執(zhí)行計(jì)劃例子：
insert overwrite TABLE lpx SELECT t1.bar, t1.foo, t2.foo FROM pokes t1 JOIN invites t2 ON (t1.bar = t2.bar) ;
OK
ABSTRACT SYNTAX TREE:
? (TOK_QUERY (TOK_FROM (TOK_JOIN (TOK_TABREF (TOK_TABNAME pokes) t1) (TOK_TABREF (TOK_TABNAME invites) t2) (= (. (TOK_TABLE_OR_COL t1) bar) (. (TOK_TABLE_OR_COL t2) bar)))) (TOK_INSERT (TOK_DESTINATION (TOK_TAB (TOK_TABNAME lpx))) (TOK_SELECT (TOK_SELEXPR (. (TOK_TABLE_OR_COL t1) bar)) (TOK_SELEXPR (. (TOK_TABLE_OR_COL t1) foo)) (TOK_SELEXPR (. (TOK_TABLE_OR_COL t2) foo)))))
STAGE DEPENDENCIES:
? Stage-1 is a root stage ? /根
? Stage-0 depends on stages: Stage-1 /0依賴1
? Stage-2 depends on stages: Stage-0 /2依賴0
STAGE PLANS:
Stage: Stage-1
Map Reduce//這個(gè)階段是一個(gè)mapreduce作業(yè)????? Alias -> Map Operator Tree:???//map操作樹，對(duì)應(yīng)map階段
t1
TableScan?? //掃描表獲取數(shù)據(jù) ??from加載表，描述中有行數(shù)和大小等
??????????? alias: t1???? //表別名
Reduce Output Operator?//這里描述map的輸出，也就是reduce的輸入。比如key，partition，sort等信息?
????????????? key expressions:??//t1表輸出到reduce階段的key信息
expr: bar
type: string
sort order: +? //一個(gè)排序字段，這個(gè)排序字段是key=bar，多個(gè)排序字段多個(gè)+
Map-reduce partition columns:? //partition的信息，由此也可以看出hive在join的時(shí)候會(huì)以join on后的列作為partition的列，以保證具有相同此列的值的行被分到同一個(gè)reduce中去
expr: bar
type: string
tag: 0???????????????????????? //對(duì)t1表打標(biāo)簽
value expressions:?? //t1表輸出到reduce階段的value信息
expr: foo
type: int
expr: bar
type: string
t2
TableScan
alias: t2
Reduce Output Operator
key expressions:
expr: bar
type: string
sort order: +
Map-reduce partition columns:
expr: bar
type: string
tag: 1
value expressions:
expr: foo
type: int
Reduce Operator Tree://reduce操作樹，相當(dāng)于reduce階段Join Operator
condition map:
Inner Join 0 to 1
????????? condition expressions:
??????????? 0 {VALUE._col0} {VALUE._col1} //對(duì)應(yīng)前面t1.bar, t1.foo
??????????? 1 {VALUE._col0} //對(duì)應(yīng)前面t2.foo
????????? handleSkewJoin: false
????????? outputColumnNames: _col0, _col1, _col5
Select Operator //篩選列，描述中有列名、類型，輸出類型、大小等。
expressions:
expr: _col1
type: string
expr: _col0
type: int
expr: _col5
????????????????? type: int
??????????? outputColumnNames: _col0, _col1, _col2 ? //為臨時(shí)結(jié)果字段按規(guī)則起的臨時(shí)字段名
File Output Operator //輸出結(jié)果到臨時(shí)文件中，描述介紹了壓縮格式、輸出文件格式。
compressed: false
GlobalTableId: 1
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
name: default.lpx
? Stage: Stage-0
Move Operator //Stage-0簡單把結(jié)果從臨時(shí)目錄，移動(dòng)到表lpx相關(guān)的目錄。
tables:
replace: true
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
name: default.lpx
Stage: Stage-2
Stats-Aggr Operator
========================================
========================================
從信息頭：
STAGE DEPENDENCIES:
Stage-1 is a root stage
Stage-0 depends on stages: Stage-1
Stage-2 depends on stages: Stage-0
從這里可以看出Plan計(jì)劃的Job任務(wù)結(jié)構(gòu)，整個(gè)任務(wù)會(huì)分為3個(gè)Job執(zhí)行，第一個(gè)Job將由Stage-1構(gòu)成;
第二個(gè)Job處理由Stage-0構(gòu)成，Stage-0的處理必須依賴Stage-1階段的結(jié)果;
第三個(gè)Job處理由Stage-2構(gòu)成，Stage-2的處理必須依賴Stage-0階段的結(jié)果。
下面分別解釋Stage-1和Stage-0，執(zhí)行SQL可以分成兩步：(1)、SELECT t1.bar, t1.foo, t2.foo FROM pokes t1 JOIN invites t2 ON (t1.bar = t2.bar);
(2)
、insert overwrite TABLE lpx;
Stage: Stage-1對(duì)應(yīng)一次完整的Map Reduce任務(wù)，包括：Map Operator Tree和Reduce Operator Tree兩步操作,Map Operator Tree對(duì)應(yīng)Map任務(wù)，Reduce Operator Tree對(duì)應(yīng)Reduce任務(wù)。從Map Operator Tree階段可以看出進(jìn)行了兩個(gè)并列的操作t1和t2，分別SELECT t1.bar, t1.foo FROM t1;和SELECT t2.foo FROM t2;而且兩個(gè)Map任務(wù)分別產(chǎn)生了Reduce階段的輸入[Reduce Output Operator]。從Reduce Operator Tree分析可以看到如下信息，條件連接Map的輸出以及通過預(yù)定義的輸出格式生成符合default.lpx的存儲(chǔ)格式的數(shù)據(jù)存儲(chǔ)到HDFS中。在我們創(chuàng)建lpx表的時(shí)候，沒有指定該表的存儲(chǔ)格式，默認(rèn)會(huì)以Text為存儲(chǔ)格式，輸入輸出會(huì)以TextInputFormat與TextOutputFormat進(jìn)行讀寫：
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
name: default.lpx
input format的值對(duì)應(yīng)org.apache.hadoop.mapred.TextInputFormat，這是因?yàn)樵陂_始的Map階段產(chǎn)生的臨時(shí)輸出文件是以TextOutputFormat格式保存的，自然Reduce的讀取是由TextInputFormat格式處理讀入數(shù)據(jù)。這些是由Hadoop的MapReduce處理細(xì)節(jié)來控制，而Hive只需要指定處理格式即可。
Serde值為org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe類，這時(shí)這個(gè)對(duì)象的保存的值為_col0, _col1, _col2，也就是我們預(yù)期要查詢的t1.bar, t1.foo, t2.foo，這個(gè)值具體的應(yīng)該為_col0+表lpx設(shè)置的列分割符+_col1+表lpx設(shè)置的列分割符+_col2。outputformat:org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat可以知道output的處理是使用該類來處理的。
Stage-0對(duì)應(yīng)上面提到的第二步操作。這時(shí)stage-1產(chǎn)生的臨時(shí)處理文件舉例如tmp,需要經(jīng)過stage-0階段操作處理到lpx表中。Move Operator代表了這并不是一個(gè)MapReduce任務(wù)，只需要調(diào)用MoveTask的處理就行，在處理之前會(huì)去檢查輸入文件是否符合lpx表的存儲(chǔ)格式。
hive執(zhí)行計(jì)劃作用
分析作業(yè)執(zhí)行過程，優(yōu)化作業(yè)執(zhí)行流程，提升作業(yè)執(zhí)行效率；例如，數(shù)據(jù)過濾條件從reduce端提前到map端，有效減少map/reduce間shuffle數(shù)據(jù)量，提升作業(yè)執(zhí)行效率；
提前過濾數(shù)據(jù)數(shù)據(jù)集，減少不必要的讀取操作；例如: hive join操作先于where條件顧慮，將分區(qū)條件放入on語句中，能夠有效減少輸入數(shù)據(jù)集；
執(zhí)行計(jì)劃分析問題hql
select a.*, b.cust_uid
from ods_ad_bid_deliver_info b join mds_ad_algo_feed_monitor_data_table a
where a.dt<=20140101 and a.dt<=20140108 and key='deliver_id_bucket_id' and a.dt=b.dt and a.key_slice=b.deliver_id
==========================================================================
==========================================================================
執(zhí)行計(jì)劃：
抽象語法樹：
ABSTRACT SYNTAX TREE:
? (TOK_QUERY (TOK_FROM (TOK_JOIN (TOK_TABREF (TOK_TABNAME ods_ad_bid_deliver_info) b) (TOK_TABREF (TOK_TABNAME mds_ad_algo_feed_monitor_data_table) a))) (TOK_INSERT (TOK_DESTINATION (TOK_DIR TOK_TMP_FILE)) (TOK_SELECT (TOK_SELEXPR (TOK_ALLCOLREF (TOK_TABNAME a))) (TOK_SELEXPR (. (TOK_TABLE_OR_COL b) cust_uid))) (TOK_WHERE (and (and (and (and (<= (. (TOK_TABLE_OR_COL a) dt) 20140101) (<= (. (TOK_TABLE_OR_COL a) dt) 20140108)) (= (TOK_TABLE_OR_COL key) 'deliver_id_bucket_id')) (= (. (TOK_TABLE_OR_COL a) dt) (. (TOK_TABLE_OR_COL b) dt))) (= (. (TOK_TABLE_OR_COL a) key_slice) (. (TOK_TABLE_OR_COL b) deliver_id))))))
STAGE DEPENDENCIES:
? Stage-1 is a root stage
? Stage-0 is a root stage
STAGE PLANS:
? Stage: Stage-1
??? Map Reduce
????? Alias -> Map Operator Tree:
??????? a
?????????TableScan
??????????? alias: a
???????????Filter Operator
????????????? predicate:
????????????????? expr: (key = 'deliver_id_bucket_id')?//按key指定值在map階段過濾
????????????????? type: boolean
?????????????Reduce Output Operator
??????????????? sort order:
??????????????? tag: 1
??????????????? value expressions:?//select *導(dǎo)致輸出到reduce的數(shù)據(jù)是全部的列信息
