{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "import sys\n", "sys.path.append(\"..\")\n", "from optimus import Optimus\n", "\n", "# Create optimus\n", "op = Optimus(\"dask\", verbose = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Mysql" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# !pip install mysqlclient" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mysql://test:test@165.227.196.70:3306/optimus\n" ] } ], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"mysql\",\n", " host=\"165.227.196.70\", \n", " database= \"optimus\", \n", " user= \"test\", \n", " password = \"test\")" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['test_data']\n" ] } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
id
\n", "
1 (int64)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
first_name
\n", "
2 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
last_name
\n", "
3 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
email
\n", "
4 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
gender
\n", "
5 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
ip_address
\n", "
6 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
\n", " 		\n", "
\n", " \n", " eedden1@nytimes.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.205.155.142\n", " \n", "
\n", "
\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rudyard\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 84.170.67.167\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " Eugen\n", " \n", "
\n", " 		\n", "
\n", " \n", " Staining\n", " \n", "
\n", " 		\n", "
\n", " \n", " estaining3@merriam-webster.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 211.36.45.228\n", " \n", "
\n", "
\n", "
\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " Banky\n", " \n", "
\n", " 		\n", "
\n", " \n", " Shires\n", " \n", "
\n", " 		\n", "
\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.18.210.158\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Chastity\n", " \n", "
\n", " 		\n", "
\n", " \n", " Birtwell\n", " \n", "
\n", " 		\n", "
\n", " \n", " cbirtwell8@seesaa.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 167.15.222.219\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " Harv\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fotherby\n", " \n", "
\n", " 		\n", "
\n", " \n", " hfotherby9@godaddy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 143.117.248.106\n", " \n", "
\n", "
\n", "
\n", " \n", " 11\n", " \n", "
\n", " 		\n", "
\n", " \n", " Janaye\n", " \n", "
\n", " 		\n", "
\n", " \n", " Farlam\n", " \n", "
\n", " 		\n", "
\n", " \n", " jfarlama@goo.gl\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 207.25.248.64\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.table_to_df(\"test_data\").ext.display()" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SELECT * FROM test_data WHERE test_data.id >= 1.0 AND test_data.id < 10.9\n", "SELECT * FROM test_data WHERE test_data.id >= 10.9 AND test_data.id < 20.8\n", "SELECT * FROM test_data WHERE test_data.id >= 20.8 AND test_data.id < 30.700000000000003\n", "SELECT * FROM test_data WHERE test_data.id >= 30.700000000000003 AND test_data.id < 40.6\n", "SELECT * FROM test_data WHERE test_data.id >= 40.6 AND test_data.id < 50.5\n", "SELECT * FROM test_data WHERE test_data.id >= 50.5 AND test_data.id < 60.400000000000006\n", "SELECT * FROM test_data WHERE test_data.id >= 60.400000000000006 AND test_data.id < 70.3\n", "SELECT * FROM test_data WHERE test_data.id >= 70.3 AND test_data.id < 80.2\n", "SELECT * FROM test_data WHERE test_data.id >= 80.2 AND test_data.id < 90.10000000000001\n", "SELECT * FROM test_data WHERE test_data.id > 90.10000000000001 AND test_data.id <= 100.0\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
10 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
first_name
\n", "
1 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
last_name
\n", "
2 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
email
\n", "
3 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
gender
\n", "
4 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
ip_address
\n", "
5 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
\n", "
\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
\n", " 		\n", "
\n", " \n", " eedden1@nytimes.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.205.155.142\n", " \n", "
\n", "
\n", "
\n", " \n", " Rudyard\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 84.170.67.167\n", " \n", "
\n", "
\n", "
\n", " \n", " Eugen\n", " \n", "
\n", " 		\n", "
\n", " \n", " Staining\n", " \n", "
\n", " 		\n", "
\n", " \n", " estaining3@merriam-webster.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 211.36.45.228\n", " \n", "
\n", "
\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " Banky\n", " \n", "
\n", " 		\n", "
\n", " \n", " Shires\n", " \n", "
\n", " 		\n", "
\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.18.210.158\n", " \n", "
\n", "
\n", "
\n", " \n", " Chastity\n", " \n", "
\n", " 		\n", "
\n", " \n", " Birtwell\n", " \n", "
\n", " 		\n", "
\n", " \n", " cbirtwell8@seesaa.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 167.15.222.219\n", " \n", "
\n", "
\n", "
\n", " \n", " Harv\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fotherby\n", " \n", "
\n", " 		\n", "
\n", " \n", " hfotherby9@godaddy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 143.117.248.106\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
10 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.execute(query=\"SELECT * FROM test_data\", partition_column= \"id\", table_name = \"test_data\").ext.display()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
9 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
id
\n", "
1 (int64)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
first_name
\n", "
2 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
last_name
\n", "
3 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
email
\n", "
4 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
gender
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5 (object)
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\n", " \n", " not nullable\n", " \n", "
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ip_address
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6 (object)
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\n", " \n", " not nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
\n", " 		\n", "
\n", " \n", " eedden1@nytimes.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.205.155.142\n", " \n", "
\n", "
\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rudyard\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 84.170.67.167\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " Eugen\n", " \n", "
\n", " 		\n", "
\n", " \n", " Staining\n", " \n", "
\n", " 		\n", "
\n", " \n", " estaining3@merriam-webster.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 211.36.45.228\n", " \n", "
\n", "
\n", "
\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " Banky\n", " \n", "
\n", " 		\n", "
\n", " \n", " Shires\n", " \n", "
\n", " 		\n", "
\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.18.210.158\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Chastity\n", " \n", "
\n", " 		\n", "
\n", " \n", " Birtwell\n", " \n", "
\n", " 		\n", "
\n", " \n", " cbirtwell8@seesaa.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 167.15.222.219\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " Harv\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fotherby\n", " \n", "
\n", " 		\n", "
\n", " \n", " hfotherby9@godaddy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 143.117.248.106\n", " \n", "
\n", "
\n", "
\n", " \n", " 11\n", " \n", "
\n", " 		\n", "
\n", " \n", " Janaye\n", " \n", "
\n", " 		\n", "
\n", " \n", " Farlam\n", " \n", "
\n", " 		\n", "
\n", " \n", " jfarlama@goo.gl\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 207.25.248.64\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
9 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.execute(query=\"SELECT * FROM test_data\", table_name = \"test_data\", num_partitions = 9).ext.display()" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['id', 'first_name', 'last_name', 'email', 'gender', 'ip_address']\n" ] }, { "data": { "text/html": [ "
Dask DataFrame Structure:
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idfirst_namelast_nameemailgenderip_address
npartitions=10
0.0int64objectobjectobjectobjectobject
1.0..................
