Add sample metric type to statsd (commaai#23557)

* add sample stat, and make current power draw work on eon/c2

* fix power monitoring test

* little cleanup

* add type hinting to dict

* save as different values

* duh

* rip out power stat

* small fix

Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>

* cleanup this too

Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>

selfdrive/statsd.py

@@ -3,8 +3,9 @@
 import zmq
 import time
 from pathlib import Path
+from collections import defaultdict
 from datetime import datetime, timezone
-from typing import NoReturn
+from typing import NoReturn, Union, List, Dict
 
 from common.params import Params
 from cereal.messaging import SubMaster
@@ -17,6 +18,7 @@
 
 class METRIC_TYPE:
   GAUGE = 'g'
+  SAMPLE = 'sa'
 
 class StatLog:
   def __init__(self):
@@ -42,14 +44,27 @@ def _send(self, metric: str) -> None:
   def gauge(self, name: str, value: float) -> None:
     self._send(f"{name}:{value}|{METRIC_TYPE.GAUGE}")
 
+  # Samples will be recorded in a buffer and at aggregation time,
+  # statistical properties will be logged (mean, count, percentiles, ...)
+  def sample(self, name: str, value: float):
+    self._send(f"{name}:{value}|{METRIC_TYPE.SAMPLE}")
+
 
 def main() -> NoReturn:
   dongle_id = Params().get("DongleId", encoding='utf-8')
-  def get_influxdb_line(measurement: str, value: float, timestamp: datetime, tags: dict) -> str:
+  def get_influxdb_line(measurement: str, value: Union[float, Dict[str, float]],  timestamp: datetime, tags: dict) -> str:
     res = f"{measurement}"
     for k, v in tags.items():
       res += f",{k}={str(v)}"
-    res += f" value={value},dongle_id=\"{dongle_id}\" {int(timestamp.timestamp() * 1e9)}\n"
+    res += " "
+
+    if isinstance(value, float):
+      value = {'value': value}
+
+    for k, v in value.items():
+      res += f"{k}={v},"
+
+    res += f"dongle_id=\"{dongle_id}\" {int(timestamp.timestamp() * 1e9)}\n"
     return res
 
   # open statistics socket
@@ -75,6 +90,7 @@ def get_influxdb_line(measurement: str, value: float, timestamp: datetime, tags:
 
   last_flush_time = time.monotonic()
   gauges = {}
+  samples: Dict[str, List[float]] = defaultdict(list)
   while True:
     started_prev = sm['deviceState'].started
     sm.update()
@@ -86,10 +102,12 @@ def get_influxdb_line(measurement: str, value: float, timestamp: datetime, tags:
         try:
           metric_type = metric.split('|')[1]
           metric_name = metric.split(':')[0]
-          metric_value = metric.split('|')[0].split(':')[1]
+          metric_value = float(metric.split('|')[0].split(':')[1])
 
           if metric_type == METRIC_TYPE.GAUGE:
             gauges[metric_name] = metric_value
+          elif metric_type == METRIC_TYPE.SAMPLE:
+            samples[metric_name].append(metric_value)
           else:
             cloudlog.event("unknown metric type", metric_type=metric_type)
         except Exception:
@@ -103,11 +121,29 @@ def get_influxdb_line(measurement: str, value: float, timestamp: datetime, tags:
       current_time = datetime.utcnow().replace(tzinfo=timezone.utc)
       tags['started'] = sm['deviceState'].started
 
-      for gauge_key in gauges:
-        result += get_influxdb_line(f"gauge.{gauge_key}", gauges[gauge_key], current_time, tags)
+      for key, value in gauges.items():
+        result += get_influxdb_line(f"gauge.{key}", value, current_time, tags)
+
+      for key, values in samples.items():
+        values.sort()
+        sample_count = len(values)
+        sample_sum = sum(values)
+
+        stats = {
+          'count': sample_count,
+          'min': values[0],
+          'max': values[-1],
+          'mean': sample_sum / sample_count,
+        }
+        for percentile in [0.05, 0.5, 0.95]:
+          value = values[int(round(percentile * (sample_count - 1)))]
+          stats[f"p{int(percentile * 100)}"] = value
+
+        result += get_influxdb_line(f"sample.{key}", stats, current_time, tags)
 
       # clear intermediate data
-      gauges = {}
+      gauges.clear()
+      samples.clear()
       last_flush_time = time.monotonic()
 
       # check that we aren't filling up the drive