During this post, I explained how to get information from a database in JSON format. In this one, I will show you how to store information sent to the database in JSON format.
I will use a very common scenario, storing a master-detail combination. For this, I use the Order-Order Details tables in Northwind database, which you can get here.
The goal is to store a new Order, with several Order Details in the same procedure, by using T-SQL OPENJSON.
Like a cooking recipe, I will explain this step by step.
Define the JSON schema.
We want to store the information received in the Order Details table, so its schema will be the schema received in the JSON information.
Simply get the Order Details schema and remove the NOT NULL modifiers. This will be used in the WITH modifier of the OPENJSON statement this way:
It must have parameters to receive all the data for the Orders Table’s columns, and one more containing the entire JSON information for the Order Details table. Notice the OrderID parameter is declared as OUTPUT, so the calling code could retrieve the new Order ID for the inserted row.
For this, the procedure must use the IDENT_CURRENT function.
SET@OrderID=IDENT_CURRENT('[Orders]');
Insert the Order Details using OPENJSON.
In this case, using Insert – select statement, and OPENJSON from the Details parameter as source, declaring it with the previously obtained schema. Notice the utilization of the @OrderID parameter for the Order Id value in each row.
INSERTINTO[Order Details]([OrderID],[ProductID],[UnitPrice],[Quantity],[Discount])SELECT@OrderID/* Using the new Order ID*/,[Productid],[UnitPrice],[Quantity],[Discount]FROMOPENJSON(@Details)WITH([OrderID][INT],[ProductID][INT],[UnitPrice][MONEY],[Quantity][SMALLINT],[Discount][REAL]);
The C# code.
Define the Order and Order Details entities in your Application.
I created a simple C# Console Application Sample. In it, the Order and Order_Details has been defined by using the Paste Special Paste JSON as Classes feature in Visual Studio. You can see the step by step here.
The Insert routine in the main program.
The code creates a new instance of the Order class, with values,
Orderorder=new(){CustomerID="ALFKI",EmployeeID=1,OrderDate=DateTime.UtcNow,RequiredDate=DateTime.UtcNow.AddDays(5),ShipAddress="Obere Str. 57",ShipCity="Berlin",Freight=12.05F,ShipCountry="Germany",ShipName="Alfreds Futterkiste",ShipPostalCode="12209",ShipRegion=null,ShipVia=1};
Then get information from a previously defined set, (as JSON), to have an array of Order Details.
// Create the details. To Avoid a long code, just get it from a JSON samplevardetails=System.Text.Json.JsonSerializer.Deserialize<OrderDetail[]>(InsertUsingJSONSample.Properties.Resources.Details);
Create the Connection and Command objects.
A connection object to the database is assigned to a Command object, with the name of the stored procedure as text, which is defined as a Stored Procedure command type.
By using this method, you reduce the calls between your app and the database server, optimizing the response, and including the entire store process in a unique implicit transaction.
In our current globalized world, at this time, any web site must be multilingual, enabling the user to select the language to use.
Moreover, a global company needs to know from which country the user connected.
A lot of sites, more of the streaming services as examples, identifies the country based on the IP address. Which could be a mistake, since a lot of people are in a different country of which belongs to.
Anyway, your database must need a language list and a countries list.
This post shows you a sample application which, using the standardized languages and countries from .Net Framework, and adding some information from external sources, set up some tables to manage this in your databases.
System.Globalization Namespace
The tool uses information from the System.Globalization namespace, which appears with .Net Framework from it very beginning.
Indicates if it is just a language or a language and country specification
Finally, I get information from two external sources. I got the GPS coordinates of each country from here meanwhile the flag’s pictures are from here. You can found the urls inside the code as well.
Storage’s schema.
Languages/Countries database schema
The tool create 3 tables as you can see in the Diagram.
It is necessary this way, because some countries use more than one language, and the relationship must be preserved.
The tables have a InUse column, to enable/disable each row for your application. So, you can query the Languages table for all the rows with the InUse value in 1, to display only those languages you desire use, or have enabled.
Note: It is important using nvarchar/nchar data types, since several Native names are in UTF-8 chars.
Using the tool.
The tool expects at least the connection string to your database. It accepts a second parameter for the schema name under the tables will be created. If this value is not provided, the tool assumes “Masters” as schema name.
In any case, the DDL scripts manage the creation of the schema if it does not exist.
The source code of the DataGen solution is in my GitHub.
If you prefer just use a T-SQL script to add the tables, here is the script.
