Limiting Number of Rows Inserted into a SQL Server Database - c#

I have a program in c# in VS that runs a mainform.
That mainform exports data to an SQL Database with stored procedures into tables. The data exported is a lot of data (600,000 + rows).
I have a problem tho. On my mainform I need to have a "database write out interval". This is a number of how many "rows" will be imported into the database.
My problem is however the steps on how to implement that interval. The mainform runs, and when the main program is done, the sql still takes IN data for another 5-10 minutes.
Therefore, if I close the mainform, the rest of the data will not me imported.
Do you professional programmers out there know a way where I can somehow communicate with SQL to only export data for a user-specified interval. T
his has to be done with my c# class.
I dont know where to begin.
I dont think a timer would be a good idea because differenct computers and cpu's perform differently. Any advice would be appreciated.

If the data is of a fixed format (ie, there are going to be the same columns for every row and its not going to change much), you should look at Bulk Insert. Its incredibly fast at inserting large numbers of rows.
The basics are you write your data out to a text file (ie, csv, but you can specify whatever delimiter you want), then execute a BULK INSERT command against the server. One of the arguments is the path to the file you wrote out. It's a bit of a pain to use because you have to write the file in a folder on the server (or a UNC path that the server has access to) which leads to configuring windows shares or setting up FTP on the server. It sounds like exactly what you want to use, though.
Here's the MSDN documentation on BULK INSERT:
http://msdn.microsoft.com/en-us/library/ms188365.aspx

Instead of exporting all of your data to SQL and then trying to abort or manage the load a a better process might be to split your load into smaller chunks (10,000 records or so) and check whether the user wants to continue after each load. This gives you a lot more flexibility and control over the load then dumping all 600,000 records to SQL and trying to manage the process.
Also what Tim Coker mentioned is spot on. Even if your stored proc is doing some data manipulation it is a lot faster to load the data via bulk insert and run a query after the load to do any work you have to do then to run all 600,000 records through the stored proc.

Like all the other comments before, i will suggest you to use BulkInsert. You will be amazed by how fast the performance is when it comes to large dataset and perhaps your concept about interval is no longer required. Inserting 100k of records may only take seconds.
Depends on how your code is written, ADO.NET has native support for BulkInsert through SqlBulkCopy, see the code below
http://www.knowdotnet.com/articles/bulkcopy_intro1.html
If you have been using Linq to db for your code, there are already some clever code written as extension method to the datacontext which transform the linq changeset into a dataset and internally use ADO.NET to achieve the bulk insert
http://blogs.microsoft.co.il/blogs/aviwortzel/archive/2008/05/06/implementing-sqlbulkcopy-in-linq-to-sql.aspx

Related

Reading Huge Data Using SQL Stored Procedure and C# (SQL Server 2005)

We have a requirement to pull huge data from SQL Server 2005 database for reporting purpose. Our stored procedure is returning more than 15,000 rows.
When I call the procedure from the application (MVC 4.0) the request is timing out!!! (May be because of the data size)
Is there is any best practice to read such a huge data from SQL Server 2005 database using
MVC 4.0 Application???
You're seeing a timeout because your SQL query takes a long time to finish. This is not due to the size of the result (15,000 records is not a huge amount of data), but because the query runs inefficiently.
Maybe you're missing a couple of indices, maybe the stored procedure is written the wrong way - it's impossible to know from here. Try optimizing your query or database (if you have a DBA available, they can help. If not, the Management Studio can have some tips for you).
If you can't optimize the query or the database, you're left with increasing the time out, as others suggested.
Even i faced the same problem, but i was about to render more than 1,48,000 records. So the solution for this is using multithreading. You will be having one method which fetches the data from database, call that particular method in a seperate thread. Your data will be loaded in less than 5 seconds. Multithreading has been introduced only to manipulate large number of data without lagging performance.
First Que is why you are not using Dataset and Data source view in the Reporting(If its reporting in SQL server).
If its not Reporting Services and you only want to use C# code then try to make some helper function for it.
see here for the timeout option
http://forums.asp.net/t/1040377.aspx
and also here for optimising the code and SP
enter link description here
Here are couple tips on how you can use to optimize this:
Optimize query – see if you can optimize your query in some way. Add indices to your tables, check where statements and such.. I can’t really give you any specific recommendations w/o seeing the query and knowing the schema. See what others have already suggested on this topic.
Limit the amount of data stored procedure is returning – my guess is that MVC app doesn’t really need all 15k rows but a lot more. Check out this post: efficient way to implement paging . This will not speed up the query so much but it will make the app more efficient.

