I need to create a distinct count of people who fall into two different dimensions.
One is called [Student Research Degree].[Is Research Degree Current].&[Yes]
The other is called [Student Research Degree].[Is Research Degree Complete].&[Yes]
If one or the other are Yes, or both, then I need to count the record.
If both are no, I can exclude it. I have a row counter measure called [Measures].[Student ID Distinct Count Hidden] already in place.
If I use just one element with the measure, I get the right answer, but if I try to cross join the other elements, I get a result of NULL.
eg
AGGREGATE(CROSSJOIN(
[Student Research Degree].[Is Research Degree Current].&[Yes]
,[Student Research Degree].[Is Research Degree Complete].&[Yes]
), [Measures].[Student ID Distinct Count Hidden])
I am aware that I can just land an extra value in the ETL, and have SQL do the work, and in the end this might be the solution. Is there a way of doing an OR statement on this sort of thing?
No, the TUPLE of &[YES], &[YES] doesn't create an OR situation, where I want [NO]s when the other is yes.
I started looking at a subtractive approach where I started with the ALL set, and removed the distinct count of invalid combinations in a tuple and subtracted that from the grand total. This approach did work, but ONLY because the data allowed for it. If a person could have been in multiple combinations, this wouldn't have worked.
I'm currently testing that approach with the rest of the cube. By all appearances this works perfectly, but I will go with ETL if any bugs or mismatches can be proven.
Related
I have a CrateDB table storing various information for zipcodes. It contains around 30k zipcodes, and I need my query to return certain profiling information for all zipcodes at once. I understand that typically it wouldn't be feasible, but since I only need ballpark information and many zipcodes are consecutive, I think an optimization is possible.
For example, if I wanted to profile population, a grouped result such as this would work for me:
group 1 (0-1000): 00000-02000,02004-02010,02012
group 2 (1001-3000): ...
...
The populations and groups above are fake, but the idea should hold. Basically, group profiled category into buckets, assign zipcodes to correct bucket, and further reduce size by using range representation. I could settle for a predefined number of groups or have group buckets defined by request/query itself. This would hopefully reduce the response from something that would be too large for a single query to one that's manageable.
Is it possible to write a cratedb function to do something similar to avoid bandwidth issues from having this grouping done on a different service/container/vm?
You could probably crate groups on the fly or as columns if you wish with a regex, I have done this on a 23M row table and group by that.
In my example regex grouping and AVG took around 30s, but this is very subjective to my hardware.
Something like this would probably work as a general pointer
SELECT avg (--yourColumn--), regexp_matches(--yourColumn--, '--your regex--','i')[1]
FROM "doc"."--yourTable--"
group by regexp_matches(postcode, '--your regex--','i')[1]
order by regexp_matches(postcode, '--your regex--','i')[1]
You could use over windowed function but this doesn't yet have the full SQL support for partitioning etc.
I am building a data model with PowerPivot for Excel 2013 and need to be able to identify the max number of emails sent per person. The DAX formula below gives me the result that I looking for but performance is incredibly slow. Is there an alternative that will compute a maximum by group without the performance hit?
Maximum Emails per Constituent:
=MAXX(SUMMARIZE('Email Data','Email Data'[person_id],"MAX Value",
([Emails Sent]/[Unique Count People])),[MAX Value])
So, without the measure definitions for [Emails Sent] or [Unique Count People], it is not possible to give definitive advice on performance. I'm going to assume they are trivial measures, though, based on their names - note that this is an assumption and its truth will affect the rest of my post. That being said, there is an obvious optimization to make to start with.
Maximum Emails per Consultant:=
MAXX(
ADDCOLUMNS(
VALUES('Email Data'[person_id])
,"MAX Value"
,[Emails Sent] / [Unique Count People]
)
,[MAX Value]
)
I used the ADDCOLUMNS() rather than a SUMMARIZE() to calculate new columns. See this post for an explanation of the performance implications.
Additionally, since you're not grouping by multiple columns, there's no need to use SUMMARIZE(). The performance impact of using VALUES() instead should be minimal.
