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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2022/03/19 21:08:31 UTC
[GitHub] [hudi] nsivabalan commented on issue #4635: [SUPPORT] Bulk write failing due to hudi timeline archive exception
nsivabalan commented on issue #4635:
URL: https://github.com/apache/hudi/issues/4635#issuecomment-1073112112
sorry. could not get time to repro this. I don't have exp w/ pyspark. I just saved the script to rep.py and tried to execute the spark-submit. but running into failures.
```
:: resolution report :: resolve 255ms :: artifacts dl 5ms
:: modules in use:
org.apache.hudi#hudi-spark-bundle_2.11;0.10.1 from local-m2-cache in [default]
org.apache.spark#spark-avro_2.11;2.4.4 from local-m2-cache in [default]
org.spark-project.spark#unused;1.0.0 from local-m2-cache in [default]
---------------------------------------------------------------------
| | modules || artifacts |
| conf | number| search|dwnlded|evicted|| number|dwnlded|
---------------------------------------------------------------------
| default | 3 | 0 | 0 | 0 || 3 | 0 |
---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent-a3077db6-05fc-4539-ab07-7fcdba4e85ba
confs: [default]
0 artifacts copied, 3 already retrieved (0kB/5ms)
22/03/19 14:05:28 WARN Utils: Your hostname, Sivabalans-MacBook-Pro.local resolves to a loopback address: 127.0.0.1; using 192.168.1.5 instead (on interface en0)
22/03/19 14:05:28 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
22/03/19 14:05:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
File "/tmp/rep.py", line 26
'hoodie.write.lock.zookeeper.lock_key': f"{table_name}",
^
SyntaxError: invalid syntax
log4j:WARN No appenders could be found for logger (org.apache.spark.util.ShutdownHookManager).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
```
Or should I launch pyspark and run through the commands you have given above.
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