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  • How do I introspect on a SQL Server?

    - by MetaHyperBolic
    I have a server with a vendor application which is heavily database-reliant. I need to make some minor changes to the data in a few tables in the database in an automated fashion. Just INSERTs and UPDATEs, nothing fancy. Vendors being vendors, I can never be quite sure when they change the schema of a database during upgrade. To that end, how do I ask the SQL server, in some scriptable fashion, "Hey, does this table still exist? Yeah, cool, okay, but does it have this column? What's the data type and size on that? Is it nullable? Could you give me a list of tables? In this table, could you give me a list of columns? Any primary keys there?" I do not need to do this for the whole schema, only part of it, just a quick check of the database before I launch into things. We have Microsoft SQL Server 2005 on it currently, but it might easily move to Microsoft SQL Server 2008. I am probably not using the correct terminology when searching. I do know that ORM is not only too much overhead for this sort of thing, but also that I have no chance of pitching it to my coworkers.

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  • Why won't JPA delete owned entities when the owner entity loses the reference to them?

    - by Nick
    Hi! I've got a JPA entity "Request", that owns a List of Answers (also JPA entities). Here's how it's defined in Request.java: @OneToMany(cascade= CascadeType.ALL, mappedBy="request") private List<Answer> answerList; And in Answer.java: @JoinColumn(name = "request", referencedColumnName="id") @ManyToOne(optional = false) private Request request; In the course of program execution, the Request's List of Answers may have Answers added or removed from it, or the actual List object may be replaced. My problem is thus: when I merge a Request to the database, the Answer objects that used to be in the List are kept in the database -- that is, Answer objects that the Request no longer holds a reference to (indirectly, via a List) are not deleted. This is not the behaviour I desire, as if I merge a Request to the database, and then fetch it again, its Answers List may not be the same. Am I making some programming mistake? Is there an annotaion or setting that will ensure that the Answers in the database are exactly the Answers in the Request's List? A solution is to keep references to the original Answers List and then use the EntityManager to remove each old Answer before merging the Request, but it seems like there should be a cleaner way. Thank you!

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  • Symfony deploying issue

    - by medhad
    I have some problem while configuring symfony project on the production server. When I run the command doctrine --build --all --and-load it gives me error in the production environment: doctrine Dropping "doctrine" database PHP Notice: Undefined index: dbname in /var/www/sf_project/lib/vendor/symfony/lib/plugins/sfDoctrinePlugin/lib/vendor/doctrine/Doctrine/Connection.php on line 1472 Notice: Undefined index: dbname in /var/www/sf_project/lib/vendor/symfony/lib/plugins/sfDoctrinePlugin/lib/vendor/doctrine/Doctrine/Connection.php on line 1472 doctrine SQLSTATE[42000]: Syntax error or access violation: 1064 You have an erro...e right syntax to use near '' at line 1. Failing Query: "DROP DATABASE " doctrine Creating "dev" environment "doctrine" database PHP Notice: Undefined index: dbname in /var/www/sf_project/lib/vendor/symfony/lib/plugins/sfDoctrinePlugin/lib/vendor/doctrine/Doctrine/Connection.php on line 1439 However after the error it creates the table successfully. But if I run the command second times it fails partially while crating the tables. I have changed my database.yml configuration properly for the production environment. here it is: all: doctrine: class: sfDoctrineDatabase param: dsn: mysql:host=localhost;dbname=sf_project port: 3306 username: root password: mainserver Its working right in the local environment though. Can some one shed some light on it ?

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  • How to loop through an array return from the Query of Mysql

    - by Jerry
    This might be easy for you guys but i could't get it. I have a php class that query the database and return the query result. I assign the result to an array and wants to use it on my main.php script. I have tried to use echo $var[0] or echo $var[1] but the output are 'array' instead of my value. Anyone can help me about this issue? Thanks a lot! My php class <?php class teamQuery { function teamQuery(){ } function getAllTeam(){ $connection = mysql_connect(DB_SERVER,DB_USER,DB_PASS); if (!$connection) { die("Database connection failed: " . mysql_error()); } $db_select = mysql_select_db(DB_NAME,$connection); if (!$db_select) { die("Database selection failed: " . mysql_error()); } $teamQuery=mysql_query("SELECT * FROM team", $connection); if (!$teamQuery){ die("database has errors: ".mysql_error()); } $ret = array(); while($row=mysql_fetch_array($teamQuery)){ $ret[]=$row; } mysql_free_result($teamQuery); return $ret; } } ?> My php on the main.php $getTeam=new teamQuery(); $team=$getTeam->getAllTeam(); //echo $team[0] or team[1] output 'array' string! // while($team){ // do something } can't work either // How to loop through the values?? Thanks!

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  • What job title should be most suitable for my object in resume and what salary range should I expect

    - by user354177
    I was a classic asp developer in 2000. After a year of full-time employment, I left the field. I found a part-time position as an asp developer again in 2005 and taught myself vb.net. In 2007, I got the current full-time job as an Asp.net web developer. I taught myself C#, LING t0 SQL, Web Services, AJAX, and creating all kinds of reports with reporting services. One and half years ago, I sent myself to part-time graduate program in Database and Web Systems. I'll have two semesters to go and so far my GPA is 4.0/4.0. My job responsibility is to collect business requirements from other departments, design the database, write stored procedures, create aspx pages, and create reports. I love what I do and want to advance my career to the next level. What I enjoy most is to design the relational database. I would want to become an .Net Architect eventually. I got an interview. They were looking for asp.net web developer. But I was surprised and disappointed that position would only create aspx pages. I would not even have opportunity to write stored procedures, let alone design the database (those would be provided by another group). Furthermore, they asked me some detailed questions about web forms, some of which I did not know the answers. they might be disappointed as well. I am eager to learn and can apply what I learn to real projects right away. I believe no matter what specific skills I am lacking for a new position, I can catch up quickly. I am looking for $70k range job. The object in my resume is Experience C# Web Application Developer. Due to the experience from last interview, I wonder if the object is really what I want. Could somebody answer my questions? Thank you.

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  • Question about how AppFabric's cache feature can be used.

    - by Kevin Buchan
    Question about how AppFabric's cache feature can be used. I apologize for asking a question that I should be able to answer from the documentation, but I have read and read and searched and cannot answer this question, which leads me to believe that I have a fundamentally flawed understanding of what AppFabric's caching capabilities are intended for. I work for a geographically disperse company. We have a particular application that was originally written as a client/server application. It’s so massive and business critical that we want to baby step converting it to a better architected solution. One of the ideas we had was to convert the app to read its data using WCF calls to a co-located web server that would cache communication with the database in the United States. The nature of the application is such that everyone will tend to be viewing the same 2000 records or so with only occasional updates and those updates will be made by a limited set of users. I was hoping that AppFabric’s cache mechanism would allow me to set up one global cache and when a user in Asia, for example, requested data that was not in the cache or was stale that the web server would read from the database in the USA, provide the data to the user, then update the cache which would propagate that data to the other web servers so that they would know not to go back to the database themselves. Can AppFabric work this way or should I just have the servers retrieve their own data from the database?

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  • Can it be done?

    - by bzarah
    We are in design phase of a project whose goal is replatforming an ASP classic application to ASP.Net 4.0. The system needs to be entirely web based. There are several new requirements for the new system that make this a challenging project: The system needs to be database independent. It must, at version 1.0, support MS SQL Server, Oracle, MySQL, Postgres and DB2. The system must be able to allow easy reporting from the database by third party reporting packages. The system must allow an administrative end user to create their own tables in the database through the web based interface. The system must allow an administrative end user to design/configure a user interface (web based) where they can select tables and fields in the system (either our system's core tables or their own custom tables created in #3) The system must allow an administrative end user to create and maintain relationships between these custom created tables, and also between these tables and our system's core tables. The system must allow an administrative end user to create business rules that will enforce validation, show/hide UI elements, block certain actions based on the identity of specific users, specific user groups or privileges. Essentially it's a system that has some core ticket tracking functionality, but allows the end user to extend the interface, business rules and the database. Is this possible to build in a .Net, Web based environment? If so, what do you think the level of effort would be to get this done? We are currently a 6 person shop, with 2.5 full time developers.

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  • Scalable way to store files on server (PHP)?

    - by Nathaniel Bennett
    I'm creating my first web application - a really simplistic online text editor. What I need to do is find the best way to store text based files - a lot of them. These text files can be past 10,000 words in size (text words not computer words.) in essence I want the text documents to be limitless in size. I was thinking about storing the text files in my MySQL database - but thought there was a better way. Instead I'm planing on storing the text files in XML based format in a directory on my server. The rows in the database define the name of the xml based text file and the user who created the text along with basic metadata. An ID is generated using a V4 GUID generator , which gives the text an id and stores the text in the "/store" directory on my server. The text definitions in my server contain this id, and the android app I'm developing gets the contents of the text file by retrieving the text definition and then downloading the text to the local device using the GUID in the text definition. I just think this is a botch job? how can I improve this system? There has been cases of GUID colliding. I don't want this to happen. A "slim" possibility isn't good enough - I need to make sure there is absolutely no chance in a GUID collision. I was planning on checking the database for texts that have the same id before storing the text with a particular id - I however believe with over 20,000 pieces of text in my database this would take an long time and produce unneeded stress on the server. How can I make GUID safe? What happens when a GUID collides? The server backend is going to be written in PHP.

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  • How to current snapshot of MySQL Table and store it into CSV file(after creating it) ?

