[
https://issues.apache.org/jira/browse/HIVE-8731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14197737#comment-14197737
]
Gunther Hagleitner commented on HIVE-8731:
------------------------------------------
The problem is that this union all query is parsed as (query) union all (query
+ order by/limit) instead of (query union all query) order by /limit. This has
been there since we introduced top level unions and the workaround is to use a
subquery to express the union. I don't think this should hold up .14.
Here's the ast for
{noformat}
select * from store union all select * from store order by s_store_sk
{noformat}
{noformat}
ABSTRACT SYNTAX TREE:
TOK_QUERY
TOK_FROM
TOK_SUBQUERY
TOK_UNION
TOK_QUERY
TOK_FROM
TOK_TABREF
TOK_TABNAME
store
TOK_INSERT
TOK_DESTINATION
TOK_DIR
TOK_TMP_FILE
TOK_SELECT
TOK_SELEXPR
TOK_ALLCOLREF
TOK_QUERY
TOK_FROM
TOK_TABREF
TOK_TABNAME
store
TOK_INSERT
TOK_DESTINATION
TOK_DIR
TOK_TMP_FILE
TOK_SELECT
TOK_SELEXPR
TOK_ALLCOLREF
TOK_ORDERBY
TOK_TABSORTCOLNAMEASC
TOK_TABLE_OR_COL
s_store_sk
_u1
TOK_INSERT
TOK_DESTINATION
TOK_DIR
TOK_TMP_FILE
TOK_SELECT
TOK_SELEXPR
TOK_ALLCOLREF
{noformat}
> TPC-DS Q49 : Semantic analyzer order by is not honored when used after union
> all
> ---------------------------------------------------------------------------------
>
> Key: HIVE-8731
> URL: https://issues.apache.org/jira/browse/HIVE-8731
> Project: Hive
> Issue Type: Bug
> Components: Vectorization
> Affects Versions: 0.13.0, 0.14.0
> Reporter: Mostafa Mokhtar
> Assignee: Gunther Hagleitner
> Priority: Critical
>
> TPC-DS query 49 returns more rows than that set in limit.
> Query
> {code}
> set hive.cbo.enable=true;
> set hive.stats.fetch.column.stats=true;
> set hive.exec.dynamic.partition.mode=nonstrict;
> set hive.tez.auto.reducer.parallelism=true;
> set hive.auto.convert.join.noconditionaltask.size=1280000000;
> set hive.exec.reducers.bytes.per.reducer=100000000;
> set hive.txn.manager=org.apache.hadoop.hive.ql.lockmgr.DummyTxnManager;
> set hive.support.concurrency=false;
> set hive.tez.exec.print.summary=true;
> explain
> select
> 'web' as channel
> ,web.item
> ,web.return_ratio
> ,web.return_rank
> ,web.currency_rank
> from (
> select
> item
> ,return_ratio
> ,currency_ratio
> ,rank() over (order by return_ratio) as return_rank
> ,rank() over (order by currency_ratio) as currency_rank
> from
> ( select ws.ws_item_sk as item
> ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/
> cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as
> return_ratio
> ,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
> cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as
> currency_ratio
> from
> web_sales ws left outer join web_returns wr
> on (ws.ws_order_number = wr.wr_order_number and
> ws.ws_item_sk = wr.wr_item_sk)
> ,date_dim
> where
> wr.wr_return_amt > 10000
> and ws.ws_net_profit > 1
> and ws.ws_net_paid > 0
> and ws.ws_quantity > 0
> and ws.ws_sold_date_sk = date_dim.d_date_sk
> and d_year = 2000
> and d_moy = 12
> group by ws.ws_item_sk
> ) in_web
> ) web
> where
> (
> web.return_rank <= 10
> or
> web.currency_rank <= 10
> )
> union all
> select
> 'catalog' as channel
> ,catalog.item
> ,catalog.return_ratio
> ,catalog.return_rank
> ,catalog.currency_rank
> from (
> select
> item
> ,return_ratio
> ,currency_ratio
> ,rank() over (order by return_ratio) as return_rank
> ,rank() over (order by currency_ratio) as currency_rank
> from
> ( select
> cs.cs_item_sk as item
> ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
> cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as
> return_ratio
> ,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
> cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as
> currency_ratio
> from
> catalog_sales cs left outer join catalog_returns cr
> on (cs.cs_order_number = cr.cr_order_number and
> cs.cs_item_sk = cr.cr_item_sk)
> ,date_dim
> where
> cr.cr_return_amount > 10000
> and cs.cs_net_profit > 1
> and cs.cs_net_paid > 0
> and cs.cs_quantity > 0
> and cs_sold_date_sk = d_date_sk
> and d_year = 2000
> and d_moy = 12
> group by cs.cs_item_sk
> ) in_cat
> ) catalog
> where
> (
> catalog.return_rank <= 10
> or
> catalog.currency_rank <=10
> )
> union all
> select
