http://git-wip-us.apache.org/repos/asf/hive/blob/a5d5473f/ql/src/test/results/clientpositive/spark/parquet_vectorization_13.q.out
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diff --git 
a/ql/src/test/results/clientpositive/spark/parquet_vectorization_13.q.out 
b/ql/src/test/results/clientpositive/spark/parquet_vectorization_13.q.out
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--- a/ql/src/test/results/clientpositive/spark/parquet_vectorization_13.q.out
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@@ -1,679 +0,0 @@
-PREHOOK: query: EXPLAIN VECTORIZATION DETAIL
-SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > 11)
-              AND ((ctimestamp2 != 12)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-PREHOOK: type: QUERY
-POSTHOOK: query: EXPLAIN VECTORIZATION DETAIL
-SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > 11)
-              AND ((ctimestamp2 != 12)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-POSTHOOK: type: QUERY
-PLAN VECTORIZATION:
-  enabled: true
-  enabledConditionsMet: [hive.vectorized.execution.enabled IS true]
-
-STAGE DEPENDENCIES:
-  Stage-1 is a root stage
-  Stage-0 depends on stages: Stage-1
-
-STAGE PLANS:
-  Stage: Stage-1
-    Spark
-      Edges:
-        Reducer 2 <- Map 1 (GROUP, 2)
-        Reducer 3 <- Reducer 2 (SORT, 1)
-#### A masked pattern was here ####
-      Vertices:
-        Map 1 
-            Map Operator Tree:
-                TableScan
-                  alias: alltypesparquet
-                  Statistics: Num rows: 12288 Data size: 147456 Basic stats: 
COMPLETE Column stats: NONE
-                  TableScan Vectorization:
-                      native: true
-                      vectorizationSchemaColumns: [0:ctinyint:tinyint, 
1:csmallint:smallint, 2:cint:int, 3:cbigint:bigint, 4:cfloat:float, 
5:cdouble:double, 6:cstring1:string, 7:cstring2:string, 
8:ctimestamp1:timestamp, 9:ctimestamp2:timestamp, 10:cboolean1:boolean, 
11:cboolean2:boolean, 
12:ROW__ID:struct<transactionid:bigint,bucketid:int,rowid:bigint>]
-                  Filter Operator
-                    Filter Vectorization:
-                        className: VectorFilterOperator
-                        native: true
-                        predicateExpression: FilterExprOrExpr(children: 
FilterExprAndExpr(children: FilterDoubleColLessDoubleScalar(col 4:float, val 
3569.0), FilterDoubleScalarGreaterEqualDoubleColumn(val 10.175, col 5:double), 
FilterLongColNotEqualLongScalar(col 10:boolean, val 1)), 
FilterExprAndExpr(children: FilterDoubleColGreaterDoubleScalar(col 13:double, 
val 11.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), 
FilterDoubleColNotEqualDoubleScalar(col 13:double, val 12.0)(children: 
CastTimestampToDouble(col 9:timestamp) -> 13:double), 
FilterDecimalColLessDecimalScalar(col 14:decimal(11,4), val 
9763215.5639)(children: CastLongToDecimal(col 0:tinyint) -> 14:decimal(11,4))))
-                    predicate: (((UDFToDouble(ctimestamp1) > 11.0) and 
(UDFToDouble(ctimestamp2) <> 12.0) and (CAST( ctinyint AS decimal(11,4)) < 
9763215.5639)) or ((cfloat < 3569) and (10.175 >= cdouble) and (cboolean1 <> 
1))) (type: boolean)
-                    Statistics: Num rows: 2730 Data size: 32760 Basic stats: 
COMPLETE Column stats: NONE
-                    Select Operator
-                      expressions: ctinyint (type: tinyint), cfloat (type: 
float), cstring1 (type: string), ctimestamp1 (type: timestamp), cboolean1 
(type: boolean)
-                      outputColumnNames: ctinyint, cfloat, cstring1, 
ctimestamp1, cboolean1
-                      Select Vectorization:
-                          className: VectorSelectOperator
-                          native: true
-                          projectedOutputColumnNums: [0, 4, 6, 8, 10]
-                      Statistics: Num rows: 2730 Data size: 32760 Basic stats: 
COMPLETE Column stats: NONE
-                      Group By Operator
-                        aggregations: max(ctinyint), sum(cfloat), 
stddev_pop(cfloat), stddev_pop(ctinyint), max(cfloat), min(ctinyint)
-                        Group By Vectorization:
-                            aggregators: VectorUDAFMaxLong(col 0:tinyint) -> 
tinyint, VectorUDAFSumDouble(col 4:float) -> double, VectorUDAFVarDouble(col 
4:float) -> struct<count:bigint,sum:double,variance:double> aggregation: 
stddev_pop, VectorUDAFVarLong(col 0:tinyint) -> 
struct<count:bigint,sum:double,variance:double> aggregation: stddev_pop, 
VectorUDAFMaxDouble(col 4:float) -> float, VectorUDAFMinLong(col 0:tinyint) -> 
tinyint
-                            className: VectorGroupByOperator
-                            groupByMode: HASH
-                            keyExpressions: col 10:boolean, col 0:tinyint, col 
8:timestamp, col 4:float, col 6:string
-                            native: false
-                            vectorProcessingMode: HASH
-                            projectedOutputColumnNums: [0, 1, 2, 3, 4, 5]
-                        keys: cboolean1 (type: boolean), ctinyint (type: 
tinyint), ctimestamp1 (type: timestamp), cfloat (type: float), cstring1 (type: 
string)
-                        mode: hash
-                        outputColumnNames: _col0, _col1, _col2, _col3, _col4, 
_col5, _col6, _col7, _col8, _col9, _col10
-                        Statistics: Num rows: 2730 Data size: 32760 Basic 
stats: COMPLETE Column stats: NONE
-                        Reduce Output Operator
