SQL Fascination

Bizarrely given that transaction log decoding is not really viable as a technique beyond interest, it’s quite surprising how many people visit just to understand or learn how to do it. Either a lot of data is being lost and no backup’s exist – or it fascinates a large number of people.

In either instance, there are sometimes subtle changes can pass you by, and the use of old habits can make life a bit harder. One such recent change that I missed was an alteration to the ::fn_dblog function. I really should have spent some time investigating the new fields that had been added – but with documentation being limited to say the least, it has not been the top priority and my habit is to fire up SQL 2005 when checking something in the transaction log – so I had not noticed them.

One of the changes is the creation of a link between the contents of sys.dm_tran_current_transaction and the transaction log itself. The contents of the view have not altered, but one of the new fields within the output from ::fn_fblog is a new field called Xact_ID – this field contains the same value as the Transaction_ID that is output from the DMV.

Now that is significantly convenient for when you’re poking around in logs trying to understand cause and effect .

A couple of simple stored procedures later to assist in saving and returning that filtered information as follows:

CREATE PROCEDURE sp_store_transaction
<AS
BEGIN
  DECLARE @dm_transaction_id bigint
  SELECT @dm_transaction_id = transaction_id FROM sys.dm_tran_current_transaction
  IF OBJECT_ID (N'tempdb.dbo.##db_last_transaction') IS NOT NULL
    DROP TABLE ##db_last_transaction
  SELECT [transaction id] INTO ##db_last_transaction
  FROM ::fn_dblog(null,null)
  WHERE [Xact ID] = @dm_transaction_id
<END
GO

CREATE PROCEDURE sp_get_last_transaction
AS
BEGIN
  SELECT *
  FROM ::fn_dblog(null,null)
  WHERE [Transaction ID] = (SELECT [transaction id] FROM ##db_last_transaction)
END
GO

And that is going to make looking at cause an effect far easier – first procedure you call anywhere within your transaction to store the current transaction_id within the log, and the second to retrieve the values for that stored transaction id. Something like:

BEGIN TRAN
UPDATE tbltest SET firstname = 'ab'

EXEC sp_store_transaction
COMMIT TRAN

sp_get_last_transaction

If you are wondering why I did not dump the log records out and only the transaction id that ties them together – if you dumped the records before the transaction committed or rolled back, you would not see the effect of that action – you need to retrieve all the log rows associated to that transaction, after it has finished.

I have been involved in a long running case with a client, trying to establish why an ETL process of a couple of gig of data, would result in over 5 gig of transaction log space being used.

The database was set in bulk mode, and confirmed as being correctly in bulk mode with appropriate full backups and transaction log backups occurring – so how could the log be expanding so rapidly for such a simple import. One clue was that this was only occurring on a single system, and that no other system had ever witnessed this behaviour, so it had to be something environmental.

The output from the transaction log captured during a load window was sent to me and some quick aggregation of the rows show that there was close to 280k LOP_FORMAT_PAGE entries, but instead of the normal log entry size of 84 bytes, they were coming in at 8276 bytes. This was due to the log record overhead but basically meant that for each page being allocated by the inload, an entry was added larger than the page just added.

I contacted Paul Randal to ask why the log entry would get allocated this large and he identified it as not being in bulk logged mode – which made sense given the log expansion but there was little proof. Examining an individual LOP_FORMAT_PAGE entry I could see a clear repeating pattern within the hex data – which would be consistent to a page with rows within it.

One field of what was being imported was a known value for every row (the data related to a specific week number), and translating that value into hex, it was visible multiple times. Using the breakdown of a row and that this value was field number 3 the row could be decoded and actual values of a row imported reconstructed.

Using these values the main database was queried and that row did indeed exist – the data has 27 decimal values within it also, so the chances of a random match are incredibly small. This proved that the log was recording every single row, even though it was in bulk logged mode.

There are a number of things that can prevent bulk logged mode from operating correctly, and on examining the list the problem became clear to the client’s DBA; the main database backup was still running at the same time as the data inload was being scheduled. The bulk log operations have to be fully logged during the backup to ensure that the database can be returned to a consistent state once it has been restored.

