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@satybald
Last active May 28, 2018 18:54
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>node_id</th>\n",
" <th>query_id</th>\n",
" <th>state</th>\n",
" <th>user</th>\n",
" <th>source</th>\n",
" <th>query</th>\n",
" <th>queued_time_ms</th>\n",
" <th>analysis_time_ms</th>\n",
" <th>distributed_planning_time_ms</th>\n",
" <th>created</th>\n",
" <th>started</th>\n",
" <th>last_heartbeat</th>\n",
" <th>end</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ffffffff-ffff-ffff-ffff-ffffffffffff</td>\n",
" <td>20180526_115416_00010_nwiis</td>\n",
" <td>RUNNING</td>\n",
" <td>satybald</td>\n",
" <td>pyhive</td>\n",
" <td>select * from queries limit 1</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" <td>0</td>\n",
" <td>2018-05-26 13:54:16.654</td>\n",
" <td>2018-05-26 13:54:16.675</td>\n",
" <td>2018-05-26 13:54:16.656</td>\n",
" <td>None</td>\n",
" </tr>\n",
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],
"text/plain": [
" node_id query_id state \\\n",
"0 ffffffff-ffff-ffff-ffff-ffffffffffff 20180526_115416_00010_nwiis RUNNING \n",
"\n",
" user source query queued_time_ms \\\n",
"0 satybald pyhive select * from queries limit 1 1 \n",
"\n",
" analysis_time_ms distributed_planning_time_ms created \\\n",
"0 17 0 2018-05-26 13:54:16.654 \n",
"\n",
" started last_heartbeat end \n",
"0 2018-05-26 13:54:16.675 2018-05-26 13:54:16.656 None "
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"from sqlalchemy.engine import create_engine\n",
"\n",
"# Presto\n",
"engine = create_engine('presto://localhost:8080/system/runtime') \n",
"\n",
"#Read Presto Data query into a DataFrame\n",
"df = pd.read_sql('select * from queries limit 1', engine)\n",
"df.head()"
]
}
],
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"file_extension": ".py",
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"nbconvert_exporter": "python",
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"version": "2.7.12"
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