?????????????????????expr: key
????????????????????? type: string
????????????????????? expr: key_slice
????????????????????? type: string
????????????????????? expr: billing_mode_slice
????????????????????? type: string
????????????????????? expr: bucket_id
????????????????????? type: string
????????????????????? expr: ctr
????????????????????? type: string
????????????????????? expr: ecpm
????????????????????? type: string
????????????????????? expr: auc
????????????????????? type: string
????????????????????? expr: pctr
????????????????????? type: string
????????????????????? expr: pctr_ctr
????????????????????? type: string
????????????????????? expr: total_pv
????????????????????? type: string
????????????????????? expr: total_click
????????????????????? type: string
????????????????????? expr: dt
????????????????????? type: string
??????? b
?????????TableScan
??????????? alias: b
???????????Reduce Output Operator
????????????? sort order:
????????????? tag: 0
????????????? value expressions:
??????????????????? expr: deliver_id
??????????????????? type: string
??????????????????? expr: cust_uid
??????????????????? type: string
??????????????????? expr: dt
??????????????????? type: string
????? Reduce Operator Tree:
???????Join Operator
????????? condition map:
?????????????? Inner Join 0 to 1
????????? condition expressions:
??????????? 0 {VALUE._col0} {VALUE._col6} {VALUE._col35}
??????????? 1 {VALUE._col0} {VALUE._col1} {VALUE._col2} {VALUE._col3} {VALUE._col4} {VALUE._col5} {VALUE._col6} {VALUE._col7} {VALUE._col8} {VALUE._col9} {VALUE._col10} {VALUE._col11}
????????? handleSkewJoin: false
????????? outputColumnNames: _col0, _col6, _col35, _col38, _col39, _col40, _col41, _col42, _col43, _col44, _col45, _col46, _col47, _col48, _col49
?????????Filter Operator
??????????? predicate:
???????????????expr: (((((_col49 <= 20140101) and (_col49 <= 20140108)) and (_col38 = 'deliver_id_bucket_id')) and (_col49 = _col35)) and (_col39 = _col0))
??????????????? type: boolean
???????????Select Operator
????????????? expressions:
??????????????????? expr: _col38
??????????????????? type: string
??????????????????? expr: _col39
??????????????????? type: string
??????????????????? expr: _col40
??????????????????? type: string
??????????????????? expr: _col41
??????????????????? type: string
??????????????????? expr: _col42
??????????????????? type: string
??????????????????? expr: _col43
??????????????????? type: string
??????????????????? expr: _col44
??????????????????? type: string
??????????????????? expr: _col45
??????????????????? type: string
??????????????????? expr: _col46
??????????????????? type: string
??????????????????? expr: _col47
??????????????????? type: string
??????????????????? expr: _col48
??????????????????? type: string
??????????????????? expr: _col49
??????????????????? type: string
??????????????????? expr: _col6
??????????????????? type: string
????????????? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
?????????????File Output Operator
??????????????? compressed: false
??????????????? GlobalTableId: 0
??????????????? table:
??????????????????? input format: org.apache.hadoop.mapred.TextInputFormat