-                          key expressions: _col0 (type: boolean), _col1 (type: 
tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 (type: string)
-                          sort order: +++++
-                          Map-reduce partition columns: _col0 (type: boolean), 
_col1 (type: tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 
(type: string)
-                          Reduce Sink Vectorization:
-                              className: VectorReduceSinkMultiKeyOperator
-                              keyColumnNums: [0, 1, 2, 3, 4]
-                              native: true
-                              nativeConditionsMet: 
hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine 
spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS 
true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true
-                              valueColumnNums: [5, 6, 7, 8, 9, 10]
-                          Statistics: Num rows: 2730 Data size: 32760 Basic 
stats: COMPLETE Column stats: NONE
-                          value expressions: _col5 (type: tinyint), _col6 
(type: double), _col7 (type: struct<count:bigint,sum:double,variance:double>), 
_col8 (type: struct<count:bigint,sum:double,variance:double>), _col9 (type: 
float), _col10 (type: tinyint)
-            Execution mode: vectorized
-            Map Vectorization:
-                enabled: true
-                enabledConditionsMet: 
hive.vectorized.use.vectorized.input.format IS true
-                inputFormatFeatureSupport: []
-                featureSupportInUse: []
-                inputFileFormats: 
org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-                rowBatchContext:
-                    dataColumnCount: 12
-                    includeColumns: [0, 4, 5, 6, 8, 9, 10]
-                    dataColumns: ctinyint:tinyint, csmallint:smallint, 
cint:int, cbigint:bigint, cfloat:float, cdouble:double, cstring1:string, 
cstring2:string, ctimestamp1:timestamp, ctimestamp2:timestamp, 
cboolean1:boolean, cboolean2:boolean
-                    partitionColumnCount: 0
-                    scratchColumnTypeNames: [double, decimal(11,4)]
-        Reducer 2 
-            Execution mode: vectorized
-            Reduce Vectorization:
-                enabled: true
-                enableConditionsMet: hive.vectorized.execution.reduce.enabled 
IS true, hive.execution.engine spark IN [tez, spark] IS true
-                reduceColumnNullOrder: aaaaa
-                reduceColumnSortOrder: +++++
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-                rowBatchContext:
-                    dataColumnCount: 11
-                    dataColumns: KEY._col0:boolean, KEY._col1:tinyint, 
KEY._col2:timestamp, KEY._col3:float, KEY._col4:string, VALUE._col0:tinyint, 
VALUE._col1:double, 
VALUE._col2:struct<count:bigint,sum:double,variance:double>, 
VALUE._col3:struct<count:bigint,sum:double,variance:double>, VALUE._col4:float, 
VALUE._col5:tinyint
-                    partitionColumnCount: 0
-                    scratchColumnTypeNames: []
-            Reduce Operator Tree:
-              Group By Operator
-                aggregations: max(VALUE._col0), sum(VALUE._col1), 
stddev_pop(VALUE._col2), stddev_pop(VALUE._col3), max(VALUE._col4), 
min(VALUE._col5)
-                Group By Vectorization:
-                    aggregators: VectorUDAFMaxLong(col 5:tinyint) -> tinyint, 
VectorUDAFSumDouble(col 6:double) -> double, VectorUDAFVarFinal(col 
7:struct<count:bigint,sum:double,variance:double>) -> double aggregation: 
stddev_pop, VectorUDAFVarFinal(col 
8:struct<count:bigint,sum:double,variance:double>) -> double aggregation: 
stddev_pop, VectorUDAFMaxDouble(col 9:float) -> float, VectorUDAFMinLong(col 
10:tinyint) -> tinyint
-                    className: VectorGroupByOperator
-                    groupByMode: MERGEPARTIAL
-                    keyExpressions: col 0:boolean, col 1:tinyint, col 
2:timestamp, col 3:float, col 4:string
-                    native: false
-                    vectorProcessingMode: MERGE_PARTIAL
-                    projectedOutputColumnNums: [0, 1, 2, 3, 4, 5]
-                keys: KEY._col0 (type: boolean), KEY._col1 (type: tinyint), 
KEY._col2 (type: timestamp), KEY._col3 (type: float), KEY._col4 (type: string)
-                mode: mergepartial
-                outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10
-                Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                Select Operator
-                  expressions: _col0 (type: boolean), _col1 (type: tinyint), 
_col2 (type: timestamp), _col3 (type: float), _col4 (type: string), (- _col1) 
(type: tinyint), _col5 (type: tinyint), ((- _col1) + _col5) (type: tinyint), 
_col6 (type: double), (_col6 * UDFToDouble(((- _col1) + _col5))) (type: 
double), (- _col6) (type: double), (79.553 * _col3) (type: float), _col7 (type: 
double), (- _col6) (type: double), _col8 (type: double), (CAST( ((- _col1) + 
_col5) AS decimal(3,0)) - 10.175) (type: decimal(7,3)), (- (- _col6)) (type: 
double), (-26.28 / (- (- _col6))) (type: double), _col9 (type: float), ((_col6 
* UDFToDouble(((- _col1) + _col5))) / UDFToDouble(_col1)) (type: double), 
_col10 (type: tinyint)
-                  outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, 
_col16, _col17, _col18, _col19, _col20
-                  Select Vectorization:
-                      className: VectorSelectOperator
-                      native: true
