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Add minor fixes for PySpark Document Loader Docs (#5525)
# Add minor fixes for PySpark Document Loader Docs Renamed "PySpack" to "PySpark" and executed the notebook to show outputs.
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@ -1,17 +1,18 @@
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# PySpack DataFrame Loader\n",
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"# PySpark DataFrame Loader\n",
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"\n",
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"This shows how to load data from a PySpark DataFrame"
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"This notebook goes over how to load data from a [PySpark](https://spark.apache.org/docs/latest/api/python/) DataFrame."
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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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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -20,7 +21,7 @@
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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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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -29,16 +30,26 @@
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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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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Setting default log level to \"WARN\".\n",
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"To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
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"23/05/31 14:08:33 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n"
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]
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}
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],
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"source": [
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"spark = SparkSession.builder.getOrCreate()"
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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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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -47,7 +58,7 @@
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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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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -56,7 +67,7 @@
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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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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -65,9 +76,56 @@
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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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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[Stage 8:> (0 + 1) / 1]\r"
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]
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},
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{
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"data": {
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"text/plain": [
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"[Document(page_content='Nationals', metadata={' \"Payroll (millions)\"': ' 81.34', ' \"Wins\"': ' 98'}),\n",
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" Document(page_content='Reds', metadata={' \"Payroll (millions)\"': ' 82.20', ' \"Wins\"': ' 97'}),\n",
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" Document(page_content='Yankees', metadata={' \"Payroll (millions)\"': ' 197.96', ' \"Wins\"': ' 95'}),\n",
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" Document(page_content='Giants', metadata={' \"Payroll (millions)\"': ' 117.62', ' \"Wins\"': ' 94'}),\n",
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" Document(page_content='Braves', metadata={' \"Payroll (millions)\"': ' 83.31', ' \"Wins\"': ' 94'}),\n",
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" Document(page_content='Athletics', metadata={' \"Payroll (millions)\"': ' 55.37', ' \"Wins\"': ' 94'}),\n",
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" Document(page_content='Rangers', metadata={' \"Payroll (millions)\"': ' 120.51', ' \"Wins\"': ' 93'}),\n",
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" Document(page_content='Orioles', metadata={' \"Payroll (millions)\"': ' 81.43', ' \"Wins\"': ' 93'}),\n",
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" Document(page_content='Rays', metadata={' \"Payroll (millions)\"': ' 64.17', ' \"Wins\"': ' 90'}),\n",
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" Document(page_content='Angels', metadata={' \"Payroll (millions)\"': ' 154.49', ' \"Wins\"': ' 89'}),\n",
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" Document(page_content='Tigers', metadata={' \"Payroll (millions)\"': ' 132.30', ' \"Wins\"': ' 88'}),\n",
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" Document(page_content='Cardinals', metadata={' \"Payroll (millions)\"': ' 110.30', ' \"Wins\"': ' 88'}),\n",
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" Document(page_content='Dodgers', metadata={' \"Payroll (millions)\"': ' 95.14', ' \"Wins\"': ' 86'}),\n",
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" Document(page_content='White Sox', metadata={' \"Payroll (millions)\"': ' 96.92', ' \"Wins\"': ' 85'}),\n",
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" Document(page_content='Brewers', metadata={' \"Payroll (millions)\"': ' 97.65', ' \"Wins\"': ' 83'}),\n",
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" Document(page_content='Phillies', metadata={' \"Payroll (millions)\"': ' 174.54', ' \"Wins\"': ' 81'}),\n",
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" Document(page_content='Diamondbacks', metadata={' \"Payroll (millions)\"': ' 74.28', ' \"Wins\"': ' 81'}),\n",
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" Document(page_content='Pirates', metadata={' \"Payroll (millions)\"': ' 63.43', ' \"Wins\"': ' 79'}),\n",
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" Document(page_content='Padres', metadata={' \"Payroll (millions)\"': ' 55.24', ' \"Wins\"': ' 76'}),\n",
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" Document(page_content='Mariners', metadata={' \"Payroll (millions)\"': ' 81.97', ' \"Wins\"': ' 75'}),\n",
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" Document(page_content='Mets', metadata={' \"Payroll (millions)\"': ' 93.35', ' \"Wins\"': ' 74'}),\n",
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" Document(page_content='Blue Jays', metadata={' \"Payroll (millions)\"': ' 75.48', ' \"Wins\"': ' 73'}),\n",
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" Document(page_content='Royals', metadata={' \"Payroll (millions)\"': ' 60.91', ' \"Wins\"': ' 72'}),\n",
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" Document(page_content='Marlins', metadata={' \"Payroll (millions)\"': ' 118.07', ' \"Wins\"': ' 69'}),\n",
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" Document(page_content='Red Sox', metadata={' \"Payroll (millions)\"': ' 173.18', ' \"Wins\"': ' 69'}),\n",
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" Document(page_content='Indians', metadata={' \"Payroll (millions)\"': ' 78.43', ' \"Wins\"': ' 68'}),\n",
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" Document(page_content='Twins', metadata={' \"Payroll (millions)\"': ' 94.08', ' \"Wins\"': ' 66'}),\n",
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" Document(page_content='Rockies', metadata={' \"Payroll (millions)\"': ' 78.06', ' \"Wins\"': ' 64'}),\n",
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" Document(page_content='Cubs', metadata={' \"Payroll (millions)\"': ' 88.19', ' \"Wins\"': ' 61'}),\n",
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" Document(page_content='Astros', metadata={' \"Payroll (millions)\"': ' 60.65', ' \"Wins\"': ' 55'})]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"loader.load()"
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]
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@ -89,7 +147,7 @@
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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": "3.9.1"
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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