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?
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.For such a big table, you should instead use the
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 existingIDataReader
), but this way, you'll get "streaming" from end to end, and will avoid a 200 million loop.You should not construct entire datatable in memory. Use this overload of WrtieToServer, that takes array of DataRow. Just split in chunks your data.