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#!/usr/bin/env python3
import sys
import json
from os.path import abspath
import argparse
import matplotlib.pyplot as pyplot
LOG_ID_WORKLOAD_NAME = 7782100
LOG_ID_METRICS = 7782101
parser = argparse.ArgumentParser(description="Process simulator log output piped to stdin")
parser.add_argument(
"-o",
"--outputDirectory",
help="Path to an existing directory where output should be stored",
metavar="~/path/for/output",
)
args = parser.parse_args()
directory = args.outputDirectory
# Load the log data that's piped in.
workloads = {}
currentWorkload = ""
firstTime = 0
for line in sys.stdin:
parsed = json.loads(line)
if parsed["id"] == LOG_ID_WORKLOAD_NAME:
# Starting output for a new workload.
currentWorkload = parsed["attr"]["workload"]
# Can't reuse the workload name
assert currentWorkload not in workloads
# Initialize the data structure for the output.
workloads[currentWorkload] = {"time": [], "metrics": {}}
elif parsed["id"] == LOG_ID_METRICS:
# Check that data structure for current workload has been initialized properly.
assert isinstance(workloads[currentWorkload], dict)
assert isinstance(workloads[currentWorkload]["time"], list)
assert isinstance(workloads[currentWorkload]["metrics"], dict)
# Parsing output for the current workload.
# Normalize time values so that first time value in series is '0', displayed in seconds.
if len(workloads[currentWorkload]["time"]) == 0:
firstTime = parsed["attr"]["time"]
workloads[currentWorkload]["time"].append((parsed["attr"]["time"] - firstTime) / 1e9)
# Process the metrics, initializing structures as necessary
metrics = parsed["attr"]["metrics"]
for grouping, data in metrics.items():
if grouping not in workloads[currentWorkload]["metrics"]:
workloads[currentWorkload]["metrics"][grouping] = {}
for key, value in data.items():
if key not in workloads[currentWorkload]["metrics"][grouping]:
workloads[currentWorkload]["metrics"][grouping][key] = []
workloads[currentWorkload]["metrics"][grouping][key].append(value)
# Plot the data and save the resulting figures to the output directory.
for workload, data in workloads.items():
numPlots = len(data["metrics"])
width = min(numPlots, 3)
height = int(numPlots / width) + (numPlots % width > 0)
fig, ax = pyplot.subplots(
nrows=height,
ncols=width,
figsize=(7.5 * width, 3.5 * height),
sharex=True,
layout="constrained",
)
fig.suptitle("Workload: " + workload)
i = 0
for grouping, metrics in data["metrics"].items():
ax[i].set_title(grouping)
ax[i].set_xlabel("Time (s)")
for key, values in metrics.items():
ax[i].plot(data["time"], values, label=key)
ax[i].legend()
i = i + 1
fig.savefig(directory + "/" + workload + ".png", dpi=300)
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