation and store empid,date,presentstatus as a row for every employee everyday. Create a single table for whole organisation and store a single row for each day with a comma delimited string of empids which are absent. I will generate the string on my application. Create different tables for each department and follow the 1 method. Please share your views and do mention any other good methods

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  • Database Administration as a Service

    A DBA should provide two things, a service and leadership. For Grant Fritchey, it was whilst serving a role in the Scouts of America that he had his epiphany. Creative chaos and energy, if tactfully harnessed and directed, led to effective ways to perform team-based tasks. Then he wondered why these skills couldn't be applied to the workplace. Are we DBAs doing it wrong in the way we interact with our co-workers?

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  • Unexpected advantage of Engineered Systems

    - by user12244672
    It's not surprising that Engineered Systems accelerate the debugging and resolution of customer issues. But what has surprised me is just how much faster issue resolution is with Engineered Systems such as SPARC SuperCluster. These are powerful, complex, systems used by customers wanting extreme database performance, app performance, and cost saving server consolidation. A SPARC SuperCluster consists or 2 or 4 powerful T4-4 compute nodes, 3 or 6 extreme performance Exadata Storage Cells, a ZFS Storage Appliance 7320 for general purpose storage, and ultra fast Infiniband switches.  Each with its own firmware. It runs Solaris 11, Solaris 10, 11gR2, LDoms virtualization, and Zones virtualization on the T4-4 compute nodes, a modified version of Solaris 11 in the ZFS Storage Appliance, a modified and highly tuned version of Oracle Linux running Exadata software on the Storage Cells, another Linux derivative in the Infiniband switches, etc. It has an Infiniband data network between the components, a 10Gb data network to the outside world, and a 1Gb management network. And customers can run whatever middleware and apps they want on it, clustered in whatever way they want. In one word, powerful.  In another, complex. The system is highly Engineered.  But it's designed to run general purpose applications. That is, the physical components, configuration, cabling, virtualization technologies, switches, firmware, Operating System versions, network protocols, tunables, etc. are all preset for optimum performance and robustness. That improves the customer experience as what the customer runs leverages our technical know-how and best practices and is what we've tested intensely within Oracle. It should also make debugging easier by fixing a large number of variables which would otherwise be in play if a customer or Systems Integrator had assembled such a complex system themselves from the constituent components.  For example, there's myriad network protocols which could be used with Infiniband.  Myriad ways the components could be interconnected, myriad tunable settings, etc. But what has really surprised me - and I've been working in this area for 15 years now - is just how much easier and faster Engineered Systems have made debugging and issue resolution. All those error opportunities for sub-optimal cabling, unusual network protocols, sub-optimal deployment of virtualization technologies, issues with 3rd party storage, issues with 3rd party multi-pathing products, etc., are simply taken out of the equation. All those error opportunities for making an issue unique to a particular set-up, the "why aren't we seeing this on any other system ?" type questions, the doubts, just go away when we or a customer discover an issue on an Engineered System. It enables a really honed response, getting to the root cause much, much faster than would otherwise be the case. Here's a couple of examples from the last month, one found in-house by my team, one found by a customer: Example 1: We found a node eviction issue running 11gR2 with Solaris 11 SRU 12 under extreme load on what we call our ExaLego test system (mimics an Exadata / SuperCluster 11gR2 Exadata Storage Cell set-up).  We quickly established that an enhancement in SRU12 enabled an 11gR2 process to query Infiniband's Subnet Manager, replacing a fallback mechanism it had used previously.  Under abnormally heavy load, the query could return results which were misinterpreted resulting in node eviction.  In several daily joint debugging sessions between the Solaris, Infiniband, and 11gR2 teams, the issue was fully root caused, evaluated, and a fix agreed upon.  That fix went back into all Solaris releases the following Monday.  From initial issue discovery to the fix being put back into all Solaris releases was just 10 days. Example 2: A customer reported sporadic performance degradation.  The reasons were unclear and the information sparse.  The SPARC SuperCluster Engineered Systems support teams which comprises both SPARC/Solaris and Database/Exadata experts worked to root cause the issue.  A number of contributing factors were discovered, including tunable parameters.  An intense collaborative investigation between the engineering teams identified the root cause to a CPU bound networking thread which was being starved of CPU cycles under extreme load.  Workarounds were identified.  Modifications have been put back into 11gR2 to alleviate the issue and a development project already underway within Solaris has been sped up to provide the final resolution on the Solaris side.  The fixed SPARC SuperCluster configuration greatly aided issue reproduction and dramatically sped up root cause analysis, allowing the correct workarounds and fixes to be identified, prioritized, and implemented.  The customer is now extremely happy with performance and robustness.  Since the configuration is common to other customers, the lessons learned are being proactively rolled out to other customers and incorporated into the installation procedures for future customers.  This effectively acts as a turbo-boost to performance and reliability for all SPARC SuperCluster customers.  If this had occurred in a "home grown" system of this complexity, I expect it would have taken at least 6 months to get to the bottom of the issue.  But because it was an Engineered System, known, understood, and qualified by both the Solaris and Database teams, we were able to collaborate closely to identify cause and effect and expedite a solution for the customer.  That is a key advantage of Engineered Systems which should not be underestimated.  Indeed, the initial issue mitigation on the Database side followed by final fix on the Solaris side, highlights the high degree of collaboration and excellent teamwork between the Oracle engineering teams.  It's a compelling advantage of the integrated Oracle Red Stack in general and Engineered Systems in particular.

