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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-25256) Plan mismatch errors in Hive tests in 2.12
Date Mon, 27 Aug 2018 20:55:00 GMT
Sean Owen created SPARK-25256:
---------------------------------

             Summary: Plan mismatch errors in Hive tests in 2.12
                 Key: SPARK-25256
                 URL: https://issues.apache.org/jira/browse/SPARK-25256
             Project: Spark
          Issue Type: Sub-task
          Components: SQL
    Affects Versions: 2.4.0
            Reporter: Sean Owen


In Hive tests, in the Scala 2.12 build, still seeing a few failures that seem to show mismatching
schema inference. Not clear whether it's the same as SPARK-25044. Examples:
{code:java}
- SPARK-5775 read array from partitioned_parquet_with_key_and_complextypes *** FAILED ***
Results do not match for query:
Timezone: sun.util.calendar.ZoneInfo[id="America/Los_Angeles",offset=-28800000,dstSavings=3600000,useDaylight=true,transitions=185,lastRule=java.util.SimpleTimeZone[id=America/Los_Angeles,offset=-28800000,dstSavings=3600000,useDaylight=true,startYear=0,startMode=3,startMonth=2,startDay=8,startDayOfWeek=1,startTime=7200000,startTimeMode=0,endMode=3,endMonth=10,endDay=1,endDayOfWeek=1,endTime=7200000,endTimeMode=0]]
Timezone Env: 

== Parsed Logical Plan ==
'Project ['arrayField, 'p]
+- 'Filter ('p = 1)
+- 'UnresolvedRelation `partitioned_parquet_with_key_and_complextypes`

== Analyzed Logical Plan ==
arrayField: array<int>, p: int
Project [arrayField#82569, p#82570]
+- Filter (p#82570 = 1)
+- SubqueryAlias `default`.`partitioned_parquet_with_key_and_complextypes`
+- Relation[intField#82566,stringField#82567,structField#82568,arrayField#82569,p#82570] parquet

== Optimized Logical Plan ==
Project [arrayField#82569, p#82570]
+- Filter (isnotnull(p#82570) && (p#82570 = 1))
+- Relation[intField#82566,stringField#82567,structField#82568,arrayField#82569,p#82570] parquet

== Physical Plan ==
*(1) Project [arrayField#82569, p#82570]
+- *(1) FileScan parquet default.partitioned_parquet_with_key_and_complextypes[arrayField#82569,p#82570]
Batched: false, Format: Parquet, Location: PrunedInMemoryFileIndex[file:/home/srowen/spark-2.12/sql/hive/target/tmp/spark-d8d87d74-33e7-4f22...,
PartitionCount: 1, PartitionFilters: [isnotnull(p#82570), (p#82570 = 1)], PushedFilters: [],
ReadSchema: struct<arrayField:array<int>>
== Results ==

== Results ==
!== Correct Answer - 10 == == Spark Answer - 10 ==
!struct<> struct<arrayField:array<int>,p:int>
![Range 1 to 1,1] [WrappedArray(1),1]
![Range 1 to 10,1] [WrappedArray(1, 2),1]
![Range 1 to 2,1] [WrappedArray(1, 2, 3),1]
![Range 1 to 3,1] [WrappedArray(1, 2, 3, 4),1]
![Range 1 to 4,1] [WrappedArray(1, 2, 3, 4, 5),1]
![Range 1 to 5,1] [WrappedArray(1, 2, 3, 4, 5, 6),1]
![Range 1 to 6,1] [WrappedArray(1, 2, 3, 4, 5, 6, 7),1]
![Range 1 to 7,1] [WrappedArray(1, 2, 3, 4, 5, 6, 7, 8),1]
![Range 1 to 8,1] [WrappedArray(1, 2, 3, 4, 5, 6, 7, 8, 9),1]
![Range 1 to 9,1] [WrappedArray(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),1] (QueryTest.scala:163){code}
{code:java}
- SPARK-2693 udaf aggregates test *** FAILED ***
Results do not match for query:
Timezone: sun.util.calendar.ZoneInfo[id="America/Los_Angeles",offset=-28800000,dstSavings=3600000,useDaylight=true,transitions=185,lastRule=java.util.SimpleTimeZone[id=America/Los_Angeles,offset=-28800000,dstSavings=3600000,useDaylight=true,startYear=0,startMode=3,startMonth=2,startDay=8,startDayOfWeek=1,startTime=7200000,startTimeMode=0,endMode=3,endMonth=10,endDay=1,endDayOfWeek=1,endTime=7200000,endTimeMode=0]]
Timezone Env: 

== Parsed Logical Plan ==
'GlobalLimit 1
+- 'LocalLimit 1
+- 'Project [unresolvedalias('percentile('key, 'array(1, 1)), None)]
+- 'UnresolvedRelation `src`

== Analyzed Logical Plan ==
percentile(key, array(1, 1), 1): array<double>
GlobalLimit 1
+- LocalLimit 1
+- Aggregate [percentile(key#205098, cast(array(1, 1) as array<double>), 1, 0, 0) AS
percentile(key, array(1, 1), 1)#205101]
+- SubqueryAlias `default`.`src`
+- HiveTableRelation `default`.`src`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe,
[key#205098, value#205099]

== Optimized Logical Plan ==
GlobalLimit 1
+- LocalLimit 1
+- Aggregate [percentile(key#205098, [1.0,1.0], 1, 0, 0) AS percentile(key, array(1, 1), 1)#205101]
+- Project [key#205098]
+- HiveTableRelation `default`.`src`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe,
[key#205098, value#205099]

== Physical Plan ==
CollectLimit 1
+- ObjectHashAggregate(keys=[], functions=[percentile(key#205098, [1.0,1.0], 1, 0, 0)], output=[percentile(key,
array(1, 1), 1)#205101])
+- Exchange SinglePartition
+- ObjectHashAggregate(keys=[], functions=[partial_percentile(key#205098, [1.0,1.0], 1, 0,
0)], output=[buf#205104])
+- Scan hive default.src [key#205098], HiveTableRelation `default`.`src`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe,
[key#205098, value#205099]
== Results ==

== Results ==
!== Correct Answer - 1 == == Spark Answer - 1 ==
!struct<array(max(key), max(key)):array<int>> struct<percentile(key, array(1,
1), 1):array<double>>
![WrappedArray(498, 498)] [WrappedArray(498.0, 498.0)] (QueryTest.scala:163){code}



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