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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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  • SQL and Database: Where to start! [closed]

    - by Nizar
    First of all I just know HTML and CSS (this is my background in web development and design) and I have found that before I move to a server-side language I need to learn about databases and SQL. My first question: Do you think this order of learning is good (I mean to learn SQL after HTML and CSS)? My secod related question: Do I have to learn a lot about SQL and databases? or just the basics? and if you know any good beginners books please write their titles.

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  • PHP class data implementation

    - by Bakanyaka
    I'm studying OOP PHP and have watched two tutorials that implement user login\registration system as an example. But implementation varies. Which way will be more correct one to work with data such as this? Load all data retrieved from database as array into a property called something like _data on class creation and further methods operate with this property Create separate properties for each field retrieved from database, on class creation load all data fields into respective properties and operate with that properties separately? Then let's say I want to create a method that returns a list of all users with their data. Which way is better? Method that returns just an array of userdata like this: Array([0]=>array([id] => 1, [username] => 'John', ...), [1]=>array([id] => 2, [username] => 'Jack', ...), ...) Method that creates a new instance of it's class for each user and returns an array of objects

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  • How to overcome shortcomings in reporting from EAV database?

    - by David Archer
    The major shortcomings with Entity-Attribute-Value database designs in SQL all seem to be related to being able to query and report on the data efficiently and quickly. Most of the information I read on the subject warn against implementing EAV due to these problems and the commonality of querying/reporting for almost all applications. I am currently designing a system where almost all the fields necessary for data storage are not known at design/compile time and are defined by the end-user of the system. EAV seems like a good fit for this requirement but due to the problems I've read about, I am hesitant in implementing it as there are also some pretty heavy reporting requirements for this system as well. I think I've come up with a way around this but would like to pose the question to the SO community. Given that typical normalized database (OLTP) still isn't always the best option for running reports, a good practice seems to be having a "reporting" database (OLAP) where the data from the normalized database is copied to, indexed extensively, and possibly denormalized for easier querying. Could the same idea be used to work around the shortcomings of an EAV design? The main downside I see are the increased complexity of transferring the data from the EAV database to reporting as you may end up having to alter the tables in the reporting database as new fields are defined in the EAV database. But that is hardly impossible and seems to be an acceptable tradeoff for the increased flexibility given by the EAV design. This downside also exists if I use a non-SQL data store (i.e. CouchDB or similar) for the main data storage since all the standard reporting tools are expecting a SQL backend to query against. Do the issues with EAV systems mostly go away if you have a seperate reporting database for querying? EDIT: Thanks for the comments so far. One of the important things about the system I'm working on it that I'm really only talking about using EAV for one of the entities, not everything in the system. The whole gist of the system is to be able to pull data from multiple disparate sources that are not known ahead of time and crunch the data to come up with some "best known" data about a particular entity. So every "field" I'm dealing with is multi-valued and I'm also required to track history for each. The normalized design for this ends up being 1 table per field which makes querying it kind of painful anyway. Here are the table schemas and sample data I'm looking at (obviously changed from what I'm working on but I think it illustrates the point well): EAV Tables Person ------------------- - Id - Name - ------------------- - 123 - Joe Smith - ------------------- Person_Value ------------------------------------------------------------------- - PersonId - Source - Field - Value - EffectiveDate - ------------------------------------------------------------------- - 123 - CIA - HomeAddress - 123 Cherry Ln - 2010-03-26 - - 123 - DMV - HomeAddress - 561 Stoney Rd - 2010-02-15 - - 123 - FBI - HomeAddress - 676 Lancas Dr - 2010-03-01 - ------------------------------------------------------------------- Reporting Table Person_Denormalized ---------------------------------------------------------------------------------------- - Id - Name - HomeAddress - HomeAddress_Confidence - HomeAddress_EffectiveDate - ---------------------------------------------------------------------------------------- - 123 - Joe Smith - 123 Cherry Ln - 0.713 - 2010-03-26 - ---------------------------------------------------------------------------------------- Normalized Design Person ------------------- - Id - Name - ------------------- - 123 - Joe Smith - ------------------- Person_HomeAddress ------------------------------------------------------ - PersonId - Source - Value - Effective Date - ------------------------------------------------------ - 123 - CIA - 123 Cherry Ln - 2010-03-26 - - 123 - DMV - 561 Stoney Rd - 2010-02-15 - - 123 - FBI - 676 Lancas Dr - 2010-03-01 - ------------------------------------------------------ The "Confidence" field here is generated using logic that cannot be expressed easily (if at all) using SQL so my most common operation besides inserting new values will be pulling ALL data about a person for all fields so I can generate the record for the reporting table. This is actually easier in the EAV model as I can do a single query. In the normalized design, I end up having to do 1 query per field to avoid a massive cartesian product from joining them all together.

