I am issuing an UPDATE statement to a list of records in bulk.
There's a trigger in the database table to start firing whenever detect a change of value.
Is there a way for me to hold all the update and complete then release for reading ?
Saw many options here but getting confuse ...
https://learn.microsoft.com/en-us/sql/t-sql/queries/hints-transact-sql-table?view=sql-server-ver15
My SQL Command
UPDATE tbl_table1 SET colStatus = 'Y' WHERE zDate > GETDATE()-1
There could be 10 records, 100 or 1000 or 100,000 records that need to be updated. I know it is fast but I just want to make all records to have same status then allow for reading.
Any thoughts ? Thanks.
Related
I have a table as follows:
id status
-- ------
1 pass
1 fail
1 pass
1 na
1 na
Also, I have a stored procedure that returns a table with top 100 records having status as 'na'. The stored procedure can be called by multiple nodes in an environment and I don't want them to fetch duplicate data. So, I want to lock the stored procedure while it is executing and set the status of the records obtained from the stored procedure to 'In Progress' and return that table and then release the lock, so that different nodes don't fetch the same data. How would I accomplish this?
There is already a solution provided for similar question in ms sql but it shows errors when using in sybase.
Assuming Sybase ASE ...
The bigger issue you'll likely want to consider is whether you want a single process to lock the entire table while you're grabbing your top 100 rows, or if you want other processes to still access the table?
Another question is whether you'd like multiple processes to concurrently pull 100 rows from the table without blocking each other?
I'm going to assume that you a) don't want to lock the entire table and b) you may want to allow multiple processes to concurrently pull rows from the table.
1 - if possible, make sure the table is using datarows locking (default is usually allpages); this will reduce the granularity of locks to the row level (as opposed to page level for allpages); the table will need to be datarows if you want to allow multiple processes to concurrently find/update rows in the table
2 - make sure the lock escalation setting on the table is high enough to ensure a single process's 100 row update doesn't lock the table (sp_setpglockpromote for allpages, sp_setrowlockpromote for datarows); the key here is to make sure your update doesn't escalate to a table-level lock!
3 - when it comes time to grab your set of 100 rows you'll want to ... inside a transaction ... update the 100 rows with a status value that's unique to your session, select the associated id's, then update the status again to 'In Progress'
The gist of the operation looks like the following:
declare #mysession varchar(10)
select #mysession = convert(varchar(10),##spid) -- replace ##spid with anything that
-- uniquely identifies your session
set rowcount 100 -- limit the update to 100 rows
begin tran get_my_rows
-- start with an update so that get exclusive access to the desired rows;
-- update the first 100 rows you find with your ##spid
update mytable
set status = #mysession -- need to distinguish your locked rows from
-- other processes; if we used 'In Progress'
-- we wouldn't be able to distinguish between
-- rows update earlier in the day or updated
-- by other/concurrent processes
from mytable readpast -- 'readpast' allows your query to skip over
-- locks held by other processes but it only
-- works for datarows tables
where status = 'na'
-- select your reserved id's and send back to the client/calling process
select id
from mytable
where status = #mysession
-- update your rows with a status of 'In Progress'
update mytable
set status = 'In Progress'
where status = #mysession
commit -- close out txn and release our locks
set rowcount 0 -- set back to default of 'unlimited' rows
Potential issues:
if your table is large and you don't have an index on status then your queries could take longer than necessary to run; by making sure lock escalation is high enough and you're using datarows locking (so the readpast works) you should see minimal blocking of other processes regardless of how long it takes to find the desired rows
with an index on the status column, consider that all of these updates are going to force a lot of index updates which is probably going to lead to some expensive deferred updates
if using datarows and your lock escalation is too low then an update could look the entire table, which would cause another (concurrent) process to readpast the table lock and find no rows to process
if using allpages you won't be able to use readpast so concurrent processes will block on your locks (ie, they won't be able to read around your lock)
if you've got an index on status, and several concurrent processes locking different rows in the table, there could be a chance for deadlocks to occur (likely in the index tree of the index on the status column) which in turn would require your client/application to be coded to expect and address deadlocks
To think about:
if the table is relatively small such that table scanning isn't a big cost, you could drop any index on the status column and this should reduce the performance overhead of deferred updates (related to updating the indexes)
if you can work with a session specific status value (eg, 'In Progress - #mysession') then you could eliminate the 2nd update statement (could come in handy if you're incurring deferred updates on an indexed status column)
if you have another column(s) in the table that you could use to uniquely identifier your session's rows (eg, last_updated_by_spid = ##spid, last_updated_date = #mydate - where #mydate is initially set to getdate()) then your first update could set the status = 'In Progress', the select would use ##spid and #mydate for the where clause, and the second update would not be needed [NOTE: This is, effectively, the same thing Gordon is trying to address with his session column.]
assuming you can work with a session specific status value, consider using something that will allow you to track, and fix, orphaned rows (eg, row status remains 'In Progress - #mysession' because the calling process died and never came back to (re)set the status)
if you can pass the id list back to the calling program as a single string of concatenated id values you could use the method I outline in this answer to append the id's into a #variable during the first update, allowing you to set status = 'In Progress' in the first update and also allowing you to eliminate the select and the second update
how would you tell which rows have been orphaned? you may want the ability to update a (small)datetime column with the getdate() of when you issued your update; then, if you would normally expect the status to be updated within, say, 5 minutes, you could have a monitoring process that looks for orphaned rows where status = 'In Progress' and its been more than, say, 10 minutes since the last update
If the datarows, readpast, lock escalation settings and/or deadlock potential is too much, and you can live with brief table-level locks on the table, you could have the process obtain an exclusive table level lock before performing the update and select statements; the exclusive lock would need to be obtained within a user-defined transaction in order to 'hold' the lock for the duration of your work; a quick example:
begin tran get_my_rows
-- request an exclusive table lock; wait until it's granted
lock table mytable in exclusive mode
update ...
select ...
update ...
commit
I'm not 100% sure how to do this in Sybase. But, the idea is the following.
First, add a new column to the table that represents the session or connection used to change the data. You will use this column to provide isolation.
Then, update the rows:
update top (100) t
set status = 'in progress',
session = #session
where status = 'na'
order by ?; -- however you define the "top" records
Then, you can return or process the 100 ids that are "in progress" for the given connection.
Create another table, proc_lock, that has one row
When control enters the stored procedure, start a transaction and do a select for update on the row in proc_lock (see this link). If that doesn't work for Sybase, then you could try the technique from this answer to lock the row.
Before the procedure exits, make sure to commit the transaction.
This will ensure that only one user can execute the proc at a time. When the second user tries to execute the proc, it will block until the first user's lock on the proc_lock row is released (e.g. when transaction is committed)
I have a parallel process that is using queue table in PostgreSQL. Logic is:
Begin transaction.
Mark 100 unprocessed records with some random generated ID.
Commit.
Run some heavy app logic that takes some time and is processing queue records with generated ID in step 2.
Update 100 processed records with success/bad status.
Up to 20 threads are doing those steps.
However, sometimes when I'm trying to do 2 step with query:
UPDATE QUEUE_TABLE
SET QUEUE_TXN_GUID=$RANDOM_GUID,
QUEUE_STATUS=1
WHERE QUEUE_ROW_GUID IN
(SELECT QUEUE_ROW_GUID from QUEUE_TABLE
WHERE QUEUE_STATUS IS NULL OR QUEUE_STATUS = -1
LIMIT 100 FOR UPDATE SKIP LOCKED) RETURNING QUEUE_ROW_GUID
I got error deadlock detected.
