Reto02_Actividad_01.ipynb

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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "//Import para Jupyter-notebooks \n",
    "import $ivy.`org.apache.spark::spark-sql:2.4.0`\n",
    "import $ivy.`sh.almond::almond-spark:0.6.0`\n",
    "import org.apache.log4j.{Level, Logger}\n",
    "Logger.getLogger(\"org\").setLevel(Level.OFF)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Crear una tabla temporal desde un df\n",
    "\n",
    "1. Definir la sesión de Spark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.apache.spark.sql._\n",
    "\n",
    "val spark = {\n",
    "  NotebookSparkSession.builder()\n",
    "    .master(\"local[*]\")\n",
    "    .getOrCreate()\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Crear un dataframe desde un archivo plano ubicación: resources/Impuesto_de_Transporte_-_MinEnerg_a.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "solution2": "hidden",
    "solution2_first": true
   },
   "outputs": [],
   "source": [
    "import spark.implicits._\n",
    "val df = ???"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "solution2": "hidden"
   },
   "outputs": [],
   "source": [
    "val df = spark.read.format(\"csv\").option(\"header\",true).load(\"resources/Impuesto_de_Transporte_-_MinEnerg_a.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Registra el dataframe como una tabla temporal y envia ejecuta la sentencia sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "solution2": "hidden",
    "solution2_first": true
   },
   "outputs": [],
   "source": [
    "val query = \"select ano, departamento, municipio from impuestos\"\n",
    "df.___\n",
    "spark._______"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "solution2": "hidden"
   },
   "outputs": [],
   "source": [
    "df.createOrReplaceTempView(\"impuestos\")\n",
    "spark.sql(query).where(\"departamento = 'BOLIVAR'\").show()"
   ]
  }
 ],
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