It is the only time I have seen the LOP_FORMAT_PAGE taking up this much space in a transaction log, and if anyone else gets stuck on a similar problem, google should at least find something this time.

After decoding the delete statement within the transaction log, I thought I would tackle another statement – an update statement, although I am attempting the simple version of the update which is only to update a single value within the fixed width fields section. Again to assist in decoding the log entry, I have used the AdventureWorks database and know the values of the data before and after the modification, so it is easier to decode how the log entry is constructed.

As before the database has been backed up whilst in fully logged mode and the transaction log backed up to make it as small as possible. Once the database was ready I issued a simple statement against the database

update HumanResources.Employee
set MaritalStatus = 'M' where employeeid = 6

The employee with the ID  of 6 has changed marital status, congratulations employee id 6.

The first confusion is that two LOP_MODIFY_ROW entries show up against the LCX_Clustered context, for the HumanResources.Employee.PK_Employee_EmployeeID allocation unit / name, but only 1 modification has been made.

What is the second modification?

Against each LOP_MODIFY_ROW there is an [Offset in Row] column, which indicates where within the row the modification has been made. The first modification is recorded at byte 24, the second is at byte 57. Instead of providing a field number / name, the alteration is being recorded at a byte level, so to figure out which columns have changed, we must map out the structure in terms of byte positions for the row.

Again, because there are no nullable columns at all, there is no nullability bitmap within the structure. This mapping is specific to this row, but the offsets for the fixed portion of the row would be valid for all the records, it is only the variable width columns that would change per data row.

The two modifications are at byte 24 and 57, which is clearly the Marital Status and the Modified Date. 

Why is the modified date being changed? The adventure works employee table has an update trigger on it, which alters the modified data column to be the current date when any change is made to the row.

For the Marital status transaction log entry, there are two values we need to logically know – what was it before the change, and what is the value after the change.

The Row Log Contents 0 and Row Log Contents 1 fields clearly provide that information

Row Log Contents 0 : 0x53
Row Log Contents 1 : 0x4D
select convert(nchar,0x53) = S
select convert(nchar,0x4D) = M

So they are clearly the before and after results.

Checking the transaction log entry against the trigger, the log row contents are dates within hex format, which are not too difficult to deal with

In Hex, and Row Log Contents  0 contains the previous modified date, although the SQL Management Studio results show the Hex has been shortened somewhat from the normal  8 bytes for a date. Padding the extra zeros in gives us:

0x 00 00 00 00 35 95 00 00 = 0x 00 00 95 35 00 00 00 00  = 2004-07-31 00:00:00.000

The same rules apply to the  RowLog Contents 1 which has also been cut short.

0x A5 F1 D6 00 24 9D 00 00 =  00 00 9D 24 00 D6 F1 A5 =  2010-02-21 13:02:35.217

Which is unsurprisingly today’s date and when I made the modification.

The immediate question is did the log contain two entries because there were two different causes of the change, or does it record a transaction log row per value modified. Since the Offset In Row value is within the transaction log row, you could guess at 1 entry per change.

To check, I restored the database to the starting position and issued a statement with two modifications:

update HumanResources.Employee
set MaritalStatus = 'M',
VacationHours = 60
where employeeid = 6

The transaction log alters signficantly, the modified date LOP_MODIFY_ROW entry with an offset of 57 still gets added, but the alteration of the two values does not produce 2 x LOP_MODIFY_ROW but a single LOP_MODIFY_COLUMNS – this appears to have a more complex format that is going to be tougher to crack, so that will have to wait until another day.

In the previous post we pulled out the raw information relating to a transaction log entry for a deletion of a single row.  In this post we will decode the binary section of the log entry for the deletion performed.

A reminder of the Row Log Contents for the Clustered Index log entry that we need to decode.

0x3000410001000000B90400001000000000000000406700004D004D0000000000CB8900004A15001E004AD0E1AA37C27449B4D593524773771800000000359500001000000003005D008500BD003100340034003100370038003000370061006400760065006E0074007500720065002D0077006F0072006B0073005C006700750079003100500072006F00640075006300740069006F006E00200054006500630068006E0069006300690061006E0020002D0020005700430036003000

So we have 180 bytes of information relating to the deletion, the question is – what is it? The most obvious answer has to be the record that has been deleted – lots of fixed log information has already been exposed as named fields, this generic variable length value must be the row that we deleted.

