Merge "[Reports] Use timestamps on X axis in trends report"
This commit is contained in:
Jenkins
Gerrit Code Review
commit
bea20ca6ec
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@ -167,15 +167,15 @@ def trends(tasks_results):
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class Trends(object):
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"""Process tasks results and make trends data.
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"""Process workloads results and make trends data.
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Group tasks results by their input configuration,
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Group workloads results by their input configuration,
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calculate statistics for these groups and prepare it
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for displaying in trends HTML report.
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"""
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def __init__(self):
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self._tasks = {}
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self._data = {}
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def _to_str(self, obj):
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"""Convert object into string."""
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@ -197,29 +197,39 @@ class Trends(object):
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def add_result(self, result):
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key = self._make_hash(result["key"]["kw"])
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if key not in self._tasks:
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name = result["key"]["name"]
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self._tasks[key] = {"seq": 1,
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"name": name,
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"cls": name.split(".")[0],
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"met": name.split(".")[1],
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"data": {},
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"total": None,
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"atomic": [],
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"stat": {},
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"sla_failures": 0,
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"config": json.dumps(result["key"]["kw"],
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indent=2)}
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else:
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self._tasks[key]["seq"] += 1
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if key not in self._data:
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self._data[key] = {
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"actions": {},
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"sla_failures": 0,
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"name": result["key"]["name"],
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"config": json.dumps(result["key"]["kw"], indent=2)}
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for sla in result["sla"]:
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self._tasks[key]["sla_failures"] += not sla["success"]
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self._data[key]["sla_failures"] += not sla["success"]
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task = {row[0]: dict(zip(result["info"]["stat"]["cols"], row))
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stat = {row[0]: dict(zip(result["info"]["stat"]["cols"], row))
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for row in result["info"]["stat"]["rows"]}
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ts = int(result["info"]["tstamp_start"] * 1000)
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for action in stat:
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# NOTE(amaretskiy): some atomic actions can be missed due to
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# failures. We can ignore that because we use NVD3 lineChart()
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# for displaying trends, which is safe for missed points
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if action not in self._data[key]["actions"]:
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self._data[key]["actions"][action] = {
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"durations": {"min": [], "median": [], "90%ile": [],
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"95%ile": [], "max": [], "avg": []},
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"success": []}
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try:
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success = float(stat[action]["Success"].rstrip("%"))
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except ValueError:
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# Got "n/a" for some reason
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success = 0
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self._data[key]["actions"][action]["success"].append(
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(ts, success))
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for k in task:
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for tgt, src in (("min", "Min (sec)"),
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("median", "Median (sec)"),
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("90%ile", "90%ile (sec)"),
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@ -227,49 +237,44 @@ class Trends(object):
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("max", "Max (sec)"),
