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A list comprehension is a concise way to create a list from an iterable in a single line of code. These four are Python’s core built-in data structures, and interviewers ask this question to see whether you choose the right tool for the job. We already have the host and the number of beds columns calculated in the previous steps. As a first step we need to find the total number of beds listed by each host. Let’s use this function and create another column by adding 2 more days to it since we need users who are active 3 consecutive days. Let’s select only those two columns and sort the data for each user and each date in the ascending order using sort_values() function from pandas.
- The entry-level data engineer interview questions focus on that loop.
- Avro is row-based and optimized for write-heavy streaming and handling complex schema evolution.
- The dict approach is the SQL ROW_NUMBER pattern in Python.
What are the best practices for https://uvik.io/ writing highly optimized PySpark code? What is predicate pushdown and how does it improve PySpark performance? What are PySpark’s main data sources for reading and writing data? How each scales for a traffic spike, orders keys and handles exactly-once If you already work with SQL and Python at your job, 2 months of evening practice is usually enough to start interviewing. A team running a petabyte-scale lakehouse on Databricks will absolutely ask about partitioning, skew, and the difference between a wide and narrow transformation.
First, groupby() splits the DataFrame into groups based on one or more columns. Grouping data in pandas follows a three-step pattern called Split → Apply → Combine. Df.append(), applymap(), and iteritems() are all gone, replaced by pd.concat(), DataFrame.map(), and .items(). Knowing them is a fast way to show you have actually upgraded a codebase rather than only read about one.
Once I had identified potential issues, I would then work with the appropriate teams to develop a plan for addressing them. This question can help the interviewer determine how you handle unexpected situations and whether your response shows that you have a plan for handling them. This question allows the interviewer to assess your experience with different types of data storage systems and how you apply them in your work.
Top 100+ Data Engineer Interview Questions and Answers
Preparing for data engineer interviews makes even the bravest of us anxious. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry. Has a sparse or non-existent portfolio of past projects.