Sql in db2 works with both max() function and greatest() function, but I was wondering if both are put there in the language, there must be a difference between the two?
MIN/MAX aggregate over the same attribute in multiple rows, while GREATER/LEAST choose the value from a number of expressions for just one row.
Direct quote from the DB2 documentation:
The GREATEST scalar function is a synonym for the MAX scalar function.
Related
This may be an easily solvable question but I can't see an immediate solution. I am calling a PostgreSQL function which returns multiple columns, 2 of which are relevant to this question - a date column & a numeric field of return values. An example of the function call would be
SELECT curr_date, return_val
FROM schema.function_name($1,$2);
With example output such as
"2014-07-31";0.003767
"2014-08-07";-0.028531
"2014-08-14";0.020051
"2014-08-21";-0.003541
"2014-08-28";0.007766
"2014-09-04";-0.021926
"2014-09-11";0.026330
"2014-09-18";0.008137
"2014-09-25";-0.033303
"2014-10-02";0.030100
"2014-10-09";-0.012116
"2014-10-16";-0.017148
So on, so forth. The data will always return from this function with the dates ascending. What I would like to do is to use Postgres's stddev_samp function on every row, but only considering the return_value's from that row's date back in time. Something like:
SELECT curr_date, return_val,
--stddev_samp(return_val) where curr_date <= curr_date of current row
FROM schema.function_name($1,$2);
Naturally, if I calculated the sample deviation of the return_value's from 2014-07-31 to 2014-10-02 in the sample provided, it would differ slightly to calculating it using the result set from 2014-07-31 to any other date present. I know I could probably write another function which takes a numeric array as input and returns the standard deviation as output, and then call this in my query above, but I'm hoping someone may have a simpler approach which I'm just currently not seeing. If any other information is required, feel free to ask. I'm using version 10.7.
demo:db<>fiddle
Using window functions:
SELECT
stddev_samp(return_val) OVER(ORDER BY curr_date)
FROM
mytable
Sorry if this seems trivial, but I am fairly new to Tableau. I have a simple table that has 1 dimension for columns and 1 dimension for rows. My Marks are the Count of a third dimension. I'd like to divide only 1 of the columns in the table by a constant but not all of them. When I have tried conditional statements, I receive the error regarding mix of non-aggregate and aggregate statements.
What is the best way to divide a single column's values based upon a condition?
Thanks in advance.
Typically the error regarding non-aggregate and aggregate statements can be resolved using the ATTR() function.
SUM([Sales]) / [Constant]
Turns to:
SUM([Sales]) / ATTR([Constant])
Or conversely, which might or might not fit your data:
[Sales] / [Constant]
You just cant mix the two as in the first example.
Edit
This is probably a more accurate place for the ATTR() function given what I'm guessing is your use case:
If ATTR([Segment]) = 'Corporate'
Then COUNT(Sales) / SUM([Constant])
END
Try turning the constant to a discrete measure and see if that works. (right-click on measure and select 'discrete')
Also, without seeing the conditional code you are using, you probably need to wrap the entire condition with count() in order to not get the Aggregate/Non-Aggregate error, like this:
Count(If [MyDimension] = "XX" then [MyOtherDimension] else Null End)
NOT like this:
If [MyDimension] = "XX" then Count([MyOtherDimension]) else Null End
From every references that I search how to do cumulative sum / running total. they said it's better using windows function, so I did
select grandtotal,sum(grandtotal)over(order by agentname) from call
but I realize that the results are okay as long as the value of each rows are different. Here is the result :
Is There anyway to fix this?
You might want to review the documentation on window specifications (which is here). The default is "range between" which defines the range by the values in the row. You want "rows between":
select grandtotal,
sum(grandtotal) over (order by agentname rows between unbounded preceding and current row)
from call;
Alternatively, you could include an id column in the sort to guarantee uniqueness and not have to deal with the issue of equal key values.
can any one please help me for how I can increase the PostgreSQL - max number of parameters length. I don't want to do any other way i want to use normal query as I am using. but if I am passing 90,000 parameters in IN Query then how I make it possible to execute this query?
If you believe this page https://msdn.microsoft.com/en-us/library/ms143432.aspx the number of parameters for example in a stored proc, statement, function, ... are fix.
I'm trying to annualise my data in tableau, but get an error in the Calculated Field.
"Cannot mix aggregate and non-aggregate arguments to function"
my formula is
sum(profit)/month(selected date) *12
How do I get an integer for the current month? That seems to be the problem, it tries to aggregate the month as well.
Thanks.
Short answer: wrap the call to month in a call to min() -- which works well if you have MONTH([selected date]) on the visualization as a dimension.
There are three types of calculated fields in Tableau:
row level calculations which act on a single data row. They can read from values of other fields in the same row and return a single value per row.
aggregate calculations which act on a partition or block of data rows. They can reference the result of aggregating the values for a field across the entire partition, using a an aggregate function like SUM() or MIN().
table calculations which act on an entire table of aggregated results.
You can't mix and match. Everything in a calculated field must be all at one level or another -- either all referenced fields must use aggregation functions (for aggregate calculated fields) or no referenced fields must use aggregation functions (for data row level calculated fields).
Hence the error message you saw.
Sometimes you know that all values for a field will be the same in a partition based on your visualization, so the aggregation function seems unnecessary. But Tableau still requires you to be explicit about how to turn a block of values into a single value, because the calculation must be defined even when the visualization is partitioned differently. In these cases, you can use min(), max(), avg(), or perhaps attr() because they all return the same value for a list of identical values.
The first two types are typically executed on the server (i.e. they are implemented by Tableau emitting SQL to send to the database server). Table calculations are executed by Tableau on the client site to post-process the results from the database server.
Table calcs are the most complicated type, but can be very useful. Explaining them is a post for another day.