[jira] [Resolved] (SPARK-36934) Timestamp are written as array bytes.

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-36934?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-36934.
----------------------------------
    Resolution: Not A Problem

> Timestamp are written as array bytes.
> -------------------------------------
>
>                 Key: SPARK-36934
>                 URL: https://issues.apache.org/jira/browse/SPARK-36934
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, Spark Core
>    Affects Versions: 3.3.0
>            Reporter: Bjørn Jørgensen
>            Priority: Major
>
> This is tested with master build 04.10.21
> {code}
> df = ps.DataFrame({'year': ['2015-2-4', '2016-3-5'],
>                    'month': [2, 3],
>                    'day': [4, 5],
>                   'test': [1, 2]})  
> df["year"] = ps.to_datetime(df["year"]) 
> df.info() 
> <class 'pyspark.pandas.frame.DataFrame'> Int64Index: 2 entries, 0 to 1 Data columns (total 4 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 year 2 non-null datetime64 1 month 2 non-null int64 2 day 2 non-null int64 3 test 2 non-null int64 dtypes: datetime64(1), int64(3)  
> spark_df_date = df.to_spark() 
> spark_df_date.printSchema() 
> root
> |-- year: timestamp (nullable = true)
> |-- month: long (nullable = false)
> |-- day: long (nullable = false)
> |-- test: long (nullable = false)  
> spark_df_date.write.parquet("s3a://falk0509/spark_df_date.parquet")  
> {code}
> Load the files in to Apache drill I use docker apache/drill:master-openjdk-14  
> SELECT * FROM cp.`/data/spark_df_date.*`  
> It print's
> year
> {code}
> \x00\x00\x00\x00\x00\x00\x00\x00\xE2}%\x00
> \x00\x00\x00\x00\x00\x00\x00\x00m\x7F%\x00 
> {code}
>  
> The rest of the columns are ok.   
> So is this a spark problem or Apache drill? 



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