C# Optimisation: Inserting 200 million rows into d

问题:

I have the following (simplified) code which I'd like to optimise for speed:

long inputLen = 50000000; // 50 million 
DataTable dataTable = new DataTable();
DataRow dataRow;
object[] objectRow;
while (inputLen--)
{
    objectRow[0] = ...
    objectRow[1] = ...
    objectRow[2] = ...

    // Generate output for this input
    output = ...

    for (int i = 0; i < outputLen; i++) // outputLen can range from 1 to 20,000
    {
         objectRow[3] = output[i];
         dataRow = dataTable.NewRow();
         dataRow.ItemArray = objectRow;
         dataTable.Rows.Add(dataRow);
    }
}

// Bulk copy
SqlBulkCopy bulkTask = new SqlBulkCopy(connection, SqlBulkCopyOptions.TableLock, null);
bulkTask.DestinationTableName = "newTable";
bulkTask.BatchSize = dataTable.Rows.Count;
bulkTask.WriteToServer(dataTable);
bulkTask.Close();

I'm already using SQLBulkCopy in an attempt to speed things up, but it appears assigning values to the DataTable itself proves to be slow.

I don't know how DataTables work so I'm wondering if I'm creating unnecessary overhead by first creating a reusable array, then assigning it to a DataRow, then adding the DataRow to the DataTable? Or is using DataTable not optimal in the first place? The input comes from a database.

I don't care much about LOC, just speed. Can anyone give some advice on this?

回答1:

For such a big table, you should instead use the

public void WriteToServer(IDataReader reader)

method.

It may mean you'll have to implement yourself a "fake" IDataReader interface with your code (if you' don't get the data from an existing IDataReader), but this way, you'll get "streaming" from end to end, and will avoid a 200 million loop.

回答2:

Instead of holding a huge data table in memory, I would suggest implementing a IDataReader which serves up the data as the bulk copy goes. This will reduce the need to keep everything in memory upfront, and should thus serve to improve performance.

回答3:

You should not construct entire datatable in memory. Use this overload of WrtieToServer, that takes array of DataRow. Just split in chunks your data.