For sync purposes, I am trying to get a subset of the existing objects in a table.
The table has two fields, [Group] and Member, which are both stringified Guids.
All rows together may be to large to fit into a datatable; I already encountered an OutOfMemory exception. But I have to check that everything I need right now is in the datatable. So I take the Guids I want to check (they come in chunks of 1000), and query only for the related objects.
So, instead of filling my datatable once with all
SELECT * FROM Group_Membership
I am running the following SQL query against my SQL database to get related objects for one thousand Guids at a time:
SELECT *
FROM Group_Membership
WHERE
[Group] IN (#Guid0, #Guid1, #Guid2, #Guid3, #Guid4, #Guid5, ..., #Guid999)
The table in question now contains a total of 142 entries, and the query already times out (CommandTimeout = 30 seconds). On other tables, which are not as sparsely populated, similar queries don't time out.
Could someone shed some light on the logic of SQL Server and whether/how I could hint it into the right direction?
I already tried to add a nonclustered index on the column Group, but it didn't help.
I'm not sure that WHERE IN will be able to maximally use an index on [Group], or if at all. However, if you had a second table containing the GUID values, and furthermore if that column had an index, then a join might perform very fast.
Create a temporary table for the GUIDs and populate it:
CREATE TABLE #Guids (
Guid varchar(255)
)
INSERT INTO #Guids (Guid)
VALUES
(#Guid0, #Guid1, #Guid2, #Guid3, #Guid4, ...)
CREATE INDEX Idx_Guid ON #Guids (Guid);
Now try rephrasing your current query using a join instead of a WHERE IN (...):
SELECT *
FROM Group_Membership t1
INNER JOIN #Guids t2
ON t1.[Group] = t2.Guid;
As a disclaimer, if this doesn't improve the performance, it could be because your table has low cardinality. In such a case, an index might not be very effective.
Related
I have a simple DB table with ONLY 5 columns with no primary key having 7 billion+(7,50,01,771) data. yes, you read it correctly. it has one cluster index.
DB table columns
Cluster index
if I write a simple select query to get data, it is taking 7-8 minutes to return data. now, you get my next question. what are the techniques that I can apply to this DB table? So that I can get data in time.
in the actual scenario, where I am using this table have join with 2 temp tables that have WHERE clause and filtered data. Please find below my query for reference.
SELECT dt.ZipFrom, dt.ZipTo, dt.Total_time, sz.storelocation, sz.AcctShip, sz.Licensee,sz.Entity from #Zips z INNER join DriveTime_ZIPtoZIP dt on zipFrom = z.zip INNER join #storeZips sz on ZipTo = sz.zip order by z.zip desc, total_time asc
Thanks
You can index according to the where conditions in the query. However, this comes at a cost: Storage.
Order by statement is also important. If you have to use order by in your query, you can also index accordingly.
But do not forget, the cost of indexing ...
I have an ETL process (CSV to SQL database) that runs daily, but the data in the source sometimes changes, so I want to have it run again the next day with an updated file.
How do I write a SQL statement to find all the differences?
For example, let's say Table_1 has a composite PRIMARY KEY consisting of FK_1, FK_2 and FK_3.
Do I do this in SQL or in the ETL process?
Thanks.
Edit
I realize now this question is too broad. Disregard.
You can use EXCEPT to find which are the IDs which are missing. For example:
SELECT FK_1, FK_2, FK_2
FROM new_data_table
EXCEPT
SELECT FK_1, FK_2, FK_2
FROM current_data_table;
It will be better (in performance prospective) to materialized these IDs and then to join this new table to the new_data_table in order to insert all of the columns.
If you need to do this in one query, you can use simple LEFT JOIN. For example:
INSERT INTO current_data_table
SELECT A.*
FROM new_data_table A
LEFT JOIN current_data_table B
ON A.FK_1 = B.FK_1
AND A.FK_2 = B.FK_2
AND A.FK_3 = B.FK_3
WHRE B.[FK_1] IS NULL;
The idea is to get all records in the new_data_table for which, there is no match in the current_data_table table (WHRE B.[FK_1] IS NULL).
I'm using Azure's SQL Database & MS SQL Server Management Studio and I wondering if its possible to create a self-referencing table that maintains itself.
I have three tables: Race, Runner, Names. The Race table includes the following columns:
Race_ID (PK)
Race_Date
Race_Distance
Number_of_Runners
The second table is Runner. Runner contains the following columns:
Runner_Id (PK)
Race_ID (Foreign Key)
Name_ID
Finish_Position
Prior_Race_ID
The Names Table includes the following columns:
Full Name
Name_ID
The column of interest is Prior_Race_ID in the Runner Table. I'd like to automatically populate this field via a Trigger or Stored Procedure, but I'm not sure if its possible to do so and how to go about it. The goal would be to be able to get all a runners races very quickly and easily by traversing the Prior_Race_ID field.
Can anyone point me to a good resource or references that explains if and how this is achievable. Also, if there is a preferred approach to achieving my objective please do share that.
Thanks for your input.
