I have the following tables:
In table 2 (yellow looking fields), the first field is part of the following:
name1 RECORD NULLABLE
name1. name2 RECORD REPEATED
name1.name2. date_inserted TIMESTAMP NULLABLE
As you can see the last (sub-row?) of the row 25 is greyed because it is part of the repeated record name1.name2
I am trying to join table 2, with table 1(orange looking fields) on another field. I have 0 experience with records or repeated records but using FLATTEN() I managed to join them.
The problem is, I noticed that some dates from the 2nd after the join return NULL although there aren't any NULLS before it. So since I can't figure out what the greyed cells are I guess I am doing something wrong.
All this sums up to: How can I totally flatten all tables that I want to use so that there won't be any records at all and so I can go through the data with simple SQL statements? Please provide an example as well. Looking for something generic.
How can I totally flatten all tables that I want to use so that there won't be any records at all and so I can go through the data with simple SQL statements?
It really depends on the schemas you are working with. You can preprocess them, flatten the arrays and rename the structs fields, then use that as your base table to work with simple SQL statements
For your scenario, you can start by flattening the table 2, name2 column like this
SELECT
name2.date_inserted -- Add additional fields you want on the result
FROM table2, table2.name1.name2
You can do CROSS JOIN and LEFT JOIN to further adjust your results.
Please provide an example as well. Looking for something generic.
I'm not sure about a generic approach, since each schema would probably have distinct requirements. The key concept is to know how to flatten arrays and how to query struct with arrays and arrays of structs
You can find plenty examples in that documentation
Related
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 am trying to calculate hours flowing in and out of a cost center. When the cost center lends out an employee for an hour it's +1 and when they borrow an employee for an hour it's -1.
Right now I'm using a query that says
select
columns
from dbo.table
where EmployeeCostCenter <> ProjectCostCenter
So when ProjectCostCenter = ID_CostCenter it returns +HoursQuantity.
Then I update ID_CostCenter = EmployeeCostCenter then where ID_CostCenter = EmployeeCostCenter to take -HoursQuantity.
That works fine. The problem is when I import it to Spotfire I can't filter on the main table even after I added the table relations. Can anyone explain why?
I can upload the actual code if needed, but I use 4 queries and a couple of them are quite lengthy. The main table, a temp table to calculate incoming hours, and a temp table to calculate outgoing hours are the only ones involved in this problem I think.
(moved to answer to avoid lengthy discussion)
Essentially, data relations are used to populate filtering / marking between different data-sets. Just like in RDBMS, the relation is what Spotfire uses as the link between dataset. Essentially it's the same as the column or columns you join on. Thus, any column that you wish to filter in TableA and have the result set limited in TableB (or visa versa) must be a relation.
Column matches aren't related columns, but are associated for aggregations, category axis, etc within each visualization. So if TableA has "amount" and TableB has "amount debit" and you wanted to use both of these in an expression, say Sum([TableA].[amount],[TableB].[amount debit]), they would need to be matched in order to not produce erroneous results.
Lastly, once you set up your relations, you should check your filter panel to set up how you want the filtering to work. You can have the rows included, excluded, or ignored all together. Here is a link explaining that.
I'm having a table with an id and a name.
I'm getting a list of id's and i need their names.
In my knowledge i have two options.
Create a forloop in my code which executes:
SELECT name from table where id=x
where x is always a number.
or I'm write a single query like this:
SELECT name from table where id=1 OR id=2 OR id=3
The list of id's and names is enormous so i think you wouldn't want that.
The problem of id's is the id is not always a number but a random generated id containting numbers and characters. So talking about ranges is not a solution.
I'm asking this in a performance point of view.
What's a nice solution for this problem?
SQLite has limits on the size of a query, so if there is no known upper limit on the number of IDs, you cannot use a single query.
When you are reading multiple rows (note: IN (1, 2, 3) is easier than many ORs), you don't know to which ID a name belongs unless you also SELECT that, or sort the results by the ID.
There should be no noticeable difference in performance; SQLite is an embedded database without client/server communication overhead, and the query does not need to be parsed again if you use a prepared statement.
A "nice" solution is using the INoperator:
SELECT name from table where id in (1,2,3)
Also, the IN operator is syntactic sugar built for exactly this purpose..
SELECT name from table where id IN (1,2,3,4,5,6.....)
Hoping that you are getting the list of ID's on which you have to perform a query for names as input temp table #InputIDTable,
SELECT name from table WHERE ID IN (SELECT id from #InputIDTable)
Suppose I have one table A, with 10 fields. And Table B, with 5 fields.
B links to A via a column named "key", that exists both in A, and in B, with the same name ("key").
I am generating a generic piece of SQL, that queries from a main table A, and receives a table name parameter to join to, and select all A fields + B.
In this case, I will get all the 15 fields I want, or more precisely - 16, because I get "key" twice, once from A and once from B.
What I want is to get only 15 fields (all fields from the main table + the ones existing in the generic table), without getting "key" twice.
Of course I can explicit the fields I want in the SELECT itself, but that thwarts my very objective of building a generic SQL.
It really depends on which RDBMS you're using it against, and how you're assembling your dynamic SQL. For instance, if you're using Oracle and it's a PL/SQL procedure putting together your SQL, you're presumably querying USER_TAB_COLS or something like that. In that case, you could get your final list of columns names like
SELECT DISTINCT(column_name)
FROM user_tab_cols
WHERE table_name IN ('tableA', 'tableB');
but basically, we're going to need to know a lot more about how you're building your dynamic SQL.
