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  • MDX lekérdezések az Oracle OLAP-hoz

    - by Fekete Zoltán
    Az Oracle OpenWord-ön, 2009. október 12-én jelentette be az Oracle, hogy elkészült a Simba Technologies MDX eszköze az Oracle OLAP eléréséhez: Oracle and Simba Technologies Introduce MDX Provider for Oracle® OLAP. Az MDX Provider for Oracle® OLAP eszközzel közvetlenül az Excel felületrol lehet elérni az Oracle OLAP multidimenziós (multidimenzionális) motor által kezelt adatokat. Az MDX Provider for Oracle OLAP esköz lehetové teszi, hogy az Excel kereszttábla/pivott'bla (PivotTable) és PivotChart funkciókat közvetlenül használjuk az Oracle OLAP-ban tárolt adatvagyon ékszerek eléréséhez. :) - könnyen kihasználhatjuk az Oracle Database OLAP nagy sebességét a lekérdezési és a számítási oldalon is - támogatott táblázatkezelo és adatbázis-kezelo platformok: Microsoft Excel 2007 / 2003 és Oracle Database 11g Release 1 és Release 2. Az Oracle OLAP az Oracle Database EE-ben érheto el, annak opciójaként. Az Oracle a hírös és régebben csinos rekordokat is felmutató Oracle Express Server-bol fejlesztette ki az Oracle OLAP-ot, ami az adatbáziskezelo szerver részeként muködik. Technikai OLAP információ. Mire is jó az Oracle OLAP: - az üzleti szakemberek gondolkodásához közel álló elemzési lehetoséget nyújt - kifinomult analitikus lekérdezések elvégzése - hatalmas lekérdezési sebesség, apró futási idok bármilyen mennyiségu adatra - komoly számítási sebesség óriási adatmennyiségen is - gyors aggregációk - SQL-bol is kezelhetok és lekérdezhetok az OLAP adatok! - a cube-organised materialized views alkalmazásával a relációs részletes adatok mögé transzparens aggregációs szinteket helyezhetünk el könnyen Az MDX Provider for Oracle OLAP eszköz a következo helyen letöltheto és kipróbálható: http://www.simba.com/MDX-Provider-for-Oracle-OLAP.htm.

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  • OWB 11gR2 – OLAP and Simba

    - by David Allan
    Oracle Warehouse Builder was the first ETL product to provide a single integrated and complete environment for managing enterprise data warehouse solutions that also incorporate multi-dimensional schemas. The OWB 11gR2 release provides Oracle OLAP 11g deployment for multi-dimensional models (in addition to support for prior releases of OLAP). This means users can easily utilize Simba's MDX Provider for Oracle OLAP (see here for details and cost) which allows you to use the powerful and popular ad hoc query and analysis capabilities of Microsoft Excel PivotTables® and PivotCharts® with your Oracle OLAP business intelligence data. The extensions to the dimensional modeling capabilities have been built on established relational concepts, with the option to seamlessly move from a relational deployment model to a multi-dimensional model at the click of a button. This now means that ETL designers can logically model a complete data warehouse solution using one single tool and control the physical implementation of a logical model at deployment time. As a result data warehouse projects that need to provide a multi-dimensional model as part of the overall solution can be designed and implemented faster and more efficiently. Wizards for dimensions and cubes let you quickly build dimensional models and realize either relationally or as an Oracle database OLAP implementation, both 10g and 11g formats are supported based on a configuration option. The wizard provides a good first cut definition and the objects can be further refined in the editor. Both wizards let you choose the implementation, to deploy to OLAP in the database select MOLAP: multidimensional storage. You will then be asked what levels and attributes are to be defined, by default the wizard creates a level bases hierarchy, parent child hierarchies can be defined in the editor. Once the dimension or cube has been designed there are special mapping operators that make it easy to load data into the objects, below we load a constant value for the total level and the other levels from a source table.   Again when the cube is defined using the wizard we can edit the cube and define a number of analytic calculations by using the 'generate calculated measures' option on the measures panel. This lets you very easily add a lot of rich analytic measures to your cube. For example one of the measures is the percentage difference from a year ago which we can see in detail below. You can also add your own custom calculations to leverage the capabilities of the Oracle OLAP option, either by selecting existing template types such as moving averages to defining true custom expressions. The 11g OLAP option now supports percentage based summarization (the amount of data to precompute and store), this is available from the option 'cost based aggregation' in the cube's configuration. Ensure all measure-dimensions level based aggregation is switched off (on the cube-dimension panel) - previously level based aggregation was the only option. The 11g generated code now uses the new unified API as you see below, to generate the code, OWB needs a valid connection to a real schema, this was not needed before 11gR2 and is a new requirement since the OLAP API which OWB uses is not an offline one. Once all of the objects are deployed and the maps executed then we get to the fun stuff! How can we analyze the data? One option which is powerful and at many users' fingertips is using Microsoft Excel PivotTables® and PivotCharts®, which can be used with your Oracle OLAP business intelligence data by utilizing Simba's MDX Provider for Oracle OLAP (see Simba site for details of cost). I'll leave the exotic reporting illustrations to the experts (see Bud's demonstration here), but with Simba's MDX Provider for Oracle OLAP its very simple to easily access the analytics stored in the database (all built and loaded via the OWB 11gR2 release) and get the regular features of Excel at your fingertips such as using the conditional formatting features for example. That's a very quick run through of the OWB 11gR2 with respect to Oracle 11g OLAP integration and the reporting using Simba's MDX Provider for Oracle OLAP. Not a deep-dive in any way but a quick overview to illustrate the design capabilities and integrations possible.

