CODEWITHSUNDEEP
pysparkapache-spark-sql
Praveen Mandadi
Praveen Mandadi

Reputation: 381

Not able to fetch all the columns while using groupby in pyspark

columnList = [item[0] for item in df1.dtypes if item[1].startswith('string')]

df2 = df1.groupBy("TCID",columnList).agg(mean("Runtime").alias("Runtime"))

While using like this I am getting the following error :

py4j.protocol.Py4JError: An error occurred while calling    z:org.apache.spark.sql.functions.col. Trace:
py4j.Py4JException: Method col([class java.util.ArrayList]) does not exist
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318)
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:339)
at py4j.Gateway.invoke(Gateway.java:274)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)

Upvotes: 2

Views: 2308

Answers (1)

pault
pault

Reputation: 43534

From the docs pyspark.sql.DataFrame.groupBy takes in a "list of columns to group by."

Your code fails because the second argument (columnList) isn't a valid column identifier. Hence the error: col([class java.util.ArrayList]) does not exist.

Instead you can do the following: 

df2 = df1.groupBy(["TCID"] + columnList).agg(mean("Runtime").alias("Runtime"))

Or equivalently, and easier to read IMO:

columnList = [item[0] for item in df1.dtypes if item[1].startswith('string')]
groupByColumns = ["TCID"] + columnList
df2 = df1.groupBy(groupByColumns).agg(mean("Runtime").alias("Runtime"))

Upvotes: 2

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