I have about a dozen related tables that I have suppose to implement a tracking system for. I cannot use triggers or trace. I am also specific the the types of changes that I have to track such as a certain type of user. How would I get started?
How about this one:
Track Data changes
Related
I wanted to know how many people are accessing a particular ssas cube. Please let me know the process to find them.
I don't think there's a simple way to get connected users from a cube. You can use a couple of different tools to collect that information (along with lot's of other information as well).
To get a list for users currently connected to a SSAS instance, you might use SQL Server Profiler. Then you can filter one cube from the resulting data.
For tracking users extended period of time, you can use Extended events
Both of these tools create data for a lot of data and you'll need to parse distinct users from that is some way.
To see the current sessions:
SELECT * FROM $System.DISCOVER_SESSIONS
I'm looking for an auditing solution that does exactly what Change Data Capture (CDC) does, except I need it to also track the application user that made the change. I'm currently using SQL Server 2012 Enterprise and may be upgrading to 2014 later this year.
We already have an auditing solution in place that leverages Delete, Insert, and Update triggers, but some new requirements might force us to update every audit trigger and corresponding audit table. Given various problems we've run in to with that solution over the years, this seems like as good a time as any to reevaluate and potentially replace the solution.
To give you an idea of what I'm currently working with (and may be able to leverage), we use a stored procedure (ConnectionInitialize) to store a user id with a SPID in a table (ApplicationUser) and then we delete the row using another stored procedure (ConnectionReset) once we're done making our deletes, inserts, and updates.
Were we to use CDC, I looked into adding a trigger to something like the cdc.lsn_time_mapping table, but I couldn't find a way to map the LSN back to the SPID (and therefore the user id) that was being used. This also presented some other issues in that CDC is always a little bit behind.
I looked into SQL Server Audit a little bit, but that presented some challenges of its own. We're using Transparent Data Encryption (TDE) to appease some of our security requirements, but SQL Server Audit looks like it'd need a separate encryption strategy; that and I'm more interested in the columns than in the actual SQL statements. Even so, these aren't deal-breakers for me, so I'm still looking into it.
Given what I'm trying to accomplish, does anyone have any feedback or recommendations?
By itself, CDC doesn't meet the requirements. The reason being is that CDC only grabs changes to your data, not any underlying context under which those changes were made. You can, however, get what you're looking for if you're willing to tag your data with some audit columns. The basic idea is that you append a column to your table (or to a different table if you aren't able to modify the actual table for whatever reason) and populate it with the user who last modified the record (pretty simple to do via an insert/update trigger). Once that is actual data, you can consume it however you need to (CDC being one possible mechanism).
Late answer but hopefully useful.
There is a third party tool, ApexSQL Audit, capable of meeting your requirements. My previous company is using it for years and they have been satisfied with it.
There is a helpful comparison article you can read to find more details about audited data, auditing mechanisms, integrity protection etc, for both CDC & Audit tool at one place.
I have a database with 50 tables and I want to log users requests, such as inserts, updates or deletes on all the tables in the database. I can also create a trigger for this for each request type.
What is the best way to do this from a performance perspective or is there a better way to track this?
You can also create audit tables which are populated by triggers (and which allow much more flexibility than change data capture). The critical component is to capture sets of data not try to work row-by-row. It does add some overhead yes, but if you write the triggers correctly, it isn't that much. Be sure to capture who (including which application if you have multiple applications hitting the database) and when as well as the old and new values. Set up one audit table per table you want audited (too much locking if you use only one audit table). And at the time you set up your system, write the code to get data back from a bad transaction or set of transactions. That makes it easier to recover when you do have something go wrong and you need to revert. We use two tables per table audited, one contains the info about the process that did the changes (name of the application, date, user, etc. and an auditid), the other contains the details about what was changed (old and new values, ID of the record being affected and column affected). Our structure enables us to use the same structure for each table being audited, and allows the tables to change without having to change the audit table and allows us to easily script the audit tables for a new tables. It is also easy for us to see what records were changed at the same time or in the same process or to find out which of the many applications which touch our database was responsible for the bad data as well as telling us who in particular was responsible for the bad data. This helps us track down application bugs and find out why the data was changed the way it was in some cases. It also makes it easier for us to track down all the data that was affected by a broken process rather than just the one we knew about.
If you have Enterprise Edition, look into Change Data Capture. If you don't have Enterprise and aren't interested in capturing the historical values of the columns that change, look into Change Tracking.
See Comparing Change Data Capture and Change Tracking to understand the differences between the two.
Assuming all requests to insert, update and/or delete data goes through some middle-tier data access layer, I would suggest you do your logging there. This is where we do all of ours. It is much simpler than trying to extract the actual insert / delete / update statements out of SQL Server.
If you want to do auditing of data, you can look into Change Data Capture (CDC). But this requires the Enterprise Edition.
I wan't sure how to word this question so I'll try and explain. I have a third-party database on SQL Server 2005. I have another SQL Server 2008, which I want to "publish" some of the data in the third-party database too. This database I shall then use as the back-end for a portal and reporting services - it shall be the data warehouse.
On the destination server I want store the data in different table structures to that in the third-party db. Some tables I want to denormalize and there are lots of columns that aren't necessary. I'll also need to add additional fields to some of the tables which I'll need to update based on data stored in the same rows. For example, there are varchar fields that contain info I'll want to populate other columns with. All of this should cleanse the data and make it easier to report on.
I can write the query(s) to get all the info I want in a particular destination table. However, I want to be able to keep it up-to-date with the source on the other server. It doesn't have to be updated immediately (although that would be good) but I'd like for it be updated perhaps every 10 minutes. There are 100's of thousands of rows of data but the changes to the data and addition of new rows etc. isn't huge.
I've had a look around but I'm still not sure the best way to achieve this. As far as I can tell replication won't do what I need. I could manually write the t-sql to do the updates perhaps using the Merge statement and then schedule it as a job with sql server agent. I've also been having a look at SSIS and that looks to be geared at the ETL kind of thing.
I'm just not sure what to use to achieve this and I was hoping to get some advice on how one should go about doing this kind-of thing? Any suggestions would be greatly appreciated.
For that tables whose schemas/realtions are not changing, I would still strongly recommend Replication.
For the tables whose data and/or relations are changing significantly, then I would recommend that you develop a Service Broker implementation to handle that. The hi-level approach with service broker (SB) is:
Table-->Trigger-->SB.Service >====> SB.Queue-->StoredProc(activated)-->Table(s)
I would not recommend SSIS for this, unless you wanted to go to something like dialy exports/imports. It's fine for that kind of thing, but IMHO far too kludgey and cumbersome for either continuous or short-period incremental data distribution.
Nick, I have gone the SSIS route myself. I have jobs that run every 15 minutes that are based in SSIS and do the exact thing you are trying to do. We have a huge relational database and then we wanted to do complicated reporting on top of it using a product called Tableau. We quickly discovered that our relational model wasn't really so hot for that so I built a cube over it with SSAS and that cube is updated and processed every 15 minutes.
Yes SSIS does give the aura of being mainly for straight ETL jobs but I have found that it can be used for simple quick jobs like this as well.
I think, staging and partitioning will be too much for your case. I am implementing the same thing in SSIS now but with a frequency of 1 hour as I need to give some time for support activities. I am sure that using SSIS is a good way of doing it.
During the design, I had thought of another way to achieve custom replication, by customizing the Change Data Capture (CDC) process. This way you can get near real time replication, but is a tricky thing.
I know SQL Server 2008 can do this, but essentially I need a way to log all the changes made to a database. I don't need to log selects, and I don't need to log the user, the only important data is what has been added or changed, both with regard to data and structural changes like columns, tables, and indices.
What are my options?
I've used AutoAudit quite a bit, you simply apply it to whatever tables you wish to audit.
Main drawback is that it requires a single column PK. But most of my tables have surrogate identity PKs, so it's fine for that design philosophy.
Event Notifications can be deployed to monitor all schema changes at the database and even entire isntance level.
Global gata changes is not possible to monitor. You can select specific tables to monitor and deploy a trigger based monitoring. There are also low-impact log bassed solutions, but not out-of-the-box, they all need third party tools.