    - by Rachel
    I have large database table, approximately 5GB, now I wan to getCurrentSnapshot of Database using "Select * from MyTableName", am using PDO in PHP to interact with Database. So preparing a query and then executing it // Execute the prepared query $result->execute(); $resultCollection = $result->fetchAll(PDO::FETCH_ASSOC); is not an efficient way as lots of memory is being user for storing into the associative array data which is approximately, 5GB. My final goal is to collect data returned by Select query into an CSV file and put CSV file at an FTP Location from where Client can get it. Other Option I thought was to do: SELECT * INTO OUTFILE "c:/mydata.csv" FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"' LINES TERMINATED BY "\n" FROM my_table; But I am not sure if this would work as I have cron that initiates the complete process and we do not have an csv file, so basically for this approach, PHP Scripts will have to create an CSV file. Do a Select query on the database. Store the select query result into the CSV file. What would be the best or efficient way to do this kind of task ? Any Suggestions !!!

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  • Joomla User Login Question

    - by user277127
    I would like to enable users of my existing web app to login to Joomla with the credentials already stored in my web app's database. By using the Joomla 1.5 authentication plugin system -- http://docs.joomla.org/Tutorial:Creating_an_Authentication_Plugin_for_Joomla_1.5 -- I would like to bypass the Joomla registration process and bypass creating users in the Joomla database altogether. My thought had been that I could simply populate a User object, which would be stored in the Session, and that this would replace the need to store a user in the Joomla database. After looking through the code surrounding user management in Joomla, it seems like any time you interact with the User object, the database is being queried. It therefore seems like my initial idea won't work. Is that right? It looks like, in order to achieve the effect I want, I will have to actually register a user from within the authentication plugin at the time they first login. This is not ideal, so before I go forward with it, I wanted to check with Joomla developers whether it is possible to do what I described above. Thanks in advance -- I am new to Joomla and greatly appreciate your help!

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  • Dependency Injection: How to pass DB around?

    - by Stephane
    Edit: This is a conceptual question first and foremost. I can make applications work without knowing this, but I'm trying to learn the concept. I've seen lots of videos with related classes and that makes sense, but when it comes to classes wrapping around other classes, I can't seem to grasp where things should be instantiated/passed around. =-=-=-=-=-=-= Question: Let's say I have a simple page that loads data from a table, manipulates the result and displays it. Simple. I'm going to use '=' for instantiating a class and '-' for passing a class in using constructor injection. It seems to me that the database has to be passed from one end of the application to the other which doesn't seem right. Here's how I would do it if I wanted to separate concerns: index =>Controller =>Model Layer =>Database =>DAO->Database I have this rule in my head that says I'm not supposed to create objects inside other objects. So what do I do with the Database? Or even the Model for that matter? I'm obviously missing something so basic about this. I would love a simplified example so that I can move forward in my code. I feel really hamstrung by this.

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  • '<=' operator is not working in sql server 2000

    - by Lalit
    Hello, Scenario is, database is in the maintenance phase. this database is not developed by ours developer. it is an existing database developed by the 'xyz' company in sql server 2000. This is real time database, where i am working now. I wanted to write the stored procedure which will retrieve me the records From date1 to date 2.so query is : Select * from MyTableName Where colDate>= '3-May-2010' and colDate<= '5-Oct-2010' and colName='xyzName' whereas my understanding I must get data including upper bound date as well as lower bound date. but somehow I am getting records from '3-May-2010' (which is fine but) to '10-Oct-2010' As i observe in table design , for ColDate, developer had used 'varchar' to store the date. i know this is wrong remedy by them. so in my stored procedure I have also used varchar parameters as @FromDate1 and @ToDate to get inputs for SP. this is giving me result which i have explained. i tried to take the parameter type as 'Datetime' but it is showing error while saving/altering the stored procedure that "@FromDate1 has invalid datatype", same for "@ToDate". situation is that, I can not change the table design at all. what i have to do here ? i know we can use user defined table in sql server 2008 , but there is version sql server 2000. which does not support the same. Please guide me for this scenario. **Edited** I am trying to write like this SP: CREATE PROCEDURE USP_Data (@Location varchar(100), @FromDate DATETIME, @ToDate DATETIME) AS SELECT * FROM dbo.TableName Where CAST(Dt AS DATETIME) >=@fromDate and CAST(Dt AS DATETIME)<=@ToDate and Location=@Location GO but getting Error: Arithmetic overflow error converting expression to data type datetime. in sql server 2000 What should be that ? is i am wrong some where ? also (202 row(s) affected) is changes every time in circular manner means first time sayin (122 row(s) affected) run again saying (80 row(s) affected) if again (202 row(s) affected) if again (122 row(s) affected) I can not understand what is going on ?

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  • Php header('Location") error

    - by Umeed
    I'm having some difficulty with my php coding. I have 3 files, add.php, lib.php, and view.php I created a simple form, and when the user clicks submit, it should direct them to the view.php where it will display the database. Now I'm having a couple issues I can't seem to resolve. when the user clicks submit and the fields are blank or there is an error no entry should be made into the view page (or database)...however when I click submit a blank entry is made into the database. ALSO if i click "enter product" from the top menu bar anytime I click it, it causes a blank entry into the database. I can't figure out why that's happening. My next issue is with the header('Location') and my browser says: "Warning: Cannot modify header information - headers already sent by (output started at lib.php:13) in add.php on line 16" However if I click submit on my form it goes away. Here is the code for the pages: http://ideone.com/Vvz8x I truly apologize if the code is really messy. Any help / advice / solution is greatly appreciated thank you. And yes this was an assignment---it was due last week but since I couldn't finish it, it's not worth any marks anymore.

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  • LINQ to SQL and missing Many to Many EntityRefs

    - by Rick Strahl
    Ran into an odd behavior today with a many to many mapping of one of my tables in LINQ to SQL. Many to many mappings aren’t transparent in LINQ to SQL and it maps the link table the same way the SQL schema has it when creating one. In other words LINQ to SQL isn’t smart about many to many mappings and just treats it like the 3 underlying tables that make up the many to many relationship. Iain Galloway has a nice blog entry about Many to Many relationships in LINQ to SQL. I can live with that – it’s not really difficult to deal with this arrangement once mapped, especially when reading data back. Writing is a little more difficult as you do have to insert into two entities for new records, but nothing that can’t be handled in a small business object method with a few lines of code. When I created a database I’ve been using to experiment around with various different OR/Ms recently I found that for some reason LINQ to SQL was completely failing to map even to the linking table. As it turns out there’s a good reason why it fails, can you spot it below? (read on :-}) Here is the original database layout: There’s an items table, a category table and a link table that holds only the foreign keys to the Items and Category tables for a typical M->M relationship. When these three tables are imported into the model the *look* correct – I do get the relationships added (after modifying the entity names to strip the prefix): The relationship looks perfectly fine, both in the designer as well as in the XML document: <Table Name="dbo.wws_Item_Categories" Member="ItemCategories"> <Type Name="ItemCategory"> <Column Name="ItemId" Type="System.Guid" DbType="uniqueidentifier NOT NULL" CanBeNull="false" /> <Column Name="CategoryId" Type="System.Guid" DbType="uniqueidentifier NOT NULL" CanBeNull="false" /> <Association Name="ItemCategory_Category" Member="Categories" ThisKey="CategoryId" OtherKey="Id" Type="Category" /> <Association Name="Item_ItemCategory" Member="Item" ThisKey="ItemId" OtherKey="Id" Type="Item" IsForeignKey="true" /> </Type> </Table> <Table Name="dbo.wws_Categories" Member="Categories"> <Type Name="Category"> <Column Name="Id" Type="System.Guid" DbType="UniqueIdentifier NOT NULL" IsPrimaryKey="true" IsDbGenerated="true" CanBeNull="false" /> <Column Name="ParentId" Type="System.Guid" DbType="UniqueIdentifier" CanBeNull="true" /> <Column Name="CategoryName" Type="System.String" DbType="NVarChar(150)" CanBeNull="true" /> <Column Name="CategoryDescription" Type="System.String" DbType="NVarChar(MAX)" CanBeNull="true" /> <Column Name="tstamp" AccessModifier="Internal" Type="System.Data.Linq.Binary" DbType="rowversion" CanBeNull="true" IsVersion="true" /> <Association Name="ItemCategory_Category" Member="ItemCategory" ThisKey="Id" OtherKey="CategoryId" Type="ItemCategory" IsForeignKey="true" /> </Type> </Table> However when looking at the code generated these navigation properties (also on Item) are completely missing: [global::System.Data.Linq.Mapping.TableAttribute(Name="dbo.wws_Item_Categories")] [global::System.Runtime.Serialization.DataContractAttribute()] public partial class ItemCategory : Westwind.BusinessFramework.EntityBase { private System.Guid _ItemId; private System.Guid _CategoryId; public ItemCategory() { } [global::System.Data.Linq.Mapping.ColumnAttribute(Storage="_ItemId", DbType="uniqueidentifier NOT NULL")] [global::System.Runtime.Serialization.DataMemberAttribute(Order=1)] public System.Guid ItemId { get { return this._ItemId; } set { if ((this._ItemId != value)) { this._ItemId = value; } } } [global::System.Data.Linq.Mapping.ColumnAttribute(Storage="_CategoryId", DbType="uniqueidentifier NOT NULL")] [global::System.Runtime.Serialization.DataMemberAttribute(Order=2)] public System.Guid CategoryId { get { return this._CategoryId; } set { if ((this._CategoryId != value)) { this._CategoryId = value; } } } } Notice that the Item and Category association properties which should be EntityRef properties are completely missing. They’re there in the model, but the generated code – not so much. So what’s the problem here? The problem – it appears – is that LINQ to SQL requires primary keys on all entities it tracks. In order to support tracking – even of the link table entity – the link table requires a primary key. Real obvious ain’t it, especially since the designer happily lets you import the table and even shows the relationship and implicitly the related properties. Adding an Id field as a Pk to the database and then importing results in this model layout: which properly generates the Item and Category properties into the link entity. It’s ironic that LINQ to SQL *requires* the PK in the middle – the Entity Framework requires that a link table have *only* the two foreign key fields in a table in order to recognize a many to many relation. EF actually handles the M->M relation directly without the intermediate link entity unlike LINQ to SQL. [updated from comments – 12/24/2009] Another approach is to set up both ItemId and CategoryId in the database which shows up in LINQ to SQL like this: This also work in creating the Category and Item fields in the ItemCategory entity. Ultimately this is probably the best approach as it also guarantees uniqueness of the keys and so helps in database integrity. It took me a while to figure out WTF was going on here – lulled by the designer to think that the properties should be when they were not. It’s actually a well documented feature of L2S that each entity in the model requires a Pk but of course that’s easy to miss when the model viewer shows it to you and even the underlying XML model shows the Associations properly. This is one of the issue with L2S of course – you have to play by its rules and once you hit one of those rules there’s no way around them – you’re stuck with what it requires which in this case meant changing the database.© Rick Strahl, West Wind Technologies, 2005-2010Posted in ADO.NET  LINQ  