> 'store' as channel
> ,store.item
> ,store.return_ratio
> ,store.return_rank
> ,store.currency_rank
> from (
> select
> item
> ,return_ratio
> ,currency_ratio
> ,rank() over (order by return_ratio) as return_rank
> ,rank() over (order by currency_ratio) as currency_rank
> from
> ( select sts.ss_item_sk as item
> ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as
> decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as
> return_ratio
> ,(cast(sum(coalesce(sr.sr_return_amt,0)) as
> decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as
> currency_ratio
> from
> store_sales sts left outer join store_returns sr
> on (sts.ss_ticket_number = sr.sr_ticket_number and
> sts.ss_item_sk = sr.sr_item_sk)
> ,date_dim
> where
> sr.sr_return_amt > 10000
> and sts.ss_net_profit > 1
> and sts.ss_net_paid > 0
> and sts.ss_quantity > 0
> and ss_sold_date_sk = d_date_sk
> and d_year = 2000
> and d_moy = 12
> group by sts.ss_item_sk
> ) in_store
> ) store
> where (
> store.return_rank <= 10
> or
> store.currency_rank <= 10
> )
> order by 1,4,5
> limit 100
> {code}
> Explain
> {code}
> OK
> STAGE DEPENDENCIES:
> Stage-1 is a root stage
> Stage-0 depends on stages: Stage-1
> STAGE PLANS:
> Stage: Stage-1
> Tez
> Edges:
> Map 11 <- Map 2 (BROADCAST_EDGE)
> Map 16 <- Map 1 (BROADCAST_EDGE)
> Map 9 <- Map 10 (BROADCAST_EDGE)
> Reducer 12 <- Map 11 (SIMPLE_EDGE), Map 23 (SIMPLE_EDGE)
> Reducer 13 <- Reducer 12 (SIMPLE_EDGE)
> Reducer 14 <- Reducer 13 (SIMPLE_EDGE)
> Reducer 15 <- Reducer 14 (SIMPLE_EDGE), Union 8 (CONTAINS)
> Reducer 17 <- Map 16 (SIMPLE_EDGE), Map 22 (SIMPLE_EDGE)
> Reducer 18 <- Reducer 17 (SIMPLE_EDGE)
> Reducer 19 <- Reducer 18 (SIMPLE_EDGE)
> Reducer 20 <- Reducer 19 (SIMPLE_EDGE)
> Reducer 21 <- Reducer 20 (SIMPLE_EDGE), Union 8 (CONTAINS)
> Reducer 4 <- Map 3 (SIMPLE_EDGE), Map 9 (SIMPLE_EDGE)
> Reducer 5 <- Reducer 4 (SIMPLE_EDGE)
> Reducer 6 <- Reducer 5 (SIMPLE_EDGE)
> Reducer 7 <- Reducer 6 (SIMPLE_EDGE), Union 8 (CONTAINS)
> DagName: mmokhtar_20141104031616_2feed955-8bb2-41e9-a7be-247a5fd102f0:1
> Vertices:
> Map 1
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 73049 Data size: 81741831 Basic
> stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 652 Data size: 7824 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Dynamic Partitioning Event Operator
> Target Input: sts
> Partition key expr: ss_sold_date_sk
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Target column: ss_sold_date_sk
> Target Vertex: Map 16
> Execution mode: vectorized
> Map 10
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 73049 Data size: 81741831 Basic
> stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 652 Data size: 7824 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Dynamic Partitioning Event Operator
> Target Input: ws
> Partition key expr: ws_sold_date_sk
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Target column: ws_sold_date_sk
> Target Vertex: Map 9
> Execution mode: vectorized
> Map 11
> Map Operator Tree:
> TableScan
> alias: cs
> filterExpr: (((((cs_net_profit > 1.0) and (cs_net_paid >
> 0.0)) and (cs_quantity > 0)) and cs_order_number is not null) and cs_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 43005109025 Data size: 5569553841288
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((((cs_net_profit > 1.0) and (cs_net_paid >
> 0.0)) and (cs_quantity > 0)) and cs_order_number is not null) and cs_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 712248037 Data size: 15504677212
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: cs_item_sk (type: int), cs_order_number
> (type: int), cs_quantity (type: int), cs_net_paid (type: float),
> cs_sold_date_sk (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 712248037 Data size: 12655685064
> Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {_col0} {_col1} {_col2} {_col3}
> 1
> keys:
> 0 _col5 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3
> input vertices:
> 1 Map 2
> Statistics: Num rows: 795181027 Data size:
> 12722896432 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), _col1 (type: int),
> _col2 (type: int), _col3 (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 795181027 Data size:
