tutorials/using-dask/1.intro-to-dask.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to Dask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade dask distributed bokeh adlfs fsspec fastparquet pyarrow python-snappy lz4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from azureml.core import Workspace\n",
    "\n",
    "ws = Workspace.from_config()\n",
    "ws"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask.distributed import Client\n",
    "\n",
    "c = Client()\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read data\n",
    "\n",
    "Edit storage options per https://github.com/dask/adlfs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "container_name = \"isdweatherdatacontainer\"\n",
    "\n",
    "storage_options = {\"account_name\": \"azureopendatastorage\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from adlfs import AzureBlobFileSystem\n",
    "\n",
    "fs = AzureBlobFileSystem(**storage_options)\n",
    "fs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "fs.ls(f\"{container_name}/ISDWeather/year=2020\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = fs.glob(f\"{container_name}/ISDWeather/year=2020/month=2/*.parquet\")\n",
    "files = [f\"az://{file}\" for file in files]\n",
    "files[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.dataframe as dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "ddf = dd.read_parquet(files, storage_options=storage_options, chunksize=\"20MB\")\n",
    "ddf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf = ddf.persist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "len(ddf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "len(ddf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "ddf.describe().compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "gbs = round(ddf.memory_usage(index=True, deep=True).sum().compute() / 1e9, 2)\n",
    "print(f\"ddf is {gbs} GBs\")"
   ]
  }
 ],
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