The other question that comes to mind is whether this needs to be a measure. Are you going to be slicing by other dimensions? If not, this becomes a static attribute of a [person_id] which could be calculated during ETL, or in a calculated column.
A final note - I've also been assuming that your model is optimal as well. Again, we'd need to see it to make comment on whether you could see performance issues from something you're doing there.
currently we're building a database to track different factories' pollutant emissions. Now a query is needed that gives us information about relative quantities. Somehow I feel this should be straight forward but I have had no success implementing it in SQL.
I'm starting from a working query that returns the following fields:
PRODUCTION_YEAR, COMPANY, PRODUCT_CATEGORY, POLLUTANT, TOTAL_EMISSIONS, SHARE
TOTAL_EMISSIONS contains the total emissions for each company in a particular year and product category. SHARE is a computed field and contains the contribution (as a fraction) of each company to that year's overall emissions of that particular pollutant in that particular product category.
Now the task is to count the factories contributing to each pollutant. I arrived at this:
SELECT PRODUCTION_YEAR, POLLUTANT, PRODUCT_CATEGORY, Count(COMPANY)
FROM theQuery
GROUP BY PRODUCTION_YEAR, POLLUTANT, PRODUCT_CATEGORY;
However, now our client wants something more sophisticated: count only the biggest polluters who contribute 95% of emissions. In a script, I'd probably just have the pollution percentages in each category sorted ascendingly, then walk the dataset, sum up the shares and only start counting after reaching 5%. Doing it in SQL, no idea.
My first step (adding a SUM(SHARE) field to the new query) already resulted in errors ("expression not included in aggregate function", roughly translated, not sure what to make of it because all the expressions were indeed included). Is there even a way to do this in an SQL query, or am I wasting my time and would be better off just writing some VBA?
Thanks for any input!
Best,
Ben
Gord's method (see link in comment) works well for this task.
BACKGROUND:
I've been trying to streamline the work involved in running a report in my program. Lately, I've had to supply a listing of job numbers an instrument has been used on with the listing of items for cost/benefit analysis. Mostly to see how often an instrument is used since it was last serviced/calibrated and the last time anyone did use it. I was looking to integrate this into the query that helps generate the report - but I keep hitting a brick wall of sorts with the number of uses - since I want that aggregate to be based on the date the instrument was last calibrated (a field based in the same query). I can get it to give me the number of uses in the system total - but it will not accept the limitation that I want it to be only counting the times used since the last time it was calibrated
PROBLEM:
Attempts to put an aggregate function in my report for the number of uses since the item's calibration are met either with undesired results, or the dreaded 'aggregate missing' error (don't remember the exact warning).
-- Edited to add 8/12/2011 # 16:09 --
An additional problem with the use of the Max aggregate has been found for instruments that have never been used being excluded by this query.
DETAILS:
Here is the query that does work so far:
SELECT
dbo_tblPOGaugeDetail.intGagePOID,
dbo_tblPOGaugeDetail.strGageDetailID,
dbo_Gage_Master.Description,
dbo_Gage_Master.Manufacturer,
dbo_Gage_Master.Model_No,
dbo_Gage_Master.Gage_SN,
dbo_Gage_Master.Unit_of_Meas,
dbo_Gage_Master.User_Defined,
dbo_Gage_Master.Calibration_Frequency,
dbo_Gage_Master.Calibration_Frequency_UOM,
dbo_tblPOGaugeDetail.bolGageLeavePriceBlank,
dbo_tblPOGaugeDetail.intGageCost,
dbo_Gage_Master.Last_Calibration_Date,
dbo_Gage_Master.Next_Due_Date,
dbo_tblPOGaugeDetail.bolGageEvaluate,
dbo_tblPOGaugeDetail.bolGageExpedite,
dbo_tblPOGaugeDetail.bolGageAccredited,
dbo_tblPOGaugeDetail.bolGageCalibrate,
dbo_tblPOGaugeDetail.bolGageRepair,
dbo_tblPOGaugeDetail.bolGageReturned,
dbo_tblPOGaugeDetail.bolGageBER,
dbo_tblPOGaugeDetail.intTurnaroundDaysOut,
qryRCEquipmentLastUse.MaxOfdatDateEntered
FROM (dbo_tblPOGaugeDetail
INNER JOIN dbo_Gage_Master ON dbo_tblPOGaugeDetail.strGageDetailID = dbo_Gage_Master.Gage_ID)
INNER JOIN qryRCEquipmentLastUse ON dbo_Gage_Master.Gage_ID = qryRCEquipmentLastUse.Gage_ID
ORDER BY dbo_tblPOGaugeDetail.strGageDetailID;
But I can't seem to aggregate a count of Uses (making a Count(strCustomerJobNum)) from the tblGageActivity with the following fields:
strGageID
strCustomerJobNum
datDateEntered
datTimeEntered
I tried to add a field to the formerly listed query to do a Count(strCustomerJobNum) where datDateEntered matched the Last_Calibration_Date from the calling query - but I got the 'missing aggregate' error. If I leave this condition out - it will run - but will list every instrument ever sent out only if it's had a usage count of at least one (not what I want at all, sadly).
I also want to make sure that if I should get a zero uses count - I will get a zero back instead of my expected records minus the null results.
I hope someone out there can tell me where I am going wrong with this - I want to save the time I am currently spending running an activity report in another program whenever I want to generate this report. Thanks in advance, and let me know if you need me to post more information.
-- Edited to add 08/15/2011 # 14:41 --
I managed to solve the Max() aggregate problem by creating a 'pure' first-step query to get a listing of all instrument with most modern date as qryRCEquipmentUsed.
qryRCEquipmentLastUse:
SELECT dbo.tblGageActivity.strGageID, Max(dbo.tblGageActivity.datDateEntered) AS datLastDateUsed
FROM dbo.tblGageActivity
GROUP BY dbo.tblGageActivity.strGageID;
Then I created a 'pure' listing of all instruments that have no usage at all as a query named qryRCEquipmentNeverUsed.
qryRCEquipmentNeverUsed:
SELECT dbo_Gage_Master.Gage_ID, NULL AS datLastDateUsed
FROM dbo_Gage_Master LEFT JOIN dbo_tblGageActivity ON dbo_Gage_Master.Gage_ID = dbo_tblGageActivity.strGageID
WHERE (((dbo_tblGageActivity.strGageID) Is Null));
NOTE: The NULL was inserted so that the third combining UNION query will not fail due to a mismatch in the number of fields being retrieved from the tables.
At last, I created a UNION query named qryCombinedUseEquipment to combine the two into a list:
qryCombinedUseEquipment:
SELECT *
FROM qryRCEquipmentLastUse
UNION SELECT *
FROM qryRCEquipmentNeverUsed;
Using this last union query to feed the Last Used date to the parent query works in datasheet view, but when the parent query is called in the report - I get a blank report; so a nudge in the right direction would still be wonderfully appreciated.
APPENDIX
Same script as above, but with shorter table aliases (in case someone finds that clearer):
SELECT
gd.intGagePOID,
gd.strGageDetailID,
gm.Description,
gm.Manufacturer,
gm.Model_No,
gm.Gage_SN,
gm.Unit_of_Meas,
gm.User_Defined,
gm.Calibration_Frequency,
gm.Calibration_Frequency_UOM,
gd.bolGageLeavePriceBlank,
gd.intGageCost,
gm.Last_Calibration_Date,
gm.Next_Due_Date,
gd.bolGageEvaluate,
gd.bolGageExpedite,
gd.bolGageAccredited,
gd.bolGageCalibrate,
gd.bolGageRepair,
gd.bolGageReturned,
gd.bolGageBER,
gd.intTurnaroundDaysOut,
lu.MaxOfdatDateEntered
FROM (dbo_tblPOGaugeDetail gd
INNER JOIN dbo_Gage_Master gm ON gd.strGageDetailID = gm.Gage_ID)
INNER JOIN qryRCEquipmentLastUse lu ON gm.Gage_ID = lu.Gage_ID
ORDER BY gd.strGageDetailID;
Piece by piece...
First -- I suspect you're trying to answer too many questions at once (as evidenced by 23 fields in your SELECT), which will make aggregation near-impossible. Start by narrowing down the scope of the query -- What question is this query attempting to answer? (You can always make more queries to answer other questions... :-)
1) How many uses since last calibration?
2) How many uses since last ...use? (not sure what you mean by that -- maybe last sign-out, or last rental, etc.?)
Tip -- learn to use table aliases. Large queries are difficult to read; worse because of repeated table names.
1) Ex.: dbo_tbl_POGaugeDetail.intGagePOID becomes d.intGagePOID
Here's a sample that might get you started:
SELECT
d.strCustomerJobNum,
Max(d.last_calibration_date) -- not sure what you named that field
Count(d.strCustomerJobNum)
FROM
dbo_tblPOGaugeDetail d
GROUP BY
d.strCustomerJobNum
Does this work:
SELECT dbo_tblPOGaugeDetail.intGagePOID, dbo_tblPOGaugeDetail.strGageDetailID,
OuterGageMaster.Description, OuterGageMaster.Manufacturer, OuterGageMaster.Model_No,
OuterGageMaster.Gage_SN, OuterGageMaster.Unit_of_Meas, OuterGageMaster.User_Defined,
OuterGageMaster.Calibration_Frequency, OuterGageMaster.Calibration_Frequency_UOM,
dbo_tblPOGaugeDetail.bolGageLeavePriceBlank, dbo_tblPOGaugeDetail.intGageCost,
OuterGageMaster.Last_Calibration_Date, OuterGageMasterNext_Due_Date,
dbo_tblPOGaugeDetail.bolGageEvaluate, dbo_tblPOGaugeDetail.bolGageExpedite,
dbo_tblPOGaugeDetail.bolGageAccredited, dbo_tblPOGaugeDetail.bolGageCalibrate,
dbo_tblPOGaugeDetail.bolGageRepair, dbo_tblPOGaugeDetail.bolGageReturned,
dbo_tblPOGaugeDetail.bolGageBER, dbo_tblPOGaugeDetail.intTurnaroundDaysOut,
qryRCEquipmentLastUse.MaxOfdatDateEntered,
(Select Count(strCustomerJobNum)
FROM tblGageActivity WHERE
OuterGageMaster.Last_Calibration_Date=tblGageActivity.datDateEntered) As JobCount
FROM
(dbo_tblPOGaugeDetail INNER JOIN dbo_Gage_Master OuterGageMaster ON
dbo_tblPOGaugeDetail.strGageDetailID = OuterGageMaster.Gage_ID) INNER JOIN
qryRCEquipmentLastUse ON OuterGageMaster.Gage_ID = qryRCEquipmentLastUse.Gage_ID
ORDER BY
dbo_tblPOGaugeDetail.strGageDetailID;
or is that what you tried?
Summary Problem:
Attempts to put an aggregate function in my report for the number of uses since the item's calibration are met either with undesired results, or the dreaded 'aggregate missing' error.
Solution:
I decided to leave the query driving the report alone - instead choosing to employ the use of DLookup and DCount as appropriate to retrieve the last used date from a query that provides the last used date of all the instruments, and the number of uses an instrument has had since it's last calibration, using the aforementioned domain aggregates respectively.
Using the query described in the problem description, I am able to retrieve the last used date for all instruments. I used a =DLookup statement as the source for a text box on the report's subreport dealing with various items as such:
=IIf((DLookUp("[qryRCCombinedUseEquipment]![datLastDateUsed]","[qryRCCombinedUseEquipment]","[qryRCCombinedUseEquipment]![strGageID]=[strGageDetailID]")) Is Null Or ([bolGageReturned]=True),"",DLookUp("[qryRCCombinedUseEquipment]![datLastDateUsed]","[qryRCCombinedUseEquipment]","[qryRCCombinedUseEquipment]![strGageID]=[strGageDetailID]"))
This allows items that have never been used to return a NULL result, which will display as a blank text box.
