I'm trying to find the match no in which Germany played against Poland. This is from https://www.w3resource.com/sql-exercises/soccer-database-exercise/sql-subqueries-exercise-soccer-database-4.php. There are two tables : match_details and soccer_country. I don't understand how the count(distinct) works in this case. Can someone please clarify? Thanks!
SELECT match_no
FROM match_details
WHERE team_id = (
SELECT country_id
FROM soccer_country
WHERE country_name = 'Germany')
OR team_id = (
SELECT country_id
FROM soccer_country
WHERE country_name = 'Poland')
GROUP BY match_no
HAVING COUNT(DISTINCT team_id) = 2;
As Lamak mentioned, what an ugly consideration for a query, but many ways to approach a query.
As mentioned, counting for (Distinct team_id) makes sure that there are only 2 unique teams. If there is ever a Cartesian result, you could get repetition of multiple rows showing more than one instance of both teams. So the count of distinct on the TEAM_ID eliminates that.
Now, that said, Other "team" query data structures I have seen have a single record for the match and a column for EACH TEAM playing the match. That is easier by a long-shot, but still a relatively easy query.
Break the query down a little, and consider a large scale set of data (not that this, or any sort of even professional league would have such large record counts to give delay with a sql engine).
Your first criteria is games with Germany. So lets start with that.
SELECT
md1.match_no
FROM
match_details md1
JOIN soccer_country sc1
on md1.team_id = sc1.country_id
AND sc1.country_name = 'Germany'
So, why even look at any other record/match if Germany is not even part of the match on either side. Of which this in itself would return 6 matches from the sample data of 51 matches. So now, all you need to do is join AGAIN to the match details table a second time for only those matches, but ALSO the second team is Poland
SELECT
md1.match_no
FROM
match_details md1
JOIN soccer_country sc1
on md1.team_id = sc1.country_id
AND sc1.country_name = 'Germany'
-- joining again for the same match Germany was already qualified
JOIN match_details md2
on md1.match_no = md2.match_no
-- but we want the OTHER team record since Germany was first team
and md1.team_id != md2.team_id
-- and on to the second country table based on the SECOND team ID
JOIN soccer_country sc2
on md2.team_id = sc2.country_id
-- and the second team was Poland
AND sc2.country_name = 'Poland'
Yes, may be a longer query, but by eliminating 45 other matches (again, thinking a LARGE database), you have already saved blowing through tons of data to a very finite set. And now finishing only those Germany / Poland. No aggregates, counts, distincts, just direct joins.
FEEDBACK
Lets take a look at some BAD sample data... which as all programmers know, there is no such thing (NOT). Anyhow, lets take a look at these few matches.
Match Team ID blah
52 Poland Just put the names here for simplistic purposes
52 Poland
53 Germany
53 Germany
If you were to run the query without DISTINCT Teams, both match 52 and 53 would show up... As Poland is one team and appears 2 times for match 52, and similarly Germany 2 times for match 53. By doing DISTINCT Team, you can see that for each match, there is only 1 team being returned and thus excluded. Does that help? Again, no such thing as bad data :)
And yet another sample match where more than 2 teams created
Match Team ID
54 France
54 Poland
54 England
55 Hungary
56 Austria
In each of these matches, NONE would be returned. Match 54 has 3 distinct teams, and Match 55 and 56 only have single entry, thus no opponent to compete against.
2nd FEEDBACK
To clarify the query. If you look at the short query for just Germany, that aliased instance of "md1" is already sitting on any given record for a Germany match. So the second join to the "md2", I only care about the same match, so I can join on the same match_no. However, in the "md2" alias, the "!=" means NOT EQUAL. ! = logical NOT. So the join is saying from the MD1, join to the MD2 alias on the same match id. However, only give me where the teams are NOT the same. So the first instance holds Germany's team ID (already qualified) and thus give me the secondary team id. So now I can use the secondary (md2) instance team ID to join to the country to confirm only for Poland.
Does this now clarify things for you?
Related
I'm using BigQuery.
I have two simple tables with "bad" data quality from our systems. One represents revenue and the other production rows for bus journeys.
I need to match every journey to a revenue transaction but I only have a set of fields and no key and I don't really know how to do this matching.