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  • Oracle Data Mining a Star Schema: Telco Churn Case Study

    - by charlie.berger
    There is a complete and detailed Telco Churn case study "How to" Blog Series just posted by Ari Mozes, ODM Dev. Manager.  In it, Ari provides detailed guidance in how to leverage various strengths of Oracle Data Mining including the ability to: mine Star Schemas and join tables and views together to obtain a complete 360 degree view of a customer combine transactional data e.g. call record detail (CDR) data, etc. define complex data transformation, model build and model deploy analytical methodologies inside the Database  His blog is posted in a multi-part series.  Below are some opening excerpts for the first 3 blog entries.  This is an excellent resource for any novice to skilled data miner who wants to gain competitive advantage by mining their data inside the Oracle Database.  Many thanks Ari! Mining a Star Schema: Telco Churn Case Study (1 of 3) One of the strengths of Oracle Data Mining is the ability to mine star schemas with minimal effort.  Star schemas are commonly used in relational databases, and they often contain rich data with interesting patterns.  While dimension tables may contain interesting demographics, fact tables will often contain user behavior, such as phone usage or purchase patterns.  Both of these aspects - demographics and usage patterns - can provide insight into behavior.Churn is a critical problem in the telecommunications industry, and companies go to great lengths to reduce the churn of their customer base.  One case study1 describes a telecommunications scenario involving understanding, and identification of, churn, where the underlying data is present in a star schema.  That case study is a good example for demonstrating just how natural it is for Oracle Data Mining to analyze a star schema, so it will be used as the basis for this series of posts...... Mining a Star Schema: Telco Churn Case Study (2 of 3) This post will follow the transformation steps as described in the case study, but will use Oracle SQL as the means for preparing data.  Please see the previous post for background material, including links to the case study and to scripts that can be used to replicate the stages in these posts.1) Handling missing values for call data recordsThe CDR_T table records the number of phone minutes used by a customer per month and per call type (tariff).  For example, the table may contain one record corresponding to the number of peak (call type) minutes in January for a specific customer, and another record associated with international calls in March for the same customer.  This table is likely to be fairly dense (most type-month combinations for a given customer will be present) due to the coarse level of aggregation, but there may be some missing values.  Missing entries may occur for a number of reasons: the customer made no calls of a particular type in a particular month, the customer switched providers during the timeframe, or perhaps there is a data entry problem.  In the first situation, the correct interpretation of a missing entry would be to assume that the number of minutes for the type-month combination is zero.  In the other situations, it is not appropriate to assume zero, but rather derive some representative value to replace the missing entries.  The referenced case study takes the latter approach.  The data is segmented by customer and call type, and within a given customer-call type combination, an average number of minutes is computed and used as a replacement value.In SQL, we need to generate additional rows for the missing entries and populate those rows with appropriate values.  To generate the missing rows, Oracle's partition outer join feature is a perfect fit.  select cust_id, cdre.tariff, cdre.month, minsfrom cdr_t cdr partition by (cust_id) right outer join     (select distinct tariff, month from cdr_t) cdre     on (cdr.month = cdre.month and cdr.tariff = cdre.tariff);   ....... Mining a Star Schema: Telco Churn Case Study (3 of 3) Now that the "difficult" work is complete - preparing the data - we can move to building a predictive model to help identify and understand churn.The case study suggests that separate models be built for different customer segments (high, medium, low, and very low value customer groups).  To reduce the data to a single segment, a filter can be applied: create or replace view churn_data_high asselect * from churn_prep where value_band = 'HIGH'; It is simple to take a quick look at the predictive aspects of the data on a univariate basis.  While this does not capture the more complex multi-variate effects as would occur with the full-blown data mining algorithms, it can give a quick feel as to the predictive aspects of the data as well as validate the data preparation steps.  Oracle Data Mining includes a predictive analytics package which enables quick analysis. begin  dbms_predictive_analytics.explain(   'churn_data_high','churn_m6','expl_churn_tab'); end; /select * from expl_churn_tab where rank <= 5 order by rank; ATTRIBUTE_NAME       ATTRIBUTE_SUBNAME EXPLANATORY_VALUE RANK-------------------- ----------------- ----------------- ----------LOS_BAND                                      .069167052          1MINS_PER_TARIFF_MON  PEAK-5                   .034881648          2REV_PER_MON          REV-5                    .034527798          3DROPPED_CALLS                                 .028110322          4MINS_PER_TARIFF_MON  PEAK-4                   .024698149          5From the above results, it is clear that some predictors do contain information to help identify churn (explanatory value > 0).  The strongest uni-variate predictor of churn appears to be the customer's (binned) length of service.  The second strongest churn indicator appears to be the number of peak minutes used in the most recent month.  The subname column contains the interior piece of the DM_NESTED_NUMERICALS column described in the previous post.  By using the object relational approach, many related predictors are included within a single top-level column. .....   NOTE:  These are just EXCERPTS.  Click here to start reading the Oracle Data Mining a Star Schema: Telco Churn Case Study from the beginning.    

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  • Using SQL Source Control with Fortress or Vault &ndash; Part 2

    - by AjarnMark
    In Part 1, I started talking about using Red-Gate’s newest version of SQL Source Control and how I really like it as a viable method to source control your database development.  It looks like this is going to turn into a little series where I will explain how we have done things in the past, and how life is different with SQL Source Control.  I will also explain some of my philosophy and methodology around deployment with these tools.  But for now, let’s talk about some of the good and the bad of the tool itself. More Kudos and Features I mentioned previously how impressed I was with the responsiveness of Red-Gate’s team.  I have been having an ongoing email conversation with Gyorgy Pocsi, and as I have run into problems or requested things behave a little differently, it has not been more than a day or two before a new Build is ready for me to download and test.  Quite impressive! I’m sure much of the requests I put in were already in the plans, so I can’t really take credit for them, but throughout this conversation, Red-Gate has implemented several features that were not in the first Early Access version.  Those include: Honoring the Fortress configuration option to require Work Item (Bug) IDs on check-ins. Adding the check-in comment text as a comment to the Work Item. Adding the list of checked-in files, along with the Fortress links for automatic History and DIFF view Updating the status of a Work Item on check-in (e.g. setting the item to Complete or, in our case “Dev-Complete”) Support for the Fortress 2.0 API, and not just the Vault Pro 5.1 API.  (See later notes regarding support for Fortress 2.0). These were all features that I felt we really needed to have in-place before I could honestly consider converting my team to using SQL Source Control on a regular basis.  Now that I have those, my only excuse is not wanting to switch boats on the team mid-stream.  So when we wrap up our current release in a few weeks, we will make the jump.  In the meantime, I will continue to bang on it to make sure it is stable.  It passed one test for stability when I did a test load of one of our larger database schemas into Fortress with SQL Source Control.  That database has about 150 tables, 200 User-Defined Functions and nearly 900 Stored Procedures.  The initial load to source control went smoothly and took just a brief amount of time. Warnings Remember that this IS still in pre-release stage and while I have not had any problems after that first hiccup I wrote about last time, you still need to treat it with a healthy respect.  As I understand it, the RTM is targeted for February.  There are a couple more features that I hope make it into the final release version, but if not, they’ll probably be coming soon thereafter.  Those are: A Browse feature to let me lookup the Work Item ID instead of having to remember it or look back in my Item details.  This is just a matter of convenience. I normally have my Work Item list open anyway, so I can easily look it up, but hey, why not make it even easier. A multi-line comment area.  The current space for writing check-in comments is a single-line text box.  I would like to have a multi-line space as I sometimes write lengthy commentary.  But I recognize that it is a struggle to get most developers to put in more than the word “fixed” as their comment, so this meets the need of the majority as-is, and it’s not a show-stopper for us. Merge.  SQL Source Control currently does not have a Merge feature.  If two or more people make changes to the same database object, you will get a warning of the conflict and have to choose which one wins (and then manually edit to include the others’ changes).  I think it unlikely you will run into actual conflicts in Stored Procedures and Functions, but you might with Views or Tables.  This will be nice to have, but I’m not losing any sleep over it.  And I have multiple tools at my disposal to do merges manually, so really not a show-stopper for us. Automation has its limits.  As cool as this automation is, it has its limits and there are some changes that you will be better off scripting yourself.  For example, if you are refactoring table definitions, and want to change a column name, you can write that as a quick sp_rename command and preserve the data within that column.  But because this tool is looking just at a before and after picture, it cannot tell that you just renamed a column.  To the tool, it looks like you dropped one column and added another.  This is not a knock against Red-Gate.  All automated scripting tools have this issue, unless the are actively monitoring your every step to know exactly what you are doing.  This means that when you go to Deploy your changes, SQL Compare will script the change as a column drop and add, or will attempt to rebuild the entire table.  Unfortunately, neither of these approaches will preserve the existing data in that column the way an sp_rename will, and so you are better off scripting that change yourself.  Thankfully, SQL Compare will produce warnings about the potential loss of data before it does the actual synchronization and give you a chance to intercept the script and do it yourself. Also, please note that the current official word is that SQL Source Control supports Vault Professional 5.1 and later.  Vault Professional is the new name for what was previously known as Fortress.  (You can read about the name change on SourceGear’s site.)  The last version of Fortress was 2.x, and the API for Fortress 2.x is different from the API for Vault Pro.  At my company, we are currently running Fortress 2.0, with plans to upgrade to Vault Pro early next year.  Gyorgy was able to come up with a work-around for me to be able to use SQL Source Control with Fortress 2.0, even though it is not officially supported.  If you are using Fortress 2.0 and want to use SQL Source Control, be aware that this is not officially supported, but it is working for us, and you can probably get the work-around instructions from Red-Gate if you’re really, really nice to them. Upcoming Topics Some of the other topics I will likely cover in this series over the next few weeks are: How we used to do source control back in the old days (a few weeks ago) before SQL Source Control was available to Vault users What happens when you restore a database that is linked to source control Handling multiple development branches of source code Concurrent Development practices and handling Conflicts Deployment Tips and Best Practices A recap after using the tool for a while

