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• Parallelize incremental processing in Tabular #ssas #tabular

  - by Marco Russo (SQLBI)

  I recently came in a problem trying to improve the parallelism of Tabular processing. As you know, multiple tables can be processed in parallel, whereas the processing of several partitions within the same table cannot be parallelized. When you perform an incremental update by adding only new rows to existing table, what you really do is adding rows to a partition, so adding rows to many tables means adding rows to several partitions. The particular condition you have in this case is that every partition in which you add rows belongs to a different table. Adding rows implies using the ProcessAdd command; its QueryBinding parameter specifies a SQL syntax to read new rows, otherwise the original query specified for the partition will be used, and it could generate duplicated data if you don’t have a dynamic behavior on the SQL side. If you create the required XMLA code manually, you will find that the QueryBinding node that should be part of the ProcessAdd command has to be moved out from ProcessAdd in case you are using a Batch command with more than one Process command (which is the reason why you want to use a single batch: run multiple process operations in parallel!). If you use AMO (Analysis Management Objects) you will find that this combination is not supported, even if you don’t have a syntax error compiling the code, but you might obtain this error at execution time: The syntax for the 'Process' command is incorrect. The 'Bindings' keyword cannot appear under a 'Process' command if the 'Process' command is a part of a 'Batch' command and there are more than one 'Process' commands in the 'Batch' or the 'Batch' command contains any out of line related information. In this case, the 'Bindings' keyword should be a part of the 'Batch' command only. If this is happening to you, the best solution I’ve found is manipulating the XMLA code generated by AMO moving the Binding nodes in the right place. A more detailed description of the issue and the code required to send a correct XMLA batch to Analysis Services is available in my article Parallelize ProcessAdd with AMO. By the way, the same technique (and code) can be used also if you have the same problem in a Multidimensional model.

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• Parameterize Charts using Excel Slicers in PowerPivot

  - by Marco Russo (SQLBI)

  One new nice feature of Excel 2010 is the Slicer. Usually, slicers are used to filter data in a PivotTable. But they might be also useful to parameterize an algorithm or a chart! We discussed this technique in our book , but Alberto Ferrari wrote a post that shows how to use this technique to allow the user to select two stocks that should be compared in an Excel Chart – as you might imagine, this will work also when you will publish the workbook on SharePoint! This is the result: Nice to see that...(read more)

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• Understanding #DAX Query Plans for #powerpivot and #tabular

  - by Marco Russo (SQLBI)

  Alberto Ferrari wrote a very interesting white paper about DAX query plans. We published it on a page where we'll gather articles and tools about DAX query plans: http://www.sqlbi.com/topics/query-plans/I reviewed the paper and this is the result of many months of study - we know that we just scratched the surface of this topic, also because we still don't have enough information about internal behavior of many of the operators contained in a query plan. However, by reading the paper you will start reading a query plan and you will understand how it works the optimization found by Chris Webb one month ago to the events-in-progress scenario. The white paper also contains a more optimized query (10 time faster), even if the performance depends on data distribution and the best choice really depends on the data you have. Now you should be curious enough to read the paper until the end, because the more optimized query is the last example in the paper!

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• Strange date relationships with #PowerPivot

  - by Marco Russo (SQLBI)

  A reader of my PowerPivot book highlighted a strange behavior of the relationship between a datetime column and a Calendar table. Long story short: it seems that PowerPivot automatically round the date to the “neareast day”, but instead of simply removing the time (truncating the decimal part of the decimal number internally used to represent a datetime value) a rounding function seems used, moving the date to the next day if the time part contain a PM time. As you can imagine, this becomes particularly...(read more)

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• Optimize Many-to-Many with SUMMARIZE and Other Techniques

  - by Marco Russo (SQLBI)

  We are still in the early days of DAX and even if I have been using it since 2 years ago, there is still a lot to learn on that. One of the topics that historically interests me (and many of the readers here, probably) is the many-to-many relationships between dimensions in a dimensional data model. When I and Alberto wrote the The Many to Many Revolution 2.0 we discovered the SUMMARIZE based pattern very late in the whitepaper writing. It is very important for performance optimization and it should be always used. In the last month, Gerhard Brueckl also presented an approach based on cross table filtering behavior that simplify the syntax involved, even if it’s harder to explain how it works internally. I published a short article titled Optimize Many-to-Many Calculation in DAX with SUMMARIZE and Cross Table Filtering on SQLBI website just to provide a quick reference to the three patterns available. A further study is still required to compare performance between SUMMARIZE and Cross Table Filtering patterns. Up to now, I haven’t observed big differences between them, even if their execution plans might be not identical and this suggest me that depending on other conditions you might favor one over the other.

