spark_xgboost_gpu.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request\n",
    "url = 'https://repo1.maven.org/maven2/ai/rapids/cudf/0.14/cudf-0.14-cuda10-1.jar'\n",
    "filename = 'rapid_cudf.jar'\n",
    "urllib.request.urlretrieve(url, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://repo1.maven.org/maven2/com/nvidia/xgboost4j_3.0/1.0.0-0.1.0/xgboost4j_3.0-1.0.0-0.1.0.jar'\n",
    "filename = 'xgboost4j.jar'\n",
    "urllib.request.urlretrieve(url, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://repo1.maven.org/maven2/com/nvidia/xgboost4j-spark_3.0/1.0.0-0.1.0/xgboost4j-spark_3.0-1.0.0-0.1.0.jar'\n",
    "filename = 'xgboost4j-spark.jar'\n",
    "urllib.request.urlretrieve(url, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'http://insecure.repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/0.1.0/rapids-4-spark_2.12-0.1.0.jar'\n",
    "filename = 'rapids-4-spark.jar'\n",
    "urllib.request.urlretrieve(url, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars rapid_cudf.jar, xgboost4j.jar, xgboost4j-spark.jar, rapids-4-spark.jar pyspark-shell'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import findspark\n",
    "# findspark.init()\n",
    "# from pyspark.sql import SparkSession\n",
    "# spark = SparkSession.builder.master(\"local[*]\").config(\"spark.plugins\", \"com.nvidia.spark.SQLPlugin\").config(\"spark.rapids.memory.gpu.pooling.enabled\",False).getOrCreate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import SparkSession\n",
    "\n",
    "spark = SparkSession \\\n",
    "    .builder \\\n",
    "    .appName(\"Python Spark data cleaning and engineering\") \\\n",
    "    .config(\"spark.some.config.option\", \"some-value\") \\\n",
    "    .getOrCreate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "spark.sparkContext.addPyFile('xgboost4j-spark.jar')\n",
    "spark.sparkContext.addPyFile('rapids-4-spark.jar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "spark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ml.dmlc.xgboost4j.scala.spark import XGBoostClassificationModel, XGBoostClassifier\n",
    "from ml.dmlc.xgboost4j.scala.spark.rapids import GpuDataReader\n",
    "from pyspark.ml.evaluation import MulticlassClassificationEvaluator\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
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