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  • If we make a number every millisecond, how much data would we have in a day?

    - by Roger Travis
    I'm a bit confused here... I'm being offered to get into a project, where would be an array of certain sensors, that would give off reading every millisecond ( yes, 1000 reading in a second ). Reading would be a 3 or 4 digit number, for example like 818 or 1529. This reading need to be stored in a database on a server and accessed remotely. I never worked with such big amounts of data, what do you think, how much in terms of MBs reading from one sensor for a day would be?... 4(digits)x1000x60x60x24 ... = 345600000 bits ... right ? about 42 MB per day... doesn't seem too bad, right? therefor a DB of, say, 1 GB, would hold 23 days of info from 1 sensor, correct? I understand that MySQL & PHP probably would not be able to handle it... what would you suggest, maybe some aps? azure? oracle? ... Thansk!

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  • Delivering activity feed items in a moderately scalable way

    - by sotangochips
    The application I'm working on has an activity feed where each user can see their friends' activity (much like Facebook). I'm looking for a moderately scalable way to show a given users' activity stream on the fly. I say 'moderately' because I'm looking to do this with just a database (Postgresql) and maybe memcached. For instance, I want this solution to scale to 200k users each with 100 friends. Currently, there is a master activity table that stores the rendered html for the given activity (Jim added a friend, George installed an application, etc.). This master activity table keeps the source user, the html, and a timestamp. Then, there's a separate ('join') table that simply keeps a pointer to the person who should see this activity in their friend feed, and a pointer to the object in the main activity table. So, if I have 100 friends, and I do 3 activities, then the join table will then grow to 300 items. Clearly this table will grow very quickly. It has the nice property, though, that fetching activity to show to a user takes a single (relatively) inexpensive query. The other option is to just keep the main activity table and query it by saying something like: select * from activity where source_user in (1, 2, 44, 2423, ... my friend list) This has the disadvantage that you're querying for users who may never be active, and as your friend list grows, this query can get slower and slower. I see the pros and the cons of both sides, but I'm wondering if some SO folks might help me weigh the options and suggest one way or they other. I'm also open to other solutions, though I'd like to keep it simple and not install something like CouchDB, etc. Many thanks!

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  • Having to insert a record, then update the same record warrants 1:1 relationship design?

    - by dianovich
    Let's say an Order has many Line items and we're storing the total cost of an order (based on the sum of prices on order lines) in the orders table. -------------- orders -------------- id ref total_cost -------------- -------------- lines -------------- id order_id price -------------- In a simple application, the order and line are created during the same step of the checkout process. So this means INSERT INTO orders .... -- Get ID of inserted order record INSERT into lines VALUES(null, order_id, ...), ... where we get the order ID after creating the order record. The problem I'm having is trying to figure out the best way to store the total cost of an order. I don't want to have to create an order create lines on an order calculate cost on order based on lines then update record created in 1. in orders table This would mean a nullable total_cost field on orders for starters... My solution thus far is to have an order_totals table with a 1:1 relationship to the orders table. But I think it's redundant. Ideally, since everything required to calculate total costs (lines on an order) is in the database, I would work out the value every time I need it, but this is very expensive. What are your thoughts?

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  • guarantee child records either in one table or another, but not both?

    - by user151841
    I have a table with two child tables. For each record in the parent table, I want one and only one record in one of the child tables -- not one in each, not none. How to I define that? Here's the backstory. Feel free to criticize this implementation, but please answer the question above, because this isn't the only time I've encountered it: I have a database that holds data pertaining to user surveys. It was originally designed with one authentication method for starting a survey. Since then, requirements have changed, and now there are two different ways someone could sign on to start a survey. Originally I captured the authentication token in a column in the survey table. Since requirements changed, there are three other bits of data that I want to capture in authentication. So for each record in the survey table, I'm either going to have one token, or a set of three. All four of these are of different types, so my thought was, instead of having four columns where either one is going to be null, or three are going to be null ( or even worse, a bad mashup of either of those scenarios ), I would have two child tables, one for holding the single authentication token, the other for holding the three. Problem is, I don't know offhand how to define that in DDL. I'm using MySQL, so maybe there's a feature that MySQL doesn't implement that lets me do this.

