Unix time stamp conversion in Azure synapse analytics - azure-synapse

Question

I am using the below script to do refining the data in silver layer:
# Read from existing internal table
dfAsset =(spark.read.option(Constants.SERVER,"xyz.sql.azuresynapse.net")
.synapsesql("abc.Salesforce.Asset")
.select("Id","ContactId","CreatedDate","CreatedById","LastModifiedDate")
.filter(col("productCode").contains("11061164")).limit(10))
dfAsset.show()
For particular column CreatedDate the data is appearing in the Unix format.Please refer
the below :
CreateDate
1652108980000
1632313243000
1632312269000
1632312410000
I need to convert the data into YYYY-MM-DD. In the above script
Please advise how it can be done.
Regards
RK

Answer 1

This is my sample Dataframe saved in the variable dfAsset.
#+-----------+
#| date1 |
#+-----------+
#|16521089 |
#|16323132 |
#|16323122 |
#|16323124 |
#+-----------+
Using below code you can convert the data into YYYY-MM-DD.
from pyspark.sql.types import TimestampType
from pyspark.sql.functions import col,to_date
df = dfAsset.withColumn('date',to_date(col('date1').cast(TimestampType())))
df.show()
Output: