New functions for Prometheus histograms

Currently, Zabbix technically supports ingesting Prometheus metrics of all types, but some of the metrics are difficult to work with. Specifically, metrics of type Histogram can be presented in Zabbix as multiple items with the same key names but different parameters. However, even though such items are logically related and represent the same data, it's difficult to analyze this data without specialized functions.

Zabbix must support PromQL rate() and histogram_quantile() functions for easier integration with Prometheus-compatible exporters (such as Kubernetes). The rate() function calculates per-second rates (such as the number of API requests per second) and can be used either separately or along with histogram_quantile() function. histogram_quantile() accepts a quantile (percentage / 100), analyzes buckets (derived from Histogram metrics), and returns an approximation expressed in bucket units.