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("avg", "Avg (sec)")):
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# NOTE(amaretskiy): some atomic actions can be
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# missed due to failures. We can ignore that
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# because we use NVD3 lineChart() for displaying
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# trends, which is safe for missed points
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if k not in self._tasks[key]["data"]:
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self._tasks[key]["data"][k] = {"min": [],
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"median": [],
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"90%ile": [],
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"95%ile": [],
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"max": [],
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"avg": [],
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"success": []}
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self._tasks[key]["data"][k][tgt].append(
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(self._tasks[key]["seq"], task[k][src]))
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try:
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success = float(task[k]["Success"].rstrip("%"))
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except ValueError:
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# Got "n/a" for some reason
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success = 0
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self._tasks[key]["data"][k]["success"].append(
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(self._tasks[key]["seq"], success))
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self._data[key]["actions"][action]["durations"][tgt].append(
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(ts, stat[action][src]))
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def get_data(self):
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for key, value in self._tasks.items():
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total = None
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for k, v in value["data"].items():
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success = [("success", v.pop("success"))]
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if k == "total":
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total = {"values": v, "success": success}
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trends = []
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for wload in self._data.values():
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trend = {"stat": {},
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"name": wload["name"],
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"cls": wload["name"].split(".")[0],
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"met": wload["name"].split(".")[1],
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"sla_failures": wload["sla_failures"],
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"config": wload["config"],
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"actions": []}
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for action, data in wload["actions"].items():
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action_durs = [(k, sorted(v))
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for k, v in data["durations"].items()]
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if action == "total":
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trend.update(
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{"length": len(data["success"]),
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"durations": action_durs,
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"success": [("success", sorted(data["success"]))]})
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else:
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self._tasks[key]["atomic"].append(
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{"name": k, "values": list(v.items()),
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"success": success})
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trend["actions"].append(
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{"name": action,
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"durations": action_durs,
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"success": [("success", sorted(data["success"]))]})
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for stat, comp in (("min", charts.streaming.MinComputation()),
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("max", charts.streaming.MaxComputation()),
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("avg", charts.streaming.MeanComputation())):
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for k, v in total["values"][stat]:
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if isinstance(v, (float,) + six.integer_types):
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comp.add(v)
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self._tasks[key]["stat"][stat] = comp.result()
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del self._tasks[key]["data"]
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total["values"] = list(total["values"].items())
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self._tasks[key]["total"] = total
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self._tasks[key]["single"] = self._tasks[key]["seq"] < 2
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return sorted(self._tasks.values(), key=lambda s: s["name"])
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for k, v in trend["durations"]:
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for i in v:
