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From "Chun Chang (JIRA)" <j...@apache.org>
Subject [jira] [Created] (DRILL-3062) regression: Mondrian query447.q - lots of rows missing in result set
Date Wed, 13 May 2015 19:08:00 GMT
Chun Chang created DRILL-3062:
---------------------------------

             Summary: regression: Mondrian query447.q - lots of rows missing in result set
                 Key: DRILL-3062
                 URL: https://issues.apache.org/jira/browse/DRILL-3062
             Project: Apache Drill
          Issue Type: Bug
          Components: Execution - Data Types
    Affects Versions: 1.0.0
            Reporter: Chun Chang
            Assignee: Daniel Barclay (Drill)
            Priority: Blocker


{code}
0: jdbc:drill:schema=dfs.drillTestDirComplexJ> select * from sys.version;
+------------+----------------+-------------+-------------+------------+
| commit_id  | commit_message | commit_time | build_email | build_time |
+------------+----------------+-------------+-------------+------------+
| d1526f9462f6817a76631464ff332bb99b3bdf28 | DRILL-2750: Running 1 or more queries against
Drillbits having insufficient DirectMem renders the Drillbits in an unusable state | 13.05.2015
@ 08:47:20 EDT | Unknown     | 13.05.2015 @ 10:44:43 EDT |
+------------+----------------+-------------+-------------+------------+
{code}

Many (total of 42) mondrian queries regressed. All of them missing rows in the returned result
set.

Here is an example, query447.q

{code}
SELECT time_by_day.the_year            AS c0, 
       product_class.product_family    AS c1, 
       customer.state_province         AS c2, 
       customer.city                   AS c3, 
       Sum(sales_fact_1997.unit_sales) AS m0 
FROM   time_by_day AS time_by_day, 
       sales_fact_1997 AS sales_fact_1997, 
       product_class AS product_class, 
       product AS product, 
       customer AS customer 
WHERE  sales_fact_1997.time_id = time_by_day.time_id 
       AND time_by_day.the_year = 1997 
       AND sales_fact_1997.product_id = product.product_id 
       AND product.product_class_id = product_class.product_class_id 
       AND product_class.product_family = 'Drink' 
       AND sales_fact_1997.customer_id = customer.customer_id 
       AND customer.state_province = 'WA' 
       AND customer.city IN ( 'Anacortes', 'Ballard', 'Bellingham', 'Bremerton', 
                              'Burien', 'Edmonds', 'Everett', 'Issaquah', 
                              'Kirkland', 'Lynnwood', 'Marysville', 'Olympia', 
                              'Port Orchard', 'Puyallup', 'Redmond', 'Renton', 
                              'Seattle', 'Sedro Woolley', 'Spokane', 'Tacoma', 
                              'Walla Walla', 'Yakima' ) 
GROUP  BY time_by_day.the_year, 
          product_class.product_family, 
          customer.state_province, 
          customer.city; 
{code}

This query should return the following result:

{code}
[root@qa-node120 mondrian]# cat query447.e
1997	Drink	WA	Walla Walla	191.0000
1997	Drink	WA	Issaquah	203.0000
1997	Drink	WA	Everett	208.0000
1997	Drink	WA	Olympia	1066.0000
1997	Drink	WA	Edmonds	166.0000
1997	Drink	WA	Bremerton	1160.0000
1997	Drink	WA	Renton	225.0000
1997	Drink	WA	Bellingham	68.0000
1997	Drink	WA	Ballard	214.0000
1997	Drink	WA	Burien	251.0000
1997	Drink	WA	Seattle	168.0000
1997	Drink	WA	Redmond	137.0000
1997	Drink	WA	Lynnwood	201.0000
1997	Drink	WA	Puyallup	1040.0000
1997	Drink	WA	Tacoma	986.0000
1997	Drink	WA	Kirkland	247.0000
1997	Drink	WA	Sedro Woolley	58.0000
1997	Drink	WA	Yakima	1159.0000
1997	Drink	WA	Port Orchard	1128.0000
1997	Drink	WA	Spokane	2238.0000
1997	Drink	WA	Anacortes	82.0000
1997	Drink	WA	Marysville	193.0000
{code}

But drill now returns:

{code}
1997	Drink	WA	Sedro Woolley	58.0000
{code}

Here is the plan:

{code}
0: jdbc:drill:schema=dfs.drillTestDirComplexJ> explain plan for select time_by_day.the_year
as c0, product_class.product_family as c1, customer.state_province as c2, customer.city as
c3, sum(sales_fact_1997.unit_sales) as m0 from time_by_day as time_by_day, sales_fact_1997
as sales_fact_1997, product_class as product_class, product as product, customer as customer
where sales_fact_1997.time_id = time_by_day.time_id and time_by_day.the_year = 1997 and sales_fact_1997.product_id
= product.product_id and product.product_class_id = product_class.product_class_id and product_class.product_family
= 'Drink' and sales_fact_1997.customer_id = customer.customer_id and customer.state_province
= 'WA' and customer.city in ('Anacortes', 'Ballard', 'Bellingham', 'Bremerton', 'Burien',
'Edmonds', 'Everett', 'Issaquah', 'Kirkland', 'Lynnwood', 'Marysville', 'Olympia', 'Port Orchard',
'Puyallup', 'Redmond', 'Renton', 'Seattle', 'Sedro Woolley', 'Spokane', 'Tacoma', 'Walla Walla',
'Yakima') group by time_by_day.the_year, product_class.product_family, customer.state_province,
customer.city;
+------------+------------+
|    text    |    json    |
+------------+------------+
| 00-00    Screen
00-01      Project(c0=[$0], c1=[$1], c2=[$2], c3=[$3], m0=[$4])
00-02        HashAgg(group=[{0, 1, 2, 3}], m0=[SUM($4)])
00-03          Project(c0=[$0], c1=[$2], c2=[$3], c3=[$4], unit_sales=[$1])
00-04            HashJoin(condition=[=($5, $6)], joinType=[inner])
00-06              Project(the_year=[$0], unit_sales=[$5], product_family=[$6], state_province=[$10],
city=[$11], f17=[$11])
00-08                Project(the_year=[$4], time_id=[$5], time_id0=[$0], product_id=[$1],
customer_id=[$2], unit_sales=[$3], product_family=[$8], product_class_id=[$9], product_id0=[$6],
product_class_id0=[$7], state_province=[$10], city=[$11], customer_id0=[$12])
00-09                  HashJoin(condition=[=($2, $12)], joinType=[inner])
00-11                    HashJoin(condition=[=($1, $6)], joinType=[inner])
00-14                      HashJoin(condition=[=($0, $5)], joinType=[inner])
00-18                        Project(time_id=[$2], product_id=[$0], customer_id=[$1], unit_sales=[$3])
00-23                          Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath
[path=maprfs:/drill/testdata/mondrian/sales_fact_1997]], selectionRoot=/drill/testdata/mondrian/sales_fact_1997,
numFiles=1, columns=[`time_id`, `product_id`, `customer_id`, `unit_sales`]]])
00-17                        Project(the_year=[$0], time_id0=[$1])
00-22                          SelectionVectorRemover
00-26                            Filter(condition=[=($0, 1997)])
00-28                              Project(the_year=[$1], time_id=[$0])
00-30                                Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath
[path=maprfs:/drill/testdata/mondrian/time_by_day]], selectionRoot=/drill/testdata/mondrian/time_by_day,
numFiles=1, columns=[`the_year`, `time_id`]]])
00-13                      Project(product_id0=[$0], product_class_id=[$1], product_family=[$2],
product_class_id0=[$3])
00-16                        HashJoin(condition=[=($1, $3)], joinType=[inner])
00-21                          Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath
[path=maprfs:/drill/testdata/mondrian/product]], selectionRoot=/drill/testdata/mondrian/product,
numFiles=1, columns=[`product_id`, `product_class_id`]]])
00-20                          Project(product_family=[$0], product_class_id0=[$1])
00-25                            SelectionVectorRemover
00-27                              Filter(condition=[=($0, 'Drink')])
00-29                                Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath
[path=maprfs:/drill/testdata/mondrian/product_class]], selectionRoot=/drill/testdata/mondrian/product_class,
numFiles=1, columns=[`product_family`, `product_class_id`]]])
00-10                    Project(state_province=[$0], city=[$1], customer_id0=[$2])
00-12                      SelectionVectorRemover
00-15                        Filter(condition=[=($0, 'WA')])
00-19                          Project(state_province=[$1], city=[$2], customer_id=[$0])
00-24                            Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath
[path=maprfs:/drill/testdata/mondrian/customer]], selectionRoot=/drill/testdata/mondrian/customer,
numFiles=1, columns=[`state_province`, `city`, `customer_id`]]])
00-05              HashAgg(group=[{0}])
00-07                Values
 | {
{code}



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