Okay, so we want, for each Competitor (better name than Names?), to find their two most recent races. You'd write a query like this:
SELECT
* --TODO - Specific columns
FROM
(SELECT
*, --TODO - Specific columns
ROW_NUMBER() OVER (PARTITION BY n.Name_ID ORDER BY r.Race_Date DESC) rn
FROM
Names n
inner join
Runners rs
on
n.Name_ID = rs.Name_ID
inner join
Races r
on
rs.Race_ID = r.Race_ID
) t
WHERE
t.rn in (1,2)
That should produce two rows per competitor. If needed, you can then PIVOT this data if you want a single row per competitor, but I'd usually leave that up to the presentation layer, rather than do it in SQL.
And so, no, I wouldn't even have a Prior_Race_ID column. As a general rule, don't store data that can be calculated - that just introduces opportunities for that data to be incorrect compared to the base data.
run the following sql(The distinct here is to avoid that a runner has more than one race at a same day):
update runner r1
set r1.prior_race_id =
(
select distinct race.race_id from runner, race where runner.race_id = race.race_id and runner.runner_id = r1.runner_id group by runner.runner_id having race.race_date = max(race.race_date)
)
I have benefited from this website for a long time now. This is my first question on the site. It is regarding performance tuning a reporting query. Here it goes.
1.
SELECT Count(b1.primkey)
from tableA b1 --WITH (NOLOCK)
join tableA b2 --WITH (NOLOCK)
on b1.email = b2.email
and DateDiff(day, b2.BookedDate , b1.BookedDate) > 1
tableA has around 7 million rows. Email is a varchar(100) field. Bookeddate is a datetime field. primkey is a primary key column that is an int.
My purpose of writing this query is to find out the count entries that have same email ids but have come in one day late. This query take about 45 minutes to run. I really want to reduce the time it takes to execute.
Since this is for reporting, i tried in vain to use --WITH (NOLOCK) option to improve the read time. I have a column store index on tableA and I know that it is being used by the SQL optimizer - can see in the execution plan. I am using SQL Server 2012.
Can someone tell me in such a case, what would be better? Using a nonclustered index on email or a nonclustered columnstore index on tableA?
Please help me.
Your query is relatively complex. You are essentially joining two tables that have 7 million records each on a column that is not unique.
How about the following query instead:
select Email
from TableA
group by Email
having MAX(BookedDate) > MIN(BookedDate) + 1
Also make sure you have an index with Email and BookedDate.
Hope this helps.
You have 3 options here:
Create clustered index on email field at least for a larger table.
But I suppose there are other queries running on these tables, and
clustered index is needed on other fields
Move emails to another table, and store email id's in TableA and
TableB; join on int field would be much faster than on varchar
fields
Create indexes on email fields with included columns BookedDate (no
need to include primkey, you can count on another field, or count(*). Code: create index idx_email on TableA include(BoodedDate)
I think that third option is the one you should go with. There's not much work to be done, and there will be great performance gain. The only problem is that index on varchar field will take a lot of space and impact insert/update operations; but you said that this is a reporting db, so I think you can allow that.
Well, I have a table which is 40,000,000+ records but when I try to execute a simple query, it takes ~3 min to finish execution. Since I am using the same query in my c# solution, which it needs to execute over 100+ times, the overall performance of the solution is deeply hit.
This is the query that I am using in a proc
DECLARE #Id bigint
SELECT #Id = MAX(ExecutionID) from ExecutionLog where TestID=50881
select #Id
Any help to improve the performance would be great. Thanks.
What indexes do you have on the table? It sounds like you don't have anything even close to useful for this particular query, so I'd suggest trying to do:
CREATE INDEX IX_ExecutionLog_TestID ON ExecutionLog (TestID, ExecutionID)
...at the very least. Your query is filtering by TestID, so this needs to be the primary column in the composite index: if you have no indexes on TestID, then SQL Server will resort to scanning the entire table in order to find rows where TestID = 50881.
It may help to think of indexes on SQL tables in the same way as those you'd find in the back of a big book that are hierarchial and multi-level. If you were looking for something, then you'd manually look under 'T' for TestID then there'd be a sub-heading under TestID for ExecutionID. Without an index entry for TestID, you'd have to read through the entire book looking for TestID, then see if there's a mention of ExecutionID with it. This is effectively what SQL Server has to do.
If you don't have any indexes, then you'll find it useful to review all the queries that hit the table, and ensure that one of those indexes is a clustered index (rather than non-clustered).
Try to re-work everything into something that works in a set based manner.
So, for instance, you could write a select statement like this:
;With OrderedLogs as (
Select ExecutionID,TestID,
ROW_NUMBER() OVER (PARTITION BY TestID ORDER By ExecutionID desc) as rn
from ExecutionLog
)
select * from OrderedLogs where rn = 1 and TestID in (50881, 50882, 50883)
This would then find the maximum ExecutionID for 3 different tests simultaneously.
You might need to store that result in a table variable/temp table, but hopefully, instead, you can continue building up a larger, single, query, that processes all of the results in parallel.
This is the sort of processing that SQL is meant to be good at - don't cripple the system by iterating through the TestIDs in your code.
If you need to pass many test IDs into a stored procedure for this sort of query, look at Table Valued Parameters.