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if isinstance(i[1], (float,) + six.integer_types):
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comp.add(i[1])
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trend["stat"][stat] = comp.result()
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trends.append(trend)
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return sorted(trends, key=lambda i: i["name"])
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@ -73,9 +73,9 @@ var widgetDirective = function($compile) {
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.showControls(opts.controls)
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.clipEdge(true);
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chart.xAxis
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.tickFormat(d3.format(opts.xformat || "d"))
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.axisLabel(opts.xname || "")
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.showMaxMin(false);
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.axisLabel(opts.xname)
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.tickFormat(opts.xformat)
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.showMaxMin(opts.showmaxmin);
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chart.yAxis
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.orient("left")
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.tickFormat(d3.format(opts.yformat || ",.3f"));
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@ -92,9 +92,10 @@ var widgetDirective = function($compile) {
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.useInteractiveGuideline(opts.guide)
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.clipEdge(true);
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chart.xAxis
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.tickFormat(d3.format(opts.xformat || "d"))
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.axisLabel(opts.xname || "")
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.showMaxMin(false);
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.axisLabel(opts.xname)
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.tickFormat(opts.xformat)
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.rotateLabels(opts.xrotate)
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.showMaxMin(opts.showmaxmin);
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chart.yAxis
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.orient("left")
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.tickFormat(d3.format(opts.yformat || ",.3f"));
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@ -184,14 +185,20 @@ var widgetDirective = function($compile) {
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}
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}
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var options = {
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var opts = {
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xname: attrs.nameX || "",
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xformat: attrs.formatX || "d",
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xrotate: attrs.rotateX || 0,
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yformat: attrs.formatY || ",.3f",
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controls: attrs.controls === "true",
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guide: attrs.guide === "true"
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guide: attrs.guide === "true",
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showmaxmin: attrs.showmaxmin === "true"
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};
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Chart.get_chart(attrs.widget)(el, data, options, do_after);
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if (attrs.formatDateX) {
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opts.xformat = function(d) { return d3.time.format(attrs.formatDateX)(new Date(d)) }
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} else {
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opts.xformat = d3.format(attrs.formatX || "d")
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}
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Chart.get_chart(attrs.widget)(el, data, opts, do_after);
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}
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if (attrs.nameY) {
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@ -97,9 +97,9 @@
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name: "Total",
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visible: function(){ return true }
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}, {
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id: "atomic",
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id: "actions",
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name: "Atomic actions",
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visible: function(){ return (! $scope.wload.single) && $scope.wload.atomic.length }
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visible: function(){ return ($scope.wload.length !== 1) && $scope.wload.actions.length }
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}, {
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id: "config",
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name: "Configuration",
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@ -134,6 +134,8 @@
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}
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}
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/* Other helpers */
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$scope.showError = function(message) {