The number of uses, however, would not feed off a query using =DCount (I tried, it would take over ten minutes to retrieve results, if it ever did). However, using the underlying activity table, I used the following statement:
=IIf([bolGageReturned],"","Used " & DCount("[dbo_tblGageActivity]![strGageID]","[dbo_tblGageActivity]","[dbo_tblGageActivity]![strGageID] = [strGageDetailID] And [dbo_tblGageActivity]![datDateEntered] Between [txtLastCalibrationDate] And date()") & " times since last calibration")
It would retrieve a number of times used since the instrument was last calibrated, but no uses that are before that or after today (some jobs are post dated, strangely). Of course, this is SLOW (about thirty seconds for a large document with thirty or forty instruments).
Does anyone else have a better solution for this, or will I have to take the performance hit? If no one has any better ideas, I will accept this as the answer after five days (8/21/2011) .
I have several sources of tables with personal data, like this:
SOURCE 1
ID, FIRST_NAME, LAST_NAME, FIELD1, ...
1, jhon, gates ...
SOURCE 2
ID, FIRST_NAME, LAST_NAME, ANOTHER_FIELD1, ...
1, jon, gate ...
SOURCE 3
ID, FIRST_NAME, LAST_NAME, ANOTHER_FIELD1, ...
2, jhon, ballmer ...
So, assuming that records with ID 1, from sources 1 and 2, are the same person, my problem is how to determine if a record in every source, represents the same person. Additionally, sure not every records exists in all sources. All the names, are written in spanish, mainly.
In this case, the exact matching needs to be relaxed because we assume the data sources has not been rigurously checked against the official bureau of identification of the country. Also we need to assume typos are common, because the nature of the processes to collect the data. What is more, the amount of records is around 2 or 3 millions in every source...
Our team had thought in something like this: first, force exact matching in selected fields like ID NUMBER, and NAMES to know how hard the problem can be. Second, relaxing the matching criteria, and count how much records more can be matched, but is here where the problem arises: how to do to relax the matching criteria without generating too noise neither restricting too much?
What tool can be more effective to handle this?, for example, do you know about some especific extension in some database engine to support this matching?
Do you know about clever algorithms like soundex to handle this approximate matching, but for spanish texts?
Any help would be appreciated!
Thanks.
The crux of the problem is to compute one or more measures of distance between each pair of entries and then consider them to be the same when one of the distances is less than a certain acceptable threshold. The key is to setup the analysis and then vary the acceptable distance until you reach what you consider to be the best trade-off between false-positives and false-negatives.
One distance measurement could be phonetic. Another you might consider is the Levenshtein or edit distance between the entires, which would attempt to measure typos.
If you have a reasonable idea of how many persons you should have, then your goal is to find the sweet spot where you are getting about the right number of persons. Make your matching too fuzzy and you'll have too few. Make it to restrictive and you'll have too many.
If you know roughly how many entries a person should have, then you can use that as the metric to see when you are getting close. Or you can divide the number of records into the average number of records for each person and get a rough number of persons that you're shooting for.
If you don't have any numbers to use, then you're left picking out groups of records from your analysis and checking by hand whether they look like the same person or not. So it's guess and check.
I hope that helps.
This sounds like a Customer Data Integration problem. Search on that term and you might find some more information. Also, have a poke around inside The Data Warehousing Institude, and you might find some answers there as well.
Edit: In addition, here's an article that might interest you on spanish phonetic matching.
I've had to do something similar before and what I did was use a double metaphone phonetic search on the names.
Before I compared the names though, I tried to normalize away any name/nickname differences by looking up the name in a nick name table I created. (I populated the table with census data I found online) So people called Bob became Robert, Alex became Alexander, Bill became William, etc.
Edit: Double Metaphone was specifically designed to be better than Soundex and work in languages other than English.
SSIS , try using the Fuzzy Lookup transformation
Just to add some details to solve this issue, I'd found this modules for Postgresql 8.3
Fuzzy String Match
Trigrams
You might try to cannonicalise the names by comparing them with a dicionary.
This would allow you to spot some common typos and correct them.
Sounds to me you have a record linkage problem. You can use the references in the link.