Rohan Barman created SPARK-40835:
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Summary: to_utc_timestamp creates null column
Key: SPARK-40835
URL: https://issues.apache.org/jira/browse/SPARK-40835
Project: Spark
Issue Type: Bug
Components: PySpark
Affects Versions: 3.2.0
Reporter: Rohan Barman
We are in the process of migrating our PySpark applications from Spark version
3.1.2 to Spark version 3.2.0.
This bug is present in version 3.2.0. We do not see this issue in version 3.1.2.
*Minimal example to reproduce bug*
Below is a minimal example.
from pyspark.sql.types import StringType
from pyspark.sql.functions import *
# Source data
columns = ["id","timestamp_field"]
data = [("1", "2022-10-16T00:00:00.000+0000"), ("2",
"2022-10-16T00:00:00.000+0000")]
source_df = spark.createDataFrame(data).toDF(*columns)
source_df.createOrReplaceTempView("source")
print("Source:")
print(source_df.show())
# Execute query
query = """
SELECT
id,
timestamp_field as original,
to_utc_timestamp(timestamp_field, 'UTC') AS received_timestamp
FROM source
"""
df = spark.sql(query)
print("Transformed:")
print(df.show())
print(df.count())
*Post Execution*
The source data has a column called _timestamp_field_ which is a string type.
{code:java}
Source:
+---+--------------------+
| id| timestamp_field|
+---+--------------------+
| 1|2022-10-16T00:00:...|
| 2|2022-10-16T00:00:...|
+---+--------------------+ {code}
The query applies to_utc_timestamp() on timestamp_field. The result column is
null.
{code:java}
+---+--------------------+------------------+
| id| original|received_timestamp|
+---+--------------------+------------------+
| 1|2022-10-16T00:00:...| null|
| 2|2022-10-16T00:00:...| null|
+---+--------------------+------------------+ {code}
--
*Questions*
* Did the to_utc_timestamp function get any new changes in spark version
3.2.0? We don't see this issue in spark 3.1.2
* Can we apply any spark settings to resolve this?
* Is there a new preferred function in spark 3.2.0 that replaces
to_utc_timestamp?
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