I have a table with 20 billion rows. Table does not have any indexes as it was created on fly for doing bulk insert operation. The table is being used in a stored procedure which does the following operation
Delete A
from master a
inner join (Select distinct Col from TableB ) b
on A.Col = B.Col
Insert into master
Select *
from tableB
group by col1,col2,col3
TableB is the one which has 20 billion rows. I don't want to execute SP directly because it might take days to complete the execution. Master is also a huge table and has clustered index on Col
Can i pass chunks of rows to the stored procedure and perform the operation.This might reduce the log file growth. If yes how can i do that
Should i create clustered index on the table and execute the SP which might be little faster but then again i think creating CI on a huge table might take 10 hours to complete.
Or is there any way to perform this operation fast
I've used a method similar to this one. I'd recommend putting your DB into Bulk Logged recovery mode instead of Full recovery mode if you can.
Blog entry reproduced below to future proof it.
Below is a technique used to transfer a large amount of records from
one table to another. This scales pretty well for a couple reasons.
First, this will not fill up the entire log prior to committing the
transaction. Rather, it will populate the table in chunks of 10,000
records. Second, it’s generally much quicker. You will have to play
around with the batch size. Sometimes it’s more efficient at 10,000,
sometimes 500,000, depending on the system.
If you do not need to insert into an existing table and just need a
copy of the table, it is better to do a SELECT INTO. However for this
example, we are inserting into an existing table.
Another trick you should do is to change the recovery model of the
database to simple. This way, there will be much less logging in the
transaction log.
The WITH (TABLOCK) below only works in SQL 2008.
DECLARE #BatchSize INT = 10000
WHILE 1 = 1
BEGIN
INSERT INTO [dbo].[Destination] --WITH (TABLOCK) -- Uncomment for 2008
(
FirstName
,LastName
,EmailAddress
,PhoneNumber
)
SELECT TOP(#BatchSize)
s.FirstName
,s.LastName
,s.EmailAddress
,s.PhoneNumber
FROM [dbo].[SOURCE] s
WHERE NOT EXISTS (
SELECT 1
FROM dbo.Destination
WHERE PersonID = s.PersonID
)
IF ##ROWCOUNT < #BatchSize BREAK
END
With the above example, it is important to have at least a non
clustered index on PersonID in both tables.
Another way to transfer records is to use multiple threads. Specifying
a range of records as such:
INSERT INTO [dbo].[Destination]
(
FirstName
,LastName
,EmailAddress
,PhoneNumber
)
SELECT TOP(#BatchSize)
s.FirstName
,s.LastName
,s.EmailAddress
,s.PhoneNumber
FROM [dbo].[SOURCE] s
WHERE PersonID BETWEEN 1 AND 5000
GO
INSERT INTO [dbo].[Destination]
(
FirstName
,LastName
,EmailAddress
,PhoneNumber
)
SELECT TOP(#BatchSize)
s.FirstName
,s.LastName
,s.EmailAddress
,s.PhoneNumber
FROM [dbo].[SOURCE] s
WHERE PersonID BETWEEN 5001 AND 10000
For super fast performance however, I’d recommend using SSIS.
Especially in SQL Server 2008. We recently transferred 17 million
records in 5 minutes with an SSIS package executed on the same server
as the two databases it transferred between.
SQL Server 2008 SQL Server 2008 has made changes with regards to it’s
logging mechanism when inserting records. Previously, to do an insert
that was minimally logged, you would have to perform a SELECT.. INTO.
Now, you can perform a minimally logged insert if you can lock the
table you are inserting into. The example below shows an example of
this. The exception to this rule is if you have a clustered index on
the table AND the table is not empty. If the table is empty and you
acquire a table lock and you have a clustered index, it will be
minimally logged. However if you have data in the table, the insert
will be logged. Now if you have a non clustered index on a heap and
you acquire a table lock then only the non clustered index will be
logged. It is always better to drop indexes prior to inserting
records.
