# setup
import pandas as pd
import io
import subprocess
import matplotlib.pyplot as plt
!wget -nc https://github.com/parttimenerd/jfr-query-experiments/releases/download/snapshot/query.jar
def query_and_to_dataframe(select_value):
command = [
"/home/dlovison/.sdkman/candidates/java/24.0.1-tem/bin/java",
"-jar",
"query.jar",
"query",
str(select_value),
"/home/dlovison/Downloads/bkp2/bkp/profiling-data/data.jfr"
]
result = subprocess.run(command, capture_output=True, text=True, check=True)
output_string = result.stdout
df = pd.read_csv(
io.StringIO(output_string),
sep=r'\s{2,}',
engine='python',
skiprows=[1] # Skip the separator line (index 1)
)
df.columns = df.columns.str.strip()
return dfdf = query_and_to_dataframe("SELECT * FROM CPULoad")
df.tail(10)
|
Time |
JVM User |
JVM System |
Machine Total |
| 49 |
17:34:15 |
14.54% |
2.17% |
17.19% |
| 50 |
17:34:16 |
14.48% |
2.18% |
17.17% |
| 51 |
17:34:17 |
14.56% |
2.13% |
17.17% |
| 52 |
17:34:18 |
14.46% |
2.24% |
17.19% |
| 53 |
17:34:19 |
14.39% |
2.30% |
17.16% |
| 54 |
17:34:20 |
14.36% |
2.34% |
17.18% |
| 55 |
17:34:21 |
14.37% |
2.26% |
17.08% |
| 56 |
17:34:22 |
14.22% |
2.32% |
17.02% |
| 57 |
17:34:23 |
14.24% |
2.30% |
17.08% |
| 58 |
17:34:24 |
14.15% |
2.26% |
16.84% |
df['Machine Total'].str.replace('%', '').astype(float).plot()
df['JVM User'].str.replace('%', '').astype(float).plot()
df['JVM System'].str.replace('%', '').astype(float).plot()
