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  • Desktop GUI Client - Remote RDBMS communication

    - by magom001
    Sorry if I am asking a trivial question but I have been searching for a while without any luck. I need to design a system and I am looking for advice on the technology that should be used. The layout is very simple: it is a sales application with a centralized database and multiple clients. Each salesperson has GUI app installed on his/her laptop that should be able to connect to the database to retrieve data and upload data (i.e. register new orders). My question is the following: how should the communication between the client and the server be implemented? I doubt that connecting directly to the RDBMS is a good idea... Should I use web-services? XML-RPC? How to implement authentication and encode the data? Thanks for your advice!

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  • Why many designs ignore normalization in RDBMS?

    - by Yosi
    I got to see many designs that normalization wasn't the first consideration in decision making phase. In many cases those designs included more than 30 columns, and the main approach was "to put everything in the same place" According to what I remember normalization is one of the first, most important things, so why is it dropped so easily sometimes? Edit: Is it true that good architects and experts choose a denormalized design while non-experienced developers choose the opposite? What are the arguments against starting your design with normalization in mind?

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  • ???Past Image(pi)

    - by todd.bao(at)oracle.com
    Past Image???RAC??????????,????????????????????????????????,Past Image??????????,?????????????????,?????????????????,??????????????(pi)?????????????????Past Image,????????????:HR.EMPLOYEES??100????101?????5????88???????????????,???????????# ??1: ?????????SYS@RAC1//scripts> select inst_id,status from gv$bh where file#=5 and block#=88;no rows selected# ??1???(???Steve King, ????24000????)SYS@RAC1//scripts> update hr.employees set salary=1 where employee_id=100;1 row updated.# ??2: ????1??xcur????????????,?????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + xcur1 row selected.# ??2???SYS@RAC2//scripts> update hr.employees set salary=2 where employee_id=101;1 row updated.# ??3: ????2?,?????1??pi??Past Image,???????????????????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + pi         2 + Y + xcur2 rows selected.# ??1???SYS@RAC1//scripts> update hr.employees set salary=3 where employee_id=100;1 row updated.# ??4: ????1?,?????2???1???????2???????1???????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + pi         1 + Y + xcur         2 + Y + pi3 rows selected.# ??2????SYS@RAC2//scripts> update hr.employees set salary=4 where employee_id=101;1 row updated.# ??5: ????2?,??????????????,DBWR??,??????,??(pi)?????????????(cr)??????????????????????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + N + cr         1 + N + cr         2 + Y + xcur3 rows selected.# ?????1???SYS@RAC1//scripts> update hr.employees set salary=5 where employee_id=100;1 row updated.# ??6: ????1?,?????2????????????????,?????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + xcur         1 + N + cr         1 + N + cr         2 + Y + pi4 rows selected.# ??2???SYS@RAC2//scripts> update hr.employees set salary=6 where employee_id=101;1 row updated.# ??7: ????2?,?????1?2????1???????2?????????????4,????????????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + pi         2 + Y + pi         2 + Y + xcur3 rows selected.# ??1???SYS@RAC1//scripts> update hr.employees set salary=7 where employee_id=100;1 row updated.# ??8: ????1?,?????2?1????2???????1????????????2????????????????????????????????????(????????)????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and  block#=88;   INST_ID + D + STATUS---------- + - + -------         1 + Y + pi         1 + Y + xcur         2 + Y + pi         2 + N + cr4 rows selected.??????????, ?xcur??????????:??????xcur????pi?????pi?(?????)???cr?,???cr?????,pi????????????????????????????:?????????????A?B?A:SYS@RAC1//scripts> run  1  begin  2  for i in 1..100000 loop  3  update hr.employees set salary=i where employee_id=100;  4  end loop;  5* end;B:SYS@RAC2//scripts> run  1  begin  2  for i in 1..100000 loop  3  update hr.employees set salary=i where employee_id=101;  4  end loop;  5* end;?????????,???5???88?????buffer cache???????:SYS@RAC2//scripts> select count(*) from gv$bh where file#=5 and block#=88;  COUNT(*)----------       4121 row selected.??409?????????(cur):SYS@RAC2//scripts> select count(*) from gv$bh where file#=5 and block#=88 where status='cr';  COUNT(*)----------       4091 row selected.1????????(xcur):SYS@RAC2//scripts> select count(*) from gv$bh where file#=5 and block#=88 where status='xcur';  COUNT(*)----------           11 row selected.??...2??????--????(pi)??????????SYS@RAC1//scripts> select inst_id,dirty,status from gv$bh where file#=5 and block#=88 and status='pi';   INST_ID + D + STATUS---------- + - + -------         1 + Y + pi         2 + Y + pi2 rows selected.????,???RAC??????????????(cr)?,????????????????????????xcur?pi??cr??????pi?????? ?????????,???????????pi???cr?,?????????cr???,???xcur???????,pi??????xcur?,[email protected]

