Best Practices for Deployments with Large Data Volumes

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Best Practices for Deployments with Large Data Volumes
Introduction
Underlying Concepts
Infrastructure for Systems with Large Data Volumes
Techniques for Optimizing Performance
Best Practices
Reporting
Loading Data from the API
Extracting Data from the API
Searching
SOQL and SOSL
Deleting Data
General
Large Data Volumes Case Studies
Summary
PDF

Reporting

Goal Best Practice
Maximizing reporting performance by:
  • Partitioning data to match its likely use
  • Minimizing the number of records per object
 Reduce the number of records to query—use a value in the data to segment the query. For example, query for only a single state instead of for all states. (See Divisions.)
Reducing the number of joins
  • Minimize the number of:
    • Objects queried in the report
    • Relationships used to generate the report
  • De-normalize data when practical—“over de-normalizing” the data results in more overhead. Use summarized data stored on the parent record for the report. This practice is more efficient than having the report summarize the child records.
    Reducing the amount of data returned Reduce the number of fields queried—only add fields to a report, list view, or SOQL query that is required.
    Reducing the number of records to query
    • Reduce the amount of data by archiving unused records—move unused records to a custom object table to reduce the size of the report object.
    • Use report filters that emphasize the use of standard or custom indexed fields. Use index fields in report filters, whenever possible.