GuangFancui(ISCAS) created SPARK-21582:
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Summary: DataFrame.withColumnRenamed cause huge performance
overhead
Key: SPARK-21582
URL: https://issues.apache.org/jira/browse/SPARK-21582
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 2.1.0
Reporter: GuangFancui(ISCAS)
Table "item_feature" (DataFrame) has over 900 columns.
When I use
{code:java}
val nameSequeceExcept = Set("gid","category_name","merchant_id")
val df1 = spark.table("item_feature")
val newdf1 = df1.schema.map(_.name).filter(name =>
!nameSequeceExcept.contains(name)).foldLeft(df1)((df1, name) =>
df1.withColumnRenamed(name, name + "_1" ))
{code}
It took over 30 minutes.
*PID* in stack file is *0x126d*
It seems that _transform_ took too long time.
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