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.
Related
PostgreSQL has excellent support for evaluating JSONPath expressions against JSON data.
For example, this query returns true because the value of the nested field is indeed "foo".
select '{"header": {"nested": "foo"}}'::jsonb #? '$.header ? (#.nested == "foo")'
Notably this query does not reference any schemas or tables. Ideally, I would like to use this functionality of PostgreSQL without creating or connecting to a full database instance. Is it possible to run PostgreSQL in such a way that it doesn't have schemas or tables, but is still able to evaluate "standalone" queries?
Some other context on the project, we need to evaluate JSONPath expressions against JSON data in both a Postgres database and Python application. Unfortunately, Python does not have any JSONPath libraries that support enough of the spec to be useful to us.
Ideally, I would like to use this functionality of PostgreSQL without creating or connecting to a full database instance.
Well, it is open source. You can always pull out the source code for this functionality you want and adapt it to compile by itself. But that seems like a large and annoying undertaking, and I probably wouldn't do it. And short of that, no.
Why do you need this? Are you worried about scalability or ease of installation or performance or what? If you are already using PostgreSQL anyway, firing up a dummy connection to just fire some queries at the JSONB engine doesn't seem too hard.
My ssis package has an oledb source which joins oracle and sql server to get source data and loads it into sql server oledb destination. Earlier we were using linked server for this purpose but we cannot use linked server anymore.
So I am taking the data from sql server and want to return it to the in clause of the oracle query which i am keeping as sql command oledb source.
I tried parsing an object type variable from sql server and putting it into the in clause of oracle query in oledb source but i get error that oracle cannot have more than 1000 literals in the in statement. So basically I think I have to do something like this:
select * from oracle.db where id in (select id from sqlserver.db).
Since I cannot use linked server so i was thinking if I could have a temp table which can be used throughout the package.
I tried out another way of using merge join in ssis. but my source data set is really large and the merge join is returning fewer rows than expecetd. I am badly stuck at this point. I have tried a number if things nothung seems to be working.
Can someone please help. Any help will be greatly appreciated.
A couple of options to try.
Lookup:
My first instinct was a Lookup Task, but that might not be a great solution depending on the size of your data sets, since all of the records from both tables have to pulled over the wire and stored in memory on the SSIS server. But if you were able to pull off a Merge Join, then a Lookup should also work, but it might be slow.
Set an OLE DB Source to pull the Oracle data, without the WHERE clause.
Set a Lookup to pull the id column from your SQL Server table.
On the General tab of the Lookup, under Specify how to handle rows with no matching entries, select Redirect rows to no-match output.
The output of the Lookup will just be the Oracle rows that found a matching row in your SQL Server query.
Working Table on the Oracle server
If you have the option of creating a table in the Oracle database, you could create a Data Flow Task to pipe the results of your SQL Server query into a working table on the Oracle box. Then, in a subsequent Data Flow, just construct your Oracle query to use that working table as a filter.
Probably follow that up with an Execute SQL Task to truncate that working table.
Although this requires write access to Oracle, it has the advantage of off-loading the heavy lifting of the query to the database machine, and only pulling the rows you care about over the wire.
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 a stored procedure that takes in a set of parameters (from dimension tables) and then outputs a set of rows from which a report has to be created.
Till now this is done in a .NET app using an ORM, but is it possible to integrate it with MicroStrategy?. How do I pass the selected params (from a report prompt) to a Stored Procedure on the database and then map the results back to the report?
In the past I did a Free Form SQL (FFSQL) report in MicroStrategy on top of a PL/SQL function which returned a 'table' (Of course that was an Oracle database, more info about returning a table with a function here).
So what you are looking for is something doable.
You can use the prompts in FFSQL report as parameters for your function
Then you have to map the columns of the returned table as attributes and metrics returned by the FFSQL report
This is something I did in a very old MicroStrategy implementation to provide writeback functionality: the users were allowed to update some values in some tables and the function returned a Success or Error message.
As you can imagine this was not a standard Data Warehouse solution, it was more an hoc solution for an operational database.
My suggestion is to avoid similar solution if not necessary and prepare in advance the tables/rows that you need. Of course in your case you have already the procedure ready so you have just to figure out how to combine it with MicroStrategy.
Some useful readings:
TN37783: Instructions to use stored procedures within Freeform SQL reports in MicroStrategy 9.x against different databases
Using Prompts in Freeform SQL Reports
I am new to Tableau, and having performance issues and need some help. I have a query that joins several large tables. I am using a live data connection to a MySQL db.
The issue I am having is that it is not applying the filter criteria before asking MySQL for the data. So it is essentially doing a SELECT * from my query and not applying the filter criteria to the where clause. It pulls all the data from MySQL db back to Tableau, then throws away the un-needed data based on my filter criteria. My two main filter criteria are on account_id and a date range.
I can cleanly get a list of the accounts from just doing a select from my account table to populate the filter list, then need to know how to apply that selection when it goes to pull the data from the main data query from MySQL.
To apply a filter at the data source first, try using context filters.
Performance can also be improved by using extracts.
I would personally use an extract, go into your MySQL DB Back-end, run the query, and a CREATE TABLE extract1 AS statement, or whatever you want to call your data table.
When you import this table into Tableau it will already have a SELECT * of your aggregate data in the workbook. From here your query efficiency will be increased ten fold.
Unfortunately, it's going to take awhile for Tableau processing time + mySQL backend DB query time = Ntime to process your data.
Try the extracts...
I've been struggling with the very same thing. I have found that the tableau extracts aren't any faster than pulling directly from a SQL table. What I have done is within SQL created tables that already have the filtered data in them, so the Select * will have only the needed data. The downside to this is it takes up more space on the server, but this isn't a problem on my side.
For the Large Data sets Tableau recommend using an Extract.
An extract will create a snapshot of the data that you are connected with and processing on this data will be faster than a live connection.
All the charts and visualization will load faster and saves your time, each time when you go to the Dashboard.
For the filters that you are using to filter the data-set will work faster in an extract connection. But to get the latest data you have to refresh the extract or schedule a refresh in the server ( if you are uploading the report to server).
There are multiple type of filters available in Tableau, the use of which depends on your application, context filters and global filters can be use to filter the whole set of data.