Reputation: 739
I have a DataSet
which contains just one Table
, so you could say I'm working with a DataTable here.
The code you see below works, but I want to have the best and most efficient way to perform the task because I work with some data here.
Basically, the data from the Table should later be in a Database, where the primary key - of course - must be unique.
The primary key of the data I work with is in a column called Computer Name
. For each entry we also have a date in another column date
.
I wrote a function which searches for duplicates in the Computer Name
column, and then compare the dates of these duplicates to delete all but the newest.
The Function I wrote looks like this:
private void mergeduplicate(DataSet importedData)
{
Dictionary<String, List<DataRow>> systems = new Dictionary<String, List<DataRow>>();
DataSet importedDataCopy = importedData.Copy();
importedData.Tables[0].Clear();
foreach (DataRow dr in importedDataCopy.Tables[0].Rows)
{
String systemName = dr["Computer Name"].ToString();
if (!systems.ContainsKey(systemName))
{
systems.Add(systemName, new List<DataRow>());
}
systems[systemName].Add(dr);
}
foreach (KeyValuePair<String,List<DataRow>> entry in systems) {
if (entry.Value.Count > 1) {
int firstDataRowIndex = 0;
int secondDataRowIndex = 1;
while (entry.Value.Count > 1) {
DateTime time1 = Validation.ConvertStringIntoDateTime(entry.Value[firstDataRowIndex]["date"].ToString());
DateTime time2 = Validation.ConvertStringIntoDateTime(entry.Value[secondDataRowIndex]["date"].ToString());
//delete older entry
if (DateTime.Compare(time1,time2) >= 0) {
entry.Value.RemoveAt(firstDataRowIndex);
} else {
entry.Value.RemoveAt(secondDataRowIndex);
}
}
}
importedData.Tables[0].ImportRow(entry.Value[0]);
}
}
My Question is, since this code works - what is the best and fastest/most efficient way to perform the task?
I appreciate any answers!
Upvotes: 0
Views: 1953
Reputation: 7019
I think this can be done more efficiently. You copy the DataSet once with DataSet importedDataCopy = importedData.Copy();
and then you copy it again into a dictionary and then you delete the unnecessary data from the dictionary. I would rather just remove the unnecessary information in one pass. What about something like this:
private void mergeduplicate(DataSet importedData)
{
Dictionary<String, DataRow> systems = new Dictionary<String, DataRow>();
int i = 0;
while (i < importedData.Tables[0].Rows.Count)
{
DataRow dr = importedData.Tables[0].Rows[i];
String systemName = dr["Computer Name"].ToString();
if (!systems.ContainsKey(systemName))
{
systems.Add(systemName, dr);
}
else
{
// Existing date is the date in the dictionary.
DateTime existing = Validation.ConvertStringIntoDateTime(systems[systemName]["date"].ToString());
// Candidate date is the date of the current DataRow.
DateTime candidate = Validation.ConvertStringIntoDateTime(dr["date"].ToString());
// If the candidate date is greater than the existing date then replace the existing DataRow
// with the candidate DataRow and delete the existing DataRow from the table.
if (DateTime.Compare(existing, candidate) < 0)
{
importedData.Tables[0].Rows.Remove(systems[systemName]);
systems[systemName] = dr;
}
else
{
importedData.Tables[0].Rows.Remove(dr);
}
}
i++;
}
}
Upvotes: 2
Reputation: 8584
You could try to use CopyToDataTable
, like this:
importedData.Tables[0] = importedData.Tables[0].AsEnumerable()
.GroupBy(r => new {CN = r["Computer Name"], Date = r["date"]})
.Select(g => g.OrderBy(r => r["Date"]).(First())
.CopyToDataTable();
Upvotes: 0
Reputation: 45947
maybe not the most efficient way but you said you appreciate any answers
List<DataRow> toDelete = dt.Rows.Cast<DataRow>()
.GroupBy(s => s["Computer Name"])
.SelectMany(grp => grp.OrderBy(x => x["date"])
.Skip(1)).ToList();
toDelete.ForEach(x => dt.Rows.Remove(x));
Upvotes: 0