I'm loading large amounts of data from a text file into SQL Server. Currently each record is inserted (or updated) in a separate transaction, but this leaves the DB in a bad state if a record fails.
I'd like to put it all in one big transaction. In my case, I'm looking at ~250,000 inserts or updates and maybe ~1,000,000 queries. The text file is roughly 60MB.
Is it unreasonable to put the entire operation into one transaction? What's the limiting factor?
It's not only not unreasonable to do so, but it's a must in case you want to preserve integrity in case any record fails, so you get an "all or nothing" import as you note. 250000 inserts or updates will be no problem for SQL to handle, but I would take a look at what are those million queries. If they're not needed to perform the data modification, I would take them out of the transaction, so they don't slow down the whole process.
You have to consider that when you have an open transaction (regardless of size), looks will occur at the tables it touches, and lengthy transactions like yours might cause blocking in other users that are trying to read them at the same time. If you expect the import to be big and time-consuming and the system will be under load, consider doing the whole process over the night (or any non-peak hours) to mitigate the effect.
About the size, there is no specific size limit in SQL Server, they can theoretically modify any amount of data without problems. The practical limit is really the size of the transaction log file of the target database. The DB engine stores all the temporary and modified data in this file while the transaction is in progress (so it can use it to roll it back if needed), so this file will grow in size. It must have enough free space in the DB properties, and enough HD space for the file to grow. Also, the row or table locks that the engine will put on the affected tables consumes memory, so the server must have enough free memory for all this plumbing too. Anyway, 60MB in size is often too little to worry about generally. 250,000 rows is considerable, but not that much too, so any decent-sized server will be able to handle it.
SQL Server can handle those size transactions. We use a single transaction to bulk load several million records.
The most expensive part of a database operation is usually the client server connection and traffic. For inserts/updates indexing and logging are also expensive, but you can mitigate those costs by using the correct loading techniques(see below). You really want to limit the amount of connections and data transfered between client and server.
To that end, you should consider bulk loading the data using SSIS or C# with SqlBulkCopy. Once you bulk load everything then you can use set based operations ON THE SERVER to update or verify your data.
Take a look at this question for more suggestions about optimizing data loads. The question is related to C# but a lot of the information is useful for SSIS or other loading methods. What's the fastest way to bulk insert a lot of data in SQL Server (C# client) .
There is no issue with doing an all or nothing bulk operation, unless a complete rollback is problematic for your business. In fact, a single transaction is the default behavior for a lot of bulk insert utilities.
I would strongly advise against a single operation per row. If you want to weed out bad data, you can load the data into a staging table first and pro grammatically determine "bad data" and skip those rows.
Well personally, I don't load imported data directly to my prod tables ever and I weed out all the records which won't pass muster long before I ever get to the point of loading. Some kinds of errors kill the import completely and others might just send the record to an exception table to be sent back to the provider and fixed for the next load. Typically I have logic that determines if there are too many exceptions and kills the package as well.
For instance suppose the city is a reuired field in your database and in the file of 1,000,000 records, you have ten that have no city. It is probably best to send them to an exception table and load the rest. But suppose you have 357,894 records with no city. Then you might need to be having a conversation with the data provider to get the data fixed before loading. It will certainly affect prod less if you can determine that the file is unuseable before you ever try to affect production tables.
Also, why are you doing this one record at a time? You can often go much faster with set-based processing especially if you have already managed to clean the data beforehand. Now you may still need to do in batches, but one record at a time can be very slow.
If you really want to roll back the whole thing if any part errors, yes you need to use transactions. If you do this in SSIS, then you can put transactions on just the part of the package where you affect prod tables and not worry about them in the staging of the data and the clean up parts.
