What are common PromQL query types?

PromQL (Prometheus Query Language) is used to query time series data in Prometheus. Here are some common types of PromQL queries:

Instant Vector Queries: These queries return the current value of a metric at a specific point in time. For example:
```
http_requests_total
```
Range Vector Queries: These queries return a set of data points over a specified time range. For example:
```
http_requests_total[5m]
```
Aggregation Queries: These queries aggregate data across multiple time series. Common aggregation functions include sum, avg, max, min, and count. For example:
```
sum(http_requests_total) by (status)
```
Rate Queries: These queries calculate the per-second average rate of increase of a counter over a specified time range. For example:
```
rate(http_requests_total[5m])
```
Subquery Queries: These allow you to perform calculations over a range of data points and can be nested. For example:
```
sum(rate(http_requests_total[5m])[10m:1m])
```
Filtering Queries: You can filter metrics based on labels. For example:
```
http_requests_total{method="GET"}
```
Join Queries: These queries can combine metrics with different labels using operations like +, -, *, and /. For example:
```
http_requests_total + http_errors_total
```

These query types allow users to extract meaningful insights from time series data stored in Prometheus.