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https://issues.apache.org/jira/browse/SPARK-34292?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-34292.
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Resolution: Duplicate
> NOW is interpreted as the NOW SQL function
> ------------------------------------------
>
> Key: SPARK-34292
> URL: https://issues.apache.org/jira/browse/SPARK-34292
> Project: Spark
> Issue Type: Bug
> Components: PySpark, Spark Core
> Affects Versions: 3.0.0
> Reporter: Gaelan Mines
> Priority: Major
>
> I think we ran into a bug in the Spark framework. Basically, the bug we
> caught is like this: when reading a data frame in Parquet format partitioned
> by a column, if the column contains values of “NOW”, NOW will be interpreted
> as the NOW function as in SQL, and returns the literal timestamp of NOW.
>
> Steps to reproduce:
> from pyspark.sql.session import SparkSession
> spark = SparkSession.builder.getOrCreate()
> df = spark.createDataFrame([['NOW', 1], ['THEN', 2]], schema=['Col1', 'Col2'])
> df.write.parquet('/tmp/my_partitioned_data', mode='overwrite',
> partitionBy=['Col1'])
> df_read_back = spark.read.parquet('/tmp/my_partitioned_data')
> """
> In [1]: df.show()
> +----+----+
> |Col1|Col2|
> +----+----+
> | NOW| 1|
> |THEN| 2|
> +----+----+
> In [2]: df_read_back.show()
> +----+--------------------+
> |Col2| Col1|
> +----+--------------------+
> | 1|2021-01-22 10:46:...|
> | 2| THEN|
> +----+--------------------+
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