This post is to share a script I’ve been working on periodically over the last couple of months to monitor and report on replication latency at the distributor.
I use this in monitoring transactional replication with a stand-alone distributor.
My life is a bit easier since I learned how to use SQL agent tokens. They are particularly nice for setting date and timestamps on backup files. Unfortunately, they only work in the context of executing agent jobs.
There’s some pretty cool things about SSMS 2008– I am really pleased that execution plans open graphically by default now, and it’s easy to view the XML on demand. I had gotten pretty fast at saving things as .sqlplan, but it was a bit of a drag.
Until recently I’d never used the deadlock graph event in Profiler. I’ve been pretty lucky and haven’t had to troubleshoot deadlocks much until now. The deadlock graph turns out to be quite nice!
This past week at work we found an instance where a replicated table (transactional push) was out of sync on the subscriber. In evaluating how to address the situation, we did some testing in pre-production and discovered the following (using profiler).
I often need to find a query plan in the cache for a process that has run long overnight. Typically I’ll be able to figure out from our logging some of the tables involved in the query. Sometimes I will have most of the executing text but won’t know exactly what dates or reference points were included.
Update from Kendra (Nov 2018): I’m keeping this post for posterity, but I REALLY don’t recommend the script. You’d be much better off using a production monitoring tool that did this job, or @AdamMachanic ‘s sp_WhoIsActive.
Maybe you’re a user in a reporting database running a long query in the read committed isolation level, merrily blocking a process which needs to load data.
As an add on to my last post, here is what I currently do use to track index usage. This shows usage, columns in the index, and index size on disk. The size can be quite useful to know when evaluating how much an index is worth– typically if this index is large then you’re paying a fair amount on the inserts.
Update: improved/more recent version of queries for this are here.
It can be pretty difficult to manage statistics in data warehouses, or even OLTP databases that have very large tables.
One reason I started this blog was just the idea of going through my catalog of scripts and reviewing them and sharing out what might be useful to people.
Here is a quick one I put together a while back. I was starting to work with a group of servers [at an unnamed company, always an unnamed company!]. Some of the instances had been configured long ago, and I found some linked servers where passwords had been hardcoded into the login mappings.
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