Skip to main content

Windows Azure Table - How to chunk commands in batches of 100 items

Based on what kind of data store we are using, there are cases when the size of a batch is limited. For example if we want to execute an update batch command over Windows Azure Tables we will notify that the maxim size of a batch is 100. Also all the updated command needs to be on the same partition key.
What should we do if we have a batch that with more than 100 items. The simples’ solution is to create groups of chunks of 100 items and execute and execute them in parallel. In the next part of the post we will see how we can create chunks of items from a list:
List<Foo> items = new List<Foo>();
….
int chunkSize = 100;
List<List<Foo>> chunks = new List<List<Foo>>();
int index = 0;
int itemsCount = items.Count;
while( index < itemsCount )
{
int count = itemsCount > chunkSize
        ? itemsCount
        : index;
Chunks.Add( items.GetRange( index, count));
}
After this step if we need to execute the update command over the table context we can do this very easily:
foreach( var chunk in chunks )
{
    // execute the update command using the Save command.
}
In this post we saw how we can create chunks of items to be able to execute different command on them. If we don’t do this step we will get error when we will try, for example, to update 101 items using only a batch command.

Comments

  1. An useful post!
    Based on your idea, I wrote the following complete generic methods:

    https://gist.github.com/4410294

    (I tried to put the code here but it lost formating)
    Lucian

    ReplyDelete

Post a Comment

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 Understanding Modernisation Beyond Migration Database modernisation is distinct from merely relocating an outdated database to Azure.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...