Time series data
Each data point is a tuple of a timestamp and a value
A 64 bit float turns out to be a good representation for counter as well as gauge values, so we go with that. (时间戳？)
定义好相应的label部分
Vertical and Horizontal
series
^
│ . . . . . . . . . . . . . . . . . . . . . . {__name__="request_total", method="GET"}
│ . . . . . . . . . . . . . . . . . . . . . . {__name__="request_total", method="POST"}
│ . . . . . . .
│ . . . . . . . . . . . . . . . . . . . ...
│ . . . . . . . . . . . . . . . . . . . . .
│ . . . . . . . . . . . . . . . . . . . . . {__name__="errors_total", method="POST"}
│ . . . . . . . . . . . . . . . . . {__name__="errors_total", method="GET"}
│ . . . . . . . . . . . . . .
│ . . . . . . . . . . . . . . . . . . . ...
│ . . . . . . . . . . . . . . . . . . . .
v
<-------------------- time --------------------->关于写放大的问题？
解决方案:
- Writes are now batched, samples are stored sequentially
$ tree ./data
./data
├── b-000001
│ ├── chunks
│ │ ├── 000001
│ │ ├── 000002
│ │ └── 000003
│ ├── index
│ └── meta.json
├── b-000004
│ ├── chunks
│ │ └── 000001
│ ├── index
│ └── meta.json
├── b-000005
│ ├── chunks
│ │ └── 000001
│ ├── index
│ └── meta.json
└── b-000006
├── meta.json
└── wal
├── 000001
├── 000002
└── 000003Queried data can be rather aggressively cached in memory, yet under memory pressure the pages will be evicted. If the machine has unused memory, Prometheus will now happily cache the entire database, yet will immediately return it once another application needs it.