This is a sample of the data:
Revenue
Year, Agreement, Station_origin, Station_destination, Product
2020, 123123, London, Manchester, Qwerty
Journeys
Year, Agreement, Station_origin, Station_destination, Product
2020, 123123, Kings Cross, Piccadilly Gardens, Qwer
2020, 123123, Kings Cross, Victoria Station, Qwert
2020, 123123, London, Manchester, Qwerty
Every station has a maximum of 9 alternative names and these are stored in a "station" table.
Stations
Station Name, Station Name 2, Station Name 3,...
London, Kings Cross, Euston,...
Manchester, Piccadilly Gardens, Victoria Station,...
I would like to test matching or joining the tables first with the original fields. This will generate some matches but there are many journeys that are not matched. For the unmatched revenue rows, I would like to change the product name (shorten it to two letters and possibly get many matches from production table) and then station names by first change the station_origin and then station_destination. When using a shorter product name I could possibly get many matches but I want the row from the production table with the most common product.
Something like this:
1. Do a direct match. That is, I can use the fields as they are in the tables.
2. Do a match where the revenue.product is changed by shortening it to two letters. substr(product,0,2)
3. Change the rev.station_origin to the first alternative, Station Name 2, and then try a join. The product or other station are not changed.
4. Change the rev.station_origin to the first alternative, Station Name 2, and then try a join. The product is changed as above with a substr(product,0,2) but rev.station_destination is not changed.
5. Change the rev.station_destination to the first alternative, Station Name 2, and then try a join. The product or other station are not changed.
I was told that maybe I should create an intermediate table with all combinations of stations and products and let a rank column decide the order. The station names in the station's table are in order of importance so "station name" is more important than "station name 2" and so on.
I started to do a query with a subquery per rank and do a UNION ALL but there are so many combinations that there must be another way to do this.
Don't know if this makes any sense but I would appreciate any help or ideas to do this in a better way.
Cheers,
Cris
To implement a complex joining strategy with approximate matching, it might make more sense to define the strategy within JavaScript - and call the function from a BigQuery SQL query.
For example, the following query does the following steps:
Take the top 200 male names in the US.
Find if one of the top 200 female names matches.
If not, look for the most similar female name within the options.
Note that the logic to choose the closest option is encapsulated within the JS UDF fhoffa.x.fuzzy_extract_one(). See https://medium.com/#hoffa/new-in-bigquery-persistent-udfs-c9ea4100fd83 to learn more about this.
WITH data AS (
SELECT name, gender, SUM(number) c
FROM `bigquery-public-data.usa_names.usa_1910_2013`
GROUP BY 1,2
), top_men AS (
SELECT * FROM data WHERE gender='M'
ORDER BY c DESC LIMIT 200
), top_women AS (
SELECT * FROM data WHERE gender='F'
ORDER BY c DESC LIMIT 200
)
SELECT name male_name,
COALESCE(
(SELECT name FROM top_women WHERE name=a.name)
, fhoffa.x.fuzzy_extract_one(name, ARRAY(SELECT name FROM top_women))
) female_version
FROM top_men a
Looking into my notes for introduction to databases, I have stumbled upon a case that i do not understand (Between except and distinct).
It says so in my notes that:
The two queries below have the same results, but this will not be the case in general.
First query:
Select c.first_name,c.last_name,c.email
FROM customers as c
WHERE c.country = 'Japan'
EXCEPT
Select c.first_name,c.last_name,c.email
FROM customers as c
WHERE c.last_name LIKE 'D%';
Second query:
Select DISTINCT c.first_name,c.last_name,c.email
FROM customers as c
WHERE c.country = 'Japan' AND NOT (c.last_name LIKE 'D%');
Could anyone provide me some insights as to what are cases whereby the results would differ?
Number 1 selects first, last & email from customers who are from Japan and whose last names do not start with D.
Number 2 selects first, last & email, where no two records have all 3 fields the same, where the customers are from Singapore and their last names do not begin with D.
I suppose I can imagine a table where these would yield the same results, but I don't think it would ever appear except in very contrived circumstances.
Joe Smith jsmith#abc.com Japan
Joe Smith jsmith#abc.com Singapore
Would be one of them. Both queries would yield Joe Smith jsmith#abc.com. Another case would be if no-one was from either country or everyone's last name started with D, then they would both yield nothing.