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return (function (e) {
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e.style.display = "block";
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@ -173,8 +175,7 @@
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w.order_idx = itr > 1 ? " ["+itr+"]" : ""
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$scope.wload_map[w.ref] = w;
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$scope.nav_map[w.ref] = cls_idx;
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met.push({name:w.met, itr:itr, idx:idx, order_idx:w.order_idx,
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ref:w.ref, single:w.single});
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met.push({name:w.met, itr:itr, idx:idx, order_idx:w.order_idx, ref:w.ref});
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prev_met = w.met;
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itr += 1;
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}
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@ -271,7 +272,7 @@
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<div class="navmet"
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title="{{m.name}}{{m.order_idx}}"
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ng-show="n.idx==nav_idx"
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ng-class="{active:wload && m.ref==wload.ref, single:m.single}"
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ng-class="{active:wload && m.ref==wload.ref, single:m.length === 1}"
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ng-click="location.path(m.ref)"
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ng-repeat="m in n.met track by $index"
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ng-repeat-end>{{m.name}}{{m.order_idx}}</div>
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@ -336,18 +337,18 @@
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<tbody>
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<tr ng-repeat="w in data | orderBy:ov_srt:ov_dir"
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ng-click="location.path(w.ref)"
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ng-class="{single:w.single}">
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ng-class="{single:w.length === 1}">
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<td>{{w.ref}}
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<td>{{w.seq}}
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<td>{{w.length}}
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<td>
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<span ng-if="w.single">-</span>
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<span ng-if="!w.single">{{w.stat.min | number:4}}</span>
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<span ng-if="w.length === 1">-</span>
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<span ng-if="w.length !== 1">{{w.stat.min | number:4}}</span>
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<td>
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<span ng-if="w.single">-</span>
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<span ng-if="!w.single">{{w.stat.max | number:4}}</span>
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<span ng-if="w.length === 1">-</span>
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<span ng-if="w.length !== 1">{{w.stat.max | number:4}}</span>
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<td>
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<span ng-if="w.single">-</span>
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<span ng-if="!w.single">{{w.stat.avg | number:4}}</span>
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<span ng-if="w.length === 1">-</span>
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<span ng-if="w.length !== 1">{{w.stat.avg | number:4}}</span>
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<td title="{{w.sla_failures ? 'Failures: ' + w.sla_failures : 'No failures'}}">
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<span ng-hide="w.sla_failures" class="status-pass">✔</span>
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<span ng-show="w.sla_failures" class="status-fail">✖</span>
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@ -371,46 +372,58 @@
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<div ng-include="tab"></div>
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<script type="text/ng-template" id="total">
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<div ng-if="wload.single">
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<div ng-if="wload.length === 1">
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<div style="margin:30px 0 10px; font-size:14px; color:#ff6622">
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This workload has single run so trends can not be displayed.<br>
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There should be at least two workload results with the same configuration
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</div>
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</div>
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<div ng-if="!wload.single">
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<div ng-if="wload.length !== 1">
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<h2>Total durations</h2>
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<div widget="Lines"
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data="wload.total.values"
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name-x="Task run sequence number"
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data="wload.durations"
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controls="true"
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guide="true">
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guide="true"