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  • SQL SERVER – Copy Data from One Table to Another Table – SQL in Sixty Seconds #031 – Video

    - by pinaldave
    Copy data from one table to another table is one of the most requested questions on forums, Facebook and Twitter. The question has come in many formats and there are places I have seen developers are using cursor instead of this direct method. Earlier I have written the similar article a few years ago - SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE. The article has been very popular and I have received many interesting and constructive comments. However there were two specific comments keep on ending up on my mailbox. 1) SQL Server AdventureWorks Samples Database does not have table I used in the example 2) If there is a video tutorial of the same example. After carefully thinking I decided to build a new set of the scripts for the example which are very similar to the old one as well video tutorial of the same. There was no better place than our SQL in Sixty Second Series to cover this interesting small concept. Let me know what you think of this video. Here is the updated script. -- Method 1 : INSERT INTO SELECT USE AdventureWorks2012 GO ----Create TestTable CREATE TABLE TestTable (FirstName VARCHAR(100), LastName VARCHAR(100)) ----INSERT INTO TestTable using SELECT INSERT INTO TestTable (FirstName, LastName) SELECT FirstName, LastName FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO --------------------------------------------------------- --------------------------------------------------------- -- Method 2 : SELECT INTO USE AdventureWorks2012 GO ----Create new table and insert into table using SELECT INSERT SELECT FirstName, LastName INTO TestTable FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO Related Tips in SQL in Sixty Seconds: SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE Powershell – Importing CSV File Into Database – Video SQL SERVER – 2005 – Export Data From SQL Server 2005 to Microsoft Excel Datasheet SQL SERVER – Import CSV File into Database Table Using SSIS SQL SERVER – Import CSV File Into SQL Server Using Bulk Insert – Load Comma Delimited File Into SQL Server SQL SERVER – 2005 – Generate Script with Data from DatabaseDatabase Publishing Wizard What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com)   Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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  • SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

    - by pinaldave
    Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • What is Database Continuous Integration?

    - by David Atkinson
    Although not everyone is practicing continuous integration, many have at least heard of the concept. A recent poll on www.simple-talk.com indicates that 40% of respondents are employing the technique. It is widely accepted that the earlier issues are identified in the development process, the lower the cost to the development process. The worst case scenario, of course, is for the bug to be found by the customer following the product release. A number of Agile development best practices have evolved to combat this problem early in the development process, including pair programming, code inspections and unit testing. Continuous integration is one such Agile concept that tackles the problem at the point of committing a change to source control. This can alternatively be run on a regular schedule. This triggers a sequence of events that compiles the code and performs a variety of tests. Often the continuous integration process is regarded as a build validation test, and if issues were to be identified at this stage, the testers would simply not 'waste their time ' and touch the build at all. Such a ‘broken build’ will trigger an alert and the development team’s number one priority should be to resolve the issue. How application code is compiled and tested as part of continuous integration is well understood. However, this isn’t so clear for databases. Indeed, before I cover the mechanics of implementation, we need to decide what we mean by database continuous integration. For me, database continuous integration can be implemented as one or more of the following: 1)      Your application code is being compiled and tested. You therefore need a database to be maintained at the corresponding version. 2)      Just as a valid application should compile, so should the database. It should therefore be possible to build a new database from scratch. 3)     Likewise, it should be possible to generate an upgrade script to take your already deployed databases to the latest version. I will be covering these in further detail in future blogs. In the meantime, more information can be found in the whitepaper linked off www.red-gate.com/ci If you have any questions, feel free to contact me directly or post a comment to this blog post.