To determine the amount of logging you can use the following statement
SELECT * FROM ::fn_dblog(NULL, NULL)
Credit for above goes to Derek Dieter at SQL Server Planet.
If you're dead set on passing a table to your stored procedure, you can pass a table-valued parameter to a stored procedure in SQL Server 2008. You might have better luck with some other approaches suggested, like partitioning. Select distinct on a table with 20 billion rows might be part of the problem. I wonder if some very basic tuning wouldn't help, too:
Delete A
from master a
where exists (select 1 from TableB b where b.Col = a.Col)
Related
Consider two very large tables, Table A with 20 million rows in, and Table B which has a large overlap with TableA with 10 million rows. Both have an identifier column and a bunch of other data. I need to move all items from Table B into Table A updating where they already exist.
Both table structures
- Identifier int
- Date DateTime,
- Identifier A
- Identifier B
- General decimal data.. (maybe 10 columns)
I can get the items in Table B that are new, and get the items in Table B that need to be updated in Table A very quickly, but I can't get an update or a delete insert to work quickly. What options are available to merge the contents of TableB into TableA (i.e. updating existing records instead of inserting) in the shortest time?
I've tried pulling out existing records in TableB and running a large update on table A to update just those rows (i.e. an update statement per row), and performance is pretty bad, even with a good index on it.
I've also tried doing a one shot delete of the different values out of TableA that exist in TableB and performance of the delete is also poor, even with the indexes dropped.
I appreciate that this may be difficult to perform quickly, but I'm looking for other options that are available to achieve this.
Since you deal with two large tables, in-place updates/inserts/merge can be time consuming operations. I would recommend to have some bulk logging technique just to load a desired content to a new table and the perform a table swap:
Example using SELECT INTO:
SELECT *
INTO NewTableA
FROM (
SELECT * FROM dbo.TableB b WHERE NOT EXISTS (SELECT * FROM dbo.TableA a WHERE a.id = b.id)
UNION ALL
SELECT * FROM dbo.TableA a
) d
exec sp_rename 'TableA', 'BackupTableA'
exec sp_rename 'NewTableA', 'TableA'
Simple or at least Bulk-Logged recovery is highly recommended for such approach. Also, I assume that it has to be done out of business time since plenty of missing objects to be recreated on a new tables: indexes, default constraints, primary key etc.
A Merge is probably your best bet, if you want to both inserts and updates.
MERGE #TableB AS Tgt
USING (SELECT * FROM #TableA) Src
ON (Tgt.Identifier = SRc.Identifier)
WHEN MATCHED THEN
UPDATE SET Date = Src.Date, ...
WHEN NOT MATCHED THEN
INSERT (Identifier, Date, ...)
VALUES (Src.Identifier, Src.Date, ...);
Note that the merge statement must be terminated with a ;
Hi consider there is an INSERT statement running on a table TABLE_A, which takes a long time, I would like to see how has it progressed.
What I tried was to open up a new session (new query window in SSMS) while the long running statement is still in process, I ran the query
SELECT COUNT(1) FROM TABLE_A WITH (nolock)
hoping that it will return right away with the number of rows everytime I run the query, but the test result was even with (nolock), still, it only returns after the INSERT statement is completed.
What have I missed? Do I add (nolock) to the INSERT statement as well? Or is this not achievable?
(Edit)
OK, I have found what I missed. If you first use CREATE TABLE TABLE_A, then INSERT INTO TABLE_A, the SELECT COUNT will work. If you use SELECT * INTO TABLE_A FROM xxx, without first creating TABLE_A, then non of the following will work (not even sysindexes).
Short answer: You can't do this.
Longer answer: A single INSERT statement is an atomic operation. As such, the query has either inserted all the rows or has inserted none of them. Therefore you can't get a count of how far through it has progressed.
Even longer answer: Martin Smith has given you a way to achieve what you want. Whether you still want to do it that way is up to you of course. Personally I still prefer to insert in manageable batches if you really need to track progress of something like this. So I would rewrite the INSERT as multiple smaller statements. Depending on your implementation, that may be a trivial thing to do.