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  • When to use CouchDB vs RDBMS

    - by Andrew Whitehouse
    I am looking at CouchDB, which has a number of appealing features over relational databases including: intuitive REST/HTTP interface easy replication data stored as documents, rather than normalised tables I appreciate that this is not a mature product so should be adopted with caution, but am wondering whether it is actually a viable replacement for an RDBMS (in spite of the intro page saying otherwise - http://couchdb.apache.org/docs/intro.html). Under what circumstances would CouchDB be a better choice of database than an RDBMS (e.g. MySQL), e.g. in terms of scalability, design + development time, reliability and maintenance. Are there still cases where an RDBMS is still clearly the right choice? Is this an either-or choice, or is a hybrid solution more likely to emerge as best practice?

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  • flat files vs. RDBMS database, few read/writes, few changes

    - by Bob Lapique
    I have to handle data from long term (years, decades) climate monitoring stations. The data flow usually starts with raw data (voltages, etc.) plus quality check information (pressure, temperature, flow rate, etc.) generally recorded @ 1Hz. Then, the data are assigned a quality flag (human and/or program), processed (apply calibration curves) and flagged. So, we basically end up with 2 datasets : raw and processed data. New data are typically added once a day (~500Ko/day/instrument). Simultaneous queries are not likely to ever happen. I wanted to go for a RDBMS (we have a MySQL server) and have some experience in database design, but the IT guy keeps telling me that flat files will to the job just as well. I suspect him to try to make his life easier when it comes to backup/upgrade the MySQL. There are not so many links between data, they don't change much, but the quality flags will change. A RDBMS is easier to compare data from different instruments on a "many days" scale, compared to daily text files. Well, what would you advise ? Thanks.

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  • Spreadsheet RDBMS

    - by John Nilsson
    I'm looking for a software (or set of software) that will let me combine spreadsheet and database workflows. Data entry in spreadsheet to enable simple entry from clipboard, analysis based on joins, unions and aggregates and pivot/data pilot summaries. So far I've only found either spreadsheets OR db applications but no good combination. OO base with calc for tables doesn't support aggregates f.ex. Google Spreadsheet + Visualizaion API doesn't support unions or joins, zoho db doesn't let me paste from clipboard. Any hints on software that could be used? Basically I'm trying to do some analysis of my personal bank transactions. Problem 1, ETL. The data has to be moved from my bank to a database. My current solution is to manually copy and paste the data into one spread sheet per account from my internet bank. Pains: Not very scriptable. Lots of scrolling to reach the point to paste. Have to apply sorting and formatting to the pasted data each time. Problem 2, analysis. I then want to aggregate the different accounts in one sweep to track transfers per type of transfer over all accounts. The actual aggregation is still unsolved because I can't find a UNION equivalent in the spreadsheets I've tried.

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  • Why is filesystem preferred for logs instead of RDBMS?

    - by Yasir
    Question should be clear from its title. For example Apache saves its access and error logs in files instead of RDBMS no matter on how large or small scale it is being utilized. For RDMS we just have to write SQL queries and it will do the work while for files we must decide a particular format and then write regex or may be parsers to manipulate them. And those might even fail in particular circumstances if great care was not paid. Yet everyone seems to prefer filesystem for maintaining the logs. I am not biased against any of these methods but I would like to know why it is practiced like this. Is it speed or maintainability or something else?