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  • Java EE 6 and NoSQL/MongoDB on GlassFish using JPA and EclipseLink 2.4 (TOTD #175)

    - by arungupta
    TOTD #166 explained how to use MongoDB in your Java EE 6 applications. The code in that tip used the APIs exposed by the MongoDB Java driver and so requires you to learn a new API. However if you are building Java EE 6 applications then you are already familiar with Java Persistence API (JPA). Eclipse Link 2.4, scheduled to release as part of Eclipse Juno, provides support for NoSQL databases by mapping a JPA entity to a document. Their wiki provides complete explanation of how the mapping is done. This Tip Of The Day (TOTD) will show how you can leverage that support in your Java EE 6 applications deployed on GlassFish 3.1.2. Before we dig into the code, here are the key concepts ... A POJO is mapped to a NoSQL data source using @NoSQL or <no-sql> element in "persistence.xml". A subset of JPQL and Criteria query are supported, based upon the underlying data store Connection properties are defined in "persistence.xml" Now, lets lets take a look at the code ... Download the latest EclipseLink 2.4 Nightly Bundle. There is a Installer, Source, and Bundle - make sure to download the Bundle link (20120410) and unzip. Download GlassFish 3.1.2 zip and unzip. Install the Eclipse Link 2.4 JARs in GlassFish Remove the following JARs from "glassfish/modules": org.eclipse.persistence.antlr.jar org.eclipse.persistence.asm.jar org.eclipse.persistence.core.jar org.eclipse.persistence.jpa.jar org.eclipse.persistence.jpa.modelgen.jar org.eclipse.persistence.moxy.jar org.eclipse.persistence.oracle.jar Add the following JARs from Eclipse Link 2.4 nightly build to "glassfish/modules": org.eclipse.persistence.antlr_3.2.0.v201107111232.jar org.eclipse.persistence.asm_3.3.1.v201107111215.jar org.eclipse.persistence.core.jpql_2.4.0.v20120407-r11132.jar org.eclipse.persistence.core_2.4.0.v20120407-r11132.jar org.eclipse.persistence.jpa.jpql_2.0.0.v20120407-r11132.jar org.eclipse.persistence.jpa.modelgen_2.4.0.v20120407-r11132.jar org.eclipse.persistence.jpa_2.4.0.v20120407-r11132.jar org.eclipse.persistence.moxy_2.4.0.v20120407-r11132.jar org.eclipse.persistence.nosql_2.4.0.v20120407-r11132.jar org.eclipse.persistence.oracle_2.4.0.v20120407-r11132.jar Start MongoDB Download latest MongoDB from here (2.0.4 as of this writing). Create the default data directory for MongoDB as: sudo mkdir -p /data/db/sudo chown `id -u` /data/db Refer to Quickstart for more details. Start MongoDB as: arungup-mac:mongodb-osx-x86_64-2.0.4 <arungup> ->./bin/mongod./bin/mongod --help for help and startup optionsMon Apr  9 12:56:02 [initandlisten] MongoDB starting : pid=3124 port=27017 dbpath=/data/db/ 64-bit host=arungup-mac.localMon Apr  9 12:56:02 [initandlisten] db version v2.0.4, pdfile version 4.5Mon Apr  9 12:56:02 [initandlisten] git version: 329f3c47fe8136c03392c8f0e548506cb21f8ebfMon Apr  9 12:56:02 [initandlisten] build info: Darwin erh2.10gen.cc 9.8.0 Darwin Kernel Version 9.8.0: Wed Jul 15 16:55:01 PDT 2009; root:xnu-1228.15.4~1/RELEASE_I386 i386 BOOST_LIB_VERSION=1_40Mon Apr  9 12:56:02 [initandlisten] options: {}Mon Apr  9 12:56:02 [initandlisten] journal dir=/data/db/journalMon Apr  9 12:56:02 [initandlisten] recover : no journal files present, no recovery neededMon Apr  9 12:56:02 [websvr] admin web console waiting for connections on port 28017Mon Apr  9 12:56:02 [initandlisten] waiting for connections on port 27017 Check out the JPA/NoSQL sample from SVN repository. The complete source code built in this TOTD can be downloaded here. Create Java EE 6 web app Create a Java EE 6 Maven web app as: mvn archetype:generate -DarchetypeGroupId=org.codehaus.mojo.archetypes -DarchetypeArtifactId=webapp-javaee6 -DgroupId=model -DartifactId=javaee-nosql -DarchetypeVersion=1.5 -DinteractiveMode=false Copy the model files from the checked out workspace to the generated project as: cd javaee-nosqlcp -r ~/code/workspaces/org.eclipse.persistence.example.jpa.nosql.mongo/src/model src/main/java Copy "persistence.xml" mkdir src/main/resources cp -r ~/code/workspaces/org.eclipse.persistence.example.jpa.nosql.mongo/src/META-INF ./src/main/resources Add the following dependencies: <dependency> <groupId>org.eclipse.persistence</groupId> <artifactId>org.eclipse.persistence.jpa</artifactId> <version>2.4.0-SNAPSHOT</version> <scope>provided</scope></dependency><dependency> <groupId>org.eclipse.persistence</groupId> <artifactId>org.eclipse.persistence.nosql</artifactId> <version>2.4.0-SNAPSHOT</version></dependency><dependency> <groupId>org.mongodb</groupId> <artifactId>mongo-java-driver</artifactId> <version>2.7.3</version></dependency> The first one is for the EclipseLink latest APIs, the second one is for EclipseLink/NoSQL support, and the last one is the MongoDB Java driver. And the following repository: <repositories> <repository> <id>EclipseLink Repo</id> <url>http://www.eclipse.org/downloads/download.php?r=1&amp;nf=1&amp;file=/rt/eclipselink/maven.repo</url> <snapshots> <enabled>true</enabled> </snapshots> </repository>  </repositories> Copy the "Test.java" to the generated project: mkdir src/main/java/examplecp -r ~/code/workspaces/org.eclipse.persistence.example.jpa.nosql.mongo/src/example/Test.java ./src/main/java/example/ This file contains the source code to CRUD the JPA entity to MongoDB. This sample is explained in detail on EclipseLink wiki. Create a new Servlet in "example" directory as: package example;import java.io.IOException;import java.io.PrintWriter;import javax.servlet.ServletException;import javax.servlet.annotation.WebServlet;import javax.servlet.http.HttpServlet;import javax.servlet.http.HttpServletRequest;import javax.servlet.http.HttpServletResponse;/** * @author Arun Gupta */@WebServlet(name = "TestServlet", urlPatterns = {"/TestServlet"})public class TestServlet extends HttpServlet { protected void processRequest(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { response.setContentType("text/html;charset=UTF-8"); PrintWriter out = response.getWriter(); try { out.println("<html>"); out.println("<head>"); out.println("<title>Servlet TestServlet</title>"); out.println("</head>"); out.println("<body>"); out.println("<h1>Servlet TestServlet at " + request.getContextPath() + "</h1>"); try { Test.main(null); } catch (Exception ex) { ex.printStackTrace(); } out.println("</body>"); out.println("</html>"); } finally { out.close(); } } @Override protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { processRequest(request, response); } @Override protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { processRequest(request, response); }} Build the project and deploy it as: mvn clean packageglassfish3/bin/asadmin deploy --force=true target/javaee-nosql-1.0-SNAPSHOT.war Accessing http://localhost:8080/javaee-nosql/TestServlet shows the following messages in the server.log: connecting(EISLogin( platform=> MongoPlatform user name=> "" MongoConnectionSpec())) . . .Connected: User: Database: 2.7  Version: 2.7 . . .Executing MappedInteraction() spec => null properties => {mongo.collection=CUSTOMER, mongo.operation=INSERT} input => [DatabaseRecord( CUSTOMER._id => 4F848E2BDA0670307E2A8FA4 CUSTOMER.NAME => AMCE)]. . .Data access result: [{TOTALCOST=757.0, ORDERLINES=[{DESCRIPTION=table, LINENUMBER=1, COST=300.0}, {DESCRIPTION=balls, LINENUMBER=2, COST=5.0}, {DESCRIPTION=rackets, LINENUMBER=3, COST=15.0}, {DESCRIPTION=net, LINENUMBER=4, COST=2.0}, {DESCRIPTION=shipping, LINENUMBER=5, COST=80.0}, {DESCRIPTION=handling, LINENUMBER=6, COST=55.0},{DESCRIPTION=tax, LINENUMBER=7, COST=300.0}], SHIPPINGADDRESS=[{POSTALCODE=L5J1H7, PROVINCE=ON, COUNTRY=Canada, CITY=Ottawa,STREET=17 Jane St.}], VERSION=2, _id=4F848E2BDA0670307E2A8FA8,DESCRIPTION=Pingpong table, CUSTOMER__id=4F848E2BDA0670307E2A8FA7, BILLINGADDRESS=[{POSTALCODE=L5J1H8, PROVINCE=ON, COUNTRY=Canada, CITY=Ottawa, STREET=7 Bank St.}]}] You'll not see any output in the browser, just the output in the console. But the code can be easily modified to do so. Once again, the complete Maven project can be downloaded here. Do you want to try accessing relational and non-relational (aka NoSQL) databases in the same PU ?