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  • Relational vs. Dimensional Databases, what's the difference?

    - by grautur
    I'm trying to learn about OLAP and data warehousing, and I'm confused about the difference between relational and dimensional modeling. Is dimensional modeling basically relational modeling, but allowing for redundant/un-normalized data? For example, let's say I have historical sales data on (product, city, # sales). I understand that the following would be a relational point-of-view: Product | City | # Sales Apples, San Francisco, 400 Apples, Boston, 700 Apples, Seattle, 600 Oranges, San Francisco, 550 Oranges, Boston, 500 Oranges, Seattle, 600 While the following is a more dimensional point-of-view: Product | San Francisco | Boston | Seattle Apples, 400, 700, 600 Oranges, 550, 500, 600 But it seems like both points of view would nonetheless be implemented in an identical star schema: Fact table: Product ID, Region ID, # Sales Product dimension: Product ID, Product Name City dimension: City ID, City Name And it's not until you start adding some additional details to each dimension that the differences start popping up. For instance, if you wanted to track regions as well, a relational database would tend to have a separate region table, in order to keep everything normalized: City dimension: City ID, City Name, Region ID Region dimension: Region ID, Region Name, Region Manager, # Regional Stores While a dimensional database would allow for denormalization to keep the region data inside the city dimension, in order to make it easier to slice the data: City dimension: City ID, City Name, Region Name, Region Manager, # Regional Stores Is this correct?

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  • Ha a hutés nem elég a gépteremben: Sun Cooling Door a Database Machine-hoz

    - by Fekete Zoltán
    A Database Machine hatalmas teljesítménye miatt általában jóval kevesebb hutésre van szükség, mintha egy külön high-end servert és külön high-end storage-ot hutenénk! Ha viszont a géptermünk maradék hutési kapacitása nem elegendo, és nem elégszünk meg a "hagyományos mosóporral", akkor újabb hutési trükkre van szükség. Erre kínálnak megoldást a Sun Cooling Door modellek, például az 5200-as és az 5600-as modellek.

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  • Adatlap az Exadata, Database Machine supporthoz

    - by Fekete Zoltán
    Letöltheto és megtekintheto, sot elolvasható :) a COMPLETE SUPPORT SERVICES FOR ORACLE EXADATA dokumentum, amely részletesen leírja, milyen trméktámogatási lehetoségeket lehet igénybe venni egy Database Machine megoldáshoz. Az Exadata termékcsalád elemei mind tranzakciós rendszerek mind adattárházak adatbázisának futtatásához és adatbázisok egy közös szerveren muködtetéséhez nyújtanak optimális, nagy teljesítményu platformot.

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  • Details on Oracle's Primavera P6 Reporting Database R2

    - by mark.kromer
    Below is a graphic screenshot of our detailed announcement for the new Oracle data warehouse product for Primavera P6 called P6 Reporting Database R2. This DW product includes the ETL, data warehouse star schemas and ODS that you'll need to build an enterprise reporting solution for your projects & portfolios. This product is included on a restricted license basis with the new Primavera P6 Analytics R1 product from Oracle because those Analytics are built in OBIEE based on this data warehouse product.

