Xrhrft

We are attempting to update/delete a large number of records in a multi-billion row table. Since this is a popular table, there is a lot of activity in different sections of this table. Any large update/delete activity is being blocked for extended periods of time (as it is waiting to get locks on all the rows or page lock or table lock) resulting in timeouts or taking multiple days to complete the task.

So, we are changing the approach to delete small batch of rows at at time. But we want to check if the selected (let's say 100 or 1000 or 2000 rows) are currently locked by a different process or not.

• If not, then proceed with delete/update.


• If they are locked, then move on to the next group of records.


• At end, come back to the begining and attempt to update/delete the left out ones.

Is this doable?

Thanks,
ToC

So, we are changing the approach to delete small batch of rows at at time.

This is a really good idea to delete in small careful batches or chunks. I would add a small waitfor delay '00:00:05' and depending on the recovery model of the database - if FULL, then do a log backup and if SIMPLE then do a manual CHECKPOINT to avoid bloating of transaction log - between batches.

But we want to check if the selected (let's say 100 or 1000 or 2000 rows) are currently locked by a different process or not.

What you are telling is not entirely possible out of box (keeping in mind your 3 bullet points). If the above suggestion - small batches + waitfor delay does not work (provided you do proper testing), then you can use the query HINT.

Do not use NOLOCK - see kb/308886, SQL Server Read-Consistency Problems by Itzik Ben-Gan, Putting NOLOCK everywhere - By Aaron Bertrand and SQL Server NOLOCK Hint & other poor ideas.

READPAST hint will help in your scenario. The gist of READPAST hint is - if there is a row level lock then SQL server wont read it.

Specifies that the Database Engine not read rows that are locked by other transactions. When READPAST is specified, row-level locks are skipped. That is, the Database Engine skips past the rows instead of blocking the current transaction until the locks are released.

During my limited testing, I found really good throughput when using DELETE from schema.tableName with (READPAST, READCOMMITTEDLOCK) and setting the query session isolation level to READ COMMITTED using SET TRANSACTION ISOLATION LEVEL READ COMMITTED which is default isolation level anyway.

If I understand the request correctly, the goal is to delete batches of rows, while at the same time, DML operations are occurring on rows throughout the table. The goal is to delete a batch; however, if any underlying rows contained within the range defined by said batch are locked, then we must skip that batch and move to the next batch. We must then return to any batches that were not previously deleted and retry our original delete logic. We must repeat this cycle until all required batches of rows are deleted.

As has been mentioned, it is reasonable to use a READPAST hint and the READ COMMITTED (default) isolation level, in order to skip past ranges that may contain blocked rows. I will go a step further and recommend using the SERIALIZABLE isolation level and nibbling deletes.

SQL Server uses Key-Range locks to protect a range of rows implicitly included in a record set being read by a Transact-SQL statement while using the serializable transaction isolation level...find more here:
https://technet.microsoft.com/en-US/library/ms191272(v=SQL.105).aspx

With nibbling deletes, our goal is to isolate a range of rows and ensure that no changes will occur to those rows while we are deleting them, that is to say, we do not want phantom reads or insertions. The serializable isolation level is meant to solve this problem.

Before I demonstrate my solution, I would like to add that neither am I recommending switching your database's default isolation level to SERIALIZABLE nor am I recommending that my solution is the best. I merely wish to present it and see where we can go from here.

A few house-keeping notes:

1. The SQL Server version that I am using is Microsoft SQL Server 2012 - 11.0.5343.0 (X64)


2. My test database is using the FULL recovery model

To begin my experiment, I will set up a test database, a sample table, and I will fill the table with 2,000,000 rows.

