Spark / Scala-当一个数据为空时，比较数据框中的两列

Question

I'm using Spark (Scala) to QA data movement - moving tables from one relational database to another. The QA process involves executing a full outer join between the source table, and the target table.

The source table and target tables are joined in a data frame on the key(s):

val joinColumns = for (i <- 0 to (sourceJoinFields.length - 1)) yield sourceDF.col(sourceJoinFields(i)) <=> targetDF.col(targetJoinFields(i))
val joinedDF = sourceDF.join(targetDF, joinColumns.reduce((_&&_)), "fullouter")

I'm using the following logic to find mismatches:

val mismatchColumns = for (i <- 0 to (sourceDF.columns.length-1)) yield (joinedDF.col(joinedDF.columns(i)) =!= joinedDF.col(joinedDF.columns(i+(sourceDF.columns.length))))
val mismatchedDF = joinedDF.filter(mismatchColumns.reduce((_||_)))

However if there is a key missing from one side of the full outer join:

+--------------+--------------+--------------+--------------+
|source_key    |source_field  |target_key    |target_field  |
+--------------+--------------+--------------+--------------+
|null          |null          |XXX           |XXX           |

will not be in the mismatchedDF data set.

So my question: is the =!= operator the opposite of the <=> operator? It does not appear to be, so is there an operator that will return FALSE for this case? I can't find much documentation on either operator.

Answer 1

The opposite of IS NOT DISTINCT FROM ( <=> ) is IS DISTINCT FROM ( not(... <=> ...) ).

import org.apache.spark.sql.not

val df = Seq(("foo", null), ("foo", "bar"), ("foo", "foo")).toDF("x", "y")
df.select(not($"x" <=> $"y"))

or

df.select(!($"x" <=> $"y"))

or

df.selectExpr("x IS DISTINCT FROM y")

all giving the same result:

+---------------+
|(NOT (x <=> y))|
+---------------+
|           true|
|           true|
|          false|
+---------------+

Of course if you have a disjunction of negations:

(NOT P) OR (NOT Q)

you can always use De Morgan's laws to rewrite it as a negation of concjunctions

NOT(P AND Q)

therefore:

not(joinColumns.foldLeft(lit(true))(_ and _))

should work just fine.