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  • SQL SERVER – Creating All New Database with Full Recovery Model

    - by pinaldave
    Sometimes, complex problems have very simple solutions. Let us see the following email which I received recently. “Hi Pinal, In our system when we create new database, by default, they are all created with the Simple Recovery Model. We have to manually change the recovery model after we create the database. We used the following simple T-SQL code: CREATE DATABASE dbname. We are very frustrated with this situation. We want all our databases to have the Full Recovery Model option by default. We are considering the following methods; please suggest the most efficient one among them. 1) Creating a Policy; when it is violated, the database model can be fixed 2) Triggers at Server Level 3) Automated Job which goes through all the databases and checks their recovery model; if the DBA has not changed the model, then the job will list the Databases and change their recovery model Also, we have a situation where we need a database in the Simple Recovery Model as well – how to white list them? Please suggest the best method.” Indeed, an interesting email! The answer to their question, i.e., which is the best method to fit their needs (white list, default, etc)? It will be NONE of the above. Here is the solution in one line and also the easiest way: Just go to your Model database: Path in SSMS >> Databases > System Databases >> model >> Right Click Properties >> Options >> Recovery Model - Select Full from dropdown. Every newly created database takes its base template from the Model Database. If you create a custom SP in the Model Database, when you create a new database, it will automatically exist in that database. Any database that was already created before making changes in the Model Database will not be affected at all. Creating Policy is also a good method, and I will blog about this in a separate blog post, but looking at current specifications of the reader, I think the Model Database should be modified to have a Full Recovery Option. While writing this blog post, I remembered my another blog post where the model database log file was growing drastically even though there were no transactions SQL SERVER – Log File Growing for Model Database – model Database Log File Grew Too Big. NOTE: Please do not touch the Model Database unnecessary. It is a strict “No.” If you want to create an object that you need in all the databases, then instead of creating it in model database, I suggest that you create a new database called maintenance and create the object there. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, Readers Question, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Oracle Database 12 c New Partition Maintenance Features by Gwen Lazenby

