In the previous blog http://blogs.msdn.com/sqlserverstorageengine/archive/2008/12/31/managing-tempdb-in-sql-server-tempdb-basics-version-store-logical-structure.aspx , I described the logical/physical structure of a row in version store. A natural question that comes up is how these pages are grouped together and how does SQL Server garbage collect these rows. You may recall that if you need to DELETE a large number of rows from a table, an efficient option is to truncate or even drop the table rather than deleting one row at a time. For this reason, the SQL Server groups the row versions in a physical unit called ‘Append-Only store’. All the versioned rows in an Append-Only store are garbage collected together. Alternatively, you can think of Append-Only store as an internal table, but it is not really a table like #table, and this table is dropped once SQL Server determines that it does not need the row versions in it. You can see that this operation is much more efficient compared to deleting 1 versioned row at a time. A new ‘Append-Only Store’ is created very minute, if needed (i.e. if there is no transactional activity that generates a row version, the Append-Only store will not be created). The version store represents the aggregation of all active ‘Append-Only’ stores.
Let us now work through an example to illustrate the functioning of the version store. For simplicity, let us assume that the transactional activity is such that a new Append-Only store is being created every minute. Let us say that Append-Only store AS1 was created at time T and the two subsequent Append-Only stores AS2 and AS3 were created at time (T+1) and (T+2) respectively. You may now wonder how SQL Server chooses a specific Append-Only store to “insert” the row version. Well, the SQL Server associates an Append-Only store to a transaction at its start. So for example, for transactions that start between T and (T+1), the version store is stored in AS1. Similarly, for transactions that start between (T+1) and (T+2), the row versions are stored in AS2. Note, a transaction may be long running say 5 minutes and can be generating row versions throughout its life time, but still all the row versions it creates go to the Append-Only store that was assigned to it in the begin of the transaction. You can also imagine that in its life-time, each Append-Only store will have different sizes depending upon the row versions generated by associated transactions. One important point that I did not mention earlier is the “insert” into the Append-Only store are not logged. Why? Well if SQL Server has to fail, all active transactions will be rolled back anyways so the SQL Server does not need the “state” of version store as of the time when SQL Server stopped.
Let us now look at when it is safe to remove an Append-Only store. To remove an Append-Only store, the SQL Server must guarantee that no transaction will need to look at the row versions it contains. For the above example, to remove Append-Only store AS1, the following conditions must be met
1. All transactions that started between T and (T + 1) have completed. Let us say that these transactions completed at time T2.
2. All transactions that started between time T and T2 needing row versions (i.e. the transactions running with RCSI or SI) from AS1 have completed.
3. All Append-Only stores created before AS1 have been removed
Here are some key observations (a) typically, the transactions commit in the order they were started so this scheme of deleting Append-Only store works well. (b) if you have a long running transaction, it will prevent deleting Append-Only stores created since the start of the transaction. This can cause version store to grow and subsequently the TempDB may go out of space. While this may sound alarming but it is similar to when a long running transaction can cause the transaction log to fill up. The key difference here is that the impact of versioning is wider as it can impact all databases that need to create row versions. Typically a long running transaction indicates a poor application design. SQL Server provides tools to detect the version store growth. I will cover this in troubleshooting section in later blogs.
On another note, you may wonder how the version store is managed for ONLINE index which can potentially take an order of magnitude more time than a transaction. The SQL Server gets around this issue by ‘internally’ creating another version store, distinct from the one I just described, for ONLINE index build containing the row versions of the table on which the index is being built.
This concludes my discussion on the version store. I will cover the troubleshooting of version store as part of overall troubleshooting of TempDB. Hope this provided you with some deeper understanding and I look forward to your comments. I also want to take this opportunity to wish you all a very happy new year.