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  • SPARC T3-1 Record Results Running JD Edwards EnterpriseOne Day in the Life Benchmark with Added Batch Component

    - by Brian
    Using Oracle's SPARC T3-1 server for the application tier and Oracle's SPARC Enterprise M3000 server for the database tier, a world record result was produced running the Oracle's JD Edwards EnterpriseOne applications Day in the Life benchmark run concurrently with a batch workload. The SPARC T3-1 server based result has 25% better performance than the IBM Power 750 POWER7 server even though the IBM result did not include running a batch component. The SPARC T3-1 server based result has 25% better space/performance than the IBM Power 750 POWER7 server as measured by the online component. The SPARC T3-1 server based result is 5x faster than the x86-based IBM x3650 M2 server system when executing the online component of the JD Edwards EnterpriseOne 9.0.1 Day in the Life benchmark. The IBM result did not include a batch component. The SPARC T3-1 server based result has 2.5x better space/performance than the x86-based IBM x3650 M2 server as measured by the online component. The combination of SPARC T3-1 and SPARC Enterprise M3000 servers delivered a Day in the Life benchmark result of 5000 online users with 0.875 seconds of average transaction response time running concurrently with 19 Universal Batch Engine (UBE) processes at 10 UBEs/minute. The solution exercises various JD Edwards EnterpriseOne applications while running Oracle WebLogic Server 11g Release 1 and Oracle Web Tier Utilities 11g HTTP server in Oracle Solaris Containers, together with the Oracle Database 11g Release 2. The SPARC T3-1 server showed that it could handle the additional workload of batch processing while maintaining the same number of online users for the JD Edwards EnterpriseOne Day in the Life benchmark. This was accomplished with minimal loss in response time. JD Edwards EnterpriseOne 9.0.1 takes advantage of the large number of compute threads available in the SPARC T3-1 server at the application tier and achieves excellent response times. The SPARC T3-1 server consolidates the application/web tier of the JD Edwards EnterpriseOne 9.0.1 application using Oracle Solaris Containers. Containers provide flexibility, easier maintenance and better CPU utilization of the server leaving processing capacity for additional growth. A number of Oracle advanced technology and features were used to obtain this result: Oracle Solaris 10, Oracle Solaris Containers, Oracle Java Hotspot Server VM, Oracle WebLogic Server 11g Release 1, Oracle Web Tier Utilities 11g, Oracle Database 11g Release 2, the SPARC T3 and SPARC64 VII+ based servers. This is the first published result running both online and batch workload concurrently on the JD Enterprise Application server. No published results are available from IBM running the online component together with a batch workload. The 9.0.1 version of the benchmark saw some minor performance improvements relative to 9.0. When comparing between 9.0.1 and 9.0 results, the reader should take this into account when the difference between results is small. Performance Landscape JD Edwards EnterpriseOne Day in the Life Benchmark Online with Batch Workload This is the first publication on the Day in the Life benchmark run concurrently with batch jobs. The batch workload was provided by Oracle's Universal Batch Engine. System RackUnits Online Users Resp Time (sec) BatchConcur(# of UBEs) BatchRate(UBEs/m) Version SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10 M3000, 1xSPARC64 VII+ (2.86 GHz), Solaris 10 4 5000 0.88 19 10 9.0.1 Resp Time (sec) — Response time of online jobs reported in seconds Batch Concur (# of UBEs) — Batch concurrency presented in the number of UBEs Batch Rate (UBEs/m) — Batch transaction rate in UBEs/minute. JD Edwards EnterpriseOne Day in the Life Benchmark Online Workload Only These results are for the Day in the Life benchmark. They are run without any batch workload. System RackUnits Online Users ResponseTime (sec) Version SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10 M3000, 1xSPARC64 VII (2.75 GHz), Solaris 10 4 5000 0.52 9.0.1 IBM Power 750, 1xPOWER7 (3.55 GHz), IBM i7.1 4 4000 0.61 9.0 IBM x3650M2, 2xIntel X5570 (2.93 GHz), OVM 2 1000 0.29 9.0 IBM result from http://www-03.ibm.com/systems/i/advantages/oracle/, IBM used WebSphere Configuration Summary Hardware Configuration: 1 x SPARC T3-1 server 1 x 1.65 GHz SPARC T3 128 GB memory 16 x 300 GB 10000 RPM SAS 1 x Sun Flash Accelerator F20 PCIe Card, 92 GB 1 x 10 GbE NIC 1 x SPARC Enterprise M3000 server 1 x 2.86 SPARC64 VII+ 64 GB memory 1 x 10 GbE NIC 2 x StorageTek 2540 + 2501 Software Configuration: JD Edwards EnterpriseOne 9.0.1 with Tools 8.98.3.3 Oracle Database 11g Release 2 Oracle 11g WebLogic server 11g Release 1 version 10.3.2 Oracle Web Tier Utilities 11g Oracle Solaris 10 9/10 Mercury LoadRunner 9.10 with Oracle Day in the Life kit for JD Edwards EnterpriseOne 9.0.1 Oracle’s Universal Batch Engine - Short UBEs and Long UBEs Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and other manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE workload of 15 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large UBEs, and the QPROCESS queue for short UBEs run concurrently. One of the Oracle Solaris Containers ran 4 Long UBEs, while another Container ran 15 short UBEs concurrently. The mixed size UBEs ran concurrently from the SPARC T3-1 server with the 5000 online users driven by the LoadRunner. Oracle’s UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers and two Oracle Fusion Middleware WebLogic Servers 11g R1 coupled with two Oracle Fusion Middleware 11g Web Tier HTTP Server instances on the SPARC T3-1 server were hosted in four separate Oracle Solaris Containers to demonstrate consolidation of multiple application and web servers. See Also SPARC T3-1 oracle.com SPARC Enterprise M3000 oracle.com Oracle Solaris oracle.com JD Edwards EnterpriseOne oracle.com Oracle Database 11g Release 2 Enterprise Edition oracle.com Disclosure Statement Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 6/27/2011.

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  • SQL SERVER – Weekly Series – Memory Lane – #035

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Row Overflow Data Explanation  In SQL Server 2005 one table row can contain more than one varchar(8000) fields. One more thing, the exclusions has exclusions also the limit of each individual column max width of 8000 bytes does not apply to varchar(max), nvarchar(max), varbinary(max), text, image or xml data type columns. Comparison Index Fragmentation, Index De-Fragmentation, Index Rebuild – SQL SERVER 2000 and SQL SERVER 2005 An old but like a gold article. Talks about lots of concepts related to Index and the difference from earlier version to the newer version. I strongly suggest that everyone should read this article just to understand how SQL Server has moved forward with the technology. Improvements in TempDB SQL Server 2005 had come up with quite a lots of improvements and this blog post describes them and explains the same. If you ask me what is my the most favorite article from early career. I must point out to this article as when I wrote this one I personally have learned a lot of new things. Recompile All The Stored Procedure on Specific TableI prefer to recompile all the stored procedure on the table, which has faced mass insert or update. sp_recompiles marks stored procedures to recompile when they execute next time. This blog post explains the same with the help of a script.  2008 SQLAuthority Download – SQL Server Cheatsheet You can download and print this cheat sheet and use it for your personal reference. If you have any suggestions, please let me know and I will see if I can update this SQL Server cheat sheet. Difference Between DBMS and RDBMS What is the difference between DBMS and RDBMS? DBMS – Data Base Management System RDBMS – Relational Data Base Management System or Relational DBMS High Availability – Hot Add Memory Hot Add CPU and Hot Add Memory are extremely interesting features of the SQL Server, however, personally I have not witness them heavily used. These features also have few restriction as well. I blogged about them in detail. 2009 Delete Duplicate Rows I have demonstrated in this blog post how one can identify and delete duplicate rows. Interesting Observation of Logon Trigger On All Servers – Solution The question I put forth in my previous article was – In single login why the trigger fires multiple times; it should be fired only once. I received numerous answers in thread as well as in my MVP private news group. Now, let us discuss the answer for the same. The answer is – It happens because multiple SQL Server services are running as well as intellisense is turned on. Blog post demonstrates how we can do the same with the help of SQL scripts. Management Studio New Features I have selected my favorite 5 features and blogged about it. IntelliSense for Query Editing Multi Server Query Query Editor Regions Object Explorer Enhancements Activity Monitors Maximum Number of Index per Table One of the questions I asked in my user group was – What is the maximum number of Index per table? I received lots of answers to this question but only two answers are correct. Let us now take a look at them in this blog post. 2010 Default Statistics on Column – Automatic Statistics on Column The truth is, Statistics can be in a table even though there is no Index in it. If you have the auto- create and/or auto-update Statistics feature turned on for SQL Server database, Statistics will be automatically created on the Column based on a few conditions. Please read my previously posted article, SQL SERVER – When are Statistics Updated – What triggers Statistics to Update, for the specific conditions when Statistics is updated. 2011 T-SQL Scripts to Find Maximum between Two Numbers In this blog post there are two different scripts listed which demonstrates way to find the maximum number between two numbers. I need your help, which one of the script do you think is the most accurate way to find maximum number? Find Details for Statistics of Whole Database – DMV – T-SQL Script I was recently asked is there a single script which can provide all the necessary details about statistics for any database. This question made me write following script. I was initially planning to use sp_helpstats command but I remembered that this is marked to be deprecated in future. 2012 Introduction to Function SIGN SIGN Function is very fundamental function. It will return the value 1, -1 or 0. If your value is negative it will return you negative -1 and if it is positive it will return you positive +1. Let us start with a simple small example. Template Browser – A Very Important and Useful Feature of SSMS Templates are like a quick cheat sheet or quick reference. Templates are available to create objects like databases, tables, views, indexes, stored procedures, triggers, statistics, and functions. Templates are also available for Analysis Services as well. The template scripts contain parameters to help you customize the code. You can Replace Template Parameters dialog box to insert values into the script. An invalid floating point operation occurred If you run any of the above functions they will give you an error related to invalid floating point. Honestly there is no workaround except passing the function appropriate values. SQRT of a negative number will give you result in real numbers which is not supported at this point of time as well LOG of a negative number is not possible (because logarithm is the inverse function of an exponential function and the exponential function is NEVER negative). Validating Spatial Object with IsValidDetailed Function SQL Server 2012 has introduced the new function IsValidDetailed(). This function has made my life very easy. In simple words, this function will check if the spatial object passed is valid or not. If it is valid it will give information that it is valid. If the spatial object is not valid it will return the answer that it is not valid and the reason for the same. This makes it very easy to debug the issue and make the necessary correction. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Using Node.js as an accelerator for WCF REST services

