👀 Views: 92 💬 Answers: 1 📅 Created: 2025-06-14

apache-spark spark-streaming state-management scala

I'm stuck trying to I'm performance testing and I'm prototyping a solution and I'm currently working with Apache Spark 3.4.1 and facing challenges with managing state in a structured streaming application. Specifically, I am trying to perform a stateful aggregation on a streaming DataFrame that processes user events in real-time. My goal is to maintain a running total of events per user while handling late arrivals efficiently. Here’s a snippet of my code: ```scala import org.apache.spark.sql.SparkSession import org.apache.spark.sql.streaming.Trigger val spark = SparkSession.builder() .appName("UserEventAggregation") .getOrCreate() import spark.implicits._ val userEvents = spark.readStream .format("json") .option("path", "/path/to/events") .load() val aggregatedEvents = userEvents .groupByKey(event => event.getString("userId")) .mapGroupsWithState(StateSpec.function((key: String, value: Option[UserEvent], state: GroupState[UserTotal]) => { val total = state.getOption.map(_.total).getOrElse(0) + value.map(_.amount).getOrElse(0) state.update(UserTotal(total)) UserTotal(total) })) val query = aggregatedEvents.writeStream .outputMode("update") .format("console") .trigger(Trigger.ProcessingTime("10 seconds")) .start() query.awaitTermination() ``` However, I’m noticing that the state is accumulating indefinitely, and the application is hitting memory limits. The Spark UI shows that the state size grows significantly over time, leading to `java.lang.OutOfMemoryError: Java heap space` errors. I’ve tried adjusting the `spark.sql.streaming.stateStore.maintenance.interval` and `spark.sql.streaming.stateStore.rolldown.interval`, but it hasn't helped in reducing the memory usage. Also, I have set the watermark using `withWatermark("timestamp", "10 minutes")`, yet it seems ineffective as the state continues to grow. Could someone provide insights on best practices for managing state in structured streaming, particularly around stateful aggregations? Are there any specific configurations or optimizations you would recommend to prevent excessive memory usage? My development environment is Debian. I'd really appreciate any guidance on this. What's the correct way to implement this? Thanks for taking the time to read this!