How Can I Optimize Bulk Inserts in Entity Framework for Improved Performance?

Boosting Entity Framework Bulk Insert Performance: Strategies and Benchmarks

Efficiently inserting large datasets into Entity Framework is crucial for avoiding performance bottlenecks. This article tackles the challenge of inserting 4000 records within a transaction, a scenario prone to incomplete transactions.

Avoiding the Pitfalls of Frequent SaveChanges() Calls

The primary performance drain stems from repeatedly calling SaveChanges() for each record. This approach significantly slows down the process. Here's how to optimize:

1. Single SaveChanges() Call: Execute a single SaveChanges() call after all records are added.

2. Batched SaveChanges() Calls: Insert records in batches (e.g., 100 or 1000) and call SaveChanges() after each batch.

3. Context Disposal with Batched SaveChanges(): Combine batching with creating a new database context after each SaveChanges() call. This clears the context, further enhancing performance.

Optimized Bulk Insert Pattern:

This code illustrates the recommended approach:

using (TransactionScope scope = new TransactionScope())
{
    using (MyDbContext context = new MyDbContext())
    {
        context.Configuration.AutoDetectChangesEnabled = false;

        int count = 0;
        int commitCount = 100; // Adjust as needed
        foreach (var entity in someCollection)
        {
            count++;
            context.Set<entity>().Add(entity);

            if (count % commitCount == 0)
            {
                context.SaveChanges();
                context.Dispose();
                context = new MyDbContext();
                context.Configuration.AutoDetectChangesEnabled = false;
            }
        }
        context.SaveChanges();
    }
    scope.Complete();
}

Performance Analysis:

Testing with 560,000 entities (9 scalar properties) yielded these results:

• Incremental SaveChanges() (commit count 1): > 20 minutes
• Batched SaveChanges() (commit count 1000): 242 seconds
• Batched SaveChanges() with Context Disposal (commit count 100): 164 seconds

Conclusion:

By avoiding frequent SaveChanges() calls and utilizing batched inserts with context disposal, significant performance gains are achieved in Entity Framework bulk inserts. This optimization minimizes the risk of transaction timeouts and ensures efficient data handling within active transactions.

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