If you are using SQL Server 2016 the live query statistics feature can allow you to see the progress of the insert in real time.
The below screenshot was taken while inserting 10 million rows into a table with a clustered index and a single nonclustered index.
It shows that the insert was 88% complete on the clustered index and this will be followed by a sort operator to get the values into non clustered index key order before inserting into the NCI. This is a blocking operator and the sort cannot output any rows until all input rows are consumed so the operators to the left of this are 0% done.
With respect to your question on NOLOCK
It is trivial to test
Connection 1
USE tempdb
CREATE TABLE T2
(
X INT IDENTITY PRIMARY KEY,
F CHAR(8000)
);
WHILE NOT EXISTS(SELECT * FROM T2 WITH (NOLOCK))
LOOP:
SELECT COUNT(*) AS CountMethod FROM T2 WITH (NOLOCK);
SELECT rows FROM sysindexes WHERE id = OBJECT_ID('T2');
RAISERROR ('Waiting for 10 seconds',0,1) WITH NOWAIT;
WAITFOR delay '00:00:10';
SELECT COUNT(*) AS CountMethod FROM T2 WITH (NOLOCK);
SELECT rows FROM sysindexes WHERE id = OBJECT_ID('T2');
RAISERROR ('Waiting to drop table',0,1) WITH NOWAIT
DROP TABLE T2
Connection 2
use tempdb;
--Insert 2000 * 2000 = 4 million rows
WITH T
AS (SELECT TOP 2000 'x' AS x
FROM master..spt_values)
INSERT INTO T2
(F)
SELECT 'X'
FROM T v1
CROSS JOIN T v2
OPTION (MAXDOP 1)
Example Results - Showing row count increasing
SELECT queries with NOLOCK allow dirty reads. They don't actually take no locks and can still be blocked, they still need a SCH-S (schema stability) lock on the table (and on a heap it will also take a hobt lock).
The only thing incompatible with a SCH-S is a SCH-M (schema modification) lock. Presumably you also performed some DDL on the table in the same transaction (e.g. perhaps created it in the same tran)
For the use case of a large insert, where an approximate in flight result is fine, I generally just poll sysindexes as shown above to retrieve the count from metadata rather than actually counting the rows (non deprecated alternative DMVs are available)
When an insert has a wide update plan you can even see it inserting to the various indexes in turn that way.
If the table is created inside the inserting transaction this sysindexes query will still block though as the OBJECT_ID function won't return a result based on uncommitted data regardless of the isolation level in effect. It's sometimes possible to get around that by getting the object_id from sys.tables with nolock instead.
Use the below query to find the count for any large table or locked table or being inserted table in seconds . Just replace the table name which you want to search.
SELECT
Total_Rows= SUM(st.row_count)
FROM
sys.dm_db_partition_stats st
WHERE
object_name(object_id) = 'TABLENAME' AND (index_id < 2)
For those who just need to see the record count while executing a long running INSERT script, I found you can see the current record count through SSMS by right clicking on the destination database table, -> Properties -> Storage, then view the "Row Count" value like so:
Close window and repeat to see the updated record count.
Let we have a table of payments having 35 columns with a primary key (autoinc bigint) and 3 non-clustered, non-unique indeces (each on one int column).
Among the table's columns we have two datetime fields:
payment_date datetime NOT NULL
edit_date datetime NULL
The table has about 1 200 000 rows.
Only ~1000 of rows have edit_date column = null.
9000 of rows have edit_date not null and not equal to payment_date
Others have edit_date=payment_date
When we run the following query 1:
select top 1 *
from payments
where edit_date is not null and (payment_date=edit_date or payment_date<>edit_date)
order by payment_date desc
server needs a couple of seconds to do it. But if we run query 2:
select top 1 *
from payments
where edit_date is not null
order by payment_date desc
the execution ends up with The log file for database 'tempdb' is full. Back up the transaction log for the database to free up some log space.
