Spark Question: What happens in the memory when you collect() in Spark ?

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I know collect() is often not recommended for large datasets (because it can cause Java Out of Memory issue), but this is for learning what really going on in the background.

If you use Spark, you don’t really need to fully understand what’s going on in the background, memory. But this is important topic.

Example:

Suppose you write this code in PySpark. In the last line, you are doing collect().

Use Cases: It’s typically used for gathering small datasets or the final output of a data processing pipeline. It’s not recommended for large datasets.

# Example in PySpark
from pyspark.sql import SparkSession

# Initialize Spark Session
spark = SparkSession.builder.appName("Example").getOrCreate()

# Suppose emp_df is your distributed DataFrame containing employee data…