Add Spark Table Interoperability tutorial.

Author: igorborgest

tutorials/020 - Spark Table Interoperability.ipynb

@@ -0,0 +1,72 @@
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+    "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)\n",
+    "\n",
+    "# 20 - Spark Table Interoperability\n",
+    "\n",
+    "[Wrangler](https://github.com/awslabs/aws-data-wrangler) has no difficults to insert, overwrite or do any other kind of interaction with a Table created by Apache Spark.\n",
+    "\n",
+    "But if you want to do the oposite (Spark interacting with a table created by Wrangler) you should be aware that Wrangler follows the Hive's format and you must be explicit when using the Spark's `saveAsTable` method:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spark_df.write.format(\"hive\").saveAsTable(\"database.table\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Or just move forward using the `insertInto` alternative:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spark_df.write.insertInto(\"database.table\")"
+   ]
+  }
+ ],
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