Add simple Spark notebook and environment (#45)

spark.ipynb

@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f8eafed2-77a1-4691-8e8b-aeb1187ce8f5",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "\n",
+    "Spark on Coiled\n",
+    "===============\n",
+    "\n",
+    "<img src=\"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRLsyvblPuU1h0NRGoZiODTKqIYbTpCu3hrHoM1rXzt1A&s\"\n",
+    "     align=\"right\"\n",
+    "     width=\"40%\"/>\n",
+    "\n",
+    "Coiled can run Spark Jobs.\n",
+    "\n",
+    "You get all the same Coiled ease of use features:\n",
+    "\n",
+    "1.  Quick startup\n",
+    "2.  Copies all of your local packages and code\n",
+    "3.  Runs in any region on any hardware\n",
+    "4.  Runs from your local notebook\n",
+    "\n",
+    "But now rather than just Dask you can run Spark too."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0d130128-ac72-4ce6-87b1-b7a20337fd2a",
+   "metadata": {},
+   "source": [
+    "### Read a little bit of data with pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09728a96-0c84-4198-ab52-4dcdfd704606",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_parquet(\n",
+    "    \"s3://coiled-data/uber/part.0.parquet\",\n",
+    ")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3148ad8d-3de7-47b6-91a3-1d1f5a393f64",
+   "metadata": {},
+   "source": [
+    "## Start Spark cluster to read lots of data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9a9e6076-c8b3-4282-90a4-0fe3ab49440d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import coiled\n",
+    "\n",
+    "cluster = coiled.Cluster(\n",
+    "    n_workers=10,\n",
+    "    worker_memory=\"16 GiB\",\n",
+    "    region=\"us-east-2\",\n",
+    ")\n",
+    "\n",
+    "spark = cluster.get_spark()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "33b598a4-fe0a-43c5-8007-0e955ac193f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = spark.read.parquet(\"s3a://coiled-data/uber\")\n",
+    "df.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "56e2b982-af1b-4140-8cc1-414343ba1f0a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.count()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:spark]",
+   "language": "python",
+   "name": "conda-env-spark-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

spark.yml

@@ -0,0 +1,16 @@
+name: spark
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - dask
+  - coiled
+  - ipykernel
+  - pyspark==3.4.1
+  - pyarrow
+  - grpcio
+  - grpcio-status
+  - openjdk~=11.0
+  - protobuf
+  - jupyterlab
+  - s3fs