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  • Practical size limitations for RDBMS

    - by grenade
    I am working on a project that must store very large datasets and associated reference data. I have never come across a project that required tables quite this large. I have proved that at least one development environment cannot cope at the database tier with the processing required by the complex queries against views that the application layer generates (views with multiple inner and outer joins, grouping, summing and averaging against tables with 90 million rows). The RDBMS that I have tested against is DB2 on AIX. The dev environment that failed was loaded with 1/20th of the volume that will be processed in production. I am assured that the production hardware is superior to the dev and staging hardware but I just don't believe that it will cope with the sheer volume of data and complexity of queries. Before the dev environment failed, it was taking in excess of 5 minutes to return a small dataset (several hundred rows) that was produced by a complex query (many joins, lots of grouping, summing and averaging) against the large tables. My gut feeling is that the db architecture must change so that the aggregations currently provided by the views are performed as part of an off-peak batch process. Now for my question. I am assured by people who claim to have experience of this sort of thing (which I do not) that my fears are unfounded. Are they? Can a modern RDBMS (SQL Server 2008, Oracle, DB2) cope with the volume and complexity I have described (given an appropriate amount of hardware) or are we in the realm of technologies like Google's BigTable? I'm hoping for answers from folks who have actually had to work with this sort of volume at a non-theoretical level.

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  • Many-to-many relations in RDBMS databases

    - by Industrial
    What is the best way of handling many-to-many relations in a RDBMS database like mySQL? Have tried using a pivot table to keep track of the relationships, but it leads to either one of the following: Normalization gets left behind Columns that is empty or null What approach have you taken in order to support many-to-many relationships?

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  • Oracle RDBMS Server 11gR2 Pre-Install RPM for Oracle Linux 6 has been released

    - by Lenz Grimmer
    Now that the certification of the Oracle Database 11g R2 with Oracle Linux 6 and the Unbreakable Enterprise Kernel has been announced, we are glad to announce the availability of oracle-rdbms-server-11gR2-preinstall, the Oracle RDBMS Server 11gR2 Pre-install RPM package (formerly known as oracle-validated). Designed specifically for Oracle Linux 6, this RPM aids in the installation of the Oracle Database. In order to install the Oracle Database 11g R2 on Oracle Linux 6, your system needs to meet a few prerequisites, as outlined in the Linux Installation Guides. Using the Oracle RDBMS Server 11gR2 Pre-install RPM, you can complete most of the pre-installation configuration tasks. which is now available from the Unbreakable Linux Network, or via the Oracle public yum repository. The pre-install package is available for x86_64 only. Specifically, the package: Causes the download and installation of various software packages and specific versions needed for database installation, with package dependencies resolved via yum Creates the user oracle and the groups oinstall and dba, which are the defaults used during database installation Modifies kernel parameters in /etc/sysctl.conf to change settings for shared memory, semaphores, the maximum number of file descriptors, and so on Sets hard and soft shell resource limits in /etc/security/limits.conf, such as the number of open files, the number of processes, and stack size to the minimum required based on the Oracle Database 11g Release 2 Server installation requirements Sets numa=off in the kernel boot parameters for x86_64 machines Please see the release announcement for further details and instructions. Also take a look at Ginny Henningsen's "How I Simplified Oracle Database Installation on Oracle Linux" article on the Oracle Technology Network for a general description on how to perform the installation of the Oracle Database on Oracle Linux. While the article refers to Oracle Linux 5 and the former "oracle-validated" package, the steps for Oracle Linux 6 are still very similar (we're looking into updating that article for Oracle Linux 6).

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  • What is a Relational Database Management System (RDBMS)?

    A Relational Database Management System (RDBMS)  can also be called a traditional database that uses a Structured Query Language (SQL) to provide access to stored data while insuring the integrity of the data. The data is stored in a collection of tables that is defined by relationships between data items. In addition, data permitted to be joined in new relationships. Traditional databases primarily process data through transactions called transaction processing. Transaction processing is the methodology of grouping related business operations based predefined business events. An example of this can be seen when a person attempts to purchase an item from an online e-tailor. The business must execute specific operations for a related  business event. In this case, a business must store the following information: Customer Info, Order Info, Order Item Info, Customer Payment Data, Payment Results, and Current Order Status. Example: Pseudo SQL Operations needed for processing an online e-tailor sale. Insert Customer into Customers Insert New Order into Orders Insert Each New Order Item into OrderItems Insert Customer Payment Info into PaymentInfo Insert Payment Processing Result into PaymentDetails Update Customer for Current Order Status Common Relational Database Management System Microsoft SQL Server Microsoft Access Oracle MySQL DB2 It is important to note that no current RDBMS has fully implemented all of the Relational Principles. Common RDBMS Traits Volatile Data Supports Transaction Processing Optimized for Updates and Simple Queries 

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  • RDBMS???????Key-Value?

