[jira] [Commented] (CARBONDATA-2661) Query failed with group by column when MV Datamap created without group by column

[Akash R Nilugal (Jira)]

    [ https://issues.apache.org/jira/browse/CARBONDATA-2661?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16536938#comment-16536938 ]

Ravindra Pesala commented on CARBONDATA-2661:
---------------------------------------------

It is duplicated to Jira 2568 , please close it

> Query failed with group by column when MV Datamap created without group by column
> ---------------------------------------------------------------------------------
>
>                 Key: CARBONDATA-2661
>                 URL: https://issues.apache.org/jira/browse/CARBONDATA-2661
>             Project: CarbonData
>          Issue Type: Bug
>            Reporter: xubo245
>            Assignee: xubo245
>            Priority: Major
>
> {code:java}
> drop table if exists fact_table1;
> CREATE TABLE fact_table1 (empno int, empname String, designation String, doj Timestamp,
> workgroupcategory int, workgroupcategoryname String, deptno int, deptname String,
> projectcode int, projectjoindate Timestamp, projectenddate Timestamp,attendance int,
> utilization int,salary int)
> STORED BY 'org.apache.carbondata.format';
>  
>   LOAD DATA local inpath 'hdfs://hacluster/user/hive/warehouse//data_mv.csv' INTO TABLE fact_table1 OPTIONS('DELIMITER'= ',', 'QUOTECHAR'= '"','timestampformat'='dd-MM-yyyy');
>  
>   LOAD DATA local inpath 'hdfs://hacluster/user/hive/warehouse//data_mv.csv' INTO TABLE fact_table1 OPTIONS('DELIMITER'= ',', 'QUOTECHAR'= '"','timestampformat'='dd-MM-yyyy');
> 0: jdbc:hive2://hadoop1:10000> create datamap mv1 using 'mv' as select sum(salary),count(empno) from fact_table1 group by empname;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.399 seconds)
> 0: jdbc:hive2://hadoop1:10000> rebuild datamap mv1;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (1.57 seconds)
> 0: jdbc:hive2://hadoop1:10000> create datamap mv2 using 'mv' as select sum(salary) from fact_table1 group by empname;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.321 seconds)
> 0: jdbc:hive2://hadoop1:10000> rebuild datamap mv2;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (1.241 seconds)
> 0: jdbc:hive2://hadoop1:10000> show datamap on table fact_table1;
> +--------------+------------+--------------------------+--+
> | DataMapName  | ClassName  |     Associated Table     |
> +--------------+------------+--------------------------+--+
> | datamap25    | mv         | default.datamap25_table  |
> | mv1          | mv         | default.mv1_table        |
> | mv2          | mv         | default.mv2_table        |
> +--------------+------------+--------------------------+--+
> 3 rows selected (0.047 seconds)
> 0: jdbc:hive2://hadoop1:10000> select * from default.mv1_table;
> +-------------+--------------+--+
> | sum_salary  | count_empno  |
> +-------------+--------------+--+
> | 172332      | 18           |
> | 162972      | 18           |
> | 90720       | 18           |
> | 202572      | 18           |
> | 90720       | 18           |
> | 128232      | 18           |
> | 130410      | 18           |
> | 202464      | 18           |
> | 243846      | 18           |
> | 238410      | 18           |
> +-------------+--------------+--+
> 10 rows selected (0.314 seconds)
> 0: jdbc:hive2://hadoop1:10000> select count(*) from default.mv1_table;
> +-----------+--+
> | count(1)  |
> +-----------+--+
> | 10        |
> +-----------+--+
> 1 row selected (0.139 seconds)
> 0: jdbc:hive2://hadoop1:10000> select * from default.mv2_table;
> +-------------+--+
> | sum_salary  |
> +-------------+--+
> | 172332      |
> | 162972      |
> | 90720       |
> | 202464      |
> | 243846      |
> | 128232      |
> | 130410      |
> | 90720       |
> | 202572      |
> | 238410      |
> +-------------+--+
> 10 rows selected (0.262 seconds)
> 0: jdbc:hive2://hadoop1:10000> explain select sum(salary) from fact_table1 group by empname;
> +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
> |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            plan                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