??????????????????? output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
? Stage: Stage-0
??? Fetch Operator
????? limit: -1
優(yōu)化之后hql：
select a.*, b.cust_uid
from ods_ad_bid_deliver_info b
join mds_ad_algo_feed_monitor_data_table a
on(a.dt<=20140101 and a.dt<=20140108 and a.dt=b.dt and a.key_slice=b.deliver_id and a.key='deliver_id_bucket_id')
=================================================================
=================================================================
執(zhí)行計(jì)劃：
抽象語法樹：
STAGE DEPENDENCIES:
? Stage-1 is a root stage
? Stage-0 is a root stage
STAGE PLANS:
? Stage: Stage-1
??? Map Reduce
????? Alias -> Map Operator Tree:
??????? a
??????????TableScan
??????????? alias: a
???????????Filter Operator
????????????? predicate:
????????????????? expr: (key = 'deliver_id_bucket_id')
????????????????? type: boolean
?????????????Filter Operator
??????????????? predicate:
??????????????????? expr: (dt <= 20140101)? //分區(qū)過濾條件在map端生效
??????????????????? type: boolean
???????????????Filter Operator
????????????????? predicate:
????????????????????? expr: (dt <= 20140108)? //分區(qū)過濾條件在map端生效
????????????????????? type: boolean
????????????????? Filter Operator
??????????????????? predicate:
??????????????????????? expr: (key = 'deliver_id_bucket_id')
??????????????????????? type: boolean
??????????????????? Reduce Output Operator
????????????????????? key expressions:
??????????????????????????? expr: dt
??????????????????????????? type: string
??????????????????????????? expr: key_slice
??????????????????????????? type: string
?????????? ???????????sort order: ++
????????????????????? Map-reduce partition columns:
??????????????????????????? expr: dt
??????????????????????????? type: string
??????????????????????????? expr: key_slice
??????????????????????????? type: string
?????????????? ???????tag: 1
????????????????????? value expressions:
??????????????????????????? expr: key
??????????????????????????? type: string
??????????????????????????? expr: key_slice
??????????????????????????? type: string
??????????????????????????? expr: billing_mode_slice
??????????????????????????? type: string
??????????????????????????? expr: bucket_id
??????????????????????????? type: string
??????????????????????????? expr: ctr
??????????????????????????? type: string
??????????????????????????? expr: ecpm
??????????????????????????? type: string
??????????????????????????? expr: auc
??????????????????????????? type: string
??????????????????????????? expr: pctr
??????????????????????????? type: string
??????????????????????????? expr: pctr_ctr
??????????????????????????? type: string
??????????????????????????? expr: total_pv
??????????????????????????? type: string
??????????????????????????? expr: total_click
??????????????????????????? type: string
??????????????????????????? expr: dt
?????? ?????????????????????type: string
??????? b
??????????TableScan
??????????? alias: b
??????????? Reduce Output Operator
????????????? key expressions:
??????????????????? expr: dt
??????????????????? type: string
??????????????????? expr: deliver_id
???? ???????????????type: string
????????????? sort order: ++