-                      projectedOutputColumnNums: [0, 1, 2, 3, 4, 11, 5, 13, 6, 
16, 15, 17, 7, 18, 8, 20, 22, 21, 9, 25, 10]
-                      selectExpressions: LongColUnaryMinus(col 1:tinyint) -> 
11:tinyint, LongColAddLongColumn(col 12:tinyint, col 5:tinyint)(children: 
LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 13:tinyint, 
DoubleColMultiplyDoubleColumn(col 6:double, col 15:double)(children: 
CastLongToDouble(col 14:tinyint)(children: LongColAddLongColumn(col 12:tinyint, 
col 5:tinyint)(children: LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 
14:tinyint) -> 15:double) -> 16:double, DoubleColUnaryMinus(col 6:double) -> 
15:double, DoubleScalarMultiplyDoubleColumn(val 79.5530014038086, col 3:float) 
-> 17:float, DoubleColUnaryMinus(col 6:double) -> 18:double, 
DecimalColSubtractDecimalScalar(col 19:decimal(3,0), val 10.175)(children: 
CastLongToDecimal(col 14:tinyint)(children: LongColAddLongColumn(col 
12:tinyint, col 5:tinyint)(children: LongColUnaryMinus(col 1:tinyint) -> 
12:tinyint) -> 14:tinyint) -> 19:decimal(3,0)) -> 20:decimal(7,3), 
DoubleColUnaryMinus(col 21:double)(children: DoubleColUna
 ryMinus(col 6:double) -> 21:double) -> 22:double, 
DoubleScalarDivideDoubleColumn(val -26.28, col 23:double)(children: 
DoubleColUnaryMinus(col 21:double)(children: DoubleColUnaryMinus(col 6:double) 
-> 21:double) -> 23:double) -> 21:double, DoubleColDivideDoubleColumn(col 
24:double, col 23:double)(children: DoubleColMultiplyDoubleColumn(col 6:double, 
col 23:double)(children: CastLongToDouble(col 14:tinyint)(children: 
LongColAddLongColumn(col 12:tinyint, col 5:tinyint)(children: 
LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 14:tinyint) -> 23:double) -> 
24:double, CastLongToDouble(col 1:tinyint) -> 23:double) -> 25:double
-                  Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                  Reduce Output Operator
-                    key expressions: _col0 (type: boolean), _col1 (type: 
tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 (type: string), 
_col5 (type: tinyint), _col6 (type: tinyint), _col7 (type: tinyint), _col8 
(type: double), _col9 (type: double), _col10 (type: double), _col11 (type: 
float), _col12 (type: double), _col13 (type: double), _col14 (type: double), 
_col15 (type: decimal(7,3)), _col16 (type: double), _col17 (type: double), 
_col18 (type: float), _col19 (type: double), _col20 (type: tinyint)
-                    sort order: +++++++++++++++++++++
-                    Reduce Sink Vectorization:
-                        className: VectorReduceSinkObjectHashOperator
-                        keyColumnNums: [0, 1, 2, 3, 4, 11, 5, 13, 6, 16, 15, 
17, 7, 18, 8, 20, 22, 21, 9, 25, 10]
-                        native: true
-                        nativeConditionsMet: 
hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine 
spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS 
true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true
-                        valueColumnNums: []
-                    Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                    TopN Hash Memory Usage: 0.1
-        Reducer 3 
-            Execution mode: vectorized
-            Reduce Vectorization:
-                enabled: true
-                enableConditionsMet: hive.vectorized.execution.reduce.enabled 
IS true, hive.execution.engine spark IN [tez, spark] IS true
-                reduceColumnNullOrder: aaaaaaaaaaaaaaaaaaaaa
-                reduceColumnSortOrder: +++++++++++++++++++++
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-                rowBatchContext:
-                    dataColumnCount: 21
-                    dataColumns: KEY.reducesinkkey0:boolean, 
KEY.reducesinkkey1:tinyint, KEY.reducesinkkey2:timestamp, 
KEY.reducesinkkey3:float, KEY.reducesinkkey4:string, 
KEY.reducesinkkey5:tinyint, KEY.reducesinkkey6:tinyint, 
KEY.reducesinkkey7:tinyint, KEY.reducesinkkey8:double, 
KEY.reducesinkkey9:double, KEY.reducesinkkey10:double, 
KEY.reducesinkkey11:float, KEY.reducesinkkey12:double, 
KEY.reducesinkkey13:double, KEY.reducesinkkey14:double, 
KEY.reducesinkkey15:decimal(7,3), KEY.reducesinkkey16:double, 
KEY.reducesinkkey17:double, KEY.reducesinkkey18:float, 
KEY.reducesinkkey19:double, KEY.reducesinkkey20:tinyint
-                    partitionColumnCount: 0
-                    scratchColumnTypeNames: []
-            Reduce Operator Tree:
-              Select Operator
-                expressions: KEY.reducesinkkey0 (type: boolean), 
KEY.reducesinkkey1 (type: tinyint), KEY.reducesinkkey2 (type: timestamp), 
KEY.reducesinkkey3 (type: float), KEY.reducesinkkey4 (type: string), 
KEY.reducesinkkey5 (type: tinyint), KEY.reducesinkkey6 (type: tinyint), 
KEY.reducesinkkey7 (type: tinyint), KEY.reducesinkkey8 (type: double), 
KEY.reducesinkkey9 (type: double), KEY.reducesinkkey10 (type: double), 
KEY.reducesinkkey11 (type: float), KEY.reducesinkkey12 (type: double), 
KEY.reducesinkkey10 (type: double), KEY.reducesinkkey14 (type: double), 
KEY.reducesinkkey15 (type: decimal(7,3)), KEY.reducesinkkey16 (type: double), 
KEY.reducesinkkey17 (type: double), KEY.reducesinkkey18 (type: float), 
KEY.reducesinkkey19 (type: double), KEY.reducesinkkey20 (type: tinyint)
-                outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, 
_col16, _col17, _col18, _col19, _col20
-                Select Vectorization:
-                    className: VectorSelectOperator
