tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server, Oracle.ipynb

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    "[![AWS SDK for pandas](_static/logo.png \"AWS SDK for pandas\")](https://github.com/aws/aws-sdk-pandas)\n",
    "\n",
    "# 7 - Redshift, MySQL, PostgreSQL, SQL Server and Oracle\n",
    "\n",
    "[awswrangler](https://github.com/aws/aws-sdk-pandas)'s Redshift, MySQL and PostgreSQL have two basic functions in common that try to follow Pandas conventions, but add more data type consistency.\n",
    "\n",
    "- [wr.redshift.to_sql()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.redshift.to_sql.html)\n",
    "- [wr.redshift.read_sql_query()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.redshift.read_sql_query.html)\n",
    "- [wr.mysql.to_sql()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.mysql.to_sql.html)\n",
    "- [wr.mysql.read_sql_query()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.mysql.read_sql_query.html)\n",
    "- [wr.postgresql.to_sql()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.postgresql.to_sql.html)\n",
    "- [wr.postgresql.read_sql_query()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.postgresql.read_sql_query.html)\n",
    "- [wr.sqlserver.to_sql()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.sqlserver.to_sql.html)\n",
    "- [wr.sqlserver.read_sql_query()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.sqlserver.read_sql_query.html)\n",
    "- [wr.oracle.to_sql()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.oracle.to_sql.html)\n",
    "- [wr.oracle.read_sql_query()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.oracle.read_sql_query.html)"
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "# Install the optional modules first\n",
    "!pip install 'awswrangler[redshift, postgres, mysql, sqlserver, oracle]'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import awswrangler as wr\n",
    "\n",
    "df = pd.DataFrame({\"id\": [1, 2], \"name\": [\"foo\", \"boo\"]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connect using the Glue Catalog Connections\n",
    "\n",
    "- [wr.redshift.connect()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.redshift.connect.html)\n",
    "- [wr.mysql.connect()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.mysql.connect.html)\n",
    "- [wr.postgresql.connect()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.postgresql.connect.html)\n",
    "- [wr.sqlserver.connect()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.sqlserver.connect.html)\n",
    "- [wr.oracle.connect()](https://aws-sdk-pandas.readthedocs.io/en/3.11.0/stubs/awswrangler.oracle.connect.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "con_redshift = wr.redshift.connect(\"aws-sdk-pandas-redshift\")\n",
    "con_mysql = wr.mysql.connect(\"aws-sdk-pandas-mysql\")\n",
    "con_postgresql = wr.postgresql.connect(\"aws-sdk-pandas-postgresql\")\n",
    "con_sqlserver = wr.sqlserver.connect(\"aws-sdk-pandas-sqlserver\")\n",
    "con_oracle = wr.oracle.connect(\"aws-sdk-pandas-oracle\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Raw SQL queries (No Pandas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\n"
     ]
    }
   ],
   "source": [
    "with con_redshift.cursor() as cursor:\n",
    "    for row in cursor.execute(\"SELECT 1\"):\n",
    "        print(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data to Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "wr.redshift.to_sql(df, con_redshift, schema=\"public\", table=\"tutorial\", mode=\"overwrite\")\n",
    "wr.mysql.to_sql(df, con_mysql, schema=\"test\", table=\"tutorial\", mode=\"overwrite\")\n",
    "wr.postgresql.to_sql(df, con_postgresql, schema=\"public\", table=\"tutorial\", mode=\"overwrite\")\n",
    "wr.sqlserver.to_sql(df, con_sqlserver, schema=\"dbo\", table=\"tutorial\", mode=\"overwrite\")\n",
    "wr.oracle.to_sql(df, con_oracle, schema=\"test\", table=\"tutorial\", mode=\"overwrite\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unloading data from Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "   id name\n",
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   "source": [
    "wr.redshift.read_sql_query(\"SELECT * FROM public.tutorial\", con=con_redshift)\n",
    "wr.mysql.read_sql_query(\"SELECT * FROM test.tutorial\", con=con_mysql)\n",
    "wr.postgresql.read_sql_query(\"SELECT * FROM public.tutorial\", con=con_postgresql)\n",
    "wr.sqlserver.read_sql_query(\"SELECT * FROM dbo.tutorial\", con=con_sqlserver)\n",
    "wr.oracle.read_sql_query(\"SELECT * FROM test.tutorial\", con=con_oracle)"
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    "con_redshift.close()\n",
    "con_mysql.close()\n",
    "con_postgresql.close()\n",
    "con_sqlserver.close()\n",
    "con_oracle.close()"
   ]
  }
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