PySpark超时异常

我在Google Dataproc上运行pySpark，我正在尝试大规模地使用网络图

这是我的配置

import pyspark
from pyspark.sql import SparkSession

conf = pyspark.SparkConf().setAll([('spark.jars', 'gs://spark-lib/bigquery/spark-bigquery-latest.jar'),
                                   ('spark.jars.packages', 'graphframes:graphframes:0.7.0-spark2.3-s_2.11')])

spark = SparkSession.builder \
  .appName('testing bq')\
  .config(conf=conf) \
  .getOrCreate()

然而，当我从网络图上的图帧运行“标签传播”算法时，由于超时，它总是返回Py4JJavaError

result = g_df.labelPropagation(maxIter=5)

错误：

Py4JJavaError: An error occurred while calling o287.run.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 197.0 failed 4 times, most recent failure: Lost task 0.3 in stage 197.0 (TID 7247, cluster-network-graph-w-7.c.geotab-bi.internal, executor 50): ExecutorLostFailure (executor 50 exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 127971 ms

---

如何从PySpark更改此超时参数？它会影响什么？

我认为它与默认为120秒的

spark.network.timeout

有关

所有网络交互的默认超时。如果未配置spark.core.connection.ack.wait.timeout、spark.storage.blockManagerSlaveTimeoutMs、spark.shuffle.io.connectionTimeout、spark.rpc.askTimeout或spark.rpc.lookupTimeout，则将使用此配置代替它们

看