Query that I'm using in step 5 is
UPDATE QUEUE_TABLE SET CDC_QUEUE_REZ_STATUS=$STATUS WHERE CDC_QUEUE_REZ_TXN_GUID=$RANDOM_GUID;
I don't know why I'm getting this strange deadlock, with FOR UPDATE SKIP LOCKED in first update subquery.
The reason of the issue is the fact that there are duplicates in QUEUE_ROW_GUID. Select locks some rows but then query updates not those rows that were locked. That's why concurrently running query may try to update the same rows as this one. So the SKIP LOCKED does not work in this case.
Given that update of rows may happen in different order the first query (that tries to update say row 1 and row 2) may first update row 1 and then try to update row 2 but waits on lock. Concurrently running query (that tries to update 1 and 2 as well) already updated row 2 and waits for lock for row 1. Hence the deadlock.
You need to use unique identifiers to update rows after they are locked.
While executing a SQL update,
update request set state_id = 2 where id in (
select id from request where state_id = 0 and entity_id in
(<list of numbers>)
)
This updates only 7 rows at a time.
The inner select query,
select id from request where state_id = 0 and entity_id in (<list of numbers>)
returns 2000+ records.
I am using Squirrel SQL client to run the query and checked if the limit rows is set to 3000.
What makes it more interesting is, if I wait for more time in between successive executing of the update query, more rows gets updated.
I mean, When I waited for 10 secs, and executed the update, 45 rows got updated.
but when ran rapidly, just 7 rows gets updated.
Can someone please help me point out what I might be doing wrong?
Executing the inner select -
Executing the update -
I suggest writing a proper update, since I see no reason to introduce a more complex query involving a subquery. Also just to be sure you didn't previously alter ##ROWCOUNT:
SET ##ROWCOUNT 0;
UPDATE dbo.request
SET state_id = 2
WHERE state_id = 0
AND entity_id IN (<list of numbers>);
Also check that you haven't artificially limited the row count in Management Studio. In Tools > Options:
(Well, that would have been relevant if you had tagged correctly. Check whatever client tool you use against Sybase and see if it has some similar option.)
I am using MS SQL Server 2008
i have a table which is constantly in use (data is always changing and inserted to it)
it contains now ~70 Mill rows,
I am trying to run a simple query over the table with a stored procedure that should properly take a few days,
I need the table to keep being usable, now I executed the stored procedure and after a while every simple select by identity query that I try to execute on the table is not responding/running too much time that I break it
what should I do?
here is how my stored procedure looks like:
SET NOCOUNT ON;
update SOMETABLE
set
[some_col] = dbo.ufn_SomeFunction(CONVERT(NVARCHAR(500), another_column))
WHERE
[some_col] = 243
even if i try it with this on the where clause (with an 'and' logic..) :
ID_COL > 57000000 and ID_COL < 60000000 and
it still doesn't work
BTW- SomeFunction does some simple mathematics actions and looks up rows in another table that contains about 300k items, but is never changed
From my perspective your server has a serious performance problem. Even if we assume that none of the records in the query
select some_col with (nolock) where id_col between 57000000 and 57001000
was in memory, it shouldn't take 21 seconds to read the few pages sequentially from disk (your clustered index on the id_col should not be fragmented if it's an auto-identity and you didn't do something stupid like adding a "desc" to the index definition).
But if you can't/won't fix that, my advice would be to make the update in small packages like 100-1000 records at a time (depending on how much time the lookup function consumes). One update/transaction should take no more than 30 seconds.
You see each update keeps an exclusive lock on all the records it modified until the transaction is complete. If you don't use an explicit transaction, each statement is executed in a single, automatic transaction context, so the locks get released when the update statement is done.
But you can still run into deadlocks that way, depending on what the other processes do. If they modify more than one record at a time, too, or even if they gather and hold read locks on several rows, you can get deadlocks.
