I've got a cube set up with a number of partitions - one for each year of data in my fact table. I'd like to process partitions on an individual basis. Is this possible? If so, how do I go about this?
Thanks
The easiest way to process a individual partition manually is the SQL Server Management Studio, where you can simply right-click any partition and select "Process". I guess this is not what you want.
How do you process your cube in the first place? If you use SSIS for instance, you could use a script transformation to generate an XMLA script that processes the individual partition. In the simplest form the script would only take an existing XMLA and replace the name of the partition with the correct value. We have done this in a project and it works very well. The generated script can the be executed with the SSIS XMLA task as well.
If you explain your requirements in more detail maybe I can help you better.
Nicolas
you can also do it from BIDS, go to the Partitions tab of your cube, locate the partition you want to process, right click on it and you'll see an option
Related
I have wondering if there is an option to run scheduled report in BigQuery manually. I've got report in Google Data Studio that source is BigQuery table which is scheduled from BigQuery view every hour. But sometimes when I am working on query and would like to try if the changes that I have made are correct, but I have to wait that 1 hour to check it out. I read that backfill can do it but if I set start date and end date as today I can't go further. How can I solve this problem?
If you want realtime reports, just create a View with your query and create a Report in Data Studio that consumes this View.
Another approach would be to put the custom query directly on Data Studio. This way you can change the query in Data Studio and it will reprocess your data everytime you refresh the report.
Obviously, this is not the most cost-effective or efficient solution, but it is a good workaround if you just want to test something while developing.
For a production scenario (with lots of concurrent users), if you're able to pre-process your data as you already do, your reports will be faster and they'll probably consume less Big Query resources.
I have 5 dimensions and a fact table in my DWH. Build SSAS Tabular Model cube and created Partitions for my fact table. Say 2015, 2016 and 2017.Then, deploy my cube in my server. And, I am creating a job to refresh my data for the partition 2017 alone. Not the entire data.
How to achieve this by scheduling a job to refresh all my dimensions and 2017 partition alone?
Thanks in advance. Please anyone.
If you want to process a specific partition you can do it with a xmla script.
How to retrieve it?
From Management studio, Right click on your fact and choose Partitions
Choose your partition (in my example I only have one) and click on the process icon.
Choose your partition
Select your process mode (In your case, process full)
Click and generate your XMLA code
Your XMLA Code:
Now you can create your job:
Otherwise you can create one SSIS Package and use an Analysis Services Execute DDL Task
I did some test and screenshot, but I saw that microsoft did already a nice explanation.
https://learn.microsoft.com/en-us/sql/analysis-services/instances/schedule-ssas-administrative-tasks-with-sql-server-agent
I hope that I helped you.
Regards,
Arnaud
I am trying to find out an ideal way to automatically copy new records from one database to another. the databases have different structure! I achieved it by writing VBS scripts which copy the data from one to another and triggered the scripts from another application which passes arguments to the script. But I faced issues at points where there were more than 100 triggers. i.e. 100wscript processes trying to access the database and they couldn't complete the task.
I want to find out a simpler solution inside SQL, I read about setting triggers, Stored procedure and running them from SQL agent, replication etc. The requirement is that I have to copy records to another database periodically or when there is a new record into another database.
Which method will suit me the best?
You can use CDC to do this activity. Create a SSIS package using CDC and run that package periodically through SQL Server Agent Job. CDC will store all the changes of that table and will do all those changes to the destination table when you run the package. Please follow the below link.
http://sqlmag.com/sql-server-integration-services/combining-cdc-and-ssis-incremental-data-loads
The word periodically in your question suggests that you should go for Jobs. You can schedule jobs in SQL Server using Sql Server agent and assign a period. The job will run your script as per assigned frequency.
PrabirS: Change Data Capture
This is a good option. Because it uses the truncation-log to create something similar to the Command Query Segregation Pattern (CQRS).
Alok Gupta: A SQL Job that runs in the SQL Agent
This too is a good option, given that you have something like a modified date thus you can filter the altered data. You can create a Stored Procedure and let it run regularly in the SQL Agent.
A third option could be triggers (the change will happen in the same transaction).
This option is useful for auditing and logging. But you should definitely avoid writing business logic in triggers, as triggers are more or less hidden and occur without directly calling them (similar to CDC actually). I have actually created a trigger about half a year ago that captured the data and inserted it somewhere else in xml-format as the columns in the original table could change over time (multiple projects using the same database(s)).
-Edit-
By the way, your question more or less suggest a lack of a clear design pattern and that the used technique is not the main problem. You could try to read how an ETL-layer is build, or try to implement a "separations of concerns". Note; it is hard to tell if this is the case, but given how you formulated your question, an unclear design is something that pops up in my mind as possible problem.