USE [master];

GO



SET NOCOUNT ON;



IF DATABASEPROPERTYEX (N'test', N'Version') > 0

BEGIN

    ALTER DATABASE [test] SET SINGLE_USER

        WITH ROLLBACK IMMEDIATE;

    DROP DATABASE [test];

END

GO



-- Create the test database

CREATE DATABASE [test];

GO



-- Set the recovery model to FULL

ALTER DATABASE [test] SET RECOVERY FULL;



-- Create a FULL database backup

-- in order to ensure we are in fact using 

-- the FULL recovery model

-- I pipe it to dev null for simplicity

BACKUP DATABASE [test]

TO DISK = N'nul';

GO



USE [test];

GO



-- Create our table

IF OBJECT_ID('dbo.tbl','U') IS NOT NULL

BEGIN

    DROP TABLE dbo.tbl;

END;

CREATE TABLE dbo.tbl

(

      c1 BIGINT IDENTITY (1,1) NOT NULL

    , c2 INT NOT NULL

) ON [PRIMARY];

GO



-- Insert 2,000,000 rows 

INSERT INTO dbo.tbl

    SELECT TOP 2000

        number

    FROM

        master..spt_values

    ORDER BY 

        number

GO 1000

At this point, we will need one or more indexes upon which the locking mechanisms of the SERIALIZABLE isolation level can act.

-- Add a clustered index

CREATE UNIQUE CLUSTERED INDEX CIX_tbl_c1

    ON dbo.tbl (c1);

GO



-- Add a non-clustered index

CREATE NONCLUSTERED INDEX IX_tbl_c2 

    ON dbo.tbl (c2);

GO

Now, let us check to see that our 2,000,000 rows were created

SELECT

    COUNT(*)

FROM

    tbl;

So, we have our database, table, indexes, and rows. So, let us set up the experiment for nibbling deletes. First, we must decide how best to create a typical nibbling delete mechanism.

DECLARE

      @BatchSize        INT    = 100

    , @LowestValue      BIGINT = 20000

    , @HighestValue     BIGINT = 20010

    , @DeletedRowsCount BIGINT = 0

    , @RowCount         BIGINT = 1;



SET NOCOUNT ON;

GO



WHILE  @DeletedRowsCount &lt  ( @HighestValue - @LowestValue ) 

BEGIN



    SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;

    BEGIN TRANSACTION



        DELETE 

        FROM

            dbo.tbl 

        WHERE

            c1 IN ( 

                    SELECT TOP (@BatchSize)

                        c1

                    FROM

                        dbo.tbl 

                    WHERE 

                        c1 BETWEEN @LowestValue AND @HighestValue

                    ORDER BY 

                        c1

                  );



        SET @RowCount = ROWCOUNT_BIG();



    COMMIT TRANSACTION;



    SET @DeletedRowsCount += @RowCount;

    WAITFOR DELAY '000:00:00.025';

    CHECKPOINT;



END;

As you can see, I placed the explicit transaction inside the while loop. If you would like to limit log flushes, then feel free to place it outside the loop. Furthermore, since we are in the FULL recovery model, you may wish to create transaction log backups more often while running your nibbling delete operations, in order to ensure that your transaction log can be prevented from growing outrageously.

So, I have a couple goals with this setup. First, I want my key-range locks; so, I try to keep the batches as small as possible. I also do not want to impact negatively the concurrency on my "gigantic" table; so, I want to take my locks and leave them as fast as I can. So, I recommend that you make your batch sizes small.

Now, I want to provide a very short example of this deletion routine in action. We must open a new window within SSMS and delete one row from our table. I will do this within an implicit transaction using the default READ COMMITTED isolation level.

DELETE FROM

    dbo.tbl

WHERE

    c1 = 20005;

Was this row actually deleted?

SELECT

    c1

FROM

    dbo.tbl

WHERE

    c1 BETWEEN 20000 AND 20010;

Yes, it was deleted.

Now, in order to see our locks, let us open a new window within SSMS and add a code snippet or two. I am using Adam Mechanic's sp_whoisactive, which can be found here: sp_whoisactive

SELECT

    DB_NAME(resource_database_id) AS DatabaseName

  , resource_type

  , request_mode

FROM

    sys.dm_tran_locks

WHERE

    DB_NAME(resource_database_id) = 'test'

    AND resource_type = 'KEY'

ORDER BY

    request_mode;



-- Our insert

sp_lock 55;



-- Our deletions

sp_lock 52;



-- Our active sessions

sp_whoisactive;

Now, we are ready to begin. In a new SSMS window, let us begin an explicit transaction that will attempt to re-insert the one row that we deleted. At the same time, we will fire off our nibbling delete operation.