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• Meet @marcorus and @ferrarialberto at TechEd Europe 2012 #tee2012

  - by Marco Russo (SQLBI)

  I and Alberto are in Amsterdam this week at TechEd Europe 2012. If you are here at the conference, you can meet us here: Wed, Jun 27 10:15 AM - 11:30 AM – Room G106 DBI319 - BISM: Multidimensional vs. Tabular Wed, Jun 27 02:15 PM – 02:30 PM – Microsoft Press Booth in the TechExpo area PowerPivot for Excel 2010 Book Signing Thu, Jun 28 8:30 AM - 9:45 AM – Room E107 Many-to-Many Relationships in BISM Tabular Fri, Jun 29 1:00 PM - 2:45 PM – Breakthrough Insight at Microsoft SQL Server Booth – TechExpo area Staff and Q&A We’ll try to visit the Microsoft Booth very often and we’ll be in the area Breakthrough Insight of SQL Server zone (see the picture to identify it). And don’t miss the PowerPivot for Excel 2010 book signing event:

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• Meet @marcorus and @ferrarialberto at TechEd Europe 2012 #tee2012

  - by Marco Russo (SQLBI)

  I and Alberto are in Amsterdam this week at TechEd Europe 2012. If you are here at the conference, you can meet us here: Wed, Jun 27 10:15 AM - 11:30 AM – Room G106 DBI319 - BISM: Multidimensional vs. Tabular Wed, Jun 27 02:15 PM – 02:30 PM – Microsoft Press Booth in the TechExpo area PowerPivot for Excel 2010 Book Signing Thu, Jun 28 8:30 AM - 9:45 AM – Room E107 Many-to-Many Relationships in BISM Tabular Fri, Jun 29 1:00 PM - 2:45 PM – Breakthrough Insight at Microsoft SQL Server Booth – TechExpo area Staff and Q&A We’ll try to visit the Microsoft Booth very often and we’ll be in the area Breakthrough Insight of SQL Server zone (see the picture to identify it). And don’t miss the PowerPivot for Excel 2010 book signing event:

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• Investigating on xVelocity (VertiPaq) column size

  - by Marco Russo (SQLBI)

    In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

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• Slowly Changing Dimensions handling in PowerPivot (and BISM?)

  - by Marco Russo (SQLBI)

  During the PowerPivot Workshop in London we received many interesting questions and Alberto had the inspiration to write this nice post about Slowly Changing Dimensions handling in PowerPivot. It is interesting the consideration about SCD Type I attributes in a SCD Type II dimension – you can probably generate them in a more dynamic way in PowerPivot (thanks to Vertipaq and DAX) instead of relying on a relational table containing all the data you need, which usually requires a more complex ETL process....(read more)

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• Thinking in DAX (#powerpivot and #bism)

  - by Marco Russo (SQLBI)

  Last week Alberto published an interesting post about Counting Products in the Current Status with PowerPivot . Starting from a question raised from a reader, Alberto described how to solve a common issue (let me know the “current status” of each item at a given point in time starting from a transactions table) by using a single DAX formula. I suggest you to read his post to understand the technical details of that. What is inspiring of this example is that we can look at Vertipaq and DAX from several...(read more)

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• Power Query in Modern Corporate BI–Copenhagen, June 3, 2014–#powerquery

  - by Marco Russo (SQLBI)

  I will be in Copenhagen to deliver the SSAS Tabular Workshop on June 2-4, 2014 (few seats still available, but hurry up!). In the same week I will be a speaker in an evening community event, MsBIP møde nr. 21, delivering the Power Query in Modern Corporate BI session that I also presented at TechEd North America 2014 last week. It’s not just a session about Power Query, there is a broader scope related to Corporate BI vs. Self-Service BI, which could be open to many consideration. I think that the two worlds can (and should) collaborate, instead of fighting against each other, especially when there is an existing investment in Corporate BI. I hope to meet many of you there!