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  • Building dynamic OLAP data marts on-the-fly

    - by DrJohn
    At the forthcoming SQLBits conference, I will be presenting a session on how to dynamically build an OLAP data mart on-the-fly. This blog entry is intended to clarify exactly what I mean by an OLAP data mart, why you may need to build them on-the-fly and finally outline the steps needed to build them dynamically. In subsequent blog entries, I will present exactly how to implement some of the techniques involved. What is an OLAP data mart? In data warehousing parlance, a data mart is a subset of the overall corporate data provided to business users to meet specific business needs. Of course, the term does not specify the technology involved, so I coined the term "OLAP data mart" to identify a subset of data which is delivered in the form of an OLAP cube which may be accompanied by the relational database upon which it was built. To clarify, the relational database is specifically create and loaded with the subset of data and then the OLAP cube is built and processed to make the data available to the end-users via standard OLAP client tools. Why build OLAP data marts? Market research companies sell data to their clients to make money. To gain competitive advantage, market research providers like to "add value" to their data by providing systems that enhance analytics, thereby allowing clients to make best use of the data. As such, OLAP cubes have become a standard way of delivering added value to clients. They can be built on-the-fly to hold specific data sets and meet particular needs and then hosted on a secure intranet site for remote access, or shipped to clients' own infrastructure for hosting. Even better, they support a wide range of different tools for analytical purposes, including the ever popular Microsoft Excel. Extension Attributes: The Challenge One of the key challenges in building multiple OLAP data marts based on the same 'template' is handling extension attributes. These are attributes that meet the client's specific reporting needs, but do not form part of the standard template. Now clearly, these extension attributes have to come into the system via additional files and ultimately be added to relational tables so they can end up in the OLAP cube. However, processing these files and filling dynamically altered tables with SSIS is a challenge as SSIS packages tend to break as soon as the database schema changes. There are two approaches to this: (1) dynamically build an SSIS package in memory to match the new database schema using C#, or (2) have the extension attributes provided as name/value pairs so the file's schema does not change and can easily be loaded using SSIS. The problem with the first approach is the complexity of writing an awful lot of complex C# code. The problem of the second approach is that name/value pairs are useless to an OLAP cube; so they have to be pivoted back into a proper relational table somewhere in the data load process WITHOUT breaking SSIS. How this can be done will be part of future blog entry. What is involved in building an OLAP data mart? There are a great many steps involved in building OLAP data marts on-the-fly. The key point is that all the steps must be automated to allow for the production of multiple OLAP data marts per day (i.e. many thousands, each with its own specific data set and attributes). Now most of these steps have a great deal in common with standard data warehouse practices. The key difference is that the databases are all built to order. The only permanent database is the metadata database (shown in orange) which holds all the metadata needed to build everything else (i.e. client orders, configuration information, connection strings, client specific requirements and attributes etc.). The staging database (shown in red) has a short life: it is built, populated and then ripped down as soon as the OLAP Data Mart has been populated. In the diagram below, the OLAP data mart comprises the two blue components: the Data Mart which is a relational database and the OLAP Cube which is an OLAP database implemented using Microsoft Analysis Services (SSAS). The client may receive just the OLAP cube or both components together depending on their reporting requirements.  So, in broad terms the steps required to fulfil a client order are as follows: Step 1: Prepare metadata Create a set of database names unique to the client's order Modify all package connection strings to be used by SSIS to point to new databases and file locations. Step 2: Create relational databases Create the staging and data mart relational databases using dynamic SQL and set the database recovery mode to SIMPLE as we do not need the overhead of logging anything Execute SQL scripts to build all database objects (tables, views, functions and stored procedures) in the two databases Step 3: Load staging database Use SSIS to load all data files into the staging database in a parallel operation Load extension files containing name/value pairs. These will provide client-specific attributes in the OLAP cube. Step 4: Load data mart relational database Load the data from staging into the data mart relational database, again in parallel where possible Allocate surrogate keys and use SSIS to perform surrogate key lookup during the load of fact tables Step 5: Load extension tables & attributes Pivot the extension attributes from their native name/value pairs into proper relational tables Add the extension attributes to the views used by OLAP cube Step 6: Deploy & Process OLAP cube Deploy the OLAP database directly to the server using a C# script task in SSIS Modify the connection string used by the OLAP cube to point to the data mart relational database Modify the cube structure to add the extension attributes to both the data source view and the relevant dimensions Remove any standard attributes that not required Process the OLAP cube Step 7: Backup and drop databases Drop staging database as it is no longer required Backup data mart relational and OLAP database and ship these to the client's infrastructure Drop data mart relational and OLAP database from the build server Mark order complete Start processing the next order, ad infinitum. So my future blog posts and my forthcoming session at the SQLBits conference will all focus on some of the more interesting aspects of building OLAP data marts on-the-fly such as handling the load of extension attributes and how to dynamically alter the structure of an OLAP cube using C#.

