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pyspark/create_marts_clickhouse.py
2026-02-24 07:09:37 +03:00

88 lines
3.8 KiB
Python

import os
from typing import List
from pyspark.sql import SparkSession
from pyspark.sql import functions as F
from pyspark.sql import DataFrame
spark = SparkSession.builder \
.appName("create_marts_clickhouse") \
.master("local[*]") \
.getOrCreate()
def read_csv_folder(path: str) -> DataFrame:
return spark.read \
.option("header", "true") \
.option("inferSchema", "true") \
.csv(path)
users = read_csv_folder("data/clickhouse/users")
courses = read_csv_folder("data/clickhouse/courses")
lessons = read_csv_folder("data/clickhouse/lessons")
enrollments = read_csv_folder("data/clickhouse/enrollments")
lesson_views = read_csv_folder("data/clickhouse/lesson_views")
def cast_int_columns(df: DataFrame, int_cols: List[str]) -> DataFrame:
for c in int_cols:
if c in df.columns:
df = df.withColumn(c, F.col(c).cast("int"))
return df
users = cast_int_columns(users, ["id"])
courses = cast_int_columns(courses, ["id"])
lessons = cast_int_columns(lessons, ["id", "course_id"])
enrollments = cast_int_columns(enrollments, ["id", "user_id", "course_id"])
lesson_views = cast_int_columns(lesson_views, ["id", "user_id", "lesson_id"])
lesson_popularity_summary = lesson_views.alias("lv") \
.join(lessons.alias("l"), F.col("lv.lesson_id") == F.col("l.id")) \
.join(courses.alias("c"), F.col("l.course_id") == F.col("c.id")) \
.groupBy(F.col("l.id").alias("lesson_id"),
F.col("l.title").alias("lesson_title"),
F.col("c.id").alias("course_id"),
F.col("c.title").alias("course_title")) \
.agg(
F.count("lv.lesson_id").alias("total_views"),
F.countDistinct("lv.user_id").alias("unique_users"),
F.min("lv.viewed_at").alias("first_view"),
F.max("lv.viewed_at").alias("last_view")
).orderBy("lesson_id")
inactive_users_summary = users.alias("u") \
.join(enrollments.alias("e"), F.col("u.id") == F.col("e.user_id"), "left") \
.join(lesson_views.alias("lv"), F.col("u.id") == F.col("lv.user_id"), "left") \
.filter(F.col("lv.user_id").isNull()) \
.groupBy(F.col("u.id").alias("user_id"),
F.col("u.name").alias("user_name"),
F.col("u.email").alias("user_email"),
F.col("u.age").alias("user_age"),
F.col("u.registration_date").alias("user_registration_date")) \
.agg(
F.countDistinct("e.course_id").alias("enrollments_count")
).orderBy("user_id")
course_completion_rate = courses.alias("c") \
.join(enrollments.alias("e"), F.col("c.id") == F.col("e.course_id")) \
.join(users.alias("u"), F.col("e.user_id") == F.col("u.id")) \
.join(lessons.alias("l"), F.col("c.id") == F.col("l.course_id")) \
.join(lesson_views.alias("lv"),
(F.col("u.id") == F.col("lv.user_id")) &
(F.col("l.id") == F.col("lv.lesson_id")),
"left") \
.groupBy(F.col("u.id").alias("user_id"),
F.col("u.name").alias("user_name"),
F.col("c.id").alias("course_id"),
F.col("c.title").alias("course_title")) \
.agg(
F.countDistinct("l.id").alias("lessons_in_course"),
F.countDistinct("lv.lesson_id").alias("lessons_viewed"),
F.round(F.countDistinct("lv.lesson_id") * 1.0 / F.countDistinct("l.id"), 2).alias("completion_rate")
).orderBy("user_id", "course_id")
output_dir = "data/marts/clickhouse"
os.makedirs(output_dir, exist_ok=True)
lesson_popularity_summary.write.mode("overwrite").option("header", "true").csv(f"{output_dir}/lesson_popularity_summary")
inactive_users_summary.write.mode("overwrite").option("header", "true").csv(f"{output_dir}/inactive_users_summary")
course_completion_rate.write.mode("overwrite").option("header", "true").csv(f"{output_dir}/course_completion_rate")
print(".............витрины clickhouse созданы")