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  • What is Database Continuous Integration?

    - by SQLDev
    Although not everyone is practicing continuous integration, many have at least heard of the concept. A recent poll on www.simple-talk.com indicates that 40% of respondents are employing the technique. It is widely accepted that the earlier issues are identified in the development process, the lower the cost to the development process. The worst case scenario, of course, is for the bug to be found by the customer following the product release. A number of Agile development best practices have evolved to combat this problem early in the development process, including pair programming, code inspections and unit testing. Continuous integration is one such Agile concept that tackles the problem at the point of committing a change to source control. This can alternatively be run on a regular schedule. This triggers a sequence of events that compiles the code and performs a variety of tests. Often the continuous integration process is regarded as a build validation test, and if issues were to be identified at this stage, the testers would simply not 'waste their time ' and touch the build at all. Such a ‘broken build’ will trigger an alert and the development team’s number one priority should be to resolve the issue. How application code is compiled and tested as part of continuous integration is well understood. However, this isn’t so clear for databases. Indeed, before I cover the mechanics of implementation, we need to decide what we mean by database continuous integration. For me, database continuous integration can be implemented as one or more of the following: 1)      Your application code is being compiled and tested. You therefore need a database to be maintained at the corresponding version. 2)      Just as a valid application should compile, so should the database. It should therefore be possible to build a new database from scratch. 3)     Likewise, it should be possible to generate an upgrade script to take your already deployed databases to the latest version. I will be covering these in further detail in future blogs. In the meantime, more information can be found in the whitepaper linked off www.red-gate.com/ci If you have any questions, feel free to contact me directly or post a comment to this blog post.

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  • Do you test your SQL/HQL/Criteria ?

    - by 0101
    Do you test your SQL or SQL generated by your database framework? There are frameworks like DbUnit that allow you to create real in-memory database and execute real SQL. But its very hard to use(not developer-friendly so to speak), because you need to first prepare test data(and it should not be shared between tests). P.S. I don't mean mocking database or framework's database methods, but tests that make you 99% sure that your SQL is working even after some hardcore refactoring.

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  • .Net Application & Database Modularity/Reuse

    - by Martaver
    I'm looking for some guidance on how to architect an app with regards to modularity, separation of concerns and re-usability. I'm working on an application (ASP.Net, C#) that has distinctly generic chunks of functionality, that I'd love to be able to lift out, all layers, into re-usable components. This means the module handles the database schema, data access, API, everything so that the next time I want to use it I can just register the module and hook into it. Developing modules of re-usable functionality is a no-brainer, but what is really confusing me is what to do when it comes to handling a core re-usable database schema that serves the module's functionality. In an ideal world, I would register a module and it would ensure that the associated database schema exists in the DB. I would code on the assumption that the tables exist, calling the module's functionality through the DLL, agnostic of the database layer. Kind of like Enterprise Library's Caching/Logging Application Block, which can create a DB schema in the target DB to use as a data store. My Questions is: What do you think is the best way to achieve this, firstly, in terms design architecture, and secondly solution structure. What patterns/frameworks do you know that exist & support this kind of thing? My thoughts so far: I mostly use Entity Framework and SQL Server DB Projects. I thought about a 'black box' approach to modules of functionality. I could use use a code-first approach in EF4, and use the ObjectContext to create a database when the module is initialized. However this means that all of the entities that my module encapsulates would be disconnected from the rest of the application because they belonged to an abstracted ObjectContext. Further - Creating appropriate indexes and references between domain entities and the module's entities would be impossible to do practically. I've thought of adopting Enterprise Library and creating my own Application Blocks. I'm not sure how this would play nice with Entity Framework (if at all) though. I like the idea of building on proven patterns & practices to encapsulate established, reusable functionality. I thought of abandoning Entity Framework for the Module, and just creating a separate DB schema for the module with its own set of stored procedures & ADO.Net. Then deploying the script at run-time if interrogation shows that it doesn't exist. But once again, for application developing outside of the application, I would want to use Entity Framework and I would have to use the module separately, disconnected from the domain ObjectContext. Has anyone had experience developing these sorts of full-stack modules? What advice can you offer? Am I biting off more than I can chew?

