ZIP 100 RECORD IT INSTALL
ZIP 100 RECORD IT CODE

Once you've successfully parsed the CSV file, it's time to store it in a database table. Var reader = File.OpenText('cities.csv')

ZIP 100 RECORD IT CODE

Listing 1: Code used to parse a CSV file into a list of objects private List LoadZipCodeFile()Īssembly.GetExecutingAssembly().Location) Once the library is installed, you can use the code in Listing 1 to open the CSV file and create a list of ZipCodeRecord objects from its contents. This installs the CsvHelper library into your project and adds the proper references. From Visual Studio select TOOLS > NuGet Package Manager > Package Manager Console.

ZIP 100 RECORD IT INSTALL

To install the CSVHelper package perform the following steps: The developers of that library have created a NuGet package to assist in its installation.

The source code for CSVHelper can be found at this location on Github. To perform this operation, use an open source application called CSVHelper. NET Framework doesn't have a native library for processing CSV files. The next snippet is a C# class definition that matches the structure of the CSV file you'll be converting. The next step is to create a C# class that represents this structure. This code snippet is a representation of the data contained in the CSV zip code file. This file contains the city, state, longitude, and latitude properties for approximately 27,000 zip codes. In this example, you'll create a C# list of zip code records from a CSV (Comma Separated Value) file downloaded from here. The question: How do we load large datasets into SQL Server from our application's C# code? Zip Code Loader Problemįor this article, you'll be solving a common business problem: creating a data table of zip codes and related metadata. It didn't take long to realize that this wasn't a practical way to load large datasets in a reasonable amount of time. We loaded the records into the database one at a time using a SQL Server stored procedure (one of our business' requirements is to use stored procedures).

Initially, we chose to process this data using a rather naive process. Recently, the team added Google Analytics data to the download process and we found ourselves faced with the prospect of loading hundreds of thousands of records daily. One of the projects I work on involves processing large datasets and saving them into SQL Server databases.

Zip 100 record it