Test Result : DatasetSuite

0 failures (±0)
158 tests (+1)
Took 51 sec.

All Tests

Test nameDurationStatus
Check KeyValueGroupedDataset toString: Named KV-pair18 msPassed
Check KeyValueGroupedDataset toString: Single data17 msPassed
Check KeyValueGroupedDataset toString: Unnamed KV-pair36 msPassed
Check KeyValueGroupedDataset toString: over length schema21 msPassed
Check RelationalGroupedDataset toString: Single data6 msPassed
Check RelationalGroupedDataset toString: over length schema29 msPassed
Dataset should support flat input object to be null30 msPassed
Dataset should throw RuntimeException if top-level product input object is null5 msPassed
Java encoder0.29 secPassed
Java encoder self join84 msPassed
Kryo encoder0.37 secPassed
Kryo encoder self join0.14 secPassed
Kryo encoder: check the schema mismatch when converting DataFrame to Dataset13 msPassed
Map0.4 secPassed
REGEX column specification0.91 secPassed
SPARK-11436: we should rebind right encoder when join 2 datasets0.13 secPassed
SPARK-11894: Incorrect results are returned when using null0.19 secPassed
SPARK-12404: Datatype Helper Serializability79 msPassed
SPARK-12478: top level null field0.24 secPassed
SPARK-13440: Resolving option fields0.13 secPassed
SPARK-13540 Dataset of nested class defined in Scala object0.26 secPassed
SPARK-14000: case class with tuple type field0.1 secPassed
SPARK-14696: implicit encoders for boxed types72 msPassed
SPARK-14838: estimating sizeInBytes in operators with ObjectProducer shouldn't fail0.38 secPassed
SPARK-15097: implicits on dataset's spark can be imported0.1 secPassed
SPARK-15112: EmbedDeserializerInFilter should not optimize plan fragment that changes schema0.11 secPassed
SPARK-15381: physical object operator should define `reference` correctly0.15 secPassed
SPARK-15441: Dataset outer join0.12 secPassed
SPARK-15632: typed filter should preserve the underlying logical schema6 msPassed
SPARK-16853: select, case class and tuple0.25 secPassed
SPARK-16995: flat mapping on Dataset containing a column created with lit/expr0.52 secPassed
SPARK-17460: the sizeInBytes in Statistics shouldn't overflow to a negative number0.15 secPassed
SPARK-18125: Spark generated code causes CompileException0.65 secPassed
SPARK-18189: Fix serialization issue in KeyValueGroupedDataset0.61 secPassed
SPARK-18284: Serializer should have correct nullable value0.24 secPassed
SPARK-18746: add implicit encoder for BigDecimal, date, timestamp0.36 secPassed
SPARK-19896: cannot have circular references in case class0.15 secPassed
SPARK-20125: option of map87 msPassed
SPARK-20399: do not unescaped regex pattern when ESCAPED_STRING_LITERALS is enabled0.25 secPassed
SPARK-21538: Attribute resolution inconsistency in Dataset API0.8 secPassed
SPARK-21567: Dataset should work with type alias0.81 secPassed
SPARK-22442: Generate correct field names for special characters0.6 secPassed
SPARK-22472: add null check for top-level primitive values0.79 secPassed
SPARK-23025: Add support for null type in scala reflection51 msPassed
SPARK-23614: Union produces incorrect results when caching is used0.89 secPassed
SPARK-23627: provide isEmpty in DataSet0.14 secPassed
SPARK-23835: null primitive data type should throw NullPointerException48 msPassed
SPARK-24548: Dataset with tuple encoders should have correct schema0.17 secPassed
SPARK-24569: Option of primitive types are mistakenly mapped to struct type0.17 secPassed
SPARK-24571: filtering of string values by char literal0.24 secPassed
SPARK-24762: Enable top-level Option of Product encoders0.11 secPassed
SPARK-24762: Resolving Option[Product] field82 msPassed
SPARK-24762: joinWith on Option[Product]0.16 secPassed
SPARK-24762: select Option[Product] field0.32 secPassed
SPARK-24762: typed agg on Option[Product] type0.47 secPassed
SPARK-25108 Fix the show method to display the full width character alignment problem94 msPassed
SPARK-25153: Improve error messages for columns with dots/periods78 msPassed
SPARK-25942: typed aggregation on primitive type1.3 secPassed
SPARK-25942: typed aggregation on product type0.59 secPassed
SPARK-26085: fix key attribute name for atomic type for typed aggregation48 msPassed
SPARK-26233: serializer should enforce decimal precision and scale0.55 secPassed
SPARK-26366: return nulls which are not filtered in except0.41 secPassed
SPARK-26690: checkpoints should be executed with an execution id77 msPassed
SPARK-30791: sameSemantics and semanticHash work47 msPassed
SPARK-8288: class with only a companion object constructor0.1 secPassed