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• PowerPivot Workshop in Frankfurt (and London early-bird expiring soon) #ppws

  - by Marco Russo (SQLBI)

  One week ago I described the PowerPivot Workshop Roadshow that we are planning in several European countries. The news today is that the Workshop will be in Frankfurt (Germany) on February 21-22, 2011 ! The registrations are open on www.powerpivotworkshop.com web site. The early-bird price for Frankfurt will expire on February 4, 2011. And if you are willing to attend the London date on Febrary 7-8, remember that early-bird price for London is going to expire on Monday (January 17) ! Save your money...(read more)

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• ALL, ALLEXCEPT and VALUES in DAX

  - by Marco Russo (SQLBI)

  When you use CALCULATE in DAX you are creating a new filter context for the calculation, based on the existing one. There are a few functions that are used to clear or preserve a column filter. These functions are: ALL – it can be used with one or more columns from a table, or with the name of a table. It returns all the values from the column(s) or all the rows from the table, ignoring any existing filter context. In other words, ALL clear an existing filter context on columns or table. We can use...(read more)

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• The updated Survey pattern for Power Pivot and Tabular #powerpivot #tabular #ssas #dax

  - by Marco Russo (SQLBI)

  One of the first models I created for the many-to-many revolution white paper was the Survey one. At the time, it was in Analysis Services Multidimensional, and then we implemented it in Analysis Services Tabular and in Power Pivot, using the DAX language. I recently reviewed the data model and published it in the Survey article on DAX Patterns site. The Survey pattern is the foundation for others, such as the Basket Analysis, and it is widely used in many different business scenario. I was particularly happy to know it has been using to perform data analysis for cancer research! In this article I did some maintenance on the DAX formulas, checking that the proper error handling is part of the formulas, and highlighting some differences in slicers behavior between Excel 2010 and Excel 2013, which could be particularly important for the Survey scenario. As usual, we provide sample workbooks for both Excel 2010 and Excel 2013, and we use DAX Formatter to make the DAX code easier to read. Any feedback will be appreciated!

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• Stock Analysis and Moving Average with PowerPivot

  - by Marco Russo (SQLBI)

  One week ago Alberto Ferrari wrote a post about how to do working days calculation in PowerPivot . You might think this is necessary only for accounting department or something like that… but in reality the same techniques are really useful to implement calculations that might be useful when you want to implement some stock analysis using PowerPivot and Excel! As you might know, in PowerPivot it is important having a Dates table containing all the days, without exceptions. But when you manage stock...(read more)

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• Investigating on xVelocity (VertiPaq) column size

  - by Marco Russo (SQLBI)

    In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

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• Speaking at PASS 2012 Summit in Seattle #sqlpass

  - by Marco Russo (SQLBI)

  I will deliver two sessions at the next PASS Summit 2012: one is title Inside DAX Query Plans and the other is Near Real-Time Analytics with xVelocity (without DirectQuery).These will be two sessions that require a lot of preparation and even if I have already much to say, I still have a long work to do this summer in order to go deeper in several details that I want to investigate for completing these sessions.I already look forward to come back in Seattle!In the meantime, you have to study SSAS Tabular and if you want to get a real jumpstart why not attending one of the next SSAS Tabular Workshop Online? We are working on more dates for this fall, but there are a few dates already scheduled.And, last but not least, the early Rough Cuts edition of our upcoming SSAS Tabular book is finally available here (really near to the final print)!

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• PowerPivot FILTER condition optimizations

  - by Marco Russo (SQLBI)

  In the comments of a recent post from Alberto Ferrari there was an interesting note about different performance related to the order of conditions in a FILTER call. I investigated about that and Jeffrey Wang has been so nice to give me some info about actual implementation that I can share on a blog post. First of all, an important disclaimer: PowerPivot is intended to make life easier, not requiring the user to think how to write the order of elements in a formula just to get better performance....(read more)

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• Speaking at PASS 2012 Summit in Seattle #sqlpass

  - by Marco Russo (SQLBI)

  I will deliver two sessions at the next PASS Summit 2012: one is title Inside DAX Query Plans and the other is Near Real-Time Analytics with xVelocity (without DirectQuery).These will be two sessions that require a lot of preparation and even if I have already much to say, I still have a long work to do this summer in order to go deeper in several details that I want to investigate for completing these sessions.I already look forward to come back in Seattle!In the meantime, you have to study SSAS Tabular and if you want to get a real jumpstart why not attending one of the next SSAS Tabular Workshop Online? We are working on more dates for this fall, but there are a few dates already scheduled.And, last but not least, the early Rough Cuts edition of our upcoming SSAS Tabular book is finally available here (really near to the final print)!

