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July 8, 2017 21:21
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TRAPpy_MergeDF_API_Example.ipynb
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
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"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 | |
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"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, | |
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"outputs": [ | |
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"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>util_avg</th>\n", | |
" <th>__line</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>Time</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
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" <th>2943.184105</th>\n", | |
" <td>7</td>\n", | |
" <td>825</td>\n", | |
" <td>1</td>\n", | |
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" <tr>\n", | |
" <th>2943.184106</th>\n", | |
" <td>6</td>\n", | |
" <td>292</td>\n", | |
" <td>2</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2943.184108</th>\n", | |
" <td>7</td>\n", | |
" <td>850</td>\n", | |
" <td>4</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2943.184110</th>\n", | |
" <td>6</td>\n", | |
" <td>315</td>\n", | |
" <td>6</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\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 | |
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"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", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>2943.184105</th>\n", | |
" <td>7</td>\n", | |
" <td>1</td>\n", | |
" <td>0</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2943.184107</th>\n", | |
" <td>6</td>\n", | |
" <td>2</td>\n", | |
" <td>3</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2943.184109</th>\n", | |
" <td>7</td>\n", | |
" <td>3</td>\n", | |
" <td>5</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"</div>" | |
], | |
"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", | |
" <th></th>\n", | |
" <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", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\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", | |
" <tr>\n", | |
" <th>2943.184106</th>\n", | |
" <td>2</td>\n", | |
" <td>6</td>\n", | |
" <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": { | |
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"outputs": [], | |
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