I have a database ("DatabaseA") that I cannot modify in any way, but I need to detect the addition of rows to a table in it and then add a log record to a table in a separate database ("DatabaseB") along with some info about the user who added the row to DatabaseA. (So it needs to be event-driven, not merely a periodic scan of the DatabaseA table.)
I know that normally, I could add a trigger to DatabaseA and run, say, a stored procedure to add log records to the DatabaseB table. But how can I do this without modifying DatabaseA?
I have free-reign to do whatever I like in DatabaseB.
EDIT in response to questions/comments ...
Databases A and B are MS SQL 2008/R2 databases (as tagged), users are interacting with the DB via a proprietary Windows desktop application (not my own) and each user has a SQL login associated with their application session.
Any ideas?
Ok, so I have not put together a proof of concept, but this might work.
You can configure an extended events session on databaseB that watches for all the procedures on databaseA that can insert into the table or any sql statements that run against the table on databaseA (using a LIKE '%your table name here%').
This is a custom solution that writes the XE session to a table:
https://github.com/spaghettidba/XESmartTarget
You could probably mimic functionality by writing the XE events table to a custom user table every 1 minute or so using the SQL job agent.
Your session would monitor databaseA, write the XE output to databaseB, you write a trigger that upon each XE output write, it would compare the two tables and if there are differences, write the differences to your log table. This would be a nonstop running process, but it is still kind of a period scan in a way. The XE only writes when the event happens, but it is still running a check every couple of seconds.
I recommend you look at a data integration tool that can mine the transaction log for Change Data Capture events. We are recently using StreamSets Data Collector for Oracle CDC but it also has SQL Server CDC. There are many other competing technologies including Oracle GoldenGate and Informatica PowerExchange (not PowerCenter). We like StreamSets because it is open source and is designed to build realtime data pipelines between DB at the schema level. Till now we have used batch ETL tools like Informatica PowerCenter and Pentaho Data Integration. I can near real-time copy all the tables in a schema in one StreamSets pipeline provided I already deployed DDL in the target. I use this approach between Oracle and Vertica. You can add additional columns to the target and populate them as part of the pipeline.
The only catch might be identifying which user made the change. I don't know whether that is in the SQL Server transaction log. Seems probable but I am not a SQL Server DBA.
I looked at both solutions provided by the time of writing this answer (refer Dan Flippo and dfundaka) but found that the first - using Change Data Capture - required modification to the database and the second - using Extended Events - wasn't really a complete answer, though it got me thinking of other options.
And the option that seems cleanest, and doesn't require any database modification - is to use SQL Server Dynamic Management Views. Within this library residing, in the System database, are various procedures to view server process history - in this case INSERTs and UPDATEs - such as sys.dm_exec_sql_text and sys.dm_exec_query_stats which contain records of database transactions (and are, in fact, what Extended Events seems to be based on).
Though it's quite an involved process initially to extract the required information, the queries can be tuned and generalized to a degree.
There are restrictions on transaction history retention, etc but for the purposes of this particular exercise, this wasn't an issue.
I'm not going to select this answer as the correct one yet partly because it's a matter of preference as to how you approach the problem and also because I'm yet to provide a complete solution. Hopefully, I'll post back with that later. But if anyone cares to comment on this approach - good or bad - I'd be interested in your views.
I am trying to implement an ETL process for our Type 1 slowly changing dimension tables in a SQL 2014 database. The load needs to happen across servers, and I would prefer not to use linked servers.
I have been looking for ways to do this in SSIS and found the slowly changing dimension wizard which works fine except that this seems to only allow either inserting new rows or updating rows where there is a match on the business key, however I haven't found a place where it allows me to handle when a record exists in the dimension table but was deleted from the source. I would like to make sure these are deleted. Am I missing something? Has anyone found a better way to handle this in SSIS?
I know that I could just dump everything into another table on the destination server and write a TSQL merge, but there just seems like should be a simple way to do this in SSIS.
First, I would avoid the SCD functionality in SSIS, as its performance tends to be terrible - I've actually been told to avoid it by MS certified trainers, as well as plenty of people with a lot of experience. It's OK-ish on very small dimensions, but quickly tends to become unmanageable. There's a blog post here from someone who thinks it's usable in some situations, but even they suggest using a staging table for updates.
If you want to do this in SSIS you could use a Lookup to find the rows that need to be deleted (find the rows in your destination which aren't in the source using the no match output), then an OLE DB Command to delete them. But I'd give some serious thought to simply moving the data over to a staging area and doing this in TSQL, because SSIS will do it row by agonising row. Similarly to the SCD tool - it might be OK on small amounts of data, but if you're dealing with larger amounts (or might be in future), it may well become unmanageable.
If you don't want to move all of the data over to a staging area, you could use SSIS to build up a table only holding the unique IDs of the rows that need deleting, then fire off an Execute SQL Task from the Control Flow to delete them all at once.
To allow more realistic conditions during development and testing, we want to automate a process to copy our SQL Server 2008 databases down from production to developer workstations. Because these databases range in size from several GB up to 1-2 TB, it will take forever and not fit onto some machines (I'm talking to you, SSDs). I want to be able to press a button or run a script that can clone a database - structure and data - except be able to specify WHERE clauses during the data copy to reduce the size of the database.
I've found several partial solutions but nothing that is able to copy schema objects and a custom restricted data without requiring lots of manual labor to ensure objects/data are copied in correct order to satisfy dependencies, FK constraints, etc. I fully expect to write the WHERE clause for each table manually, but am hoping the rest can be automated so we can use this easily, quickly, and frequently. Bonus points if it automatically picks up new database objects as they are added.
Any help is greatly appreciated.
Snapshot replication with conditions on tables. That way you will get your schema and data replicated whenever needed.
This article describes how to create a merge replication, but when you choose snapshot replication the steps are the same. And the most interesting part is Step 8: Filter Table Rows. of course, because with this you can filter out all the unnecessary data to get replicated. But this step needs to be done for every entity and if you've got like hundreds of them, then you'd better analyze how to do that programmatically instead of going through the wizard windows.
My company has recently put up a demo database on his remote servers to allow some of our partners to test our beta version of the software.
We noticed, as expected, some bottlenecks in some parts of the program, in particular on the places in which many queries are done.
For example, I have to load customer from database, with all his products associated to him.
Normally this operation would be done as
select somefields from customers where id = someId
Store it to business class
select someotherfiels from products where customerid = previousid
store to collection and show/use them.
Imagine a much more complex business logic, which would gather 8 to 12 tables in the same way. With a local database, this would be instant. But by connecting to a remotely hosted SQL Server, this is extremely slow.
We found out that making a single query, like
SELECT Customer.Field1, Customer.Field2, Product.Field1, Product.Field2,
--//LIST OTHER 200 FIELDS FROM 10 DIFFERENT TABLE SE SAME WAY
FROM Customer
LEFT JOIN Product ON Product.IdCustomer = Customer.IdCustomer
--//LEFT JOIN OTHER 10 TABLES THE SAME WAY
WHERE Customer.IdCustomer = 10
amazingly improved the speed of the whole execution.
The fact that this is more complex than the single selects of each of them doesn't compare to the fact that is only one access to the server.
I am talking about ~2000/3000ms to 80-120ms.
Here comes the true problem (sorry about the long preface).
How can i save data to a remote SQL Server in an efficient way?
Imagine i have a window/form/dialog/frame/whatever where i ought to save more tables after a given operation.
For example:
INSERT INTO Customer (Field) VALUES ('hello world') "IdCustomer" is an identity column
Fetch the new Id from database
INSERT INTO SomeLinkedTable (IdCustomer, Field) VALUES (x, 'new value')
Fetch new "IdSomeLinkedTable", use it to link some table, ecc ecc..
This is a common way of multiple saving in our program. Even if we don't leave the user without some message that the operation is gonna take a while, waiting ~10s to do a frequent multi-insert operation is way too much.
Maybe it's a simple server configuration problem, but i swear all the firewalls in both sides (our & server) are properly configured to allow some SQL Server access.
Anyone encountered the same problem?
If you pulled all your business logic into the app layer, then your app layer must live close to the database.
The solution to make a fast and snappy remote applicaiton is to use fiefdoms-and-emissaries so you remove the tight coupling to the database.
As an interim solution you can speed up any operation by removing the round-trips to the database. If you have to save a master-detail form, you send the entire operation as a single T-SQL batch (INSERT header, SELECT ##identity, INSERT all details) as one single batch. Of course, in practice this means you moved your business logic into the T-SQL batches, and now that the logic lives in the database is better to have in in stored procs anyway.
At the end of the day, you can't have your cake and eat it too. You can either make a autonomous disconnected application that supports a remote, ocassionally connected db, and demo that, or make a tightly coupled application that must live close to the database and demo that.
In an update project i have to do the following:
Move 3 databases from SQL2000 to SQL2005 and merge them at the same time. There are already quite a few cross database queries used in SP's and Views.
The current plan is to move each of the old databases into a separate schema in 1 database.
That means we will also have to change our current SP's and Views, we now have:
SELECT OrderId, OrderDate FROM Sales.dbo.Orders
and expect we will have to change that into
SELECT OrderId, OrderDate FROM Sales.Orders
The question is: how do we do that as automated as possible?
I know about SED and similar for changing the scripts. I would welcome tips about how to be 'smart' about this, like strategies for partitioning the scripts, performance (tons of INSERT INTO lines) etc.
Note: I did look at the Import/Export Wizard but apparently I would have to set the Schema manually on each output table and fix the SP's through ALTER scripts anyway.