In future posts, I will show some faqncy methods for site AND CONTENT localization.
In this example, we will see how we can test the different versions from a web application.
It is a simple page that calls consecutively the different versions, repeatedly (100), and returns the number of milliseconds involved in the whole process.
To increase the impedance of the evaluation, the option is given in a check box, to perform the same query, 100 times, but for all countries.
In any case, the responses will be in approximately the same proportion.
Performance
As you can see, from the point of view of the client application, the final result is faster with EF than with simple code, exactly the opposite of the performance in the first test.
It should be noted, however, that in that first test, the process requested was not the same at all, since data from different tables were required, while, in this case, the data came from only one.
In any case, the comparison could be established with the second publication of this series, which obtains the same data as the latter.
In any case, this last test has some advantage on the part of EF, compared to the rest.
In other words, let us point out conclusions:
The result is not always as expected. You must try. ALWAYS.
There is no single way to do things. We must investigate to improve the quality of the applications we generate.
An unit test of the final set of the application can lead to false conclusions, since other factors, such as communication, data transformation, etc., also influence performance. That is, unit tests are highly valid for testing functionality, but they are not always valid for evaluating performance.
In fact, most likely, in a real-world application environment, performance results can also change.
Therefore, it is important to monitor the application deployed in production, include counters, logs etc. to have permanent information and be able to periodically evaluate it, to anticipate possible problems.
En este ejemplo, veremos como podemos probar las distintas versiones desde un aplicativo web.
Se trata de una página sencilla que, llama consecutivamente a las distintas versiones, repetidas veces (100), y nos retorna la cantidad de milisegundos implicados en todo el proceso.
Para incrementar la impedancia de la evaluación, se da la opción en una casilla, de realizar la misma consulta, 100 veces, pero para todos los países.
En cualquier caso, las respuestas serán aproximadamente en la misma proporción.
Rendimiento
Como se puede ver, desde el punto de vista de la aplicación cliente, el resultado final es más rápido con EF que con código plano, exactamente lo contrario a la respuesta en la primera prueba.
Es de notar, sin embargo, que en aquella primera prueba, el proceso solicitado no era el mismo en lo absoluto, dado que se requerían datos de distintas tablas, mientras que, en este caso, los datos provienen de una sola.
En todo caso, la comparativa la podríamos establecer con la segunda publicación de esta serie, que obtiene los mismos datos que ésta última.
En cualquier caso, esta última prueba presenta alguna ventaja de parte de EF, respecto del resto.
O sea, puntualicemos conclusiones:
No siempre el resultado es el esperado. Hay que probar. SIEMPRE.
No hay una sola forma de hacer las cosas. Hay que investigar para mejorar la calidad de las aplicaciones que generamos.
Una prueba aislada del conjunto final de la aplicación, puede llevarnos a falsas conclusiones, ya que otros factores, como comunicación, transformación de datos, etc., también influyen en el rendimiento. O sea, las pruebas unitarias son muy validad para comprobar funcionalidad, pero no siempre son válidas para evaluar rendimiento.
De hecho, muy probablemente, en un entorno de una aplicación real, también los resultados de rendimiento pueden cambiar.
Por ello, es importante hacer seguimiento de la aplicación desplegada en producción, incluir contadores, bitácoras etc. para tener información permanente y poder evaluar periódicamente la misma, para adelantarnos a posibles problemas.
Finally, I’ll add projects to use stored procedures instead of statements constructed in code.
Moreover, and based on the recommendation of a greater entity framework expert than me, I added «AsNoTracking()» to the Entity Framework LINQ query set to Generating a REST API (JSON)[2].
The Stored Procedure.
This is the stored procedure which receives the country ID, the date from and date to, and the page to display.
Is the stored procedure which is responsible for setting values that are appropriate to the date parameters, rather than setting them from the component in C#.
Exactly the same, but with «FOR JSON PATH» at the end, is used in the project that uses pure code.
El Cambio en Entity Framework
Based on the proposal and comment, the code is as follows:
public IEnumerable<OwidCovidDatum> GetCountryData(
intCountryId,
DateTime?fromDate=null,
DateTime?toDate=null,
intPage=1)
{
fromDate=fromDate??
(from el in _context.OwidCovidData orderby el.Date select el.Date).FirstOrDefault();
toDate=toDate??
