如果您添加的实体（）依赖于上下文中的其他预加载实体（例如导航财产），则Dispose（）上下文会产生问题

我使用类似的概念来保持我的上下文较小，以实现相同的性能

但我只是分离已经SaveChanges（）的实体，而不是Dispose（）上下文并重新创建

public void AddAndSave<TEntity>(List<TEntity> entities) where TEntity : class {

const int CommitCount = 1000; //set your own best performance number here
int currentCount = 0;

while (currentCount < entities.Count())
{
    //make sure it don't commit more than the entities you have
    int commitCount = CommitCount;
    if ((entities.Count - currentCount) < commitCount)
        commitCount = entities.Count - currentCount;

    //e.g. Add entities [ i = 0 to 999, 1000 to 1999, ... , n to n+999... ] to conext
    for (int i = currentCount; i < (currentCount + commitCount); i++)        
        _context.Entry(entities[i]).State = System.Data.EntityState.Added;
        //same as calling _context.Set<TEntity>().Add(entities[i]);       

    //commit entities[n to n+999] to database
    _context.SaveChanges();

    //detach all entities in the context that committed to database
    //so it won't overload the context
    for (int i = currentCount; i < (currentCount + commitCount); i++)
        _context.Entry(entities[i]).State = System.Data.EntityState.Detached;

    currentCount += commitCount;
} }

如果需要，用try-catch和TrasactionScope（）将其包装起来，为了保持代码干净，没有在这里显示它们

使用SqlBulkCopy：

void BulkInsert(GpsReceiverTrack[] gpsReceiverTracks)
{
    if (gpsReceiverTracks == null)
    {
        throw new ArgumentNullException(nameof(gpsReceiverTracks));
    }

    DataTable dataTable = new DataTable("GpsReceiverTracks");
    dataTable.Columns.Add("ID", typeof(int));
    dataTable.Columns.Add("DownloadedTrackID", typeof(int));
    dataTable.Columns.Add("Time", typeof(TimeSpan));
    dataTable.Columns.Add("Latitude", typeof(double));
    dataTable.Columns.Add("Longitude", typeof(double));
    dataTable.Columns.Add("Altitude", typeof(double));

    for (int i = 0; i < gpsReceiverTracks.Length; i++)
    {
        dataTable.Rows.Add
        (
            new object[]
            {
                    gpsReceiverTracks[i].ID,
                    gpsReceiverTracks[i].DownloadedTrackID,
                    gpsReceiverTracks[i].Time,
                    gpsReceiverTracks[i].Latitude,
                    gpsReceiverTracks[i].Longitude,
                    gpsReceiverTracks[i].Altitude
            }
        );
    }

    string connectionString = (new TeamTrackerEntities()).Database.Connection.ConnectionString;
    using (var connection = new SqlConnection(connectionString))
    {
        connection.Open();
        using (var transaction = connection.BeginTransaction())
        {
            using (var sqlBulkCopy = new SqlBulkCopy(connection, SqlBulkCopyOptions.TableLock, transaction))
            {
                sqlBulkCopy.DestinationTableName = dataTable.TableName;
                foreach (DataColumn column in dataTable.Columns)
                {
                    sqlBulkCopy.ColumnMappings.Add(column.ColumnName, column.ColumnName);
                }

                sqlBulkCopy.WriteToServer(dataTable);
            }
            transaction.Commit();
        }
    }

    return;
}

我同意亚当·拉基斯的观点。SqlBulkCopy是将批量记录从一个数据源传输到另一数据源的最快方法。我用这个复制了20K张唱片，只用了不到3秒钟。看看下面的例子。

public static void InsertIntoMembers(DataTable dataTable)
{           
    using (var connection = new SqlConnection(@"data source=;persist security info=True;user id=;password=;initial catalog=;MultipleActiveResultSets=True;App=EntityFramework"))
    {
        SqlTransaction transaction = null;
        connection.Open();
        try
        {
            transaction = connection.BeginTransaction();
            using (var sqlBulkCopy = new SqlBulkCopy(connection, SqlBulkCopyOptions.TableLock, transaction))
            {
                sqlBulkCopy.DestinationTableName = "Members";
                sqlBulkCopy.ColumnMappings.Add("Firstname", "Firstname");
                sqlBulkCopy.ColumnMappings.Add("Lastname", "Lastname");
                sqlBulkCopy.ColumnMappings.Add("DOB", "DOB");
                sqlBulkCopy.ColumnMappings.Add("Gender", "Gender");
                sqlBulkCopy.ColumnMappings.Add("Email", "Email");

                sqlBulkCopy.ColumnMappings.Add("Address1", "Address1");
                sqlBulkCopy.ColumnMappings.Add("Address2", "Address2");
                sqlBulkCopy.ColumnMappings.Add("Address3", "Address3");
                sqlBulkCopy.ColumnMappings.Add("Address4", "Address4");
                sqlBulkCopy.ColumnMappings.Add("Postcode", "Postcode");

                sqlBulkCopy.ColumnMappings.Add("MobileNumber", "MobileNumber");
                sqlBulkCopy.ColumnMappings.Add("TelephoneNumber", "TelephoneNumber");

                sqlBulkCopy.ColumnMappings.Add("Deleted", "Deleted");

                sqlBulkCopy.WriteToServer(dataTable);
            }
            transaction.Commit();
        }
        catch (Exception)
        {
            transaction.Rollback();
        }

    }
}

您应该考虑为此使用System.Data.SqlClient.SqlBulkCopy。这是文档，当然还有很多在线教程。

抱歉，我知道您正在寻找一个简单的答案来让EF做您想做的事情，但批量操作并不是ORM真正的用途。

秘密是插入到相同的空白暂存表中。插件快速发光。然后在主大表中运行一个单独的插入。然后截断临时表，为下一批做好准备。

ie.

insert into some_staging_table using Entity Framework.

-- Single insert into main table (this could be a tiny stored proc call)
insert into some_main_already_large_table (columns...)
   select (columns...) from some_staging_table
truncate table some_staging_table

〔2019更新〕EF Core 3.1

如上所述，在EF Core中禁用AutoDetectChangesEnabled非常有效：插入时间除以100（从几分钟到几秒，10k条记录具有交叉表关系）

更新的代码为：

context.ChangeTracker.AutoDetectChangesEnabled = false;
foreach (IRecord record in records) {
    //Add records to your database        
}
context.ChangeTracker.DetectChanges();
context.SaveChanges();
context.ChangeTracker.AutoDetectChangesEnabled = true; //do not forget to re-enable