The Hidden Scaling Trap in Entity Framework's .Contains

When using the .Contains method in Entity Framework Core queries, there is a hidden scaling trap that can negatively impact performance when querying SQL Server. This issue stems from a limitation in the number of parameters SQL Server can handle, which is set at 2100.

Entity Framework Core handles .Contains queries in two different ways depending on the number of parameters. If the total number of parameters is below 2100, SQL Server generates a WHERE ... IN clause with each parameter. However, if the parameter count exceeds this limit, Entity Framework Core uses the SQL Server Table value function OPENJSON to generate the query.

This reliance on OPENJSON can lead to significant performance degradation. To explain further, SQL Server generates a query plan to determine the best execution strategy for a given query. Unfortunately, when table value functions like OPENJSON are involved, SQL Server cannot accurately estimate the number of rows it will return. Consequently, it makes an approximate estimation (50 in this case), leading to suboptimal query performance.

In practice, this means that queries using the OPENJSON approach can take an excessive amount of time to execute, sometimes even six minutes when working with tables containing millions of rows. This performance bottleneck can occur without any warning, as developers may not be aware of this hidden scaling trap in Entity Framework Core.

To mitigate this issue, there are two possible solutions. A short-term fix is to break up queries into smaller chunks, sending them as separate database calls. While this approach may introduce additional overhead due to the increased number of database roundtrips, it can help avoid the severe performance degradation associated with the OPENJSON approach.

A long-term solution involves leveraging Entity Framework Core 3's interceptors. With interceptors, developers can replace the OPENJSON table value function with an ad-hoc table parameter, which can help restore performance. This can be achieved by augmenting the actual query text that is sent to SQL Server, replacing the problematic OPENJSON function with a more efficient table parameter.