????????????? Map-reduce partition columns:
??????????????????? expr: dt
??????????????????? type: string
??????????????????? expr: deliver_id
??????????????????? type: string
????????????? tag: 0
? ????????????value expressions:
??????????????????? expr: cust_uid
??????????????????? type: string
????? Reduce Operator Tree:
??????? Join Operator
????????? condition map:
?????????????? Inner Join 0 to 1
????????? condition expressions:
??????????? 0 {VALUE._col6}
??????????? 1 {VALUE._col0} {VALUE._col1} {VALUE._col2} {VALUE._col3} {VALUE._col4} {VALUE._col5} {VALUE._col6} {VALUE._col7} {VALUE._col8} {VALUE._col9} {VALUE._col10} {VALUE._col11}
????????? handleSkewJoin: false
????????? outputColumnNames: _col6, _col38, _col39, _col40, _col41, _col42, _col43, _col44, _col45, _col46, _col47, _col48, _col49
????????? Select Operator
??????????? expressions:
????????????????? expr: _col38
????????????????? type: string
????????????????? expr: _col39
????????????????? type: string
????????????????? expr: _col40
????????????????? type: string
????????????????? expr: _col41
????????????????? type: string
????????????????? expr: _col42
????????????????? type: string
????????????????? expr: _col43
?????????????????type: string
????????????????? expr: _col44
????????????????? type: string
????????????????? expr: _col45
????????????????? type: string
????????????????? expr: _col46
????????????????? type: string
????????????????? expr: _col47
????????????????? type: string
????????????????? expr: _col48
????????????????? type: string
????????????????? expr: _col49
????????????????? type: string
????????????????? expr: _col6
????????????????? type: string
??????????? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
??????????? File Output Operator
????????????? compressed: false
????????????? GlobalTableId: 0
????????????? table:
????????????????? input format: org.apache.hadoop.mapred.TextInputFormat
????????????????? output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
? Stage: Stage-0
??? Fetch Operator
????? limit: -1
例子：
select?*?from?emp e
left?join?dept d?on?e.deptno=d.deptno
where d.dt='2018-06-04';
花費(fèi)時(shí)間:Time taken: 44.401 seconds, Fetched: 17 row(s)
執(zhí)行計(jì)劃:
STAGE DEPENDENCIES:
? Stage-4 is a root stage
? Stage-3 depends on stages: Stage-4
? Stage-0 depends on stages: Stage-3
STAGE PLANS:
? Stage: Stage-4
? ? Map Reduce Local Work ?/本地執(zhí)行
? ? ? Alias -> Map Local Tables:
? ? ? ? d
? ? ? ? ? Fetch Operator
? ? ? ? ? ? limit: -1
? ? ? Alias -> Map Local Operator Tree:
? ? ? ? d
? ? ? ? ? TableScan
? ? ? ? ? ? alias: d
? ? ? ? ? ? Statistics: Num rows: 1 Data size: 168 Basic stats: PARTIAL Column stats: PARTIAL
HashTable Sink Operator/ReduceSinkOperator將Map端的字段組合序列化為Reduce Key/value, Partition Key，只可能出現(xiàn)在Map階段，同時(shí)也標(biāo)志著Hive生成的MapReduce程序中Map階段的結(jié)束。
? ? ? ? ? ? ? keys:
? ? ? ? ? ? ? ? 0 deptno (type: string)
? ? ? ? ? ? ? ? 1 deptno (type: string)
? Stage: Stage-3
? ? Map Reduce
? ? ? Map Operator Tree:
? ? ? ? ? TableScan
? ? ? ? ? ? alias: e
? ? ? ? ? ? Statistics: Num rows: 1 Data size: 757 Basic stats: PARTIAL Column stats: PARTIAL
? ? ? ? ? ? Map Join Operator
? ? ? ? ? ? ? condition map:
? ? ? ? ? ? ? ? ? ?Left Outer Join0 to 1
? ? ? ? ? ? ? keys:
? ? ? ? ? ? ? ? 0 deptno (type: string)
? ? ? ? ? ? ? ? 1 deptno (type: string)
? ? ? ? ? ? ? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col12, _col13, _col14, _col15
? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? Filter Operator
? ? ? ? ? ? ? ? predicate: (_col15 = '2018-06-04') (type: boolean)
? ? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? ? Select Operator
? ? ? ? ? ? ? ? ? expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: string), _col7 (type: string), _col8 (type: str
ing), _col12 (type: string), _col13 (type: string), _col14 (type: string), '2018-06-04' (type: string)? ? ? ? ? ? ? ? ? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
? ? ? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? ? ? File Output Operator
? ? ? ? ? ? ? ? ? ? compressed: false
? ? ? ? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? ? ? ? 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
? ? ? Local Work:
? ? ? ? Map Reduce Local Work
? Stage: Stage-0
? ? Fetch Operator
? ? ? limit: -1
? ? ? Processor Tree:
? ? ? ? ListSink
select?*?from?emp e
left?join?dept d?on (e.deptno=d.deptno and? d.dt='2018-06-04');
花費(fèi)時(shí)間:Time taken: 23.804 seconds, Fetched: 17 row(s)
STAGE DEPENDENCIES:
? Stage-4 is a root stage
? Stage-3 depends on stages: Stage-4
? Stage-0 depends on stages: Stage-3
STAGE PLANS:
? Stage: Stage-4
? ? Map Reduce Local Work
? ? ? Alias -> Map Local Tables:
? ? ? ? d
? ? ? ? ? Fetch Operator
? ? ? ? ? ? limit: -1
? ? ? Alias -> Map Local Operator Tree:
? ? ? ? d
? ? ? ? ? TableScan
? ? ? ? ? ? alias: d
? ? ? ? ? ? filterExpr: (dt = '2018-06-04') (type: boolean)
? ? ? ? ? ? Statistics: Num rows: 1 Data size: 84 Basic stats: PARTIAL Column stats: PARTIAL
? ? ? ? ? ? HashTable Sink Operator
? ? ? ? ? ? ? keys:
? ? ? ? ? ? ? ? 0 deptno (type: string)
? ? ? ? ? ? ? ? 1 deptno (type: string)
? Stage: Stage-3
? ? Map Reduce
? ? ? Map Operator Tree:
? ? ? ? ? TableScan
? ? ? ? ? ? alias: e
? ? ? ? ? ? Statistics: Num rows: 1 Data size: 757 Basic stats: PARTIAL Column stats: PARTIAL
? ? ? ? ? ? Map Join Operator
? ? ? ? ? ? ? condition map:
? ? ? ? ? ? ? ? ? ?Left Outer Join0 to 1
? ? ? ? ? ? ? keys:
? ? ? ? ? ? ? ? 0 deptno (type: string)
? ? ? ? ? ? ? ? 1 deptno (type: string)
? ? ? ? ? ? ? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col12, _col13, _col14, _col15
? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? Select Operator
? ? ? ? ? ? ? ? expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: string), _col7 (type: string), _col8 (type: strin
g), _col12 (type: string), _col13 (type: string), _col14 (type: string), _col15 (type: string)? ? ? ? ? ? ? ? outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
? ? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? ? File Output Operator
? ? ? ? ? ? ? ? ? compressed: false
? ? ? ? ? ? ? ? ? Statistics: Num rows: 1 Data size: 832 Basic stats: COMPLETE Column stats: NONE
? ? ? ? ? ? ? ? ? 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
? ? ? Local Work:
? ? ? ? Map Reduce Local Work
? Stage: Stage-0
? ? Fetch Operator
? ? ? limit: -1
? ? ? Processor Tree:
? ? ? ? ListSink
