I'm using .Net 4.0 and SQL server 2008 R2.
I'm running a big SQL select query which returns millions of results and takes up a long time to fully run.
Does anyone know how can I read only some of the results returned by the query without having to wait for the whole query to complete?
In other words, I want to read the first by 10,000 records chunks while the query still runs and getting the next results.
The most recommended and best option is to have a STANDBY server, restore the backup of the production database on that server, and then run the DBCC command. If the consistency checks run ok on the standby database, the production database should be ok as it is the source of the standby.
To retrieve large select by chunks, you need to use ORDER BY LIMIT. The syntax is as follows: SELECT *FROM yourTableName ORDER BY yourColumnName LIMIT 0,10; From the above syntax, you will get 10 rows from the table.
It depends in part on whether the query itself is streaming, or whether it does lots of work in temporary tables then (finally) starts returning data. You can't do much in the second scenario except re-write the query; however, in the first case an iterator block would usually help, i.e.
public IEnumerable<Foo> GetData() {
// not shown; building command etc
using(var reader = cmd.ExecuteReader()) {
while(reader.Read()) {
Foo foo = // not shown; materialize Foo from reader
yield return foo;
}
}
}
This is now a streaming iterator - you can foreach
over it and it will retrieve records live from the incoming TDS data without buffering all the data first.
If you (perhaps wisely) don't want to write your own materialization code, there are tools that will do this for you - for example, LINQ-to-SQL's ExecuteQuery<T>(tsql, args)
will do the above pain-free.
You'd need to use data paging.
SQL Server has the TOP clause (SQL TOP 10 a,b,c from d) and BETWEEN:
SELECT TOP 10000 a,b,c from d BETWEEN X and Y
Having this, I guess you'd be able of retrieving an N number of rows, do some partial processing, then load next N number of rows and so on.
This can be achieved by implementing a multithreaded solution: one will be retrieving results while the other will asynchronously wait for data and it'll be doing some processing.
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