    - by Elton Stoneman
    Node.js is a server-side JavaScript platform "for easily building fast, scalable network applications". It's built on Google's V8 JavaScript engine and uses an (almost) entirely async event-driven processing model, running in a single thread. If you're new to Node and your reaction is "why would I want to run JavaScript on the server side?", this is the headline answer: in 150 lines of JavaScript you can build a Node.js app which works as an accelerator for WCF REST services*. It can double your messages-per-second throughput, halve your CPU workload and use one-fifth of the memory footprint, compared to the WCF services direct.   Well, it can if: 1) your WCF services are first-class HTTP citizens, honouring client cache ETag headers in request and response; 2) your services do a reasonable amount of work to build a response; 3) your data is read more often than it's written. In one of my projects I have a set of REST services in WCF which deal with data that only gets updated weekly, but which can be read hundreds of times an hour. The services issue ETags and will return a 304 if the client sends a request with the current ETag, which means in the most common scenario the client uses its local cached copy. But when the weekly update happens, then all the client caches are invalidated and they all need the same new data. Then the service will get hundreds of requests with old ETags, and they go through the full service stack to build the same response for each, taking up threads and processing time. Part of that processing means going off to a database on a separate cloud, which introduces more latency and downtime potential.   We can use ASP.NET output caching with WCF to solve the repeated processing problem, but the server will still be thread-bound on incoming requests, and to get the current ETags reliably needs a database call per request. The accelerator solves that by running as a proxy - all client calls come into the proxy, and the proxy routes calls to the underlying REST service. We could use Node as a straight passthrough proxy and expect some benefit, as the server would be less thread-bound, but we would still have one WCF and one database call per proxy call. But add some smart caching logic to the proxy, and share ETags between Node and WCF (so the proxy doesn't even need to call the servcie to get the current ETag), and the underlying service will only be invoked when data has changed, and then only once - all subsequent client requests will be served from the proxy cache.   I've built this as a sample up on GitHub: NodeWcfAccelerator on sixeyed.codegallery. Here's how the architecture looks:     The code is very simple. The Node proxy runs on port 8010 and all client requests target the proxy. If the client request has an ETag header then the proxy looks up the ETag in the tag cache to see if it is current - the sample uses memcached to share ETags between .NET and Node. If the ETag from the client matches the current server tag, the proxy sends a 304 response with an empty body to the client, telling it to use its own cached version of the data. If the ETag from the client is stale, the proxy looks for a local cached version of the response, checking for a file named after the current ETag. If that file exists, its contents are returned to the client as the body in a 200 response, which includes the current ETag in the header. If the proxy does not have a local cached file for the service response, it calls the service, and writes the WCF response to the local cache file, and to the body of a 200 response for the client. So the WCF service is only troubled if both client and proxy have stale (or no) caches.   The only (vaguely) clever bit in the sample is using the ETag cache, so the proxy can serve cached requests without any communication with the underlying service, which it does completely generically, so the proxy has no notion of what it is serving or what the services it proxies are doing. The relative path from the URL is used as the lookup key, so there's no shared key-generation logic between .NET and Node, and when WCF stores a tag it also stores the "read" URL against the ETag so it can be used for a reverse lookup, e.g:   Key Value /WcfSampleService/PersonService.svc/rest/fetch/3 "28cd4796-76b8-451b-adfd-75cb50a50fa6" "28cd4796-76b8-451b-adfd-75cb50a50fa6" /WcfSampleService/PersonService.svc/rest/fetch/3    In Node we read the cache using the incoming URL path as the key and we know that "28cd4796-76b8-451b-adfd-75cb50a50fa6" is the current ETag; we look for a local cached response in /caches/28cd4796-76b8-451b-adfd-75cb50a50fa6.body (and the corresponding .header file which contains the original service response headers, so the proxy response is exactly the same as the underlying service). When the data is updated, we need to invalidate the ETag cache – which is why we need the reverse lookup in the cache. In the WCF update service, we don't need to know the URL of the related read service - we fetch the entity from the database, do a reverse lookup on the tag cache using the old ETag to get the read URL, update the new ETag against the URL, store the new reverse lookup and delete the old one.   Running Apache Bench against the two endpoints gives the headline performance comparison. Making 1000 requests with concurrency of 100, and not sending any ETag headers in the requests, with the Node proxy I get 102 requests handled per second, average response time of 975 milliseconds with 90% of responses served within 850 milliseconds; going direct to WCF with the same parameters, I get 53 requests handled per second, mean response time of 1853 milliseconds, with 90% of response served within 3260 milliseconds. Informally monitoring server usage during the tests, Node maxed at 20% CPU and 20Mb memory; IIS maxed at 60% CPU and 100Mb memory.   Note that the sample WCF service does a database read and sleeps for 250 milliseconds to simulate a moderate processing load, so this is *not* a baseline Node-vs-WCF comparison, but for similar scenarios where the  service call is expensive but applicable to numerous clients for a long timespan, the performance boost from the accelerator is considerable.     * - actually, the accelerator will work nicely for any HTTP request, where the URL (path + querystring) uniquely identifies a resource. In the sample, there is an assumption that the ETag is a GUID wrapped in double-quotes (e.g. "28cd4796-76b8-451b-adfd-75cb50a50fa6") – which is the default for WCF services. I use that assumption to name the cache files uniquely, but it is a trivial change to adapt to other ETag formats.

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  • Cloud Computing = Elasticity * Availability

    - by Herve Roggero
    What is cloud computing? Is hosting the same thing as cloud computing? Are you running a cloud if you already use virtual machines? What is the difference between Infrastructure as a Service (IaaS) and a cloud provider? And the list goes on… these questions keep coming up and all try to fundamentally explain what “cloud” means relative to other concepts. At the risk of over simplification, answering these questions becomes simpler once you understand the primary foundations of cloud computing: Elasticity and Availability.   Elasticity The basic value proposition of cloud computing is to pay as you go, and to pay for what you use. This implies that an application can expand and contract on demand, across all its tiers (presentation layer, services, database, security…).  This also implies that application components can grow independently from each other. So if you need more storage for your database, you should be able to grow that tier without affecting, reconfiguring or changing the other tiers. Basically, cloud applications behave like a sponge; when you add water to a sponge, it grows in size; in the application world, the more customers you add, the more it grows. Pure IaaS providers will provide certain benefits, specifically in terms of operating costs, but an IaaS provider will not help you in making your applications elastic; neither will Virtual Machines. The smallest elasticity unit of an IaaS provider and a Virtual Machine environment is a server (physical or virtual). While adding servers in a datacenter helps in achieving scale, it is hardly enough. The application has yet to use this hardware.  If the process of adding computing resources is not transparent to the application, the application is not elastic.   As you can see from the above description, designing for the cloud is not about more servers; it is about designing an application for elasticity regardless of the underlying server farm.   Availability The fact of the matter is that making applications highly available is hard. It requires highly specialized tools and trained staff. On top of it, it's expensive. Many companies are required to run multiple data centers due to high availability requirements. In some organizations, some data centers are simply on standby, waiting to be used in a case of a failover. Other organizations are able to achieve a certain level of success with active/active data centers, in which all available data centers serve incoming user requests. While achieving high availability for services is relatively simple, establishing a highly available database farm is far more complex. In fact it is so complex that many companies establish yearly tests to validate failover procedures.   To a certain degree certain IaaS provides can assist with complex disaster recovery planning and setting up data centers that can achieve successful failover. However the burden is still on the corporation to manage and maintain such an environment, including regular hardware and software upgrades. Cloud computing on the other hand removes most of the disaster recovery requirements by hiding many of the underlying complexities.   Cloud Providers A cloud provider is an infrastructure provider offering additional tools to achieve application elasticity and availability that are not usually available on-premise. For example Microsoft Azure provides a simple configuration screen that makes it possible to run 1 or 100 web sites by clicking a button or two on a screen (simplifying provisioning), and soon SQL Azure will offer Data Federation to allow database sharding (which allows you to scale the database tier seamlessly and automatically). Other cloud providers offer certain features that are not available on-premise as well, such as the Amazon SC3 (Simple Storage Service) which gives you virtually unlimited storage capabilities for simple data stores, which is somewhat equivalent to the Microsoft Azure Table offering (offering a server-independent data storage model). Unlike IaaS providers, cloud providers give you the necessary tools to adopt elasticity as part of your application architecture.    Some cloud providers offer built-in high availability that get you out of the business of configuring clustered solutions, or running multiple data centers. Some cloud providers will give you more control (which puts some of that burden back on the customers' shoulder) and others will tend to make high availability totally transparent. For example, SQL Azure provides high availability automatically which would be very difficult to achieve (and very costly) on premise.   Keep in mind that each cloud provider has its strengths and weaknesses; some are better at achieving transparent scalability and server independence than others.    Not for Everyone Note however that it is up to you to leverage the elasticity capabilities of a cloud provider, as discussed previously; if you build a website that does not need to scale, for which elasticity is not important, then you can use a traditional host provider unless you also need high availability. Leveraging the technologies of cloud providers can be difficult and can become a journey for companies that build their solutions in a scale up fashion. Cloud computing promises to address cost containment and scalability of applications with built-in high availability. If your application does not need to scale or you do not need high availability, then cloud computing may not be for you. In fact, you may pay a premium to run your applications with cloud providers due to the underlying technologies built specifically for scalability and availability requirements. And as such, the cloud is not for everyone.   Consistent Customer Experience, Predictable Cost With all its complexities, buzz and foggy definition, cloud computing boils down to a simple objective: consistent customer experience at a predictable cost.  The objective of a cloud solution is to provide the same user experience to your last customer than the first, while keeping your operating costs directly proportional to the number of customers you have. Making your applications elastic and highly available across all its tiers, with as much automation as possible, achieves the first objective of a consistent customer experience. And the ability to expand and contract the infrastructure footprint of your application dynamically achieves the cost containment objectives.     Herve Roggero is a SQL Azure MVP and co-author of Pro SQL Azure (APress).  He is the co-founder of Blue Syntax Consulting (www.bluesyntax.net), a company focusing on cloud computing technologies helping customers understand and adopt cloud computing technologies. For more information contact herve at hroggero @ bluesyntax.net .

