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Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:

1. In the code block below, aggDF contains aggregations on a streaming DataFrame:

Which output mode at line 3 ensures that the entire result table is written to the console during each trigger execution?

A) aggregate
B) complete
C) replace
D) append

2. 26 of 55.
A data scientist at an e-commerce company is working with user data obtained from its subscriber database and has stored the data in a DataFrame df_user.
Before further processing, the data scientist wants to create another DataFrame df_user_non_pii and store only the non-PII columns.
The PII columns in df_user are name, email, and birthdate.
Which code snippet can be used to meet this requirement?

A) df_user_non_pii = df_user.select("name", "email", "birthdate")
B) df_user_non_pii = df_user.dropFields("name", "email", "birthdate")
C) df_user_non_pii = df_user.drop("name", "email", "birthdate")
D) df_user_non_pii = df_user.remove("name", "email", "birthdate")

3. A data engineer replaces the exact percentile() function with approx_percentile() to improve performance, but the results are drifting too far from expected values.
Which change should be made to solve the issue?

A) Decrease the first value of the percentage parameter to increase the accuracy of the percentile ranges
B) Increase the last value of the percentage parameter to increase the accuracy of the percentile ranges
C) Increase the value of the accuracy parameter in order to increase the memory usage but also improve the accuracy
D) Decrease the value of the accuracy parameter in order to decrease the memory usage but also improve the accuracy

4. 3 of 55. A data engineer observes that the upstream streaming source feeds the event table frequently and sends duplicate records. Upon analyzing the current production table, the data engineer found that the time difference in the event_timestamp column of the duplicate records is, at most, 30 minutes.
To remove the duplicates, the engineer adds the code:
df = df.withWatermark("event_timestamp", "30 minutes")
What is the result?

A) It removes duplicates that arrive within the 30-minute window specified by the watermark.
B) It removes all duplicates regardless of when they arrive.
C) It is not able to handle deduplication in this scenario.
D) It accepts watermarks in seconds and the code results in an error.

5. 9 of 55.
Given the code fragment:
import pyspark.pandas as ps
pdf = ps.DataFrame(data)
Which method is used to convert a Pandas API on Spark DataFrame (pyspark.pandas.DataFrame) into a standard PySpark DataFrame (pyspark.sql.DataFrame)?

A) pdf.to_dataframe()
B) pdf.spark()
C) pdf.to_pandas()
D) pdf.to_spark()

Solutions: