tutorials/009 - Redshift - Append, Overwrite, Upsert.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",
    "# 9 - Redshift - Append, Overwrite and Upsert\n",
    "\n",
    "awswrangler's `copy/to_sql` function has three different `mode` options for Redshift.\n",
    "\n",
    "1 - `append`\n",
    "\n",
    "2 - `overwrite`\n",
    "\n",
    "3 - `upsert`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install the optional modules first\n",
    "!pip install 'awswrangler[redshift]'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import awswrangler as wr\n",
    "\n",
    "con = wr.redshift.connect(\"aws-sdk-pandas-redshift\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enter your bucket name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ···········································\n"
     ]
    }
   ],
   "source": [
    "import getpass\n",
    "\n",
    "bucket = getpass.getpass()\n",
    "path = f\"s3://{bucket}/stage/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enter your IAM ROLE ARN:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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      " ····················································································\n"
     ]
    }
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   "source": [
    "iam_role = getpass.getpass()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating the table (Overwriting if it exists)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 10,
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   "outputs": [
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       "      <td>boo</td>\n",
       "      <td>2020-01-02</td>\n",
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       "   id value        date\n",
       "0   2   boo  2020-01-02\n",
       "1   1   foo  2020-01-01"
      ]
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   "source": [
    "df = pd.DataFrame({\"id\": [1, 2], \"value\": [\"foo\", \"boo\"], \"date\": [date(2020, 1, 1), date(2020, 1, 2)]})\n",
    "\n",
    "wr.redshift.copy(\n",
    "    df=df,\n",
    "    path=path,\n",
    "    con=con,\n",
    "    schema=\"public\",\n",
    "    table=\"my_table\",\n",
    "    mode=\"overwrite\",\n",
    "    iam_role=iam_role,\n",
    "    primary_keys=[\"id\"],\n",
    ")\n",
    "\n",
    "wr.redshift.read_sql_table(table=\"my_table\", schema=\"public\", con=con)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Appending"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
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       "      <td>boo</td>\n",
       "      <td>2020-01-02</td>\n",
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       "   id value        date\n",
       "0   1   foo  2020-01-01\n",
       "1   2   boo  2020-01-02\n",
       "2   3   bar  2020-01-03"
      ]
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   "source": [
    "df = pd.DataFrame({\"id\": [3], \"value\": [\"bar\"], \"date\": [date(2020, 1, 3)]})\n",
    "\n",
    "wr.redshift.copy(\n",
    "    df=df, path=path, con=con, schema=\"public\", table=\"my_table\", mode=\"append\", iam_role=iam_role, primary_keys=[\"id\"]\n",
    ")\n",
    "\n",
    "wr.redshift.read_sql_table(table=\"my_table\", schema=\"public\", con=con)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Upserting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "      <td>2020-01-01</td>\n",
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       "      <td>2</td>\n",
       "      <td>xoo</td>\n",
       "      <td>2020-01-02</td>\n",
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       "      <td>2020-01-03</td>\n",
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      "text/plain": [
       "   id value        date\n",
       "0   1   foo  2020-01-01\n",
       "1   2   xoo  2020-01-02\n",
       "2   3   bar  2020-01-03"
      ]
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   "source": [
    "df = pd.DataFrame({\"id\": [2, 3], \"value\": [\"xoo\", \"bar\"], \"date\": [date(2020, 1, 2), date(2020, 1, 3)]})\n",
    "\n",
    "wr.redshift.copy(\n",
    "    df=df, path=path, con=con, schema=\"public\", table=\"my_table\", mode=\"upsert\", iam_role=iam_role, primary_keys=[\"id\"]\n",
    ")\n",
    "\n",
    "wr.redshift.read_sql_table(table=\"my_table\", schema=\"public\", con=con)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "with con.cursor() as cursor:\n",
    "    cursor.execute(\"DROP TABLE public.my_table\")\n",
    "con.close()"
   ]
  }
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