From d4572cb42202bdda1cc446269c2a9ae8da6f7596 Mon Sep 17 00:00:00 2001
From: rahulkumar <rkumar@aerospike.com>
Date: Thu, 18 Jan 2024 16:12:35 -0800
Subject: [PATCH 1/2] Fix notebook for latest Trino connector release

---
 notebooks/presto/AerospikePrestoDemo.ipynb | 114 ++++++++++++++++-----
 1 file changed, 88 insertions(+), 26 deletions(-)

diff --git a/notebooks/presto/AerospikePrestoDemo.ipynb b/notebooks/presto/AerospikePrestoDemo.ipynb
index 38cf5a8..a92a830 100644
--- a/notebooks/presto/AerospikePrestoDemo.ipynb
+++ b/notebooks/presto/AerospikePrestoDemo.ipynb
@@ -5,70 +5,139 @@
    "metadata": {},
    "source": [
     "## Aerospike Connect for Presto Tutorial for Python\n",
-    "## Tested with Python 3.7, Java 11, Presto 343, Presto Connector (Beta), and PyHive 0.6.3"
+    "## Tested with Python 3.10.6, Java 17.0.5, Trino 435, Aerospike Trino Connector 4.5.0-431, and PyHive 0.18.3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip3 install pyhive\n",
+    "!pip3 install requests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
     "from pyhive import presto\n",
+    "import requests\n",
+    "from requests.auth import HTTPBasicAuth\n",
     "presto_conn = presto.connect(\n",
     "    host='localhost',\n",
     "    port=8080,\n",
+    "    username='admin',\n",
     "    catalog='aerospike',\n",
-    "    schema='test'\n",
+    "    schema='test',\n",
+    "     requests_kwargs={\n",
+    "        'auth': HTTPBasicAuth('admin', '')\n",
+    "    }\n",
     ")\n",
     "presto_cursor=presto_conn.cursor()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Following examples assumes that data was created using accompanying python notebook."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Print infered schema of table `write_set`"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('__key', 'varchar', '', '')\n",
+      "('name', 'varchar', '', '')\n",
+      "('id', 'bigint', '', '')\n",
+      "('salary', 'bigint', '', '')\n",
+      "('age', 'double', '', '')\n"
+     ]
+    }
+   ],
+   "source": [
+    "query = \"DESCRIBE aerospike.test.write_set\"\n",
+    "presto_cursor.execute(query)\n",
+    "\n",
+    "# Fetch all the results\n",
+    "descriptions = presto_cursor.fetchall()\n",
+    "\n",
+    "# Print the descriptions\n",
+    "for col in descriptions:\n",
+    "    print(col)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "presto_cursor.execute('SELECT * FROM test.write_set LIMIT 3')"
+    "### Print all records of the table `write_set`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(234, 'Individual: 234', 33.568431516802406, 66363)\n",
-      "(13, 'Individual: 013', 25.752921531369164, 48610)\n",
-      "(79, 'Individual: 079', 25.16109674428971, 60357)\n"
+      "(None, 'Individual: 237', 237, 61928, 35.40459945502513)\n",
+      "(None, 'Individual: 145', 145, 81405, 45.02808010201396)\n",
+      "(None, 'Individual: 022', 22, 43865, 26.69338780386945)\n"
      ]
     }
    ],
    "source": [
+    "presto_cursor.execute('SELECT * FROM aerospike.test.write_set LIMIT 3')\n",
     "records = presto_cursor.fetchall()\n",
     "for row in records:\n",
     "    print(row)"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "presto_cursor.execute('select name from test.write_set where age>40 and age<45')"
+    "### Extract records of the table `write_set` by applying filters on the column `age`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 76,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('Individual: 176',)\n",
+      "('Individual: 153',)\n",
+      "('Individual: 111',)\n",
+      "('Individual: 118',)\n",
+      "('Individual: 151',)\n"
+     ]
+    }
+   ],
    "source": [
+    "presto_cursor.execute('select name from aerospike.test.write_set where age>40 and age<45 limit 5')\n",
     "records1 = presto_cursor.fetchall()\n",
     "for row in records1:\n",
     "    print(row)"
@@ -78,20 +147,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Refer to https://www.aerospike.com/docs/connect/access/presto/examples.html for more examples."
+    "### Refer to https://aerospike.com/docs/connect/trino/examples for more examples."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -105,7 +167,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,

From 2dfd24dfc5c12fe54b3d51bfc23c72afb208ecbe Mon Sep 17 00:00:00 2001
From: rahulkumar <rkumar@aerospike.com>
Date: Mon, 22 Jan 2024 11:44:40 -0800
Subject: [PATCH 2/2] Removed Trino notebooks

---
 notebooks/presto/AerospikePrestoDemo.ipynb | 175 -----
 notebooks/presto/AerospikePython.ipynb     | 840 ---------------------
 2 files changed, 1015 deletions(-)
 delete mode 100644 notebooks/presto/AerospikePrestoDemo.ipynb
 delete mode 100644 notebooks/presto/AerospikePython.ipynb

diff --git a/notebooks/presto/AerospikePrestoDemo.ipynb b/notebooks/presto/AerospikePrestoDemo.ipynb
deleted file mode 100644
index a92a830..0000000
--- a/notebooks/presto/AerospikePrestoDemo.ipynb
+++ /dev/null
@@ -1,175 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Aerospike Connect for Presto Tutorial for Python\n",
-    "## Tested with Python 3.10.6, Java 17.0.5, Trino 435, Aerospike Trino Connector 4.5.0-431, and PyHive 0.18.3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!pip3 install pyhive\n",