    - by ?? ?
    ??????????????????????RDBMS????????????????????????????????????????????? ?????????????DB??(?)???????????Key-Value?DB???? ????????????????????????·?????????? ?????DB???TimesTen??Key-Value????Coherence????????? ?????????????????????????????? ????????????RDBMS??????????????????? ??????????????????????????? ???????????????????????????????????? ????????????Web???????????(????????????????) ??????????????????????BI?????????????????? ??????????????? ????ERP??????????????????????????????? ????????????????????????????? ?????????????(???????)?? ? ?????????????????????????????????? ????????(??????????????????????Key-Value? ???????) ????????????????? ? ??????????????????????????????????????????? ???????????????????????(???5???10??????????) ????????????????????? ? ??????????????????????????????????????? ????????????????????????????????????????? ?????????????????????????????? ?????TB?????????????????? ? ???????????????????????????????????? ?????? ????????????? ? ?????????????????(??)?????????? ???????????Key-Value???????????????????????????? ????(??????????????RDBMS???????)? ??????????????????????????????????????? ??????????????????????????????????????? ??????????? ???????????????????????????????????????? ??????????????????????????????????? ????????????????? ??????????DB???????????????????????? ????????????????????????????????????? ????? ????????????????????????????? ?????????????????????????????????? ??????????????????????????????????????? ?????????????????????????????????????(??????) ??????????????????????????????????????? ???????·??????????????????????????????? ?????????? ???????????????????

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  • Studying MySQL, SQLite source code to learn about RDBMS implementation

    - by Yang
    I know implementing database is a huge topic, but I want to have a basic understanding of how database systems work (e.g. memory management, binary tree, transaction, sql parsing, multi-threading, partitions, etc) by investigating the source code of the database. Since there are a few already proven very robust open source databases like mysql, sqlite and so on. However, the code are very complicated and I have no clue where to start. Also I find that the old school database textbooks are only explaining the theory, not the implementation details. Can anyone suggest how I should get started and if there are any books that emphasis on the technology and techniques of building dbms used in modern database industry?

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  • SQL Developer Data Modeler: On Notes, Comments, and Comments in RDBMS

    - by thatjeffsmith
    Ah the beautiful data model. They say a picture is worth a 1,000 words. And then we have our diagrams, how many words are they worth? Our friends from the Human Relations sample schema So our models describe how the data ‘works’ – whether that be at a logical-business level, or a technical-physical level. Developers like to say that their code is self-documenting. These would be very lazy or very bad (or both) developers. Models are the same way, you should document your models with comments and notes! I have 3 basic options: Comments Comments in RDBMS Notes So what’s the difference? Comments You’re describing the entity/table or attribute/column. This information will NOT be published in the database. It will only be available to the model, and hence, folks with access to the model. Table Comments (in the design only!) Comments in RDBMS You’re doing the same thing as above, but your words will be stored IN the data dictionary of the database. Oracle allows you to store comments on the table and column definitions. So your awesome documentation is going to be viewable to anyone with access to the database. RDBMS is an acronym for Relational Database Management System – of which Oracle is one of the first commercial examples If the DDL is produced and ran against a database, these comments WILL be stored in the data dictionary. Notes A place for you to add notes, maybe from a design meeting. Or maybe you’re using this as a to-do or requirements list. Basically it’s for anything that doesn’t literally describe the object at hand – that’s what the comments are for. I totally made these up. Now these are free text fields and you can put whatever you want here. Just make sure you put stuff here that’s worth reading. And it will live on…forever.