> 12722896432 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type:
> int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 795181027 Data size:
> 12722896432 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3
> (type: float)
> Execution mode: vectorized
> Map 16
> Map Operator Tree:
> TableScan
> alias: sts
> filterExpr: (((((ss_net_profit > 1.0) and (ss_net_paid >
> 0.0)) and (ss_quantity > 0)) and ss_ticket_number is not null) and ss_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 82510879939 Data size: 6873789738208
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((((ss_net_profit > 1.0) and (ss_net_paid >
> 0.0)) and (ss_quantity > 0)) and ss_ticket_number is not null) and ss_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 911486684 Data size: 19059525624
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ss_item_sk (type: int), ss_ticket_number
> (type: int), ss_quantity (type: int), ss_net_paid (type: float),
> ss_sold_date_sk (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 911486684 Data size: 15499570644
> Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {_col0} {_col1} {_col2} {_col3}
> 1
> keys:
> 0 _col5 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3
> input vertices:
> 1 Map 1
> Statistics: Num rows: 1017618695 Data size:
> 16281899120 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), _col1 (type: int),
> _col2 (type: int), _col3 (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 1017618695 Data size:
> 16281899120 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type:
> int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 1017618695 Data size:
> 16281899120 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3
> (type: float)
> Execution mode: vectorized
> Map 2
> Map Operator Tree:
> TableScan
> alias: date_dim
> filterExpr: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 73049 Data size: 81741831 Basic
> stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((d_year = 2000) and (d_moy = 12)) and
> d_date_sk is not null) (type: boolean)
> Statistics: Num rows: 652 Data size: 7824 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: d_date_sk (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int)
> outputColumnNames: _col0
> Statistics: Num rows: 652 Data size: 2608 Basic
> stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Dynamic Partitioning Event Operator
> Target Input: cs
> Partition key expr: cs_sold_date_sk
> Statistics: Num rows: 326 Data size: 1304 Basic
> stats: COMPLETE Column stats: COMPLETE
> Target column: cs_sold_date_sk
> Target Vertex: Map 11
> Execution mode: vectorized
> Map 22
> Map Operator Tree:
> TableScan
> alias: sr
> filterExpr: (((sr_return_amt > 10000.0) and
> sr_ticket_number is not null) and sr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 8332595709 Data size: 599630285540
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((sr_return_amt > 10000.0) and
> sr_ticket_number is not null) and sr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 828937940 Data size: 10816321020
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: sr_item_sk (type: int), sr_ticket_number
> (type: int), sr_return_quantity (type: int), sr_return_amt (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 828937940 Data size: 10816321020
> Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type: int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 828937940 Data size:
> 10816321020 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type:
> float)
> Execution mode: vectorized
> Map 23
> Map Operator Tree:
> TableScan
> alias: cr
> filterExpr: (((cr_return_amount > 10000.0) and
> cr_order_number is not null) and cr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 4320980099 Data size: 431907559456
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((cr_return_amount > 10000.0) and
> cr_order_number is not null) and cr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 644267320 Data size: 8780816984
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: cr_item_sk (type: int), cr_order_number
> (type: int), cr_return_quantity (type: int), cr_return_amount (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 644267320 Data size: 8780816984
> Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type: int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 644267320 Data size: 8780816984
> Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type:
> float)
> Execution mode: vectorized
> Map 3
> Map Operator Tree:
> TableScan
> alias: wr
> filterExpr: (((wr_return_amt > 10000.0) and wr_order_number
> is not null) and wr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 2062802370 Data size: 185695406284
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((wr_return_amt > 10000.0) and
> wr_order_number is not null) and wr_item_sk is not null) (type: boolean)
> Statistics: Num rows: 687600790 Data size: 10872009264
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: wr_item_sk (type: int), wr_order_number
> (type: int), wr_return_quantity (type: int), wr_return_amt (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 687600790 Data size: 10872009264
> Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type: int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 687600790 Data size:
> 10872009264 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3 (type:
> float)
> Execution mode: vectorized
> Map 9
> Map Operator Tree:
> TableScan
> alias: ws
> filterExpr: (((((ws_net_profit > 1.0) and (ws_net_paid >
> 0.0)) and (ws_quantity > 0)) and ws_order_number is not null) and ws_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 21594638446 Data size: 2850189889652
> Basic stats: COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: (((((ws_net_profit > 1.0) and (ws_net_paid >
> 0.0)) and (ws_quantity > 0)) and ws_order_number is not null) and ws_item_sk
> is not null) (type: boolean)
> Statistics: Num rows: 799801423 Data size: 19194435896
> Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: ws_item_sk (type: int), ws_order_number
> (type: int), ws_quantity (type: int), ws_net_paid (type: float),
> ws_sold_date_sk (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col5
> Statistics: Num rows: 799801423 Data size: 15995230204
> Basic stats: COMPLETE Column stats: COMPLETE
> Map Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {_col0} {_col1} {_col2} {_col3}
> 1
> keys:
> 0 _col5 (type: int)
> 1 _col0 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3
> input vertices:
> 1 Map 10
> Statistics: Num rows: 892928985 Data size:
> 14286863760 Basic stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), _col1 (type: int),
> _col2 (type: int), _col3 (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3
> Statistics: Num rows: 892928985 Data size:
> 14286863760 Basic stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col1 (type: int), _col0 (type:
> int)
> sort order: ++
> Map-reduce partition columns: _col1 (type: int),
> _col0 (type: int)
> Statistics: Num rows: 892928985 Data size:
> 14286863760 Basic stats: COMPLETE Column stats: COMPLETE
> value expressions: _col2 (type: int), _col3
> (type: float)
> Execution mode: vectorized
> Reducer 12
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {VALUE._col0} {VALUE._col1}
> 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1}
> outputColumnNames: _col2, _col3, _col4, _col6, _col7
> Statistics: Num rows: 750469116 Data size: 9005629392 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col4 (type: int), COALESCE(_col2,0) (type:
> int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float),
> COALESCE(_col7,0) (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 750469116 Data size: 9005629392 Basic
> stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> aggregations: sum(_col1), sum(_col2), sum(_col3),
> sum(_col4)
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 461643 Data size: 16619148 Basic
> stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 461643 Data size: 16619148 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: bigint), _col2 (type:
> bigint), _col3 (type: double), _col4 (type: double)
> Reducer 13
> Reduce Operator Tree:
> Group By Operator
> aggregations: sum(VALUE._col0), sum(VALUE._col1),
> sum(VALUE._col2), sum(VALUE._col3)
> keys: KEY._col0 (type: int)
> mode: mergepartial
