Skip to main content

Programare paralela in .NET 4.0

Plecam de la premiza ca avem o metoda care executa acelasi cod pentru fiecare element dintr-o colectie:
public bool CheckItem(Item item)
{
...
}
In mod natural am scrie:
foreach (Item item in items)
{
item.IsValid = CheckItem(item);
}

sau
items.ForEach(item=>CheckItem(item));
Am putea sa rulam paralel acest cod foarte usor, daca ne folosim de clasa ajutatoare Parallel:
Parallel.ForEach(items,new Action(item=>CheckItem(item)));
O varianta mai simpla in acest caz este sa scriem direct:
Parallel.ForEach(items,CheckItem);
Daca vrem sa parcurgem doar o parte din colectie putem sa scriem in felul urmator:
Parallel.For(0, 3, new Action(index => CheckItem(items[index])));
Atentie, daca lucrati cu stream-uri sau baze de date trebuie avut grija la close si dispose.
Problema este ceea ce se petrece in spate. N threaduri sunt folosite pentru linia de cod scrisa mai sus. Daca suntem pe client side, acest lucru nu este atat de important, dar daca suntem pe partea de server, putem avea mari probleme. De exemplu putem sa ajunge sa avem toate threadurile din pool folosite. Aceasta problema apare din cauza ca pentru fiecare request care vine prin WCF sau HTTP poate sa porneasca N threaduri. Din punct de vedere a scalabilității aici pot sa apara mari problem( vezi P.S. de la sfîrșitul postului).
public async Task CheckItem(ITempDataProvider item)
{
...
}
Task.Factory.ContinueWhenAll(
from item in items select CheckItem(item),
endTask => NotifyWaiter());
Pentru a putea face acest lucru aveti nevoie de Async CTP instalat. Acesta in spate apeleaza asyncron pentru fiecare item in parte metoda CheckItem. Keywordul async ii spune compilatorului ca acesta metoda o sa fie apelata asyncron. Iar ContinueWhenAll creaza un task care o sa fie rulat la sfarsitul executiei listei de taskuri specificate.
Async CTP
O alta varianta este sa folosim
WithDegreeOfParallelism. Aceasta ne permite sa specificam numarul de threaduri care pot sa ruleze paralel prin intermediul limbajului PLINQ
P.S.: Am ajuns sa scriu acest post in momentul in care am scris un cod server side care folosea Parallel.ForEach pentru a prelucra un request de la client si am ajuns doar prin cateva requesturi sa ocup peste 200MB din memorie.

Comments

Popular posts from this blog

Why Database Modernization Matters for AI

  When companies transition to the cloud, they typically begin with applications and virtual machines, which is often the easier part of the process. The actual complexity arises later when databases are moved. To save time and effort, cloud adoption is more of a cloud migration in an IaaS manner, fulfilling current, but not future needs. Even organisations that are already in the cloud find that their databases, although “migrated,” are not genuinely modernised. This disparity becomes particularly evident when they begin to explore AI technologies. Understanding Modernisation Beyond Migration Database modernisation is distinct from merely relocating an outdated database to Azure. It's about making your data layer ready for future needs, like automation, real-time analytics, and AI capabilities. AI needs high throughput, which can be achieved using native DB cloud capabilities. When your database runs in a traditional setup (even hosted in the cloud), in that case, you will enc...

Cloud Myths: Migrating to the cloud is quick and easy (Pill 2 of 5 / Cloud Pills)

The idea that migration to the cloud is simple, straightforward and rapid is a wrong assumption. It’s a common misconception of business stakeholders that generates delays, budget overruns and technical dept. A migration requires laborious planning, technical expertise and a rigorous process.  Migrations, especially cloud migrations, are not one-size-fits-all journeys. One of the most critical steps is under evaluation, under budget and under consideration. The evaluation phase, where existing infrastructure, applications, database, network and the end-to-end estate are evaluated and mapped to a cloud strategy, is crucial to ensure the success of cloud migration. Additional factors such as security, compliance, and system dependencies increase the complexity of cloud migration.  A misconception regarding lift-and-shits is that they are fast and cheap. Moving applications to the cloud without changes does not provide the capability to optimise costs and performance, leading to ...

Cloud Myths: Cloud is Cheaper (Pill 1 of 5 / Cloud Pills)

Cloud Myths: Cloud is Cheaper (Pill 1 of 5 / Cloud Pills) The idea that moving to the cloud reduces the costs is a common misconception. The cloud infrastructure provides flexibility, scalability, and better CAPEX, but it does not guarantee lower costs without proper optimisation and management of the cloud services and infrastructure. Idle and unused resources, overprovisioning, oversize databases, and unnecessary data transfer can increase running costs. The regional pricing mode, multi-cloud complexity, and cost variety add extra complexity to the cost function. Cloud adoption without a cost governance strategy can result in unexpected expenses. Improper usage, combined with a pay-as-you-go model, can result in a nightmare for business stakeholders who cannot track and manage the monthly costs. Cloud-native services such as AI services, managed databases, and analytics platforms are powerful, provide out-of-the-shelve capabilities, and increase business agility and innovation. H...