If we replace * with some certain column, see query 3
select top 1 payment_date
from payments
where edit_date is not null
order by payment_date desc
it also finishes in a couple of seconds.
Where is the magic?
EDIT
I've changed query 1 so that it operates over exactly the same number of rows as the 2nd query. And still it returns in a second, while query 2 fills tempdb.
ANSWER
I followed the advice to add an index, did this for both date fields - everything started working quick, as expected. Though, the question was - why in this exact situation sql server behave differently on similar queries (query 1 vs query 2); I wanted to understand the logic of the server optimization. I would agree if both queries did used tempdb similarly, but they didn't....
In the end I mark as the answer the first one, where I saw the must-be symptoms of my problem and the first, as well, thoughts on how to avoid this (i.e. indeces)
This is happening cause certain steps in an execution plan can trigger writes to tempdb in particular certain sorts and joins involving lots of data.
Since you are sorting a table with a boat load of columns, SQL decides it would be crazy to perform the sort alone in temp db without the associated data. If it did that it would need to do a gazzilion inefficient bookmark lookups on the underlying table.
Follow these rules:
Try to select only the data you need
Size tempdb appropriately, if you need to do crazy queries that sort a gazzilion rows, you better have an appropriately sized tempdb
Usually, tempdb fills up when you are low on disk space, or when you have set an unreasonably low maximum size for database growth.
Many people think that tempdb is only used for #temp tables. When in fact, you can easily fill up tempdb without ever creating a single temp table. Some other scenarios that can cause tempdb to fill up:
any sorting that requires more memory than has been allocated to SQL
Server will be forced to do its work in tempdb;
if the sorting requires more space than you have allocated to tempdb,
one of the above errors will occur;
DBCC CheckDB('any database') will perform its work in tempdb -- on
larger databases, this can consume quite a bit of space;
DBCC DBREINDEX or similar DBCC commands with 'Sort in tempdb' option
set will also potentially fill up tempdb;
large resultsets involving unions, order by / group by, cartesian
joins, outer joins, cursors, temp tables, table variables, and
hashing can often require help from tempdb;
any transactions left uncommitted and not rolled back can leave
objects orphaned in tempdb;
use of an ODBC DSN with the option 'create temporary stored
procedures' set can leave objects there for the life of the
connection.
USE tempdb
GO
SELECT name
FROM tempdb..sysobjects
SELECT OBJECT_NAME(id), rowcnt
FROM tempdb..sysindexes
WHERE OBJECT_NAME(id) LIKE '#%'
ORDER BY rowcnt DESC
The higher rowcount, values will likely indicate the biggest temporary tables that are consuming space.
Short-term fix
DBCC OPENTRAN -- or DBCC OPENTRAN('tempdb')
DBCC INPUTBUFFER(<number>)
KILL <number>
Long-term prevention
-- SQL Server 7.0, should show 'trunc. log on chkpt.'
-- or 'recovery=SIMPLE' as part of status column:
EXEC sp_helpdb 'tempdb'
-- SQL Server 2000, should yield 'SIMPLE':
SELECT DATABASEPROPERTYEX('tempdb', 'recovery')
ALTER DATABASE tempdb SET RECOVERY SIMPLE
Reference : https://web.archive.org/web/20080509095429/http://sqlserver2000.databases.aspfaq.com:80/why-is-tempdb-full-and-how-can-i-prevent-this-from-happening.html
Other references : http://social.msdn.microsoft.com/Forums/is/transactsql/thread/af493428-2062-4445-88e4-07ac65fedb76
I have a very large database (~100Gb) primarily consisting of two tables I want to reduce in size (both of which have approx. 50 million records). I have an archive DB set up on the same server with these two tables, using the same schema. I'm trying to determine the best conceptual way of going about removing the rows from the live db and inserting them in the archive DB. In pseudocode this is what I'm doing now:
Declare #NextIDs Table(UniqueID)
Declare #twoYearsAgo = two years from today's date
Insert into #NextIDs
SELECT top 100 from myLargeTable Where myLargeTable.actionDate < twoYearsAgo
Insert into myArchiveTable
<fields>
SELECT <fields>
FROM myLargeTable INNER JOIN #NextIDs on myLargeTable.UniqueID = #NextIDs.UniqueID
DELETE MyLargeTable
FROM MyLargeTable INNER JOIN #NextIDs on myLargeTable.UniqueID = #NextIDs.UniqueID
Right now this takes a horrifically slow 7 minutes to complete 1000 records. I've tested the Delete and the Insert, both taking approx. 3.5 minutes to complete, so its not necessarily one is drastically more inefficient than the other. Can anyone point out some optimization ideas in this?
