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spark/homework/task3.ipynb
2026-06-07 13:48:55 +07:00

114 lines
2.3 KiB
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{
"cells": [
{
"cell_type": "code",
"execution_count": 5,
"id": "e3cf6fb7-e4e7-4cd7-baa7-03209328631c",
"metadata": {},
"outputs": [],
"source": [
"from pyspark.sql import SparkSession\n",
"import pyspark.sql.functions as F\n",
"\n",
"spark = SparkSession.builder.appName(\"some_name\").getOrCreate()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0f1fb08-2373-48b2-99d9-1424a4ceb0c0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"+---------+\n",
"|log_level|\n",
"+---------+\n",
"|INFO |\n",
"|DEBUG |\n",
"|ERROR |\n",
"|INFO |\n",
"|ERROR |\n",
"|DEBUG |\n",
"|ERROR |\n",
"+---------+\n",
"\n"
]
}
],
"source": [
"parts = F.split(F.col(\"value\"), \" \", 2)\n",
"df_logs = spark.read.text(\"logs.txt\").select(parts[0].alias(\"log_level\"))\n",
"df_logs.show(truncate=False)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "6d784b52-9369-4051-8084-a7f705c001fa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_error_logs = df_logs.filter(F.col(\"log_level\") == \"ERROR\").count()\n",
"count_error"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "592dc010-5700-4cc1-b0bf-8738c3b1567e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.42857142857142855"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total = df_logs.count()\n",
"count_error / total"
]
}
],
"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": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}