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showmaxmin="true"
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rotate-x="-70"
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format-date-x="%Y-%m-%d %H:%M:%S"
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style="height:370px">
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</div>
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<h2>Total success rate</h2>
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<div widget="Lines"
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data="wload.total.success"
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name-x="Task run sequence number"
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data="wload.success"
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controls="true"
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guide="true">
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guide="true"
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showmaxmin="true"
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rotate-x="-70"
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format-date-x="%Y-%m-%d %H:%M:%S"
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style="height:370px">
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</div>
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</div>
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</script>
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<script type="text/ng-template" id="atomic">
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<script type="text/ng-template" id="actions">
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<h2>Atomic actions durations / success rate</h2>
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<div ng-repeat="chart in wload.atomic track by $index">
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<div ng-repeat="chart in wload.actions track by $index">
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<span id="{{chart.name}}"></span>
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<div class="chart-title">{{chart.name}}</div>
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<div widget="Lines"
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data="chart.values"
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name-x="Task run sequence number"
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data="chart.durations"
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controls="true"
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guide="true">
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guide="true"
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showmaxmin="true"
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rotate-x="-70"
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format-date-x="%Y-%m-%d %H:%M:%S"
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style="height:370px">
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</div>
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<div widget="Lines"
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data="chart.success"
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name-x="Task run sequence number"
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controls="true"
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guide="true">
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guide="true"
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showmaxmin="true"
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rotate-x="-70"
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format-date-x="%Y-%m-%d %H:%M:%S"
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style="height:400px">
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</div>
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</div>
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</script>
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@ -178,7 +178,7 @@ class TrendsTestCase(test.TestCase):
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def test___init__(self):
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trends = plot.Trends()
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self.assertEqual({}, trends._tasks)
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self.assertEqual({}, trends._data)
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self.assertRaises(TypeError, plot.Trends, 42)
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@ddt.data({"args": [None], "result": "None"},
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@ -227,11 +227,12 @@ class TrendsTestCase(test.TestCase):
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atomic = {"a": 123, "b": 456}
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stat_rows = [["a", 0.7, 0.85, 0.9, 0.87, 1.25, 0.67, "100.0%", 4],
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["b", 0.5, 0.75, 0.85, 0.9, 1.1, 0.58, "100.0%", 4],
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["total", 1.2, 1.55, 1.7, 1.9, 1.5, 1.6, "100.0%", 4]]
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["total", 1.2, 1.55, 1.7, 1.8, 1.5, 0.8, "100.0%", 4]]
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return {
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"key": {"kw": salt + "_kw", "name": "Scenario.name_%s" % salt},
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"key": {"kw": "kw_%d" % salt, "name": "Scenario.name_%d" % salt},
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"sla": [{"success": sla_success}],
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"info": {"iterations_count": 4, "atomic": atomic,
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"tstamp_start": 123456.789 + salt,
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"stat": {"rows": stat_rows,