To avoid the deadlocks, your update statement needs to take a lock on all the records it will modify at once. The way to do this is to place the single update statement (with only the few rows limited by the id_col) in a serializable transaction like
IF ##TRANCOUNT > 0
-- Error: You are in a transaction context already
SET NOCOUNT ON
SET TRANSACTION ISOLATION LEVEL SERIALIZABLE
-- Insert Loop here to work "x" through the id range
BEGIN TRANSACTION
UPDATE SOMETABLE
SET [some_col] = dbo.ufn_SomeFunction(CONVERT(NVARCHAR(500), another_column))
WHERE [some_col] = 243 AND id_col BETWEEN x AND x+500 -- or whatever keeps the update in the small timerange
COMMIT
-- Next loop
-- Get all new records while you where running the loop. If these are too many you may have to paginate this also:
BEGIN TRANSACTION
UPDATE SOMETABLE
SET [some_col] = dbo.ufn_SomeFunction(CONVERT(NVARCHAR(500), another_column))
WHERE [some_col] = 243 AND id_col >= x
COMMIT
For each update this will take an update/exclusive key-range lock on the given records (but only them, because you limit the update through the clustered index key). It will wait for any other updates on the same records to finish, then get it's lock (causing blocking for all other transactions, but still only for the given records), then update the records and release the lock.
The last extra statement is important, because it will take a key range lock up to "infinity" and thus prevent even inserts on the end of the range while the update statement runs.
I have a rather basic and general question about atomicity of "UPDATE ... SET .. WHERE ..." statement.
having a table (without extra constraint),
+----------+
| id | name|
+----------+
| 1 | a |
+----+-----+
now, I would execute following 4 statements "at the same time" (concurrently).
UPDATE table SET name='b1' WHERE name='a'
UPDATE table SET name='b2' WHERE name='a'
UPDATE table SET name='b3' WHERE name='a'
UPDATE table SET name='b4' WHERE name='a'
is there only one UPDATE statement would be executed with table update?
or, is it possible that more than one UPDATE statements can really update the table?
should I need extra transaction or lock to let only one UPDATE write values into table?
thanks
[EDIT]
the 4 UPDATE statements are executed parallel from different processes.
[EDIT] with Postgresql
One of these statements will lock the record (or the page, or the whole table, depending on your engine and locking granularity) and will be executed.
The others will wait for the resource to be freed.
When the lucky statement will commit, the others will either reread the table and do nothing (if your transaction isolation mode is set to READ COMMITTED) or fail to serialize the transaction (if the transaction isolation level is SERIALIZABLE).
If you ran these UPDATEs in one go, it will run them in order, so it would update everything to b1 but then the other 3 would fail to update any as there will be no A's left to update.
There would be an implicit transaction around each which would hold other UPDATEs in a queue. Only the first one through would win in this case as each subsequent update will not see a name called 'a'.
Edit: I was assuming here that you were calling each UPDATE from separate processes. If they were called in a single script, they would be run consecutively in the order of appearence.
There is only ever one UPDATE statement that can access a record. Before it runs, it starts a transaction and locks the table (or more correctly, the page the record is on, or even only the record itself - this depends on many factors). Then it makes the change and unlocks the table again, commiting the transaction in the process.
Updates/deletes/inserts to a certain record are single threaded by their very nature, it is required to ensure table integrity. This does not mean that updates to many records (that are on different pages) could not run in parallel.
With the statement you posted and you would end up with an error because after the first update 'a' can't be found. What are you trying to achieve with this?
Even if you don't specify begin transaction and commit transaction, a single SQL statement is always transactional. That means only one of the updates is allowed to modify the row at the same time. The other queries will block on the update lock owned by the first query.
I believe this may be what you are looking for (in T-SQL):
UPDATE [table]
SET [table].[name] = temp.new_name
FROM
[table],
(
SELECT
id,
new_name = 'B'+ cast(row_number() over (order by [name]) as varchar)
FROM
[table]
WHERE
[table].name = 'A'
) temp
WHERE [table].id = temp.id
There should be an equivalent function to row_number in the other SQL flavors.