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https://issues.apache.org/jira/browse/SPARK-28411?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Maria Rebelka updated SPARK-28411:
----------------------------------
Description:
The df.write.mode("overwrite").insertInto("table") has inconsistent behaviour
between Scala and Python. In Python, insertInto ignores "mode" parameter and
appends by default. Only when changing syntax to df.write.insertInto("table",
overwrite=True) we get expected behaviour.
This is a native Spark syntax, expected to be the same between languages...
Also, in other write methods, like saveAsTable or write.parquet "mode" seem to
be respected.
Reproduce, Python, ignore "overwrite":
{code:java}
df = spark.createDataFrame(sc.parallelize([(1, 2),(3,4)]),['i','j'])
# create the table and load data
df.write.saveAsTable("spark_overwrite_issue")
# insert overwrite, expected result - 2 rows
df.write.mode("overwrite").insertInto("spark_overwrite_issue")
spark.sql("select * from spark_overwrite_issue").count()
# result - 4 rows, insert appended data instead of overwrite{code}
Reproduce, Scala, works as expected:
{code:java}
val df = Seq((1, 2),(3,4)).toDF("i","j")
df.write.mode("overwrite").insertInto("spark_overwrite_issue")
spark.sql("select * from spark_overwrite_issue").count()
# result - 2 rows{code}
Tested on Spark 2.2.1 (EMR) and 2.4.0 (Databricks)
was:
The df.write.mode("overwrite").insertInto("table") has inconsistent behaviour
between Scala and Python. In Python, insertInto ignores "mode" parameter and
appends by default. Only when changing syntax to df.write.insertInto("table",
overwrite=True) we get expected behaviour.
This is a native Spark syntax, expected to be the same between languages...
Also, in other write methods, like saveAsTable or write.parquet "mode" seem to
be respected.
Reproduce, Python, ignore "overwrite":
{{}}
{code:java}
df = spark.createDataFrame(sc.parallelize([(1, 2),(3,4)]),['i','j'])
# create the table and load data
df.write.saveAsTable("spark_overwrite_issue")
# insert overwrite, expected result - 2 rows
df.write.mode("overwrite").insertInto("spark_overwrite_issue")
spark.sql("select * from spark_overwrite_issue").count()
# result - 4 rows, insert appended data instead of overwrite{code}
Reproduce, Scala, works as expected:
{code:java}
val df = Seq((1, 2),(3,4)).toDF("i","j")
df.write.mode("overwrite").insertInto("spark_overwrite_issue")
spark.sql("select * from spark_overwrite_issue").count()
# result - 2 rows{code}
Tested on Spark 2.2.1 (EMR) and 2.4.0 (Databricks)
> insertInto with overwrite inconsistent behaviour Python/Scala
> -------------------------------------------------------------
>
> Key: SPARK-28411
> URL: https://issues.apache.org/jira/browse/SPARK-28411
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 2.2.1, 2.4.0
> Reporter: Maria Rebelka
> Priority: Minor
>
> The df.write.mode("overwrite").insertInto("table") has inconsistent behaviour
> between Scala and Python. In Python, insertInto ignores "mode" parameter and
> appends by default. Only when changing syntax to df.write.insertInto("table",
> overwrite=True) we get expected behaviour.
> This is a native Spark syntax, expected to be the same between languages...
> Also, in other write methods, like saveAsTable or write.parquet "mode" seem
> to be respected.
> Reproduce, Python, ignore "overwrite":
> {code:java}
> df = spark.createDataFrame(sc.parallelize([(1, 2),(3,4)]),['i','j'])
> # create the table and load data
> df.write.saveAsTable("spark_overwrite_issue")
> # insert overwrite, expected result - 2 rows
> df.write.mode("overwrite").insertInto("spark_overwrite_issue")
> spark.sql("select * from spark_overwrite_issue").count()
> # result - 4 rows, insert appended data instead of overwrite{code}
> Reproduce, Scala, works as expected:
> {code:java}
> val df = Seq((1, 2),(3,4)).toDF("i","j")
> df.write.mode("overwrite").insertInto("spark_overwrite_issue")
> spark.sql("select * from spark_overwrite_issue").count()
> # result - 2 rows{code}
> Tested on Spark 2.2.1 (EMR) and 2.4.0 (Databricks)
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