-                    native: true
-                    projectedOutputColumnNums: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 10, 14, 15, 16, 17, 18, 19, 20]
-                Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                Limit
-                  Number of rows: 40
-                  Limit Vectorization:
-                      className: VectorLimitOperator
-                      native: true
-                  Statistics: Num rows: 40 Data size: 480 Basic stats: 
COMPLETE Column stats: NONE
-                  File Output Operator
-                    compressed: false
-                    File Sink Vectorization:
-                        className: VectorFileSinkOperator
-                        native: false
-                    Statistics: Num rows: 40 Data size: 480 Basic stats: 
COMPLETE Column stats: NONE
-                    table:
-                        input format: 
org.apache.hadoop.mapred.SequenceFileInputFormat
-                        output format: 
org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
-                        serde: 
org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
-
-  Stage: Stage-0
-    Fetch Operator
-      limit: 40
-      Processor Tree:
-        ListSink
-
-PREHOOK: query: SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > 11)
-              AND ((ctimestamp2 != 12)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-PREHOOK: type: QUERY
-PREHOOK: Input: default@alltypesparquet
-#### A masked pattern was here ####
-POSTHOOK: query: SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > 11)
-              AND ((ctimestamp2 != 12)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-POSTHOOK: type: QUERY
-POSTHOOK: Input: default@alltypesparquet
-#### A masked pattern was here ####
-NULL   -55     1969-12-31 16:00:11.38  -55.0   NULL    55      -55     0       
-55.0   -0.0    55.0    -4375.415       0.0     55.0    0.0     -10.175 -55.0   
0.47781818181818186     -55.0   0.0     -55
-NULL   -55     1969-12-31 16:00:11.751 -55.0   NULL    55      -55     0       
-55.0   -0.0    55.0    -4375.415       0.0     55.0    0.0     -10.175 -55.0   
0.47781818181818186     -55.0   0.0     -55
-NULL   -56     1969-12-31 16:00:13.602 -56.0   NULL    56      -56     0       
-56.0   -0.0    56.0    -4454.9683      0.0     56.0    0.0     -10.175 -56.0   
0.4692857142857143      -56.0   0.0     -56
-NULL   -56     1969-12-31 16:00:13.958 -56.0   NULL    56      -56     0       
-56.0   -0.0    56.0    -4454.9683      0.0     56.0    0.0     -10.175 -56.0   
0.4692857142857143      -56.0   0.0     -56
-NULL   -56     1969-12-31 16:00:15.038 -56.0   NULL    56      -56     0       
-56.0   -0.0    56.0    -4454.9683      0.0     56.0    0.0     -10.175 -56.0   
0.4692857142857143      -56.0   0.0     -56
-NULL   -57     1969-12-31 16:00:11.451 -57.0   NULL    57      -57     0       
-57.0   -0.0    57.0    -4534.521       0.0     57.0    0.0     -10.175 -57.0   
0.4610526315789474      -57.0   0.0     -57
-NULL   -57     1969-12-31 16:00:11.883 -57.0   NULL    57      -57     0       
-57.0   -0.0    57.0    -4534.521       0.0     57.0    0.0     -10.175 -57.0   
0.4610526315789474      -57.0   0.0     -57
-NULL   -57     1969-12-31 16:00:12.626 -57.0   NULL    57      -57     0       
-57.0   -0.0    57.0    -4534.521       0.0     57.0    0.0     -10.175 -57.0   
0.4610526315789474      -57.0   0.0     -57
-NULL   -57     1969-12-31 16:00:13.578 -57.0   NULL    57      -57     0       
-57.0   -0.0    57.0    -4534.521       0.0     57.0    0.0     -10.175 -57.0   
0.4610526315789474      -57.0   0.0     -57
-NULL   -57     1969-12-31 16:00:15.39  -57.0   NULL    57      -57     0       
-57.0   -0.0    57.0    -4534.521       0.0     57.0    0.0     -10.175 -57.0   
0.4610526315789474      -57.0   0.0     -57
-NULL   -58     1969-12-31 16:00:12.065 -58.0   NULL    58      -58     0       
-58.0   -0.0    58.0    -4614.074       0.0     58.0    0.0     -10.175 -58.0   
0.4531034482758621      -58.0   0.0     -58
-NULL   -58     1969-12-31 16:00:12.683 -58.0   NULL    58      -58     0       
-58.0   -0.0    58.0    -4614.074       0.0     58.0    0.0     -10.175 -58.0   
0.4531034482758621      -58.0   0.0     -58
-NULL   -58     1969-12-31 16:00:12.948 -58.0   NULL    58      -58     0       
-58.0   -0.0    58.0    -4614.074       0.0     58.0    0.0     -10.175 -58.0   
0.4531034482758621      -58.0   0.0     -58
-NULL   -58     1969-12-31 16:00:14.066 -58.0   NULL    58      -58     0       
-58.0   -0.0    58.0    -4614.074       0.0     58.0    0.0     -10.175 -58.0   
0.4531034482758621      -58.0   0.0     -58
-NULL   -58     1969-12-31 16:00:15.658 -58.0   NULL    58      -58     0       
-58.0   -0.0    58.0    -4614.074       0.0     58.0    0.0     -10.175 -58.0   
0.4531034482758621      -58.0   0.0     -58
-NULL   -59     1969-12-31 16:00:12.008 -59.0   NULL    59      -59     0       
-59.0   -0.0    59.0    -4693.627       0.0     59.0    0.0     -10.175 -59.0   
0.44542372881355935     -59.0   0.0     -59
-NULL   -59     1969-12-31 16:00:13.15  -59.0   NULL    59      -59     0       
-59.0   -0.0    59.0    -4693.627       0.0     59.0    0.0     -10.175 -59.0   
0.44542372881355935     -59.0   0.0     -59
-NULL   -59     1969-12-31 16:00:13.625 -59.0   NULL    59      -59     0       
-59.0   -0.0    59.0    -4693.627       0.0     59.0    0.0     -10.175 -59.0   
