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				|  |  | +{
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				|  |  | + "cells": [
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				|  |  | +  {
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				|  |  | +   "cell_type": "markdown",
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				|  |  | +   "metadata": {},
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				|  |  | +   "source": [
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				|  |  | +    "#### Writing to Apache Iceberg\n",
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				|  |  | +    "\n",
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				|  |  | +    "1. Insure you have a Google Bigquery service account key on disk\n",
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				|  |  | +    "2. The service key location is set as an environment variable **BQ_KEY**\n",
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				|  |  | +    "3. The dataset will be automatically created within the project associated with the service key\n",
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				|  |  | +    "\n",
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				|  |  | +    "The cell below creates a dataframe that will be stored within Google Bigquery"
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				|  |  | +   ]
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				|  |  | +  },
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				|  |  | +  {
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				|  |  | +   "cell_type": "code",
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				|  |  | +   "execution_count": 15,
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				|  |  | +   "metadata": {},
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				|  |  | +   "outputs": [
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				|  |  | +    {
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				|  |  | +     "name": "stdout",
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				|  |  | +     "output_type": "stream",
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				|  |  | +     "text": [
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				|  |  | +      "['data transport version ', '2.4.0']\n"
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				|  |  | +     ]
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				|  |  | +    }
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				|  |  | +   ],
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				|  |  | +   "source": [
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				|  |  | +    "#\n",
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				|  |  | +    "# Writing to Google Bigquery database\n",
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				|  |  | +    "#\n",
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				|  |  | +    "import transport\n",
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				|  |  | +    "from transport import providers\n",
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				|  |  | +    "import pandas as pd\n",
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				|  |  | +    "import os\n",
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				|  |  | +    "\n",
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				|  |  | +    "PRIVATE_KEY = os.environ['BQ_KEY'] #-- location of the service key\n",
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				|  |  | +    "DATASET = 'demo'\n",
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				|  |  | +    "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
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				|  |  | +    "# bqw = transport.get.writer(provider=providers.ICEBERG,catalog='mz',database='edw.mz',table='friends')\n",
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				|  |  | +    "bqw = transport.get.writer(provider=providers.ICEBERG,table='edw.mz.friends')\n",
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				|  |  | +    "bqw.write(_data,if_exists='replace') #-- default is append\n",
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				|  |  | +    "print (['data transport version ', transport.__version__])\n"
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				|  |  | +   ]
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				|  |  | +  },
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				|  |  | +  {
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				|  |  | +   "cell_type": "markdown",
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				|  |  | +   "metadata": {},
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				|  |  | +   "source": [
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				|  |  | +    "#### Reading from Google Bigquery\n",
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				|  |  | +    "\n",
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				|  |  | +    "The cell below reads the data that has been written by the cell above and computes the average age within a Google Bigquery (simple query). \n",
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				|  |  | +    "\n",
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				|  |  | +    "- Basic read of the designated table (friends) created above\n",
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				|  |  | +    "- Execute an aggregate SQL against the table\n",
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				|  |  | +    "\n",
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				|  |  | +    "**NOTE**\n",
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				|  |  | +    "\n",
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				|  |  | +    "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
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				|  |  | +    "Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
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				|  |  | +   ]
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				|  |  | +  },
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				|  |  | +  {
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				|  |  | +   "cell_type": "code",
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				|  |  | +   "execution_count": 14,
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				|  |  | +   "metadata": {},
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				|  |  | +   "outputs": [
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				|  |  | +    {
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				|  |  | +     "name": "stdout",
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				|  |  | +     "output_type": "stream",
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				|  |  | +     "text": [
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				|  |  | +      "           name  age\n",
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				|  |  | +      "0    James Bond   55\n",
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				|  |  | +      "1  Steve Rogers  150\n",
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				|  |  | +      "2  Steve Nyemba   44\n",
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				|  |  | +      "--------- STATISTICS ------------\n"
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				|  |  | +     ]
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				|  |  | +    }
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				|  |  | +   ],
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				|  |  | +   "source": [
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				|  |  | +    "\n",
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				|  |  | +    "import transport\n",
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				|  |  | +    "from transport import providers\n",
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				|  |  | +    "import os\n",
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				|  |  | +    "PRIVATE_KEY=os.environ['BQ_KEY']\n",
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				|  |  | +    "pgr = transport.get.reader(provider=providers.ICEBERG,database='edw.mz')\n",
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				|  |  | +    "_df = pgr.read(table='friends')\n",
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				|  |  | +    "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
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				|  |  | +    "_sdf = pgr.read(sql=_query)\n",
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				|  |  | +    "print (_df)\n",
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				|  |  | +    "print ('--------- STATISTICS ------------')\n",
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				|  |  | +    "# print (_sdf)"
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				|  |  | +   ]
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				|  |  | +  },
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				|  |  | +  {
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				|  |  | +   "cell_type": "markdown",
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				|  |  | +   "metadata": {},
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				|  |  | +   "source": [
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				|  |  | +    "An **auth-file** is a file that contains database parameters used to access the database. \n",
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				|  |  | +    "For code in shared environments, we recommend \n",
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				|  |  | +    "\n",
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				|  |  | +    "1. Having the **auth-file** stored on disk \n",
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				|  |  | +    "2. and the location of the file is set to an environment variable.\n",
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				|  |  | +    "\n",
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				|  |  | +    "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
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				|  |  | +   ]
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				|  |  | +  },
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				|  |  | +  {
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				|  |  | +   "cell_type": "code",
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				|  |  | +   "execution_count": null,
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				|  |  | +   "metadata": {},
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				|  |  | +   "outputs": [],
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				|  |  | +   "source": []
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				|  |  | +  }
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				|  |  | + ],
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				|  |  | +  "kernelspec": {
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				|  |  | +   "display_name": "Python 3",
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				|  |  | +   "language": "python",
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				|  |  | +  "language_info": {
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				|  |  | +   "codemirror_mode": {
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				|  |  | +    "name": "ipython",
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				|  |  | +    "version": 3
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				|  |  | +   "file_extension": ".py",
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				|  |  | +   "mimetype": "text/x-python",
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				|  |  | +   "name": "python",
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				|  |  | +   "nbconvert_exporter": "python",
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				|  |  | +   "pygments_lexer": "ipython3",
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				|  |  | +   "version": "3.9.7"
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				|  |  | + "nbformat": 4,
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				|  |  | + "nbformat_minor": 2
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				|  |  | +}
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