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Apacheにnull値を含めるSpark Join

Apacheにnull値を含めたいSpark join。Sparkはデフォルトでnullの行を含みません。

デフォルトのSpark動作。

_val numbersDf = Seq(
  ("123"),
  ("456"),
  (null),
  ("")
).toDF("numbers")

val lettersDf = Seq(
  ("123", "abc"),
  ("456", "def"),
  (null, "zzz"),
  ("", "hhh")
).toDF("numbers", "letters")

val joinedDf = numbersDf.join(lettersDf, Seq("numbers"))
_

joinedDf.show()の出力は次のとおりです。

_+-------+-------+
|numbers|letters|
+-------+-------+
|    123|    abc|
|    456|    def|
|       |    hhh|
+-------+-------+
_

これは私が望む出力です：

_+-------+-------+
|numbers|letters|
+-------+-------+
|    123|    abc|
|    456|    def|
|       |    hhh|
|   null|    zzz|
+-------+-------+
_
sqlscalaapache-sparkjoinapache-spark-sql
37
Powers

Sparkは特別なNULL安全な等価演算子を提供します：

numbersDf
  .join(lettersDf, numbersDf("numbers") <=> lettersDf("numbers"))
  .drop(lettersDf("numbers"))

+-------+-------+
|numbers|letters|
+-------+-------+
|    123|    abc|
|    456|    def|
|   null|    zzz|
|       |    hhh|
+-------+-------+

Spark 1.5以前で使用しないように注意してください。Spark 1.6より前は、デカルト積（ SPARK-11111 -高速なヌルセーフ結合）。

Spark 2.3.以降では、PySparkでColumn.eqNullSafeを使用できます。

numbers_df = sc.parallelize([
    ("123", ), ("456", ), (None, ), ("", )
]).toDF(["numbers"])

letters_df = sc.parallelize([
    ("123", "abc"), ("456", "def"), (None, "zzz"), ("", "hhh")
]).toDF(["numbers", "letters"])

numbers_df.join(letters_df, numbers_df.numbers.eqNullSafe(letters_df.numbers))

+-------+-------+-------+
|numbers|numbers|letters|
+-------+-------+-------+
|    456|    456|    def|
|   null|   null|    zzz|
|       |       |    hhh|
|    123|    123|    abc|
+-------+-------+-------+

および%<=>% in SparkR：

numbers_df <- createDataFrame(data.frame(numbers = c("123", "456", NA, "")))
letters_df <- createDataFrame(data.frame(
  numbers = c("123", "456", NA, ""),
  letters = c("abc", "def", "zzz", "hhh")
))

head(join(numbers_df, letters_df, numbers_df$numbers %<=>% letters_df$numbers))

  numbers numbers letters
1     456     456     def
2    <NA>    <NA>     zzz
3                     hhh
4     123     123     abc

[〜＃〜] sql [〜＃〜]（Spark 2.2.0 +）では、IS NOT DISTINCT FROMを使用できます。

SELECT * FROM numbers JOIN letters 
ON numbers.numbers IS NOT DISTINCT FROM letters.numbers

これはDataFrame AP​​Iでも使用できます。

numbersDf.alias("numbers")
  .join(lettersDf.alias("letters"))
  .where("numbers.numbers IS NOT DISTINCT FROM letters.numbers")
52
user6910411
val numbers2 = numbersDf.withColumnRenamed("numbers","num1") //rename columns so that we can disambiguate them in the join
val letters2 = lettersDf.withColumnRenamed("numbers","num2")
val joinedDf = numbers2.join(letters2, $"num1" === $"num2" || ($"num1".isNull &&  $"num2".isNull) ,"outer")
joinedDf.select("num1","letters").withColumnRenamed("num1","numbers").show  //rename the columns back to the original names
8
jasonS