Databricks-Spark-Assoc Pandas API on Spark Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  from databricks import pandas as ps

  Why it's wrong here

  This is incorrect because there is no `pandas` module in the `databricks` package. Databricks provides its own utilities, but the Pandas API on Spark is part of PySpark. The correct import is `pyspark.pandas`. Using this incorrect import will raise an ImportError.

• ✓

  import pyspark.pandas as ps

  Why this is correct

  This is correct. The Pandas API on Spark is available in the `pyspark.pandas` module. Importing it as `ps` is a common convention. This provides access to functions like `ps.DataFrame`, `ps.read_csv`, etc., which mimic the pandas API but operate on Spark DataFrames for scalability.

• ✗

  from pyspark.sql import pandas as ps

  Why it's wrong here

  This is incorrect because there is no `pandas` submodule in `pyspark.sql`. The correct module is `pyspark.pandas`. Attempting this import will result in an ImportError. The Pandas API on Spark is separate from the SQL module, although it uses Spark SQL under the hood.

• ✗

  import pandas as ps

  Why it's wrong here

  This is incorrect because `import pandas as ps` imports the standard pandas library, which operates on local data and does not provide distributed computing capabilities. While the API is similar, it will not scale to large datasets and will fail with out-of-memory errors on big data.