In part 1 of this series, I talked about my current customer’s decision to abandon the use of the variations feature in Microsoft Office SharePoint Server (MOSS) 2007 after we encountered several major issues prior to deployment. The first issue that I described is the incompatibility of out-of-the-box (OOTB) content types and variations. Refer to the previous post for a simple set of repro steps to break the variations feature by changing the content type of pages.
One thing I forgot to mention in the previous post that is related to the issues with content types and variations:
You may think you are safe from the variation/content type bugs if you don’t change the content type of the default page. However, also be aware that the variations feature does not enable content types on the Pages libraries in the variation sites. Consequently, if you have any pages that specify a content type other than the default Page, Article Page, or Welcome Page, then you are going to break the variations feature if you attempt to propagate pages before the additional content types have been enabled on the Pages libraries (either manually or through some automated fashion). Oh, and good luck enabling these additional content types before propagation begins after creating a new variation label. Feature stapling (i.e. not relying on the OOTB Publishing with Workflow site definition like we did) might allow you to curcumvent this problem. However we did not explore this possibility, I am just thinking out loud here.
Anyway, on to the second major issue that we encountered…
It is important to note that we are currently on the second major version (i.e. v2) of the solution for this customer. In v1, we migrated a custom document management system to MOSS 2007. Consequently, prior to starting our v2 solution, we had about 120,000 items in our AllUserData table and approximately 150,000 items in our AllDocs table.
As I mentioned in the previous post, a big part of our v2 solution is migrating this customer’s 3,200 FAQs and 500 other pages from a legacy custom code soluton to MOSS. Also note that this customer provides this content in English, Japanese, Korean, Simplified Chinese, and Traditional Chinese. Thus our initial design included the following variations: en-US (the source label), ja-JP, ko-KR, zh-CN, and zh-TW.
After we modified our content migration tools to circumvent the issues with variations and content types (as described in part 1), we were able to migrate FAQ pages to the en-US site and the variations system subsequently propagated each page to each variation site (e.g. ja-JP). The problem was that, in our Test environment (TEST), we were only propagating about one page (to the four variation sites) every minute. Thus our initial “guess-timate” was around 3,700 minutes (around 62 hours) for the initial migration. Ugh!
What was really puzzling is that in our Development environment (DEV), we observed propagation throughput of about 3 pages every minute. Note that DEV is comprised of a bunch of VMs running on a single server. TEST has separate physical servers for the Web front-end, SSP, and active-passive SQL Server cluster (complete with SAN storage). However, it is also important to note that we only configured two variation labels (en-US and ja-JP) in DEV (we just needed to prove that our approach worked), whereas TEST had all five variation labels (en-US, ja-JP, ko-KR, zh-CN, and zh-TW). It certainly seemed, in my mind at least, that the “beefier” hardware in TEST should more than compensate for the additional variation labels.
However, the problem got worse — meaning the throughput of the propagation to the variation sites deteriorated rapidly as more and more pages were loaded.
At that point, I sent a message out to one of our internal lists inquiring if anyone had experienced similar performance problems with variations. An MCS peer in Europe replied that he had seen 3,000 pages take 7 days to propagate. Ouch.
After investigating the perf problem, I discovered that the fundamental problem was due to the very lengthy SQL SELECT inside one of the PRIME (a.k.a. the SharePoint content deployment API) stored procedures (specifically, proc_DeplGetListItemData). On the Friday we kicked off the FAQ migration, this sproc was taking 30-40 seconds to complete. By the following Tuesday, it was taking roughly 100 seconds for each execution. Note that proc_DeplGetListItemData is just one part of the variation propagation. On Tuesday morning, each variation page propagation was taking about 10 minutes (to the four variation sites).
Seven days for 3,000 pages was looking optimistic at that point (most likely because we had more variation labels than my peer in Europe).
Examining the execution plan for the lengthy SQL statement inside proc_DeplGetListItemData identified that a Key Lookup was being performed on the AllUserData table. In our environment we were seeing on the order of 2M reads for this one SELECT statement. It is also important to note that users began complaining about the overall performance of SharePoint in this environment while the migration was running.
The slow performance was subsequently confirmed by SQL Profiler traces. The traces identified that INSERTs, UPDATEs, and SELECTs on the AllUserData table (such as proc_AddListItem, proc_UpdateDocument, proc_UpdateListItem, proc_CheckOutDocument, etc.) would often require more than 60 seconds to complete – obviously due to the very high I/O being performed on the AllUserData table.
In parallel with another team member raising the issue to PSS and the Product Group, I then analyzed the SELECT statement in proc_DeplGetListItemData to determine an index that could be added to eliminate the Key Lookup and greatly reduce the time required to execute this sproc.
I tested three different indexes on the AllUserData table and found similar results for all three – decreasing the execution time from around 140 seconds to approximately 2.2 seconds. Of the three indexes, the following was deemed to be the “least expensive” (in terms of overhead with DML operations):
CREATE INDEX Idx_AllUserData_Tmp2
A couple of things to note about the index:
The naming convention implies that this is not intended to be final manifestation of this fix (you cannot add an index — or make any other changes — to your SharePoint database unless it has been approved by PSS, unless you don’t object to falling under the “unsupported” moniker)
Since tp_DirName specifies a server relative URL, this was chosen as the first column in the index – rather than tp_SiteId.
In environments where the content database only contains a single site collection (such as ours), including tp_SiteId provides essentially no value (i.e. it does not influence the selectivity of the index)
Lastly, it is worth noting that even after adding the index to TEST, we were still experiencing relatively long execution times with other sprocs during the variation page propagation – specifically proc_DeplAddExportObjectLinks and, to a lesser extent, proc_DeplCalculateChildrenToExport. I attempted to resolve this in a similar fashion by creating a similar index on the AllDocs table. However, the initial index attempted did not improve performance and I abandoned additional tuning efforts due to schedule and resource constraints.
SQL Profiler traces continued to show some latency in the various PRIME sprocs:
Over a 3-1/2 hour period, approximately 900 operations took longer than 1 second (a small fraction compared with before the index was added)
Of the 900, a small fraction were in the 10-12 second range (e.g. proc_DeplAddExportObjectLinks)
Overall, performance drastically improved with the new index on AllUserData. However, even with the index, variations page propagations still took around one minute to propagate to four variation sites (just prior to adding the index, page propagations were taking about 10 minutes and gradually taking longer as more pages were added).
By the way, as of this time of this post, we never did receive a “blessing” from PSS or the Product Group on my index recommendation. In fact, we are still waiting for PSS to repro the performance problem (we ended up having to ship them a copy of our database). It baffles me that PSS doesn’t have sample “large” databases in their labs for reproducing performance problems.
Even though it won’t do my current customer any good (since they decided to abandon variations), we are still pursuing a QFE for the variations propagation performance problem, hoping that it will potentially help other customers in the future.
[Part 3 in this series is now available.]