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• Parent-child hierarchies and unary operators in PowerPivot

  - by Marco Russo (SQLBI)

  Alberto wrote an excellent post describing how to implement the Unary Operator feature (which is present in Analysis Services) in PowerPivot (there was a previous post about parent-child hierarchies, too). I have to say that the solution is not so easy to implement as in Analysis Services, but it just works and, from a practical point of view, it is not so difficult to implement if you understand how it works and accept its limitations (only sum and subtractions are supported). I think that many...(read more)

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• TechEd North America 2012–Day 3 #msTechEd #teched

  - by Marco Russo (SQLBI)

  Yesterday I spent the longest day at this TechEd: we talked with many people at Community Night until 9pm and I have to say that just a few months after Analysis Services 2012 has been released, there are many people already using it. And the adoption of PowerPivot is starting to be quite large. Many new ideas and challenging coming from several different real world scenarios. I was tired but really happy. Alberto presented his Many-to-Many Relationships in BISM Tabular session that was in the same time slot of the BI Power Hour. For this reason, very few people attended Alberto’s session so I think many will watch the recorded session (it should be available within a few days). So what about today? I’ll spend some time at Technical Learning Center area (full schedule here) but the most important event today will be the Querying multi-billion rows with many to many relationships in SSAS Tabular (xVelocity) at the Private Cloud, Public Cloud and Data Platform Theater in the Technical Learning Center area (next to the SQL Server 2012 zone).  Why you should attend? Mainly because you will see live demo over 4 billion rows table with many-to-many relationships involved in complex queries. But for those of you that think this is not enough to attend a 15 minute funny session, well, we’ll give away some 8GB USB Memory Keys to those of you that will guess exact response time of queries before execution. Convinced? Join us at 11:15am and don’t be late, the session will finish at 11:30am! After that, we’ll run a book signing session at the Bookstore at 12:30pm and I will be in the Technical Learning Center area at 3:00pm until 5:00pm. See you there!

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• Community Events in Köln (October) and Copenhagen November #ssas #tabular #powerpivot

  - by Marco Russo (SQLBI)

  Short update about community events in Europe where I will speak.On October 11 I will present DAX in Action in Köln - all details in the PASS local chapter here: http://www.sqlpass.de/Regionen/Deutschland/K%C3%B6lnBonnD%C3%BCsseldorf.aspxI will be speaking at a community event in Copenhagen on November 21, 2012. The session will be Excel 2013 PowerPivot in Action and details about time and location are available here: http://msbip.dk/events/30/msbip-mode-nr-9/I will be in Köln and Copenhagen to teach the SSAS Tabular Workshop. The workshop in Köln is the first in Germany and I look forward to meet new BI developers there.Copenhagen is the second edition after another we delivered this spring. It is a convenient location also for people coming from Malmoe and Göteborg in Sweden. Last event in Copenhagen were conflicting with a large event in Sweden, maybe this time I'll meet more people coming from the other side of the Øresund Bridge!Many other dates and location are available on the SSAS Tabular Workshop website.

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• Parameterize Charts using Excel Slicers in PowerPivot

  - by Marco Russo (SQLBI)

  One new nice feature of Excel 2010 is the Slicer. Usually, slicers are used to filter data in a PivotTable. But they might be also useful to parameterize an algorithm or a chart! We discussed this technique in our book , but Alberto Ferrari wrote a post that shows how to use this technique to allow the user to select two stocks that should be compared in an Excel Chart – as you might imagine, this will work also when you will publish the workbook on SharePoint! This is the result: Nice to see that...(read more)

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• TechEd North America 2012-Day 4 #msTechEd #teched

  - by Marco Russo (SQLBI)

  I hadn’t time yesterday to write a blog post before of the beginning of the day and I recover now that I’m already back to Europe. I spent many hours at the Microsoft booth meeting people who asked questions about Tabular, Power View and PowerPivot. I have to say that I’m really glad so many people started using PowerPivot and of the large interest around Tabular. During my BISM: Multidimensional vs. Tabular I’ve been helped by Alberto during the demo (we joked about he was the demo monkey) and the feedback received are good. I tried to compare the strength and weakness of the two modeling options without spending time describing the area in which they are similar. During the days before I had many discussions about scenarios based on snapshots and I added a few slides to the presentation in order to cover this area that I thought was marginal but seems to be a very common one. To know more, watch the presentation when it will be available or wait for some article I’ll write in the future describing these patterns. In less than 10 days, I’ll be at TechEd Europe and I’m really looking forward to meet other Tabular developers and PowerPivot users there!

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• BonaVista Dimensions used as a report service

  - by Marco Russo (SQLBI)

  Recently I have seen a long demo of BonaVista Dimensions . It is a product that is able to create reports and, most important dashboards. You can use it also without SQL Server and Analysis Services, just by importing data in a local cube file that you can model using its own simple to use user interface. But what is interesting to me (in this post) is the capability to connect to a SSAS cube. It is somewhat similar to XLCubed and in reality these two products have something in common, because both...(read more)

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