0.44542372881355935     -59.0   0.0     -59
-NULL   -59     1969-12-31 16:00:15.296 -59.0   NULL    59      -59     0       
-59.0   -0.0    59.0    -4693.627       0.0     59.0    0.0     -10.175 -59.0   
0.44542372881355935     -59.0   0.0     -59
-NULL   -59     1969-12-31 16:00:15.861 -59.0   NULL    59      -59     0       
-59.0   -0.0    59.0    -4693.627       0.0     59.0    0.0     -10.175 -59.0   
0.44542372881355935     -59.0   0.0     -59
-NULL   -60     1969-12-31 16:00:11.504 -60.0   NULL    60      -60     0       
-60.0   -0.0    60.0    -4773.18        0.0     60.0    0.0     -10.175 -60.0   
0.438   -60.0   0.0     -60
-NULL   -60     1969-12-31 16:00:11.641 -60.0   NULL    60      -60     0       
-60.0   -0.0    60.0    -4773.18        0.0     60.0    0.0     -10.175 -60.0   
0.438   -60.0   0.0     -60
-NULL   -60     1969-12-31 16:00:11.996 -60.0   NULL    60      -60     0       
-60.0   -0.0    60.0    -4773.18        0.0     60.0    0.0     -10.175 -60.0   
0.438   -60.0   0.0     -60
-NULL   -60     1969-12-31 16:00:12.779 -60.0   NULL    60      -60     0       
-60.0   -0.0    60.0    -4773.18        0.0     60.0    0.0     -10.175 -60.0   
0.438   -60.0   0.0     -60
-NULL   -61     1969-12-31 16:00:11.842 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:12.454 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:14.192 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:16.558 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -62     1969-12-31 16:00:12.388 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:12.591 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.154 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.247 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.517 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.965 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -63     1969-12-31 16:00:11.946 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:12.188 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:15.436 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -64     1969-12-31 16:00:11.912 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:12.339 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:13.274 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-PREHOOK: query: EXPLAIN VECTORIZATION EXPRESSION
-SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > -1.388)
-              AND ((ctimestamp2 != -1.3359999999999999)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-PREHOOK: type: QUERY
-POSTHOOK: query: EXPLAIN VECTORIZATION EXPRESSION
-SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > -1.388)
-              AND ((ctimestamp2 != -1.3359999999999999)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-POSTHOOK: type: QUERY
-PLAN VECTORIZATION:
-  enabled: true
-  enabledConditionsMet: [hive.vectorized.execution.enabled IS true]
-
-STAGE DEPENDENCIES:
-  Stage-1 is a root stage
-  Stage-0 depends on stages: Stage-1
-
-STAGE PLANS:
-  Stage: Stage-1
-    Spark
-      Edges:
-        Reducer 2 <- Map 1 (GROUP, 2)
-        Reducer 3 <- Reducer 2 (SORT, 1)
-#### A masked pattern was here ####
-      Vertices:
-        Map 1 
-            Map Operator Tree:
-                TableScan
-                  alias: alltypesparquet
-                  Statistics: Num rows: 12288 Data size: 147456 Basic stats: 
COMPLETE Column stats: NONE
-                  TableScan Vectorization:
-                      native: true
-                  Filter Operator
-                    Filter Vectorization:
-                        className: VectorFilterOperator
-                        native: true
-                        predicateExpression: FilterExprOrExpr(children: 
FilterExprAndExpr(children: FilterDoubleColLessDoubleScalar(col 4:float, val 
3569.0), FilterDoubleScalarGreaterEqualDoubleColumn(val 10.175, col 5:double), 
FilterLongColNotEqualLongScalar(col 10:boolean, val 1)), 
FilterExprAndExpr(children: FilterDoubleColGreaterDoubleScalar(col 13:double, 
val -1.388)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), 
FilterDoubleColNotEqualDoubleScalar(col 13:double, val 
-1.3359999999999999)(children: CastTimestampToDouble(col 9:timestamp) -> 
13:double), FilterDecimalColLessDecimalScalar(col 14:decimal(11,4), val 
9763215.5639)(children: CastLongToDecimal(col 0:tinyint) -> 14:decimal(11,4))))
-                    predicate: (((UDFToDouble(ctimestamp1) > -1.388) and 
(UDFToDouble(ctimestamp2) <> -1.3359999999999999) and (CAST( ctinyint AS 
decimal(11,4)) < 9763215.5639)) or ((cfloat < 3569) and (10.175 >= cdouble) and 
(cboolean1 <> 1))) (type: boolean)
-                    Statistics: Num rows: 2730 Data size: 32760 Basic stats: 
COMPLETE Column stats: NONE
-                    Select Operator
-                      expressions: ctinyint (type: tinyint), cfloat (type: 
float), cstring1 (type: string), ctimestamp1 (type: timestamp), cboolean1 
(type: boolean)
-                      outputColumnNames: ctinyint, cfloat, cstring1, 
ctimestamp1, cboolean1
-                      Select Vectorization:
-                          className: VectorSelectOperator
-                          native: true
-                          projectedOutputColumnNums: [0, 4, 6, 8, 10]
-                      Statistics: Num rows: 2730 Data size: 32760 Basic stats: 
COMPLETE Column stats: NONE
-                      Group By Operator