    - by hamsun
    One of my favourite new features in Oracle Database 12c is the ability to perform partition maintenance operations on multiple partitions. This means we can now add, drop, truncate and merge multiple partitions in one operation, and can split a single partition into more than two partitions also in just one command. This would certainly have made my life slightly easier had it been available when I administered a data warehouse at Oracle 9i. To demonstrate this new functionality and syntax, I am going to create two tables, ORDERS and ORDERS_ITEMS which have a parent-child relationship. ORDERS is to be partitioned using range partitioning on the ORDER_DATE column, and ORDER_ITEMS is going to partitioned using reference partitioning and its foreign key relationship with the ORDERS table. This form of partitioning was a new feature in 11g and means that any partition maintenance operations performed on the ORDERS table will also take place on the ORDER_ITEMS table as well. First create the ORDERS table - SQL CREATE TABLE orders ( order_id NUMBER(12), order_date TIMESTAMP, order_mode VARCHAR2(8), customer_id NUMBER(6), order_status NUMBER(2), order_total NUMBER(8,2), sales_rep_id NUMBER(6), promotion_id NUMBER(6), CONSTRAINT orders_pk PRIMARY KEY(order_id) ) PARTITION BY RANGE(order_date) (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007 VALUES LESS THAN (TO_DATE('01-JAN-2008','DD-MON-YYYY')) ); Table created. Now the ORDER_ITEMS table SQL CREATE TABLE order_items ( order_id NUMBER(12) NOT NULL, line_item_id NUMBER(3) NOT NULL, product_id NUMBER(6) NOT NULL, unit_price NUMBER(8,2), quantity NUMBER(8), CONSTRAINT order_items_fk FOREIGN KEY(order_id) REFERENCES orders(order_id) on delete cascade) PARTITION BY REFERENCE(order_items_fk) tablespace example; Table created. Now look at DBA_TAB_PARTITIONS to get details of what partitions we have in the two tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 Just as an aside it is also now possible in 12c to use interval partitioning on reference partitioned tables. In 11g it was not possible to combine these two new partitioning features. For our first example of the new 12cfunctionality, let us add all the partitions necessary for 2008 to the tables using one command. Notice that the partition specification part of the add command is identical in format to the partition specification part of the create command as shown above - SQL alter table orders add PARTITION Q1_2008 VALUES LESS THAN (TO_DATE('01-APR-2008','DD-MON-YYYY')), PARTITION Q2_2008 VALUES LESS THAN (TO_DATE('01-JUL-2008','DD-MON-YYYY')), PARTITION Q3_2008 VALUES LESS THAN (TO_DATE('01-OCT-2008','DD-MON-YYYY')), PARTITION Q4_2008 VALUES LESS THAN (TO_DATE('01-JAN-2009','DD-MON-YYYY')); Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 4 new partitions have been added to both tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q1_2008 5 TIMESTAMP' 2008-04-01 00:00:00' ORDER_ITEMS Q1_2008 5 ORDERS Q2_2008 6 TIMESTAMP' 2008-07-01 00:00:00' ORDER_ITEM Q2_2008 6 ORDERS Q3_2008 7 TIMESTAMP' 2008-10-01 00:00:00' ORDER_ITEMS Q3_2008 7 ORDERS Q4_2008 8 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 8 Next, we can drop or truncate multiple partitions by giving a comma separated list in the alter table command. Note the use of the plural ‘partitions’ in the command as opposed to the singular ‘partition’ prior to 12c– SQL alter table orders drop partitions Q3_2008,Q2_2008,Q1_2008; Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 3 partitions have been dropped in both the two tables – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Now let us merge all the 2007 partitions together to form one single partition – SQL alter table orders merge partitions Q1_2005, Q2_2005, Q3_2005, Q4_2005 into partition Y_2007; Table altered. TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Y_2007 1 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Y_2007 1 ORDERS Q4_2008 2 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 2 Splitting partitions is a slightly more involved. In the case of range partitioning one of the new partitions must have no high value defined, and in list partitioning one of the new partitions must have no list of values defined. I call these partitions the ‘everything else’ partitions, and will contain any rows contained in the original partition that are not contained in the any of the other new partitions. For example, let us split the Y_2007 partition back into 4 quarterly partitions – SQL alter table orders split partition Y_2007 into (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007); Now look at DBA_TAB_PARTITIONS to get details of the new partitions – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Partition Q4_2007 has a high value equal to the high value of the original Y_2007 partition, and so has inherited its upper boundary from the partition that was split. As for a list partitioning example let look at the following another table, SALES_PAR_LIST, which has 2 partitions, Americas and Europe and a partitioning key of country_name. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE -------------- --------------- ----------------------------- SALES_PAR_LIST AMERICAS 'Argentina', 'Canada', 'Peru', 'USA', 'Honduras', 'Brazil', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' Now split the Americas partition into 3 partitions – SQL alter table sales_par_list split partition americas into (partition south_america values ('Argentina','Peru','Brazil'), partition north_america values('Canada','USA'), partition central_america); Table altered. Note that no list of values was given for the ‘Central America’ partition. However it should have inherited any values in the original ‘Americas’ partition that were not assigned to either the ‘North America’ or ‘South America’ partitions. We can confirm this by looking at the DBA_TAB_PARTITIONS view. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE --------------- --------------- -------------------------------- SALES_PAR_LIST SOUTH_AMERICA 'Argentina', 'Peru', 'Brazil' SALES_PAR_LIST NORTH_AMERICA 'Canada', 'USA' SALES_PAR_LIST CENTRAL_AMERICA 'Honduras', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' In conclusion, I hope that DBA’s whose work involves maintaining partitions will find the operations a bit more straight forward to carry out once they have upgraded to Oracle Database 12c. Gwen Lazenby is a Principal Training Consultant at Oracle. She is part of Oracle University's Core Technology delivery team based in the UK, teaching Database Administration and Linux courses. Her specialist topics include using Oracle Partitioning and Parallelism in Data Warehouse environments, as well as Oracle Spatial and RMAN.

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  • Statistical Sampling for Verifying Database Backups

    A DBA's huge workload can start to threaten best practices for data backup and recovery, but ingenuity, and an eye for a good tactic, can usually find a way. For Tom, the revelation about a solution came from eating crabs. Statistical sampling can be brought to bear to minimise the risk of faliure of an emergency database restore.