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  • How to mount an Oracle database to new instance?

    - by Vimvq1987
    I have an instance of Oracle 10g R2 installed on Windows Server 2003. This instance was running an database, which does not have any backup. Now the OS went down, and could not repaired, all I got is the running files of the old instance. How can I restore the database from these files to new instance? A step-by-step guide will be much appreciated because I'm new with Oracle. Thank you very much

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  • Cannot Attach Database in SQL Express More Than Two Directories Deep?

    - by Dave Mackey
    I have a database in one of my Visual Studio Express projects. I want to attach it to my local SQLEXPRESS instance so I can run aspnet_regsql on it and add the membership database. When I select Attach Databases and then attempt to browse to the files (C:\Users\username\Documents\Visual Studio 2010\Projects\nameofproject) it only lets me navigate to C:\Users\username...Why? How can I fix this?

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  • How do I convert a Mac OS Filemaker 2 database to a recent FM or Bento db, preserving the relations

    - by willc2
    I'm hoping for more than just exporting the data, I would like to preserve the relation between the databases. This is for a friend's legacy database that tracks monthly fees from a list of clients. I have the original FM database file on hand, but not the machine it ran on with the old version of Filemaker 2. Recent versions won't import it, saying it's too old. If there is a Mac-only solution that would make things simpler for me.

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  • When and how often to start connection to database in php?

    - by AndHeiberg
    When and how often is it good practice to start the connection to your database in php? I'm new to databases, and I'm wondering when I should start by database connection. I'm creating a api with an index, controllers and model. Should I start the connection in the index and then pass it to all the other files, start the connection at the top of all files and call it as a global in functions as needed or start and end the connection in every function?

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  • Normalizing Item Names & Synonyms

    - by RabidFire
    Consider an e-commerce application with multiple stores. Each store owner can edit the item catalog of his store. My current database schema is as follows: item_names: id | name | description | picture | common(BOOL) items: id | item_name_id | picture | price | description | picture item_synonyms: id | item_name_id | name | error(BOOL) Notes: error indicates a wrong spelling (eg. "Ericson"). description and picture of the item_names table are "globals" that can optionally be overridden by "local" description and picture fields of the items table (in case the store owner wants to supply a different picture for an item). common helps separate unique item names ("Jimmy Joe's Cheese Pizza" from "Cheese Pizza") I think the bright side of this schema is: Optimized searching & Handling Synonyms: I can query the item_names & item_synonyms tables using name LIKE %QUERY% and obtain the list of item_name_ids that need to be joined with the items table. (Examples of synonyms: "Sony Ericsson", "Sony Ericson", "X10", "X 10") Autocompletion: Again, a simple query to the item_names table. I can avoid the usage of DISTINCT and it minimizes number of variations ("Sony Ericsson Xperia™ X10", "Sony Ericsson - Xperia X10", "Xperia X10, Sony Ericsson") The down side would be: Overhead: When inserting an item, I query item_names to see if this name already exists. If not, I create a new entry. When deleting an item, I count the number of entries with the same name. If this is the only item with that name, I delete the entry from the item_names table (just to keep things clean; accounts for possible erroneous submissions). And updating is the combination of both. Weird Item Names: Store owners sometimes use sentences like "Harry Potter 1, 2 Books + CDs + Magic Hat". There's something off about having so much overhead to accommodate cases like this. This would perhaps be the prime reason I'm tempted to go for a schema like this: items: id | name | picture | price | description | picture (... with item_names and item_synonyms as utility tables that I could query) Is there a better schema you would suggested? Should item names be normalized for autocomplete? Is this probably what Facebook does for "School", "City" entries? Is the first schema or the second better/optimal for search? Thanks in advance! References: (1) Is normalizing a person's name going too far?, (2) Avoiding DISTINCT

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  • DB Design Pattern - Many to many classification / categorised tagging.