Re-thinking about what I asked makes me conclude that this is not plausible. Selecting columns in a SELECT statement picks the columns we are interested in from the list of tables provided. In cases where the same column name exists in more than one of the tables involved, which are the cases my question is addressing, it would, ideally, be nice if the DB engine could return a unique list of fields - BUT - for that it would have to decide itself which column (and from which table) to choose, from all the matches - which is something that the DB cannot do, because it is solely dependent in the user's choice.
I've set up a view which combines all the data across several tables. Is there a way to write this so that only columns which contain non-null data are displayed, and those columns which contain all NULL values are not included?
ADDED:
Sorry, still studying and working on my first big project so every day seems to be a new experience at the minute. I haven't been very clear, and that's partly because I'm not sure I'm going about things the right way! The client is an academic library, and the database records details of specific collections. The view I mentioned is to display all the data held about an item, so it is bringing together tables on publication, copy, author, publisher, language and so on. A small number of items in the collection are papers, so have additional details over and above the standard bibliographic details. What I didn't want was a user to get all the empty fields relating to papers if what was returned only consisted of books, therefore the paper table fields were all null. So I thought perhaps there would be a way to not show these. Someone has commented that this is the job of the client application rather than the database itself, so I can leave this until I get to that phase of the project.
There is no way to do this in sql.
CREATE VIEW dbo.YourView
AS
SELECT (list of fields)
FROM dbo.Table1 t1
INNER JOIN dbo.Table2 t2 ON t1.ID = t2.FK_ID
WHERE t1.SomeColumn IS NOT NULL
AND t2.SomeOtherColumn IS NOT NULL
In your view definition, you can include WHERE conditions which can exclude rows that have certain columns that are NULL.
Update: you cannot really filter out columns - you define the list of columns that are part of your view in your view definition, and this list is fixed and cannot be dynamically changed......
What you might be able to do is us a ISNULL(column, '') construct to replace those NULLs with an empty string. Or then you need to handle excluding those columns in your display front end - not in the SQL view definition...
The only thing I see you could do is make sure to select only those columns from the view that you know aren't NULL:
SELECT (list of non-null fields) FROM dbo.YourView
WHERE (column1 IS NOT NULL)
and so forth - but there's no simple or magic way to select all columns that aren't NULL in one SELECT statement...
You cannot do this in a view, but you can do it fairly easily using dynamic SQL in a stored procedure.
Of course, having a schema which shifts is not necessarily good for clients who consume the data, but it can be efficient if you have very sparse data AND the consuming client understands the varying schema.
If you have to have a view, you can put a "header" row in your view which you can inspect client-side on the first row in your loop to see if you want to not bother with the column in your grid or whatever, you can do something like this:
SELECT * FROM (
-- This is the view code
SELECT 'data' as typ
,int_col
,varchar_col
FROM TABLE
UNION ALL
SELECT 'hdr' as typ
-- note that different types have to be handled differently
,CASE WHEN COUNT(int_col) = 0 THEN NULL ELSE 0 END
,CASE WHEN COUNT(varchar_col) = 0 THEN NULL ELSE '' END
FROM TABLE
) AS X
-- have to get header row first
ORDER BY typ DESC -- add other sort criteria here
If we're reading your question right, there won't be a way to do this in SQL. The output of a view must be a relation - in (over-)simplified terms, it must be rectangular. That is, each row must have the same number of columns.
If you can tell us more about your data and give us some idea of what you want to do with the output, we can perhaps offer more positive suggestions.
In general, add a WHERE clause to your query, e.g.
WHERE a IS NOT NULL AND b IS NOT NULL AND c IS NOT NULL
Here, a b c are your column names.
If you are joining tables together on potentially NULL columns, then use an INNER JOIN, and NULL values will not be included.
EDIT: I may have misunderstood - the above filters out rows, but you may be asking to filter out columns, e.g. you have several columns and you only want to display columns that contain at least one null value across all the rows you are returning. Using dynamic SQL offers a solution, since the set columns varies depending upon your data.
Here's a SQL query that builds another SQL query containing the appropriate columns. You could run this query, and then submit it's result as another query. It assumes 'pk' is some column that is always non-null, e.g. a primary key - this means we can prefix additional row names with a comma.
SELECT CONCAT("SELECT pk"
CASE (count(columnA)) WHEN 0 THEN '' ELSE ',columnA' END,
CASE (count(columnB)) WHEN 0 THEN '' ELSE ',columnB' END,
// etc..
' FROM (YourQuery) base')
FROM
(YourQuery) As base
The query works using Count(column) - the aggregate function ignores NULL values, and so returns 0 for a column consisting entirely of NULLs. The query builder assumes that YourQuery uses aliases to ensure there no duplicate column names.
While you cant put this into a view, you could wrap it up as a stored procedure that copies the data to another table - the result table. You may also set up a trigger so that the result table is updated whenever the base tables change.
I suspect what's going on is that an end user is running CrystalReports and complaining about all the empty columns that have to be removed manually.
It would actually be possible to create a stored procedure that would create a view on the fly, leaving out dataless columns. But then you would have to run this proc before using the view.
Is that acceptable?