-    "!pip3 install requests"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from pyhive import presto\n",
-    "import requests\n",
-    "from requests.auth import HTTPBasicAuth\n",
-    "presto_conn = presto.connect(\n",
-    "    host='localhost',\n",
-    "    port=8080,\n",
-    "    username='admin',\n",
-    "    catalog='aerospike',\n",
-    "    schema='test',\n",
-    "     requests_kwargs={\n",
-    "        'auth': HTTPBasicAuth('admin', '')\n",
-    "    }\n",
-    ")\n",
-    "presto_cursor=presto_conn.cursor()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Following examples assumes that data was created using accompanying python notebook."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Print infered schema of table `write_set`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "('__key', 'varchar', '', '')\n",
-      "('name', 'varchar', '', '')\n",
-      "('id', 'bigint', '', '')\n",
-      "('salary', 'bigint', '', '')\n",
-      "('age', 'double', '', '')\n"
-     ]
-    }
-   ],
-   "source": [
-    "query = \"DESCRIBE aerospike.test.write_set\"\n",
-    "presto_cursor.execute(query)\n",
-    "\n",
-    "# Fetch all the results\n",
-    "descriptions = presto_cursor.fetchall()\n",
-    "\n",
-    "# Print the descriptions\n",
-    "for col in descriptions:\n",
-    "    print(col)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Print all records of the table `write_set`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 72,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(None, 'Individual: 237', 237, 61928, 35.40459945502513)\n",
-      "(None, 'Individual: 145', 145, 81405, 45.02808010201396)\n",
-      "(None, 'Individual: 022', 22, 43865, 26.69338780386945)\n"
-     ]
-    }
-   ],
-   "source": [
-    "presto_cursor.execute('SELECT * FROM aerospike.test.write_set LIMIT 3')\n",
-    "records = presto_cursor.fetchall()\n",
-    "for row in records:\n",
-    "    print(row)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract records of the table `write_set` by applying filters on the column `age`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "('Individual: 176',)\n",
-      "('Individual: 153',)\n",
-      "('Individual: 111',)\n",
-      "('Individual: 118',)\n",
-      "('Individual: 151',)\n"
-     ]
-    }
-   ],
-   "source": [
-    "presto_cursor.execute('select name from aerospike.test.write_set where age>40 and age<45 limit 5')\n",
-    "records1 = presto_cursor.fetchall()\n",
-    "for row in records1:\n",
-    "    print(row)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Refer to https://aerospike.com/docs/connect/trino/examples for more examples."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.10.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/presto/AerospikePython.ipynb b/notebooks/presto/AerospikePython.ipynb
deleted file mode 100644
index 207b436..0000000
--- a/notebooks/presto/AerospikePython.ipynb
+++ /dev/null
@@ -1,840 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Aerospike Python Client Tutorial \n",
-    "### Refer to https://www.aerospike.com/docs/client/python/index.html for information on installing the Aerospike Python client.\n",
-    "#### Tested with Python 3.7\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# IP Address or DNS name for one host in your Aerospike cluster\n",
-    "AS_HOST =\"127.0.0.1\"\n",
-    "\n",
-    "# Please reach out to us if you do not have a feature key\n",
-    "AS_FEATURE_KEY_PATH = \"/etc/aerospike/features.conf\"\n",
-    "\n",
-    "AS_PORT = 3000 # Usually 3000, but change here if not"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import aerospike"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Create Sample Data and load it into Aerospike"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data created\n"
-     ]
-    }
-   ],
-   "source": [
-    "# We create age vs salary data, using three different Gaussian distributions\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import math\n",
-    "\n",
-    "# Create covariance matrix from std devs + correlation\n",
-    "def covariance_matrix(std_dev_1,std_dev_2,correlation):\n",
-    "    return [[std_dev_1 ** 2, correlation * std_dev_1 * std_dev_2], \n",
-    "           [correlation * std_dev_1 * std_dev_2, std_dev_2 ** 2]]\n",
-    "\n",
-    "# Return a bivariate sample given means/std dev/correlation\n",
-    "def age_salary_sample(distribution_params,sample_size):\n",
-    "    mean = [distribution_params[\"age_mean\"], distribution_params[\"salary_mean\"]]\n",
-    "    cov = covariance_matrix(distribution_params[\"age_std_dev\"],distribution_params[\"salary_std_dev\"],\n",
-    "                            distribution_params[\"age_salary_correlation\"])\n",
-    "    return np.random.multivariate_normal(mean, cov, sample_size).T\n",
-    "\n",
-    "# Define the characteristics of our age/salary distribution\n",
-    "age_salary_distribution_1 = {\"age_mean\":25,\"salary_mean\":50000,\n",
-    "                             \"age_std_dev\":1,\"salary_std_dev\":5000,\"age_salary_correlation\":0.3}\n",
-    "\n",