(from el in _context.OwidCovidData orderby el.Date descendingselect el.Date).FirstOrDefault();
return (from OwidCovidDatum el in
_context.OwidCovidData
.Where(x=> x.Date>=fromDate && x.Date<=toDate && x.CountriesId==CountryId)
.Skip((Page-1)*100)
.Take(100) select el).AsNoTracking().ToList();
}
Dapper Using Stored Procedure
We use Dapper’s stored procedure execution capability, which is capable of assign values to parameters by name matching.
publicasyncTask<string>GetCountryData(intCountryId,DateTime?fromDate=null,DateTime?toDate=null,intPage=1){varresult=await_dal.GetDataAsync("[Owid Covid Data Get By Country]",new{fromDate,toDate,CountryId,Page});stringjson=JsonSerializer.Serialize(result,newJsonSerializerOptions(){WriteIndented=true,ReferenceHandler=ReferenceHandler.Preserve});returnjson;}
Code using Stored Procedure
In the case of direct code, we assign the parameters one by one, also specifying the data type, which allows greater specificity.
publicasyncTask<string>GetCountryData(intCountryId,DateTime?fromDate=null,DateTime?toDate=null,intPage=1){varcommand=_dal.CreateCommand("[Owid Covid Data Get By Country JSON]");command.Parameters.Add("@fromDate",System.Data.SqlDbType.SmallDateTime).Value=fromDate;command.Parameters.Add("@toDate",System.Data.SqlDbType.SmallDateTime).Value=toDate;command.Parameters.Add("@CountryId",System.Data.SqlDbType.Int).Value=CountryId;command.Parameters.Add("@skip",System.Data.SqlDbType.Int).Value=Page;varjson=await_dal.GetJSONDataAsync(command);returnjson;}
Performance
The graph shows that even when you use features that improve effectiveness, the simplicity of the code improves performance.
That is, for better response to the user, more time should be invested by developers in improving their development.
As a detail, stored procedure calls directly make calls to the SP, instead of using, as we saw in the previous post, sp_executesql.
EXEC[Owid Covid Data Get By Country]@fromDate=NULL,@toDate=NULL,@CountryId=4,@Page=3;
Aquí, finalmente, agregaré proyectos para utilizar procedimientos almacenados en lugar de sentencias construidas en el código.
De paso, y por recomendación de un mayor experto que yo en Entity Framework, agregué «AsNoTracking()» a la consulta LINQ de Entity Framework establecida en Generando una API REST (JSON) [2].
El procedimiento Almacenado.
Este es el procedimiento almacenado que recibe, el Id de país, la fecha desde y la fecha hasta, y la página a mostrar.
Es el procedimiento almacenado el responsable de establecer valores adecuados a los parámetros de fecha, en lugar de establecerlos desde el componente en C#.
Exactamente igual, pero con «FOR JSON PATH» al final, se usa en el proyecto que utiliza código puro.
El Cambio en Entity Framework
Basado en la propuesta y comentario, el código queda como sigue:
public IEnumerable<OwidCovidDatum> GetCountryData(
intCountryId,
DateTime?fromDate=null,
DateTime?toDate=null,
intPage=1)
{
fromDate=fromDate??
(from el in _context.OwidCovidData orderby el.Date select el.Date).FirstOrDefault();
toDate=toDate??
(from el in _context.OwidCovidData orderby el.Date descendingselect el.Date).FirstOrDefault();
return (from OwidCovidDatum el in
_context.OwidCovidData
.Where(x=> x.Date>=fromDate && x.Date<=toDate && x.CountriesId==CountryId)
.Skip((Page-1)*100)
.Take(100) select el).AsNoTracking().ToList();
}
Dapper Usando Procedimientos Almacenados
Utilizamos la capacidad de ejecución de procedimientos almacenados de Dapper, que es capaz de asignar valores a los parámetros por coincidencia de nombres.
publicasyncTask<string>GetCountryData(intCountryId,DateTime?fromDate=null,DateTime?toDate=null,intPage=1){varresult=await_dal.GetDataAsync("[Owid Covid Data Get By Country]",new{fromDate,toDate,CountryId,Page});stringjson=JsonSerializer.Serialize(result,newJsonSerializerOptions(){WriteIndented=true,ReferenceHandler=ReferenceHandler.Preserve});returnjson;}
Código usando Procedimientos Almacenados
En el caso del código directo, asignamos los parámetros uno a uno, especificando además el tipo de dato, que permite una mayor especificidad.
