- .net linq ef increase db command timeout generator#
- .net linq ef increase db command timeout software#
Still new to LINQ? Below are some real quick starters My numbers can be 10% up and down as I had come to that figure using my environmental situations. In this article, we will first look into how LINQ queries are executed, and then we will touch base on how compiled LINQ queries can help us improve our application performance at least 5 times.
.net linq ef increase db command timeout generator#
I am sure you will never like to touch a DBML code generator again. Try doing this, make a simple LINQ to SQL project using DBML and see your SQL profiler. Well, if you are just going to drag and drop using a DBML code generator, I am sure you will land up in a mess. LINQ has been criticized by many early adopters for its performance issues.
.net linq ef increase db command timeout software#
Hardware and software configuration used for test conduction.Steps involved in writing compiled LINQ queries.Still new to LINQ? Some real quick starters.("Many hours" is an estimation, I never finished this test, I stopped at 50.000 entities after 20 minutes.) This non-linear behaviour is not so significant in all other tests.
The behaviour in the first test above is that the performance is very non-linear and decreases extremely over time. commitCount = 1000, recreateContext = true: 191 sec.commitCount = 100, recreateContext = true: 164 sec.commitCount = 10, recreateContext = true: 241 sec.commitCount = 1, recreateContext = true: more than 10 minutes.commitCount = 1000000, recreateContext = false: out of memory exception.commitCount = 100000, recreateContext = false: 199 sec.
commitCount = 10000, recreateContext = false: 202 sec. commitCount = 1000, recreateContext = false: 242 sec. commitCount = 100, recreateContext = false: more than 20 minutes. commitCount = 1, recreateContext = false: many hours (That's your current procedure). Here are a few measurements for my 560000 entities: So, it is helpful to clear it after some time. It is the growing size of attached entities in the context what slows down the insertion step by step. This clears the context from all entites, SaveChanges doesn't do that, the entities are still attached to the context in state Unchanged. It also improves the performance to dispose the context after SaveChanges and create a new one. With this code it works in less than 3 minutes.įor the performance it is important to call SaveChanges() after "many" records ("many" around 100 or 1000). I have a test program which inserts 560.000 entities (9 scalar properties, no navigation properties) into the DB. Private MyDbContext AddToContext(MyDbContext context,Įntity entity, int count, int commitCount, bool recreateContext) Call SaveChanges() after for example 100 records and dispose the context and create a new one.įor bulk inserts I am working and experimenting with a pattern like this: using (TransactionScope scope = new TransactionScope())Ĭ = false įoreach (var entityToInsert in someCollectionOfEntitiesToInsert)Ĭontext = AddToContext(context, entityToInsert, count, 100, true). Call SaveChanges() after for example 100 records. Call SaveChanges() once after ALL records. I would do a few simple tests which will very likely improve the performance: That's the worst thing you can do! Calling SaveChanges() for each record slows bulk inserts extremely down. To your remark in the comments to your question: So the answer is to manually set the CommandTimeout in your repository on your context object like so: = 180 Īpparently setting the timeout settings in the connection string has no effect on it. When I removed the Default Command Timeout from the connection string, it worked. I had both the connection string with Default Command Timeout=300000 and the CommandTimeout set to 180. OK – I got this working and it's silly what happened. The timeout period elapsed prior to completion of the operation or the server is not responding. 圜ommandExecutionException: An error occurred while executing the command definition. Everything works fine with small datasets. What else can I do to get the EF from timing out? This only happens for very large datasets. I tried setting the CommandTimeout in my repository directly like so: private TrekEntities context = new TrekEntities() This is what my connection string looks like: I added Default Command Timeout=300000 to the connection string in the App.Config file in the project that has the EDMX file as suggested here. I tried the following and have not been able to resolve this issue: I am getting timeouts using the Entity Framework (EF) when using a function import that takes over 30 seconds to complete.
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