BEGINNER • SQL Fundamentals
Sprint: optimize query performance #12
This lesson focuses on optimize query performance for a recommendation engine environment. You will use: python etl_script.py | CREATE TABLE events (id SERIAL PRIMARY KEY) | python -m venv venv. The content is designed for practical data engineering execution.
Code Example
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("recommendation engine").getOrCreate()
df = spark.read.parquet("s3://bucket/raw/")
df.filter("event_type = 'purchase'").write.mode("overwrite").parquet("s3://bucket/processed/")
# Objective: optimize query performanceCommands & References
- python etl_script.py
- CREATE TABLE events (id SERIAL PRIMARY KEY)
- python -m venv venv
Lab Steps
- Prepare environment with: python etl_script.py
- Design or modify the data pipeline for the scenario.
- Validate data quality and document lineage.
- Propose one optimization for production.
Exercises
- Add one data quality check.
- Implement one incremental loading pattern.
- Write a rollback procedure for this pipeline.