None of this is tested, and the EXCEPT statement is something I've read about but never had occasion to use.
The first is looking at Japan, the second at Singapore, so I don't see why these would generally -- or specifically -- return the same data.
Even if the countries were the same you have another issue with NULL values. So, if your data looks like this:
first_name last_name email country
xxx NULL a Japan
Your first query would return the row. The second would not.
The problem
Users are frequently inputting "country name" strings into the "city name" field. Heuristically, this appears to be an extremely common practice. For example, a user might put "TAIPEI TAIWAN" in the city name when only "TAIPEI" should be input and then the country would be "TAIWAN". I am working to aggregate these instances for this specific field (your help will allow me to expand this to other columns and tables) and then identify where possible rankings associated with strictly the "country" names in the "city" field.
I have two tables that I am attempting to leverage to track down data validation issues. Tbl1 is named "Customer_Address" comprised of geographic columns like (Customer_Num, Address, City_Name, State, Country_Code, Zipcode). Tbl2 named "HR_Countries" is clean table of 2-digit ISO country codes with their corresponding name values (Lebanon, Taiwan, China, Syria, Russia, Ukraine, etc) and some other fields not presently used.
The initial step is to query "Customer_Address" to find City_Names LIKE a series of OR statements (LIKE '%CHINA', OR LIKE 'TAIWAN', OR etc etc) and count the number of occurrences where the City_Name is like the designated country_name string I passed it and the results are pretty good. I've coded in some exclusions to deal with things like "Lebanon, OH" so my overall results are satisfactory for the first phase.
Part of the query does a LEFT join from Tbl1 to Tbl2 to add the risk rating from tbl2 as a result of the query against tbl1:
LEFT JOIN tbl2 risk
ON INSTR(addr.CITY_NM, risk.COUNTRY_NAME,1) <> 0
Example of Tbl1 Data Output (head(tbl1), n=7)
CountryNameInCity CountOfOccurences RR
China 15 High
Taiwan 2000 Medium
Japan 250 Low
Taipei, Taiwan 25 NULL
Kabul, Afghanistan 10 NULL
Shenzen China 100 NULL
Afghanistan 52 Very High
Example of Tb2 Data (head(tbl2), n=6)
CountryName CountryCode RR
China CN High
Taiwan TW High
Iraq IQ Very High
Cuba CU Medium
Lebanon LB Very High
Greece GR High
So my question(s) are as follows:
1) Instead of manually passing in a series of OR-statements for country codes is there a better way to using Tbl2 as the matching "LIKE" driving the query?
2) Can you recommend a better way of comparing the output of the query (see Tbl1 example) and ensuring that multiple strings (Taipei, Taiwan, etc) are appropriately aggregated and bring back the correct 'RR' rating.
Thanks for taking the time to review this and respond.
Being new with SQL and SSRS and can do many things already, but I think I must be missing some basics and therefore bang my head on the wall all the time.
A report that is almost working, needs to have more results in it, based on conditions.
My working query so far is like this:
SELECT projects.project_number, project_phases.project_phase_id, project_phases.project_phase_number, project_phases.project_phase_header, project_phase_expensegroups.projectphase_expense_total, invoicerows.invoicerow_total
FROM projects INNER JOIN
project_phases ON projects.project_id = project_phases.project_id
LEFT OUTER JOIN
project_phase_expensegroups ON project_phases.project_phase_id = project_phase_expensegroups.project_phase_id
LEFT OUTER JOIN
invoicerows ON project_phases.project_phase_id = invoicerows.project_phase_id
WHERE ( projects.project_number = #iProjectNumber )
AND
( project_phase_expensegroups.projectphase_expense_total >0 )
The parameter is for selectionlist that is used to choose a project to the report.
How to have also records that have
( project_phase_expensegroups.projectphase_expense_total ) with value 0 but there might be invoices for that project phase?
Tried already to add another condition like this:
WHERE ( projects.project_number = #iProjectNumber )
AND
( project_phase_expensegroups.projectphase_expense_total > 0 )
OR
( invoicerows.invoicerow_total > 0 )
but while it gives some results - also the one with projectphase_expense_total with value 0, but the report is total mess.
So my question is: what am I doing wrong here?