publicasyncTask<string>GetCountryData(intCountryId,DateTime?fromDate=null,DateTime?toDate=null,intPage=1){varcommand=_dal.CreateCommand("[Owid Covid Data Get By Country JSON]");command.Parameters.Add("@fromDate",System.Data.SqlDbType.SmallDateTime).Value=fromDate;command.Parameters.Add("@toDate",System.Data.SqlDbType.SmallDateTime).Value=toDate;command.Parameters.Add("@CountryId",System.Data.SqlDbType.Int).Value=CountryId;command.Parameters.Add("@skip",System.Data.SqlDbType.Int).Value=Page;varjson=await_dal.GetJSONDataAsync(command);returnjson;}
Rendimiento
El gráfico muestra que, aún cuando se utilizan características que mejoran la efectividad, la simpleza del código mejora el rendimiento.
O sea, para mejor respuesta al usuario, se deberá invertir más tiempo de los desarrolladores en mejorar su desarrollo.
Como detalle, las llamadas de procedimiento almacenado, realizan directamente llamadas al mismo, en lugar de utilizar, como vimos en la publicación anterior, sp_executesql.
EXEC[Owid Covid Data Get By Country]@fromDate=NULL,@toDate=NULL,@CountryId=4,@Page=3;
Let’s consider another requirement, to evaluate how you can best take advantage of the features of the Entity Framework and emulate that functionality in cases where it cannot be used, or it is more convenient to do something else.
In this example, we are using the same database explained in Data-for-demos
The requirement
You need to get the statistical information of cases, vaccinations, etc. By country, between certain dates, with the following conditions:
If no start date is entered, the first available date is used.
If the end date is not entered, the last available date is used.
The information must be returned in batches of 100 entries, so the requested page number must be received.
In this case, it will be implemented in the “Country» controller
Entity Framework.
The code leverages EF’s Fluent capabilities to nest conditions. Similarly, below, the Entity Framework generates a statement according to the data engine in use, in this case, SQL Server.
publicasync Task<ActionResult<IEnumerable<OwidCovidDatum>>> GetCountryData(
intCountryId,
DateTime?fromDate=null,
DateTime?toDate=null,
intPage=1)
{
fromDate=fromDate??
(from el in _context.OwidCovidData orderby el.Date select el.Date).FirstOrDefault();
toDate=toDate??
(from el in _context.OwidCovidData orderby el.Date descendingselect el.Date).FirstOrDefault();
return (from OwidCovidDatum el in
_context.OwidCovidData
.Where(x=> x.Date>=fromDate && x.Date<=toDate && x.CountriesId==CountryId)
.Skip((Page-1)*100)
.Take(100) select el).ToList();
}
Dapper
Using the returned DapperRows, we implement the call with an SQL statement that is almost the same as the one automatically generated by EF.
As in the previous example, we create a parameterized Command object that returns a string of characters with the resulting JSON, implemented in the SQL statement.
Consideremos otro requisito, para evaluar como puede aprovecharse mejor las características de Entity Framework y emular esa funcionalidad en los casos en que no se pueda utilizar, o sea más conveniente otra forma de realizar la tarea.
En este ejemplo, estamos utilizando la misma base de datos explicada en Datos-para-demos
El requisito
Se necesita obtener la información estadística de casos, vacunaciones, etc. Por país, entre determinadas fechas, con las siguientes condiciones:
Si no se consigna fecha de inicio, se usa la primera disponible.
Si no se consigna la fecha de fin, se usa la última disponible.
Se debe retornar la información en lotes de a 100 entradas, con lo cual, se deberá recibir el número de página solicitado.
En este caso, se implementará en el controlador «Country«
Entity Framework.
El código aprovecha las funcionalidades Fluent de EF para anidar las condiciones. Igualmente, por debajo, Entity Framework genera una sentencia acorde al motor de datos en uso, en este caso, SQL Server.
publicasync Task<ActionResult<IEnumerable<OwidCovidDatum>>> GetCountryData(
intCountryId,
DateTime?fromDate=null,
DateTime?toDate=null,
intPage=1)
{
fromDate=fromDate??
(from el in _context.OwidCovidData orderby el.Date select el.Date).FirstOrDefault();
toDate=toDate??
(from el in _context.OwidCovidData orderby el.Date descendingselect el.Date).FirstOrDefault();
return (from OwidCovidDatum el in
_context.OwidCovidData
.Where(x=> x.Date>=fromDate && x.Date<=toDate && x.CountriesId==CountryId)
.Skip((Page-1)*100)
.Take(100) select el).ToList();
}
Dapper
Utilizando los DapperRow de retorno, implementamos la llamada con una sentencia SQL que es casi igual a la generada automáticamente por EF.