-    "age_salary_distribution_2 = {\"age_mean\":45,\"salary_mean\":80000,\n",
-    "                             \"age_std_dev\":4,\"salary_std_dev\":10000,\"age_salary_correlation\":0.7}\n",
-    "\n",
-    "age_salary_distribution_3 = {\"age_mean\":35,\"salary_mean\":70000,\n",
-    "                             \"age_std_dev\":2,\"salary_std_dev\":9000,\"age_salary_correlation\":0.1}\n",
-    "\n",
-    "distribution_data = [age_salary_distribution_1,age_salary_distribution_2,age_salary_distribution_3]\n",
-    "\n",
-    "# Sample age/salary data for each distributions\n",
-    "group_1_ages,group_1_salaries = age_salary_sample(age_salary_distribution_1,sample_size=100)\n",
-    "group_2_ages,group_2_salaries = age_salary_sample(age_salary_distribution_2,sample_size=120)\n",
-    "group_3_ages,group_3_salaries = age_salary_sample(age_salary_distribution_3,sample_size=80)\n",
-    "\n",
-    "ages=np.concatenate([group_1_ages,group_2_ages,group_3_ages])\n",
-    "salaries=np.concatenate([group_1_salaries,group_2_salaries,group_3_salaries])\n",
-    "\n",
-    "print(\"Data created\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(1, 'Individual: 001', 24.304499333848025, 46865)\n",
-      "(2, 'Individual: 002', 25.127370725646376, 58731)\n",
-      "(3, 'Individual: 003', 24.433587308486384, 39822)\n",
-      "(4, 'Individual: 004', 23.466317614770414, 46800)\n",
-      "(5, 'Individual: 005', 25.901554554617075, 44622)\n",
-      "(6, 'Individual: 006', 25.244089945979592, 48962)\n",
-      "(7, 'Individual: 007', 25.513546531713885, 54015)\n",
-      "(8, 'Individual: 008', 24.384542542073284, 48850)\n",
-      "(9, 'Individual: 009', 23.969228059245417, 49939)\n",
-      "(10, 'Individual: 010', 25.32659498864832, 52270)\n",
-      "(11, 'Individual: 011', 24.52188955913116, 56682)\n",
-      "(12, 'Individual: 012', 25.307831842818935, 48937)\n",
-      "(13, 'Individual: 013', 25.25646020804283, 54880)\n",
-      "(14, 'Individual: 014', 25.678511730398245, 50121)\n",
-      "(15, 'Individual: 015', 24.05942103892467, 60348)\n",
-      "(16, 'Individual: 016', 25.749046404565952, 53522)\n",
-      "(17, 'Individual: 017', 22.897339115317486, 41738)\n",
-      "(18, 'Individual: 018', 25.85659550137486, 51606)\n",
-      "(19, 'Individual: 019', 25.344785148917193, 47040)\n",
-      "(20, 'Individual: 020', 23.821932401631045, 51202)\n",
-      "(21, 'Individual: 021', 25.525114369502592, 48633)\n",
-      "(22, 'Individual: 022', 24.02621230558812, 51414)\n",
-      "(23, 'Individual: 023', 25.36660236909869, 53445)\n",
-      "(24, 'Individual: 024', 26.166761584649567, 59844)\n",
-      "(25, 'Individual: 025', 24.925568239677723, 55420)\n",
-      "(26, 'Individual: 026', 25.334241438007734, 52286)\n",
-      "(27, 'Individual: 027', 24.35634257798389, 47127)\n",
-      "(28, 'Individual: 028', 24.379764011709945, 43354)\n",
-      "(29, 'Individual: 029', 25.970751080494217, 58479)\n",
-      "(30, 'Individual: 030', 23.031631668580637, 61643)\n",
-      "(31, 'Individual: 031', 25.486396662028405, 46286)\n",
-      "(32, 'Individual: 032', 25.02768193636628, 47781)\n",
-      "(33, 'Individual: 033', 24.702078982456936, 46787)\n",
-      "(34, 'Individual: 034', 23.622632894752655, 41763)\n",
-      "(35, 'Individual: 035', 25.18245840193072, 44396)\n",
-      "(36, 'Individual: 036', 24.327072736740977, 37789)\n",
-      "(37, 'Individual: 037', 27.179832440998133, 55226)\n",
-      "(38, 'Individual: 038', 24.416278669685425, 48327)\n",
-      "(39, 'Individual: 039', 25.45717123985681, 51153)\n",
-      "(40, 'Individual: 040', 25.950506439788757, 53308)\n",
-      "(41, 'Individual: 041', 25.05222521590697, 52994)\n",
-      "(42, 'Individual: 042', 24.522624339544254, 45892)\n",
-      "(43, 'Individual: 043', 25.865077973388786, 47073)\n",
-      "(44, 'Individual: 044', 25.125544636768744, 43031)\n",
-      "(45, 'Individual: 045', 25.475983736889532, 54665)\n",
-      "(46, 'Individual: 046', 23.9603502068871, 51321)\n",
-      "(47, 'Individual: 047', 25.088279119759616, 50190)\n",
-      "(48, 'Individual: 048', 24.40922247819197, 49816)\n",
-      "(49, 'Individual: 049', 25.728646404457788, 49272)\n",
-      "(50, 'Individual: 050', 25.590778965014902, 44507)\n",
-      "(51, 'Individual: 051', 24.165785224719208, 50863)\n",
-      "(52, 'Individual: 052', 25.02524070590101, 45812)\n",
-      "(53, 'Individual: 053', 25.90688832187065, 50855)\n",
-      "(54, 'Individual: 054', 25.405612867685388, 50310)\n",
-      "(55, 'Individual: 055', 27.106849920099684, 58744)\n",
-      "(56, 'Individual: 056', 24.884981714203818, 47770)\n",
-      "(57, 'Individual: 057', 22.569035802223326, 53649)\n",
-      "(58, 'Individual: 058', 24.589150886413034, 41339)\n",
-      "(59, 'Individual: 059', 23.116363143771242, 54119)\n",
-      "(60, 'Individual: 060', 25.614449536992023, 47725)\n",
-      "(61, 'Individual: 061', 23.818011583570772, 50631)\n",
-      "(62, 'Individual: 062', 25.754418810189147, 46127)\n",
-      "(63, 'Individual: 063', 23.37159754146576, 42471)\n",
-      "(64, 'Individual: 064', 24.63858826707661, 47517)\n",
-      "(65, 'Individual: 065', 24.95043220241014, 49399)\n",