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"cols": ["Action", "Min (sec)", "Median (sec)",
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"90%ile (sec)", "95%ile (sec)",
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@ -240,120 +241,151 @@ class TrendsTestCase(test.TestCase):
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"iterations": ["<iter-0>", "<iter-1>", "<iter-2>", "<iter-3>"]}
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def _sort_trends(self, trends_result):
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for r_idx, res in enumerate(trends_result):
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trends_result[r_idx]["total"]["values"].sort()
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for a_idx, dummy in enumerate(res["atomic"]):
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trends_result[r_idx]["atomic"][a_idx]["values"].sort()
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for idx in range(len(trends_result)):
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trends_result[idx]["durations"].sort()
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for a_idx in range(len(trends_result[idx]["actions"])):
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trends_result[idx]["actions"][a_idx]["durations"].sort()
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return trends_result
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def test_add_result_and_get_data(self):
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trends = plot.Trends()
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for i in 0, 1:
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trends.add_result(self._make_result(str(i)))
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trends.add_result(self._make_result(i))
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expected = [
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{"atomic": [
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{"name": "a",
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"success": [("success", [(1, 100.0)])],
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"values": [("90%ile", [(1, 0.9)]), ("95%ile", [(1, 0.87)]),
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("avg", [(1, 0.67)]), ("max", [(1, 1.25)]),
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("median", [(1, 0.85)]), ("min", [(1, 0.7)])]},
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{"name": "b",
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"success": [("success", [(1, 100.0)])],
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"values": [("90%ile", [(1, 0.85)]), ("95%ile", [(1, 0.9)]),
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("avg", [(1, 0.58)]), ("max", [(1, 1.1)]),
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("median", [(1, 0.75)]), ("min", [(1, 0.5)])]}],
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"cls": "Scenario", "config": "\"0_kw\"", "met": "name_0",
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"name": "Scenario.name_0", "seq": 1, "single": True,
|
||||
"sla_failures": 0, "stat": {"avg": 1.6, "max": 1.5, "min": 1.2},
|
||||
"total": {"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 1.7)]),
|
||||
("95%ile", [(1, 1.9)]),
|
||||
("avg", [(1, 1.6)]),
|
||||
("max", [(1, 1.5)]),
|
||||
("median", [(1, 1.55)]),
|
||||
("min", [(1, 1.2)])]}},
|
||||
{"atomic": [
|
||||
{"name": "a",
|
||||
"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 0.9)]), ("95%ile", [(1, 0.87)]),
|
||||
("avg", [(1, 0.67)]), ("max", [(1, 1.25)]),
|
||||
("median", [(1, 0.85)]), ("min", [(1, 0.7)])]},
|
||||
{"name": "b",
|
||||
"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 0.85)]), ("95%ile", [(1, 0.9)]),
|
||||
("avg", [(1, 0.58)]), ("max", [(1, 1.1)]),
|
||||
("median", [(1, 0.75)]), ("min", [(1, 0.5)])]}],
|
||||
"cls": "Scenario", "config": "\"1_kw\"", "met": "name_1",
|
||||
"name": "Scenario.name_1", "seq": 1, "single": True,
|
||||
"sla_failures": 0, "stat": {"avg": 1.6, "max": 1.5, "min": 1.2},
|
||||
"total": {"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 1.7)]),
|
||||
("95%ile", [(1, 1.9)]),
|
||||
("avg", [(1, 1.6)]),
|
||||
("max", [(1, 1.5)]),
|
||||
("median", [(1, 1.55)]),
|
||||
("min", [(1, 1.2)])]}}]
|
||||
{"actions": [{"durations": [("90%ile", [(123456789, 0.9)]),
|
||||
("95%ile", [(123456789, 0.87)]),
|
||||
("avg", [(123456789, 0.67)]),
|
||||
("max", [(123456789, 1.25)]),
|
||||
("median", [(123456789, 0.85)]),
|
||||
("min", [(123456789, 0.7)])],
|
||||
"name": "a",
|
||||
"success": [("success", [(123456789, 100.0)])]},
|
||||
{"durations": [("90%ile", [(123456789, 0.85)]),
|
||||
("95%ile", [(123456789, 0.9)]),
|
||||
("avg", [(123456789, 0.58)]),
|
||||
("max", [(123456789, 1.1)]),
|
||||
("median", [(123456789, 0.75)]),
|
||||
("min", [(123456789, 0.5)])],
|
||||
"name": "b",
|
||||
"success": [("success", [(123456789, 100.0)])]}],
|
||||
"cls": "Scenario",
|
||||
"config": "\"kw_0\"",
|
||||
"durations": [("90%ile", [(123456789, 1.7)]),
|
||||
("95%ile", [(123456789, 1.8)]),
|
||||
("avg", [(123456789, 0.8)]),
|
||||
("max", [(123456789, 1.5)]),
|
||||
("median", [(123456789, 1.55)]),
|
||||
("min", [(123456789, 1.2)])],
|
||||
"length": 1,
|
||||
"met": "name_0",
|
||||
"name": "Scenario.name_0",
|
||||
"sla_failures": 0,
|
||||
"stat": {"avg": 1.425, "max": 1.8, "min": 0.8},
|
||||
"success": [("success", [(123456789, 100.0)])]},
|
||||
{"actions": [{"durations": [("90%ile", [(123457789, 0.9)]),
|
||||
("95%ile", [(123457789, 0.87)]),
|
||||
("avg", [(123457789, 0.67)]),
|
||||
("max", [(123457789, 1.25)]),
|
||||
("median", [(123457789, 0.85)]),
|
||||
("min", [(123457789, 0.7)])],
|
||||
"name": "a",
|
||||
"success": [("success", [(123457789, 100.0)])]},
|
||||
{"durations": [("90%ile", [(123457789, 0.85)]),
|
||||
("95%ile", [(123457789, 0.9)]),
|
||||
("avg", [(123457789, 0.58)]),
|
||||
("max", [(123457789, 1.1)]),
|
||||
("median", [(123457789, 0.75)]),
|
||||
("min", [(123457789, 0.5)])],
|
||||
"name": "b",
|
||||
"success": [("success", [(123457789, 100.0)])]}],
|
||||
"cls": "Scenario",
|
||||
"config": "\"kw_1\"",
|
||||
"durations": [("90%ile", [(123457789, 1.7)]),
|
||||
("95%ile", [(123457789, 1.8)]),
|
||||
("avg", [(123457789, 0.8)]),
|
||||
("max", [(123457789, 1.5)]),
|
||||
("median", [(123457789, 1.55)]),
|
||||
("min", [(123457789, 1.2)])],
|
||||
"length": 1,
|
||||
"met": "name_1",
|
||||
"name": "Scenario.name_1",
|
||||
"sla_failures": 0,
|
||||
"stat": {"avg": 1.425, "max": 1.8, "min": 0.8},
|
||||
"success": [("success", [(123457789, 100.0)])]}]
|
||||
self.assertEqual(expected, self._sort_trends(trends.get_data()))
|
||||
|
||||
def test_add_result_once_and_get_data(self):
|
||||
trends = plot.Trends()
|
||||
trends.add_result(self._make_result("foo", sla_success=False))
|
||||
trends.add_result(self._make_result(42, sla_success=False))
|
||||
expected = [
|
||||
{"atomic": [
|
||||
{"name": "a",
|
||||
"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 0.9)]), ("95%ile", [(1, 0.87)]),
|
||||
("avg", [(1, 0.67)]), ("max", [(1, 1.25)]),
|
||||
("median", [(1, 0.85)]), ("min", [(1, 0.7)])]},
|
||||
{"name": "b",
|
||||
"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 0.85)]), ("95%ile", [(1, 0.9)]),
|
||||
("avg", [(1, 0.58)]), ("max", [(1, 1.1)]),
|
||||
("median", [(1, 0.75)]), ("min", [(1, 0.5)])]}],
|
||||
"cls": "Scenario", "config": "\"foo_kw\"", "met": "name_foo",
|
||||
"name": "Scenario.name_foo", "seq": 1, "single": True,
|
||||
"sla_failures": 1, "stat": {"avg": 1.6, "max": 1.5, "min": 1.2},
|
||||
"total": {"success": [("success", [(1, 100.0)])],
|
||||
"values": [("90%ile", [(1, 1.7)]),
|
||||
("95%ile", [(1, 1.9)]),
|
||||
("avg", [(1, 1.6)]),
|
||||
("max", [(1, 1.5)]),
|
||||
("median", [(1, 1.55)]),
|
||||
("min", [(1, 1.2)])]}}]
|
||||
{"actions": [{"durations": [("90%ile", [(123498789, 0.9)]),
|
||||
("95%ile", [(123498789, 0.87)]),
|
||||
("avg", [(123498789, 0.67)]),
|
||||
("max", [(123498789, 1.25)]),
|
||||
("median", [(123498789, 0.85)]),
|
||||
("min", [(123498789, 0.7)])],
|
||||
"name": "a",
|
||||
"success": [("success", [(123498789, 100.0)])]},
|
||||
{"durations": [("90%ile", [(123498789, 0.85)]),
|
||||
("95%ile", [(123498789, 0.9)]),
|
||||
("avg", [(123498789, 0.58)]),
|
||||
("max", [(123498789, 1.1)]),
|
||||
("median", [(123498789, 0.75)]),
|
||||
("min", [(123498789, 0.5)])],
|
||||
"name": "b",
|
||||
"success": [("success", [(123498789, 100.0)])]}],
|
||||
"cls": "Scenario",
|
||||
"config": "\"kw_42\"",
|
||||
"durations": [("90%ile", [(123498789, 1.7)]),
|
||||
("95%ile", [(123498789, 1.8)]),
|
||||
("avg", [(123498789, 0.8)]),
|
||||
("max", [(123498789, 1.5)]),
|
||||
("median", [(123498789, 1.55)]),
|
||||
("min", [(123498789, 1.2)])],
|
||||
"length": 1,
|
||||
"met": "name_42",
|
||||
"name": "Scenario.name_42",
|
||||
"sla_failures": 1,
|
||||
"stat": {"avg": 1.425, "max": 1.8, "min": 0.8},
|
||||
"success": [("success", [(123498789, 100.0)])]}]
|
||||
self.assertEqual(expected, self._sort_trends(trends.get_data()))
|
||||
|
||||
def test_add_result_with_na_and_get_data(self):
|
||||
trends = plot.Trends()
|
||||
trends.add_result(self._make_result("foo",
|
||||
sla_success=False, with_na=True))
|
||||
trends.add_result(
|
||||
self._make_result(42, sla_success=False, with_na=True))
|
||||
expected = [
|
||||
{"atomic": [{"name": "a",
|
||||
"success": [("success", [(1, 0)])],
|
||||
"values": [("90%ile", [(1, "n/a")]),
|
||||
("95%ile", [(1, "n/a")]),
|
||||
("avg", [(1, "n/a")]),
|
||||
("max", [(1, "n/a")]),
|
||||
("median", [(1, "n/a")]),
|
||||
("min", [(1, "n/a")])]},
|
||||
{"name": "b",
|
||||
"success": [("success", [(1, 0)])],
|
||||
"values": [("90%ile", [(1, "n/a")]),
|
||||
("95%ile", [(1, "n/a")]),
|
||||
("avg", [(1, "n/a")]),
|
||||
("max", [(1, "n/a")]),
|
||||
("median", [(1, "n/a")]),
|
||||
("min", [(1, "n/a")])]}],
|
||||
"cls": "Scenario", "config": "\"foo_kw\"", "met": "name_foo",
|
||||
"name": "Scenario.name_foo", "seq": 1, "single": True,
|
||||
"sla_failures": 1, "stat": {"avg": None, "max": None,
|
||||
"min": None},
|
||||
"total": {"success": [("success", [(1, 0)])],
|
||||
"values": [("90%ile", [(1, "n/a")]),
|
||||
("95%ile", [(1, "n/a")]),
|
||||
("avg", [(1, "n/a")]),
|
||||
("max", [(1, "n/a")]),
|
||||
("median", [(1, "n/a")]),
|
||||
("min", [(1, "n/a")])]}}]
|
||||
{"actions": [{"durations": [("90%ile", [(123498789, "n/a")]),
|
||||
("95%ile", [(123498789, "n/a")]),
|
||||
("avg", [(123498789, "n/a")]),
|
||||
("max", [(123498789, "n/a")]),
|
||||
("median", [(123498789, "n/a")]),
|
||||
("min", [(123498789, "n/a")])],
|
||||
"name": "a",
|
||||
"success": [("success", [(123498789, 0)])]},
|
||||
{"durations": [("90%ile", [(123498789, "n/a")]),
|
||||
("95%ile", [(123498789, "n/a")]),
|
||||
("avg", [(123498789, "n/a")]),
|
||||
("max", [(123498789, "n/a")]),
|
||||
("median", [(123498789, "n/a")]),
|
||||
("min", [(123498789, "n/a")])],
|
||||
"name": "b",
|
||||
"success": [("success", [(123498789, 0)])]}],
|
||||
"cls": "Scenario",
|
||||
"config": "\"kw_42\"",
|
||||
"durations": [("90%ile", [(123498789, "n/a")]),
|
||||
("95%ile", [(123498789, "n/a")]),
|
||||
("avg", [(123498789, "n/a")]),
|
||||
("max", [(123498789, "n/a")]),
|
||||
("median", [(123498789, "n/a")]),
|
||||
("min", [(123498789, "n/a")])],
|
||||
"length": 1,
|
||||
"met": "name_42",
|
||||
"name": "Scenario.name_42",
|
||||
"sla_failures": 1,
|
||||
"stat": {"avg": None, "max": None, "min": None},
|
||||
"success": [("success", [(123498789, 0)])]}]
|
||||
|
||||
self.assertEqual(expected, self._sort_trends(trends.get_data()))
|
||||
|
||||
def test_get_data_no_results_added(self):
|
||||
|
|
|
|||
Loading…
Reference in New Issue