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  • Oracle is #1 in the RDBMS Sector for 2011

    - by jgelhaus
    Gartner 2011 Worldwide RDBMS Market Share Reports 48.8% revenue share for Oracle (*) Gartner has published their market share numbers for 2011 based on total software revenues.  According to Gartner, Oracle: is #1 in worldwide RDBMS software revenue share holds more revenue share than its seven closest competitors combined grew at 18.0%, exceeding both the industry average (16.3%) and the growth rates of its closest competitors. (*) Source: Market Share: All Software Markets, Worldwide 2011 by Colleen Graham, Joanne Correia, David Coyle, Fabrizio Biscotti, Matthew Cheung, Ruggero Contu, Yanna Dharmasthira, Tom Eid, Chad Eschinger, Bianca Granetto, Hai Hong Swinehart, Sharon Mertz, Chris Pang, Asheesh Raina, Dan Sommer, Bhavish Sood, Marianne D'Aquila, Laurie Wurster and Jie Zhang. - March 29, 2012

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  • Do database engines other than SQL Server behave this way?

    - by Yishai
    I have a stored procedure that goes something like this (pseudo code) storedprocedure param1, param2, param3, param4 begin if (param4 = 'Y') begin select * from SOME_VIEW order by somecolumn end else if (param1 is null) begin select * from SOME_VIEW where (param2 is null or param2 = SOME_VIEW.Somecolumn2) and (param3 is null or param3 = SOME_VIEW.SomeColumn3) order by somecolumn end else select somethingcompletelydifferent end All ran well for a long time. Suddenly, the query started running forever if param4 was 'Y'. Changing the code to this: storedprocedure param1, param2, param3, param4 begin if (param4 = 'Y') begin set param2 = null set param3 = null end if (param1 is null) begin select * from SOME_VIEW where (param2 is null or param2 = SOME_VIEW.Somecolumn2) and (param3 is null or param3 = SOME_VIEW.SomeColumn3) order by somecolumn end else select somethingcompletelydifferent And it runs again within expected parameters (15 seconds or so for 40,000+ records). This is with SQL Server 2005. The gist of my question is this particular "feature" specific to SQL Server, or is this a common feature among RDBMS' in general that: Queries that ran fine for two years just stop working as the data grows. The "new" execution plan destroys the ability of the database server to execute the query even though a logically equivalent alternative runs just fine? This may seem like a rant against SQL Server, and I suppose to some degree it is, but I really do want to know if others experience this kind of reality with Oracle, DB2 or any other RDBMS. Although I have some experience with others, I have only seen this kind of volume and complexity on SQL Server, so I'm curious if others with large complex databases have similar experience in other products.

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  • Building an Oracle (and other RDBMS) Server Environment

    In previous articles discussing Oracle and VMware, the hardware and software components consisted of a Windows-based PC and the Oracle RDBMS. Steve Callan expands upon the "Oracle in a virtualized environment" concept by looking at other alternatives for the hardware and software.

