data-engineering-zoomcamp-week-5
Mastering Batch Processing with Data Engineering: A Small Dive into Week 5 of DataTalksClub Zoomcamp.
Here are some of the key takeaways from Week 5:
- Hands-on exercises provide an opportunity to apply what you’ve learned to real-world scenarios, reinforcing your understanding of the material.
- The course covers how to set up a distributed computing environment using Hadoop, allowing you to configure Hadoop nodes, create a Hadoop cluster, and run MapReduce jobs on the cluster. This is a great way to see how batch processing can handle large amounts of data efficiently.
- PySpark is covered extensively, including creating Spark DataFrames, performing transformations and aggregations, and saving results to disk. This is particularly useful since PySpark is widely used in the industry for batch processing.
- We also learned how to use PySpark to write data to Google Cloud Storage and directly to BigQuery. This was a great opportunity to see how PySpark can be used to handle data at scale in a cloud environment.
Overall, Week 5 of the Zoomcamp data engineering course is a valuable resource for anyone looking to expand their knowledge of batch processing in data engineering.
Link to week 5: https://lnkd.in/eCd7_hvD
#dez #spark #pyspark #apachespark #hadoop #python