-      "(66, 'Individual: 066', 25.825723002809923, 47980)\n",
-      "(67, 'Individual: 067', 25.38116525590079, 47765)\n",
-      "(68, 'Individual: 068', 25.95619174147496, 50509)\n",
-      "(69, 'Individual: 069', 24.134908997669214, 51007)\n",
-      "(70, 'Individual: 070', 26.5048906027763, 54763)\n",
-      "(71, 'Individual: 071', 25.478989329342994, 48621)\n",
-      "(72, 'Individual: 072', 26.45845682526833, 53003)\n",
-      "(73, 'Individual: 073', 25.662969000311413, 45049)\n",
-      "(74, 'Individual: 074', 26.481196564890848, 53655)\n",
-      "(75, 'Individual: 075', 25.482834202787874, 55909)\n",
-      "(76, 'Individual: 076', 25.47922452340438, 54586)\n",
-      "(77, 'Individual: 077', 25.539193902306028, 54423)\n",
-      "(78, 'Individual: 078', 23.989370434750832, 56504)\n",
-      "(79, 'Individual: 079', 24.800464625800352, 49653)\n",
-      "(80, 'Individual: 080', 25.91745073089148, 55976)\n",
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-      "(83, 'Individual: 083', 24.122386931080346, 51192)\n",
-      "(84, 'Individual: 084', 25.835178277596235, 49336)\n",
-      "(85, 'Individual: 085', 26.557708567837512, 49848)\n",
-      "(86, 'Individual: 086', 26.328168407167418, 50899)\n",
-      "(87, 'Individual: 087', 25.303875652836627, 49636)\n",
-      "(88, 'Individual: 088', 24.61552848462999, 50013)\n",
-      "(89, 'Individual: 089', 24.98829084149272, 51337)\n",
-      "(90, 'Individual: 090', 25.980273061379584, 48970)\n",
-      "(91, 'Individual: 091', 24.982495965765835, 36760)\n",
-      "(92, 'Individual: 092', 27.470143507806128, 58199)\n",
-      "(93, 'Individual: 093', 25.070253849853316, 44874)\n",
-      "(94, 'Individual: 094', 25.562313973520876, 56027)\n",
-      "(95, 'Individual: 095', 26.455271228221175, 51132)\n",
-      "(96, 'Individual: 096', 23.299087097690666, 50492)\n",
-      "(97, 'Individual: 097', 23.44473007409865, 46982)\n",
-      "(98, 'Individual: 098', 23.422271690705045, 52086)\n",
-      "(99, 'Individual: 099', 25.227519479773093, 46926)\n",
-      "(100, 'Individual: 100', 23.82188149499848, 47263)\n",
-      "(101, 'Individual: 101', 47.404260544110684, 82062)\n",
-      "(102, 'Individual: 102', 48.849100622901396, 90226)\n",
-      "(103, 'Individual: 103', 42.31913479741497, 83705)\n",
-      "(104, 'Individual: 104', 39.87179613706066, 74468)\n",
-      "(105, 'Individual: 105', 37.031880002591414, 60062)\n",
-      "(106, 'Individual: 106', 39.8639387073848, 56646)\n",
-      "(107, 'Individual: 107', 48.97468539060065, 89025)\n",
-      "(108, 'Individual: 108', 41.06202707700086, 79817)\n",
-      "(109, 'Individual: 109', 48.85965925586444, 75993)\n",
-      "(110, 'Individual: 110', 41.7052261810714, 80825)\n",
-      "(111, 'Individual: 111', 46.44624550330593, 93133)\n",
-      "(112, 'Individual: 112', 46.6970215394055, 73495)\n",
-      "(113, 'Individual: 113', 48.43076474144459, 98342)\n",
-      "(114, 'Individual: 114', 42.98301425090402, 76492)\n",
-      "(115, 'Individual: 115', 46.71721186607902, 87529)\n",
-      "(116, 'Individual: 116', 42.655728930073906, 74896)\n",
-      "(117, 'Individual: 117', 46.111502884684946, 88516)\n",
-      "(118, 'Individual: 118', 51.527792759430284, 85514)\n",
-      "(119, 'Individual: 119', 49.59727417914037, 94416)\n",
-      "(120, 'Individual: 120', 51.00041690623652, 104275)\n",
-      "(121, 'Individual: 121', 46.68990901522216, 83431)\n",
-      "(122, 'Individual: 122', 45.39539596410638, 80706)\n",
-      "(123, 'Individual: 123', 40.92895589491278, 76339)\n",
-      "(124, 'Individual: 124', 44.856459604428096, 80049)\n",
-      "(125, 'Individual: 125', 46.27904686514323, 82443)\n",
-      "(126, 'Individual: 126', 48.295284178221415, 83460)\n",
-      "(127, 'Individual: 127', 41.740363945016874, 80123)\n",
-      "(128, 'Individual: 128', 37.44332752423415, 67809)\n",
-      "(129, 'Individual: 129', 39.99378985151627, 79658)\n",
-      "(130, 'Individual: 130', 42.96677899515424, 78229)\n",
-      "(131, 'Individual: 131', 47.97306089837442, 83574)\n",
-      "(132, 'Individual: 132', 41.20898424443146, 67627)\n",
-      "(133, 'Individual: 133', 43.84910252640341, 91616)\n",
-      "(134, 'Individual: 134', 45.63161191521578, 76677)\n",
-      "(135, 'Individual: 135', 42.305646588838755, 75264)\n",
-      "(136, 'Individual: 136', 48.5952394745472, 71680)\n",
-      "(137, 'Individual: 137', 37.17352544608759, 68649)\n",
-      "(138, 'Individual: 138', 47.046044205253075, 68082)\n",
-      "(139, 'Individual: 139', 44.059713310749146, 82409)\n",
-      "(140, 'Individual: 140', 53.15257619942137, 95877)\n",
-      "(141, 'Individual: 141', 47.28787601265288, 80766)\n",
-      "(142, 'Individual: 142', 43.38128213023818, 87329)\n",
-      "(143, 'Individual: 143', 42.67995234013793, 71068)\n",
-      "(144, 'Individual: 144', 49.23052084465668, 81845)\n",
-      "(145, 'Individual: 145', 50.346481154337745, 90087)\n",
-      "(146, 'Individual: 146', 44.23402694194281, 79914)\n",
-      "(147, 'Individual: 147', 38.79429200311992, 70207)\n",
-      "(148, 'Individual: 148', 51.2116534948333, 103244)\n",
-      "(149, 'Individual: 149', 45.923965459314836, 82734)\n",