Al igual que en el ejemplo previo, creamos un objeto Command con parámetros que retorne una cadena de caracteres con el JSON resultante, implementado en la sentencia SQL.
I’m not going to go into detail here describing what is REST (Representational State Transfer) an API (Application Programming Interface) or JSON (JavaScript Object Notation). I start from the base that is already known to which we refer.
In this case, using the database published in the previous entry Data for demos, I will present how to expose the information from that database, in a read-only API.
At the same time, I will try to show advantages and disadvantages of different methods to achieve the same objective.
Entity Framework
Although in general, I dislike its use, I will try to include it in each demonstration, to see what advantages it brings, and the disadvantages that arise.
The project within the solution is ApiRestEF
Dapper
As a data access package/library, it allows you to easily obtain information from databases.
The project, within the solution is ApiRestDapper
Coding directly
In this case, I’ll be showing how to do, the same thing, but step by step, without libraries.
The project, within the solution is ApiRestCode
First requirement
A method is needed to obtain the information that is displayed, for a continent indicated as a parameter.
Continent
Country
Total Cases
Total Deaths
Total Cases per Million
Total Deaths per Million
Population
Population Density
GDP per Capita
Africa
Seychelles
12466
46
126764
468
98340
208
26382
Africa
Cape Verde
31433
271
56535
487
555988
136
6223
Africa
Tunisia
362658
13305
30685
1126
11818618
74
10849
Africa
South Africa
1722086
57410
29036
968
59308690
47
12295
Africa
Libya
188386
3155
27416
459
6871287
4
17882
Africa
Botswana
59480
896
25293
381
2351625
4
15807
Africa
Namibia
61374
968
24154
381
2540916
3
9542
Africa
Eswatini
18705
676
16123
583
1160164
79
7739
Africa
Morocco
522765
9192
14163
249
36910558
80
7485
Africa
Djibouti
11570
154
11711
156
988002
41
2705
Africa
Gabon
24696
156
11096
70
2225728
8
16562
Entity Framework
The code used obtains the continent and its constituent countries in a single query but required to go through the countries, to obtain from each one, the demographic data.
As I said, I don’t like EF and maybe that’s why my research into methods to do it, may not have found another way.
Of course, if someone offers another proposal in the comments, I’ll add it here, and I’ll also proceed to evaluate the corresponding metric.
For the case of implementation with Dapper, we directly use the «DapperRow» types as the query return, thus decreasing the mapping between columns and properties. If defined classes were used, the response time would surely be longer.
Finally, for direct query by code, we optimize using the FOR JOSN modifier, and then directly obtaining the resulting JSON string.
publicasyncTask<ActionResult<string>>GetContinent(intid){stringsql=@" SELECT
[C].[Continent]
, [CO].[Country]
, [D].[total_cases]
, [D].[total_deaths]
, [D].[total_cases_per_million]
, [D].[total_deaths_per_million]
, [D].[population]
, [D].[population_density]
, [D].[gdp_per_capita]
FROM
[OwidCountriesData] AS [D]
INNER JOIN
[Continents] AS [C]
ON [D].[ContinentId] = [C].[Id]
INNER JOIN
[Countries] AS [CO]
ON [D].[CountriesId] = [CO].[Id]
WHERE([C].[Id] = @continent)
ORDER BY
[D].[total_cases_per_million] DESC FOR JSON AUTO, INCLUDE_NULL_VALUES, ROOT('CountriesInfo');";SqlCommandcom=_dal.CreateCommand(sql);com.Parameters.AddWithValue("@continent",id);returnawait_dal.GetJSONDataAsync(com);}
Note
In both the Dapper and code projects, a minimal data access layer was built to emulate functionality similar to that provided by EF-generated code.
Performance
The graph below shows the comparison in CPU utilization, lifetime, and disk reads, in each of the cases. A picture is worth a thousand words. 🙂
In the graph, values are evaluated only from the point of view of the database, not the .Net code, nor its runtime. I will add this in the next installment.
No voy a entrar aquí en detalles de descripción de lo que es REST (Representational State Transfer) una API (Application Programming Interface) o JSON (JavaScript Object Notation). Parto de la base que ya se conoce a que nos referimos.
