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Databricks Clusters on GCP stop working "Environment directory not found" issue - waitForEnvironmentFileSystem

720677
New Contributor III

Starting from yesterday 17/5/2022 i start getting errors while running notebooks or jobs on clusters of Databricks GCP.

The error is:

SparkException: Environment directory not found at /local_disk0/.ephemeral_nfs/cluster_libraries/python

The job/notebooks can do some of the operations but some of the operations like:

display(dbutils.fs.ls("/%s" % mount_name))

I tried to start a new cluster. I tried to reduce any init scripts.

The full error:

22/05/18 05:30:09 WARN TaskSetManager: Lost task 3.0 in stage 0.0 (TID 3) (10.71.1.3 executor 0): org.apache.spark.SparkException: Environment directory not found at /local_disk0/.ephemeral_nfs/cluster_libraries/python

at org.apache.spark.util.DatabricksUtils$.waitForEnvironmentFileSystem(DatabricksUtils.scala:685)

at org.apache.spark.api.python.PythonWorkerFactory.$anonfun$startDaemon$1(PythonWorkerFactory.scala:273)

at org.apache.spark.api.python.PythonWorkerFactory.$anonfun$startDaemon$1$adapted(PythonWorkerFactory.scala:273)

at scala.Option.foreach(Option.scala:407)

at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:273)

at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:185)

at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:134)

at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:209)

at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:251)

at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:77)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.sql.execution.SQLExecutionRDD.$anonfun$compute$1(SQLExecutionRDD.scala:57)

at org.apache.spark.sql.internal.SQLConf$.withExistingConf(SQLConf.scala:170)

at org.apache.spark.sql.execution.SQLExecutionRDD.compute(SQLExecutionRDD.scala:57)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)

at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)

at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)

at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$3(ResultTask.scala:75)

at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)

at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$1(ResultTask.scala:75)

at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)

at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:55)

at org.apache.spark.scheduler.Task.doRunTask(Task.scala:156)

at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:125)

at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)

at org.apache.spark.scheduler.Task.run(Task.scala:95)

at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:826)

at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1670)

at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:829)

at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)

at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)

at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:684)

at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)

at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)

at java.lang.Thread.run(Thread.java:748)

1 ACCEPTED SOLUTION

Accepted Solutions

720677
New Contributor III

Databricks supports detected an issue with the NFS mounts on GCP.

Looks like DBR 10.X versions were affected.

After several hours they fixed it and now the same clusters are back to normal.

View solution in original post

1 REPLY 1

720677
New Contributor III

Databricks supports detected an issue with the NFS mounts on GCP.

Looks like DBR 10.X versions were affected.

After several hours they fixed it and now the same clusters are back to normal.

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