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 5073 Data size: 182628 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), (CAST( _col1 AS
> decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)),
> (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type:
> decimal(35,20))
> outputColumnNames: _col0, _col1, _col2
> Statistics: Num rows: 5073 Data size: 1156644 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col1 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 5073 Data size: 1156644 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _col0 (type: int), _col1 (type:
> decimal(35,20)), _col2 (type: decimal(35,20))
> Execution mode: vectorized
> Reducer 14
> Reduce Operator Tree:
> Extract
> Statistics: Num rows: 5073 Data size: 1156644 Basic stats:
> COMPLETE Column stats: COMPLETE
> PTF Operator
> Statistics: Num rows: 5073 Data size: 1156644 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col2 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 5073 Data size: 1156644 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _wcol0 (type: int), _col0 (type: int),
> _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20))
> Reducer 15
> Reduce Operator Tree:
> Extract
> PTF Operator
> Filter Operator
> predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type:
> boolean)
> Select Operator
> expressions: 'catalog' (type: string), _col1 (type:
> int), _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Select Operator
> expressions: _col0 (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> File Output Operator
> compressed: false
> table:
> input format:
> org.apache.hadoop.mapred.TextInputFormat
> output format:
> org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
> serde:
> org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
> Reducer 17
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {VALUE._col0} {VALUE._col1}
> 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1}
> outputColumnNames: _col2, _col3, _col4, _col6, _col7
> Statistics: Num rows: 5092708834 Data size: 61112506008 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col4 (type: int), COALESCE(_col2,0) (type:
> int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float),
> COALESCE(_col7,0) (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 5092708834 Data size: 61112506008
> Basic stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> aggregations: sum(_col1), sum(_col2), sum(_col3),
> sum(_col4)
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 2194632 Data size: 79006752 Basic
> stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 2194632 Data size: 79006752 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: bigint), _col2 (type:
> bigint), _col3 (type: double), _col4 (type: double)
> Reducer 18
> Reduce Operator Tree:
> Group By Operator
> aggregations: sum(VALUE._col0), sum(VALUE._col1),
> sum(VALUE._col2), sum(VALUE._col3)
> keys: KEY._col0 (type: int)
> mode: mergepartial
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 3586 Data size: 129096 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), (CAST( _col1 AS
> decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)),
> (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type:
> decimal(35,20))
> outputColumnNames: _col0, _col1, _col2
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col1 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> value expressions: _col0 (type: int), _col1 (type:
> decimal(35,20)), _col2 (type: decimal(35,20))
> Execution mode: vectorized
> Reducer 19
> Reduce Operator Tree:
> Extract
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> PTF Operator
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col2 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> value expressions: _wcol0 (type: int), _col0 (type: int),
> _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20))
> Reducer 20
> Reduce Operator Tree:
> Extract
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> PTF Operator
> Statistics: Num rows: 3586 Data size: 817608 Basic stats:
> COMPLETE Column stats: COMPLETE
> Filter Operator
> predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type:
> boolean)
> Statistics: Num rows: 2390 Data size: 0 Basic stats:
> PARTIAL Column stats: COMPLETE
> Select Operator
> expressions: 'store' (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int), 1 (type:
> int), 4 (type: int), 5 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4,
> _col5, _col6, _col7
> Statistics: Num rows: 2390 Data size: 0 Basic stats:
> PARTIAL Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col5 (type: int), _col6 (type:
> int), _col7 (type: int)
> sort order: +++
> Statistics: Num rows: 2390 Data size: 0 Basic stats:
> PARTIAL Column stats: COMPLETE
> TopN Hash Memory Usage: 0.04
> value expressions: _col0 (type: string), _col1 (type:
> int), _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int)
> Reducer 21
> Reduce Operator Tree:
> Select Operator
> expressions: VALUE._col0 (type: string), VALUE._col1 (type:
> int), VALUE._col2 (type: decimal(35,20)), VALUE._col3 (type: int),
> VALUE._col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Limit
> Number of rows: 100
> Select Operator
> expressions: _col0 (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Select Operator
> expressions: _col0 (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> File Output Operator
> compressed: false
> table:
> input format:
> org.apache.hadoop.mapred.TextInputFormat
> output format:
> org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
> serde:
> org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
> Execution mode: vectorized
> Reducer 4
> Reduce Operator Tree:
> Merge Join Operator
> condition map:
> Inner Join 0 to 1
> condition expressions:
> 0 {VALUE._col0} {VALUE._col1}
> 1 {KEY.reducesinkkey1} {VALUE._col0} {VALUE._col1}
> outputColumnNames: _col2, _col3, _col4, _col6, _col7
> Statistics: Num rows: 375616827 Data size: 4507401924 Basic
> stats: COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col4 (type: int), COALESCE(_col2,0) (type:
> int), COALESCE(_col6,0) (type: int), COALESCE(_col3,0) (type: float),
> COALESCE(_col7,0) (type: float)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 375616827 Data size: 4507401924 Basic
> stats: COMPLETE Column stats: COMPLETE
> Group By Operator
> aggregations: sum(_col1), sum(_col2), sum(_col3),
> sum(_col4)
> keys: _col0 (type: int)
> mode: hash
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 232622 Data size: 8374392 Basic
> stats: COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: _col0 (type: int)
> sort order: +
> Map-reduce partition columns: _col0 (type: int)
> Statistics: Num rows: 232622 Data size: 8374392 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _col1 (type: bigint), _col2 (type:
> bigint), _col3 (type: double), _col4 (type: double)
> Reducer 5
> Reduce Operator Tree:
> Group By Operator
> aggregations: sum(VALUE._col0), sum(VALUE._col1),
> sum(VALUE._col2), sum(VALUE._col3)
> keys: KEY._col0 (type: int)
> mode: mergepartial
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Statistics: Num rows: 5057 Data size: 182052 Basic stats:
> COMPLETE Column stats: COMPLETE
> Select Operator
> expressions: _col0 (type: int), (CAST( _col1 AS
> decimal(15,4)) / CAST( _col2 AS decimal(15,4))) (type: decimal(35,20)),
> (CAST( _col3 AS decimal(15,4)) / CAST( _col4 AS decimal(15,4))) (type:
> decimal(35,20))
> outputColumnNames: _col0, _col1, _col2
> Statistics: Num rows: 5057 Data size: 1152996 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col1 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 5057 Data size: 1152996 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _col0 (type: int), _col1 (type:
> decimal(35,20)), _col2 (type: decimal(35,20))
> Execution mode: vectorized
> Reducer 6
> Reduce Operator Tree:
> Extract
> Statistics: Num rows: 5057 Data size: 1152996 Basic stats:
> COMPLETE Column stats: COMPLETE
> PTF Operator
> Statistics: Num rows: 5057 Data size: 1152996 Basic stats:
> COMPLETE Column stats: COMPLETE
> Reduce Output Operator
> key expressions: 0 (type: int), _col2 (type:
> decimal(35,20))
> sort order: ++
> Map-reduce partition columns: 0 (type: int)
> Statistics: Num rows: 5057 Data size: 1152996 Basic
> stats: COMPLETE Column stats: COMPLETE
> value expressions: _wcol0 (type: int), _col0 (type: int),
> _col1 (type: decimal(35,20)), _col2 (type: decimal(35,20))