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  • Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Cloud in the Big Data Story. In this article we will understand the role of Operational Databases Supporting Big Data Story. Even though we keep on talking about Big Data architecture, it is extremely crucial to understand that Big Data system can’t just exist in the isolation of itself. There are many needs of the business can only be fully filled with the help of the operational databases. Just having a system which can analysis big data may not solve every single data problem. Real World Example Think about this way, you are using Facebook and you have just updated your information about the current relationship status. In the next few seconds the same information is also reflected in the timeline of your partner as well as a few of the immediate friends. After a while you will notice that the same information is now also available to your remote friends. Later on when someone searches for all the relationship changes with their friends your change of the relationship will also show up in the same list. Now here is the question – do you think Big Data architecture is doing every single of these changes? Do you think that the immediate reflection of your relationship changes with your family member is also because of the technology used in Big Data. Actually the answer is Facebook uses MySQL to do various updates in the timeline as well as various events we do on their homepage. It is really difficult to part from the operational databases in any real world business. Now we will see a few of the examples of the operational databases. Relational Databases (This blog post) NoSQL Databases (This blog post) Key-Value Pair Databases (Tomorrow’s post) Document Databases (Tomorrow’s post) Columnar Databases (The Day After’s post) Graph Databases (The Day After’s post) Spatial Databases (The Day After’s post) Relational Databases We have earlier discussed about the RDBMS role in the Big Data’s story in detail so we will not cover it extensively over here. Relational Database is pretty much everywhere in most of the businesses which are here for many years. The importance and existence of the relational database are always going to be there as long as there are meaningful structured data around. There are many different kinds of relational databases for example Oracle, SQL Server, MySQL and many others. If you are looking for Open Source and widely accepted database, I suggest to try MySQL as that has been very popular in the last few years. I also suggest you to try out PostgreSQL as well. Besides many other essential qualities PostgreeSQL have very interesting licensing policies. PostgreSQL licenses allow modifications and distribution of the application in open or closed (source) form. One can make any modifications and can keep it private as well as well contribute to the community. I believe this one quality makes it much more interesting to use as well it will play very important role in future. Nonrelational Databases (NOSQL) We have also covered Nonrelational Dabases in earlier blog posts. NoSQL actually stands for Not Only SQL Databases. There are plenty of NoSQL databases out in the market and selecting the right one is always very challenging. Here are few of the properties which are very essential to consider when selecting the right NoSQL database for operational purpose. Data and Query Model Persistence of Data and Design Eventual Consistency Scalability Though above all of the properties are interesting to have in any NoSQL database but the one which most attracts to me is Eventual Consistency. Eventual Consistency RDBMS uses ACID (Atomicity, Consistency, Isolation, Durability) as a key mechanism for ensuring the data consistency, whereas NonRelational DBMS uses BASE for the same purpose. Base stands for Basically Available, Soft state and Eventual consistency. Eventual consistency is widely deployed in distributed systems. It is a consistency model used in distributed computing which expects unexpected often. In large distributed system, there are always various nodes joining and various nodes being removed as they are often using commodity servers. This happens either intentionally or accidentally. Even though one or more nodes are down, it is expected that entire system still functions normally. Applications should be able to do various updates as well as retrieval of the data successfully without any issue. Additionally, this also means that system is expected to return the same updated data anytime from all the functioning nodes. Irrespective of when any node is joining the system, if it is marked to hold some data it should contain the same updated data eventually. As per Wikipedia - Eventual consistency is a consistency model used in distributed computing that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value. In other words -  Informally, if no additional updates are made to a given data item, all reads to that item will eventually return the same value. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL RDBMS : one query or multiple calls

    - by None None
    After looking around the internet, I decided to create DAOs that returned objects (POJOs) to the calling business logic function/method. For example: a Customer object with a Address reference would be split in the RDBMS into two tables; Customer and ADDRESS. The CustomerDAO would be in charge of joining the data from the two tables and create both an Address POJO and Customer POJO adding the address to the customer object. Finally return the fulll Customer POJO. Simple, however, now i am at a point where i need to join three or four tables and each representing an attribute or list of attributes for the resulting POJO. The sql will include a group by but i will still result with multiple rows for the same pojo, because some of the tables are joining a one to many relationship. My app code will now have to loop through all the rows trying to figure out if the rows are the same with different attributes or if the record should be a new POJO. Should I continue to create my daos using this technique or break up my Pojo creation into multiple db calls to make the code easier to understand and maintain?

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  • What resources will help me understand the fundamentals of Relational Database Design.

    - by Rachel
    This are few of the fundamental database questions which has always given me trouble. I have tried using google and wiki but I somehow I miss out on understanding the functionality rather than terminology. If possible would really appreciate if someone can share more insights on this questions using some visual representative examples. What is a key? A candidate key? A primary key? An alternate key? A foreign key? What is an index and how does it help your database? What are the data types available and when to use which ones?

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  • Which are the RDBMS that minimize the server roundtrips? Which RDBMS are better (in this area) than

    - by user193655
    When the latency is high ("when pinging the server takes time") the server roundtrips make the difference. Now I don't want to focus on the roundtrips created in programming, but the roundtrips that occur "under the hood" in the DB engine, so the roundtrips that are 100% dependant on how the RDBMS is written itself. I have been told that FireBird has more roundtrips than MySQL. But this is the only information I know. I am currently supporting MS SQL but I'd like to change RDBMS (because I use Express Editions and in my scenario they are quite limiting from the performance point of view), so to make a wise choice I would like to include also this point into "my RDBMS comparison feature matrix" to understand which is the best RDBMS to choose as an alternative to MS SQL. So the bold sentence above would make me prefer MySQL to Firebird (for the roundtrips concept, not in general), but can anyone add informations? And MS SQL where is it located? Is someone able to "rank" the roundtrip performance of the main RDBMS, or at least: MS SQL, MySql, Postegresql, Firebird (I am not interested in Oracle since it is not free, and if I have to change I would change to a free RDBMS). Anyway MySql (as mentioned several times on stackoverflow) has a not clear future and a not 100% free license. So my final choice will probably dall on PostgreSQL or Firebird. Additional info: somehow you can answer my question by making a simple list like: MSSQL:3; MySQL:1; Firebird:2; Postgresql:2 (where 1 is good, 2 average, 3 bad). Of course if you can post some links where the roundtrips per RDBMSs are compared it would be great

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  • Could an ontology suitably replace an RDBMS for a web app?