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  • Cube project doesn't work because of permissions

    - by sms
    I'm doing "Multidimensional Project" with MS SQL Server 2012 (Server Data Tools - Visual Studio 2010 Shell). I can't run (debug) it. If the data source's impersonation information is set to "use the service account", this error occures: Error 2 Internal error: The operation terminated unsuccessfully. 0 0 Error 3 OLE DB error: OLE DB or ODBC error: Login failed for user 'NT Service\MSSQLServerOLAPService'.; 28000. 0 0 Error 4 Errors in the high-level relational engine. A connection could not be made to the data source with the DataSourceID of 'Data Warehouse', Name of 'Data Warehouse'. 0 0 Error 5 Errors in the OLAP storage engine: An error occurred while the dimension, with the ID of 'Items', Name of 'Items' was being processed. 0 0 Error 6 Errors in the OLAP storage engine: An error occurred while the 'Id' attribute of the 'Items' dimension from the 'Warehouse_MultidimensionalProject_Cube' database was being processed. 0 0 Error 7 Server: The current operation was cancelled because another operation in the transaction failed. 0 0 I guessed that this account has no premissions but (1) I coudn't even add this account (it seems that it doesn't exist) and (2) how is that even possible for it to not have built-it poremissions? When I'm setting impersonation to "use the credentials of current user" (which is the owner of the data source, btw.), another error occures: Error 2 Internal error: The operation terminated unsuccessfully. 0 0 Error 3 The datasource, 'Data Warehouse', contains an ImpersonationMode that is not supported for processing operations. 0 0 Error 4 Errors in the high-level relational engine. A connection could not be made to the data source with the DataSourceID of 'Data Warehouse', Name of 'Data Warehouse'. 0 0 Error 5 Errors in the OLAP storage engine: An error occurred while the dimension, with the ID of 'Items', Name of 'Items' was being processed. 0 0 Error 6 Errors in the OLAP storage engine: An error occurred while the 'Id' attribute of the 'Items' dimension from the 'Warehouse_MultidimensionalProject_Cube' database was being processed. 0 0 Error 7 Server: The current operation was cancelled because another operation in the transaction failed. 0 0 Any help?

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  • An OLAP client!

    - by Davide Mauri
    While surfing CodePlex I’ve come across a very interesting tool for all BI Developers who misses a decent OLAP client where to write, run & test MDX queries http://ranetuilibraryolap.codeplex.com/ I’ve not tested it yet, but I’ll surely do this week and I’ll post my impressions ASAP. The first impression, just looking the CodePlex page, is that tool Rocks!!!!! Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • An OLAP client!

    - by Davide Mauri
    While surfing CodePlex I’ve come across a very interesting tool for all BI Developers who misses a decent OLAP client where to write, run & test MDX queries http://ranetuilibraryolap.codeplex.com/ I’ve not tested it yet, but I’ll surely do this week and I’ll post my impressions ASAP. The first impression, just looking the CodePlex page, is that tool Rocks!!!!! Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • morph a sphere to a cube and a a cube to a sphere with GLSL

    - by nkint
    hi i'm getting started with glsl with quartz composer. i have a patch with a particle system in which each particle is mapped into a sphere with a blend value. with blend=0 particles are in random positions, blend=1 particles are in the sphere. the code is here: vec3 sphere(vec2 domain) { vec3 range; range.x = radius * cos(domain.y) * sin(domain.x); range.y = radius * sin(domain.y) * sin(domain.x); range.z = radius * cos(domain.x); return range; } // in main: normal = sphere(p0); * blend + gl_Normal * (1.0 - blend); i'd like the particle to be on a cube if blend=0 i've tried to find but i can't figure out some parametric equation for the cube. mayebe it is not the right way?