Thanks!
This is SQL Server 2000.
Edit: On the large table there is a clustered index on the ActionDate field. There are two other indexes, but neither are referenced in any of the queries. The Archive table has no indexes. On my test server, this is the only query hitting the SQL Server, so it should have plenty of processing power.
Code (this does a loop in batches of 1000 records at a time):
DECLARE #NextIDs TABLE(UniqueID int primary key)
DECLARE #TwoYearsAgo datetime
SELECT #TwoYearsAgo = DATEADD(d, (-2 * 365), GetDate())
WHILE EXISTS(SELECT TOP 1 UserName FROM [ISAdminDB].[dbo].[UserUnitAudit] WHERE [ActionDateTime] < #TwoYearsAgo)
BEGIN
BEGIN TRAN
--get all records to be archived
INSERT INTO #NextIDs(UniqueID)
SELECT TOP 1000 UniqueID FROM [ISAdminDB].[dbo].[UserUnitAudit] WHERE [UserUnitAudit].[ActionDateTime] < #TwoYearsAgo
--insert into archive table
INSERT INTO [ISArchive].[dbo].[userunitaudit]
(<Fields>)
SELECT <Fields>
FROM [ISAdminDB].[dbo].[UserUnitAudit] AS a
INNER JOIN #NextIDs AS b ON a.UniqueID = b.UniqueID
--remove from Admin DB
DELETE [ISAdminDB].[dbo].[UserUnitAudit]
FROM [ISAdminDB].[dbo].[UserUnitAudit] AS a
INNER JOIN #NextIDs AS b ON a.UniqueID = b.UniqueID
DELETE FROM #NextIDs
COMMIT
END
You effectively have three selects which need to be run before your insert/delete commands are executed:
for the 1st insert:
SELECT top 100 from myLargeTable Where myLargeTable.actionDate < twoYearsAgo
for the 2nd insert:
SELECT <fields> FROM myLargeTable INNER JOIN NextIDs
on myLargeTable.UniqueID = NextIDs.UniqueID
for the delete:
(select *)
FROM MyLargeTable INNER JOIN NextIDs on myLargeTable.UniqueID = NextIDs.UniqueID
I'd try and optimize these and if they are all quick, then the indexes may be slowing down your writes. Some suggestions:
start profiler and see what's happenng with the reads/writes etc.
check index usage for all three statements.
try running the SELECTs returning only the PK, to see if the delay is query execution or fetching the data (do have e.g. any fulltext-indexed fields, TEXT fields etc.)
Do you have an index on the source table for the column which you're using to filter the results? In this case, that would be the actionDate.
Also, it can often help to remove all indexes from the destination table before doing massive inserts, but in this case you're only doing 100's at a time.
You would also probably be better off doing this in larger batches. With one hundred at a time the overhead of the queries is going to end up dominating the costs/time.
Is there any other activity on the server during this time? Is there any blocking happening?
Hopefully this gives you a starting point.
If you can provide the exact code that you're using (maybe without the column names if there are privacy issues) then maybe someone can spot other ways to optimize.
EDIT:
Have you checked the query plan for your block of code? I've run into issues with table variables like this where the query optimizer couldn't figure out that the table variable would be small in size so it always tried to do a full table scan on the base table.