-      "(150, 'Individual: 150', 37.249816617139075, 65909)\n",
-      "(151, 'Individual: 151', 41.25864750495034, 66558)\n",
-      "(152, 'Individual: 152', 51.52587422238312, 106517)\n",
-      "(153, 'Individual: 153', 51.46802220962631, 104710)\n",
-      "(154, 'Individual: 154', 43.94384193393332, 75919)\n",
-      "(155, 'Individual: 155', 45.894811591634046, 71604)\n",
-      "(156, 'Individual: 156', 43.3094508543472, 76633)\n",
-      "(157, 'Individual: 157', 39.82288146636257, 67429)\n",
-      "(158, 'Individual: 158', 44.53925052093046, 83026)\n",
-      "(159, 'Individual: 159', 40.886890271237384, 85154)\n",
-      "(160, 'Individual: 160', 43.34937134219747, 74508)\n",
-      "(161, 'Individual: 161', 39.91213416083551, 72150)\n",
-      "(162, 'Individual: 162', 40.1983742007039, 78190)\n",
-      "(163, 'Individual: 163', 48.59743926272466, 83810)\n",
-      "(164, 'Individual: 164', 49.74750897777976, 88221)\n",
-      "(165, 'Individual: 165', 42.64654504779174, 84672)\n",
-      "(166, 'Individual: 166', 44.08353196544536, 77033)\n",
-      "(167, 'Individual: 167', 41.78255031764483, 73958)\n",
-      "(168, 'Individual: 168', 45.565399233578255, 75090)\n",
-      "(169, 'Individual: 169', 46.58272067939971, 80429)\n",
-      "(170, 'Individual: 170', 37.990972449367014, 64231)\n",
-      "(171, 'Individual: 171', 51.762118675058, 96494)\n",
-      "(172, 'Individual: 172', 49.91682043235008, 84609)\n",
-      "(173, 'Individual: 173', 45.44707997576431, 97364)\n",
-      "(174, 'Individual: 174', 39.78502260722891, 78780)\n",
-      "(175, 'Individual: 175', 40.03544489547708, 63982)\n",
-      "(176, 'Individual: 176', 39.690632810450666, 65359)\n",
-      "(177, 'Individual: 177', 44.81147179979179, 75839)\n",
-      "(178, 'Individual: 178', 47.786369924013016, 86580)\n",
-      "(179, 'Individual: 179', 45.63895593966375, 72824)\n",
-      "(180, 'Individual: 180', 46.40039832139477, 76674)\n",
-      "(181, 'Individual: 181', 43.31651119630133, 71132)\n",
-      "(182, 'Individual: 182', 44.913021362797785, 76118)\n",
-      "(183, 'Individual: 183', 44.13938318645851, 72143)\n",
-      "(184, 'Individual: 184', 50.16856442303606, 80257)\n",
-      "(185, 'Individual: 185', 44.52649645673774, 84435)\n",
-      "(186, 'Individual: 186', 42.947161065614196, 86515)\n",
-      "(187, 'Individual: 187', 47.92662555968543, 79512)\n",
-      "(188, 'Individual: 188', 42.64400488098836, 79399)\n",
-      "(189, 'Individual: 189', 47.40312098170525, 92675)\n",
-      "(190, 'Individual: 190', 41.278325511626974, 79549)\n",
-      "(191, 'Individual: 191', 43.43670854151717, 85657)\n",
-      "(192, 'Individual: 192', 44.42223653677814, 82829)\n",
-      "(193, 'Individual: 193', 48.683988661266106, 86467)\n",
-      "(194, 'Individual: 194', 45.317860747588064, 88749)\n",
-      "(195, 'Individual: 195', 48.12115808026187, 92202)\n",
-      "(196, 'Individual: 196', 48.57820489670735, 89582)\n",
-      "(197, 'Individual: 197', 43.01459861321762, 73901)\n",
-      "(198, 'Individual: 198', 41.163018056152254, 72652)\n",
-      "(199, 'Individual: 199', 34.94686274746908, 70491)\n",
-      "(200, 'Individual: 200', 39.74676175751297, 64654)\n",
-      "(201, 'Individual: 201', 43.913325570472814, 81504)\n",
-      "(202, 'Individual: 202', 42.547322585189264, 72385)\n",
-      "(203, 'Individual: 203', 42.100452884122454, 84812)\n",
-      "(204, 'Individual: 204', 41.315747999514706, 74993)\n",
-      "(205, 'Individual: 205', 37.51011020514996, 62669)\n",
-      "(206, 'Individual: 206', 45.08505107169978, 71041)\n",
-      "(207, 'Individual: 207', 47.07237294656676, 78040)\n",
-      "(208, 'Individual: 208', 53.04300243980572, 93545)\n",
-      "(209, 'Individual: 209', 43.834138926602165, 80655)\n",
-      "(210, 'Individual: 210', 46.57266322319943, 83954)\n",
-      "(211, 'Individual: 211', 51.230543557510124, 87634)\n",
-      "(212, 'Individual: 212', 42.0916637238154, 81780)\n",
-      "(213, 'Individual: 213', 39.519153267968804, 73012)\n",
-      "(214, 'Individual: 214', 49.040618242819995, 82095)\n",
-      "(215, 'Individual: 215', 45.31639363800543, 67403)\n",
-      "(216, 'Individual: 216', 38.031124335313564, 63788)\n",
-      "(217, 'Individual: 217', 47.9486014075113, 97173)\n",
-      "(218, 'Individual: 218', 48.206343312418724, 94927)\n",
-      "(219, 'Individual: 219', 47.32489231572965, 91604)\n",
-      "(220, 'Individual: 220', 46.11413770197612, 83922)\n",
-      "(221, 'Individual: 221', 35.301029437081255, 63627)\n",
-      "(222, 'Individual: 222', 35.03898881686214, 80083)\n",
-      "(223, 'Individual: 223', 35.00543659376893, 67421)\n",
-      "(224, 'Individual: 224', 38.268952445865935, 60153)\n",
-      "(225, 'Individual: 225', 33.91228381267188, 77378)\n",
-      "(226, 'Individual: 226', 38.34715952661958, 81699)\n",
-      "(227, 'Individual: 227', 35.5925322009585, 72465)\n",
-      "(228, 'Individual: 228', 34.58190977648209, 66225)\n",
-      "(229, 'Individual: 229', 37.68327548633769, 57314)\n",
-      "(230, 'Individual: 230', 36.122309523791834, 61779)\n",
-      "(231, 'Individual: 231', 36.10591686948013, 72038)\n",
