he ExecutorLostFailure error in Spark indicates that an executor was lost during the execution of a task. Review the driver logs for any WARN or ERROR messages that might provide more context about why the executor was lost. Also, Ensure that the executors have sufficient resources (memory, CPU) to handle the workload. Review the cluster configuration to ensure that it is optimized for the workload. If needed, Consider increasing the spark.executor.heartbeatInterval and spark.network.timeout settings to allow more time for executors to report back to the driver
