Alan Jackoway created SPARK-36867:
-------------------------------------
Summary: Misleading Error Message with Invalid Column and Group By
Key: SPARK-36867
URL: https://issues.apache.org/jira/browse/SPARK-36867
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 3.1.2
Reporter: Alan Jackoway
When you run a query with an invalid column that also does a group by on a
constructed column, the error message you get back references a missing column
for the group by rather than the invalid column.
You can reproduce this in pyspark in 3.1.2 with the following code:
{code:python}
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("Group By Issue").getOrCreate()
data = spark.createDataFrame(
[("2021-09-15", 1), ("2021-09-16", 2), ("2021-09-17", 10), ("2021-09-18",
25), ("2021-09-19", 500), ("2021-09-20", 50), ("2021-09-21", 100)],
schema=["d", "v"]
)
data.createOrReplaceTempView("data")
# This is valid
spark.sql("select sum(v) as value, date(date_trunc('week', d)) as week from
data group by week").show()
# This is invalid because val is the wrong variable
spark.sql("select sum(val) as value, date(date_trunc('week', d)) as week from
data group by week").show()
{code}
The error message for the second spark.sql line is
{quote}
pyspark.sql.utils.AnalysisException: cannot resolve '`week`' given input
columns: [data.d, data.v]; line 1 pos 81;
'Aggregate ['week], ['sum('val) AS value#21, cast(date_trunc(week, cast(d#0 as
timestamp), Some(America/New_York)) as date) AS week#22]
+- SubqueryAlias data
+- LogicalRDD [d#0, v#1L], false
{quote}
but the actual problem is that I used the wrong variable name in a different
part of the query. Nothing is wrong with {{week}} in this case.
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