    - by Robin Day
    I have an existing database design that stores Job Vacancies. The "Vacancy" table has a number of fixed fields across all clients, such as "Title", "Description", "Salary range". There is an EAV design for "Custom" fields that the Clients can setup themselves, such as, "Manager Name", "Working Hours". The field names are stored in a "ClientText" table and the data stored in a "VacancyClientText" table with VacancyId, ClientTextId and Value. Lastly there is a many to many EAV design for custom tagging / categorising the vacancies with things such as Locations/Offices the vacancy is in, a list of skills required. This is stored as a "ClientCategory" table listing the types of tag, "Locations, Skills", a "ClientCategoryItem" table listing the valid values for each Category, e.g., "London,Paris,New York,Rome", "C#,VB,PHP,Python". Finally there is a "VacancyClientCategoryItem" table with VacancyId and ClientCategoryItemId for each of the selected items for the vacancy. There are no limits to the number of custom fields or custom categories that the client can add. I am now designing a new system that is very similar to the existing system, however, I have the ability to restrict the number of custom fields a Client can have and it's being built from scratch so I have no legacy issues to deal with. For the Custom Fields my solution is simple, I have 5 additional columns on the Vacancy Table called CustomField1-5. This removes one of the EAV designs. It is with the tagging / categorising design that I am struggling. If I limit a client to having 5 categories / types of tag. Should I create 5 tables listing the possible values "CustomCategoryItems1-5" and then an additional 5 many to many tables "VacancyCustomCategoryItem1-5" This would result in 10 tables performing the same storage as the three tables in the existing system. Also, should (heaven forbid) the requirements change in that I need 6 custom categories rather than 5 then this will result in a lot of code change. Therefore, can anyone suggest any DB Design Patterns that would be more suitable to storing such data. I'm happy to stick with the EAV approach, however, the existing system has come across all the usual performance issues and complex queries associated with such a design. Any advice / suggestions are much appreciated. The DBMS system used is SQL Server 2005, however, 2008 is an option if required for any particular pattern.

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  • What does the information_schema database represent?

    - by Mirage
    I have one database in mysql. But when i log into phpMyAdmin , it shows another database called information_schema. Is that database always present with one database? I mean to say is there a copy of information_schema for every database present in mysql or is there one database called inforemation_schema per mysql server? If i modify this information_schema database how will that affect my current database?

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  • How do I efficiently write a "toggle database value" function in AJAX?

    - by AmbroseChapel
    Say I have a website which shows the user ten images and asks them to categorise each image by clicking on buttons. A button for "funny", a button for "scary", a button for "pretty" and so on. These buttons aren't exclusive. A picture can be both funny and scary. The user clicks the "funny" button. An AJAX request is sent off to the database to mark that image as funny. The "funny" button lights up, by assigning a class in the DOM to mark it as "on". But the user made a mistake. They meant to hit the next button over. They should click "funny" again to turn it off, right? At this point I'm not sure whats the most efficient way to proceed. The database knows that the "funny" flag is set, but it's inefficient to query the database every time a button is clicked to say, is this flag set or not, then go on with a second database call to toggle it. Should I infer the state of the database flag from the DOM, i.e. if that button has the class "on" then the flag must be set, and branch at that point? Or would it be better to have a data structure in Javascript in the page which duplicates the state of each image in the database, so that every time I set the database flag to true, I also set the value in the Javascript data to true and so on?

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  • Which database I can used and relationship in it ??

