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Posted to commits@hive.apache.org by xu...@apache.org on 2017/11/30 03:17:37 UTC
[09/32] hive git commit: HIVE-17528 : Add more q-tests for
Hive-on-Spark with Parquet vectorized reader (Ferdinand Xu,
reviewed by Vihang Karajgaonkar)
http://git-wip-us.apache.org/repos/asf/hive/blob/029e48b7/ql/src/test/results/clientpositive/spark/parquet_vectorization_15.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/spark/parquet_vectorization_15.q.out b/ql/src/test/results/clientpositive/spark/parquet_vectorization_15.q.out
new file mode 100644
index 0000000..c8ac3f2
--- /dev/null
+++ b/ql/src/test/results/clientpositive/spark/parquet_vectorization_15.q.out
@@ -0,0 +1,299 @@
+PREHOOK: query: EXPLAIN VECTORIZATION DETAIL
+SELECT cfloat,
+ cboolean1,
+ cdouble,
+ cstring1,
+ ctinyint,
+ cint,
+ ctimestamp1,
+ STDDEV_SAMP(cfloat),
+ (-26.28 - cint),
+ MIN(cdouble),
+ (cdouble * 79.553),
+ (33 % cfloat),
+ STDDEV_SAMP(ctinyint),
+ VAR_POP(ctinyint),
+ (-23 % cdouble),
+ (-(ctinyint)),
+ VAR_SAMP(cint),
+ (cint - cfloat),
+ (-23 % ctinyint),
+ (-((-26.28 - cint))),
+ STDDEV_POP(cint)
+FROM alltypesparquet
+WHERE (((cstring2 LIKE '%ss%')
+ OR (cstring1 LIKE '10%'))
+ OR ((cint >= -75)
+ AND ((ctinyint = csmallint)
+ AND (cdouble >= -3728))))
+GROUP BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+ORDER BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+PREHOOK: type: QUERY
+POSTHOOK: query: EXPLAIN VECTORIZATION DETAIL
+SELECT cfloat,
+ cboolean1,
+ cdouble,
+ cstring1,
+ ctinyint,
+ cint,
+ ctimestamp1,
+ STDDEV_SAMP(cfloat),
+ (-26.28 - cint),
+ MIN(cdouble),
+ (cdouble * 79.553),
+ (33 % cfloat),
+ STDDEV_SAMP(ctinyint),
+ VAR_POP(ctinyint),
+ (-23 % cdouble),
+ (-(ctinyint)),
+ VAR_SAMP(cint),
+ (cint - cfloat),
+ (-23 % ctinyint),
+ (-((-26.28 - cint))),
+ STDDEV_POP(cint)
+FROM alltypesparquet
+WHERE (((cstring2 LIKE '%ss%')
+ OR (cstring1 LIKE '10%'))
+ OR ((cint >= -75)
+ AND ((ctinyint = csmallint)
+ AND (cdouble >= -3728))))
+GROUP BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+ORDER BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+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: FilterStringColLikeStringScalar(col 7:string, pattern %ss%), FilterStringColLikeStringScalar(col 6:string, pattern 10%), FilterExprAndExpr(children: FilterLongColGreaterEqualLongScalar(col 2:int, val -75), FilterLongColEqualLongColumn(col 0:smallint, col 1:smallint)(children: col 0:tinyint), FilterDoubleColGreaterEqualDoubleScalar(col 5:double, val -3728.0)))
+ predicate: (((cint >= -75) and (UDFToShort(ctinyint) = csmallint) and (cdouble >= -3728.0)) or (cstring1 like '10%') or (cstring2 like '%ss%')) (type: boolean)
+ Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: ctinyint (type: tinyint), cint (type: int), cfloat (type: float), cdouble (type: double), cstring1 (type: string), ctimestamp1 (type: timestamp), cboolean1 (type: boolean)
+ outputColumnNames: ctinyint, cint, cfloat, cdouble, cstring1, ctimestamp1, cboolean1
+ Select Vectorization:
+ className: VectorSelectOperator
+ native: true
+ projectedOutputColumnNums: [0, 2, 4, 5, 6, 8, 10]
+ Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: stddev_samp(cfloat), min(cdouble), stddev_samp(ctinyint), var_pop(ctinyint), var_samp(cint), stddev_pop(cint)
+ Group By Vectorization:
+ aggregators: VectorUDAFVarDouble(col 4:float) -> struct<count:bigint,sum:double,variance:double> aggregation: stddev_samp, VectorUDAFMinDouble(col 5:double) -> double, VectorUDAFVarLong(col 0:tinyint) -> struct<count:bigint,sum:double,variance:double> aggregation: stddev_samp, VectorUDAFVarLong(col 0:tinyint) -> struct<count:bigint,sum:double,variance:double> aggregation: var_pop, VectorUDAFVarLong(col 2:int) -> struct<count:bigint,sum:double,variance:double> aggregation: var_samp, VectorUDAFVarLong(col 2:int) -> struct<count:bigint,sum:double,variance:double> aggregation: stddev_pop
+ className: VectorGroupByOperator
+ groupByMode: HASH
+ keyExpressions: col 4:float, col 10:boolean, col 5:double, col 6:string, col 0:tinyint, col 2:int, col 8:timestamp
+ native: false
+ vectorProcessingMode: HASH
+ projectedOutputColumnNums: [0, 1, 2, 3, 4, 5]
+ keys: cfloat (type: float), cboolean1 (type: boolean), cdouble (type: double), cstring1 (type: string), ctinyint (type: tinyint), cint (type: int), ctimestamp1 (type: timestamp)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
+ Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: float), _col1 (type: boolean), _col2 (type: double), _col3 (type: string), _col4 (type: tinyint), _col5 (type: int), _col6 (type: timestamp)
+ sort order: +++++++
+ Map-reduce partition columns: _col0 (type: float), _col1 (type: boolean), _col2 (type: double), _col3 (type: string), _col4 (type: tinyint), _col5 (type: int), _col6 (type: timestamp)
+ Reduce Sink Vectorization:
+ className: VectorReduceSinkMultiKeyOperator
+ keyColumnNums: [0, 1, 2, 3, 4, 5, 6]
+ 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: [7, 8, 9, 10, 11, 12]
+ Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col7 (type: struct<count:bigint,sum:double,variance:double>), _col8 (type: double), _col9 (type: struct<count:bigint,sum:double,variance:double>), _col10 (type: struct<count:bigint,sum:double,variance:double>), _col11 (type: struct<count:bigint,sum:double,variance:double>), _col12 (type: struct<count:bigint,sum:double,variance:double>)
+ 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, 1, 2, 4, 5, 6, 7, 8, 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: []
+ Reducer 2
+ Reduce Vectorization:
+ enabled: false
+ enableConditionsMet: hive.execution.engine spark IN [tez, spark] IS true
+ enableConditionsNotMet: hive.vectorized.execution.reduce.enabled IS false
+ Reduce Operator Tree:
+ Group By Operator
+ aggregations: stddev_samp(VALUE._col0), min(VALUE._col1), stddev_samp(VALUE._col2), var_pop(VALUE._col3), var_samp(VALUE._col4), stddev_pop(VALUE._col5)
+ keys: KEY._col0 (type: float), KEY._col1 (type: boolean), KEY._col2 (type: double), KEY._col3 (type: string), KEY._col4 (type: tinyint), KEY._col5 (type: int), KEY._col6 (type: timestamp)
+ mode: mergepartial
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12
+ Statistics: Num rows: 6144 Data size: 73728 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col0 (type: float), _col1 (type: boolean), _col2 (type: double), _col3 (type: string), _col4 (type: tinyint), _col5 (type: int), _col6 (type: timestamp), _col7 (type: double), (-26.28 - CAST( _col5 AS decimal(10,0))) (type: decimal(13,2)), _col8 (type: double), (_col2 * 79.553) (type: double), (33.0 % _col0) (type: float), _col9 (type: double), _col10 (type: double), (-23.0 % _col2) (type: double), (- _col4) (type: tinyint), _col11 (type: double), (UDFToFloat(_col5) - _col0) (type: float), (-23 % UDFToInteger(_col4)) (type: int), (- (-26.28 - CAST( _col5 AS decimal(10,0)))) (type: decimal(13,2)), _col12 (type: double)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20
