Test Result : DataFrameAggregateSuite

0 failures (±0)
65 tests (±0)
Took 29 sec.

All Tests

Test nameDurationStatus
SPARK-13860: zero moments LEGACY_STATISTICAL_AGGREGATE off0.36 secPassed
SPARK-14664: Decimal sum/avg over window should work.0.28 secPassed
SPARK-17124 agg should be ordering preserving0.1 secPassed
SPARK-17237 remove backticks in a pivot result schema0.5 secPassed
SPARK-17616: distinct aggregate combined with a non-partial aggregate0.28 secPassed
SPARK-17641: collect functions should not collect null values0.26 secPassed
SPARK-18004 limit + aggregates0.19 secPassed
SPARK-18952: regexes fail codegen when used as keys due to bad forward-slash escapes0.16 secPassed
SPARK-19471: AggregationIterator does not initialize the generated result projection before using it2.4 secPassed
SPARK-21580 ints in aggregation expressions are taken as group-by ordinal.0.56 secPassed
SPARK-21896: Window functions inside aggregate functions0.5 secPassed
SPARK-21980: References in grouping functions should be indexed with semanticEquals0.14 secPassed
SPARK-22223: ObjectHashAggregate should not introduce unnecessary shuffle36 msPassed
SPARK-22951: dropDuplicates on empty dataFrames should produce correct aggregate (whole-stage-codegen off)0.4 secPassed
SPARK-22951: dropDuplicates on empty dataFrames should produce correct aggregate (whole-stage-codegen on)0.36 secPassed
SPARK-24788: RelationalGroupedDataset.toString with unresolved exprs should not fail2 msPassed
SPARK-26021: NaN and -0.0 in grouping expressions1.4 secPassed
SPARK-27581: DataFrame count_distinct("*") shouldn't fail with AnalysisException0.53 secPassed
SPARK-31500: collect_set() of BinaryType returns duplicate elements0.25 secPassed
SPARK-31620: agg with subquery (whole-stage-codegen = false)1.5 secPassed
SPARK-31620: agg with subquery (whole-stage-codegen = true)1.5 secPassed
SPARK-32038: NormalizeFloatingNumbers should work on distinct aggregate0.46 secPassed
SPARK-32136: NormalizeFloatingNumbers should work on null struct0.17 secPassed
SPARK-32344: Unevaluable's set to FIRST/LAST ignoreNullsExpr in distinct aggregates0.41 secPassed
SPARK-32906: struct field names should not change after normalizing floats20 msPassed
SPARK-33726: Aggregation on a table where a column name is reused0.27 secPassed
SPARK-34713: group by CreateStruct with ExtractValue0.64 secPassed
SPARK-34716: Support ANSI SQL intervals by the aggregate function `sum`0.62 secPassed
SPARK-34837: Support ANSI SQL intervals by the aggregate function `avg`0.94 secPassed
SPARK-35412: groupBy of year-month/day-time intervals should work0.32 secPassed
SPARK-36054: Support group by TimestampNTZ column0.26 secPassed
SPARK-36926: decimal average mistakenly overflow0.11 secPassed
SQL decimal test (used for catching certain decimal handling bugs in aggregates)0.21 secPassed
agg without groups0.11 secPassed
agg without groups and functions0.1 secPassed
aggregate function in GROUP BY14 msPassed
average1.1 secPassed
collect functions0.49 secPassed
collect functions should be able to cast to array type with no null values0.25 secPassed
collect functions structs0.28 secPassed
collect_set functions cannot have maps12 msPassed
count0.36 secPassed
count_if0.72 secPassed
cube0.32 secPassed
cube overlapping columns0.3 secPassed
groupBy1.5 secPassed
grouping and grouping_id0.31 secPassed
grouping/grouping_id inside window function0.27 secPassed
max_by0.99 secPassed
min_by0.9 secPassed
moments0.34 secPassed
multiple column distinct count0.65 secPassed
null average0.59 secPassed
null count0.89 secPassed
null moments0.28 secPassed
rollup0.19 secPassed
rollup overlapping columns0.33 secPassed
spark.sql.retainGroupColumns config0.23 secPassed
stddev0.23 secPassed
zero average0.24 secPassed
zero count0.2 secPassed
zero moments0.41 secPassed
zero stddev0.13 secPassed
zero sum73 msPassed
zero sum distinct0.13 secPassed