Timeout error: Error with 400 StatusCode: “requirement failed: Session isn't active.”
I'm using Zeppelin v0.7.3
notebook to run Pyspark
scripts. In one paragraph, I am running script to write data from dataframe
to a parquet
file in a Blob folder. File is partitioned per country. Number of rows of dataframe is 99,452,829
. When the script reaches 1 hour
, an error is encountered -
Error with 400 StatusCode: "requirement failed: Session isn't
active.
My default interpreter for the notebook is jdbc
. I have read about timeoutlifecyclemanager
and added in the interpreter setting zeppelin.interpreter.lifecyclemanager.timeout.threshold
and set it to 7200000
but still encountered the error after it reaches 1 hour runtime at 33% processing completion.
I checked the Blob folder after the 1 hr timeout and parquet files were successfully written to Blob which are indeed partitioned per country.
The script I am running to write DF to parquet Blob is below:
trdpn_cntry_fct_denom_df.write.format("parquet").partitionBy("CNTRY_ID").mode("overwrite").save("wasbs://tradepanelpoc@blobasbackupx2066561.blob.core.windows.net/cbls/hdi/trdpn_cntry_fct_denom_df.parquet")
Is this Zeppelin timeout issue? How can it be extended for more than 1 hour runtime? Thanks for the help.
python apache-spark apache-zeppelin livy
add a comment |
I'm using Zeppelin v0.7.3
notebook to run Pyspark
scripts. In one paragraph, I am running script to write data from dataframe
to a parquet
file in a Blob folder. File is partitioned per country. Number of rows of dataframe is 99,452,829
. When the script reaches 1 hour
, an error is encountered -
Error with 400 StatusCode: "requirement failed: Session isn't
active.
My default interpreter for the notebook is jdbc
. I have read about timeoutlifecyclemanager
and added in the interpreter setting zeppelin.interpreter.lifecyclemanager.timeout.threshold
and set it to 7200000
but still encountered the error after it reaches 1 hour runtime at 33% processing completion.
I checked the Blob folder after the 1 hr timeout and parquet files were successfully written to Blob which are indeed partitioned per country.
The script I am running to write DF to parquet Blob is below:
trdpn_cntry_fct_denom_df.write.format("parquet").partitionBy("CNTRY_ID").mode("overwrite").save("wasbs://tradepanelpoc@blobasbackupx2066561.blob.core.windows.net/cbls/hdi/trdpn_cntry_fct_denom_df.parquet")
Is this Zeppelin timeout issue? How can it be extended for more than 1 hour runtime? Thanks for the help.
python apache-spark apache-zeppelin livy
add a comment |
I'm using Zeppelin v0.7.3
notebook to run Pyspark
scripts. In one paragraph, I am running script to write data from dataframe
to a parquet
file in a Blob folder. File is partitioned per country. Number of rows of dataframe is 99,452,829
. When the script reaches 1 hour
, an error is encountered -
Error with 400 StatusCode: "requirement failed: Session isn't
active.
My default interpreter for the notebook is jdbc
. I have read about timeoutlifecyclemanager
and added in the interpreter setting zeppelin.interpreter.lifecyclemanager.timeout.threshold
and set it to 7200000
but still encountered the error after it reaches 1 hour runtime at 33% processing completion.
I checked the Blob folder after the 1 hr timeout and parquet files were successfully written to Blob which are indeed partitioned per country.
The script I am running to write DF to parquet Blob is below:
trdpn_cntry_fct_denom_df.write.format("parquet").partitionBy("CNTRY_ID").mode("overwrite").save("wasbs://tradepanelpoc@blobasbackupx2066561.blob.core.windows.net/cbls/hdi/trdpn_cntry_fct_denom_df.parquet")
Is this Zeppelin timeout issue? How can it be extended for more than 1 hour runtime? Thanks for the help.
python apache-spark apache-zeppelin livy
I'm using Zeppelin v0.7.3
notebook to run Pyspark
scripts. In one paragraph, I am running script to write data from dataframe
to a parquet
file in a Blob folder. File is partitioned per country. Number of rows of dataframe is 99,452,829
. When the script reaches 1 hour
, an error is encountered -
Error with 400 StatusCode: "requirement failed: Session isn't
active.
My default interpreter for the notebook is jdbc
. I have read about timeoutlifecyclemanager
and added in the interpreter setting zeppelin.interpreter.lifecyclemanager.timeout.threshold
and set it to 7200000
but still encountered the error after it reaches 1 hour runtime at 33% processing completion.
I checked the Blob folder after the 1 hr timeout and parquet files were successfully written to Blob which are indeed partitioned per country.
The script I am running to write DF to parquet Blob is below:
trdpn_cntry_fct_denom_df.write.format("parquet").partitionBy("CNTRY_ID").mode("overwrite").save("wasbs://tradepanelpoc@blobasbackupx2066561.blob.core.windows.net/cbls/hdi/trdpn_cntry_fct_denom_df.parquet")
Is this Zeppelin timeout issue? How can it be extended for more than 1 hour runtime? Thanks for the help.
python apache-spark apache-zeppelin livy
python apache-spark apache-zeppelin livy
edited Nov 15 '18 at 5:49
Max Belousov
18918
18918
asked Nov 13 '18 at 7:14
user10644448user10644448
12
12
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
The timeout lifecycle manager is available since version 0.8.
Seems there is problem with pyspark. Try this solution
Pyspark socket timeout exception after application running for a while
add a comment |
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1 Answer
1
active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
The timeout lifecycle manager is available since version 0.8.
Seems there is problem with pyspark. Try this solution
Pyspark socket timeout exception after application running for a while
add a comment |
The timeout lifecycle manager is available since version 0.8.
Seems there is problem with pyspark. Try this solution
Pyspark socket timeout exception after application running for a while
add a comment |
The timeout lifecycle manager is available since version 0.8.
Seems there is problem with pyspark. Try this solution
Pyspark socket timeout exception after application running for a while
The timeout lifecycle manager is available since version 0.8.
Seems there is problem with pyspark. Try this solution
Pyspark socket timeout exception after application running for a while
answered Nov 14 '18 at 18:48
Max BelousovMax Belousov
18918
18918
add a comment |
add a comment |
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