Convert List<Object> to DataTable using FastMember in C#.Net

Recently, I got the requirement to convert the List<Object> to DataTable. The ad-hoc way, which we have been following to loop through the List and create the DataTable – which I don’t want to do. Therefore, I found a very good way by using FastMember. All you have to do is to download the FastMember from NuGet. Following are the steps below to download the Fastmember

 

 

Search for fastmember, and then install it.

 

 

After completing the installation, just include the FastMember namespace – and with the help of ObjectReader class we will be able to convert List to DataTabe.

 

IEnumerable<Customer> customerData = GetAllCustomers();

            if (customerData.Count() > 0)

            {

                using (DataTable table = new DataTable())

                {

                    using (var reader = ObjectReader.Create(customerData, "CustomerId","CustomerName", "CustomerAddress"))

                    {

                        table.Load(reader);

                    }

                }

            }

 

  IEnumerable<Customer> GetAllCustomers()

        {

            Customer[] customers = new Customer[]

        {

            new Customer { CustomerId = 1, CustomerName = "Ali", CustomerAddress = "Pakistan" },

            new Customer { CustomerId = 2, CustomerName = "Wakeel", CustomerAddress ="Pakistan" },

            new Customer { CustomerId = 3, CustomerName = "Anthony", CustomerAddress ="England" }

        };

            return customers;

        }

 

GetAllCustomers() will return the Sample data. I believe this is one of the efficient and quickest way to process the Data. I Hope you all must have enjoyed it after implementing this code :)

 

 

              

 

 

Bulk copy using Enterprise Library in C#

SqlBulkCopy is use to upload the data very efficiently from application to database in one shot. The best example could be of excel data; where we got the requirement to upload all the excel data into database table. One could think to hit the database row by row and storing each row into table, but this approach is totally wrong. This will lay down the performance of your application as well as your database. The best way is to do by using Bulk copy. This functionality is only limited to Sql database table.

Below is the sample code, which depicts the usage of SqlBulkCopy with Enterprise Library.

 int InsertRecord(ref SqlDatabase db, DbTransaction transaction) {
     //here you can enter your insertion code
     // db.ExecuteNonQuery("command", transaction);
     return 1;
 }
 public void InsertDataInBulk(DataTable dtData) {
     SqlDatabase db = null;
     DbTransaction transaction = null;
     try {
         int recordId = 0;
         DataTable dt = dtData;

         //remove any empty rows
         using(dt = dt.AsEnumerable().Where(row = > !row.ItemArray.All(field = > object.ReferenceEquals(field, DBNull.Value) | field.Equals(string.Empty))).CopyToDataTable()) {

             db = (SqlDatabase) DatabaseFactory.CreateDatabase();

             // insert all the records in bulk into the database.

             using(DbConnection connection = db.CreateConnection()) {
                 connection.Open();

                 // open transaction only in the case where you have to do multiple database operation
                 using(transaction = connection.BeginTransaction()) {

                     //insert the file record into filelog table
                     recordId = InsertRecord(ref db, transaction);
                     if (recordId > 0) {


                         using(SqlBulkCopy bulkCopy = new SqlBulkCopy((SqlConnection) connection, SqlBulkCopyOptions.Default, (SqlTransaction) transaction)) {
                             //if you're unsure of the column sequence in source and destination table then it's better to map the columns

                             SqlBulkCopyColumnMapping mapID = new SqlBulkCopyColumnMapping("ProductID", "ProdID");
                             bulkCopy.ColumnMappings.Add(mapID);

                             SqlBulkCopyColumnMapping mapName = new SqlBulkCopyColumnMapping("Name", "ProdName");
                             bulkCopy.ColumnMappings.Add(mapName);

                             SqlBulkCopyColumnMapping mapMumber = new SqlBulkCopyColumnMapping("ProductNumber", "ProdNum");
                             bulkCopy.ColumnMappings.Add(mapMumber);

                             bulkCopy.DestinationTableName = "YourTableName";
                             bulkCopy.WriteToServer(dt);
                         }
                         transaction.Commit();

                     } else transaction.Rollback();
                 }

             }

         }

     } catch (Exception ex) {
         if (transaction != null) transaction.Rollback();
         //Log your error

     } finally {
         db = null;
     }
 }

Bulkcopy can also be used by using SqlConnection. But the above example is other way around.

Efficient DataTransfer via DataSet (especially over Network) through Webservice in .Net

Whenever we are exposing a webservice with a webmethod of return type DataSet, we usually don't care of what extra information dataset has kept. If we serialize this Dataset in XML; then we can have a look of all the information. So particularly, if we see Dataset sends the schema information also, which sometimes isn't required, and apparently it creates a heavy data transfer specially over network.

Normally, you don't feel the difference if Dataset have one to two tables. But surely, if will boost up the performance. Considering the below example; let's suppose we have one webserivce with a webmethod of return type dataset.

public class MyWebService : System.Web.Services.WebService

    {

        [WebMethod]

        public DataSet GetDataset()

        {

            using (MyDataSet ds = new MyDataSet())

            {

                ds.Tables.Add(CreateTableWithData("Table1"));

                ds.Tables.Add(CreateTableWithData("Table2"));

                ds.Tables.Add(CreateTableWithData("Table3"));

                ds.Tables.Add(CreateTableWithData("Table4"));

                return ds;

            }

        }

        DataTable CreateTableWithData(string tableName)

        {

            using (DataTable dt = new DataTable())

            {

                dt.TableName = tableName;

                dt.Columns.Add("Column1", typeof(string));

                dt.Columns.Add("Column2", typeof(string));

                DataRow drow = dt.NewRow();

                drow[0] = "Test1";

                drow[1] = "Test2";

                dt.Rows.Add(drow);

                return dt;

            }

        }

   }

public class MyDataSet : DataSet

    {

        public override SchemaSerializationMode SchemaSerializationMode

        {

            get { return SchemaSerializationMode.ExcludeSchema  }

        }

    } 

Now if you have noticed, we have created our custom DataSet class (MyDataSet); inherited with DataSet class, with overridden property SchemaSerialiazationMode. Because if you will directly set the property of SchemaSerialiazationMode to ExcludeSchema, it won't allow you to do so. By default it is set to IncludeSchema. Below is the actual property:

public virtual SchemaSerializationMode SchemaSerializationMode {
            get {
                return SchemaSerializationMode.IncludeSchema;
        }
            set {
                if (value != SchemaSerializationMode.IncludeSchema) {
                    throw ExceptionBuilder.CannotChangeSchemaSerializationMode();
        }
    }
  }

We can check the data by serializing the Dataset into XML, which has the XML with removed schema. Here is the sample code:

MyWebService web = new MyWebService();

using (DataSet ds = web.GetDataset())

{

      XmlSerializer ser = new XmlSerializer(typeof(DataSet));

      TextWriter writer = new StreamWriter(@"C:\xm1.xml");

       ser.Serialize(writer, ds);

       writer.Close();

}

 

This is very useful if we have multiple tables in one dataset. Hence ExcludeSchema does the trick by overwhelming the load when sending dataset via WebSerivce. 

 

How to search into a DataTable without a loop in C#?

Sometimes we are in a need to compare few values or filter records from our DataTable to get the exact result. We use to follow the technique since the last decade to looping into DataTable then compare each and every row to get the desired result. This post will help you to avoid loops and provide an appropriate method to achieved your target.

Basically, there are two ways to filter the records; by considering the below example.

Let's suppose, you have a DataTable with the following Definition & Data.

Customer Table (dtCustomer)

Id    FirstName    LastName   EmailAddress                   Address
1     Abdul            Wahab           abdulwahab@xyz.com      Al Nahda Street
2     Abdul            Qayyuum      abdulqayuum@xyz.com    Al Sufoof Street
3     George           Adam           georgea@xyz.com             Al Nahda Street
4     Hemant          Singh            hSign@xyz.com                Jumerah Street
5     Muhammad   Ali                mali@xyz.com                   City Street

We are requiring two types of data,

1. Get all customers, who are residing near 'Al Nahda Street'.
2. Get all customers, who are residing near 'Al Nahda Street' & their first name starts with 'Abdul'.

Now, there are two ways to get the records: one is with the DataView & the other one with Linq.

Dataview Method

var dview = new DataView(dtCustomer);

Requirement 1

dview.RowFilter= "Address like '%Al Nahda%'";
var dtResult1 = dview.ToTable();

Requirement 2

dview.RowFilter= "Address like '%Al Nahda%' and FirstName like '%Abdul%' ";
var dtResult2 = dview.ToTable();

*dtResult1 & dtResult2 has the desired results.*

Linq Method (Lamda expression & Predicate) 

Requirement 1

var lst1= dt.AsEnumerable().Where(delegate(DataRow s){ return s["Address"].ToString().Contains("Nahda")  ; }).ToList();

OR 

var lst1= dt.AsEnumerable().Where(s=> { return s["Address"].ToString().Contains("Nahda") ; }).ToList();

OR

var lst1= dt.AsEnumerable().Where(s=> s["Address"].ToString().Contains("Nahda") ; }).ToList();

Requirement 2

var lst2= dt.AsEnumerable().Where(delegate(DataRow s){ return s["Address"].ToString().Contains("Nahda") && s["Name"].ToString().Contains("Abdul") ; }).ToList();

OR 

var lst2= dt.AsEnumerable().Where(s=> { return s["Address"].ToString().Contains("Nahda") && s["Name"].ToString().Contains("Abdul") ; }).ToList();


*lst1 & lst1 have the desired results, with DataRow as a type*.


Consequently, from the above two methods everyone can filter their records without using a loop.
Happy Coding....! :)