Which attribute types may affect log viewer performance due to excessive data generation?

High-cardinality attributes can significantly affect log viewer performance due to the nature of the data they produce. High cardinality refers to attributes that contain a large number of unique values. When logs are generated with these types of attributes, the amount of data can grow exponentially because every unique value is logged, leading to more extensive data collection and storage requirements.

This increased volume of logs can slow down processing and querying within the log viewer, as the system has to manage and analyze a vast array of unique entries. Consequently, this can hinder performance and make it more challenging to extract meaningful insights from the logs. In contrast, reference attributes, standard attributes, and custom attributes do not inherently generate excessive data in the same way that high-cardinality attributes do, making them less impactful in terms of log viewer performance issues.