> +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
> | == CarbonData Profiler ==
> Table Scan on fact_table1
>  - total blocklets: 2
>  - filter: none
>  - pruned by Main DataMap
>     - skipped blocklets: 0
>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
> | == Physical Plan ==
> *HashAggregate(keys=[empname#2499], functions=[sum(cast(salary#2511 as bigint))])
> +- Exchange hashpartitioning(empname#2499, 200)
>    +- *HashAggregate(keys=[empname#2499], functions=[partial_sum(cast(salary#2511 as bigint))])
>       +- *BatchedScan CarbonDatasourceHadoopRelation [ Database name :default, Table name :fact_table1, Schema :Some(StructType(StructField(empno,IntegerType,true), StructField(empname,StringType,true), StructField(designation,StringType,true), StructField(doj,TimestampType,true), StructField(workgroupcategory,IntegerType,true), StructField(workgroupcategoryname,StringType,true), StructField(deptno,IntegerType,true), StructField(deptname,StringType,true), StructField(projectcode,IntegerType,true), StructField(projectjoindate,TimestampType,true), StructField(projectenddate,TimestampType,true), StructField(attendance,IntegerType,true), StructField(utilization,IntegerType,true), StructField(salary,IntegerType,true))) ] default.fact_table1[empname#2499,salary#2511]  |
> +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
> 2 rows selected (0.164 seconds)
> 0: jdbc:hive2://hadoop1:10000> explain select empname,sum(salary) from fact_table1 group by empname;
> Error: org.apache.spark.sql.AnalysisException: cannot resolve '`fact_table1.empname`' given input columns: [sum_salary, count_empno]; line 6 pos 11;
> 'Aggregate ['fact_table1.empname], ['fact_table1.empname, 'sum('gen_subsumer_0.sum(salary)) AS sum(salary)#2802]
> +- 'SubqueryAlias gen_subsumer_0
>    +- 'Aggregate ['fact_table1.empname], [sum(sum_salary#2495L) AS sum(salary)#2800L, sum(count_empno#2496L) AS count(empno)#2801L]
>       +- SubqueryAlias mv1_table
>          +- Relation[sum_salary#2495L,count_empno#2496L] CarbonDatasourceHadoopRelation [ Database name :default, Table name :mv1_table, Schema :Some(StructType(StructField(sum_salary,LongType,true), StructField(count_empno,LongType,true))) ] (state=,code=0)
> 0: jdbc:hive2://hadoop1:10000> create datamap mv3 using 'mv' as select empname,sum(salary) from fact_table1 group by empname;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.318 seconds)
> 0: jdbc:hive2://hadoop1:10000> rebuild datamap mv3;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (1.437 seconds)
> 0: jdbc:hive2://hadoop1:10000> drop datamap mv3;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.941 seconds)
> 0: jdbc:hive2://hadoop1:10000> create datamap mv3 using 'mv' as select empname,sum(salary),count(empno) from fact_table1 group by empname;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.537 seconds)
> 0: jdbc:hive2://hadoop1:10000> create datamap mv4 using 'mv' as select empname,sum(salary) from fact_table1 group by empname;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.271 seconds)
> 0: jdbc:hive2://hadoop1:10000> rebuild datamap mv3;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (1.525 seconds)
> 0: jdbc:hive2://hadoop1:10000> rebuild datamap mv4;
> +---------+--+
> | Result  |
> +---------+--+
> +---------+--+
> No rows selected (0.993 seconds)
> 0: jdbc:hive2://hadoop1:10000> explain select empname,sum(salary) from fact_table1 group by empname;
> Error: org.apache.spark.sql.AnalysisException: cannot resolve '`fact_table1.empname`' given input columns: [sum_salary, count_empno]; line 6 pos 11;
> 'Aggregate ['fact_table1.empname], ['fact_table1.empname, 'sum('gen_subsumer_0.sum(salary)) AS sum(salary)#3113]
> +- 'SubqueryAlias gen_subsumer_0
>    +- 'Aggregate ['fact_table1.empname], [sum(sum_salary#2495L) AS sum(salary)#3111L, sum(count_empno#2496L) AS count(empno)#3112L]
>       +- SubqueryAlias mv1_table
>          +- Relation[sum_salary#2495L,count_empno#2496L] CarbonDatasourceHadoopRelation [ Database name :default, Table name :mv1_table, Schema :Some(StructType(StructField(sum_salary,LongType,true), StructField(count_empno,LongType,true))) ] (state=,code=0)
> {code}

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