    - by mimo-hamad
    My projece make me confused which I didn't find clear things that make me understand the required database and the relationships in it So, would a super one help me to solve it ?!! ;D this is required: 1) Model the data stored in the database (Identify the entities, roles, relationships, constraints, etc.) 2) Write the Oracle commands to create the database, find appropriate data, and populate the database 3) Write five different queries on your database, using the SELECT/FROM/WHERE construct provided in SQL. Your five queries should illustrate several different aspects of database querying, such as: a. Queries over more than one relation (by listing more than one relation in the FROM clause) b. Queries involving aggregate functions, such as SUM, COUNT, and AVG c. Queries involving complicated selects and joins d. Queries involving GROUP BY, HAVING or other similar functions. e. Queries that require the use of the DISTINCT keyword. And this the condition that we need to determine it to solve the required Q's above : 5) It is desired to develop an Internet membership club to buy products at special prices online. To join, new members must be referred by another existing member of the club. The system will keep the following information for each member: The member ID, referring member, birth date, member name, address, phone, mobile, credit card type, number and expiration date. The items are always shipped to the member's address noted in the membership application. The shipping fees will differ for each order.For each item to be requested, the member will select an item from a long list of possible items. For each item in the database, we store an item ID, an item name, description, and list price. The list price will be different from the actual sale price. The available quantity and the back-ordered quantity (the back-ordered quantity is the quantity on-order by the club from its suppliers) is also noted

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  • Do I need a spatial index in my database?

    - by Sanoj
    I am designing an application that needs to save geometric shapes in a database. I haven't choosen the database management system yet. In my application, all database queries will have an bounding box as input, and as output I want all shapes within that database. I know that databases with a spatial index is used for this kind of application. But in my application there will not be any queries of type "give me objects nearby x/y" or other more complex queries that are useful in a GIS application. I am planning of having a database without a spatial index and have queries looking like: SELECT * FROM shapes WHERE x < max_x AND x > min_x AND y < max_y AND y > min_y And have an index on the columns x (double) and y (double). As long I can see, I don't really need a database with an spatial index, howsoever my application is close to that kind of applications. And even if I would like to have nearby queries, then I could create a big enough bounding box around that point. Or will this lead to poor performance? Do I really need a spatial database? And when is a spatial index needed?

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  • VLOOKUP in Excel, part 2: Using VLOOKUP without a database