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  • Configurable tables in sql database

    - by dot
    I have the following tables in my database: Config Table: ====================================== Start_Range | End Range | Config_id 10 | 15 | 1 ====================================== Available_UserIDs ========================== ID | UserID | Used_YN | 1 | 10 | t | 1 | 11 | f | 1 | 12 | f | 1 | 13 | f | 1 | 14 | f | 1 | 15 | f | ========================== Users ========================== UserId | FName | LName | 10 |John | Doe | ========================== This is used in a reservation system of sorts... which lets an administrator specify a range of numbers that will be assigned to users in the config table. Once the range has been defined, the system then populates the Available_userIDs table with all the numbers in between the range, and sets the Used_YN flag to false As users sign up, they grab the next user_id number that's not in use... and reserve it. Then the system adds a record to the Users table. Once the admin has specified a range, it is possible that they can change it. For example, they can start with 10-15... and then when the range is used up, they should be able to specify another range like 16 - 99. I've put a unique constraint on the Available_UserIDs table, as well as on the Users table - to ensure that UserIds can't be duplicated. My questions are as follows: What's the best way to prevent the admins from using a range that's already in use? I thought of the following options: -- check either the Users table to see if the start range or ending range numbers are being used. If they are, assume that all the numbers in between are in use too, and reject the range. -- let them specify whatever they want, try to populate the Available_UserIDs table. If there are duplicates, just ignore that specific error message from the database and continue on. How do I find gaps in the number ranges? For example, if they specify 10-15, and then 20-25, it'd be nice to be able to somehow suggest on my web page that 16-19 is currently available. I found this article: http://stackoverflow.com/questions/1312101/how-to-find-a-gap-in-running-counter-with-sql But it only seems to return the first available number... so in my example above, it would only return the number 16. I'm sure there's a simpler way to do things that I'm overlooking!

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  • How to connect to database on remote server

    - by user137263
    Where there is VPN to remote server and then access to the database via local network interface, how can one establish a remote link between one's computer (with a programme such as Visual Studio 2010) and SQL Server (e.g. 2008 R2) ? Any attempts to create a direct link to the SQL Server are blocked. Whilst the SQL Server can be configured to allow external access, this provides its own host of problems. Any help would be much appreciated.

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  • What is wrong with this database query?

    - by outsyncof
    I have the following tables in a database (i'll only list the important attributes): Person(ssn,countryofbirth) Parents(ssn,fatherbirthcountry) Employment(ssn, companyID) Company(companyID, name) My task is this: given fatherbirthcountry as input, output the names of companies where persons work whose countryofbirth match the fatherbirthcountry input. I pretend that the fatherbirthcountry is Mexico and do this: SELECT name FROM Company WHERE companyid = (SELECT companyid FROM Employment WHERE ssn = (SELECT ssn FROM Person WHERE countryofbirth = 'Mexico'); but it is giving me an error: >Scalar subquery is only allowed to return a single row. am I completely off track? Can anybody please help?

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  • Has anyone ever worked with a UX designer who also did the graphic design, is it a good combination?

    - by Ami
    I need to design a new framework for web based apps, including both UX guidelines and the art/graphic design guidelines such as what menus will look like, headers, colors, fonts etc. The UX designers I met, were unable to provide the artistic side, and the graphic designers didn't have the UX skills. Should I continue to look for one person with both skills, or is it better broken to two separate tasks?

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  • replicating master tables mapping in transaction tables

    - by NoDisplay
    I have three master tables for location information Country {ID, Name} State {ID, Name, CountryID} City {ID, Name, StateID} Now I have one transcation table called Person which hold the person name and his location information. My Question is shall I have only CityID in the Person table like this: Person {ID, Name, CityID}' And have view of join query which give me detail like "Person{ID,Name,City,State,Country}" or Shall I replicate the mapping Person {ID, Name, CityID, StateID, CountryID} Please suggest which do you feel is to be selected and why? if there is any other option available, please suggest. Thanks in advance.