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  • Would a model like this translate well to a document or graph database?

    - by Eric
    I'm trying to understand what types of models that I have traditionally persisted relationally would translate well to some kind of NoSQL database. Suppose I have a model with the following relationships: Product 1-----0..N Order Customer 1-----0..N Order And suppose I need to frequently query things like All Orders, All Products, All Customers, All Orders for Given Customer, All Orders for Given Product. My feeling is that this kind of model would not denormalize cleanly - If I had Product and Customer documents with embedded Orders, both documents would have duplicate orders. So I think I'd need separate documents for all three entities. Does a characteristic like this typically indicate that a document database is not well suited for a given model? Generally speaking, would a document database perform as well as a relational database in this kind of situation? I know very little about graph databases, but I understand that a graph database handles relationships more performantly than a document database - would a graph database be suited for this kind of model?

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  • Making more complicated systems(entity-component-system model question)

    - by winch
    I'm using a model where entities are collections of components and components are just data. All the logic goes into systems which operate on components. Making basic systems(for Rendering and handling collision) was easy. But how do I do more compilcated systems? For example, in a CollisionSystem I can check if entity A collides with entity B. I have this code in CollisionSystem for checking if B damages A: if(collides(a, b)) { HealthComponent* hc = a->get<HealthComponent(); hc.reduceHealth(b->get<DamageComponent>()->getDamage()); But I feel that this code shouldn't belong to Collision system. Where should code like this be and which additional systems should I create to make this code generic?

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  • Optimal Database design regarding functionality of letting user share posts by other users

    - by codecool
    I want to implement functionality which let user share posts by other users similar to what Facebook and Google+ share button and twitter retweet. There are 2 choices: 1) I create duplicate copy of the post and have a column which keeps track of the original post id and makes clear this is a shared post. 2) I have a separate table shared post where I save the post id which is a foreign key to post id in post table. Talking in terms of programming basically I keep pointer to the original post in a separate table and when need to get post posted by user and also shared ones I do a left join on post and shared post table Post(post_id(PK), post_content, posted_by) SharedPost(post_id(FK to Post.post_id), sharing_user, sharedfrom(in case someone shares from non owners profile)) I am in favour of second choice but wanted to know the advice of experts out there? One thing more posts on my webapp will be more on the lines of facebook size not tweet size.

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  • Android application Database Framework

    - by Marek Sebera
    When creating mobile (specially Android) application, I usually come to touch with similar pattern of working with data. Usually I need to fetch some remote data (covered by authorization process) to local cache. And on next request: Check networking Check presence of cache file Check version of cache file (if networking) Get new version and save cache (if networking and file not in cache, or outdated) Data store is no-SQL JSON Document-Based (and yes, I know about CouchDB Android version, but it doesn't fit my needs yet.) Process of authorizing to data source and code for check version of local cache is adapted to application. But the other code (handling network, saving cache, handling exceptions,...) is always the same. Is there any Data Store helper I can use, which provides functions I described above?