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  • Morph a sphere to a cube and a cube to a sphere with GLSL

    - by nkint
    I'm getting started with GLSL with quartz composer. I have a patch with a particle system in which each particle is mapped into a sphere with a blend value. With blend=0 particles are in random positions, blend=1 particles are in the sphere. The code is here: vec3 sphere(vec2 domain) { vec3 range; range.x = radius * cos(domain.y) * sin(domain.x); range.y = radius * sin(domain.y) * sin(domain.x); range.z = radius * cos(domain.x); return range; } // in main: vec2 p0 = gl_Vertex.xy * twopi; vec3 normal = sphere(p0);; vec3 r0 = radius * normal; vec3 vertex = r0; normal = normal * blend + gl_Normal * (1.0 - blend); vertex = vertex * blend + gl_Vertex.xyz * (1.0 - blend); I'd like the particle to be on a cube if blend=0 I've tried to find but I can't figure out some parametric equation for the cube. Maybe it is not the right way?

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  • Crosstab/Cube/Pivot Components for Delphi

    - by Anagoge
    I'm looking for a Delphi VCL crosstab/cube/pivotcube/olap grid component for Delphi 2009, 2010, or XE. I'm willing to sacrifice advanced features to get something open/free (or very cheap if I must) to make it easier to collaborate with any future developers without anyone having to purchase more components than I already use, since this will just be used in one screen. If there isn't anything appropriate out there, I may try to implement something simple on my own. I can live with some fairly basic features: drag and drop to configure dimensions, sort by a column, allow totals/min/max for a column, and (optionally) expand/collapse or drill down to sub-categories. Blazing performance and enterprise scalability are not required, since there should be less than 2000 source rows. There appear to be several decent options in the commercial space (ExpressPivotCube, FastCube, HierCube), but they are all a few hundred dollars. This project already uses existing installations of Excel 2007 and SQL Server 2005/2008, so I might consider leveraging those, though I'd prefer a native Delphi component, if possible. There are also the very old Decision Cube components included in Delphi's Source\xtab directory, but they apparently no longer support unicode compilers (Delphi 2009+), since I got dozens of unicode-related compilation errors while test compiling that source in Delphi XE. Those components also still link to the long-deprecated BDE! Has anyone modified Decision Cube to support unicode/pure-TDataSet? The online tutorials I found were incomplete and silent on the dozens of BDE/unicode compilation errors I see, so I might have to tackle that on my own. Does anyone have suggestions where to start for a free/cheap basic crosstab/pivot grid component?

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  • SSAS Cube reprocessing fails - then succeeds if I try again

    - by EdgarVerona
    So I'm basically brand new to the concept of BI, and I've inherited an existing ETL process that is a two step process: 1) Loads the data into a database that is only used by the cube processing 2) Starts off the SSAS cube processing against said database It seems pretty well isolated, but occasionally (once a week, sometimes twice) it will fail with the following exception: "Errors in the OLAP storage engine: The attribute key cannot be found" Now the interesting thing is that: 1) The dimension having the issue is not usually the same one (i.e. there's no single dimension that consistently has this failure) 2) The source table, when I inspect it, does actually contain the attribute key that it says could not be found And, most interestingly... 3) If I then immediately reprocess the dimensions and cubes manually through SSMS, they reprocess successfully and without incident. In both the aforementioned job and when I reprocess them through SSMS, I am using "ProcessFull", so it should be reprocessing them completely. Has anyone run into such an issue? I'm scratching my head about it... because if it was a genuine data integrity issue, reprocessing the cube again wouldn't fix it. What on earth could be happening? I've been tasked with finding out why this happens, but I can neither reproduce it consistently nor can I point to a data integrity problem as the root cause. Thanks for any input you can provide!

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  • In SQL Server Business Intelligence, why would I create a report model from an OLAP cube?

    - by ngm
    In Business Intelligence Developer Studio, I'm wondering why one would want to create a report model from an OLAP cube. As far as I understand it, OLAP cubes and report models are both business-oriented views of underlying structures (usually relational databases) that may not mean much to a business user. The cube is a multidimensional view in terms of dimensions and measures, and the report model is... well I'm not sure entirely -- is it a more business-oriented, but still essentially relational view? Anyway, in Report Builder I can connect directly to both an OLAP cube or a report model. So I don't see why, if I have an OLAP cube which already provides a business-oriented view of the data suitable for end-users, why I would then convert that to a report model and use that in Report Builder instead. I think I'm obviously missing some fundamental difference between report models and cubes -- any help appreciated!