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  • Cloud Computing Forces Better Design Practices

    - by Herve Roggero
    Is cloud computing simply different than on premise development, or is cloud computing actually forcing you to create better applications than you normally would? In other words, is cloud computing merely imposing different design principles, or forcing better design principles?  A little while back I got into a discussion with a developer in which I was arguing that cloud computing, and specifically Windows Azure in his case, was forcing developers to adopt better design principles. His opinion was that cloud computing was not yielding better systems; just different systems. In this blog, I will argue that cloud computing does force developers to use better design practices, and hence better applications. So the first thing to define, of course, is the word “better”, in the context of application development. Looking at a few definitions online, better means “superior quality”. As it relates to this discussion then, I stipulate that cloud computing can yield higher quality applications in terms of scalability, everything else being equal. Before going further I need to also outline the difference between performance and scalability. Performance and scalability are two related concepts, but they don’t mean the same thing. Scalability is the measure of system performance given various loads. So when developers design for performance, they usually give higher priority to a given load and tend to optimize for the given load. When developers design for scalability, the actual performance at a given load is not as important; the ability to ensure reasonable performance regardless of the load becomes the objective. This can lead to very different design choices. For example, if your objective is to obtains the fastest response time possible for a service you are building, you may choose the implement a TCP connection that never closes until the client chooses to close the connection (in other words, a tightly coupled service from a connectivity standpoint), and on which a connection session is established for faster processing on the next request (like SQL Server or other database systems for example). If you objective is to scale, you may implement a service that answers to requests without keeping session state, so that server resources are released as quickly as possible, like a REST service for example. This alternate design would likely have a slower response time than the TCP service for any given load, but would continue to function at very large loads because of its inherently loosely coupled design. An example of a REST service is the NO-SQL implementation in the Microsoft cloud called Azure Tables. Now, back to cloud computing… Cloud computing is designed to help you scale your applications, specifically when you use Platform as a Service (PaaS) offerings. However it’s not automatic. You can design a tightly-coupled TCP service as discussed above, and as you can imagine, it probably won’t scale even if you place the service in the cloud because it isn’t using a connection pattern that will allow it to scale [note: I am not implying that all TCP systems do not scale; I am just illustrating the scalability concepts with an imaginary TCP service that isn’t designed to scale for the purpose of this discussion]. The other service, using REST, will have a better chance to scale because, by design, it minimizes resource consumption for individual requests and doesn’t tie a client connection to a specific endpoint (which means you can easily deploy this service to hundreds of machines without much trouble, as long as your pockets are deep enough). The TCP and REST services discussed above are both valid designs; the TCP service is faster and the REST service scales better. So is it fair to say that one service is fundamentally better than the other? No; not unless you need to scale. And if you don’t need to scale, then you don’t need the cloud in the first place. However, it is interesting to note that if you do need to scale, then a loosely coupled system becomes a better design because it can almost always scale better than a tightly-coupled system. And because most applications grow overtime, with an increasing user base, new functional requirements, increased data and so forth, most applications eventually do need to scale. So in my humble opinion, I conclude that a loosely coupled system is not just different than a tightly coupled system; it is a better design, because it will stand the test of time. And in my book, if a system stands the test of time better than another, it is of superior quality. Because cloud computing demands loosely coupled systems so that its underlying service architecture can be leveraged, developers ultimately have no choice but to design loosely coupled systems for the cloud. And because loosely coupled systems are better… … the cloud forces better design practices. My 2 cents.

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  • Export MS SQL database as *.dbschema

    - by jjczopek
    We have a production database and visual studio 2010 database project. We had to make some changes in database schema. Unfortunately we don't have previous database schema file for production database. Is there a way to export existing database schema as *.dbschema file, preferably from Microsoft SQL Server Management Studio (2008 R2)? This way we could run schema comparison and generate update script.