There is a core problem with your query in that you are left joining to two tables, implying that rows may not exist, but then putting conditions on those tables, which will eliminate NULLs. That means your query is internally inconsistent as is.
The next problem is that you're joining two tables to project_phases that both may have multiple rows. Since these data are not related to each other (as proven by the fact that you have no join condition between project_phase_expensegroups and invoicerows, your query is not going to work correctly. For example, given a list of people, a list of those people's favorite foods, and a list of their favorite colors like so:
People
Person
------
Joe
Mary
FavoriteFoods
Person Food
------ ---------
Joe Broccoli
Joe Bananas
Mary Chocolate
Mary Cake
FavoriteColors
Person Color
------ ----------
Joe Red
Joe Blue
Mary Periwinkle
Mary Fuchsia
When you join these with links between Person <-> Food and Person <-> Color, you'll get a result like this:
Person Food Color
------ --------- ----------
Joe Broccoli Red
Joe Bananas Red
Joe Broccoli Blue
Joe Bananas Blue
Mary Chocolate Periwinkle
Mary Chocolate Fuchsia
Mary Cake Periwinkle
Mary Cake Fuchsia
This is essentially a cross-join, also known as a Cartesian product, between the Foods and the Colors, because they have a many-to-one relationship with each person, but no relationship with each other.
There are a few ways to deal with this in the report.
Create ExpenseGroup and InvoiceRow subreports, that are called from the main report by a combination of project_id and project_phase_id parameters.
Summarize one or the other set of data into a single value. For example, you could sum the invoice rows. Or, you could concatenate the expense groups into a single string separated by commas.
Some notes:
Please, please format your query before posting it in a question. It is almost impossible to read when not formatted. It seems pretty clear that you're using a GUI to create the query, but do us the favor of not having to format it ourselves just to help you
While formatting, please use aliases, Don't use full table names. It just makes the query that much harder to understand.
You need an extra parentheses in your where clause in order to get the logic right.
WHERE ( projects.project_number = #iProjectNumber )
AND (
(project_phase_expensegroups.projectphase_expense_total > 0)
OR
(invoicerows.invoicerow_total > 0)
)
Also, you're using a column in your WHERE clause from a table that is left joined without checking for NULLs. That basically makes it a (slow) inner join. If you want to include rows that don't match from that table you also need to check for NULL. Any other comparison besides IS NULL will always be false for NULL values. See this page for more information about SQL's three value predicate logic: http://www.firstsql.com/idefend3.htm
To keep your LEFT JOINs working as you intended you would need to do this:
WHERE ( projects.project_number = #iProjectNumber )
AND (
project_phase_expensegroups.projectphase_expense_total > 0
OR project_phase_expensegroups.project_phase_id IS NULL
OR invoicerows.invoicerow_total > 0
OR invoicerows.project_phase_id IS NULL
)
I found the solution and it was kind easy after all. I changed the only the second LEFT OUTER JOIN to INNER JOIN and left away condition where the query got only results over zero. Also I used SELECT DISTINCT
Now my report is working perfectly.
I have two tables that look roughly like this:
Airports
uniqueID | Name
0001 | Dallas
Runways
uniqueID | AirportID | Length
000101 | 0001 | 8000
I'm doing a join that looks like this:
SELECT Airports.Name, Runways.Length FROM Airports, Runways
WHERE Airports.uniqueID==Runways.AirportID
Obviously, each runway has exactly one airport, and each airport has 1..n runways.
For an airport with multiple runways, this gives me several rows, one for each runway at that airport.
I want a result set that contains ONLY the row for the longest runway, i.e. MAX(Length).
Sometimes, the Length is 0 for several runways in the database, because the source data is missing. In that case I only want one row with the Length = 0 obviously.
I've tried the approach laid out here: Inner Join table with respect to a maximum value but that's actually not helpful because that's like searching for the longest runway of all, not for the longest at one particular airport.
This seems to simple to be what you want but it seems to meet all the cases you've described...
SELECT A.Name, Max(R.Length)
FROM Airports A
INNER JOIN Runways R
on A.uniqueID=R.AirportID
Group by A.Name
This should give you the max runway for each airport.
If you need additional data elements then use the above as a inline view (Subquery within the joins) to limit the results sets to just those airports and their max runway.