.....................
9.0..................
10.0..................
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Dask Name: from-delayed, 20 tasks
" ], "text/plain": [ "Dask DataFrame Structure:\n", " id first_name last_name email gender ip_address\n", "npartitions=10 \n", "0.0 int64 object object object object object\n", "1.0 ... ... ... ... ... ...\n", "... ... ... ... ... ... ...\n", "9.0 ... ... ... ... ... ...\n", "10.0 ... ... ... ... ... ...\n", "Dask Name: from-delayed, 20 tasks" ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.execute(query=\"SELECT * FROM test_data\")" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "a = \"\"\"SELECT *, NTILE (4) OVER (ORDER BY id) id FROM test_data;\"\"\"" ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['id', 'first_name', 'last_name', 'email', 'gender', 'ip_address']\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 90 rows / 90 columns
\n", "
10 partition(s)
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\n", " \n", " 199.115.204.136\n", " \n", "
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\n", " \n", " 102.243.230.248\n", " \n", "
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\n", " \n", " 12.100.76.50\n", " \n", "
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\n", " \n", " 224.124.122.55\n", " \n", "
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\n", " 		\n", "
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\n", " \n", " 73\n", " \n", "
\n", " 		\n", "
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\n", " \n", " jdarrigo20@home.pl\n", " \n", "
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\n", " \n", " Boij\n", " \n", "
\n", " 		\n", "
\n", " \n", " bboij1z@oracle.com\n", " \n", "
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\n", " \n", " Moses\n", " \n", "
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\n", " \n", " mstanding1y@skyrock.com\n", " \n", "
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\n", " \n", " 70\n", " \n", "
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\n", " \n", " pmccully1x@discuz.net\n", " \n", "
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\n", " 		\n", "
\n", " \n", " jpaulsen1w@indiatimes.com\n", " \n", "
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\n", " \n", " bbotler1v@kickstarter.com\n", " \n", "
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\n", " \n", " rnormanell1u@ted.com\n", " \n", "
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\n", " \n", " tfrarey1s@multiply.com\n", " \n", "
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\n", " \n", " lpetrie1r@mtv.com\n", " \n", "
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\n", " \n", " fwonter1q@geocities.com\n", " \n", "
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\n", " 		\n", "
\n", " \n", " jcareless1n@cloudflare.com\n", " \n", "
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\n", " \n", " clade1i@bandcamp.com\n", " \n", "
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\n", " \n", " itompkiss1h@webmd.com\n", " \n", "
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\n", " \n", " tmertsching1d@hud.gov\n", " \n", "
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\n", " \n", " lazam1c@moonfruit.com\n", " \n", "
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\n", " \n", " danthoin1b@accuweather.com\n", " \n", "
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\n", " \n", " ihalmkin1a@aboutads.info\n", " \n", "
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\n", " \n", " adobby19@t-online.de\n", " \n", "
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\n", " \n", " swivell18@eepurl.com\n", " \n", "
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\n", " \n", " tpottie15@merriam-webster.com\n", " \n", "
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\n", " \n", " cdelmonti14@phpbb.com\n", " \n", "
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\n", " \n", " jgalbreth13@statcounter.com\n", " \n", "
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\n", " \n", " cburtwell12@unicef.org\n", " \n", "
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\n", " \n", " athirwell11@amazon.co.uk\n", " \n", "
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\n", " \n", " laspole10@people.com.cn\n", " \n", "
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\n", " \n", " Gordon\n", " \n", "
\n", " 		\n", "
\n", " \n", " mgordonx@lycos.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 243.94.253.221\n", " \n", "
\n", "
\n", "
\n", " \n", " 33\n", " \n", "
\n", " 		\n", "
\n", " \n", " Pall\n", " \n", "
\n", " 		\n", "
\n", " \n", " Sawrey\n", " \n", "
\n", " 		\n", "
\n", " \n", " psawreyw@facebook.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 209.246.100.200\n", " \n", "
\n", "
\n", "
\n", " \n", " 32\n", " \n", "
\n", " 		\n", "
\n", " \n", " Jorge\n", " \n", "
\n", " 		\n", "
\n", " \n", " Racher\n", " \n", "
\n", " 		\n", "
\n", " \n", " jracherv@google.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 233.56.214.255\n", " \n", "
\n", "
\n", "
\n", " \n", " 31\n", " \n", "
\n", " 		\n", "
\n", " \n", " Davide\n", " \n", "
\n", " 		\n", "
\n", " \n", " Scourfield\n", " \n", "
\n", " 		\n", "
\n", " \n", " dscourfieldu@rediff.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 113.239.62.4\n", " \n", "
\n", "
\n", "
\n", " \n", " 30\n", " \n", "
\n", " 		\n", "
\n", " \n", " Sarge\n", " \n", "
\n", " 		\n", "
\n", " \n", " Haresign\n", " \n", "
\n", " 		\n", "
\n", " \n", " sharesignt@miitbeian.gov.cn\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 212.180.157.241\n", " \n", "
\n", "
\n", "
\n", " \n", " 29\n", " \n", "
\n", " 		\n", "
\n", " \n", " Somerset\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hawksby\n", " \n", "
\n", " 		\n", "
\n", " \n", " shawksbys@accuweather.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 209.158.180.144\n", " \n", "
\n", "
\n", "
\n", " \n", " 28\n", " \n", "
\n", " 		\n", "
\n", " \n", " Tad\n", " \n", "
\n", " 		\n", "
\n", " \n", " Domange\n", " \n", "
\n", " 		\n", "
\n", " \n", " tdomanger@wikimedia.org\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 49.219.69.114\n", " \n", "
\n", "
\n", "
\n", " \n", " 27\n", " \n", "
\n", " 		\n", "
\n", " \n", " Benedicto\n", " \n", "
\n", " 		\n", "
\n", " \n", " Holtham\n", " \n", "
\n", " 		\n", "
\n", " \n", " bholthamq@constantcontact.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 235.57.49.45\n", " \n", "
\n", "
\n", "
\n", " \n", " 26\n", " \n", "
\n", " 		\n", "
\n", " \n", " Leah\n", " \n", "
\n", " 		\n", "
\n", " \n", " Jopling\n", " \n", "
\n", " 		\n", "
\n", " \n", " ljoplingp@topsy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 39.158.211.20\n", " \n", "
\n", "
\n", "
\n", " \n", " 25\n", " \n", "
\n", " 		\n", "
\n", " \n", " Benita\n", " \n", "
\n", " 		\n", "
\n", " \n", " Zarfati\n", " \n", "
\n", " 		\n", "
\n", " \n", " bzarfatio@oakley.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 130.115.169.187\n", " \n", "
\n", "
\n", "
\n", " \n", " 24\n", " \n", "
\n", " 		\n", "
\n", " \n", " Julita\n", " \n", "
\n", " 		\n", "
\n", " \n", " Conradie\n", " \n", "
\n", " 		\n", "
\n", " \n", " jconradien@tamu.edu\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 179.65.95.37\n", " \n", "
\n", "
\n", "
\n", " \n", " 23\n", " \n", "
\n", " 		\n", "
\n", " \n", " Syman\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dumbellow\n", " \n", "
\n", " 		\n", "
\n", " \n", " sdumbellowm@bbc.co.uk\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 206.25.6.205\n", " \n", "
\n", "
\n", "
\n", " \n", " 22\n", " \n", "
\n", " 		\n", "
\n", " \n", " Chalmers\n", " \n", "
\n", " 		\n", "
\n", " \n", " Palister\n", " \n", "
\n", " 		\n", "
\n", " \n", " cpalisterl@ibm.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 0.5.174.160\n", " \n", "
\n", "
\n", "
\n", " \n", " 21\n", " \n", "
\n", " 		\n", "
\n", " \n", " Saw\n", " \n", "
\n", " 		\n", "
\n", " \n", " Habard\n", " \n", "
\n", " 		\n", "
\n", " \n", " shabardk@reuters.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 107.111.35.73\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " Harv\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fotherby\n", " \n", "
\n", " 		\n", "
\n", " \n", " hfotherby9@godaddy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 143.117.248.106\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Chastity\n", " \n", "
\n", " 		\n", "
\n", " \n", " Birtwell\n", " \n", "
\n", " 		\n", "
\n", " \n", " cbirtwell8@seesaa.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 167.15.222.219\n", " \n", "
\n", "
\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " Banky\n", " \n", "
\n", " 		\n", "
\n", " \n", " Shires\n", " \n", "
\n", " 		\n", "
\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.18.210.158\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " Eugen\n", " \n", "
\n", " 		\n", "
\n", " \n", " Staining\n", " \n", "
\n", " 		\n", "
\n", " \n", " estaining3@merriam-webster.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 211.36.45.228\n", " \n", "
\n", "
\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rudyard\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 84.170.67.167\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
\n", " 		\n", "
\n", " \n", " eedden1@nytimes.com\n", " \n", "
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\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.205.155.142\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 90 rows / 90 columns
\n", "
10 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 23.7 s\n" ] } ], "source": [ "%%time\n", "db.execute(query=\"SELECT * FROM test_data\").ext.display()" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
10 partition(s)
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\n", "
id
\n", "
1 (int64)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
first_name
\n", "
2 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
last_name
\n", "
3 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
email
\n", "
4 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
gender
\n", "
5 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", " 		\n", "
ip_address
\n", "
6 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
\n", " 		\n", "
\n", " \n", " eedden1@nytimes.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.205.155.142\n", " \n", "
\n", "
\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rudyard\n", " \n", "
\n", " 		\n", "
\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 84.170.67.167\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " Eugen\n", " \n", "
\n", " 		\n", "
\n", " \n", " Staining\n", " \n", "
\n", " 		\n", "
\n", " \n", " estaining3@merriam-webster.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 211.36.45.228\n", " \n", "
\n", "
\n", "
\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
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\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
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\n", " 		\n", "
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\n", " \n", " tmaffiottic@sciencedirect.com\n", " \n", "
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\n", " 		\n", "
\n", " \n", " bsakinsj@topsy.com\n", " \n", "
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\n", " \n", " 117.231.82.148\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 100 rows / 100 columns
\n", "
10 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "a.ext.table()" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "df = db.table_to_df(\"test_data\", limit=None)" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['test_data']" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.tables_names_to_json()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Postgres" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "ename": "AttributeError", "evalue": "'PostgreSQLDriver' object has no attribute 'uri'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mdatabase\u001b[0m\u001b[1;33m=\u001b[0m \u001b[1;34m\"optimus\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[0muser\u001b[0m\u001b[1;33m=\u001b[0m \u001b[1;34m\"testuser\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m password = \"test\")\n\u001b[0m", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\engines\\dask.py\u001b[0m in \u001b[0;36mconnect\u001b[1;34m(driver, host, database, user, password, port, schema, oracle_tns, oracle_service_name, oracle_sid, presto_catalog, cassandra_keyspace, cassandra_table)\u001b[0m\n\u001b[0;32m 34\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 35\u001b[0m return JDBC(host, database, user, password, port, driver, schema, oracle_tns, oracle_service_name, oracle_sid,\n\u001b[1;32m---> 36\u001b[1;33m presto_catalog, cassandra_keyspace, cassandra_table)\n\u001b[0m\u001b[0;32m 37\u001b[0m \u001b[1;31m# def create(self, data):\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 38\u001b[0m \u001b[1;31m# import dask.dataframe as dd\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\dask\\io\\jdbc.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, host, database, user, password, port, driver, schema, oracle_tns, oracle_service_name, oracle_sid, presto_catalog, cassandra_keyspace, cassandra_table)\u001b[0m\n\u001b[0;32m 58\u001b[0m \u001b[0moracle_sid\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moracle_sid\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[0moracle_service_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moracle_service_name\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 60\u001b[1;33m \u001b[0mpresto_catalog\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpresto_catalog\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 61\u001b[0m )\n\u001b[0;32m 62\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdatabase\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdatabase\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\spark\\io\\driver_context.py\u001b[0m in \u001b[0;36muri\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 22\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 23\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0muri\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 24\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_driver\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0muri\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 25\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 26\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mAttributeError\u001b[0m: 'PostgreSQLDriver' object has no attribute 'uri'" ] } ], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"postgresql\",\n", " host=\"165.227.196.70\", \n", " database= \"optimus\", \n", " user= \"testuser\", \n", " password = \"test\")" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(\n", " SELECT relname as table_name,cast (reltuples as integer) AS count \n", " FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) \n", " WHERE nspname IN ('public') AND relkind='r' ORDER BY reltuples DESC) AS t\n", "INFO:optimus:jdbc:postgresql://165.227.196.70:5432/optimus?currentSchema=public\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 1 of 1 rows / 2 columns
\n", "
1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
table_name
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1 (string)
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count
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2 (int)
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\n", " \n", " 1100\n", " \n", "
\n", "
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Viewing 1 of 1 rows / 2 columns
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1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:SELECT * FROM test_data\n", "INFO:optimus:(SELECT * FROM test_data) AS t\n", "INFO:optimus:jdbc:postgresql://165.227.196.70:5432/optimus?currentSchema=public\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 10 rows / 6 columns
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1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
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id
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1 (int)
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first_name
\n", "
2 (string)
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last_name
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3 (string)
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email
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4 (string)
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gender
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5 (string)
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ip_address
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ikey\n", " \n", "
\n", " 		\n", "
\n", " \n", " Crudginton\n", " \n", "
\n", " 		\n", "
\n", " \n", " icrudginton0@freewebs.com\n", " \n", "
\n", " 		\n", "
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\n", " 		\n", "
\n", " \n", " 72.210.21.255\n", " \n", "
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\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Erwin\n", " \n", "
\n", " 		\n", "
\n", " \n", " Edden\n", " \n", "
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\n", " \n", " eedden1@nytimes.com\n", " \n", "
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\n", " \n", " 16.205.155.142\n", " \n", "
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\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
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\n", " \n", " Dullaghan\n", " \n", "
\n", " 		\n", "
\n", " \n", " rdullaghan2@techcrunch.com\n", " \n", "
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\n", " \n", " Staining\n", " \n", "
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\n", " 		\n", "
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\n", " \n", " 211.36.45.228\n", " \n", "
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\n", " 		\n", "
\n", " \n", " Carleton\n", " \n", "
\n", " 		\n", "
\n", " \n", " Hammond\n", " \n", "
\n", " 		\n", "
\n", " \n", " chammond4@example.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177.7.250.134\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Ermengarde\n", " \n", "
\n", " 		\n", "
\n", " \n", " Knightly\n", " \n", "
\n", " 		\n", "
\n", " \n", " eknightly5@google.co.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 231.176.117.190\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Myles\n", " \n", "
\n", " 		\n", "
\n", " \n", " Rattray\n", " \n", "
\n", " 		\n", "
\n", " \n", " mrattray6@about.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4.193.247.67\n", " \n", "
\n", "
\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " Banky\n", " \n", "
\n", " 		\n", "
\n", " \n", " Shires\n", " \n", "
\n", " 		\n", "
\n", " \n", " bshires7@so-net.ne.jp\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.18.210.158\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Chastity\n", " \n", "
\n", " 		\n", "
\n", " \n", " Birtwell\n", " \n", "
\n", " 		\n", "
\n", " \n", " cbirtwell8@seesaa.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 167.15.222.219\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " Harv\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fotherby\n", " \n", "
\n", " 		\n", "
\n", " \n", " hfotherby9@godaddy.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 143.117.248.106\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 10 rows / 6 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.table_to_df(\"test_data\").table()" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(\n", " SELECT relname as table_name \n", " FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) \n", " WHERE nspname IN ('public') AND relkind='r' ORDER BY reltuples DESC) AS t\n", "INFO:optimus:jdbc:postgresql://165.227.196.70:5432/optimus?currentSchema=public\n" ] }, { "data": { "text/plain": [ "['test_data']" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.tables_names_to_json()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MSSQL" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:jdbc:sqlserver://165.227.196.70:1433;databaseName=optimus\n" ] } ], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"sqlserver\",\n", " host=\"165.227.196.70\", \n", " database= \"optimus\", \n", " user= \"test\", \n", " password = \"test*0261\")" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(SELECT * FROM INFORMATION_SCHEMA.TABLES) AS t\n", "INFO:optimus:jdbc:sqlserver://165.227.196.70:1433;databaseName=optimus\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 1 of 1 rows / 4 columns
\n", "
1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
TABLE_CATALOG
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
TABLE_SCHEMA
\n", "
2 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
TABLE_NAME
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
TABLE_TYPE
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " optimus\n", " \n", "
\n", " 		\n", "
\n", " \n", " dbo\n", " \n", "
\n", " 		\n", "
\n", " \n", " test_data\n", " \n", "
\n", " 		\n", "
\n", " \n", " BASE⋅TABLE\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 1 of 1 rows / 4 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:SELECT * FROM test_data\n", "INFO:optimus:(SELECT * FROM test_data) AS t\n", "INFO:optimus:jdbc:sqlserver://165.227.196.70:1433;databaseName=optimus\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 10 rows / 6 columns
\n", "
1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
id
\n", "
1 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
first_name
\n", "
2 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
last_name
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
email
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
gender
\n", "
5 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
ip_address
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Keenan\n", " \n", "
\n", " 		\n", "
\n", " \n", " McAirt\n", " \n", "
\n", " 		\n", "
\n", " \n", " kmcairt0@spotify.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 68.97.227.147\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fredelia\n", " \n", "
\n", " 		\n", "
\n", " \n", " Lemarie\n", " \n", "
\n", " 		\n", "
\n", " \n", " flemarie1@furl.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.145.123.46\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Keenan\n", " \n", "
\n", " 		\n", "
\n", " \n", " McAirt\n", " \n", "
\n", " 		\n", "
\n", " \n", " kmcairt0@spotify.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 68.97.227.147\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fredelia\n", " \n", "
\n", " 		\n", "
\n", " \n", " Lemarie\n", " \n", "
\n", " 		\n", "
\n", " \n", " flemarie1@furl.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.145.123.46\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Keenan\n", " \n", "
\n", " 		\n", "
\n", " \n", " McAirt\n", " \n", "
\n", " 		\n", "
\n", " \n", " kmcairt0@spotify.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 68.97.227.147\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fredelia\n", " \n", "
\n", " 		\n", "
\n", " \n", " Lemarie\n", " \n", "
\n", " 		\n", "
\n", " \n", " flemarie1@furl.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.145.123.46\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Keenan\n", " \n", "
\n", " 		\n", "
\n", " \n", " McAirt\n", " \n", "
\n", " 		\n", "
\n", " \n", " kmcairt0@spotify.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 68.97.227.147\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fredelia\n", " \n", "
\n", " 		\n", "
\n", " \n", " Lemarie\n", " \n", "
\n", " 		\n", "
\n", " \n", " flemarie1@furl.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.145.123.46\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Fredelia\n", " \n", "
\n", " 		\n", "
\n", " \n", " Lemarie\n", " \n", "
\n", " 		\n", "
\n", " \n", " flemarie1@furl.net\n", " \n", "
\n", " 		\n", "
\n", " \n", " Female\n", " \n", "
\n", " 		\n", "
\n", " \n", " 16.145.123.46\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " Evyn\n", " \n", "
\n", " 		\n", "
\n", " \n", " Abbey\n", " \n", "
\n", " 		\n", "
\n", " \n", " eabbey0@mlb.com\n", " \n", "
\n", " 		\n", "
\n", " \n", " Male\n", " \n", "
\n", " 		\n", "
\n", " \n", " 202.99.246.227\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 10 rows / 6 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.table_to_df(\"test_data\").table()" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(SELECT TABLE_NAME FROM INFORMATION_SCHEMA.TABLES) AS t\n", "INFO:optimus:jdbc:sqlserver://165.227.196.70:1433;databaseName=optimus\n" ] }, { "data": { "text/plain": [ "['test_data']" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.tables_names_to_json()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Redshit" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:jdbc:redshift://redshift-cluster-1.chuvgsqx7epn.us-east-1.redshift.amazonaws.com:5439/dev?currentSchema=public\n" ] } ], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"redshift\",\n", " host=\"165.227.196.70\", \n", " database= \"optimus\", \n", " user= \"testuser\", \n", " password = \"test\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(\n", " SELECT relname as table_name,cast (reltuples as integer) AS count \n", " FROM pg_class C LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace) \n", " WHERE nspname IN ('public') AND relkind='r' ORDER BY reltuples DESC) AS t\n", "INFO:optimus:jdbc:redshift://redshift-cluster-1.chuvgsqx7epn.us-east-1.redshift.amazonaws.com:5439/dev?currentSchema=public\n" ] }, { "ename": "Py4JJavaError", "evalue": "An error occurred while calling o41.load.\n: java.sql.SQLException: [Amazon](500150) Error setting/closing connection: Connection timed out: connect.\r\n\tat com.amazon.redshift.client.PGClient.connect(Unknown Source)\r\n\tat com.amazon.redshift.client.PGClient.