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  • Moving a Cube from a GUI texture on iOS [on hold]

    - by London2423
    I really hope someone can help me in this since I am working already two days but without any result. What I' am trying to achieve in this instance is to move a GameObject when a GUI Texture is touch on a Iphone. The GameObject to be moved is named Cube. The Cube has a Script named "Left" that supposedly when is "call it " from the GUITexture the Cube should move left. I hope is clear: I want to "activated" the script in the Game Object from the Guitexture. I try to use send message but without any joy as well so I am using GetComponent. This is the script "inside" the GUITexture using Unity and C# //script inside the gameobject cube so it can move left when call it from the GUItexture void Awake() { left = Cube.GetComponent<Left>().enable = true; } void Start() { Cube = GameObject.Find ("Cube"); } void Update () { //loop through all the touches on the screeen for(int i = 0 ; i < Input.touchCount; i++) { //execute this code for current touch (i) on the screen if(this.guiTexture.HitTest(Input.GetTouch(i).position)) { //if current hits our guiTecture, run this code if(Input.GetTouch (i).phase == TouchPhase.Began) //move the cube object Cube.GetComponent<Left> (); } if(Input.GetTouch (i).phase == TouchPhase.Ended) { return; } if(Input.GetTouch(i).phase == TouchPhase.Stationary); //if current finger is stationary run this code { Cube.GetComponent<Left> (); } } } } } This is the script inside the GameObject named "Cube" that is activated from the Gui Texture and when is activated from the GUITexture should allow the cube to move left public class Left : MonoBehaviour { // Use this for initialization void Start () { } // Update is called once per frame void OnMousedown () { transform.position += Vector3.left * Time.deltaTime; } } Before write here I search all documentation, tutorial videos, forums but I still don't understand where is my mistake. May please someone help me Thanks CL

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  • Writing OLAP SQL query

    - by user1859596
    I have a project I am working on that requires the following : create a normalized sample rdbms (5 tables) using Java I entered 1 million rows of data to each table run two OLTP and two OLAP queries on the normalized tables. Denormalized tables. run the same OLTP and OLAP queries on them and compare time. What does OLAP query mean? I've searched the internet and all that I can find is that I have to make a cube, and apply queries on it. How can I write an OLAP query on a RDBMS? I have a sample : tables normalized(orders,product,customer,branch,sales) sales : order_id,product_id,quantity product : product_id,name,description,price,sales_tax customer : customer_id,f_name,l_name,tel_no,addr,nic,city branch : branch_id,name,tel_no,addr,city orders : order_id,customer_id,order_date,branch_id I want to write an OLAP query on the above tables. I am using Oracle Express with SQL Developer.

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  • SSIS: Deploying OLAP cubes using C# script tasks and AMO

