 archived/r_sagemaker_hello_world.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using R with Amazon SageMaker - Basic Notebook\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "This notebook's CI test result for us-west-2 is as follows. CI test results in other regions can be found at the end of the notebook. \n",
    "\n",
    "![This us-west-2 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/us-west-2/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "**Read before running this notebook:**\n",
    "\n",
    "- This sample notebook has been updated for SageMaker SDK v2.0. \n",
    "- If you are using SageMaker Notebook instances, select `R` kernel for the notebook. If you are using SageMaker Studio notebooks, you will need to create a custom R kernel for your studio domain. Follow the instructions in this blog post to create and attach a custom R kernel. \n",
    "    - [Bringing your own R environment to Amazon SageMaker Studio](https://aws.amazon.com/blogs/machine-learning/bringing-your-own-r-environment-to-amazon-sagemaker-studio/)\n",
    "\n",
    "**Summary:**\n",
    "\n",
    "This sample Notebook describes how you can develop R scripts in [Amazon SageMaker](https://aws.amazon.com/sagemaker/) and [R](https://www.r-project.org/) Jupyer notebooks. In this notebook we only focus on setting up the SageMaker environment and permissions, and then download the [abalone dataset](https://archive.ics.uci.edu/ml/datasets/abalone) from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php). We then do some basic processing and visualization on the data, and will save the data as .CSV format to S3. \n",
    "\n",
    "For other examples related to R on SageMaker, including end-2-end examples for training, tuning, and deploying models, please visit the GitHub repository located at this link:\n",
    "\n",
    "https://github.com/awslabs/amazon-sagemaker-examples/tree/master/r_examples\n",
    "\n",
    "For more details about the R kernel in SageMaker, please visit this news release:\n",
    "[Amazon SageMaker notebooks now available with pre-installed R kernel](https://aws.amazon.com/about-aws/whats-new/2019/08/amazon-sagemaker-notebooks-available-with-pre-installed-r-kernel/)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reticulating the Amazon SageMaker Python SDK\n",
    "\n",
    "First, load the `reticulate` library and import the `sagemaker` Python module. Once the module is loaded, use the `$` notation in R instead of the `.` notation in Python to use available classes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(reticulate)\n",
    "sagemaker <- import('sagemaker')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating and accessing the data storage\n",
    "\n",
    "The `Session` class provides operations for working with the following [boto3](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html) resources with Amazon SageMaker:\n",
    "\n",
    "* [S3](https://boto3.readthedocs.io/en/latest/reference/services/s3.html)\n",
    "* [SageMaker](https://boto3.readthedocs.io/en/latest/reference/services/sagemaker.html)\n",
    "* [SageMakerRuntime](https://boto3.readthedocs.io/en/latest/reference/services/sagemaker-runtime.html)\n",
    "\n",
    "Let's create an [Amazon Simple Storage Service](https://aws.amazon.com/s3/) bucket for your data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "session <- sagemaker$Session()\n",
    "bucket <- session$default_bucket()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note** - The `default_bucket` function creates a unique Amazon S3 bucket with the following name: \n",
    "\n",
    "`sagemaker-<aws-region-name>-<aws account number>`\n",
    "\n",
    "Specify the IAM role's [ARN](https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html) to allow Amazon SageMaker to access the Amazon S3 bucket. You can use the same IAM role used to create this Notebook:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "role_arn <- sagemaker$get_execution_role()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downloading and processing the dataset\n",
    "\n",
    "The model uses the [abalone dataset](https://archive.ics.uci.edu/ml/datasets/abalone) from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php). First, download the data and start the [exploratory data analysis](https://en.wikipedia.org/wiki/Exploratory_data_analysis). Use tidyverse packages to read the data, plot the data, and transform the data into ML format for Amazon SageMaker:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(readr)\n",
    "data_file <- 's3://sagemaker-sample-files/datasets/tabular/uci_abalone/abalone.csv'\n",
    "abalone <- read_csv(file = sagemaker$s3$S3Downloader$read_file(data_file, sagemaker_session=session), \n",
    "                    col_names = FALSE)\n",
    "names(abalone) <- c('sex', 'length', 'diameter', 'height', 'whole_weight', 'shucked_weight', 'viscera_weight', 'shell_weight', 'rings')\n",
    "head(abalone)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output above shows that `sex` is a factor data type but is currently a character data type (F is Female, M is male, and I is infant). Change `sex` to a factor and view the statistical summary of the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "abalone$sex <- as.factor(abalone$sex)\n",
    "summary(abalone)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The summary above shows that the minimum value for `height` is 0.\n",
    "\n",
    "Visually explore which abalones have height equal to 0 by plotting the relationship between `rings` and `height` for each value of `sex`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggplot2)\n",
    "options(repr.plot.width = 5, repr.plot.height = 4) \n",
    "ggplot(abalone, aes(x = height, y = rings, color = sex, alpha=0.5)) + geom_point() + geom_jitter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Do OneHotEncoding for Sex column\n",
    "library(dplyr)\n",
    "\n",
    "abalone <- abalone %>%\n",
    "  mutate(female = as.integer(ifelse(sex == 'F', 1, 0)),\n",
    "         male = as.integer(ifelse(sex == 'M', 1, 0)),\n",
    "         infant = as.integer(ifelse(sex == 'I', 1, 0))) %>%\n",
    "  select(-sex)\n",
    "abalone <- abalone %>%\n",
    "  select(rings:infant, length:shell_weight)\n",
    "head(abalone)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's write the dataframe to a CSV file locally on the SageMaker instance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "write_csv(abalone, 'abalone.csv', col_names = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, upload the csv file to the Amazon S3 default bucket into the `data` key:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s3_train <- session$upload_data(path = 'abalone.csv', \n",
    "                                bucket = bucket, \n",
    "                                key_prefix = 'r_hello_world_demo/data')\n",
    "\n",
    "s3_path = paste('s3://',bucket,'/r_hello_world_demo/data/abalone.csv',sep = '')\n",
    "cat('Your CSV data is stored on S3 in this location:\\n',s3_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extensions\n",
    "This example walked you through a simple process for setting up your SageMaker environment and write your R script. In addition, you were able to download a dataset, process it, visualize it, and then store it on S3.\n",
    "\n",
    "If you are interested in learning more about how you can leverage R on SageMaker and take advantage of SageMaker features for training, tuning, and deploying machine learning models, visit other exampls in this GitHub repository:\n",
    "\n",
    "https://github.com/awslabs/amazon-sagemaker-examples/tree/master/r_examples"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook CI Test Results\n",
    "\n",
    "This notebook was tested in multiple regions. The test results are as follows, except for us-west-2 which is shown at the top of the notebook.\n",
    "\n",
    "![This us-east-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/us-east-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This us-east-2 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/us-east-2/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This us-west-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/us-west-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ca-central-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ca-central-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This sa-east-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/sa-east-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This eu-west-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/eu-west-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This eu-west-2 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/eu-west-2/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This eu-west-3 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/eu-west-3/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This eu-central-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/eu-central-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This eu-north-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/eu-north-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ap-southeast-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ap-southeast-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ap-southeast-2 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ap-southeast-2/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ap-northeast-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ap-northeast-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ap-northeast-2 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ap-northeast-2/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n",
    "\n",
    "![This ap-south-1 badge failed to load. Check your device's internet connectivity, otherwise the service is currently unavailable](https://prod.us-west-2.tcx-beacon.docs.aws.dev/sagemaker-nb/ap-south-1/r_examples|r_sagemaker_hello_world|r_sagemaker_hello_world.ipynb)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.0.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}