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  • How to deal with transactions when creating a database connection for each query

    - by webnoob
    In line with this post here I am going to change my website to create a connection per query to take advantage of .NET's connection pooling. With this in mind, I don't know how I should deal with transactions. At the moment I do something like (psuedo code): GlobalTransaction = GlobalDBConnection.BeginTransaction(); try { ExecSQL("insert into table ..") ExecSQL("update some_table ..") .... GlobalTransaction.Commit(); }catch{ GlobalTransaction.Rollback(); throw; } ExecSQL would be like this: using (SqlCommand Command = GlobalDBConnection.CreateCommand()) { Command.Connection = GlobalDBConnection; Command.Transaction = GlobalTransaction; Command.CommandText = SQLStr; Command.ExecuteNonQuery(); } I'm not quite sure how to change this concept to deal with transactions if the connection is created within ExecSQL because I would want the transaction to be shared between both the insert and update routines.

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  • Modular Database Structures

    - by John D
    I have been examining the code base we use in work and I am worried about the size the packages have grown to. The actual code is modular, procedures have been broken down into small functional (and testable) parts. The issue I see is that we have 100 procedures in a single package - almost an entire domain model. I had thought of breaking these packages down - to create sub domains that are centered around the procedure relationships to other objects. Group a bunch of procedures that have 80% of their relationships to three tables etc. The end result would be a lot more packages, but the packages would be smaller and I feel the entire code base would be more readable - when procedures cross between two domain models it is less of a struggle to figure which package it belongs to. The problem I now have is what the actual benefit of all this would really be. I looked at the general advantages of modularity: 1. Re-usability 2. Asynchronous Development 3. Maintainability Yet when I consider our latest development, the procedures within the packages are already reusable. At this advanced stage we rarely require asynchronous development - and when it is required we simply ladder the stories across iterations. So I guess my question is if people know of reasons why you would break down classes rather than just the methods inside of classes? Right now I do believe there is an issue with these mega packages forming but the only benefit I can really pin down to break them down is readability - something that experience gained from working with them would solve.

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  • Looking for free, specific Ip2Location Database

    - by Andresch Serj
    I am searching for a free db (like an updated XML or CSV file) that relates IP addresses to specific locations. I want more information than just the country. I want some sort of region or city reference, even if that ends up to be a number that makes no sense to me. Doesn't have to be super correct or always up to date either. It is just to distinguish between user groups and not to monitor or spy on them.

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  • Free, specific Ip2Location Database

    - by Andresch Serj
    I am searching for a free db (like an updated xml or csv file) that relates ip adresses to specific locations. I want more information than just the Country. I want some sort of region or city refference, even if that ends up to be a number that makes no sense to me. Doesn't have to be super correct or always up to date either. It is just to distinguish between usergroups and not to monitor or spy on them.

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  • Programming language specific package management systems

    - by m0nhawk
    There are some programming languages for which exist their own package management systems: CTAN for TeX CPAN for Perl Pip & Eggs for Python Maven for Java cabal for Haskell Gems for Ruby Is there any other languages with such systems? What about C and C++? (that's the main question!) Why there are no such systems for them? And isn't creating packages for yum, apt-get or other general package management systems better? UPD: And what about unification? Have someone tried to unify that "the zoo"? If yes, looks like that project didn't succeed.

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  • Continuous Delivery and the Database

    Continuous Delivery is fairly generally understood to be an effective way of tackling the problems of software delivery and deployment by making build, integration and delivery into a routine. The way that databases fit into the Continuous Delivery story has been less-well defined. Phil Factor explains why he's an enthusiast for databases being full participants, and suggests practical ways of doing so.

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  • Set modified date = created date or null on record creation?

    - by User
    I've been following the convention of adding created and modified columns to most of my database tables. I also have been leaving the modified column as null on record creation and only setting a value on actual modification. The other alternative is to set the modified date to be equal to created date on record creation. I've been doing it the former way but I recent ran into one con which is seriously making me think of switching. I needed to set a database cache dependency to find out if any existing data has been changed or new data added. Instead of being able to do the following: SELECT MAX(modified) FROM customer I have to do this: SELECT GREATEST(MAX(created), MAX(modified)) FROM customer The negative being that it's a more complicated query and slower. Another thing is in file systems I believe they usually use the second convention of setting modified date = created date on creation. What are the pros and cons of the different methods? That is, what are the issues to consider?

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