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@Kelvinrr
Last active June 30, 2017 17:40
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"import pyspark\n",
"from pyspark import SparkContext, SQLContext, SparkConf\n",
"\n",
"from pyspark.sql.functions import udf, col\n",
"from pyspark.sql.types import FloatType\n",
"\n",
"import os\n",
"\n",
"\n",
"os.environ['SPARK_HOME'] = \"/home/jlaura/bigdata/spark-2.1.1-bin-hadoop2.7\"\n",
"os.environ['SPARK_CONF_DIR'] = \"/tmp/spark/j_spark/749078/conf/\" # This is a per job variable\n",
"\n",
"conf = SparkConf()\\\n",
" .setMaster('spark://neb1:7077')\\\n",
" .setAppName(\"KelvinJobs\")\\\n",
" .set(\"spark.cores.max\", 20)\n",
"sc = SparkContext(conf=conf)\n",
"sqlContext = SQLContext(sc)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true,
"scrolled": false
},
"outputs": [],
"source": [
"# df = sqlContext.read.format(\"jdbc\").options(url=\"jdbc:postgresql://172.16.3.181:31180/tes?user=postgres&password=pass\", dbtable=\"tiy25\",driver=\"org.postgresql.Driver\").load()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"properties = {\n",
" \"driver\": \"org.postgresql.Driver\",\n",
" \"user\": \"postgres\",\n",
" \"password\" : \"pass\"\n",
"}\n",
"url = 'jdbc:postgresql://dcos-node1:31180/tes'\n",
"df = sqlContext.read.jdbc(url=url, table='global_y25', properties=properties)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[Row(ti=0.0, long_idx=1, lat_idx=1, lsubs_idx=75),\n",
" Row(ti=0.0, long_idx=1, lat_idx=1, lsubs_idx=76),\n",
" Row(ti=0.3888888888888889, long_idx=1, lat_idx=2, lsubs_idx=43),\n",
" Row(ti=0.06666666666666667, long_idx=1, lat_idx=2, lsubs_idx=44),\n",
" Row(ti=0.6111111111111112, long_idx=1, lat_idx=2, lsubs_idx=60)]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sc.stop()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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