(Unknown Source)\r\n\tat com.amazon.redshift.core.PGJDBCConnection.connect(Unknown Source)\r\n\tat com.amazon.jdbc.common.BaseConnectionFactory.doConnect(Unknown Source)\r\n\tat com.amazon.jdbc.common.AbstractDriver.connect(Unknown Source)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:56)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.(JDBCRelation.scala:115)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:52)\r\n\tat org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:340)\r\n\tat org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\nCaused by: com.amazon.support.exceptions.GeneralException: [Amazon](500150) Error setting/closing connection: Connection timed out: connect.\r\n\t... 24 more\r\nCaused by: java.net.ConnectException: Connection timed out: connect\r\n\tat sun.nio.ch.Net.connect0(Native Method)\r\n\tat sun.nio.ch.Net.connect(Net.java:454)\r\n\tat sun.nio.ch.Net.connect(Net.java:446)\r\n\tat sun.nio.ch.SocketChannelImpl.connect(SocketChannelImpl.java:648)\r\n\tat sun.nio.ch.SocketAdaptor.connect(SocketAdaptor.java:96)\r\n\tat com.amazon.redshift.client.PGClient.connect(Unknown Source)\r\n\tat com.amazon.redshift.client.PGClient.(Unknown Source)\r\n\tat com.amazon.redshift.core.PGJDBCConnection.connect(Unknown Source)\r\n\tat com.amazon.jdbc.common.BaseConnectionFactory.doConnect(Unknown Source)\r\n\tat com.amazon.jdbc.common.AbstractDriver.connect(Unknown Source)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:56)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.(JDBCRelation.scala:115)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:52)\r\n\tat org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:340)\r\n\tat org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\n\tat java.lang.Thread.run(Thread.java:748)\r\n", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mPy4JJavaError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\io\\jdbc.py\u001b[0m in \u001b[0;36mtables\u001b[1;34m(self, schema, database, limit)\u001b[0m\n\u001b[0;32m 179\u001b[0m FROM user_tables ORDER BY table_name\"\"\"\n\u001b[0;32m 180\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 181\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 182\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlimit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 183\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\io\\jdbc.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, query, limit)\u001b[0m\n\u001b[0;32m 309\u001b[0m \u001b[0mconf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtable\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcassandra_table\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeyspace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcassandra_keyspace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 310\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 311\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_limit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 312\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 313\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdf_to_table\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"overwrite\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pyspark\\sql\\readwriter.py\u001b[0m in \u001b[0;36mload\u001b[1;34m(self, path, format, schema, **options)\u001b[0m\n\u001b[0;32m 170\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_df\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jreader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_spark\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPythonUtils\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtoSeq\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 171\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 172\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_df\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jreader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 173\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 174\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0msince\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1.4\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\py4j\\java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m 1255\u001b[0m \u001b[0manswer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgateway_client\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend_command\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1256\u001b[0m return_value = get_return_value(\n\u001b[1;32m-> 1257\u001b[1;33m answer, self.gateway_client, self.target_id, self.name)\n\u001b[0m\u001b[0;32m 1258\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1259\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mtemp_arg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtemp_args\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pyspark\\sql\\utils.py\u001b[0m in \u001b[0;36mdeco\u001b[1;34m(*a, **kw)\u001b[0m\n\u001b[0;32m 61\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdeco\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 62\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 63\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 64\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mpy4j\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPy4JJavaError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 65\u001b[0m \u001b[0ms\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjava_exception\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtoString\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\py4j\\protocol.py\u001b[0m in \u001b[0;36mget_return_value\u001b[1;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[0;32m 326\u001b[0m raise Py4JJavaError(\n\u001b[0;32m 327\u001b[0m \u001b[1;34m\"An error occurred while calling {0}{1}{2}.\\n\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 328\u001b[1;33m format(target_id, \".\", name), value)\n\u001b[0m\u001b[0;32m 329\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 330\u001b[0m raise Py4JError(\n", "\u001b[1;31mPy4JJavaError\u001b[0m: An error occurred while calling o41.load.\n: java.sql.SQLException: [Amazon](500150) Error setting/closing connection: Connection timed out: connect.\r\n\tat com.amazon.redshift.client.PGClient.connect(Unknown Source)\r\n\tat com.amazon.redshift.client.PGClient.(Unknown Source)\r\n\tat com.amazon.redshift.core.PGJDBCConnection.connect(Unknown Source)\r\n\tat com.amazon.jdbc.common.BaseConnectionFactory.doConnect(Unknown Source)\r\n\tat com.amazon.jdbc.common.AbstractDriver.connect(Unknown Source)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:56)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.