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

1. A Spark application suffers from too many small tasks due to excessive partitioning. How can this be fixed without a full shuffle?
Options:

A) Use the sortBy() transformation to reorganize the data
B) Use the coalesce() transformation with a lower number of partitions
C) Use the distinct() transformation to combine similar partitions
D) Use the repartition() transformation with a lower number of partitions

2. What is the risk associated with this operation when converting a large Pandas API on Spark DataFrame back to a Pandas DataFrame?

A) The operation will fail if the Pandas DataFrame exceeds 1000 rows
B) The operation will load all data into the driver's memory, potentially causing memory overflow
C) The conversion will automatically distribute the data across worker nodes
D) Data will be lost during conversion

3. A Spark engineer is troubleshooting a Spark application that has been encountering out-of-memory errors during execution. By reviewing the Spark driver logs, the engineer notices multiple "GC overhead limit exceeded" messages.
Which action should the engineer take to resolve this issue?

A) Modify the Spark configuration to disable garbage collection
B) Cache large DataFrames to persist them in memory.
C) Optimize the data processing logic by repartitioning the DataFrame.
D) Increase the memory allocated to the Spark Driver.

4. Which UDF implementation calculates the length of strings in a Spark DataFrame?

A) df.withColumn("length", spark.udf("len", StringType()))
B) spark.udf.register("stringLength", lambda s: len(s))
C) df.select(length(col("stringColumn")).alias("length"))
D) df.withColumn("length", udf(lambda s: len(s), StringType()))

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

Solutions: