Test Result : DatasetSuite

0 failures (±0)
158 tests (+21)
Took 38 sec.

All Tests

Test nameDurationStatus
Check KeyValueGroupedDataset toString: Named KV-pair24 msPassed
Check KeyValueGroupedDataset toString: Single data17 msPassed
Check KeyValueGroupedDataset toString: Unnamed KV-pair41 msPassed
Check KeyValueGroupedDataset toString: over length schema25 msPassed
Check RelationalGroupedDataset toString: Single data8 msPassed
Check RelationalGroupedDataset toString: over length schema33 msPassed
Dataset should support flat input object to be null34 msPassed
Dataset should throw RuntimeException if top-level product input object is null6 msPassed
Java encoder0.18 secPassed
Java encoder self join77 msPassed
Kryo encoder0.29 secPassed
Kryo encoder self join88 msPassed
Kryo encoder: check the schema mismatch when converting DataFrame to Dataset13 msPassed
Map0.48 secPassed
REGEX column specification0.71 secPassed
SPARK-11436: we should rebind right encoder when join 2 datasets0.1 secPassed
SPARK-11894: Incorrect results are returned when using null0.16 secPassed
SPARK-12404: Datatype Helper Serializability75 msPassed
SPARK-12478: top level null field0.2 secPassed
SPARK-13440: Resolving option fields83 msPassed
SPARK-13540 Dataset of nested class defined in Scala object57 msPassed
SPARK-14000: case class with tuple type field72 msPassed
SPARK-14696: implicit encoders for boxed types0.19 secPassed
SPARK-14838: estimating sizeInBytes in operators with ObjectProducer shouldn't fail0.38 secPassed
SPARK-15097: implicits on dataset's spark can be imported85 msPassed
SPARK-15112: EmbedDeserializerInFilter should not optimize plan fragment that changes schema0.14 secPassed
SPARK-15381: physical object operator should define `reference` correctly0.19 secPassed
SPARK-15441: Dataset outer join0.14 secPassed
SPARK-15632: typed filter should preserve the underlying logical schema6 msPassed
SPARK-16853: select, case class and tuple0.24 secPassed
SPARK-16995: flat mapping on Dataset containing a column created with lit/expr0.51 secPassed
SPARK-17460: the sizeInBytes in Statistics shouldn't overflow to a negative number0.19 secPassed
SPARK-18125: Spark generated code causes CompileException0.58 secPassed
SPARK-18189: Fix serialization issue in KeyValueGroupedDataset0.3 secPassed
SPARK-18284: Serializer should have correct nullable value0.25 secPassed
SPARK-18746: add implicit encoder for BigDecimal, date, timestamp0.49 secPassed
SPARK-19896: cannot have circular references in case class24 msPassed
SPARK-20125: option of map0.1 secPassed
SPARK-20399: do not unescaped regex pattern when ESCAPED_STRING_LITERALS is enabled0.43 secPassed
SPARK-21538: Attribute resolution inconsistency in Dataset API0.59 secPassed
SPARK-21567: Dataset should work with type alias0.53 secPassed
SPARK-22442: Generate correct field names for special characters0.33 secPassed
SPARK-22472: add null check for top-level primitive values0.51 secPassed
SPARK-23025: Add support for null type in scala reflection57 msPassed
SPARK-23614: Union produces incorrect results when caching is used0.84 secPassed
SPARK-23627: provide isEmpty in DataSet42 msPassed
SPARK-23835: null primitive data type should throw NullPointerException49 msPassed
SPARK-24548: Dataset with tuple encoders should have correct schema0.15 secPassed
SPARK-24569: Option of primitive types are mistakenly mapped to struct type0.24 secPassed
SPARK-24571: filtering of string values by char literal0.21 secPassed
SPARK-24762: Enable top-level Option of Product encoders0.21 secPassed
SPARK-24762: Resolving Option[Product] field94 msPassed
SPARK-24762: joinWith on Option[Product]0.19 secPassed
SPARK-24762: select Option[Product] field0.19 secPassed
SPARK-24762: typed agg on Option[Product] type0.62 secPassed
SPARK-25108 Fix the show method to display the full width character alignment problem0.12 secPassed
SPARK-25153: Improve error messages for columns with dots/periods70 msPassed
SPARK-25942: typed aggregation on primitive type0.32 secPassed
SPARK-25942: typed aggregation on product type0.33 secPassed
SPARK-26085: fix key attribute name for atomic type for typed aggregation14 msPassed
SPARK-26233: serializer should enforce decimal precision and scale0.43 secPassed
SPARK-26366: return nulls which are not filtered in except0.33 secPassed
SPARK-26690: checkpoints should be executed with an execution id59 msPassed
SPARK-31854: Invoke in MapElementsExec should not propagate null0.24 secPassed
SPARK-8288: class with only a companion object constructor0.13 secPassed