How to decode it though? applying the structure of a row is a good place,  the format mentioned before is detailed very nicely detailed in Kalen Delaney’s SQL Internal’s book so let’s use that as a guide.

• 2 Byte : Status Bits
• 2 Bytes: Offset to find number of columns
• X Bytes:Fixed Length Columns
• 2 Bytes: Total Number of Columns in the data row
• 1 Bit per column, Rounded up: Nullability Bitmap
• 2 Bytes:Number of Variable Length Columns within the data row
• 2 Bytes per variable length column : Row Offset marking the end of each variable length column
• X Bytes:Variable Length Columns

Ok, let’s start assigning the values from the log hex dump into the fields.

Status Bits (2 Bytes) : 3000
Offset to Find Number of Columns (2 Bytes) : 4100
Because of the endian ordering in effect, the offset should be read as 0041 – 65 in Decimal.  So there must be 61 Bytes of Fixed width data, since we have already used 4 bytes.

Let’s remind ourselves of the table structure:

CREATE TABLE [HumanResources].[Employee](
 [EmployeeID] [int] IDENTITY(1,1) NOT NULL,
 [NationalIDNumber] [nvarchar](15) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL,
 [ContactID] [int] NOT NULL,
 [LoginID] [nvarchar](256) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL,
 [ManagerID] [int] NULL,
 [Title] [nvarchar](50) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL,
 [BirthDate] [datetime] NOT NULL,
 [MaritalStatus] [nchar](1) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL,
 [Gender] [nchar](1) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL,
 [HireDate] [datetime] NOT NULL,
 [SalariedFlag] [dbo].[Flag] NOT NULL CONSTRAINT [DF_Employee_SalariedFlag]  DEFAULT ((1)),
 [VacationHours] [smallint] NOT NULL CONSTRAINT [DF_Employee_VacationHours]  DEFAULT ((0)),
 [SickLeaveHours] [smallint] NOT NULL CONSTRAINT [DF_Employee_SickLeaveHours]  DEFAULT ((0)),
 [CurrentFlag] [dbo].[Flag] NOT NULL CONSTRAINT [DF_Employee_CurrentFlag]  DEFAULT ((1)),
 [rowguid] [uniqueidentifier] ROWGUIDCOL  NOT NULL CONSTRAINT [DF_Employee_rowguid]  DEFAULT (newid()),
 [ModifiedDate] [datetime] NOT NULL CONSTRAINT [DF_Employee_ModifiedDate]  DEFAULT (getdate()),
 CONSTRAINT [PK_Employee_EmployeeID] PRIMARY KEY CLUSTERED

The fixed columns are as follows:

[EmployeeID] [int]  = 4
[ContactID] [int] = 4
[ManagerID] [int] = 4
[BirthDate] [datetime] = 8
[MaritalStatus] [nchar](1) = 2
[Gender] [nchar](1) = 2
[HireDate] [datetime] = 8
[SalariedFlag] [dbo].[Flag] = 1
[VacationHours] [smallint] = 2
[SickLeaveHours] [smallint] = 2
[CurrentFlag] [dbo].[Flag] = 0 - second bit.
[rowguid] [uniqueidentifier] = 16
[ModifiedDate] [datetime] = 8

Adventure Works uses a user defined type of Flag, which is just declared as a bit. So thats 61 bytes of fixed width storage – which is the value we expected.

