I cannot find a way to calculate the median for multiple columns of data presented in a single report.
I've tried to do it directly in the SQL Server code with PERCENTILE_CONT but there are compatibility level issues (level 100 though I use SQL Server 2017).
My preferred method was to do it through Custom Code following the instructions in:
mean, median, mode in SQL Server Reporting Services
which works to calculate the ONE median in the report, not multiple.
Does anyone have an idea?
Related
We're using Tableau 10.5.6. I used a reporting tool years ago called Oracle Sales Analyzer. In that tool you could get to the queries generated by the reports and graphs you created through back-end catalogs using their command line.
There you could rewrite the query to be more efficient by fine-tuning the code if you needed. It was a very cool feature of that reporting tool for geeks like me who like to dive into the back end of the product and tune it at a very low level.
My question is, does Tableau have any of this type of facility? Is there a way to get to the queries that get stored once you create a report or a graph. Also is there command line where you can access these catalogs if they exist? Otherwise are these queries just stored in ASCII flat files that can be accessed by a user.
Thanks!
There are two ways that Tableau will query a database.
Option 1: Custom SQL
In your data source, you paste in the sql you have written and Tableau will pass that query through to the database. This gives you complete control over the sql, including adding any indexing hints you may want. See https://onlinehelp.tableau.com/current/pro/desktop/en-us/customsql.html
Option 2: Use the Tableau data source designer
This is what many people do. Here, you visually design your data source with the joins. Tableau translates that design into what the Hyper engine considers to be the most effective way to run the query. Sometimes, Hyper translates that into a regular sql statement. Sometimes it does some additional things to help boost performance, like breaking it up into different queries. A lot depends on the db engine you are connecting to. There is no "sql" stored in a flat file for this. Tableau just translates your design at run-time. The Hyper engine does a good job with fine-tuning, assuming you have an efficient database design with proper indexing and current table statistics.
There is a way to see the sql from option 2 at run-time using Performance Recording. Performance Recording keeps track of each step of the visualization process and will spit out the sql statement(s) that Tableau ran to generate your dataset. The sql is not stored in the twb file though, it's a run-time analysis.
We have developed a model in Tabular Object Model(TOM), <= 3.5 GB in size., and built few Tableau Dashboard(s) on top of this model.
Each dashboard is built by dragging multiple sheets into one dashboard. All the sheets (dragged in one dashboard) fetch data from one fact table (of course it has relationships with Date and other related dimensions) in TOM.
Now, when we interact with Tableau dashboard, we see a performance degradation. When we checked the SQL profiler, Tableau is generating a huge query for almost every interaction that we have with the dashboard.
We checked the huge query and observed that it includes the DAX/query for almost all the measures in fact tables, irrespective of whether the fact table is used in the said dashboard or not.
We have verified the filter settings in the dashboard, the settings are applicable only for the sheets dragged in our dashboard, so there is no question of visualizations getting changed in other dashboards.
Ironically, we still see that Tableau is creating a huge query and incorporating all the DAX/queries and this results into performance impact.
Is there any way we can restrict this behavior?
In case anyone else is having this issue, this is tied into Tableau not actually supporting SSAS Tabular, the connector you using is for SSAS Multidimensional so Tableau generates MDX queries against the DAX-based Tabular model.
This is also evident from Tableau's own techspecs site:
https://www.tableau.com/products/techspecs
"Microsoft SQL Server Analysis Services 2008 SP4 or later, multi-dimensional mode only*
"
Tableau's website at https://www.tableau.com/products/techspecs clearly states support for
"Microsoft SQL Server Analysis Services 2005 or later, non-tabular mode only*(incl. support for Kerberos)"
We are building a dashboard with many reports. The relationship between tables is defined in microstrategy. We found that Microstrategy is not using different SQL for different reports. It is pulling all the data from Database(which is 46 million) and then applying post processing on those data to generate individual reports.
This is taking lot of time and it is not using the query engine of the database.
How can we configure microstrategy so that it generates different query for different reports and collect only the required data for a particular report and NOT all data.
One way to do that is to use fre form SQL. But we want to have the capability for drag and drop kind of reports.
How can we achieve this?
We are using Microstrategy 10.1
From your description it sounds like Microstrategy is first pulling all data (46 million records) from the DB using its SQL Engine and then applying filtering after this.
If your reports have been created in Microstrategy developer (or web) using attribute filters then each report should correctly execute sql that has explicit where conditions that translate to those attribute filters. e.g. if you have a report with an attribute titled 'Fruit' and you want to only display apples, then you would have an attribute filter on that report that only displays results where 'Fruit' = 'Apple'. This would translate to a where condition in the SQL engine when the report is executed. However, if you are applying a view filter to the report, then the SQL engine will first obtain everything and then filter the entire dataset in the analytical engine, which would be slow especially if there are multiple reports running on the dashboard.
It's important to know how you are bringing the dataset into the dashboard - is it using a cube as a dataset, or a report, or? There are a few ways of achieving the performance you are looking for, here are a couple:
Option 1: Develop each report in Microstrategy developer using attribute filters as desired. This would require that you have all your attribute relationships defined correctly.
Option 2: Have all your 46 million records pulled into a cube. Use the cube as the dataset for the dashboard and then use view filters however you want on the various reports you want to place on the report.
Option 1 + 2: You can combine both of the above options if you wish. Store entire dataset in cube, define several reports (normal reports, not cube reports) that can dynamically source from cube, using filters as required, and then add these reports into your dashboard.
These are the things I would do as first steps:
Check your attributes and attribute relationships are defined and work
Create a test report and try to filter based on one of these attributes
Try to create a few reports, each with different filter conditions based on one of the attributes
Put these reports into the dashboard and see whether each one generates different SQL statements.
This sounds like you have either:
built the reports using view filters (which apply filtering post query execution) rather than applying filter in the generated SQL, or
you don't have attribute relationships defined, such that the system doesn't think the filters you've defined aren't relevant to the fact tables containing the data.
Are you using cubes? I am assuming that what you mean by executing the query once.
You need to replace the the individual reports with new report- regular report- not the ones made out of cubes. Thats the only way
I am trying to run RAWSQL_REAL("select sum(amount_us)from gbsa_dpo_itg.Fact_tblHistoryData_new where qtr_data='Q42014'") in calculated field and I am getting error message ERROR 2133: Aggregate function calls cannot contain subqueries.
I am using tableau 8.3.3 and HP Vertica database live connection to tableau
When I run the same query in custom sql it is working fine
pleas help in this
thanks in advance
Read the manual about these functions, look under reference, functions
You don't generally pass an entire SQL string to execute in isolation. Instead, they are useful for writing expressions or calling non standard functions that your server may provide, which are embedded within the SQL that Tableau generates. So first learn to use Tableau to get the effect you want, and then resort to Raw SQL functions in the rare case where you need to access some database server specific feature.
There is no reason that you would need Raw SQL to get the information above using Tableau. You could put amount_us on the row shelf and qtr_data on the filter shelf, and Tableau would generate a similar query.
If you are doing this to combine data from multiple queries, first learn about calculated fields and data blending.
We are using tableau and we are connected live to a redshift data source.
I cannot seem to find the Median aggregate function that i see when i connect to other types of data sources. Is this a known issue? We can't seem to find anything about it. Can we overcome it somehow using some kind of custom function?
First, I'm not a Redshift expert. However I know in other cases when the underlying datastore doesn't offer Median (MySQL for example), then a direct Tableau connection can't find the median.
If you use a Tableau extract, "Median" should appear as an aggregation option. This is due to the fact that Tableau has a median in its own data store implmentation.