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Posted to issues@spark.apache.org by "shaharlewy@gmail.com (Jira)" <ji...@apache.org> on 2022/06/14 07:22:00 UTC
[jira] [Updated] (SPARK-39302) Spark SQL - wrong field selection in group by
[ https://issues.apache.org/jira/browse/SPARK-39302?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
shaharlewy@gmail.com updated SPARK-39302:
-----------------------------------------
Description:
SQL parser select wrong field to group by.
See following example.
Sample data:
{code:java}
spark.sql("""
select "US" as pv_countryCode
union all
select "IL" as pv_countryCode
""").createOrReplaceTempView("my_test_data")
spark.sql("""
select -3 as id, "US" as countryCode
""").createOrReplaceTempView("country_codes_sample")
{code}
code:
{code:java}
spark.sql("""
WITH BASE
(SELECT
pv_countryCode AS country_id
FROM my_test_data)
SELECT
COALESCE(cct.id, -3) as country_id,
count(1) as count
FROM BASE
LEFT JOIN country_codes_sample cct ON cct.countryCode = country_id
GROUP BY
country_id
""").createOrReplaceTempView("campaign_country_bug") {code}
Error:
{code:java}
org.apache.spark.sql.AnalysisException: expression 'cct.`id`' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() (or first_value) if you don't care which value you get.;
Aggregate [country_id#910], [coalesce(id#886, -3) AS country_id#908, count(1) AS count#909L]
+- Join LeftOuter, (countryCode#887 = country_id#910)
:- SubqueryAlias BASE
: +- Project [pv_countryCode#883 AS country_id#910]
: +- SubqueryAlias my_test_data
: +- Union false, false
: :- Project [US AS pv_countryCode#883]
: : +- OneRowRelation
: +- Project [IL AS pv_countryCode#884]
: +- OneRowRelation
+- SubqueryAlias cct
+- SubqueryAlias country_codes_sample
+- Project [-3 AS id#886, US AS countryCode#887]
+- OneRowRelation {code}
I expected Spark to choose the selected country_id(country_id#908) instead of country_id#910
Or at least throw ambiguous exception when grouping by `country_id`.
This lead developers to add `cct.id` into group by which results in unexpected results.
(In case country_id has both null and -3 values)
was:
SQL parser select wrong field to group by.
See following example.
Sample data:
{code:java}
spark.sql("""
select "US" as pv_countryCode
union all
select "IL" as pv_countryCode
""").createOrReplaceTempView("my_test_data")
spark.sql("""
select -3 as id, "US" as countryCode
""").createOrReplaceTempView("country_codes_sample")
{code}
code:
{code:java}
spark.sql("""
select "US" as pv_countryCode
union all
select "IL" as pv_countryCode
""").createOrReplaceTempView("my_test_data")
spark.sql("""
select -3 as id, "US" as countryCode
""").createOrReplaceTempView("country_codes_sample")
{code}
Error:
{code:java}
org.apache.spark.sql.AnalysisException: expression 'cct.`id`' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() (or first_value) if you don't care which value you get.;
Aggregate [country_id#910], [coalesce(id#886, -3) AS country_id#908, count(1) AS count#909L]
+- Join LeftOuter, (countryCode#887 = country_id#910)
:- SubqueryAlias BASE
: +- Project [pv_countryCode#883 AS country_id#910]
: +- SubqueryAlias my_test_data
: +- Union false, false
: :- Project [US AS pv_countryCode#883]
: : +- OneRowRelation
: +- Project [IL AS pv_countryCode#884]
: +- OneRowRelation
+- SubqueryAlias cct
+- SubqueryAlias country_codes_sample
+- Project [-3 AS id#886, US AS countryCode#887]
+- OneRowRelation {code}
I expected Spark to choose the selected country_id(country_id#908) instead of country_id#910
Or at least throw ambiguous exception when grouping by `country_id`.
This lead developers to add `cct.id` into group by which results in unexpected results.
(In case country_id has both null and -3 values)
> Spark SQL - wrong field selection in group by
> ---------------------------------------------
>
> Key: SPARK-39302
> URL: https://issues.apache.org/jira/browse/SPARK-39302
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.2
> Reporter: shaharlewy@gmail.com
> Priority: Minor
>
> SQL parser select wrong field to group by.
> See following example.
> Sample data:
>
> {code:java}
> spark.sql("""
> select "US" as pv_countryCode
> union all
> select "IL" as pv_countryCode
> """).createOrReplaceTempView("my_test_data")
> spark.sql("""
> select -3 as id, "US" as countryCode
> """).createOrReplaceTempView("country_codes_sample")
> {code}
> code:
> {code:java}
>
> spark.sql("""
> WITH BASE
> (SELECT
> pv_countryCode AS country_id
> FROM my_test_data)
> SELECT
> COALESCE(cct.id, -3) as country_id,
> count(1) as count
> FROM BASE
> LEFT JOIN country_codes_sample cct ON cct.countryCode = country_id
> GROUP BY
> country_id
> """).createOrReplaceTempView("campaign_country_bug") {code}
> Error:
> {code:java}
> org.apache.spark.sql.AnalysisException: expression 'cct.`id`' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() (or first_value) if you don't care which value you get.;
> Aggregate [country_id#910], [coalesce(id#886, -3) AS country_id#908, count(1) AS count#909L]
> +- Join LeftOuter, (countryCode#887 = country_id#910)
> :- SubqueryAlias BASE
> : +- Project [pv_countryCode#883 AS country_id#910]
> : +- SubqueryAlias my_test_data
> : +- Union false, false
> : :- Project [US AS pv_countryCode#883]
> : : +- OneRowRelation
> : +- Project [IL AS pv_countryCode#884]
> : +- OneRowRelation
> +- SubqueryAlias cct
> +- SubqueryAlias country_codes_sample
> +- Project [-3 AS id#886, US AS countryCode#887]
> +- OneRowRelation {code}
> I expected Spark to choose the selected country_id(country_id#908) instead of country_id#910
> Or at least throw ambiguous exception when grouping by `country_id`.
> This lead developers to add `cct.id` into group by which results in unexpected results.
> (In case country_id has both null and -3 values)
>
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