    - by Mark Virtue
    In a recent article, we introduced the Excel function called VLOOKUP and explained how it could be used to retrieve information from a database into a cell in a local worksheet.  In that article we mentioned that there were two uses for VLOOKUP, and only one of them dealt with querying databases.  In this article, the second and final in the VLOOKUP series, we examine this other, lesser known use for the VLOOKUP function. If you haven’t already done so, please read the first VLOOKUP article – this article will assume that many of the concepts explained in that article are already known to the reader. When working with databases, VLOOKUP is passed a “unique identifier” that serves to identify which data record we wish to find in the database (e.g. a product code or customer ID).  This unique identifier must exist in the database, otherwise VLOOKUP returns us an error.  In this article, we will examine a way of using VLOOKUP where the identifier doesn’t need to exist in the database at all.  It’s almost as if VLOOKUP can adopt a “near enough is good enough” approach to returning the data we’re looking for.  In certain circumstances, this is exactly what we need. We will illustrate this article with a real-world example – that of calculating the commissions that are generated on a set of sales figures.  We will start with a very simple scenario, and then progressively make it more complex, until the only rational solution to the problem is to use VLOOKUP.  The initial scenario in our fictitious company works like this:  If a salesperson creates more than $30,000 worth of sales in a given year, the commission they earn on those sales is 30%.  Otherwise their commission is only 20%.  So far this is a pretty simple worksheet: To use this worksheet, the salesperson enters their sales figures in cell B1, and the formula in cell B2 calculates the correct commission rate they are entitled to receive, which is used in cell B3 to calculate the total commission that the salesperson is owed (which is a simple multiplication of B1 and B2). The cell B2 contains the only interesting part of this worksheet – the formula for deciding which commission rate to use: the one below the threshold of $30,000, or the one above the threshold.  This formula makes use of the Excel function called IF.  For those readers that are not familiar with IF, it works like this: IF(condition,value if true,value if false) Where the condition is an expression that evaluates to either true or false.  In the example above, the condition is the expression B1<B5, which can be read as “Is B1 less than B5?”, or, put another way, “Are the total sales less than the threshold”.  If the answer to this question is “yes” (true), then we use the value if true parameter of the function, namely B6 in this case – the commission rate if the sales total was below the threshold.  If the answer to the question is “no” (false), then we use the value if false parameter of the function, namely B7 in this case – the commission rate if the sales total was above the threshold. As you can see, using a sales total of $20,000 gives us a commission rate of 20% in cell B2.  If we enter a value of $40,000, we get a different commission rate: So our spreadsheet is working. Let’s make it more complex.  Let’s introduce a second threshold:  If the salesperson earns more than $40,000, then their commission rate increases to 40%: Easy enough to understand in the real world, but in cell B2 our formula is getting more complex.  If you look closely at the formula, you’ll see that the third parameter of the original IF function (the value if false) is now an entire IF function in its own right.  This is called a nested function (a function within a function).  It’s perfectly valid in Excel (it even works!), but it’s harder to read and understand. We’re not going to go into the nuts and bolts of how and why this works, nor will we examine the nuances of nested functions.  This is a tutorial on VLOOKUP, not on Excel in general. Anyway, it gets worse!  What about when we decide that if they earn more than $50,000 then they’re entitled to 50% commission, and if they earn more than $60,000 then they’re entitled to 60% commission? Now the formula in cell B2, while correct, has become virtually unreadable.  No-one should have to write formulae where the functions are nested four levels deep!  Surely there must be a simpler way? There certainly is.  VLOOKUP to the rescue! Let’s redesign the worksheet a bit.  We’ll keep all the same figures, but organize it in a new way, a more tabular way: Take a moment and verify for yourself that the new Rate Table works exactly the same as the series of thresholds above. Conceptually, what we’re about to do is use VLOOKUP to look up the salesperson’s sales total (from B1) in the rate table and return to us the corresponding commission rate.  Note that the salesperson may have indeed created sales that are not one of the five values in the rate table ($0, $30,000, $40,000, $50,000 or $60,000).  They may have created sales of $34,988.  It’s important to note that $34,988 does not appear in the rate table.  Let’s see if VLOOKUP can solve our problem anyway… We select cell B2 (the location we want to put our formula), and then insert the VLOOKUP function from the Formulas tab: The Function Arguments box for VLOOKUP appears.  We fill in the arguments (parameters) one by one, starting with the Lookup_value, which is, in this case, the sales total from cell B1.  We place the cursor in the Lookup_value field and then click once on cell B1: Next we need to specify to VLOOKUP what table to lookup this data in.  In this example, it’s the rate table, of course.  We place the cursor in the Table_array field, and then highlight the entire rate table – excluding the headings: Next we must specify which column in the table contains the information we want our formula to return to us.  In this case we want the commission rate, which is found in the second column in the table, so we therefore enter a 2 into the Col_index_num field: Finally we enter a value in the Range_lookup field. Important:  It is the use of this field that differentiates the two ways of using VLOOKUP.  To use VLOOKUP with a database, this final parameter, Range_lookup, must always be set to FALSE, but with this other use of VLOOKUP, we must either leave it blank or enter a value of TRUE.  When using VLOOKUP, it is vital that you make the correct choice for this final parameter. To be explicit, we will enter a value of true in the Range_lookup field.  It would also be fine to leave it blank, as this is the default value: We have completed all the parameters.  We now click the OK button, and Excel builds our VLOOKUP formula for us: If we experiment with a few different sales total amounts, we can satisfy ourselves that the formula is working. Conclusion In the “database” version of VLOOKUP, where the Range_lookup parameter is FALSE, the value passed in the first parameter (Lookup_value) must be present in the database.  In other words, we’re looking for an exact match. But in this other use of VLOOKUP, we are not necessarily looking for an exact match.  In this case, “near enough is good enough”.  But what do we mean by “near enough”?  Let’s use an example:  When searching for a commission rate on a sales total of $34,988, our VLOOKUP formula will return us a value of 30%, which is the correct answer.  Why did it choose the row in the table containing 30% ?  What, in fact, does “near enough” mean in this case?  Let’s be precise: When Range_lookup is set to TRUE (or omitted), VLOOKUP will look in column 1 and match the highest value that is not greater than the Lookup_value parameter. It’s also important to note that for this system to work, the table must be sorted in ascending order on column 1! If you would like to practice with VLOOKUP, the sample file illustrated in this article can be downloaded from here. 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  • ODI - Creating a Repository in a 12c Pluggable Database