In my case it eventually became a moot point, so I'm not sure what the ultimate solution is. You can certainly add a condition on the actionDate to all of your select queries, which would at least minimize the effects of this.
The other option would be to use a normal table to hold the IDs.
The INSERT and DELETE statements are joining on
[ISAdminDB].[dbo].[UserUnitAudit].UniqueID
If there's no index on this, and you indicate there isn't, you're doing two table scans. That's likely the source of the slowness, b/c a SQL Server table scan reads the entire table into a scratch table, searches the scratch table for matching rows, then drops the scratch table.
I think you need to add an index on UniqueID. The performance hit for maintaining it has got to be less than table scans. And you can drop it after your archive is done.
Are there any indexes on myLargeTable.actionDate and .UniqueID?
Have you tried larger batch sizes than 100?
What is taking the most time? The INSERT, or the DELETE?
You might try doing this using the output clause:
declare #items table (
<field list just like source table> )
delete top 100 source_table
output deleted.first_field, deleted.second_field, etc
into #items
where <conditions>
insert archive_table (<fields>)
select (<fields>) from #items
You also might be able to do this in a single query, by doing 'output into' directly into the archive table (eliminating the need for the table var)
We have the following simple Stored Procedure that runs as an overnight SQL server agent job. Usually it runs in 20 minutes, but recently the MatchEvent and MatchResult tables have grown to over 9 million rows each. This has resulted in the store procedure taking over 2 hours to run, with all 8GB of memory on our SQL box being used up. This renders the database unavailable to the regular queries that are trying to access it.
I assume the problem is that temp table is too large and is causing the memory and database unavailablity issues.
How can I rewrite the stored procedure to make it more efficient and less memory intensive?
Note: I have edited the SQL to indicate that there is come condition affecting the initial SELECT statement. I had previously left this out for simplicity. Also, when the query runs CPU usage is at 1-2%, but memoery, as previously stated, is maxed out
CREATE TABLE #tempMatchResult
(
matchId VARCHAR(50)
)
INSERT INTO #tempMatchResult
SELECT MatchId FROM MatchResult WHERE SOME_CONDITION
DELETE FROM MatchEvent WHERE
MatchId IN (SELECT MatchId FROM #tempMatchResult)
DELETE FROM MatchResult WHERE
MatchId In (SELECT MatchId FROM #tempMatchResult)
DROP TABLE #tempMatchResult
There's probably a lot of stuff going on here, and it's not all your query.
First, I agree with the other posters. Try to rewrite this without a temp table if at all possible.
But assuming that you need a temp table here, you have a BIG problem in that you have no PK defined on it. It's vastly going to expand the amount of time your queries will take to run. Create your table like so instead:
CREATE TABLE #tempMatchResult (
matchId VARCHAR(50) NOT NULL PRIMARY KEY /* NOT NULL if at all possible */
);
INSERT INTO #tempMatchResult
SELECT DISTINCT MatchId FROM MatchResult;
Also, make sure that your TempDB is sized correctly. Your SQL server may very well be expanding the database file dynamically on you, causing your query to suck CPU and disk time. Also, make sure your transaction log is sized correctly, and that it is not auto-growing on you. Good luck.
Looking at the code above, why do you need a temp table?
DELETE FROM MatchEvent WHERE
MatchId IN (SELECT MatchId FROM MatchResult)
DELETE FROM MatchResult
-- OR Truncate can help here, if all the records are to be deleted anyways.
You probably want to process this piecewise in some way. (I assume queries are a lot more complicated that you showed?) In that case, you'd want try one of these:
Write your stored procedure to iterate over results. (Might still lock while processing.)
Repeatedly select the N first hits, eg LIMIT 100 and process those.
Divide work by scanning regions of the table separately, using something like WHERE M <= x AND x < N.
Run the "midnight job" more often. Seriously, running stuff like this every 5 mins instead can work wonders, especially if work increases non-linearly. (If not, you could still just get the work spread out over the hours of the day.)
In Postgres, I've had some success using conditional indices. They work magic by applying an index if certain conditions are met. This means that you can keep the many 'resolved' and the few unresolved rows in the same table, but still get that special index over just the unresolved ones. Ymmv.
Should be pointed out that this is where using databases gets interesting. You need to pay close attention to your indices and use EXPLAIN on your queries a lot.
(Oh, and remember, interesting is a good thing in your hobbies, but not at work.)
First, indexes are a MUST here see Dave M's answer.
Another approach that I will sometime use when deleting very large data sets, is creating a shadow table with all the data, recreating indexes and then using sp_rename to switch it in. You have to be careful with transactions here, but depending on the amount of data being deleted this can be faster.
Note If there is pressure on tempdb consider using joins and not copying all the data into the temp table.
So for example
CREATE TABLE #tempMatchResult (
matchId VARCHAR(50) NOT NULL PRIMARY KEY /* NOT NULL if at all possible */
);
INSERT INTO #tempMatchResult
SELECT DISTINCT MatchId FROM MatchResult;
set transaction isolation level serializable
begin transaction
create table MatchEventT(columns... here)
insert into MatchEventT
select * from MatchEvent m
left join #tempMatchResult t on t.MatchId = m.MatchId
where t.MatchId is null
-- create all the indexes for MatchEvent
drop table MatchEvent
exec sp_rename 'MatchEventT', 'MatchEvent'
-- similar code for MatchResult
commit transaction
DROP TABLE #tempMatchResult
Avoid the temp table if possible
It's only using up memory.
You could try this:
DELETE MatchEvent
FROM MatchEvent e ,
MatchResult r
WHERE e.MatchId = r.MatchId
If you can't avoid a temp table
I'm going to stick my neck out here and say: you don't need an index on your temporary table because you want the temp table to be the smallest table in the equation and you want to table scan it (because all the rows are relevant). An index won't help you here.
Do small bits of work
Work on a few rows at a time.
This will probably slow down the execution, but it should free up resources.
- One row at a time
SELECT #MatchId = min(MatchId) FROM MatchResult
WHILE #MatchId IS NOT NULL
BEGIN
DELETE MatchEvent
WHERE Match_Id = #MatchId
SELECT #MatchId = min(MatchId) FROM MatchResult WHERE MatchId > #MatchId
END
- A few rows at a time
CREATE TABLE #tmp ( MatchId Varchar(50) )
/* get list of lowest 1000 MatchIds: */
INSERT #tmp
SELECT TOP (1000) MatchId
FROM MatchResult
ORDER BY MatchId
SELECT #MatchId = min(MatchId) FROM MatchResult
WHILE #MatchId IS NOT NULL
BEGIN
DELETE MatchEvent
FROM MatchEvent e ,
#tmp t
WHERE e.MatchId = t.MatchId
/* get highest MatchId we've procesed: */
SELECT #MinMatchId = MAX( MatchId ) FROM #tmp
/* get next 1000 MatchIds: */
INSERT #tmp
SELECT TOP (1000) MatchId
FROM MatchResult
WHERE MatchId > #MinMatchId
ORDER BY MatchId
END
This one deletes up to 1000 rows at a time.
The more rows you delete at a time, the more resources you will use but the faster it will tend to run (until you run out of resources!). You can experiment to find a more optimal value than 1000.
DELETE FROM MatchResult WHERE
MatchId In (SELECT MatchId FROM #tempMatchResult)
can be replaced with
DELETE FROM MatchResult WHERE SOME_CONDITION
Can you just turn cascading deletes on between matchresult and matchevent? Then you need only worry about identifying one set of data to delete, and let SQL take care of the other.
The alternative would be to make use of the OUTPUT clause, but that's definitely more fiddle.
Both of these would let you delete from both tables, but only have to state (and execute) your filter predicate once. This may still not be as performant as a batching approach as suggested by other posters, but worth considering. YMMV