-                        aggregations: max(ctinyint), sum(cfloat), 
stddev_pop(cfloat), stddev_pop(ctinyint), max(cfloat), min(ctinyint)
-                        Group By Vectorization:
-                            aggregators: VectorUDAFMaxLong(col 0:tinyint) -> 
tinyint, VectorUDAFSumDouble(col 4:float) -> double, VectorUDAFVarDouble(col 
4:float) -> struct<count:bigint,sum:double,variance:double> aggregation: 
stddev_pop, VectorUDAFVarLong(col 0:tinyint) -> 
struct<count:bigint,sum:double,variance:double> aggregation: stddev_pop, 
VectorUDAFMaxDouble(col 4:float) -> float, VectorUDAFMinLong(col 0:tinyint) -> 
tinyint
-                            className: VectorGroupByOperator
-                            groupByMode: HASH
-                            keyExpressions: col 10:boolean, col 0:tinyint, col 
8:timestamp, col 4:float, col 6:string
-                            native: false
-                            vectorProcessingMode: HASH
-                            projectedOutputColumnNums: [0, 1, 2, 3, 4, 5]
-                        keys: cboolean1 (type: boolean), ctinyint (type: 
tinyint), ctimestamp1 (type: timestamp), cfloat (type: float), cstring1 (type: 
string)
-                        mode: hash
-                        outputColumnNames: _col0, _col1, _col2, _col3, _col4, 
_col5, _col6, _col7, _col8, _col9, _col10
-                        Statistics: Num rows: 2730 Data size: 32760 Basic 
stats: COMPLETE Column stats: NONE
-                        Reduce Output Operator
-                          key expressions: _col0 (type: boolean), _col1 (type: 
tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 (type: string)
-                          sort order: +++++
-                          Map-reduce partition columns: _col0 (type: boolean), 
_col1 (type: tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 
(type: string)
-                          Reduce Sink Vectorization:
-                              className: VectorReduceSinkMultiKeyOperator
-                              native: true
-                              nativeConditionsMet: 
hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine 
spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS 
true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true
-                          Statistics: Num rows: 2730 Data size: 32760 Basic 
stats: COMPLETE Column stats: NONE
-                          value expressions: _col5 (type: tinyint), _col6 
(type: double), _col7 (type: struct<count:bigint,sum:double,variance:double>), 
_col8 (type: struct<count:bigint,sum:double,variance:double>), _col9 (type: 
float), _col10 (type: tinyint)
-            Execution mode: vectorized
-            Map Vectorization:
-                enabled: true
-                enabledConditionsMet: 
hive.vectorized.use.vectorized.input.format IS true
-                inputFormatFeatureSupport: []
-                featureSupportInUse: []
-                inputFileFormats: 
org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-        Reducer 2 
-            Execution mode: vectorized
-            Reduce Vectorization:
-                enabled: true
-                enableConditionsMet: hive.vectorized.execution.reduce.enabled 
IS true, hive.execution.engine spark IN [tez, spark] IS true
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-            Reduce Operator Tree:
-              Group By Operator
-                aggregations: max(VALUE._col0), sum(VALUE._col1), 
stddev_pop(VALUE._col2), stddev_pop(VALUE._col3), max(VALUE._col4), 
min(VALUE._col5)
-                Group By Vectorization:
-                    aggregators: VectorUDAFMaxLong(col 5:tinyint) -> tinyint, 
VectorUDAFSumDouble(col 6:double) -> double, VectorUDAFVarFinal(col 
7:struct<count:bigint,sum:double,variance:double>) -> double aggregation: 
stddev_pop, VectorUDAFVarFinal(col 
8:struct<count:bigint,sum:double,variance:double>) -> double aggregation: 
stddev_pop, VectorUDAFMaxDouble(col 9:float) -> float, VectorUDAFMinLong(col 
10:tinyint) -> tinyint
-                    className: VectorGroupByOperator
-                    groupByMode: MERGEPARTIAL
-                    keyExpressions: col 0:boolean, col 1:tinyint, col 
2:timestamp, col 3:float, col 4:string
-                    native: false
-                    vectorProcessingMode: MERGE_PARTIAL
-                    projectedOutputColumnNums: [0, 1, 2, 3, 4, 5]
-                keys: KEY._col0 (type: boolean), KEY._col1 (type: tinyint), 
KEY._col2 (type: timestamp), KEY._col3 (type: float), KEY._col4 (type: string)
-                mode: mergepartial
-                outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10
-                Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                Select Operator
-                  expressions: _col0 (type: boolean), _col1 (type: tinyint), 
_col2 (type: timestamp), _col3 (type: float), _col4 (type: string), (- _col1) 
(type: tinyint), _col5 (type: tinyint), ((- _col1) + _col5) (type: tinyint), 
_col6 (type: double), (_col6 * UDFToDouble(((- _col1) + _col5))) (type: 
double), (- _col6) (type: double), (79.553 * _col3) (type: float), _col7 (type: 
double), (- _col6) (type: double), _col8 (type: double), (CAST( ((- _col1) + 
_col5) AS decimal(3,0)) - 10.175) (type: decimal(7,3)), (- (- _col6)) (type: 
double), (-26.28 / (- (- _col6))) (type: double), _col9 (type: float), ((_col6 
* UDFToDouble(((- _col1) + _col5))) / UDFToDouble(_col1)) (type: double), 
