Open yohei1126 opened 3 years ago
This combination works.
import pydeequ
from pydeequ.repository import *
pydeequ.__version__
--
Starting Spark application
1.0.1
This combination did not work
import pydeequ
from pydeequ.repository import *
pydeequ.__version__
---
The code failed because of a fatal error:
Session 0 unexpectedly reached final status 'dead'. See logs:
stdout:
stderr:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/share/aws/glue/etl/jars/glue-assembly.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/lib/spark/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
This issue https://github.com/awslabs/deequ/issues/372 was just closed 8 days ago so my guess is that a new release of pydeequ that supports Spark 3.1.x will be coming soon.
When is 3.1 support coming?
This is not a bug or feature report.
I am going to use pydeequ on Glue Notebook instance.