Data Engineer 面接の質問と回答
質問 21. Explain the concept of ACID properties in the context of database transactions.
ACID stands for Atomicity, Consistency, Isolation, and Durability—properties that ensure the reliability and integrity of database transactions.
Example:
Ensuring that a financial transaction is atomic (either fully completed or fully rolled back) to maintain data integrity.
質問 22. What is the difference between a left join and an inner join in SQL?
An inner join returns only the rows where there is a match in both tables, while a left join returns all rows from the left table and the matched rows from the right table.
Example:
Selecting all customers and their orders, even if some customers have not placed any orders (left join).
質問 23. How does data compression impact storage and processing in a data warehouse?
Data compression reduces the storage space required for data, leading to cost savings and improved query performance in a data warehouse.
Example:
Applying columnar compression to a large dataset in a data warehouse to reduce storage costs.
質問 24. Explain the concept of data skewness and its impact on data processing.
Data skewness refers to the uneven distribution of data within a dataset. It can impact performance in distributed computing environments, causing certain tasks to take longer than others.
Example:
Identifying and addressing data skewness issues in a Spark job to improve overall processing time.
質問 25. What are the advantages of using columnar storage in a data warehouse?
Columnar storage stores data by columns rather than rows, allowing for more efficient compression, better query performance, and improved analytics in a data warehouse.
Example:
Storing and querying large volumes of historical sales data more efficiently using columnar storage.
ユーザー評価で最も役立つ内容:
- What is a schema in the context of databases?
- Explain the concept of ETL in the context of data engineering.