En este caso, utilizando la base de datos publicada en la entrada anterior Datos para demos, presentaré como exponer la información de esa base, en una API de sólo lectura.
Al mismo tiempo, intentaré mostrar ventajas y desventajas de distintos métodos para lograr el mismo objetivo.
Entity Framework
Aunque en líneas generales, me disgusta bastante su utilización, intentaré incluirlo en cada demostración, por ver que ventajas aporta, y los inconvenientes que surjan.
El proyecto dentro de la solución es ApiRestEF
Dapper
Como paquete/biblioteca de acceso a datos, permite fácilmente obtener información de bases de datos.
El proyecto, dentro de la solución es ApiRestDapper
Código directo
En este caso, estaré mostrando como hacer, lo mismo, pero paso a paso, sin bibliotecas.
El proyecto, dentro de la solución es ApiRestCode
Primer requisito.
Se necesita un mecanismo por el cual obtener la información que se muestra, para un continente indicado como parámetro.
Continent
Country
Total Cases
Total Deaths
Total Cases per Million
Total Deaths per Million
Population
Population Density
GDP per Capita
Africa
Seychelles
12466
46
126764
468
98340
208
26382
Africa
Cape Verde
31433
271
56535
487
555988
136
6223
Africa
Tunisia
362658
13305
30685
1126
11818618
74
10849
Africa
South Africa
1722086
57410
29036
968
59308690
47
12295
Africa
Libya
188386
3155
27416
459
6871287
4
17882
Africa
Botswana
59480
896
25293
381
2351625
4
15807
Africa
Namibia
61374
968
24154
381
2540916
3
9542
Africa
Eswatini
18705
676
16123
583
1160164
79
7739
Africa
Morocco
522765
9192
14163
249
36910558
80
7485
Africa
Djibouti
11570
154
11711
156
988002
41
2705
Africa
Gabon
24696
156
11096
70
2225728
8
16562
Entity Framework
El código utilizado obtiene el continente y sus países constitutivos en una sola consulta pero requirió recorrer los países, para obtener de cada uno, los datos demográficos.
Como ya dije, no me gusta EF y quizás por ello, mi investigación de métodos para hacerlo, puede no haber encontrado otra forma.
Por supuesto, si alguien ofrece otra propuesta en los comentarios, la agregaré aquí, y también procederé a evaluar la métrica correspondiente.
para el caso de la implementación con Dapper, utilizamos directamente los tipos «DapperRow» como retorno de la consulta, disminuyendo así el mapeo entre columnas y propiedades. De usarse clases definidas, seguramente el tiempo de respuesta sería mayor.
Finalmente, para la consulta directa por código, optimizamos utilizando el modificador FOR JOSN, y obteniendo entonces directamente la cadena JSON resultante.
publicasyncTask<ActionResult<string>>GetContinent(intid){stringsql=@" SELECT
[C].[Continent]
, [CO].[Country]
, [D].[total_cases]
, [D].[total_deaths]
, [D].[total_cases_per_million]
, [D].[total_deaths_per_million]
, [D].[population]
, [D].[population_density]
, [D].[gdp_per_capita]
FROM
[OwidCountriesData] AS [D]
INNER JOIN
[Continents] AS [C]
ON [D].[ContinentId] = [C].[Id]
INNER JOIN
[Countries] AS [CO]
ON [D].[CountriesId] = [CO].[Id]
WHERE([C].[Id] = @continent)
ORDER BY
[D].[total_cases_per_million] DESC FOR JSON AUTO, INCLUDE_NULL_VALUES, ROOT('CountriesInfo');";SqlCommandcom=_dal.CreateCommand(sql);com.Parameters.AddWithValue("@continent",id);returnawait_dal.GetJSONDataAsync(com);}
Aclaración
Tanto en el proyecto Dapper como en el de código, se construyó una capa de acceso a datos mínima, para emular similar funcionalidad a la brindada por el código generado por EF.
Rendimiento
El gráfico inferior muestra la comparativa en utilización de CPU, tiempo de duración, y lecturas a disco, en cada uno de los casos. Una imagen, vale más que mil palabras. 🙂
En el gráfico, solo se evalúan valores desde el punto de vista de la base de datos, no del código .Net, ni su tiempo de ejecución. Agregaré esto en la próxima entrega.
Segunda época del rockblog "Atascado en los 70". VIEJAS canciones y artistas PASADOS DE MODA. Tratamos al lector de usted y escribimos "rocanrol" y "roquero" con ortografía castellana.