I did this a couple of years ago, and I ran into a few problems that you want to be aware of.
Assumptions:
You've got a single SQL 2000 database server with 3 databases, A/B/C
You want all of the objects to end up in SQL 2005 in database A (we'll refer to that as the Target)
You want to get rid of databases B and C eventually (the old Sources)
You don't have a full-blown test environment where you can automatically restore your production databases every day, and script this again and again until it's right. (That's the best way, and I've taken that approach too, but it's labor-intensive.)
Here's my hard lessons learned:
Don't do the merge and the SQL 2005 change the same day. Either do the merge before you go to 2005, or after, but don't try to accomplish it all in a single outage. It'll be a finger-pointing mess. If it was me, I'd go to 2005 first just to get it out of the way. That way, I know anything that breaks isn't because of a schema change, and those types of breaks are easier to fix. You want at least a week of end user activity on the 2005 box before you declare victory and move on to the merge.
Build the new objects in Target ahead of time. Even if they're not being queried in your live production apps, go ahead and build 'em now. That way you can populate fake test data in there to test your applications ahead of time. Yes, this means mixing live and test data, but frankly, you're already out there working without a net. Be wary of identity fields, though, since you can end up with conflicting records with the same identity number but different data in the Target and Source databases.
Create views in Target ahead of time. You mentioned that you've got views that already do cross-database queries. Copy those from Source to Target now, and tell any other developers (report guys, power users) to start referring to the Target views instead. This isn't going to speed up your own work, but it speeds up THEIR work. If you can get to the point where you can verify that they're only hitting Target (even though the Target views still point to tables in Source) then it'll make troubleshooting easier on migration day. Then you can start denying permissions on the Source views ahead of time.
Sync tables ahead of time. Make a list of all of the tables that need to be moved out of the Sources, and for each one, analyze how it's being updated. If it's only being inserted into (not updated or deleted), like a log table, then write a T-SQL script to start keeping it in sync in Target. Run that script via a SQL Agent job during periods of low activity on your server, like nightly. This way, when it's go-live day, you won't have to push as many records around, meaning your go-live window will be smaller and your Target transaction logs can stay smaller. Tables that are being constantly updated or deleted aren't as easy, and it's up to you whether you decide to sync those as well. We did it for any tables over a million lines.
Check for record conflicts between the Source databases. It sounds like this one doesn't apply to you specifically, but I'm noting it here in case anybody else does a merge and they're reading it for tips. If you have more than one Source database, dump out the list of objects. If you've got two objects with the same name, check their schema. I've worked with instances where they had a State or Region table in each database, and they were supposed to be identical, but they had identity fields for their primary keys. Each child table (like Customers, which linked to a Region table) referred to the parent table (Region) by the primary key (identity field) - which didn't match from one database to the other. In that case, the smart thing to do is take an outage window ahead of time, before the migration day, to clean those records up with manual update scripts.
Disable any constraints or foreign key relationships
Change the identity fields (if they're lookup tables, you may be able to turn off the identity stuff and just run with manually specified pk numbers)
Modify the Region table to add a NewID field, matching to what it's going to become, and an OldID field, showing what it used to be
Update all of the child tables (Customers) to use the NewID number instead of the original
Update the Region table so that the real ID field now has the NewID value, and the OldID field has what the Region used to be. (You're probably going to screw something up like miss a child table you didn't know about, and you're going to wonder what it used to be.)
Break the migration into pieces. List every stored proc in all of the databases. If any of them can be moved without moving data, do that first. For example, if you've got Source.dbo.usp_RunReport, and it only refers to tables in the Target database, then do that in a first phase. If you've got small system lookup tables that are only used internally in your app, not visible to customers or reports, then put that in the first phase too. It sounds like it's too small to bother with, but the idea is to reduce the amount of panic on migration day. The less you wonder about, the better you can troubleshoot. We moved every static lookup table (State, Region, Calendar, etc) over ahead of time. The amount of work required in Phase 1 - just moving those small, static tables - got management to understand how huge it was going to be to move the rest, and it bought us resources and time we wouldn't have gotten otherwise.
Pre-grow the data files for Target. If you're not using SQL 2005's new Instant File Initialization, data file growths take quite a while. Enable Instant File Initialization if you've got a choice, then grow the data files to make sure they're not fragmented. If they just grow naturally during your migration day, they can be fragmented. If you can't use Instant File Initialization, you still need to pre-grow the files, but you want to do that ahead of time during periods of low activity to speed up the maintenance window.
On migration day, run your inserts one table at a time, or smaller. You want to keep your insert transactions as tight as possible. The smaller your insert transactions, the less space you'll need in the transaction log. Remember that the transaction log will grow with insert statements even in simple mode. After every round of inserts, do a sanity check to make sure that they worked, and that you're not going to run out of drive space for data files or t-log files.