-      "(232, 'Individual: 232', 32.353142028555105, 59520)\n",
-      "(233, 'Individual: 233', 35.68739011715068, 62823)\n",
-      "(234, 'Individual: 234', 36.484734910946614, 76148)\n",
-      "(235, 'Individual: 235', 34.24028050138242, 58137)\n",
-      "(236, 'Individual: 236', 36.801147645813295, 72684)\n",
-      "(237, 'Individual: 237', 33.975592395697944, 57193)\n",
-      "(238, 'Individual: 238', 35.5605656556073, 70458)\n",
-      "(239, 'Individual: 239', 34.6678889493235, 60965)\n",
-      "(240, 'Individual: 240', 35.58708372147991, 69205)\n",
-      "(241, 'Individual: 241', 34.10157722658814, 78920)\n",
-      "(242, 'Individual: 242', 36.726078511475194, 68470)\n",
-      "(243, 'Individual: 243', 37.98447063843578, 67520)\n",
-      "(244, 'Individual: 244', 36.09322432884619, 81141)\n",
-      "(245, 'Individual: 245', 35.41275007057748, 69158)\n",
-      "(246, 'Individual: 246', 36.928169946714966, 80274)\n",
-      "(247, 'Individual: 247', 34.70038001570242, 59869)\n",
-      "(248, 'Individual: 248', 33.95626263510884, 63166)\n",
-      "(249, 'Individual: 249', 35.78452940295166, 80699)\n",
-      "(250, 'Individual: 250', 34.44030127185523, 74023)\n",
-      "(251, 'Individual: 251', 35.13065446046275, 66182)\n",
-      "(252, 'Individual: 252', 33.74986844534237, 66092)\n",
-      "(253, 'Individual: 253', 32.643617710867694, 73349)\n",
-      "(254, 'Individual: 254', 33.821388333447395, 74649)\n",
-      "(255, 'Individual: 255', 36.82656956578252, 81205)\n",
-      "(256, 'Individual: 256', 35.314719715442386, 67400)\n",
-      "(257, 'Individual: 257', 36.87761625420699, 66684)\n",
-      "(258, 'Individual: 258', 34.39754679419078, 68244)\n",
-      "(259, 'Individual: 259', 41.816525712692396, 70526)\n",
-      "(260, 'Individual: 260', 32.46525588617193, 64708)\n",
-      "(261, 'Individual: 261', 38.44359361353193, 63331)\n",
-      "(262, 'Individual: 262', 31.45462183739104, 69542)\n",
-      "(263, 'Individual: 263', 37.27658957203023, 78385)\n",
-      "(264, 'Individual: 264', 38.11794848106296, 80897)\n",
-      "(265, 'Individual: 265', 35.0330527437047, 53686)\n",
-      "(266, 'Individual: 266', 32.67540495416496, 62167)\n",
-      "(267, 'Individual: 267', 30.624907612864487, 67915)\n",
-      "(268, 'Individual: 268', 36.10663656416574, 84828)\n",
-      "(269, 'Individual: 269', 35.26289910651095, 82618)\n",
-      "(270, 'Individual: 270', 36.42668440297713, 68270)\n",
-      "(271, 'Individual: 271', 33.33890058344479, 71534)\n",
-      "(272, 'Individual: 272', 35.61080963599342, 73866)\n",
-      "(273, 'Individual: 273', 35.32700016406549, 81075)\n",
-      "(274, 'Individual: 274', 34.30684902469834, 58865)\n",
-      "(275, 'Individual: 275', 32.437591076688896, 65597)\n",
-      "(276, 'Individual: 276', 37.675351964383424, 82233)\n",
-      "(277, 'Individual: 277', 35.36912648816337, 73042)\n",
-      "(278, 'Individual: 278', 33.237396086356306, 77283)\n",
-      "(279, 'Individual: 279', 37.76122970395246, 78407)\n",
-      "(280, 'Individual: 280', 34.72091607471147, 67314)\n",
-      "(281, 'Individual: 281', 34.47280067008884, 64555)\n",
-      "(282, 'Individual: 282', 36.69245718985907, 70082)\n",
-      "(283, 'Individual: 283', 34.76048672309016, 62628)\n",
-      "(284, 'Individual: 284', 36.25144906694082, 68203)\n",
-      "(285, 'Individual: 285', 34.04117576581565, 78593)\n",
-      "(286, 'Individual: 286', 38.06253723275973, 81193)\n",
-      "(287, 'Individual: 287', 34.37037920463491, 74054)\n",
-      "(288, 'Individual: 288', 35.039904593187615, 75508)\n",
-      "(289, 'Individual: 289', 31.170010356203505, 77544)\n",
-      "(290, 'Individual: 290', 33.869710865868754, 78205)\n",
-      "(291, 'Individual: 291', 37.157537622528665, 72579)\n",
-      "(292, 'Individual: 292', 34.92498073589014, 82418)\n",
-      "(293, 'Individual: 293', 32.46815694199189, 68784)\n",
-      "(294, 'Individual: 294', 32.84927148107052, 74522)\n",
-      "(295, 'Individual: 295', 37.30436105181069, 73248)\n",
-      "(296, 'Individual: 296', 33.58393392838615, 83167)\n",
-      "(297, 'Individual: 297', 33.30258842296932, 67112)\n",
-      "(298, 'Individual: 298', 38.25803588528998, 80069)\n",
-      "(299, 'Individual: 299', 37.63935961821646, 80799)\n",
-      "(300, 'Individual: 300', 35.80554909275177, 78114)\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Turn the above records into a Data Frame\n",
-    "# First of all, create an array of arrays\n",
-    "inputBuf = []\n",
-    "\n",
-    "for  i in range(0, len(ages)) :\n",
-    "     id = i + 1 # Avoid counting from zero\n",
-    "     name = \"Individual: {:03d}\".format(id)\n",
-    "     # Note we need to make sure values are typed correctly\n",
-    "     # salary will have type numpy.float64 - if it is not cast as below, an error will be thrown\n",
-    "     age = float(ages[i])\n",
-    "     salary = int(salaries[i])\n",
-    "     inputBuf.append((id, name,age,salary))\n",
-    "\n",
-    "for i in inputBuf:\n",
-    "    print (i)\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Connect to the Aerospike"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Configure the client\n",
