So I have table X with let's say 50 rows of data in it and it is being joined to another table with only 2 rows in it. When I "normal" JOIN them together only the overlapping data will show, i.e. the two rows of data that are found in the larger collection of 50. In my case I want all 50 rows to persist so I use a LEFT JOIN and I am returned all 50 rows like planned.
Now I want to start adding and joining in other tables to get additional data about these rows and have them display togehter, whenever there is no data, I am fine with getting null. Now I'm adding a new JOIN and it's only going to find data for those two rows and not for the other 48, which is perfectly fine and I would like NULL to be displayed where no match is found. My problem is that rather than doing that, displaying null, it is instead removing the 48 rows will partial null data in their columns entirely and only showing the two that match, WHY?
I can provide code if needed, I thought this may be easier to understand.
If you inner join the third table, there are only 2 rows that can match (I assume you don't match on nulls). Only 2 rows from the second table have non-null values in them, so only those 2 can produce a result if you do an inner join with the third table.
You will need another left join in this case. This will return all the rows from the second table, including those that are all null (as the result of the first left join).
Related
I have two tables I am left joining together. The first tables has transnational level detail, causing the key I join to the second table to duplicate. When I left join the second table, the measure "company_spend" is highly inflated.
I need a way to keep only a single value of the duplicated data, and my thought was to run a distinct function on only those columns, but I am not seeing that Bigquery supports distinct functions on only a few columns, but not all.
SELECT UPPER(cwnextt.Current_Contract_Number) AS Current_Contract_Number,
UPPER(cwnextt.Replacement_Contract_Number) AS Replacement_Contract_Number,
UPPER(cwnextt.Current_Contract_Name) AS Current_Contract_Name,
UPPER(cwnextt.Supplier_Top_Parent_Entity_Code) AS Supplier_Top_Parent_Entity_Code,
UPPER(cwnextt.Supplier_Top_Parent_Name) AS Supplier_Top_Parent_Name,
UPPER(cwnextt.company_Entity_Code) AS company_Entity_Code,
UPPER(cwnextt.Facility_Name) AS Facility_Name,
smart.company_Spend AS companySpend
FROM `test_etl_field.contracts_with_member_entity_codes_test_view_2` cwnextt
--this table is what is causing the below table to duplicate,
--but I need all of this data AS well in its current format.
LEFT JOIN `test.trans_analysis` tsa
ON TRIM(UPPER(cwnextt.company_entity_code)) = TRIM(UPPER(tsa.company_entity_code))
AND TRIM(UPPER(cwnextt.Supplier_Top_Parent_Entity_Code)) = TRIM(UPPER(tsa.manufacturer_top_parent_entity_code))
AND TRIM(UPPER(cwnextt.Current_Contract_Name)) = TRIM(UPPER(tsa.contract_category))
AND cwnextt.spend_period_yyyyqmm = tsa.spend_period_yyyyqmm
--this table contains "company_spend" which is now duplicated
LEFT JOIN `test_etl_field.ecr_smart_data` smart
ON smart.company_entity_code = cwnextt.company_entity_code
AND (smart.contract_number = cwnextt.current_contract_number
OR smart.contract_number = cwnextt.replacement_contract_number)
AND smart.month_key = cwnextt.spend_period_yyyyqmm
If something can be created that will keep company_spend from duplicating on the second left join, that is what I am after.
Not sure to understand all the details of your problem but here's a fact from BigQuery doc :
SELECT DISTINCT
A SELECT DISTINCT statement discards duplicate rows
and returns only the remaining rows.
You can't apply DISTINCT on specific columns because it doesn't make sense. Let's say you have 4 columns and call DISTINCT on 3 columns, what is SQL supposed to do with the last one ?
You must tell SQL which value to keep for the remaining column and GROUP BY is the right solution here.
So if you want to:
Remove a column that has been duplicated : Just adjust your SELECT to get only the columns you want
Remove lines that have the same value in specific columns : I would suggest a GROUP BY on the targeted column and taking the aggregation you want (first, avg, sum or whatever) for the remaining ones.
Remove the value from a row if another row has the same : You may not want to do that. A row has to keep its value and you won't get it back. Besides, same problem, which row do you want to keep ?
