DB Tsai created SPARK-20270:
-------------------------------
Summary: na.fill will change the values in long or integer when
the default value is in double
Key: SPARK-20270
URL: https://issues.apache.org/jira/browse/SPARK-20270
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0, 2.0.2, 2.0.1, 2.0.0
Reporter: DB Tsai
Assignee: DB Tsai
Priority: Critical
This bug was partially addressed in SPARK-18555, but the root cause isn't
completely solved. This bug is pretty critical since it changes the member id
in Long in our application if the member id can not be represented by Double
losslessly when the member id is very big.
Here is an example how this happens, with
{code}
Seq[(java.lang.Long, java.lang.Double)]((null, 3.14),
(9123146099426677101L, null),
(9123146560113991650L, 1.6), (null, null)).toDF("a", "b").na.fill(0.2),
{code}
the logical plan will be
{code}
== Analyzed Logical Plan ==
a: bigint, b: double
Project [cast(coalesce(cast(a#232L as double), cast(0.2 as double)) as bigint)
AS a#240L, cast(coalesce(nanvl(b#233, cast(null as double)), 0.2) as double) AS
b#241]
+- Project [_1#229L AS a#232L, _2#230 AS b#233]
+- LocalRelation [_1#229L, _2#230]
{code}.
Note that even the value is not null, Spark will cast the Long into Double
first. Then if it's not null, Spark will cast it back to Long which results in
losing precision.
The behavior should be that the original value should not be changed if it's
not null, but Spark will change the value which is wrong.
With the PR, the logical plan will be
{code}
== Analyzed Logical Plan ==
a: bigint, b: double
Project [coalesce(a#232L, cast(0.2 as bigint)) AS a#240L, coalesce(nanvl(b#233,
cast(null as double)), cast(0.2 as double)) AS b#241]
+- Project [_1#229L AS a#232L, _2#230 AS b#233]
+- LocalRelation [_1#229L, _2#230]
{code}
which behaves correctly without changing the original Long values.
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