Apache Spark 3.4.1 - Performance Degradation When Using Broadcast Join with Large Datasets
I'm optimizing some code but I'm a bit lost with I've been working on this all day and I'm currently working with Apache Spark 3.4.1 and working with important performance optimization when trying to implement a broadcast join between two large datasets... My goal is to join a relatively smaller DataFrame (let's call it `df_small`) with a much larger DataFrame (`df_large`) to improve query performance by leveraging the broadcast join feature. I have ensured that `df_small` is small enough to be broadcasted, yet the job seems to take an unusually long time to execute. Here’s the code I’m using to perform the join: ```scala val df_small = spark.read.format("csv").option("header", "true").load("path/to/small_dataset.csv") val df_large = spark.read.format("parquet").load("path/to/large_dataset.parquet") val broadcasted_small = broadcast(df_small) val result = df_large.join(broadcasted_small, "join_key") result.write.mode("overwrite").parquet("path/to/output_dataset.parquet") ``` However, I've noticed that the performance is still subpar, and I frequently see warnings in the logs like: ``` INFO SparkContext: Broadcast variable with ID x has been removed INFO Executor: Failed to send broadcast variable x ``` I've tried adjusting the size of the broadcast threshold by setting `spark.sql.autoBroadcastJoinThreshold` to a higher value (e.g., `10485760` bytes) to see if that helps, but the question continues. Additionally, I verified that both DataFrames have the correct schema and data types for the join key. To debug further, I enabled the Spark UI and found that the shuffle operations seem to take up a important amount of time, even though I expected the broadcast join to minimize shuffling. My Spark configuration includes optimizations like `spark.sql.shuffle.partitions` set to 200 and `spark.sql.execution.arrow.pyspark.enabled` set to true. Is there any other configuration or approach I might be overlooking that could help improve the performance of the broadcast join? Any insights or recommendations would be greatly appreciated! I recently upgraded to Scala 3.10. I'd love to hear your thoughts on this. Is there a better approach? What are your experiences with this?