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TRAPpy_MergeDF_API_Example.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import trappy\n",
"from trappy import ftrace\n",
"from trappy.ftrace import GenericFTrace\n",
"import numpy as np\n",
"import pandas"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lines = [\n",
"\" adbd-5709 [007] 2943.184105: sched_contrib_scale_f: cpu=7 cpu_scale_factor=1\\n\"\n",
"\" adbd-5709 [007] 2943.184105: sched_load_avg_cpu: cpu=7 util_avg=825\\n\"\n",
"\" ->transport-5713 [006] 2943.184106: sched_load_avg_cpu: cpu=6 util_avg=292\\n\"\n",
"\" ->transport-5713 [006] 2943.184107: sched_contrib_scale_f: cpu=6 cpu_scale_factor=2\\n\"\n",
"\" adbd-5709 [007] 2943.184108: sched_load_avg_cpu: cpu=7 util_avg=850\\n\"\n",
"\" adbd-5709 [007] 2943.184109: sched_contrib_scale_f: cpu=7 cpu_scale_factor=3\\n\"\n",
"\" adbd-5709 [007] 2943.184110: sched_load_avg_cpu: cpu=6 util_avg=315\\n\"\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"with open('/tmp/trappy_mergedf_example.txt', 'w') as fh:\n",
" for line in lines:\n",
" fh.write(line)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" adbd-5709 [007] 2943.184105: sched_contrib_scale_f: cpu=7 cpu_scale_factor=1\r\n",
" adbd-5709 [007] 2943.184105: sched_load_avg_cpu: cpu=7 util_avg=825\r\n",
" ->transport-5713 [006] 2943.184106: sched_load_avg_cpu: cpu=6 util_avg=292\r\n",
" ->transport-5713 [006] 2943.184107: sched_contrib_scale_f: cpu=6 cpu_scale_factor=2\r\n",
" adbd-5709 [007] 2943.184108: sched_load_avg_cpu: cpu=7 util_avg=850\r\n",
" adbd-5709 [007] 2943.184109: sched_contrib_scale_f: cpu=7 cpu_scale_factor=3\r\n",
" adbd-5709 [007] 2943.184110: sched_load_avg_cpu: cpu=6 util_avg=315\r\n"
]
}
],
"source": [
"!cat /tmp/trappy_mergedf_example.txt"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"trace = ftrace.FTrace('/tmp/trappy_mergedf_example.txt', events=['sched_contrib_scale_f', 'sched_load_avg_cpu'], normalize_time=False)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cpu</th>\n",
" <th>util_avg</th>\n",
" <th>__line</th>\n",
" </tr>\n",
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"text/plain": [
" cpu util_avg __line\n",
"Time \n",
"2943.184105 7 825 1\n",
"2943.184106 6 292 2\n",
"2943.184108 7 850 4\n",
"2943.184110 6 315 6"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df1 = trace.sched_load_avg_cpu.data_frame[['cpu', 'util_avg', '__line']]\n",
"df1"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cpu</th>\n",
" <th>cpu_scale_factor</th>\n",
" <th>__line</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time</th>\n",
" <th></th>\n",
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"text/plain": [
" cpu cpu_scale_factor __line\n",
"Time \n",
"2943.184105 7 1 0\n",
"2943.184107 6 2 3\n",
"2943.184109 7 3 5"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df2 = trace.sched_contrib_scale_f.data_frame[['cpu', 'cpu_scale_factor', '__line']]\n",
"df2"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
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" <th>__line</th>\n",
" <th>cpu</th>\n",
" <th>cpu_scale_factor</th>\n",
" <th>util_avg</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time</th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th>2943.184105</th>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" <td>1.0</td>\n",
" <td>825.0</td>\n",
" </tr>\n",
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" <th>2943.184106</th>\n",
" <td>2</td>\n",
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" <td>NaN</td>\n",
" <td>292.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2943.184108</th>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>1.0</td>\n",
" <td>850.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2943.184110</th>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>2.0</td>\n",
" <td>315.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" __line cpu cpu_scale_factor util_avg\n",
"Time \n",
"2943.184105 1 7 1.0 825.0\n",
"2943.184106 2 6 NaN 292.0\n",
"2943.184108 4 7 1.0 850.0\n",
"2943.184110 6 6 2.0 315.0"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trappy.ftrace.merge_dfs(df1, df2, 'cpu')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
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"description": "TRAPpy_MergeDF_API_Example",
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"kernelspec": {
"display_name": "Python 2",
"language": "python",
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"toc": {
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"running_highlight": "#FF0000",
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"nav_menu": {
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"width": "252px"
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"toc_section_display": "block",
"toc_window_display": false
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