|
@@ -0,0 +1,138 @@
|
|
|
+{
|
|
|
+ "cells": [
|
|
|
+ {
|
|
|
+ "cell_type": "markdown",
|
|
|
+ "metadata": {},
|
|
|
+ "source": [
|
|
|
+ "#### Writing to Apache Iceberg\n",
|
|
|
+ "\n",
|
|
|
+ "1. Insure you have a Google Bigquery service account key on disk\n",
|
|
|
+ "2. The service key location is set as an environment variable **BQ_KEY**\n",
|
|
|
+ "3. The dataset will be automatically created within the project associated with the service key\n",
|
|
|
+ "\n",
|
|
|
+ "The cell below creates a dataframe that will be stored within Google Bigquery"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "code",
|
|
|
+ "execution_count": 15,
|
|
|
+ "metadata": {},
|
|
|
+ "outputs": [
|
|
|
+ {
|
|
|
+ "name": "stdout",
|
|
|
+ "output_type": "stream",
|
|
|
+ "text": [
|
|
|
+ "['data transport version ', '2.4.0']\n"
|
|
|
+ ]
|
|
|
+ }
|
|
|
+ ],
|
|
|
+ "source": [
|
|
|
+ "#\n",
|
|
|
+ "# Writing to Google Bigquery database\n",
|
|
|
+ "#\n",
|
|
|
+ "import transport\n",
|
|
|
+ "from transport import providers\n",
|
|
|
+ "import pandas as pd\n",
|
|
|
+ "import os\n",
|
|
|
+ "\n",
|
|
|
+ "PRIVATE_KEY = os.environ['BQ_KEY'] #-- location of the service key\n",
|
|
|
+ "DATASET = 'demo'\n",
|
|
|
+ "_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
|
|
|
+ "# bqw = transport.get.writer(provider=providers.ICEBERG,catalog='mz',database='edw.mz',table='friends')\n",
|
|
|
+ "bqw = transport.get.writer(provider=providers.ICEBERG,table='edw.mz.friends')\n",
|
|
|
+ "bqw.write(_data,if_exists='replace') #-- default is append\n",
|
|
|
+ "print (['data transport version ', transport.__version__])\n"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "markdown",
|
|
|
+ "metadata": {},
|
|
|
+ "source": [
|
|
|
+ "#### Reading from Google Bigquery\n",
|
|
|
+ "\n",
|
|
|
+ "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",
|
|
|
+ "\n",
|
|
|
+ "- Basic read of the designated table (friends) created above\n",
|
|
|
+ "- Execute an aggregate SQL against the table\n",
|
|
|
+ "\n",
|
|
|
+ "**NOTE**\n",
|
|
|
+ "\n",
|
|
|
+ "By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
|
|
|
+ "Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "code",
|
|
|
+ "execution_count": 14,
|
|
|
+ "metadata": {},
|
|
|
+ "outputs": [
|
|
|
+ {
|
|
|
+ "name": "stdout",
|
|
|
+ "output_type": "stream",
|
|
|
+ "text": [
|
|
|
+ " name age\n",
|
|
|
+ "0 James Bond 55\n",
|
|
|
+ "1 Steve Rogers 150\n",
|
|
|
+ "2 Steve Nyemba 44\n",
|
|
|
+ "--------- STATISTICS ------------\n"
|
|
|
+ ]
|
|
|
+ }
|
|
|
+ ],
|
|
|
+ "source": [
|
|
|
+ "\n",
|
|
|
+ "import transport\n",
|
|
|
+ "from transport import providers\n",
|
|
|
+ "import os\n",
|
|
|
+ "PRIVATE_KEY=os.environ['BQ_KEY']\n",
|
|
|
+ "pgr = transport.get.reader(provider=providers.ICEBERG,database='edw.mz')\n",
|
|
|
+ "_df = pgr.read(table='friends')\n",
|
|
|
+ "_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
|
|
|
+ "_sdf = pgr.read(sql=_query)\n",
|
|
|
+ "print (_df)\n",
|
|
|
+ "print ('--------- STATISTICS ------------')\n",
|
|
|
+ "# print (_sdf)"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "markdown",
|
|
|
+ "metadata": {},
|
|
|
+ "source": [
|
|
|
+ "An **auth-file** is a file that contains database parameters used to access the database. \n",
|
|
|
+ "For code in shared environments, we recommend \n",
|
|
|
+ "\n",
|
|
|
+ "1. Having the **auth-file** stored on disk \n",
|
|
|
+ "2. and the location of the file is set to an environment variable.\n",
|
|
|
+ "\n",
|
|
|
+ "To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ {
|
|
|
+ "cell_type": "code",
|
|
|
+ "execution_count": null,
|
|
|
+ "metadata": {},
|
|
|
+ "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": "3.9.7"
|
|
|
+ }
|
|
|
+ },
|
|
|
+ "nbformat": 4,
|
|
|
+ "nbformat_minor": 2
|
|
|
+}
|