    - by David Allan
    To install ODI 11g into an Oracle 12c pluggable database, one way is to connect using a TNS string to the pluggable database service that is executing. For example when I installed my master repository, I used a JDBC URL such as; jdbc:oracle:thin:@(DESCRIPTION=(ADDRESS_LIST=(ADDRESS=(PROTOCOL=TCP)(HOST=mydbserver)(PORT=1522)))(CONNECT_DATA=(SERVER=DEDICATED)(SERVICE_NAME=PDBORA12.US.ORACLE.COM)))   I used the above approach rather than the host:port:sid which is a common mechanism many users use to quickly get up and going. Below you can see the repository creation wizard in action, I used the 11g release and simply installed the master and work repository into my pluggable database. Be wise with your repository IDs, I simply used the default, but you should be aware that these are key in larger deployments. The database in 12c has much more tighter control on users and resources, so just getting the user creating with sufficient resource on tablespaces etc in 12c was a little more work. Once you have the repositories up and running, then the fun starts using the 12c features. More to come.

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  • Database Developers Can Now Save 20%

    - by stephen.garth
    Database developers can now increase productivity and save money at the same time. For a limited time, Oracle Store is offering a 20% discount on Oracle SQL Developer Data Modeler. Just enter the code SQLDDM at checkout to get the discount. Oracle SQL Developer Data Modeler is an independent, standalone product with a full spectrum of data and database modeling tools and utilities, including modeling for Entity Relationship Diagrams (ERD), Relational (database design), Data Type and Multi-dimensional modeling, full forward and reverse engineering and DDL code generation. SQL Developer Data Modeler can connect to any supported Oracle Database and is platform independent. Save 20% on Oracle SQL Developer Data Modeler at Oracle Store - Discount Code SQLDDM Find out more about Oracle SQL Developer and Oracle SQL Developer Data Modeler var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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  • HealthSouth Upgrades to Oracle Database 11g Release 2 and Oracle RAC

    - by jenny.gelhausen
    HealthSouth Corporation, the nation's largest provider of inpatient rehabilitation services, has upgraded to Oracle Database 11g Release 2 underneath PeopleSoft Enterprise Human Capital Management. Additionally, HealthSouth improved the availability and performance of its Oracle PeopleSoft Enterprise applications and Enterprise Data Warehouse using Oracle Database 11g and Oracle Real Application Clusters. Oracle Database options -- Oracle Advanced Compression and Oracle Partitioning are key to HealthSouth's data lifecycle management practices and to utilizing storage systems more efficiently. Using compression on both partitioned as well as non-partitioned tables in its data warehouse, HealthSouth has seen a 4X storage reduction without any cost to performance. "Oracle Database 11g, along with Oracle Real Application Clusters, Advanced Compression and Partitioning, all lend themselves to delivering highly available, performant data warehousing," said Henry Lovoy, Data Manager, HealthSouth Corporation. Press Release var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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