> Reducer 7
> Reduce Operator Tree:
> Extract
> PTF Operator
> Filter Operator
> predicate: ((_col0 <= 10) or (_wcol1 <= 10)) (type:
> boolean)
> Select Operator
> expressions: 'web' (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col0 (type: int), _wcol1 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> Select Operator
> expressions: _col0 (type: string), _col1 (type: int),
> _col2 (type: decimal(35,20)), _col3 (type: int), _col4 (type: int)
> outputColumnNames: _col0, _col1, _col2, _col3, _col4
> File Output Operator
> compressed: false
> table:
> input format:
> org.apache.hadoop.mapred.TextInputFormat
> output format:
> org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
> serde:
> org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
> Union 8
> Vertex: Union 8
> Stage: Stage-0
> Fetch Operator
> limit: -1
> Processor Tree:
> ListSink
> {code}
> Results
> {code}
> OK
> web 55255 0.37373737373737373737 1072 1
> web 305651 0.38383838383838383838 1138 2
> web 336757 0.38461538461538461538 1142 3
> web 256885 0.39 1191 4
> web 229082 0.39175257731958762887 1204 5
> web 151723 0.4 1265 6
> web 293861 0.4 1265 6
> web 178178 0.4 1265 8
> web 354485 0.40449438202247191011 1315 9
> web 124375 0.40625 1334 10
> web 80125 0 1 44
> web 417227 0 1 103
> web 316352 0 1 142
> web 116672 0 1 143
> web 267277 0 1 181
> web 100247 0 1 237
> web 247022 0 1 505
> web 247679 0 1 966
> web 89753 0 1 1081
> web 88964 0 1 1492
> web 292469 0 1 1771
> web 31958 0 1 1868
> web 200161 0 1 1937
> web 194660 0 1 2064
> web 381619 0 1 2233
> web 244238 0 1 2437
> web 54247 0 1 2647
> web 105464 0 1 2669
> web 297959 0 1 3196
> web 405146 0 1 3278
> web 79435 0 1 3298
> web 101285 0 1 3625
> web 33871 0 1 3866
> web 190016 0 1 4068
> web 147661 0 1 4068
> web 164804 0 1 4076
> web 461345 0 1 4119
> web 339872 0 1 4271
> web 286802 0 1 4431
> web 127811 0 1 4636
> web 157763 0 1 4652
> web 232867 0 1 4800
> web 102164 0 1 5068
> web 170683 0 1 5404
> web 280421 0 1 5457
> web 354487 0 1 5839
> web 159923 0 1 5889
> web 326413 0 1 5940
> web 455582 0 1 6098
> web 170078 0 1 6809
> web 430406 0 1 6939
> web 372425 0 1 6939
> web 124520 0 1 7178
> web 68522 0 1 7229
> web 185078 0 1 7247
> web 364901 0 1 7262
> web 361805 0 1 7276
> web 75752 0 1 7378
> web 207637 0 1 7395
> web 32810 0 1 7743
> web 86717 0 1 8253
> web 241475 0 1 8377
> web 346709 0 1 8646
> web 280169 0 1 8661
> web 49567 0 1 8800
> web 29849 0 1 9090
> web 130943 0 1 9152
> web 301475 0 1 9260
> web 161756 0 1 9504
> web 358580 0 1 9606
> web 277976 0 1 10594
> web 134677 0 1 11027
> web 275977 0 1 11476
> web 297167 0 1 11944
> web 430345 0 1 12058
> web 166676 0 1 12808
> web 179306 0 1 12875
> web 254888 0 1 12954
> web 353521 0 1 13176
> web 240865 0 1 13998
> web 423649 0 1 14122
> web 408743 0 1 14122
> web 460999 0 1 15733
> web 286481 0 1 15733
> web 329173 0 1 17252
> web 130622 0 1 17840
> web 178213 0 1 17997
> web 335984 0 1 18289
> web 427916 0 1 18728
> web 114487 0 1 19540
> web 162031 0 1 20434
> web 55337 0 1 20436
> web 240067 0 1 20440
> web 126476 0 1 20663
> web 293327 0 1 20860
> web 190472 0 1 21262
> web 45476 0 1 21341
> web 33242 0 1 21492
> web 278471 0 1 21522
> web 91147 0 1 21528
> web 16073 0 1 21542
> web 433838 0 1 21696
> web 302984 0 1 21892
> web 29873 0 1 22205
> web 385919 0 1 22224
> web 143483 0 1 22738
> web 282407 0 1 22741
> web 450079 0 1 22868
> web 101966 0 1 23096
> web 166459 0 1 23115
> web 375350 0 1 23368
> web 97184 0 1 23376
> web 359954 0 1 24597
> web 188270 0 1 25893
> web 179275 0 1 26023
> web 454568 0 1 26873
> web 15557 0 1 26997
> web 70519 0 1 27962
> web 100357 0 1 28291
> web 301403 0 1 28709
> web 111667 0 1 28850
> web 10501 0 1 28998
> web 97295 0 1 29488
> web 375497 0 1 29488
> web 440813 0 1 30025
> web 203027 0 1 30114
> web 29135 0 1 30178
> web 105905 0 1 30452
> web 9041 0 1 32084
> web 238418 0 1 32241
> web 220373 0 1 32704
> web 160309 0 1 33182
> web 381818 0 1 33546
> web 370256 0 1 34171
> web 243403 0 1 34283
> web 20515 0 1 34603
> web 230303 0 1 35673
> web 411935 0 1 35705
> web 233701 0 1 37837
> web 443305 0 1 37946
> web 216317 0 1 38667
> web 317917 0 1 39702
> web 434725 0 1 40089