SQL Server data import dilemma

I have created an application that will be importing CSV files into a database table, and I've got multiple CSV files I need to import into a table in a SQL Server database.
I've got a couple approaches in mind but I'm not sure which is most practical. The application works by asking the user to select the files they want to import (from their local file system) and then they simply click a [Load Files] button. These files may contain 100,000+ rows at times.
What would be better for the above scenario?
Import CSV file into datatable using C# and open-source GenericParser then using a traditional method of BulkCopy to push the datatable to the database
Note: my concern is the strain on users PC when doing this for files with 100,000+ rows. How will this affect the processing or would it crash the program?
Use Bulk Insert which requires the file name and path. My concern for this option is I'm not sure if the server would be able to process the Bulk Insert command without the physical file being located on the server? The file path would relate to the users local machine. The only time I've used Bulk Insert is when I was logged onto the server itself, which is not possible for this app.
Is there a way to do it with Linq? While I'm not really familiar with Linq if it can be accomplished I'm open to trying it.
Any insight is appreciated. I know what I need to do just not sure of how to accomplish it practically.
Thanks
My recommendation would be to use the SqlBulkCopy class in .NET. It will allow you to import rows almost as fast at the BULK INSERT statement, but only requires that you populate a DataTable with the rows, and then send them to SQL Server.
Another consideration you might want to look at would be (and this is my personal favorite for simple file import programs) to use PowerShell instead of C#, which has a built-in cmdlet for imporing CSV files. Pretty cool stuff.
1) loader app in .Net is a good choice, generally. 100,000 rows is really not a strenuous workload, especially for simple loads. Only if there is a ton of multiple-table-joins involved in order to look up values on the fly would that really be a big concern.
2) although strictly speaking physical file location is just a performance question, I wouldn't do it. It will introduce administrative headaches.
3) I don't have experience with Linq, I cannot remark.
Just for bonus alternate idea: if you have IIS running somewhere, maybe even on the DB server, you can whip up a lightweight, one-page "webapp" which is just a CGI script with ODBC connection to the DB and the user just feeds the CSV in as a "web/CGI" upload. No utility application to install on user workstations this way.
To solve your problem, you have to see on in two basic views:
Do you need make some operations with data before insert in into database (some sumarization, correction,...)?
If yes, than here is the best way to upload rows from file to object (each row into one object instance). And than you can elegantly move with list of items with Linq.
Do you need only insert rows from file to database as they are?
I this case, use process described in point 2 of your question.
I'd prefer to upload file to server before any action. It's more safe.

C# Importing Large Volume of Data from CSV to Database

What's the most efficient method to load large volumes of data from CSV (3 million + rows) to a database.
The data needs to be formatted(e.g. name column needs to be split into first name and last name, etc.)
I need to do this in a efficiently as possible i.e. time constraints
I am siding with the option of reading, transforming and loading the data using a C# application row-by-row? Is this ideal, if not, what are my options? Should I use multithreading?
You will be I/O bound, so multithreading will not necessarily make it run any faster.
Last time I did this, it was about a dozen lines of C#. In one thread it ran the hard disk as fast as it could read data from the platters. I read one line at a time from the source file.
If you're not keen on writing it yourself, you could try the FileHelpers libraries. You might also want to have a look at Sébastien Lorion's work. His CSV reader is written specifically to deal with performance issues.
You could use the csvreader to quickly read the CSV.
Assuming you're using SQL Server, you use csvreader's CachedCsvReader to read the data into a DataTable which you can use with SqlBulkCopy to load into SQL Server.
I would agree with your solution. Reading the file one line at a time should avoid the overhead of reading the whole file into memory at once, which should make the application run quickly and efficiently, primarily taking time to read from the file (which is relatively quick) and parse the lines. The one note of caution I have for you is to watch out if you have embedded newlines in your CSV. I don't know if the specific CSV format you're using might actually output newlines between quotes in the data, but that could confuse this algorithm, of course.
Also, I would suggest batching the insert statements (include many insert statements in one string) before sending them to the database if this doesn't present problems in retrieving generated key values that you need to use for subsequent foreign keys (hopefully you don't need to retrieve any generated key values). Keep in mind that SQL Server (if that's what you're using) can only handle 2200 parameters per batch, so limit your batch size to account for that. And I would recommend using parameterized TSQL statements to perform the inserts. I suspect more time will be spent inserting records than reading them from the file.
You don't state which database you're using, but given the language you mention is C# I'm going to assume SQL Server.
If the data can't be imported using BCP (which it sounds like it can't if it needs significant processing) then SSIS is likely to be the next fastest option. It's not the nicest development platform in the world, but it is extremely fast. Certainly faster than any application you could write yourself in any reasonable timeframe.
BCP is pretty quick so I'd use that for loading the data. For string manipulation I'd go with a CLR function on SQL once the data is there. Multi-threading won't help in this scenario except to add complexity and hurt performance.
read the contents of the CSV file line by line into a in memory DataTable. You can manipulate the data (ie: split the first name and last name) etc as the DataTable is being populated.
Once the CSV data has been loaded in memory then use SqlBulkCopy to send the data to the database.
See http://msdn.microsoft.com/en-us/library/system.data.sqlclient.sqlbulkcopy.writetoserver.aspx for the documentation.
If you really want to do it in C#, create & populate a DataTable, truncate the target db table, then use System.Data.SqlClient.SqlBulkCopy.WriteToServer(DataTable dt).