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  • SQL SERVER – SSIS Look Up Component – Cache Mode – Notes from the Field #028

    - by Pinal Dave
    [Notes from Pinal]: Lots of people think that SSIS is all about arranging various operations together in one logical flow. Well, the understanding is absolutely correct, but the implementation of the same is not as easy as it seems. Similarly most of the people think lookup component is just component which does look up for additional information and does not pay much attention to it. Due to the same reason they do not pay attention to the same and eventually get very bad performance. Linchpin People are database coaches and wellness experts for a data driven world. In this 28th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to write a good lookup component with Cache Mode. In SQL Server Integration Services, the lookup component is one of the most frequently used tools for data validation and completion.  The lookup component is provided as a means to virtually join one set of data to another to validate and/or retrieve missing values.  Properly configured, it is reliable and reasonably fast. Among the many settings available on the lookup component, one of the most critical is the cache mode.  This selection will determine whether and how the distinct lookup values are cached during package execution.  It is critical to know how cache modes affect the result of the lookup and the performance of the package, as choosing the wrong setting can lead to poorly performing packages, and in some cases, incorrect results. Full Cache The full cache mode setting is the default cache mode selection in the SSIS lookup transformation.  Like the name implies, full cache mode will cause the lookup transformation to retrieve and store in SSIS cache the entire set of data from the specified lookup location.  As a result, the data flow in which the lookup transformation resides will not start processing any data buffers until all of the rows from the lookup query have been cached in SSIS. The most commonly used cache mode is the full cache setting, and for good reason.  The full cache setting has the most practical applications, and should be considered the go-to cache setting when dealing with an untested set of data. With a moderately sized set of reference data, a lookup transformation using full cache mode usually performs well.  Full cache mode does not require multiple round trips to the database, since the entire reference result set is cached prior to data flow execution. There are a few potential gotchas to be aware of when using full cache mode.  First, you can see some performance issues – memory pressure in particular – when using full cache mode against large sets of reference data.  If the table you use for the lookup is very large (either deep or wide, or perhaps both), there’s going to be a performance cost associated with retrieving and caching all of that data.  Also, keep in mind that when doing a lookup on character data, full cache mode will always do a case-sensitive (and in some cases, space-sensitive) string comparison even if your database is set to a case-insensitive collation.  This is because the in-memory lookup uses a .NET string comparison (which is case- and space-sensitive) as opposed to a database string comparison (which may be case sensitive, depending on collation).  There’s a relatively easy workaround in which you can use the UPPER() or LOWER() function in the pipeline data and the reference data to ensure that case differences do not impact the success of your lookup operation.  Again, neither of these present a reason to avoid full cache mode, but should be used to determine whether full cache mode should be used in a given situation. Full cache mode is ideally useful when one or all of the following conditions exist: The size of the reference data set is small to moderately sized The size of the pipeline data set (the data you are comparing to the lookup table) is large, is unknown at design time, or is unpredictable Each distinct key value(s) in the pipeline data set is expected to be found multiple times in that set of data Partial Cache When using the partial cache setting, lookup values will still be cached, but only as each distinct value is encountered in the data flow.  Initially, each distinct value will be retrieved individually from the specified source, and then cached.  To be clear, this is a row-by-row lookup for each distinct key value(s). This is a less frequently used cache setting because it addresses a narrower set of scenarios.  Because each distinct key value(s) combination requires a relational round trip to the lookup source, performance can be an issue, especially with a large pipeline data set to be compared to the lookup data set.  If you have, for example, a million records from your pipeline data source, you have the potential for doing a million lookup queries against your lookup data source (depending on the number of distinct values in the key column(s)).  Therefore, one has to be keenly aware of the expected row count and value distribution of the pipeline data to safely use partial cache mode. Using partial cache mode is ideally suited for the conditions below: The size of the data in the pipeline (more specifically, the number of distinct key column) is relatively small The size of the lookup data is too large to effectively store in cache The lookup source is well indexed to allow for fast retrieval of row-by-row values No Cache As you might guess, selecting no cache mode will not add any values to the lookup cache in SSIS.  As a result, every single row in the pipeline data set will require a query against the lookup source.  Since no data is cached, it is possible to save a small amount of overhead in SSIS memory in cases where key values are not reused.  In the real world, I don’t see a lot of use of the no cache setting, but I can imagine some edge cases where it might be useful. As such, it’s critical to know your data before choosing this option.  Obviously, performance will be an issue with anything other than small sets of data, as the no cache setting requires row-by-row processing of all of the data in the pipeline. I would recommend considering the no cache mode only when all of the below conditions are true: The reference data set is too large to reasonably be loaded into SSIS memory The pipeline data set is small and is not expected to grow There are expected to be very few or no duplicates of the key values(s) in the pipeline data set (i.e., there would be no benefit from caching these values) Conclusion The cache mode, an often-overlooked setting on the SSIS lookup component, represents an important design decision in your SSIS data flow.  Choosing the right lookup cache mode directly impacts the fidelity of your results and the performance of package execution.  Know how this selection impacts your ETL loads, and you’ll end up with more reliable, faster packages. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SSIS

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  • Cost Comparison Hard Disk Drive to Solid State Drive on Price per Gigabyte - dispelling a myth!