-    "config = {\n",
-    "  'hosts': [ (AS_HOST, AS_PORT) ]\n",
-    "}\n",
-    "\n",
-    "# Create a client and connect it to the cluster\n",
-    "try:\n",
-    "  client = aerospike.client(config).connect()\n",
-    "except:\n",
-    "  import sys\n",
-    "  print(\"failed to connect to the cluster with\", config['hosts'])\n",
-    "  sys.exit(1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Write Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Type 'show namespaces' at the aql prompt if you are not sure about the namespace\n",
-    "namespace= \"test\"\n",
-    "write_set= \"write_set\"\n",
-    "\n",
-    "for  i in inputBuf:\n",
-    "  _id, _name, _age, _salary = i\n",
-    "  key = (namespace, write_set,_id)\n",
-    "  client.put(key, {'id': _id,'name': _name,'age': _age,'salary': _salary})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Read Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'id': 1, 'name': 'Individual: 001', 'age': 24.304499333848025, 'salary': 46865}\n",
-      "{'id': 2, 'name': 'Individual: 002', 'age': 25.127370725646376, 'salary': 58731}\n",
-      "{'id': 3, 'name': 'Individual: 003', 'age': 24.433587308486384, 'salary': 39822}\n",
-      "{'id': 4, 'name': 'Individual: 004', 'age': 23.466317614770414, 'salary': 46800}\n",
-      "{'id': 5, 'name': 'Individual: 005', 'age': 25.901554554617075, 'salary': 44622}\n",
-      "{'id': 6, 'name': 'Individual: 006', 'age': 25.244089945979592, 'salary': 48962}\n",
-      "{'id': 7, 'name': 'Individual: 007', 'age': 25.513546531713885, 'salary': 54015}\n",
-      "{'id': 8, 'name': 'Individual: 008', 'age': 24.384542542073284, 'salary': 48850}\n",
-      "{'id': 9, 'name': 'Individual: 009', 'age': 23.969228059245417, 'salary': 49939}\n",
-      "{'id': 10, 'name': 'Individual: 010', 'age': 25.32659498864832, 'salary': 52270}\n",
-      "{'id': 11, 'name': 'Individual: 011', 'age': 24.52188955913116, 'salary': 56682}\n",
-      "{'id': 12, 'name': 'Individual: 012', 'age': 25.307831842818935, 'salary': 48937}\n",
-      "{'id': 13, 'name': 'Individual: 013', 'age': 25.25646020804283, 'salary': 54880}\n",
-      "{'id': 14, 'name': 'Individual: 014', 'age': 25.678511730398245, 'salary': 50121}\n",
-      "{'id': 15, 'name': 'Individual: 015', 'age': 24.05942103892467, 'salary': 60348}\n",
-      "{'id': 16, 'name': 'Individual: 016', 'age': 25.749046404565952, 'salary': 53522}\n",
-      "{'id': 17, 'name': 'Individual: 017', 'age': 22.897339115317486, 'salary': 41738}\n",
-      "{'id': 18, 'name': 'Individual: 018', 'age': 25.85659550137486, 'salary': 51606}\n",
-      "{'id': 19, 'name': 'Individual: 019', 'age': 25.344785148917193, 'salary': 47040}\n",
-      "{'id': 20, 'name': 'Individual: 020', 'age': 23.821932401631045, 'salary': 51202}\n",
-      "{'id': 21, 'name': 'Individual: 021', 'age': 25.525114369502592, 'salary': 48633}\n",
-      "{'id': 22, 'name': 'Individual: 022', 'age': 24.02621230558812, 'salary': 51414}\n",
-      "{'id': 23, 'name': 'Individual: 023', 'age': 25.36660236909869, 'salary': 53445}\n",
-      "{'id': 24, 'name': 'Individual: 024', 'age': 26.166761584649567, 'salary': 59844}\n",
-      "{'id': 25, 'name': 'Individual: 025', 'age': 24.925568239677723, 'salary': 55420}\n",
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-      "{'id': 230, 'name': 'Individual: 230', 'age': 36.122309523791834, 'salary': 61779}\n",
-      "{'id': 231, 'name': 'Individual: 231', 'age': 36.10591686948013, 'salary': 72038}\n",
-      "{'id': 232, 'name': 'Individual: 232', 'age': 32.353142028555105, 'salary': 59520}\n",
-      "{'id': 233, 'name': 'Individual: 233', 'age': 35.68739011715068, 'salary': 62823}\n",
-      "{'id': 234, 'name': 'Individual: 234', 'age': 36.484734910946614, 'salary': 76148}\n",
-      "{'id': 235, 'name': 'Individual: 235', 'age': 34.24028050138242, 'salary': 58137}\n",
-      "{'id': 236, 'name': 'Individual: 236', 'age': 36.801147645813295, 'salary': 72684}\n",
-      "{'id': 237, 'name': 'Individual: 237', 'age': 33.975592395697944, 'salary': 57193}\n",
-      "{'id': 238, 'name': 'Individual: 238', 'age': 35.5605656556073, 'salary': 70458}\n",
-      "{'id': 239, 'name': 'Individual: 239', 'age': 34.6678889493235, 'salary': 60965}\n",
-      "{'id': 240, 'name': 'Individual: 240', 'age': 35.58708372147991, 'salary': 69205}\n",
-      "{'id': 241, 'name': 'Individual: 241', 'age': 34.10157722658814, 'salary': 78920}\n",
-      "{'id': 242, 'name': 'Individual: 242', 'age': 36.726078511475194, 'salary': 68470}\n",
-      "{'id': 243, 'name': 'Individual: 243', 'age': 37.98447063843578, 'salary': 67520}\n",
-      "{'id': 244, 'name': 'Individual: 244', 'age': 36.09322432884619, 'salary': 81141}\n",
-      "{'id': 245, 'name': 'Individual: 245', 'age': 35.41275007057748, 'salary': 69158}\n",
-      "{'id': 246, 'name': 'Individual: 246', 'age': 36.928169946714966, 'salary': 80274}\n",
-      "{'id': 247, 'name': 'Individual: 247', 'age': 34.70038001570242, 'salary': 59869}\n",
-      "{'id': 248, 'name': 'Individual: 248', 'age': 33.95626263510884, 'salary': 63166}\n",
-      "{'id': 249, 'name': 'Individual: 249', 'age': 35.78452940295166, 'salary': 80699}\n",
-      "{'id': 250, 'name': 'Individual: 250', 'age': 34.44030127185523, 'salary': 74023}\n",
-      "{'id': 251, 'name': 'Individual: 251', 'age': 35.13065446046275, 'salary': 66182}\n",
-      "{'id': 252, 'name': 'Individual: 252', 'age': 33.74986844534237, 'salary': 66092}\n",
-      "{'id': 253, 'name': 'Individual: 253', 'age': 32.643617710867694, 'salary': 73349}\n",
-      "{'id': 254, 'name': 'Individual: 254', 'age': 33.821388333447395, 'salary': 74649}\n",
-      "{'id': 255, 'name': 'Individual: 255', 'age': 36.82656956578252, 'salary': 81205}\n",
-      "{'id': 256, 'name': 'Individual: 256', 'age': 35.314719715442386, 'salary': 67400}\n",
-      "{'id': 257, 'name': 'Individual: 257', 'age': 36.87761625420699, 'salary': 66684}\n",
-      "{'id': 258, 'name': 'Individual: 258', 'age': 34.39754679419078, 'salary': 68244}\n",
-      "{'id': 259, 'name': 'Individual: 259', 'age': 41.816525712692396, 'salary': 70526}\n",
-      "{'id': 260, 'name': 'Individual: 260', 'age': 32.46525588617193, 'salary': 64708}\n",
-      "{'id': 261, 'name': 'Individual: 261', 'age': 38.44359361353193, 'salary': 63331}\n",
-      "{'id': 262, 'name': 'Individual: 262', 'age': 31.45462183739104, 'salary': 69542}\n",
-      "{'id': 263, 'name': 'Individual: 263', 'age': 37.27658957203023, 'salary': 78385}\n",
-      "{'id': 264, 'name': 'Individual: 264', 'age': 38.11794848106296, 'salary': 80897}\n",
-      "{'id': 265, 'name': 'Individual: 265', 'age': 35.0330527437047, 'salary': 53686}\n",
-      "{'id': 266, 'name': 'Individual: 266', 'age': 32.67540495416496, 'salary': 62167}\n",
-      "{'id': 267, 'name': 'Individual: 267', 'age': 30.624907612864487, 'salary': 67915}\n",
-      "{'id': 268, 'name': 'Individual: 268', 'age': 36.10663656416574, 'salary': 84828}\n",
-      "{'id': 269, 'name': 'Individual: 269', 'age': 35.26289910651095, 'salary': 82618}\n",
-      "{'id': 270, 'name': 'Individual: 270', 'age': 36.42668440297713, 'salary': 68270}\n",
-      "{'id': 271, 'name': 'Individual: 271', 'age': 33.33890058344479, 'salary': 71534}\n",
-      "{'id': 272, 'name': 'Individual: 272', 'age': 35.61080963599342, 'salary': 73866}\n",
-      "{'id': 273, 'name': 'Individual: 273', 'age': 35.32700016406549, 'salary': 81075}\n",
-      "{'id': 274, 'name': 'Individual: 274', 'age': 34.30684902469834, 'salary': 58865}\n",
-      "{'id': 275, 'name': 'Individual: 275', 'age': 32.437591076688896, 'salary': 65597}\n",
-      "{'id': 276, 'name': 'Individual: 276', 'age': 37.675351964383424, 'salary': 82233}\n",
-      "{'id': 277, 'name': 'Individual: 277', 'age': 35.36912648816337, 'salary': 73042}\n",
-      "{'id': 278, 'name': 'Individual: 278', 'age': 33.237396086356306, 'salary': 77283}\n",
-      "{'id': 279, 'name': 'Individual: 279', 'age': 37.76122970395246, 'salary': 78407}\n",
-      "{'id': 280, 'name': 'Individual: 280', 'age': 34.72091607471147, 'salary': 67314}\n",
-      "{'id': 281, 'name': 'Individual: 281', 'age': 34.47280067008884, 'salary': 64555}\n",
-      "{'id': 282, 'name': 'Individual: 282', 'age': 36.69245718985907, 'salary': 70082}\n",
-      "{'id': 283, 'name': 'Individual: 283', 'age': 34.76048672309016, 'salary': 62628}\n",
-      "{'id': 284, 'name': 'Individual: 284', 'age': 36.25144906694082, 'salary': 68203}\n",
-      "{'id': 285, 'name': 'Individual: 285', 'age': 34.04117576581565, 'salary': 78593}\n",
-      "{'id': 286, 'name': 'Individual: 286', 'age': 38.06253723275973, 'salary': 81193}\n",
-      "{'id': 287, 'name': 'Individual: 287', 'age': 34.37037920463491, 'salary': 74054}\n",
-      "{'id': 288, 'name': 'Individual: 288', 'age': 35.039904593187615, 'salary': 75508}\n",
-      "{'id': 289, 'name': 'Individual: 289', 'age': 31.170010356203505, 'salary': 77544}\n",
-      "{'id': 290, 'name': 'Individual: 290', 'age': 33.869710865868754, 'salary': 78205}\n",
-      "{'id': 291, 'name': 'Individual: 291', 'age': 37.157537622528665, 'salary': 72579}\n",
-      "{'id': 292, 'name': 'Individual: 292', 'age': 34.92498073589014, 'salary': 82418}\n",
-      "{'id': 293, 'name': 'Individual: 293', 'age': 32.46815694199189, 'salary': 68784}\n",
-      "{'id': 294, 'name': 'Individual: 294', 'age': 32.84927148107052, 'salary': 74522}\n",
-      "{'id': 295, 'name': 'Individual: 295', 'age': 37.30436105181069, 'salary': 73248}\n",
-      "{'id': 296, 'name': 'Individual: 296', 'age': 33.58393392838615, 'salary': 83167}\n",
-      "{'id': 297, 'name': 'Individual: 297', 'age': 33.30258842296932, 'salary': 67112}\n",
-      "{'id': 298, 'name': 'Individual: 298', 'age': 38.25803588528998, 'salary': 80069}\n",
-      "{'id': 299, 'name': 'Individual: 299', 'age': 37.63935961821646, 'salary': 80799}\n",
-      "{'id': 300, 'name': 'Individual: 300', 'age': 35.80554909275177, 'salary': 78114}\n"
-     ]
-    }
-   ],
-   "source": [
-    "for  i in inputBuf:\n",
-    "    _id, _name, _age, _salary = i\n",
-    "    key = (namespace, write_set,_id)\n",
-    "    (key, metadata, record) = client.get(key)\n",
-    "    print(record)\n"
-   ]
-  },
-  {
-   "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": "3.8.5"
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- },
- "nbformat": 4,
- "nbformat_minor": 2
-}