The insert code:

BEGIN TRANSACTION



    SET IDENTITY_INSERT dbo.tbl ON;



    INSERT  INTO dbo.tbl

            ( c1 , c2 )

    VALUES

            ( 20005 , 1 );



    SET IDENTITY_INSERT dbo.tbl OFF;



--COMMIT TRANSACTION;

Let us kick off both operations beginning with the insert and followed by our deletes. We can see the key-range locks and exclusive locks.

The insert generated these locks:

The nibbling delete/select is holding these locks:

Our insert is blocking our delete as expected:

Now, let us commit the insert transaction and see what is up.

And as expected, all transactions complete. Now, we must check to see whether the insert was a phantom or whether the delete operation removed it as well.

SELECT

    c1

FROM

    dbo.tbl

WHERE

    c1 BETWEEN 20000 AND 20015;

In fact, the insert was deleted; so, no phantom insert was allowed.

So, in conclusion, I think the true intention of this exercise is not to try and track every single row, page, or table-level lock and try to determine whether an element of a batch is locked and would therefore require our delete operation to wait. That may have been the intent of the questioners; however, that task is herculean and basically impractical if not impossible. The real goal is to ensure that no unwanted phenomena arise once we have isolated the range of our batch with locks of our own and then precede to delete the batch. The SERIALIZABLE isolation level achieves this objective. The key is to keep your nibbles small, your transaction log under control, and eliminate unwanted phenomena.

If you want speed, then don't build gigantically deep tables that cannot be partitioned and therefore be unable to use partition switching for the fastest results. The key to speed is partitioning and parallelism; the key to suffering is nibbles and live-locking.

Please let me know what you think.

I created some further examples of the SERIALIZABLE isolation level in action. They should be available at the links below.

Delete Operation

Insert Operation

Equality Operations - Key-Range Locks on Next Key Values

Equality Operations - Singleton Fetch of Existent Data

Equality Operations - Singleton Fetch of Nonexistent Data

Inequality Operations - Key-Range Locks on Range and Next Key Values

Summarizing other approaches originally offered in comments to the question.

1. 
   

   Use NOWAIT if the desired behaviour is to fail the whole chunk as soon as an incompatible lock is encountered.

   
   
   

   From the NOWAIT documentation:

   
   
   

   
   

   Instructs the Database Engine to return a message as soon as a lock is encountered on the table. NOWAIT is equivalent to specifying SET LOCK_TIMEOUT 0 for a specific table. The NOWAIT hint does not work when the TABLOCK hint is also included. To terminate a query without waiting when using the TABLOCK hint, preface the query with SETLOCK_TIMEOUT 0; instead.

   
   

   
   


2. 
   

   Use SET LOCK_TIMEOUT to achieve a similar outcome, but with a configurable timeout:

   
   
   

   From the SET LOCK_TIMEOUT documentation

   
   
   

   
   

   Specifies the number of milliseconds a statement waits for a lock to be released.

   
   
   

   When a wait for a lock exceeds the timeout value, an error is returned. A value of 0 means to not wait at all and return a message as soon as a lock is encountered.

   
   

   
   

To assume we have 2 parallels queries:

connect/session 1: will locked the row = 777

SELECT * FROM your_table WITH(UPDLOCK,READPAST) WHERE id = 777

connect/session 2: will ignore locked row = 777

SELECT * FROM your_table WITH(UPDLOCK,READPAST) WHERE id = 777

OR connect/session 2: will throw exception

DECLARE @id integer;

SELECT @id = id FROM your_table WITH(UPDLOCK,READPAST) WHERE id = 777;

IF @id is NULL

  THROW 51000, 'Hi, a record is locked or does not exist.', 1;