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  • TDE Tablespace Encryption 11.2.0.1 Certified with EBS 12

    - by Steven Chan
    Oracle Advanced Security is an optional licenced Oracle 11g Database add-on.  Oracle Advanced Security Transparent Data Encryption (TDE) offers two different features:  column encryption and tablespace encryption.  11.2.0.1 TDE Column encryption was certified with E-Business Suite 12 as part of our overall 11.2.0.1 database certification.  As of today, 11.2.0.1 TDE Tablespace encryption is now certified with Oracle E-Business Suite Release 12. What is Transparent Data Encryption (TDE) ? Oracle Advanced Security Transparent Data Encryption (TDE) allows you to protect data at rest. TDE helps address privacy and PCI requirements by encrypting personally identifiable information (PII) such as Social Security numbers and credit card numbers. TDE is completely transparent to existing applications with no triggers, views or other application changes required. Data is transparently encrypted when written to disk and transparently decrypted after an application user has successfully authenticated and passed all authorization checks. Authorization checks include verifying the user has the necessary select and update privileges on the application table and checking Database Vault, Label Security and Virtual Private Database enforcement policies.

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  • Event on SQL Server 2008 Disk IO and the new Complex Event Processing (StreamInsight) feature in R2

    - by tonyrogerson
    Allan Mitchell and myself are doing a double act, Allan is becoming one of the leading guys in the UK on StreamInsight and will give an introduction to this new exciting technology; on top of that I'll being talking about SQL Server Disk IO - well, "Disk" might not be relevant anymore because I'll be talking about SSD and IOFusion - basically I'll be talking about the underpinnings - making sure you understand and get it right, how to monitor etc... If you've any specific problems or questions just ping me an email [email protected]. To register for the event see: http://sqlserverfaq.com/events/217/SQL-Server-and-Disk-IO-File-GroupsFiles-SSDs-FusionIO-InRAM-DBs-Fragmentation-Tony-Rogerson-Complex-Event-Processing-Allan-Mitchell.aspx 18:15 SQL Server and Disk IOTony Rogerson, SQL Server MVPTony's Blog; Tony on TwitterIn this session Tony will talk about RAID levels, how SQL server writes to and reads from disk, the effect SSD has and will talk about other options for throughput enhancement like Fusion IO. He will look at the effect fragmentation has and how to minimise the impact, he will look at the File structure of a database and talk about what benefits multiple files and file groups bring. We will also touch on Database Mirroring and the effect that has on throughput, how to get a feeling for the throughput you should expect.19:15 Break19:45 Complex Event Processing (CEP)Allan Mitchell, SQL Server MVPhttp://sqlis.com/sqlisStreamInsight is Microsoft’s first foray into the world of Complex Event Processing (CEP) and Event Stream Processing (ESP).  In this session I want to show an introduction to this technology.  I will show how and why it is useful.  I will get us used to some new terminology but best of all I will show just how easy it is to start building your first CEP/ESP application.

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  • Best approach to accessing multiple data source in a web application

    - by ced
    I've a base web application developed with .net technologies (asp.net) used into our LAN by 30 users simultanousley. From this web application I've developed two verticalization used from online users. In future i expect hundreds users simultanousley. Our company has different locations. Each site use its own database. The web application needs to retrieve information from all existing databases. Currently there are 3 database, but it's not excluded in the future expansion of new offices. My question then is: What is the best strategy for a web application to retrieve information from different databases (which have the same schema) whereas the main objective performance data access and high fault tolerance? There are case studies in the literature that I can take as an example? Do you know some good documents to study? Do you have any tips to implement this task so efficient? Intuitively I would say that two possible strategy are: perform queries from different sources in real time and aggregate data on the fly; create a repository that contains the union of the entities of interest and perform queries directly on repository;

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  • Storing revisions of a document

    - by dev.e.loper
    This is a follow up question to my original question. I'm thinking of going with generating diffs and storing those diffs in the database 'History' table. I'm using diff-match-patch library to generate what is called a 'patch'. On every save, I compare previous and new version and generate this patch. The patch could be used to generate a document at specific point in time. My dilemma is how to store this data. Should I: a Insert a new database record for every patch? b. Store these patches in javascript array and store that array in history table. So there is only one db History record for document with an array of all the patches. Concerns with: a. Too many db records generated. Will be slow and CPU intensive to query. b. Only one record. If record is somehow corrupted/deleted. Entire revision history is gone. I'm looking for suggestions, concerns with either approach.

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