After the updates finish, change security on the Source databases. Put every non-SA login into the dbdenydatareader and dbdenydatawriter roles in the Source databases. That way they can still log in if they've hard-coded the database name in the connection string, but they won't be able to do anything. This makes your troubleshooting easier too: if an app or a query runs into problems, you could consider taking their login out of the deny roles and see if it works - if it does, it's borked. The risk with that is that they might run a transaction that uses the Source database data to update the Target database (get customers from Source, update them in Target) and it might cause issues.
Other options for the Source databases are:
Rename them, so you can still query 'em but the apps won't touch 'em
Detach them, but keep the files available in case you need to troubleshoot
Strip out all logins, and use new logins to access the existing databases just in case. Then if somebody's read-only report is totally borked, you can let it work temporarily by issuing them a new login and telling them it's referring to the wrong database.
After the updates finish, rebuild indexes & statistics on Target. If you're just doing continuous inserts, this isn't a big deal, but if you're merging multiple databases (like two Sales databases that had been broken up into regions of the country) then you'll want to clean things up.
IMHO, use one schema unless you can justify a gain from multiple schemas. This last one is just my two cents, but it sounds like you're going through an awful lot of work to go from 3 databases 1 schema each, to 1 database with 3 schemas. If you're not really sure about the 3 schema thing, you might consider using 1 schema - or else you'll be in another messy rework later on down the road. 3 schemas does make sense if you have specific security needs, but otherwise, just make sure you're getting the bang for the buck that you want. Now would be a great time to go to one schema.
You could give Redgate SQL Compare and Data Compare a shot. They have a schema mapping feature that should let you map the dbo schema to the sales schema in another and then move the tables and procs. It would make it so you don't have to mess with the SQL export wizard. You still would have to refactor your other objects though.
I love these two tools.
edit:
I think you can get a fully functional demo too.
edit:
Additionally, they offer SQL Refactor, which does a 'smart' rename. Score!
Could you have a dummy database called SALES that has a VIEW called [Orders]:
CREATE VIEW Sales.dbo.Orders
AS
SELECT OrderId, OrderDate, ...
FROM CombinedDatabase.Sales.Orders
and then
SELECT ... FROM Sales.dbo.Order
will still work.
You won't be able to INSERT / UPDATE that table without some further jiggery-pokery though.
If you could have such VIEWs log that they were used that would enable you to fix the code that called them!! but I can't think of a way to do that; however you could disable each in turn, run some tests, fix whatever is broken, then move on to next one ... and thus eradicate them by refactoring, but have a largely working application during the process.
I've used SED for this type of thing, but we have unique names for all our tables and all our columns, and we use variable names within our application that match the database column names - so I would have high confidence that changing xxx_yyy_ID to aaa_bbb_ID in our application would work well, and not have accidental side effects.
If you have actual column/table names like "Sales" and "Orders" I think that something like SED would be risky
Ok, so my basic understanding of your problem is something like this:
You have three different databases (i.e. Sales, Manu, Inventory)
They have distinct table & procedure names (no table/proc names in Sales exist in Manu or Inventory)
You want all the tables/procs from all three databases in a single database (i.e. SaleManInv)
Some stored procedures in each database explicitly refer to tables in the other databases (i.e. Sales.dbo.lookupItem() explicitly refers to Inventory.dbo.Items table)
Exporting and importing the tables doesn't seem like it will be a problem, what I would do for the procs:
Export one proc from the SQL Server 2000 db to the SQL Server 2005 DB to determine if you need to get rid of the ".dbo." portion of the cross references.
Export all the procs to text files (same folder for all procs)
Use a text editor with a "Search and Replace in Files" (I use PSPAD) and replace all the "Sales.dbo." with "SaleManInv.dbo.", then all the "Iventory.dbo." with "SameManInv.dbo." etc. to convert all the references to the new db.
Then run the exported and modified procs into your new db.
Is that making any sense? :-)
I was in a similar position where I had several SQL Server 2008 databases that were merged into 1. My solution was to use Integration Services' Transfer Server Objects task into a new target database. All data was copied over along with tables. Afterwards - in what was a very complex query, I scripted out all stored procedures/functions/views/etc. to a file and changed all cross-database references and re-created the stored procedures and other objects.
The trick with the stored procedures was to script them out in the order or syscontraints in order to ensure that stored procedures or functions that were referencing other stored procedures/functions internally were created last.
If there was a tool that I felt could have handled this task in an automated fashion, I would have purchased it immediately.
I would like to know if it's same kind of data. Any way. I would create a new column with the name 'SourceSystem'. So when the boss comes running after:
" - what was the sales diff between databasesystem1 and db2 in 2004".
Then you can answer that. Then in a year or two, if that questions don't pop up. You can delete that column. Merging data removes the origin of the data.