active should be the same instance after dataset operations6 msPassed
as0.51 secPassed
as case class - reordered fields by name74 msPassed
as case class - tail86 msPassed
as case class - take66 msPassed
as case class / collect97 msPassed
as map of case class - reorder fields by name0.11 secPassed
as seq of case class - reorder fields by name90 msPassed
as tuple0.15 secPassed
change encoder with compatible schema0.34 secPassed
checkAnswer should compare map correctly0.14 secPassed
checkpoint() - basic (eager = false, reliable = false)0.34 secPassed
checkpoint() - basic (eager = false, reliable = true)3.6 secPassed
checkpoint() - basic (eager = true, reliable = false)0.36 secPassed
checkpoint() - basic (eager = true, reliable = true)1.4 secPassed
checkpoint() - should preserve partitioning information (eager = false, reliable = false)0.98 secPassed
checkpoint() - should preserve partitioning information (eager = false, reliable = true)0.89 secPassed
checkpoint() - should preserve partitioning information (eager = true, reliable = false)1.8 secPassed
checkpoint() - should preserve partitioning information (eager = true, reliable = true)2 secPassed
coalesce, repartition0.37 secPassed
cogroup0.4 secPassed
cogroup with complex data0.37 secPassed
cogroup's left and right side has field with same name0.33 secPassed
collect, first, and take should use encoders for serialization0.2 secPassed
createTempView57 msPassed
dropDuplicates0.8 secPassed
dropDuplicates: columns with same column name0.38 secPassed
emptyDataset79 msPassed
filter80 msPassed
filter and then select0.1 secPassed
foreach59 msPassed
foreachPartition42 msPassed
give nice error message when the real number of fields doesn't match encoder schema18 msPassed
groupBy function, flatMap0.19 secPassed
groupBy function, keys0.24 secPassed
groupBy function, map0.25 secPassed
groupBy function, mapValues, flatMap0.66 secPassed
groupBy function, reduce0.32 secPassed
groupBy single field class, count0.3 secPassed
grouping key and grouped value has field with same name0.26 secPassed
identity map for primitive arrays0.44 secPassed
implicit encoder for LocalDate and Instant0.37 secPassed
isStreaming returns false for static Dataset15 msPassed
isStreaming returns true after static and streaming Dataset join12 msPassed
isStreaming returns true for streaming Dataset2 msPassed
joinWith class with primitive, toDF0.18 secPassed
joinWith join types19 msPassed
joinWith tuple with primitive, expression0.1 secPassed
joinWith, flat schema0.1 secPassed
map0.11 secPassed
map and group by with class data0.36 secPassed
map may generate wrong java code for wide table2.9 secPassed
map with type change with less attributes0.16 secPassed
map with type change with the exact matched number of attributes0.22 secPassed
mapped dataset should resolve duplicated attributes for self join1 secPassed
mayTruncate for bytes5 msPassed
multi-level joinWith0.31 secPassed
range0.42 secPassed
rdd with generic case class0.19 secPassed
reduce40 msPassed
row nullability mismatch0.14 secPassed
runtime null check for RowEncoder67 msPassed
runtime nullability check0.16 secPassed
sample fraction should be on interval [0, 1] without replacement7 msPassed
sample fraction should not be negative with replacement61 msPassed
sample with replacement67 msPassed
sample with seed results shouldn't depend on downstream usage0.33 secPassed
sample without replacement55 msPassed
select73 msPassed
select 239 msPassed
select 2, primitive and class0.11 secPassed
select 2, primitive and class, fields reordered69 msPassed
select 2, primitive and tuple84 msPassed
self join0.11 secPassed
show() should show contents of the underlying logical plan0.11 secPassed
show() should show inner nested products as rows73 msPassed
support inner class in Dataset0.13 secPassed
tail should not accept minus value6 msPassed
tail with different numbers0.47 secPassed
toDS0.12 secPassed
toDS should compare map with byte array keys correctly0.51 secPassed
toDS with RDD0.53 secPassed
toString17 msPassed
tuple should handle null object correctly46 msPassed
typed aggregation: expr0.38 secPassed
typed aggregation: expr, expr0.32 secPassed
typed aggregation: expr, expr, expr0.28 secPassed
typed aggregation: expr, expr, expr, expr0.35 secPassed
typed aggregation: expr, expr, expr, expr, expr0.7 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr0.66 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr, expr1.8 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr, expr, expr0.89 secPassed
verify mismatching field names fail with a good error62 msPassed