    - by tonyrogerson
    It is often said that Hard Disk Drive storage is significantly cheaper per GiByte than Solid State Devices – this is wholly inaccurate within the database space. People need to look at the cost of the complete solution and not just a single component part in isolation to what is really required to meet the business requirement. Buying a single Hitachi Ultrastar 600GB 3.5” SAS 15Krpm hard disk drive will cost approximately £239.60 (http://scan.co.uk, 22nd March 2012) compared to an OCZ 600GB Z-Drive R4 CM84 PCIe costing £2,316.54 (http://scan.co.uk, 22nd March 2012); I’ve not included FusionIO ioDrive because there is no public pricing available for it – something I never understand and personally when companies do this I immediately think what are they hiding, luckily in FusionIO’s case the product is proven though is expensive compared to OCZ enterprise offerings. On the face of it the single 15Krpm hard disk has a price per GB of £0.39, the SSD £3.86; this is what you will see in the press and this is what sales people will use in comparing the two technologies – do not be fooled by this bullshit people! What is the requirement? The requirement is the database will have a static size of 400GB kept static through archiving so growth and trim will balance the database size, the client requires resilience, there will be several hundred call centre staff querying the database where queries will read a small amount of data but there will be no hot spot in the data so the randomness will come across the entire 400GB of the database, estimates predict that the IOps required will be approximately 4,000IOps at peak times, because it’s a call centre system the IO latency is important and must remain below 5ms per IO. The balance between read and write is 70% read, 30% write. The requirement is now defined and we have three of the most important pieces of the puzzle – space required, estimated IOps and maximum latency per IO. Something to consider with regard SQL Server; write activity requires synchronous IO to the storage media specifically the transaction log; that means the write thread will wait until the IO is completed and hardened off until the thread can continue execution, the requirement has stated that 30% of the system activity will be write so we can expect a high amount of synchronous activity. The hardware solution needs to be defined; two possible solutions: hard disk or solid state based; the real question now is how many hard disks are required to achieve the IO throughput, the latency and resilience, ditto for the solid state. Hard Drive solution On a test on an HP DL380, P410i controller using IOMeter against a single 15Krpm 146GB SAS drive, the throughput given on a transfer size of 8KiB against a 40GiB file on a freshly formatted disk where the partition is the only partition on the disk thus the 40GiB file is on the outer edge of the drive so more sectors can be read before head movement is required: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 3,733 IOps at an average latency of 34.06ms (34 MiB/s). The same test was done on the same disk but the test file was 130GiB: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 528 IOps at an average latency of 217.49ms (4 MiB/s). From the result it is clear random performance gets worse as the disk fills up – I’m currently writing an article on short stroking which will cover this in detail. Given the work load is random in nature looking at the random performance of the single drive when only 40 GiB of the 146 GB is used gives near the IOps required but the latency is way out. Luckily I have tested 6 x 15Krpm 146GB SAS 15Krpm drives in a RAID 0 using the same test methodology, for the same test above on a 130 GiB for each drive added the performance boost is near linear, for each drive added throughput goes up by 5 MiB/sec, IOps by 700 IOps and latency reducing nearly 50% per drive added (172 ms, 94 ms, 65 ms, 47 ms, 37 ms, 30 ms). This is because the same 130GiB is spread out more as you add drives 130 / 1, 130 / 2, 130 / 3 etc. so implicit short stroking is occurring because there is less file on each drive so less head movement required. The best latency is still 30 ms but we have the IOps required now, but that’s on a 130GiB file and not the 400GiB we need. Some reality check here: a) the drive randomness is more likely to be 50/50 and not a full 100% but the above has highlighted the effect randomness has on the drive and the more a drive fills with data the worse the effect. For argument sake let us assume that for the given workload we need 8 disks to do the job, for resilience reasons we will need 16 because we need to RAID 1+0 them in order to get the throughput and the resilience, RAID 5 would degrade performance. Cost for hard drives: 16 x £239.60 = £3,833.60 For the hard drives we will need disk controllers and a separate external disk array because the likelihood is that the server itself won’t take the drives, a quick spec off DELL for a PowerVault MD1220 which gives the dual pathing with 16 disks 146GB 15Krpm 2.5” disks is priced at £7,438.00, note its probably more once we had two controller cards to sit in the server in, racking etc. Minimum cost taking the DELL quote as an example is therefore: {Cost of Hardware} / {Storage Required} £7,438.60 / 400 = £18.595 per GB £18.59 per GiB is a far cry from the £0.39 we had been told by the salesman and the myth. Yes, the storage array is composed of 16 x 146 disks in RAID 10 (therefore 8 usable) giving an effective usable storage availability of 1168GB but the actual storage requirement is only 400 and the extra disks have had to be purchased to get the  IOps up. Solid State Drive solution A single card significantly exceeds the IOps and latency required, for resilience two will be required. ( £2,316.54 * 2 ) / 400 = £11.58 per GB With the SSD solution only two PCIe sockets are required, no external disk units, no additional controllers, no redundant controllers etc. Conclusion I hope by showing you an example that the myth that hard disk drives are cheaper per GiB than Solid State has now been dispelled - £11.58 per GB for SSD compared to £18.59 for Hard Disk. I’ve not even touched on the running costs, compare the costs of running 18 hard disks, that’s a lot of heat and power compared to two PCIe cards!Just a quick note: I've left a fair amount of information out due to this being a blog! If in doubt, email me :)I'll also deal with the myth that SSD's wear out at a later date as well - that's just way over done still, yes, 5 years ago, but now - no.

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  • More Great Improvements to the Windows Azure Management Portal

    - by ScottGu
    Over the last 3 weeks we’ve released a number of enhancements to the new Windows Azure Management Portal.  These new capabilities include: Localization Support for 6 languages Operation Log Support Support for SQL Database Metrics Virtual Machine Enhancements (quick create Windows + Linux VMs) Web Site Enhancements (support for creating sites in all regions, private github repo deployment) Cloud Service Improvements (deploy from storage account, configuration support of dedicated cache) Media Service Enhancements (upload, encode, publish, stream all from within the portal) Virtual Networking Usability Enhancements Custom CNAME support with Storage Accounts All of these improvements are now live in production and available to start using immediately.  Below are more details on them: Localization Support The Windows Azure Portal now supports 6 languages – English, German, Spanish, French, Italian and Japanese. You can easily switch between languages by clicking on the Avatar bar on the top right corner of the Portal: Selecting a different language will automatically refresh the UI within the portal in the selected language: Operation Log Support The Windows Azure Portal now supports the ability for administrators to review the “operation logs” of the services they manage – making it easy to see exactly what management operations were performed on them.  You can query for these by selecting the “Settings” tab within the Portal and then choosing the “Operation Logs” tab within it.  This displays a filter UI that enables you to query for operations by date and time: As of the most recent release we now show logs for all operations performed on Cloud Services and Storage Accounts.  You can click on any operation in the list and click the “Details” button in the command bar to retrieve detailed status about it.  This now makes it possible to retrieve details about every management operation performed. In future updates you’ll see us extend the operation log capability to apply to all Windows Azure Services – which will enable great post-mortem and audit support. Support for SQL Database Metrics You can now monitor the number of successful connections, failed connections and deadlocks in your SQL databases using the new “Dashboard” view provided on each SQL Database resource: Additionally, if the database is added as a “linked resource” to a Web Site or Cloud Service, monitoring metrics for the linked SQL database are shown along with the Web Site or Cloud Service metrics in the dashboard. This helps with viewing and managing aggregated information across both resources in your application. Enhancements to Virtual Machines The most recent Windows Azure Portal release brings with it some nice usability improvements to Virtual Machines: Integrated Quick Create experience for Windows and Linux VMs Creating a new Windows or Linux VM is now easy using the new “Quick Create” experience in the Portal: In addition to Windows VM templates you can also now select Linux image templates in the quick create UI: This makes it incredibly easy to create a new Virtual Machine in only a few seconds. Enhancements to Web Sites Prior to this past month’s release, users were forced to choose a single geographical region when creating their first site.  After that, subsequent sites could only be created in that same region.  This restriction has now been removed, and you can now create sites in any region at any time and have up to 10 free sites in each supported region: One of the new regions we’ve recently opened up is the “East Asia” region.  This allows you to now deploy sites to North America, Europe and Asia simultaneously.  Private GitHub Repository Support This past week we also enabled Git based continuous deployment support for Web Sites from private GitHub and BitBucket repositories (previous to this you could only enable this with public repositories).  Enhancements to Cloud Services Experience The most recent Windows Azure Portal release brings with it some nice usability improvements to Cloud Services: Deploy a Cloud Service from a Windows Azure Storage Account The Windows Azure Portal now supports deploying an application package and configuration file stored in a blob container in Windows Azure Storage. The ability to upload an application package from storage is available when you custom create, or upload to, or update a cloud service deployment. To upload an application package and configuration, create a Cloud Service, then select the file upload dialog, and choose to upload from a Windows Azure Storage Account: To upload an application package from storage, click the “FROM STORAGE” button and select the application package and configuration file to use from the new blob storage explorer in the portal. Configure Windows Azure Caching in a caching enabled cloud service If you have deployed the new dedicated cache within a cloud service role, you can also now configure the cache settings in the portal by navigating to the configuration tab of for your Cloud Service deployment. The configuration experience is similar to the one in Visual Studio when you create a cloud service and add a caching role.  The portal now allows you to add or remove named caches and change the settings for the named caches – all from within the Portal and without needing to redeploy your application. Enhancements to Media Services You can now upload, encode, publish, and play your video content directly from within the Windows Azure Portal.  This makes it incredibly easy to get started with Windows Azure Media Services and perform common tasks without having to write any code. Simply navigate to your media service and then click on the “Content” tab.  All of the media content within your media service account will be listed here: Clicking the “upload” button within the portal now allows you to upload a media file directly from your computer: This will cause the video file you chose from your local file-system to be uploaded into Windows Azure.  Once uploaded, you can select the file within the content tab of the Portal and click the “Encode” button to transcode it into different streaming formats: The portal includes a number of pre-set encoding formats that you can easily convert media content into: Once you select an encoding and click the ok button, Windows Azure Media Services will kick off an encoding job that will happen in the cloud (no need for you to stand-up or configure a custom encoding server).  When it’s finished, you can select the video in the “Content” tab and then click PUBLISH in the command bar to setup an origin streaming end-point to it: Once the media file is published you can point apps against the public URL and play the content using Windows Azure Media Services – no need to setup or run your own streaming server.  You can also now select the file and click the “Play” button in the command bar to play it using the streaming endpoint directly within the Portal: This makes it incredibly easy to try out and use Windows Azure Media Services and test out an end-to-end workflow without having to write any code.  Once you test things out you can of course automate it using script or code – providing you with an incredibly powerful Cloud Media platform that you can use. Enhancements to Virtual Network Experience Over the last few months, we have received feedback on the complexity of the Virtual Network creation experience. With these most recent Portal updates, we have added a Quick Create experience that makes the creation experience very simple. All that an administrator now needs to do is to provide a VNET name, choose an address space and the size of the VNET address space. They no longer need to understand the intricacies of the CIDR format or walk through a 4-page wizard or create a VNET / subnet. This makes creating virtual networks really simple: The portal also now has a “Register DNS Server” task that makes it easy to register DNS servers and associate them with a virtual network. Enhancements to Storage Experience The portal now lets you register custom domain names for your Windows Azure Storage Accounts.  To enable this, select a storage resource and then go to the CONFIGURE tab for a storage account, and then click MANAGE DOMAIN on the command bar: Clicking “Manage Domain” will bring up a dialog that allows you to register any CNAME you want: Summary The above features are all now live in production and available to use immediately.  If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using them today.  Visit the Windows Azure Developer Center to learn more about how to build apps with it. One of the other cool features that is now live within the portal is our new Windows Azure Store – which makes it incredibly easy to try and purchase developer services from a variety of partners.  It is an incredibly awesome new capability – and something I’ll be doing a dedicated post about shortly. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario   Conventional Structures   Columnstore   Δ SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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