I am trying to select a number of rows by the value of a column called ID. I know you can do this pretty easily by:
SELECT col1, col2, col3 FROM mytable WHERE id IN (1,2,3,4,5...)
However, what if there are a few million IDs I want to select and the IDs don't always have pattern (which means I can't use something like BETWEEN x AND y)? Does this select statement still work or is there better ways of doing so?
The actual application is this. Filters are specified by users, which is compared to some attributes of the records. From those filters, we create a subset of the data which is of interest to a particular user. There are about 30 million records each with roughly ~3000 attributes (which is stored in roughly 30 tables, but every table has ID as a primary key), so every time someone makes a query about their desired subset of records, we'd have to join many tables, apply those filters, and figure out what his subset looks like. In order to avoid joining many tables all the time, I thought maybe it's a better idea to join the tables once, figure out the id of the selected subset, and this way each time a new query is made, all we have to do is select the relevant columns of the rows that match the filtered ids.
This depends on the database and the interface you are using. For a few hundred or thousand values, no problem. But your question specifies millions. And that could start to get into limits on the length of the query -- either specified by the database, the tool you are using, or intermediate libraries.
If you have so many ids, I would strongly recommend that you load them into a table in the database with the id as the primary key. Then use join or exists to identify the rows in your table that match.
Often, such a list would be generated in the database anyway. In that case, you can use a subquery or CTE and just include that code in your final query.
Related
I've 250+ columns in customer table. As per my process, there should be only one row per customer however I've found few customers who are having more than one entry in the table
After running distinct on entire table for that customer it still returns two rows for me. I suspect one of column may be suffixed with space / junk from source tables resulting two rows of same information.
select distinct * from ( select * from customer_table where custoemr = '123' ) a;
Above query returns two rows. If you see with naked eye to results there is not difference in any of column.
I can identify which column is causing duplicates if I run query every time for each column with distinct but thinking that would be very manual task for 250+ columns.
This sounds like very dumb question but kind of stuck here. Please suggest if you have any better way to identify this, thank you.
Solving this one-time issue with sql is too much effort. Simply copy-paste to excel, transpose data into columns and use some simple function like "if a==b then 1 else 0".
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)
I am a newbie to sql. I have three tables mr1,mr2,mr3. Caseid is the primary keys in all these tables. I need to join all these table columns and display result.
Problem is that i dont know which join to use.
when i joined all these just like below query:
select mr1.col1,mr1.col2,mr2.col1,mr2.col2,mr3.col1,mr3.col2
from mr1,mr2,mr3
where mr1.caseid = mr2.caseid
and mr2.caseid = mr3.caseid;
it displays 4 records, eventhough the maximum number of records is two, which is in table mr2.
records are duplicated, can anyone help me in this regard?
Distinct will do it but it's not the correct approch.
You need to add another join (mr1.caseid = mr3.caseid) because mr2 and mr3 rows must be related to the same row in mr1, otherwise you end up with 2 pairs, onde for each tabled joined to your primary table (mr2).
First answer in SO, so forgive me if it wasn't that clear.
Your problem is that your tables are in a one-to many relationship. When you join them, it is expected that the number of rows will go up unless you take steps to limit the records returned. How to fix depends on the meaning of the data.
If all the fields are exactly the same, then adding DISTINCT will fix the problem. However, it may be faster, depending on the size of the tables and the number of records you are returning, to use a derived table to limit the records in the join to only one from the table with multiple records.
If at least one of the fields is different however, then you need to know the business rule that will allow you to pick the correct record. It might be accomplished by adding a where clause or by using an aggregate function and group by or even both. This really depends on the meaning of the result set which is why you need to ask further question in your own organization as they are the only ones who will know which of the multiple records is the correct one to pick from the perspectives of the people who will be using the results of the query. Further, the business might actually want to see all of the records and you have no problem at all.
I have a very large database I would like to split up into tables. I would like to make it so when I run a distinct, it will make a table for every distinct name. The name of the table will be the data in one of the fields.
EX:
A --------- Data 1
A --------- Data 2
B --------- Data 3
B --------- Data 4
would result in 2 tables, 1 named A and another named B. Then the entire row of data would be copied into that field.
select distinct [name] from [maintable]
-make table for each name
-select [name] from [maintable]
-copy into table name
-drop row from [maintable]
Any help would be great!
I would advise you against this.
One solution is to create indexes, so you can access the data quickly. If you have only a handful of names, though, this might not be particularly effective because the index values would have select almost all records.
Another solution is something called partitioning. The exact mechanism differs from database to database, but the underlying idea is the same. Different portions of the table (as defined by name in your case) would be stored in different places. When a query is looking only for values for a particular name, only that data gets read.
Generally, it is bad design to have multiple tables with exactly the same data columns. Here are some reasons:
Adding a column, changing a type, or adding an index has to be done times instead of one time.
It is very hard to enforce a primary key constraint on a column across the tables -- you lose the primary key.
Queries that touch more than one name become much more complicated.
Insertions and updates are more complex, because you have to first identify the right table. This often results in overuse of dynamic SQL for otherwise basic operations.
Although there may be some simplifications (security comes to mind), most databases have other mechanisms that are superior to splitting the data into separate tables.
what you want is
CREATE TABLE new_table
AS (SELECT .... //the data that you want in this table);