Quentin Auge created SPARK-20227:
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Summary: Job hangs when joining a lot of aggregated columns
Key: SPARK-20227
URL: https://issues.apache.org/jira/browse/SPARK-20227
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0
Environment: AWS emr-5.4.0 m4.xlarge
Reporter: Quentin Auge
I'm trying to replace a lot of different columns in a dataframe with aggregates
of themselves, and then join the resulting dataframe.
{code:python}
# Create a dataframe with 1 row and 50 columns
n = 50
df = sc.parallelize([Row(*range(n))]).toDF()
cols = df.columns
# Replace each column values with aggregated values
window = Window.partitionBy(cols[0])
for col in cols[1:]:
df = df.withColumn(col, sum(col).over(window))
# Join
other_df = sc.parallelize([Row(0)]).toDF()
result = other_df.join(df, on = cols[0])
result.show()
{code}
The issue is, Spark hangs forever when executing the last line.
{code}
17/04/05 14:39:28 INFO ExecutorAllocationManager: Removing executor 1 because
it has been idle for 60 seconds (new desired total will be 0)
17/04/05 14:39:29 INFO YarnSchedulerBackend$YarnDriverEndpoint: Disabling
executor 1.
17/04/05 14:39:29 INFO DAGScheduler: Executor lost: 1 (epoch 0)
17/04/05 14:39:29 INFO BlockManagerMasterEndpoint: Trying to remove executor 1
from BlockManagerMaster.
17/04/05 14:39:29 INFO BlockManagerMasterEndpoint: Removing block manager
BlockManagerId(1, ip-172-30-0-149.ec2.internal, 35666, None)
17/04/05 14:39:29 INFO BlockManagerMaster: Removed 1 successfully in
removeExecutor
17/04/05 14:39:29 INFO YarnScheduler: Executor 1 on
ip-172-30-0-149.ec2.internal killed by driver.
17/04/05 14:39:29 INFO ExecutorAllocationManager: Existing executor 1 has been
removed (new total is 0)
{code}
All executors are inactive and thus killed after 60 seconds, the master spends
some CPU on a process that hangs indefinitely, and the workers are idle.
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