    - by DrJohn
    As part of the continuing series on Building dynamic OLAP data marts on-the-fly, this blog entry will focus on how to automate the deployment of OLAP cubes using SQL Server Integration Services (SSIS) and Analysis Services Management Objects (AMO). OLAP cube deployment is usually done using the Analysis Services Deployment Wizard. However, this option was dismissed for a variety of reasons. Firstly, invoking external processes from SSIS is fraught with problems as (a) it is not always possible to ensure SSIS waits for the external program to terminate; (b) we cannot log the outcome properly and (c) it is not always possible to control the server's configuration to ensure the executable works correctly. Another reason for rejecting the Deployment Wizard is that it requires the 'answers' to be written into four XML files. These XML files record the three things we need to change: the name of the server, the name of the OLAP database and the connection string to the data mart. Although it would be reasonably straight forward to change the content of the XML files programmatically, this adds another set of complication and level of obscurity to the overall process. When I first investigated the possibility of using C# to deploy a cube, I was surprised to find that there are no other blog entries about the topic. I can only assume everyone else is happy with the Deployment Wizard! SSIS "forgets" assembly references If you build your script task from scratch, you will have to remember how to overcome one of the major annoyances of working with SSIS script tasks: the forgetful nature of SSIS when it comes to assembly references. Basically, you can go through the process of adding an assembly reference using the Add Reference dialog, but when you close the script window, SSIS "forgets" the assembly reference so the script will not compile. After repeating the operation several times, you will find that SSIS only remembers the assembly reference when you specifically press the Save All icon in the script window. This problem is not unique to the AMO assembly and has certainly been a "feature" since SQL Server 2005, so I am not amazed it is still present in SQL Server 2008 R2! Sample Package So let's take a look at the sample SSIS package I have provided which can be downloaded from here: DeployOlapCubeExample.zip  Below is a screenshot after a successful run. Connection Managers The package has three connection managers: AsDatabaseDefinitionFile is a file connection manager pointing to the .asdatabase file you wish to deploy. Note that this can be found in the bin directory of you OLAP database project once you have clicked the "Build" button in Visual Studio TargetOlapServerCS is an Analysis Services connection manager which identifies both the deployment server and the target database name. SourceDataMart is an OLEDB connection manager pointing to the data mart which is to act as the source of data for your cube. This will be used to replace the connection string found in your .asdatabase file Once you have configured the connection managers, the sample should run and deploy your OLAP database in a few seconds. Of course, in a production environment, these connection managers would be associated with package configurations or set at runtime. When you run the sample, you should see that the script logs its activity to the output screen (see screenshot above). If you configure logging for the package, then these messages will also appear in your SSIS logging. Sample Code Walkthrough Next let's walk through the code. The first step is to parse the connection string provided by the TargetOlapServerCS connection manager and obtain the name of both the target OLAP server and also the name of the OLAP database. Note that the target database does not have to exist to be referenced in an AS connection manager, so I am using this as a convenient way to define both properties. We now connect to the server and check for the existence of the OLAP database. If it exists, we drop the database so we can re-deploy. svr.Connect(olapServerName); if (svr.Connected) { // Drop the OLAP database if it already exists Database db = svr.Databases.FindByName(olapDatabaseName); if (db != null) { db.Drop(); } // rest of script } Next we start building the XMLA command that will actually perform the deployment. Basically this is a small chuck of XML which we need to wrap around the large .asdatabase file generated by the Visual Studio build process. // Start generating the main part of the XMLA command XmlDocument xmlaCommand = new XmlDocument(); xmlaCommand.LoadXml(string.Format("<Batch Transaction='false' xmlns='http://schemas.microsoft.com/analysisservices/2003/engine'><Alter AllowCreate='true' ObjectExpansion='ExpandFull'><Object><DatabaseID>{0}</DatabaseID></Object><ObjectDefinition/></Alter></Batch>", olapDatabaseName));  Next we need to merge two XML files which we can do by simply using setting the InnerXml property of the ObjectDefinition node as follows: // load OLAP Database definition from .asdatabase file identified by connection manager XmlDocument olapCubeDef = new XmlDocument(); olapCubeDef.Load(Dts.Connections["AsDatabaseDefinitionFile"].ConnectionString); // merge the two XML files by obtain a reference to the ObjectDefinition node oaRootNode.InnerXml = olapCubeDef.InnerXml;   One hurdle I had to overcome was removing detritus from the .asdabase file left by the Visual Studio build. Through an iterative process, I found I needed to remove several nodes as they caused the deployment to fail. The XMLA error message read "Cannot set read-only node: CreatedTimestamp" or similar. In comparing the XMLA generated with by the Deployment Wizard with that generated by my code, these read-only nodes were missing, so clearly I just needed to strip them out. This was easily achieved using XPath to find the relevant XML nodes, of which I show one example below: foreach (XmlNode node in rootNode.SelectNodes("//ns1:CreatedTimestamp", nsManager)) { node.ParentNode.RemoveChild(node); } Now we need to change the database name in both the ID and Name nodes using code such as: XmlNode databaseID = xmlaCommand.SelectSingleNode("//ns1:Database/ns1:ID", nsManager); if (databaseID != null) databaseID.InnerText = olapDatabaseName; Finally we need to change the connection string to point at the relevant data mart. Again this is easily achieved using XPath to search for the relevant nodes and then replace the content of the node with the new name or connection string. XmlNode connectionStringNode = xmlaCommand.SelectSingleNode("//ns1:DataSources/ns1:DataSource/ns1:ConnectionString", nsManager); if (connectionStringNode != null) { connectionStringNode.InnerText = Dts.Connections["SourceDataMart"].ConnectionString; } Finally we need to perform the deployment using the Execute XMLA command and check the returned XmlaResultCollection for errors before setting the Dts.TaskResult. XmlaResultCollection oResults = svr.Execute(xmlaCommand.InnerXml);  // check for errors during deployment foreach (Microsoft.AnalysisServices.XmlaResult oResult in oResults) { foreach (Microsoft.AnalysisServices.XmlaMessage oMessage in oResult.Messages) { if ((oMessage.GetType().Name == "XmlaError")) { FireError(oMessage.Description); HadError = true; } } } If you are not familiar with XML programming, all this may all seem a bit daunting, but perceiver as the sample code is pretty short. If you would like the script to process the OLAP database, simply uncomment the lines in the vicinity of Process method. Of course, you can extend the script to perform your own custom processing and to even synchronize the database to a front-end server. Personally, I like to keep the deployment and processing separate as the code can become overly complex for support staff.If you want to know more, come see my session at the forthcoming SQLBits conference.

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  • SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11. The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth. The SPARC T4-4 server operated on an Oracle OLAP cube with a 4 billion row fact table of sales data containing 4 dimensions. This represents as many as 90 quintillion aggregate rows (90 followed by 18 zeros). Performance Landscape Oracle OLAP Perf Version 2 Benchmark 4 Billion Fact Table Rows System Queries/hour Users* Response Time (sec) Average Median SPARC T4-4 430,000 7,300 0.85 0.43 * Users - the supported number of users with a given think time of 60 seconds Configuration Summary and Results Hardware Configuration: SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 1 TB memory Data Storage 1 x Sun Fire X4275 (using COMSTAR) 2 x Sun Storage F5100 Flash Array (each with 80 FMODs) Redo Storage 1 x Sun Fire X4275 (using COMSTAR with 8 HDD) Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option Benchmark Description The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing. The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube consisting of a number of years of sales data with fully pre-computed aggregations. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc. Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix. Key Points and Best Practices Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here. For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law N = (rt + tt) * tp where rt is the average response time, tt is the think time and tp is the measured throughput. Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds. For more information see chapter 3 from the book "Quantitative System Performance" cited below. -- See Also Quantitative System Performance Computer System Analysis Using Queueing Network Models Edward D. Lazowska, John Zahorjan, G. Scott Graham, Kenneth C. Sevcik external local Oracle Database 11g – Oracle OLAP oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, 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 11/2/2012.

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  • How to distribute an offline cube for excel

    - by Mike M
    I have the following scenario. A cube created in SSAS 2008. I can connected to this cube via Excel. I can create an offline cube file. I can connect to this offline cube file. Now, say I want to email this excel file along with the cube file so that another user can view it. I run into the problem that the connection path the offline cube is hard coded into the excel file. Its the same problem this person had. http://stackoverflow.com/questions/1253950/opening-offline-cube-from-another-machine Their solution was to just make sure the other user saved the cube in the same directory structure. I don't love that solution. I also came across this idea: http://www.pcreview.co.uk/forums/thread-948974.php I tried that, it errored out, but I am not an Excel VBA programmer and really have no idea if I even put the code in the right place. So anyway, anyone out there have any ideas about who to do this? If the VBA solution is the best, could someone give me some tips on where to actually put that code?

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  • Reporting tool for OLAP, *not* OLTP!

    - by Stefan Moser
    I'm looking for a control that I can put on top of an already existing OLAP star schema to allow the user to define their own "queries" and generate reports. Right now I have some predefined reports built on top of the cubes, but I'd like to allow the user to define their own criteria based on the cubes that I've created. I've found lots of products that will allow you to treat a transactional table like an OLAP cube, but nothing specifically for pre-existing cubes. EDIT: Let me be clear, I know there are countless reporting tools out there that claim to report on OLAP cubes. The problem is they all assume they are looking at transactional data and try to create their own cubes. I have tables that contain tens, if not hundreds of millions of records. Most tools crash when handling this much data, the others just run incredible slowly. I don't want a tool that is targeting the business people. I want a tool that understands what a star and snowflake schema is. I want to be able to tell it what the fact tables are and what the dimension tables are, and then creates a UI on top of them. This is an easier problem to solve for the tool vendor because I am spoon feeding them the cubes. I want to rely on the fact that cubes are a standardized pattern and I want a tool that takes advantage of this fact. I want a tool that targets developers and starts with the assumption that I actually know how to manage my data, it just needs to build pretty reports for me and not crumble under the weight of my data.

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  • SSAS OLAP MDX and relationships

    - by Sonic Soul
    I new to OLAP, and still not sure how to create a relationship between 2 or more entities. I am basing my cube on views. For simplicity sake let's call them like this: viewParent (ParentID PK) viewChild (ChildID PK, ParentID FK) these views have more fields, but they're not important for this question. in my data source, i defined a relationship between viewParent and viewChild using ParentID for the link. As for measures, i was forced to create separate measures for Parent and Child. in my MDX query however, the relationship does not seem to be enforced. If i select record count for parent, child, and add some filters for the parent, the child count is not reflecting it.. SELECT { [Measures].[ParentCount],[Measures].[ChildCount] } ON COLUMNS FROM [Cube] WHERE { ( {[Time].[Month].&[2011-06-01T00:00:00]} ,{[SomeDimension].&[Foo]} ) } the selected ParentCount is correct, but ChildCount is not affected by any of the filters (because they are parent filters). However, since i defined a relationship, how can i take advantage of that to filter children by parent filter?

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  • OLAP Web Visualization and Reporting Recommendations

    - by Gok Demir
    I am preparing an offer for a customer. They proide weekly data to different organizations. There is huge amount data suits OLAP that needed to be visualized with charts and pivot tables on web and custom reports will be built by non-it persons (an easy gui). They will enter a date range, location which data columns to be included and generate report and optionally export the data to Excel. They currently prepare reports with MS Excel with Pivot Tables and but they need a better online tool now to show data to their customers. Tables are huge and need of drill-down functionality. My current knowledge Spring, Flex, MySql, Linux. I have some knowledge of PostgreSQL and MSSQL and Windows. What is the easiest way of doing this project. Do you think that SSRP (haven't tried yet) and ASP.NET better suits for this kind of job. Actually I prefer open source solutions. Flex have OLAP Data Grid control which do aggregation on client side. JasperServer seems promising but it seems I need enterprise version (multiple organizations and ad hoc queries). What about Modrian + Flex + PostgreSQL solution? Any previous experience will be appreciated. Yes I am confused with options.

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  • How to create offline OLAP cube in C#?

    - by jimmyjoe
    I have a problem with creating an offline OLAP cube from C# using following code: using (var connection = new OleDbConnection()) { connection.ConnectionString = "Provider=MSOLAP; Initial Catalog=[OCWCube]; Data Source=C:\\temp\\test.cub; CreateCube=CREATE CUBE [OCWCube] ( DIMENSION [NAME], LEVEL [Wszystkie] TYPE ALL, LEVEL [NAME], MEASURE [Liczba DESCRIPTIO] FUNCTION COUNT ); InsertInto=INSERT INTO OCWCube([Liczba DESCRIPTIO], [NAME].[NAME]) OPTIONS ATTEMPT_ANALYSIS SELECT Planners.DESCRIPTIO, Planners.NAME FROM Planners Planners; Source_DSN=\"CollatingSequence=ASCII;DefaultDir=c:\\temp;Deleted=1;Driver={Microsoft dBase Driver (*.dbf)};DriverId=277;FIL=dBase IV;MaxBufferSize=2048;MaxScanRows=8;PageTimeout=600;SafeTransactions=0;Statistics=0;Threads=3;UserCommitSync=Yes;\";Mode=Write;UseExistingFile=True"; try { connection.Open(); } catch (OleDbException e) { Console.WriteLine(e); } } I keep on getting the following exception: "Multiple-step operation generated errors. Check each OLE database status value. No action was taken." I took the connection string literally from OQY file generated by Excel. I had to add "Mode=Write" section, otherwise I was getting another exception ("file may be in use"). What is wrong with the connection string? How to diagnose the error? Somebody please guide me...

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  • Visual Studio hangs when deploying a cube

    - by Richie
    Hello All, I'm having an issue with an Analysis Services project in Visual Studio 2005. My project always builds but only occasionally deploys. No errors are reported and VS just hangs. This is my first Analysis Services project so I am hoping that there is something obvious that I am just missing. Here is the situation I have a cube that I have successfully deployed. I then make some change, e.g., adding a hierarchy to a dimension. When I try to deploy again VS hangs. I have to restart Analysis Services to regain control of VS so I can shut it down. I restart everything sometimes once, sometimes twice or more before the project will eventually deploy. This happens with any change I make there seems to be no pattern to this behaviour. Sometimes I have to delete the cube from Analysis Services before restarting everything to get a successful deploy. Also I have successfully deployed the cube, and then subsequently successfully reprocessed a dimension then when I open a query window in SQL Server Management Studio it says that it can find any cubes. As a test I have deployed a cube successfully. I have then deleted it in Analysis Services and attempted to redeploy it, without making any changes to the cube, only to have the same behaviour mentioned above. VS just hangs with no reason so I have no idea where to start hunting down the problem. It is taking 15-20 minutes to make a change as simple as setting the NameColumn of a dimension attribute. As you can imagine this is taking hours of my time so I would greatly appreciate any assistance anyone can give me.

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  • New release of &quot;OLAP PivotTable Extensions&quot;

    - by Luca Zavarella
    For those who are not familiar with this add-in, the OLAP PivotTable Extensions add features of interest to Excel 2007 or 2010 PivotTables pointing to an OLAP cube in Analysis Services. One of these features I like very much, is to know the MDX query code associated with the pivot used at that time in Excel: You can find all the details here: http://olappivottableextend.codeplex.com/ It was recently released a new version of the add-in (version 0.7.4), which does not introduce any new features, but fixes a significant bug: Release 0.7.4 now properly handles languages but introduces no new features. International users who run a different Windows language than their Excel UI language may be receiving an error message when they double click a cell and perform drillthrough which reads: "XML for Analysis parser: The LocaleIdentifier property is not overwritable and cannot be assigned a new value". This error was caused by OLAP PivotTable Extensions in some situations, but release 0.7.4 fixes this problem. Enjoy!

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  • MS Analysis Services OLAP API for Python

    - by Kaloyan Todorov
    I am looking for a way to connect to a MS Analysis Services OLAP cube, run MDX queries, and pull the results into Python. In other words, exactly what Excel does. Is there a solution in Python that would let me do that? Someone with a similar question going pointed to Django's ORM. As much as I like the framework, this is not what I am looking for. I am also not looking for a way to pull rows and aggregate them -- that's what Analysis Services is for in the first place. Ideas? Thanks.

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