Help your Force.com application scale and perform by understanding differences between use of SystemModStamp and LastModifiedDate in SOQL filters.
For architects and developers implementing applications on the Salesforce1 platform, network-conscious testing is becoming increasingly important when analyzing application performance. A new best practice guide is available that will help you identify risks and find solutions to network related challenges.
Do you have a SOQL query or a report that takes a long time to complete because you are querying data from an object that has tens of millions of rows, yet your business requirements won’t allow you to add a selective filter? Read on to learn more about sort optimization, a simple technique that many developers and architects overlook when applying SOQL performance tuning best practices.
Every day, the Technical Enablement team works with customers like you to review their architectures and help them solve implementation challenges on the Salesforce platform. One of those implementation challenges involves a seemingly simple platform feature: formula fields. Under the hood, poorly designed formula fields can consume a lot of resources, lead to slow query response times, and hurt your users’ productivity. We see these problems in many of our customer cases, and we know that the best way to avoid them involves learning both what makes formula fields efficient and how to build efficient formula fields. If you're a developer, architect, or administrator who wants to build lightning-fast formula fields, you'll want to attend our intermediate-level Dreamforce session, "Revving Up the Force.com Formula Engine," and its associated workshop.
Does your salesforce.com implementation involve running reports or generating dashboards for a base object that has tens of millions of records? Do you have reports that aggregate data from more than one object? Or are your users’ dashboard refreshes timing out? This blog post will give you an overview of how to design reports for large data volumes (LDV).
You’ve been tasked with extracting data from a Salesforce object. If you’re dealing with small volumes of data, this operation might be simple, involving only a few button clicks using some of the great tools available on the AppExchange. But when it comes to dealing with millions of records in a limited time frame, you might need to take extra steps to optimize the data throughput. Read this post to learn just what those steps are.
Do you use a long list of filters in your reports or SOQL statements to exclude “noisy” data from your query results? Do you wonder why your requests take so long to run, even when they return only a few hundred rows? You might be able to overcome your performance issue with indexed formula fields, which this blog post explains in detail.
If you've built an application on the Force.com platform, you want to deliver a great experience to your users. But how can you tell if your applications are performing well and will continue to perform well? Using the Developer Console, you can use "performance profiling" to identify and fix performance hotspots, and ensure that your applications are both fast and scalable.
Managing your Salesforce organization’s data is a crucial part of keeping your organization healthy, and you might have heard about one tool that can help it stay fit: skinny tables. Read this post to learn how skinny tables work, how they can help you with large volumes of data, and what you should consider before using them.
Best practices for building Salesforce SOQL queries on large data volumes (LDV) included avoiding filtering on fields with nulls, and formula fields. If you're implementing new queries—or want to clean up some of the workarounds you implemented prior to the Winter ’13 release—consider these updates related to filtering on nulls and formula fields.