_col10 (type: tinyint)
-                  outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, 
_col16, _col17, _col18, _col19, _col20
-                  Select Vectorization:
-                      className: VectorSelectOperator
-                      native: true
-                      projectedOutputColumnNums: [0, 1, 2, 3, 4, 11, 5, 13, 6, 
16, 15, 17, 7, 18, 8, 20, 22, 21, 9, 25, 10]
-                      selectExpressions: LongColUnaryMinus(col 1:tinyint) -> 
11:tinyint, LongColAddLongColumn(col 12:tinyint, col 5:tinyint)(children: 
LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 13:tinyint, 
DoubleColMultiplyDoubleColumn(col 6:double, col 15:double)(children: 
CastLongToDouble(col 14:tinyint)(children: LongColAddLongColumn(col 12:tinyint, 
col 5:tinyint)(children: LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 
14:tinyint) -> 15:double) -> 16:double, DoubleColUnaryMinus(col 6:double) -> 
15:double, DoubleScalarMultiplyDoubleColumn(val 79.5530014038086, col 3:float) 
-> 17:float, DoubleColUnaryMinus(col 6:double) -> 18:double, 
DecimalColSubtractDecimalScalar(col 19:decimal(3,0), val 10.175)(children: 
CastLongToDecimal(col 14:tinyint)(children: LongColAddLongColumn(col 
12:tinyint, col 5:tinyint)(children: LongColUnaryMinus(col 1:tinyint) -> 
12:tinyint) -> 14:tinyint) -> 19:decimal(3,0)) -> 20:decimal(7,3), 
DoubleColUnaryMinus(col 21:double)(children: DoubleColUna
 ryMinus(col 6:double) -> 21:double) -> 22:double, 
DoubleScalarDivideDoubleColumn(val -26.28, col 23:double)(children: 
DoubleColUnaryMinus(col 21:double)(children: DoubleColUnaryMinus(col 6:double) 
-> 21:double) -> 23:double) -> 21:double, DoubleColDivideDoubleColumn(col 
24:double, col 23:double)(children: DoubleColMultiplyDoubleColumn(col 6:double, 
col 23:double)(children: CastLongToDouble(col 14:tinyint)(children: 
LongColAddLongColumn(col 12:tinyint, col 5:tinyint)(children: 
LongColUnaryMinus(col 1:tinyint) -> 12:tinyint) -> 14:tinyint) -> 23:double) -> 
24:double, CastLongToDouble(col 1:tinyint) -> 23:double) -> 25:double
-                  Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                  Reduce Output Operator
-                    key expressions: _col0 (type: boolean), _col1 (type: 
tinyint), _col2 (type: timestamp), _col3 (type: float), _col4 (type: string), 
_col5 (type: tinyint), _col6 (type: tinyint), _col7 (type: tinyint), _col8 
(type: double), _col9 (type: double), _col10 (type: double), _col11 (type: 
float), _col12 (type: double), _col13 (type: double), _col14 (type: double), 
_col15 (type: decimal(7,3)), _col16 (type: double), _col17 (type: double), 
_col18 (type: float), _col19 (type: double), _col20 (type: tinyint)
-                    sort order: +++++++++++++++++++++
-                    Reduce Sink Vectorization:
-                        className: VectorReduceSinkObjectHashOperator
-                        native: true
-                        nativeConditionsMet: 
hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine 
spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS 
true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true
-                    Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                    TopN Hash Memory Usage: 0.1
-        Reducer 3 
-            Execution mode: vectorized
-            Reduce Vectorization:
-                enabled: true
-                enableConditionsMet: hive.vectorized.execution.reduce.enabled 
IS true, hive.execution.engine spark IN [tez, spark] IS true
-                allNative: false
-                usesVectorUDFAdaptor: false
-                vectorized: true
-            Reduce Operator Tree:
-              Select Operator
-                expressions: KEY.reducesinkkey0 (type: boolean), 
KEY.reducesinkkey1 (type: tinyint), KEY.reducesinkkey2 (type: timestamp), 
KEY.reducesinkkey3 (type: float), KEY.reducesinkkey4 (type: string), 
KEY.reducesinkkey5 (type: tinyint), KEY.reducesinkkey6 (type: tinyint), 
KEY.reducesinkkey7 (type: tinyint), KEY.reducesinkkey8 (type: double), 
KEY.reducesinkkey9 (type: double), KEY.reducesinkkey10 (type: double), 
KEY.reducesinkkey11 (type: float), KEY.reducesinkkey12 (type: double), 
KEY.reducesinkkey10 (type: double), KEY.reducesinkkey14 (type: double), 
KEY.reducesinkkey15 (type: decimal(7,3)), KEY.reducesinkkey16 (type: double), 
KEY.reducesinkkey17 (type: double), KEY.reducesinkkey18 (type: float), 
KEY.reducesinkkey19 (type: double), KEY.reducesinkkey20 (type: tinyint)
-                outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, 
_col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, 
_col16, _col17, _col18, _col19, _col20
-                Select Vectorization:
-                    className: VectorSelectOperator
-                    native: true
-                    projectedOutputColumnNums: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 10, 14, 15, 16, 17, 18, 19, 20]
-                Statistics: Num rows: 1365 Data size: 16380 Basic stats: 
COMPLETE Column stats: NONE
-                Limit
-                  Number of rows: 40
-                  Limit Vectorization:
-                      className: VectorLimitOperator
-                      native: true
-                  Statistics: Num rows: 40 Data size: 480 Basic stats: 
COMPLETE Column stats: NONE
-                  File Output Operator
-                    compressed: false
-                    File Sink Vectorization:
-                        className: VectorFileSinkOperator
-                        native: false
-                    Statistics: Num rows: 40 Data size: 480 Basic stats: 
COMPLETE Column stats: NONE
-                    table:
-                        input format: 
org.apache.hadoop.mapred.SequenceFileInputFormat
-                        output format: 
org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
-                        serde: 
org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
-
-  Stage: Stage-0
-    Fetch Operator
-      limit: 40
-      Processor Tree:
-        ListSink
-
-PREHOOK: query: SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > -1.388)
-              AND ((ctimestamp2 != -1.3359999999999999)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-PREHOOK: type: QUERY
-PREHOOK: Input: default@alltypesparquet
-#### A masked pattern was here ####
-POSTHOOK: query: SELECT   cboolean1,
-         ctinyint,
-         ctimestamp1,
-         cfloat,
-         cstring1,
-         (-(ctinyint)) as c1,
-         MAX(ctinyint) as c2,
-         ((-(ctinyint)) + MAX(ctinyint)) as c3,
-         SUM(cfloat) as c4,
-         (SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) as c5,
-         (-(SUM(cfloat))) as c6,
-         (79.553 * cfloat) as c7,
-         STDDEV_POP(cfloat) as c8,
-         (-(SUM(cfloat))) as c9,
-         STDDEV_POP(ctinyint) as c10,
-         (((-(ctinyint)) + MAX(ctinyint)) - 10.175) as c11,
-         (-((-(SUM(cfloat))))) as c12,
-         (-26.28 / (-((-(SUM(cfloat)))))) as c13,
-         MAX(cfloat) as c14,
-         ((SUM(cfloat) * ((-(ctinyint)) + MAX(ctinyint))) / ctinyint) as c15,
-         MIN(ctinyint) as c16
-FROM     alltypesparquet
-WHERE    (((cfloat < 3569)
-           AND ((10.175 >= cdouble)
-                AND (cboolean1 != 1)))
-          OR ((ctimestamp1 > -1.388)
-              AND ((ctimestamp2 != -1.3359999999999999)
-                   AND (ctinyint < 9763215.5639))))
-GROUP BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1
-ORDER BY cboolean1, ctinyint, ctimestamp1, cfloat, cstring1, c1, c2, c3, c4, 
c5, c6, c7, c8, c9, c10, c11, c12, c13, c14, c15, c16
-LIMIT 40
-POSTHOOK: type: QUERY
-POSTHOOK: Input: default@alltypesparquet
-#### A masked pattern was here ####
-NULL   -61     1969-12-31 16:00:00.142 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:02.698 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:03.049 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:04.165 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -61     1969-12-31 16:00:04.977 -61.0   NULL    61      -61     0       
-61.0   -0.0    61.0    -4852.733       0.0     61.0    0.0     -10.175 -61.0   
0.4308196721311476      -61.0   0.0     -61
-NULL   -62     1969-12-31 16:00:00.037 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:01.22  -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:01.515 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:01.734 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:02.373 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:03.85  -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:08.198 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:09.025 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:09.889 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:10.069 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:10.225 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:10.485 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:12.388 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:12.591 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.154 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.247 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.517 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -62     1969-12-31 16:00:14.965 -62.0   NULL    62      -62     0       
-62.0   -0.0    62.0    -4932.286       0.0     62.0    0.0     -10.175 -62.0   
0.4238709677419355      -62.0   0.0     -62
-NULL   -63     1969-12-31 16:00:01.843 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:03.552 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:06.852 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:07.375 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:10.205 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:11.946 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:12.188 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -63     1969-12-31 16:00:15.436 -63.0   NULL    63      -63     0       
-63.0   -0.0    63.0    -5011.839       0.0     63.0    0.0     -10.175 -63.0   
0.41714285714285715     -63.0   0.0     -63
-NULL   -64     1969-12-31 16:00:00.199 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:00.29  -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:01.785 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:03.944 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:05.997 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:10.858 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:11.912 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:12.339 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64
-NULL   -64     1969-12-31 16:00:13.274 -64.0   NULL    64      -64     0       
-64.0   -0.0    64.0    -5091.392       0.0     64.0    0.0     -10.175 -64.0   
0.410625        -64.0   0.0     -64

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