(JDBCRelation.scala:115)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:52)\r\n\tat org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:340)\r\n\tat org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\nCaused by: com.amazon.support.exceptions.GeneralException: [Amazon](500150) Error setting/closing connection: Connection timed out: connect.\r\n\t... 24 more\r\nCaused by: java.net.ConnectException: Connection timed out: connect\r\n\tat sun.nio.ch.Net.connect0(Native Method)\r\n\tat sun.nio.ch.Net.connect(Net.java:454)\r\n\tat sun.nio.ch.Net.connect(Net.java:446)\r\n\tat sun.nio.ch.SocketChannelImpl.connect(SocketChannelImpl.java:648)\r\n\tat sun.nio.ch.SocketAdaptor.connect(SocketAdaptor.java:96)\r\n\tat com.amazon.redshift.client.PGClient.connect(Unknown Source)\r\n\tat com.amazon.redshift.client.PGClient.(Unknown Source)\r\n\tat com.amazon.redshift.core.PGJDBCConnection.connect(Unknown Source)\r\n\tat com.amazon.jdbc.common.BaseConnectionFactory.doConnect(Unknown Source)\r\n\tat com.amazon.jdbc.common.AbstractDriver.connect(Unknown Source)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:63)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:54)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:56)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.(JDBCRelation.scala:115)\r\n\tat org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:52)\r\n\tat org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:340)\r\n\tat org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)\r\n\tat org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\r\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\r\n\tat py4j.Gateway.invoke(Gateway.java:282)\r\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\r\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\r\n\tat py4j.GatewayConnection.run(GatewayConnection.java:238)\r\n\tat java.lang.Thread.run(Thread.java:748)\r\n" ] } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "db.table_to_df(\"test_data\").table()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Oracle" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"oracle\",\n", " host=\"165.227.196.70\", \n", " database= \"optimus\", \n", " user= \"testuser\", \n", " password = \"test\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## SQLlite" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:jdbc:sqlite:chinook.db\n" ] } ], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"sqlite\",\n", " host=\"chinook.db\", \n", " database= \"employes\", \n", " user= \"testuser\", \n", " password = \"test\")" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(SELECT name FROM sqlite_master WHERE type='table') AS t\n", "INFO:optimus:jdbc:sqlite:chinook.db\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
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Viewing 10 of 10 rows / 1 columns
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1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(SELECT COUNT(*) as COUNT FROM albums) AS t\n", "INFO:optimus:jdbc:sqlite:chinook.db\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "347 rows\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:SELECT * FROM albums\n", "INFO:optimus:(SELECT * FROM albums) AS t\n", "INFO:optimus:jdbc:sqlite:chinook.db\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 347 rows / 3 columns
\n", "
1 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
AlbumId
\n", "
1 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
Title
\n", "
2 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
ArtistId
\n", "
3 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
\n", " 		\n", "
\n", " \n", " For⋅Those⋅About⋅To⋅Rock⋅We⋅Salute⋅You\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1\n", " \n", "
\n", "
\n", "
\n", " \n", " 2\n", " \n", "
\n", " 		\n", "
\n", " \n", " Balls⋅to⋅the⋅Wall\n", " \n", "
\n", " 		\n", "
\n", " \n", " 2\n", " \n", "
\n", "
\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " Restless⋅and⋅Wild\n", " \n", "
\n", " 		\n", "
\n", " \n", " 2\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " Let⋅There⋅Be⋅Rock\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1\n", " \n", "
\n", "
\n", "
\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Big⋅Ones\n", " \n", "
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\n", " \n", " 3\n", " \n", "
\n", "
\n", "
\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Jagged⋅Little⋅Pill\n", " \n", "
\n", " 		\n", "
\n", " \n", " 4\n", " \n", "
\n", "
\n", "
\n", " \n", " 7\n", " \n", "
\n", " 		\n", "
\n", " \n", " Facelift\n", " \n", "
\n", " 		\n", "
\n", " \n", " 5\n", " \n", "
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\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " Warner⋅25⋅Anos\n", " \n", "
\n", " 		\n", "
\n", " \n", " 6\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Plays⋅Metallica⋅By⋅Four⋅Cellos\n", " \n", "
\n", " 		\n", "
\n", " \n", " 7\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " Audioslave\n", " \n", "
\n", " 		\n", "
\n", " \n", " 8\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 347 rows / 3 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "db.table_to_df(\"albums\",limit=\"all\").table()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:(SELECT name FROM sqlite_master WHERE type='table') AS t\n", "INFO:optimus:jdbc:sqlite:chinook.db\n" ] }, { "data": { "text/plain": [ "['albums',\n", " 'sqlite_sequence',\n", " 'artists',\n", " 'customers',\n", " 'employees',\n", " 'genres',\n", " 'invoices',\n", " 'invoice_items',\n", " 'media_types',\n", " 'playlists',\n", " 'playlist_track',\n", " 'tracks',\n", " 'sqlite_stat1']" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db.tables_names_to_json()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Redis" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:Downloading foo.csv from https://raw.githubusercontent.com/ironmussa/Optimus/master/examples/data/foo.csv\n", "INFO:optimus:Downloaded 967 bytes\n", "INFO:optimus:Creating DataFrame for foo.csv. Please wait...\n" ] } ], "source": [ "df = op.load.csv(\"https://raw.githubusercontent.com/ironmussa/Optimus/master/examples/data/foo.csv\", sep=\",\", header='true', infer_schema='true', charset=\"UTF-8\", null_value=\"None\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 19 rows / 8 columns
\n", "
1 partition(s)
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\n", "
id
\n", "
1 (int)
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\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
firstName
\n", "