active should be the same instance after dataset operations4 msPassed
as0.37 secPassed
as case class - reordered fields by name70 msPassed
as case class - tail57 msPassed
as case class - take58 msPassed
as case class / collect61 msPassed
as map of case class - reorder fields by name84 msPassed
as seq of case class - reorder fields by name74 msPassed
as tuple75 msPassed
change encoder with compatible schema0.47 secPassed
checkAnswer should compare map correctly0.16 secPassed
checkpoint() - basic (eager = false, reliable = false)0.23 secPassed
checkpoint() - basic (eager = false, reliable = true)0.37 secPassed
checkpoint() - basic (eager = true, reliable = false)0.34 secPassed
checkpoint() - basic (eager = true, reliable = true)0.53 secPassed
checkpoint() - should preserve partitioning information (eager = false, reliable = false)0.73 secPassed
checkpoint() - should preserve partitioning information (eager = false, reliable = true)0.93 secPassed
checkpoint() - should preserve partitioning information (eager = true, reliable = false)0.69 secPassed
checkpoint() - should preserve partitioning information (eager = true, reliable = true)0.97 secPassed
coalesce, repartition0.25 secPassed
cogroup0.27 secPassed
cogroup with complex data0.31 secPassed
cogroup's left and right side has field with same name0.33 secPassed
collect, first, and take should use encoders for serialization0.13 secPassed
createTempView39 msPassed
dropDuplicates0.78 secPassed
dropDuplicates: columns with same column name0.33 secPassed
emptyDataset77 msPassed
filter72 msPassed
filter and then select83 msPassed
foreach59 msPassed
foreachPartition53 msPassed
give nice error message when the real number of fields doesn't match encoder schema18 msPassed
groupBy function, flatMap0.17 secPassed
groupBy function, keys0.53 secPassed
groupBy function, map0.21 secPassed
groupBy function, mapValues, flatMap0.43 secPassed
groupBy function, reduce0.15 secPassed
groupBy single field class, count0.18 secPassed
grouping key and grouped value has field with same name0.25 secPassed
identity map for primitive arrays0.39 secPassed
implicit encoder for LocalDate and Instant0.23 secPassed
isStreaming returns false for static Dataset21 msPassed
isStreaming returns true after static and streaming Dataset join13 msPassed
isStreaming returns true for streaming Dataset3 msPassed
joinWith class with primitive, toDF0.2 secPassed
joinWith join types16 msPassed
joinWith tuple with primitive, expression0.12 secPassed
joinWith, flat schema80 msPassed
map0.11 secPassed
map and group by with class data0.29 secPassed
map may generate wrong java code for wide table2.8 secPassed
map with type change with less attributes0.17 secPassed
map with type change with the exact matched number of attributes0.19 secPassed
mapped dataset should resolve duplicated attributes for self join0.69 secPassed
mayTruncate for bytes4 msPassed
multi-level joinWith0.16 secPassed
range0.35 secPassed
rdd with generic case class0.19 secPassed
reduce38 msPassed
row nullability mismatch61 msPassed
runtime null check for RowEncoder71 msPassed
runtime nullability check0.17 secPassed
sample fraction should be on interval [0, 1] without replacement4 msPassed
sample fraction should not be negative with replacement55 msPassed
sample with replacement83 msPassed
sample with seed results shouldn't depend on downstream usage0.25 secPassed
sample without replacement68 msPassed
select97 msPassed
select 235 msPassed
select 2, primitive and class75 msPassed
select 2, primitive and class, fields reordered88 msPassed
select 2, primitive and tuple80 msPassed
self join0.1 secPassed
show() should show contents of the underlying logical plan0.18 secPassed
show() should show inner nested products as rows81 msPassed
support inner class in Dataset0.17 secPassed
tail should not accept minus value5 msPassed
tail with different numbers0.46 secPassed
toDS64 msPassed
toDS should compare map with byte array keys correctly0.35 secPassed
toDS with RDD0.24 secPassed
toString23 msPassed
tuple should handle null object correctly61 msPassed
typed aggregation: expr0.27 secPassed
typed aggregation: expr, expr0.28 secPassed
typed aggregation: expr, expr, expr0.82 secPassed
typed aggregation: expr, expr, expr, expr0.32 secPassed
typed aggregation: expr, expr, expr, expr, expr0.6 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr0.54 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr, expr0.8 secPassed
typed aggregation: expr, expr, expr, expr, expr, expr, expr, expr0.57 secPassed
verify mismatching field names fail with a good error31 msPassed