I wan't sure how to word this question so I'll try and explain. I have a third-party database on SQL Server 2005. I have another SQL Server 2008, which I want to "publish" some of the data in the third-party database too. This database I shall then use as the back-end for a portal and reporting services - it shall be the data warehouse.
On the destination server I want store the data in different table structures to that in the third-party db. Some tables I want to denormalize and there are lots of columns that aren't necessary. I'll also need to add additional fields to some of the tables which I'll need to update based on data stored in the same rows. For example, there are varchar fields that contain info I'll want to populate other columns with. All of this should cleanse the data and make it easier to report on.
I can write the query(s) to get all the info I want in a particular destination table. However, I want to be able to keep it up-to-date with the source on the other server. It doesn't have to be updated immediately (although that would be good) but I'd like for it be updated perhaps every 10 minutes. There are 100's of thousands of rows of data but the changes to the data and addition of new rows etc. isn't huge.
I've had a look around but I'm still not sure the best way to achieve this. As far as I can tell replication won't do what I need. I could manually write the t-sql to do the updates perhaps using the Merge statement and then schedule it as a job with sql server agent. I've also been having a look at SSIS and that looks to be geared at the ETL kind of thing.
I'm just not sure what to use to achieve this and I was hoping to get some advice on how one should go about doing this kind-of thing? Any suggestions would be greatly appreciated.
For that tables whose schemas/realtions are not changing, I would still strongly recommend Replication.
For the tables whose data and/or relations are changing significantly, then I would recommend that you develop a Service Broker implementation to handle that. The hi-level approach with service broker (SB) is:
Table-->Trigger-->SB.Service >====> SB.Queue-->StoredProc(activated)-->Table(s)
I would not recommend SSIS for this, unless you wanted to go to something like dialy exports/imports. It's fine for that kind of thing, but IMHO far too kludgey and cumbersome for either continuous or short-period incremental data distribution.
Nick, I have gone the SSIS route myself. I have jobs that run every 15 minutes that are based in SSIS and do the exact thing you are trying to do. We have a huge relational database and then we wanted to do complicated reporting on top of it using a product called Tableau. We quickly discovered that our relational model wasn't really so hot for that so I built a cube over it with SSAS and that cube is updated and processed every 15 minutes.
Yes SSIS does give the aura of being mainly for straight ETL jobs but I have found that it can be used for simple quick jobs like this as well.
I think, staging and partitioning will be too much for your case. I am implementing the same thing in SSIS now but with a frequency of 1 hour as I need to give some time for support activities. I am sure that using SSIS is a good way of doing it.
During the design, I had thought of another way to achieve custom replication, by customizing the Change Data Capture (CDC) process. This way you can get near real time replication, but is a tricky thing.
Is there an automatic way in SQL Server 2005 to create a database from several tables in another database? I need to work on a project and I only need a few tables to run it locally, and I don't want to make a backup of a 50 gig DB.
UPDATE
I tried the Tasks -> Export Data in Management studio, and while it created a new sub database with the tables I wanted, it did not copy over any table metadata, ie...no PK/FK constraints and no Identity data (Even with Preserve Identity checked).
I obviously need these for it to work, so I'm open to other suggestions. I'll try that database publishing tool.
I don't have Integration Services available, and the two SQL Servers cannot directly connect to each other, so those are out.
Update of the Update
The Database Publishing Tool worked, the SQL it generated was slightly buggy, so a little hand editing was needed (Tried to reference nonexistent triggers), but once I did that I was good to go.
You can use the Database Publishing Wizard for this. It will let you select a set of tables with or without the data and export it into a .sql script file that you can then run against your other db to recreate the tables and/or the data.
Create your new database first. Then right-click on it and go to the Tasks sub-menu in the context menu. You should have some kind of import/export functionality in there. I can't remember exactly since I'm not at work right now! :)
From there, you will get to choose your origin and destination data sources and which tables you want to transfer. When you select your tables, click on the advanced (or options) button and select the check box called "preserve primary keys". Otherwise, new primary key values will be created for you.
I know this method can hardly be called automatic but why don't you use a few simple SELECT INTO statements?
Because I'd have to reconstruct the schema, constraints and indexes first. Thats the part I want to automate...Getting the data is the easy part.
Thanks for your suggestions everyone, looks like this is easy.
Integration Services can help accomplish this task. This tool provids advanced data transformation capabilities so you will be able to get exact subset of data that you need from large database.
Assuming that such data is needed for testing/debugging you may consider applying Row Sampling to reduce amount of data exported.
Create new database
Right click on it,
Tasks -> Import Data
Follow instructions