Hope this helps ! Feel free to give clarification on your problem if you want more specific answers.
While I couldn't resolve this issue in SQL, I used Tableau via a FIXED LOD to aggregate the data passed duplicates so the end user could visualize the output with accuracy. Not ideal, but the SQL route wasn't make sense.
I'm trying to achieve 2 joins. If I run the 1st join alone it pulls 4 lots of results, which is correct. However when I add the 2nd join which queries the same reference table using the results from the select statement it pulls in additional results. Please see attached. The squared section should not be being returned
So I removed the 2nd join to try and explain better. See pic2. I'm trying to get another column which looks up InvolvedInternalID against the initial reference table IRIS.Practice.idvClient.
Your database is simply doing as you tell it. When you add in the second join (confusingly aliased as tb1 in a 3 table query) the database is finding matching rows that obey the predicate/truth statement in the ON part of the join
If you don't want those rows in there then one of two things must be the case:
1) The truth you specified in the ON clause is faulty; for example saying SELECT * FROM person INNER JOIN shoes ON person.age = shoes.size is faulty - two people with age 13 and two shoes with size 13 will produce 4 results, and shoe size has nothing to do with age anyway
2) There were rows in the table joined in that didn't apply to the results you were looking for, but you forgot to filter them out by putting some WHERE (or additional restriction in the ON) clause. Example, a table holds all historical data as well as current, and the current record is the one with a NULL in the DeletedOn column. If you forget to say WHERE deletedon IS NULL then your data will multiply as all the past rows that don't apply to your query are brought in
Don't alias tables with tbX, tbY etc.. Make the names meaningful! Not only do aliases like tbX have no relation to the original table name (so you encounter tbX, and then have to go searching the rest of the query to find where it's declared so you can say "ah, it's the addresses table") but in this case you join idvclient in twice, but give them unhelpful aliases like tb1, tb3 when really you should have aliased them with something that describes the relationship between them and the rest of the query tables
For example, ParentClient and SubClient or OriginatingClient/HandlingClient would be better names, if these tables are in some relationship with each other.
Whatever the purpose of joining this table in twice is, alias it in relation to the purpose. It may make what you've done wriong easier to spot, for example "oh, of course.. i'm missing a WHERE parentclient.type = 'parent'" (or WHERE handlingclient.handlingdate is not null etc..)
The first step to wisdom is by calling things their proper names
I have 2 tables I am trying to reconcile using SQL.
The first table has multiple instances of some records.
The second table only has one instance of each record.
I don't want to delete any duplicates out of the first table.
I need to know which records in the first table do not have any matches in the second table. What I have done so far keeps giving me the duplicate records as non-matching since one instance has already been matched. What am I missing?
Use a left outer join from the first table to the second and in your WHERE clause look for records where the second table join column(s) IS NULL.
If I join two tables together with left join and one of the tables is completely empty, I get a bunch of empty columns in the joined table.
Here is a fiddle demonstrating what I mean.
I would like the resulting joined table to not contain all those null columns
The number of columns that a query returns is fixed. It cannot change depending on whether a table is empty or not. So the answer is nope.
This query takes about a minute to give results:
SELECT MAX(d.docket_id), MAX(cus.docket_id) FROM docket d, Cashup_Sessions cus
Yet this one:
SELECT MAX(d.docket_id) FROM docket d UNION MAX(cus.docket_id) FROM Cashup_Sessions cus
gives its results instantly. I can't see what the first one is doing that would take so much longer - I mean they both simply check the same two lists of numbers for the greatest one and return them. What else could it be doing that I can't see?
I'm using jet SQL on an MS Access database via Java.
the first one is doing a cross join between 2 tables while the second one is not.
that's all there is to it.
The first one uses Cartesian product to form a source data, which means that every row from the first table is paired with each row from the second one. After that, it searches the source to find out the max values from the columns.
The second doesn't join tables. It just find max from the fist table and the max one from the second table and than returns two rows.
The first query makes a cross join between the tables before getting the maximums, that means that each record in one table is joined with every record in the other table.
If you have two tables with 1000 items each, you get a result with 1000000 items to go through to find the maximums.