Upload a Massive CSV File to SQL Server Database

I need to upload a massive (16GB, 65+ million records) CSV file to a single table in a SQL server 2005 database. Does anyone have any pointers on the best way to do this?
Details
I am currently using a C# console application (.NET framework 2.0) to split the import file into files of 50000 records, then process each file. I upload the records into the database from the console application using the SqlBulkCopy class in batches of 5000. To split the files takes approximately 30 minutes, and to upload the entire data set (65+ million records) takes approximately 4.5 hours. The generated file size and the batch upload size are both configuration settings, and I am investigating increasing the value of both to improve performance. To run the application, we use a quad core server with 16GB RAM. This server is also the database server.
Update
Given the answers so far, please note that prior to the import:
The database table is truncated, and all indexes and constraints are dropped.
The database is shrunk, and disk space reclaimed.
After the import has completed:
The indexes are recreated
If you can suggest any different approaches, or ways we can improve the existing import application, I would appreciate it. Thanks.
Related Question
The following question may be of use to others dealing with this problem:
Potential Pitfalls of inserting millions of records into SQL Server 2005 from flat file
Solution
I have investigated the affect of altering batch size, and the size of the split files, and found that batches of 500 records, and split files of 200,000 records work best for my application. Use of the SqlBulkCopyOptions.TableLock also helped. See the answer to this question for further details.
I also looked at using a SSIS DTS package, and a BULK INSERT SQL script. The SSIS package appeared quicker, but did not offer me the ability to record invalid records, etc. The BULK INSERT SQL script whilst slower than the SSIS package, was considerably faster than the C# application. It did allow me to record errors, etc, and for this reason, I am accepting the BULK INSERT answer from ConcernedOfTunbridgeWells as the solution. I'm aware that this may not be the best answer for everyone facing this issue, but it answers my immediate problem.
Thanks to everyone who replied.
Regards, MagicAndi
BULK INSERT is run from the DBMS itself, reading files described by a bcp control file from a directory on the server (or mounted on it). Write an application that splits the file into smaller chunks, places them in an appropriate directory executes a wrapper that executes a series of BULK INSERTS. You can run several threads in parallel if necessary.
This is probably about as fast as a bulk load gets. Also, if there's a suitable partitioning key available in the bulk load file, put the staging table on a partition scheme.
Also, if you're bulk loading into a table with a clustered index, make sure the data is sorted in the same order as the index. Merge sort is your friend for large data sets.
Have you tried SSIS (SQL Server Integration Services).
The SqlBulkCopy class that you're already using is going to be your best bet. The best you can do from here in your c# code is experiment with your particular system and data to see what batch sizes work best. But you're already doing that.
Going beyond the client code, there might be some things you can do with the server to make the import run more efficiently:
Try setting the table and database size before starting the import to something large enough to hold the entire set. You don't want to rely on auto-grow in the middle of this.
Depending on how the data is sorted and any indexes one the table, you might do a little a better to drop any indexes that don't match the order in which the records are imported, and then recreate them after the import.
Finally, it's tempting to try running this in parallel, with a few threads doing bulk inserts at one time. However, the biggest bottleneck is almost certainly disk performance. Anything you can do to the physical server to improve that (new disks, san, etc) will help much more.
You may be able to save the step of splitting the files as follows:
Instantiate an IDataReader to read the values from the input CSV file. There are several ways to do this: the easiest is probably to use the Microsoft OleDb Jet driver. Google for this if you need more info - e.g. there's some info in this StackOverflow question.
An alternative method is to use a technique like that used by www.csvreader.com.
Instantiate a SqlBulkCopy object, set the BatchSize and BulkCopyTimeout properties to appropriate values.
Pass the IDataReader to SqlBulkCopy.WriteToServer method.
I've used this technique successfully with large files, but not as large as yours.
See this and this blog posts for a comparison.
It seems the best alternative is to use BulkInsert with the TABLOCK option set to true.
Have you tried using the Bulk Insert method in Sql Server?
Lately, I had to upload/import a lot of stuff, too (built a PHP script).
I decided to process them record-for-record.
Of course, it takes longer, but for me, the following points were important:
- easily pause the process
- better debugging
This is just a tip.
regards,
Benedikt
BULK INSERT is probably already the fastest way. You can gain additional performance by dropping indexes and constraints while inserting and reestablishing them later. The highest performance impact comes from clustered indexes.
Have you tried SQL Server Integration Services for this? It might be better able to handle such a large text file
Just to check, your inserting will be faster if there are no indexes on the table you are inserting into.
My scenario for things like that is:
Create SSIS Package on SQL server which using BLUK insert into sql,
Create stored procedure inside the DataBase to can run that Package from T-SQL code
After that send file for bluk insert to SQL server using FTP and call SSIS Package usinfg stored procedure