We need to know the column order, we could assume it is the same as the table declaration, but we should double check the actual colum ordering to be certain.

select colorder, syscolumns.name
from syscolumns
inner join systypes on syscolumns.xusertype = systypes.xusertype
where id =object_id('HumanResources.Employee') and variable = 0
order by colorder

colorder name
-------- -------------
1        EmployeeID
3        ContactID
5        ManagerID
7        BirthDate
8        MaritalStatus
9        Gender
10       HireDate
11       SalariedFlag
12       VacationHours
13       SickLeaveHours
14       CurrentFlag
15       rowguid
16       ModifiedDate

So the order looks good, let’s start assigning values:

[EmployeeID] [int]  = 01000000 = 00000001 = 1
[ContactID] [int] = B9040000 = 000004B9 = 1209
[ManagerID] [int] = 10000000 = 00000001 = 1
[BirthDate] [datetime] = 0000000040670000 = 0000674000000000 = '1972-05-15 00:00:00.000'  - (Use Select convert(datetime, 0x0000674000000000) to check)
[MaritalStatus] [nchar](1) = 004D = 77 = UniCode for M (Use Select nchar(77) to check)
[Gender] [nchar](1) = 4D00 = 004D = 77 = M
[HireDate] [datetime] = 00000000CB890000 = 000089CB00000000 = '1996-07-31 00:00:00.000'
[SalariedFlag] [dbo].[Flag] = 4A = 01001010 in Binary, which will need further work.
[VacationHours] [smallint] = 1500 = 0015 = 21
[SickLeaveHours] [smallint] = 1E00 = 001E = 30
[CurrentFlag] [dbo].[Flag] = Contained within the First Flag Byte
[rowguid] [uniqueidentifier] = 4AD0E1AA37C27449B4D5935247737718
[ModifiedDate] [datetime] = 0000000035950000 = 0000953500000000 = '2004-07-31 00:00:00.000'
Number of Columns : 1000 = 0010 - = 16 Columns - which is correct.
Nullability Bitmap : 1 bit per Column, so 16/8 = 2 Bytes : 0000
Number of Variable Rows : 0300 = 0003 = 3 Variable Length Columns
Var Column End 1 : 5d00 = 005D = 93
Var Column End 2 : 8500 = 0085 = 133
Var Column End 3 : BD00 = 00BD = 189

The number of columns was at the offset of 65, that used 2 bytes, the nullability was 2, the variable number of rows was 2 bytes and each variable row pointer used a further 2 each, so the data starts at byte after e.g. 65 + 12 = 77. First variable width data ends at 93, so the first variable width column is using 16 bytes of space.

I should mention why the nullability bitmap was 2, all the columns are declared as not null, so the bitmap did not increase in size, if there was a single nullable column, then the bitmap would have a bit per column in the table  – not a bit per nullable column, it is an all or nothing approach.

Raw Values : 3100 3400 3400 3100 3700 3800 3000 3700

Reverse Bytes : 0031 0034 0034 0031 0037 0038 0030 0037
Result : 14417807  (You can use Select NChar(0x0031) etc to check each value.)

Next up is 93 to 133, a gap of 40 bytes.

Raw Values    : 6100 6400 7600 6500 6E00 7400 7500 7200 6500 
2D00 7700 6F00 7200 6B00 7300 5C00 6700 7500 7900 3100
Reverse Bytes : 0061 0064 0076 0065 006E 0074 0075 0072 0065 
002D 0077 006F 0072 006B 0073 005C 0067 0075 0079 0031
Output : adventure-works\guy1

Final column, should be 189 – 133 = 56 bytes long, which it is, and decoding it again in the same way gives the following.

Raw Values    : 5000 7200 6F00 6400 7500 6300 7400 6900 6F00 6E00 2000 5400 6500 6300
6800 6E00 6900 6300 6900 6100 6E00 2000 2D00 2000 5700 4300 3600 3000
Reverse Bytes : 0050 0072 006F 0064 0075 0063 0074 0069 006F 006E 0020 0054 0065 0063
 0068 006E 0069 0063 0069 0061 006E 0020 002D 0020 0057 0043 0036 0030
Result : Production Technician - WC60

That is the row contents decoded, and the deleted row’s original values are now exposed.

As you can see from the complexity of decoding one part of a trivial delete operation within the log, this is not something that you would wish to rely on / use as an audit trail etc. But hopefully it has provided some insight and added to the minimal documentation on how to approach the decoding process. I will try to decode more of the operations as, insert and update shouldn’t be too hard to manage, but sucess is not guarenteed.