2 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
lastName
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
billingId
\n", "
4 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
product
\n", "
5 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
price
\n", "
6 (int)
\n", "
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\n", " 		\n", "
birth
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
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dummyCol
\n", "
8 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
\n", " \n", " 1\n", " \n", "
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\n", " \n", " Luis\n", " \n", "
\n", " 		\n", "
\n", " \n", " Alvarez$$%!\n", " \n", "
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\n", " \n", " 1950/07/08\n", " \n", "
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\n", " \n", " gonna\n", " \n", "
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\n", " \n", " 3\n", " \n", "
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\n", " \n", " NiELS\n", " \n", "
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\n", " \n", " Böhr//((%%\n", " \n", "
\n", " 		\n", "
\n", " \n", " 551\n", " \n", "
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\n", " \n", " pizza\n", " \n", "
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\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1990/07/09\n", " \n", "
\n", " 		\n", "
\n", " \n", " give\n", " \n", "
\n", "
\n", "
\n", " \n", " 4\n", " \n", "
\n", " 		\n", "
\n", " \n", " PAUL\n", " \n", "
\n", " 		\n", "
\n", " \n", " dirac$\n", " \n", "
\n", " 		\n", "
\n", " \n", " 521\n", " \n", "
\n", " 		\n", "
\n", " \n", " pizza\n", " \n", "
\n", " 		\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1954/07/10\n", " \n", "
\n", " 		\n", "
\n", " \n", " you\n", " \n", "
\n", "
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\n", " \n", " 5\n", " \n", "
\n", " 		\n", "
\n", " \n", " Albert\n", " \n", "
\n", " 		\n", "
\n", " \n", " Einstein\n", " \n", "
\n", " 		\n", "
\n", " \n", " 634\n", " \n", "
\n", " 		\n", "
\n", " \n", " pizza\n", " \n", "
\n", " 		\n", "
\n", " \n", " 8\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1990/07/11\n", " \n", "
\n", " 		\n", "
\n", " \n", " up\n", " \n", "
\n", "
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\n", " \n", " 6\n", " \n", "
\n", " 		\n", "
\n", " \n", " Galileo\n", " \n", "
\n", " 		\n", "
\n", " \n", " ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅GALiLEI\n", " \n", "
\n", " 		\n", "
\n", " \n", " 672\n", " \n", "
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\n", " 		\n", "
\n", " \n", " 5\n", " \n", "
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\n", " 		\n", "
\n", " \n", " CaRL\n", " \n", "
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\n", " \n", " Ga%%%uss\n", " \n", "
\n", " 		\n", "
\n", " \n", " 323\n", " \n", "
\n", " 		\n", "
\n", " \n", " taco\n", " \n", "
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\n", " 		\n", "
\n", " \n", " 1970/07/13\n", " \n", "
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\n", " 		\n", "
\n", " \n", " David\n", " \n", "
\n", " 		\n", "
\n", " \n", " H$$$ilbert\n", " \n", "
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\n", " \n", " 624\n", " \n", "
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\n", " \n", " taaaccoo\n", " \n", "
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\n", " \n", " 3\n", " \n", "
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\n", " 		\n", "
\n", " \n", " let\n", " \n", "
\n", "
\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Johannes\n", " \n", "
\n", " 		\n", "
\n", " \n", " KEPLER\n", " \n", "
\n", " 		\n", "
\n", " \n", " 735\n", " \n", "
\n", " 		\n", "
\n", " \n", " taco\n", " \n", "
\n", " 		\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1920/04/22\n", " \n", "
\n", " 		\n", "
\n", " \n", " you\n", " \n", "
\n", "
\n", "
\n", " \n", " 10\n", " \n", "
\n", " 		\n", "
\n", " \n", " JaMES\n", " \n", "
\n", " 		\n", "
\n", " \n", " M$$ax%%well\n", " \n", "
\n", " 		\n", "
\n", " \n", " 875\n", " \n", "
\n", " 		\n", "
\n", " \n", " taco\n", " \n", "
\n", " 		\n", "
\n", " \n", " 3\n", " \n", "
\n", " 		\n", "
\n", " \n", " 1923/03/12\n", " \n", "
\n", " 		\n", "
\n", " \n", " down\n", " \n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 19 rows / 8 columns
\n", "
1 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df.table()" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "# Put your db credentials here\n", "db = op.connect(\n", " driver=\"redis\",\n", " host=\"165.227.196.70\", \n", " port = 6379,\n", " database= 1, \n", " password = \"\")" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:`id`,`firstName`,`lastName`,`billingId`,`product`,`price`,`birth`,`dummyCol` column(s) was not processed because is/are not array,vector\n", "INFO:optimus:Outputting 0 columns after filtering. Is this expected?\n", "INFO:optimus:Using 'column_exp' to process column 'id' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'firstName' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'lastName' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'billingId' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'product' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'price' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'birth' with function _cast_to\n", "INFO:optimus:Using 'column_exp' to process column 'dummyCol' with function _cast_to\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "hola1\n" ] } ], "source": [ "db.df_to_table(df, \"hola1\", redis_primary_key=\"id\")" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "can only concatenate str (not \"int\") to str", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m# https://stackoverflow.com/questions/56707978/how-to-write-from-a-pyspark-dstream-to-redis\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtable_to_df\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\io\\jdbc.py\u001b[0m in \u001b[0;36mtable_to_df\u001b[1;34m(self, table_name, columns, limit)\u001b[0m\n\u001b[0;32m 122\u001b[0m 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\u001b[1;32mreturn\u001b[0m \u001b[1;34m\"SELECT COUNT(*) as COUNT FROM \"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"db_table\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str" ] } ], "source": [ "# https://stackoverflow.com/questions/56707978/how-to-write-from-a-pyspark-dstream-to-redis\n", " \n", "db.table_to_df(0)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 2 }