+ Statistics: Num rows: 6144 Data size: 73728 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: float), _col1 (type: boolean), _col2 (type: double), _col3 (type: string), _col4 (type: tinyint), _col5 (type: int), _col6 (type: timestamp)
+ sort order: +++++++
+ Statistics: Num rows: 6144 Data size: 73728 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col7 (type: double), _col8 (type: decimal(13,2)), _col9 (type: double), _col10 (type: double), _col11 (type: float), _col12 (type: double), _col13 (type: double), _col14 (type: double), _col15 (type: tinyint), _col16 (type: double), _col17 (type: float), _col18 (type: int), _col19 (type: decimal(13,2)), _col20 (type: double)
+ Reducer 3
+ Reduce Vectorization:
+ enabled: false
+ enableConditionsMet: hive.execution.engine spark IN [tez, spark] IS true
+ enableConditionsNotMet: hive.vectorized.execution.reduce.enabled IS false
+ Reduce Operator Tree:
+ Select Operator
+ expressions: KEY.reducesinkkey0 (type: float), KEY.reducesinkkey1 (type: boolean), KEY.reducesinkkey2 (type: double), KEY.reducesinkkey3 (type: string), KEY.reducesinkkey4 (type: tinyint), KEY.reducesinkkey5 (type: int), KEY.reducesinkkey6 (type: timestamp), VALUE._col0 (type: double), VALUE._col1 (type: decimal(13,2)), VALUE._col2 (type: double), VALUE._col3 (type: double), VALUE._col4 (type: float), VALUE._col5 (type: double), VALUE._col6 (type: double), VALUE._col7 (type: double), VALUE._col8 (type: tinyint), VALUE._col9 (type: double), VALUE._col10 (type: float), VALUE._col11 (type: int), VALUE._col12 (type: decimal(13,2)), VALUE._col13 (type: double)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20
+ Statistics: Num rows: 6144 Data size: 73728 Basic stats: COMPLETE Column stats: NONE
+ File Output Operator
+ compressed: false
+ Statistics: Num rows: 6144 Data size: 73728 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: -1
+ Processor Tree:
+ ListSink
+
+PREHOOK: query: SELECT cfloat,
+ cboolean1,
+ cdouble,
+ cstring1,
+ ctinyint,
+ cint,
+ ctimestamp1,
+ STDDEV_SAMP(cfloat),
+ (-26.28 - cint),
+ MIN(cdouble),
+ (cdouble * 79.553),
+ (33 % cfloat),
+ STDDEV_SAMP(ctinyint),
+ VAR_POP(ctinyint),
+ (-23 % cdouble),
+ (-(ctinyint)),
+ VAR_SAMP(cint),
+ (cint - cfloat),
+ (-23 % ctinyint),
+ (-((-26.28 - cint))),
+ STDDEV_POP(cint)
+FROM alltypesparquet
+WHERE (((cstring2 LIKE '%ss%')
+ OR (cstring1 LIKE '10%'))
+ OR ((cint >= -75)
+ AND ((ctinyint = csmallint)
+ AND (cdouble >= -3728))))
+GROUP BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+ORDER BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+PREHOOK: type: QUERY
+PREHOOK: Input: default@alltypesparquet
+#### A masked pattern was here ####
+POSTHOOK: query: SELECT cfloat,
+ cboolean1,
+ cdouble,
+ cstring1,
+ ctinyint,
+ cint,
+ ctimestamp1,
+ STDDEV_SAMP(cfloat),
+ (-26.28 - cint),
+ MIN(cdouble),
+ (cdouble * 79.553),
+ (33 % cfloat),
+ STDDEV_SAMP(ctinyint),
+ VAR_POP(ctinyint),
+ (-23 % cdouble),
+ (-(ctinyint)),
+ VAR_SAMP(cint),
+ (cint - cfloat),
+ (-23 % ctinyint),
+ (-((-26.28 - cint))),
+ STDDEV_POP(cint)
+FROM alltypesparquet
+WHERE (((cstring2 LIKE '%ss%')
+ OR (cstring1 LIKE '10%'))
+ OR ((cint >= -75)
+ AND ((ctinyint = csmallint)
+ AND (cdouble >= -3728))))
+GROUP BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+ORDER BY cfloat, cboolean1, cdouble, cstring1, ctinyint, cint, ctimestamp1
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@alltypesparquet
+#### A masked pattern was here ####
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