    - by Thomas
    I'm considering storing the content of a web app in an RDF or OWL ontology instead of an RDBMS. However, when I research ontologies they seem to always exist in the context of publicly accessible data stores serving as the backbone of the semantic web. I've never heard of them being used as the content engine behind a web app. Is it reasonable to use an ontology instead of an RDBMS for such an application? (Again, this is just for content. User data, commerce and stuff like that will stay in a database as I see no need to reinvent the wheel there.)

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  • Is there a canonical source supporting "all-surrogates"?

    - by user61852
    Background The "all-PK-must-be-surrogates" approach is not present in Codd's Relational Model or any SQL Standard (ANSI, ISO or other). Canonical books seems to elude this restrictions too. Oracle's own data dictionary scheme uses natural keys in some tables and surrogate keys in other tables. I mention this because these people must know a thing or two about RDBMS design. PPDM (Professional Petroleum Data Management Association) recommend the same canonical books do: Use surrogate keys as primary keys when: There are no natural or business keys Natural or business keys are bad ( change often ) The value of natural or business key is not known at the time of inserting record Multicolumn natural keys ( usually several FK ) exceed three columns, which makes joins too verbose. Also I have not found canonical source that says natural keys need to be immutable. All I find is that they need to be very estable, i.e need to be changed only in very rare ocassions, if ever. I mention PPDM because these people must know a thing or two about RDBMS design too. The origins of the "all-surrogates" approach seems to come from recommendations from some ORM frameworks. It's true that the approach allows for rapid database modeling by not having to do much business analysis, but at the expense of maintainability and readability of the SQL code. Much prevision is made for something that may or may not happen in the future ( the natural PK changed so we will have to use the RDBMS cascade update funtionality ) at the expense of day-to-day task like having to join more tables in every query and having to write code for importing data between databases, an otherwise very strightfoward procedure (due to the need to avoid PK colisions and having to create stage/equivalence tables beforehand ). Other argument is that indexes based on integers are faster, but that has to be supported with benchmarks. Obviously, long, varying varchars are not good for PK. But indexes based on short, fix-length varchar are almost as fast as integers. The questions - Is there any canonical source that supports the "all-PK-must-be-surrogates" approach ? - Has Codd's relational model been superceded by a newer relational model ?

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  • MongoDB: Replicate data in documents vs. “join”

    - by JavierCane
    Disclaimer: This is a question derived from this one. What do you think about the following example of use case? I have a table containing orders. These orders has a lot of related information needed by my current queries (think about the products; the buyer information; the region, country and state of the sale point; and so on) In order to think with a de-normalized approach, I don't have to put identifiers of these related items in my main orders collection. Instead, I have to repeat all the information for each order (ie: I will repeat the buyer's name, surname, etc. for each of its orders). Assuming the previous premise, I'm committing to maintain all the data related to an order without a lot of updates (because if I modify the buyer's name, I'll have to iterate through all orders updating the ones made by the same buyer, and as MongoDB blocks at a document level on updates, I would be blocking the entire order at the update moment). I'll have to replicate all the products' related data? (ie: category, maker and optional attributes like color, size…) What if a new feature is requested and I've to make a lot of queries with the products "as the entry point of the query"? (ie: reports showing the products' sales performance grouping by region, country, or whatever) Is it fair enough to apply the $unwind operation to my orders original collection? (What about the performance?) I should have to do another collection with these queries in mind and replicate again all the products' information (and their orders)? Wouldn't be better to store a product_id in the original orders collection in order to be more tolerable to requirements change? (What about emulating JOINs?) The optimal approach would be a mixed solution with a RDBMS system like MySQL in order to retrieve the complete data? I mean: store products, users, and location identifiers in the orders collection and have queries in MySQL like getAllUsersDataByIds in which I would perform a SELECT * FROM users WHERE user_id IN ( :identifiers_retrieved_from_the_mongodb_query )

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