> web 244205 0 1 41401
> web 43489 0 1 41622
> web 75620 0 1 42416
> web 175826 0 1 42550
> web 152153 0 1 43205
> web 149119 0 1 43608
> web 211130 0 1 44405
> web 24283 0 1 44707
> web 281659 0 1 44955
> web 371879 0 1 44960
> web 136409 0 1 45813
> web 299177 0 1 46233
> web 438806 0 1 46450
> web 238466 0 1 46451
> web 299749 0 1 47191
> web 71201 0 1 48191
> web 114923 0 1 48312
> web 174617 0 1 48846
> web 20420 0 1 50055
> web 219266 0 1 50118
> web 54392 0 1 51281
> web 11507 0 1 51359
> web 24517 0 1 51719
> web 306482 0 1 51945
> web 110642 0 1 52339
> web 433994 0 1 52722
> web 313400 0 1 52873
> web 252587 0 1 53020
> web 318925 0 1 53983
> web 409789 0 1 54250
> web 270332 0 1 54454
> web 314339 0 1 54457
> web 399728 0 1 54962
> web 5275 0 1 55300
> web 296609 0 1 55474
> web 126703 0 1 56460
> web 3847 0 1 56483
> web 434144 0 1 57400
> web 270977 0 1 57678
> web 357530 0 1 58668
> web 415016 0 1 59103
> web 364253 0 1 59424
> web 138307 0 1 59424
> web 446414 0 1 61467
> web 243497 0 1 61496
> web 88586 0 1 62134
> web 21259 0 1 62872
> web 275609 0 1 63160
> web 347183 0 1 63160
> web 454637 0 1 63761
> web 338377 0 1 63889
> web 92663 0 1 64335
> web 4477 0 1 64458
> web 4999 0 1 65909
> web 7748 0 1 65909
> web 287239 0 1 65909
> web 323351 0 1 66236
> web 58081 0 1 66398
> web 91541 0 1 66398
> web 441350 0 1 67000
> web 3367 0 1 68511
> web 29492 0 1 68511
> web 167318 0 1 70048
> web 249703 0 1 70673
> web 294482 0 1 71769
> web 429041 0 1 73030
> web 147769 0 1 73049
> web 228656 0 1 73062
> web 57223 0 1 73185
> web 431921 0 1 74475
> web 443024 0 1 74750
> web 95546 0 1 74750
> web 56474 0 1 75727
> web 439543 0 1 76122
> web 58297 0 1 77271
> web 73100 0 1 77278
> web 94982 0 1 78993
> web 104297 0 1 79275
> web 141467 0 1 80408
> web 44077 0 1 80417
> web 237227 0 1 80952
> web 67067 0 1 80968
> web 347354 0 1 81793
> web 320251 0 1 83749
> web 452603 0 1 83883
> web 337321 0 1 86256
> web 367706 0 1 86304
> web 75293 0 1 86311
> web 66464 0 1 89520
> web 417877 0 1 90913
> web 100349 0 1 92083
> web 178415 0 1 92095
> web 145946 0 1 92121
> web 342131 0 1 92172
> web 118316 0 1 92172
> web 242335 0 1 92292
> web 296270 0 1 92309
> web 177391 0 1 93635
> web 240829 0 1 93645
> web 264623 0 1 95054
> web 288746 0 1 95276
> web 146369 0 1 95292
> web 356861 0 1 95504
> web 354331 0 1 95508
> web 224348 0 1 96361
> web 228715 0 1 97615
> web 247843 0 1 98442
> web 347473 0 1 98728
> web 156895 0 1 98977
> web 351461 0 1 99521
> web 304111 0 1 99608
> web 428719 0 1 100158
> web 82130 0 1 100197
> web 82010 0 1 101038
> web 24121 0 1 101239
> web 296849 0 1 101694
> web 194371 0 1 102225
> web 112235 0 1 103045
> web 127214 0 1 103867
> web 164423 0 1 103972
> web 439169 0 1 104959
> web 163760 0 1 104964
> web 368695 0 1 104981
> web 298418 0 1 105715
> web 13838 0 1 105866
> web 432998 0 1 105867
> web 446179 0 1 106045
> web 412615 0 1 106777
> web 120055 0 1 107221
> web 191501 0 1 107289
> web 360653 0 1 107307
> web 190070 0 1 108386
> web 107633 0 1 108518
> web 366209 0 1 109023
> web 429101 0 1 109466
> web 316070 0 1 109482
> web 10712 0 1 109692
> web 266069 0 1 109700
> web 249733 0 1 111139
> web 70045 0 1 111164
> web 240698 0 1 111551
> web 401072 0 1 111573
> web 355184 0 1 111962
> web 377269 0 1 112397
> web 202675 0 1 112397
> web 42194 0 1 112934
> web 134465 0 1 113204
> web 217639 0 1 113553
> web 80789 0 1 113553
> web 115991 0 1 114061
> web 239695 0 1 114247
> web 444767 0 1 114730
> web 110083 0 1 114730
> web 275573 0 1 115520
> web 197687 0 1 116150
> web 446195 0 1 116700
> web 307259 0 1 117173
> web 323371 0 1 117189
> web 381079 0 1 117605
> web 128753 0 1 117762
> web 39799 0 1 117791
> web 310532 0 1 118044
> web 221660 0 1 118184
> web 268621 0 1 118202
> web 110063 0 1 118210
> web 249179 0 1 118212
> web 42971 0 1 119018
> web 310208 0 1 119076
> web 454793 0 1 120232
> web 208957 0 1 120465
> web 82849 0 1 121192
> web 53702 0 1 121192
> web 21062 0 1 121415
> web 324653 0 1 121428
> web 153002 0 1 121429
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> Time taken: 201.381 seconds, Fetched: 764 row(s)
> {code}
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