What are the pitfalls of inserting millions of records into SQL Server from flat file?

I am about to start on a journey writing a windows forms application that will open a txt file that is pipe delimited and about 230 mb in size. This app will then insert this data into a sql server 2005 database (obviously this needs to happen swiftly). I am using c# 3.0 and .net 3.5 for this project.
I am not asking for the app, just some communal advise here and potential pitfalls advise. From the site I have gathered that SQL bulk copy is a prerequisite, is there anything I should think about (I think that just opening the txt file with a forms app will be a large endeavor; maybe break it into blob data?).
Thank you, and I will edit the question for clarity if anyone needs it.
Do you have to write a winforms app? It might be much easier and faster to use SSIS. There are some built-in tasks available especially Bulk Insert task.
Also, worth checking Flat File Bulk Import methods speed comparison in SQL Server 2005.
Update: If you are new to SSIS, check out some of these sites to get you on fast track. 1) SSIS Control Flow Basics 2) Getting Started with SQL Server Integration Services
This is another How to: on importing Excel file into SQL 2005.
This is going to be a streaming endeavor.
If you can, do not use transactions here. The transactional cost will simply be too great.
So what you're going to do is read the file a line at a time and insert it in a line at a time. You should dump failed inserts into another file that you can diagnose later and see where they failed.
At first I would go ahead and try a bulk insert of a couple of hundred rows just to see that the streaming is working properly and then you can open up all you want.
You could try using SqlBulkCopy. It lets you pull from "any data source".
Just as a side note, it's sometimes faster to drop the indices of your table and recreate them after the bulk insert operation.
You might consider switching from full recovery to bulk-logged. This will help to keep your backups a reasonable size.
I totally recommend SSIS, you can read in millions of records and clean them up along the way in relatively little time.
You will need to set aside some time to get to grips with SSIS, but it should pay off. There are a few other threads here on SO which will probably be useful:
What's the fastest way to bulk insert a lot of data in SQL Server (C# client)
What are the recommended learning material for SSIS?
You can also create a package from C#. I have a C# program which reads a 3GL "master file" from a legacy system (parses into an object model using an API I have for a related project), takes a package template and modifies it to generate a package for the ETL.
The size of data you're talking about actually isn't that gigantic. I don't know what your efficiency concerns are, but if you can wait a few hours for it to insert, you might be surprised at how easy this would be to accomplish with a really naive technique of just INSERTing each row one at a time. Batching together a thousand or so rows at a time and submitting them to SQL server may make it quite a bit faster as well.
Just a suggestion that could save you some serious programming time, if you don't need it to be as fast as conceivable. Depending on how often this import has to run, saving a few days of programming time could easily be worth it in exchange for waiting a few hours while it runs.
You could use SSIS for the read & insert, but call it as a package from your WinForms app. Then you could pass in things like source, destination, connection strings etc as parameter/configurations.
HowTo: http://msdn.microsoft.com/en-us/library/aa337077.aspx
You can set up transforms and error handling inside SSIS and even create logical branching based on input parameters.
If the column format of the file matches the target table where the data needs to end up, I prefer using the command line utility bcp to load the data file. It's blazingly fast and you can specify and error file for any "odd" records that fail to be inserted.
Your app could kick off the command if you need to store the command line parameters for it (server, database, username / password or trusted connection, table, error file etc.).
I like this method better than running a BULK INSERT SQL command because the data file isn't required to be on a system accessible by the database server. To use bulk insert you have to specify the path to the data file to load, so it must be a path visible and readable by the system user on the database server that is running the load. Too much hassle for me usually. :-)

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