Scala 如何通过比较一列与另一列rdd来过滤rdd'；s列不使用toDf

我有两个rdd，其中一个类似：

39250E6B-DB60-496E-8770-225EDB29A85F,0,ar,2018-10-09 00:00:00.0,2018-10-09 00:00:04.0,United Arab Emirates
2b98d4f4-0c55-4906-82ec-cfc7c5380652,40967837,en,2018-10-09 00:00:01.0,2018-10-09 00:00:31.0,Qatar
5bb587bc-54a0-4873-b0ba-2da38458ba1c,0,en,2018-10-09 00:00:03.0,2018-10-09 00:04:02.0,United Arab Emirates
466B96B5-DC12-4A35-8865-3A8702037A23,0,ar,2018-10-09 00:00:04.0,2018-10-09 00:00:06.0,Saudi Arabia
be51265e-ab8b-462c-928b-8dd7fab608de,0,ar,2018-10-09 00:00:06.0,2018-10-09 00:02:23.0,Jordan
9abb8b2c-beca-43b3-ab15-3df34bbbe69c,0,ar,2018-10-09 00:00:06.0,2018-10-09 00:00:06.0,United Arab Emirates
0841630C-D869-48E5-BCD3-533F4BD8764C,0,ar,2018-10-09 00:00:09.0,2018-10-09 00:00:13.0,Turkey
bb2cbcad-1580-4aa0-b9bf-d4f8a99cc493,46130751,id,2018-10-09 00:00:09.0,2018-10-09 15:45:02.0,Indonesia
61EA3935-495B-4C5A-A9CD-4ACC66FD5A47,46130713,ar,2018-10-09 00:00:11.0,2018-10-09 00:00:21.0,Kuwait
A7CADD7A-36D7-4B21-ADED-A5CAA2DD73F7,0,ar,2018-10-09 00:00:12.0,2018-10-09 00:00:12.0,Saudi Arabia
7c3187ea-f0f7-4da4-96b3-d0b118cd12a4,0,ar,2018-10-08 00:00:03.0,2018-10-08 18:12:59.0,Saudi Arabia
a0b7e6ad-8ef0-4259-b791-2e0c921a078e,46085131,en,2018-10-08 00:00:05.0,2018-10-08 00:02:20.0,Saudi Arabia
5418ab39-2cf5-4b66-9b9b-bce2be6c17d2,0,en,2018-10-08 00:00:06.0,2018-10-08 00:00:06.0,United Arab Emirates
74314d88-0e5c-46b6-97b3-2cdbf1c23a3e,0,en,2018-10-08 00:00:10.0,2018-10-09 21:18:16.0,United Arab Emirates
2D5D50B5-9570-490F-8B1A-D36F73B34AE7,46085073,ar,2018-10-08 00:00:11.0,2018-10-08 02:17:47.0,Saudi Arabia
1c74c1a4-c921-44b4-9941-ba6c2995360b,0,en,2018-10-08 00:00:11.0,2018-10-08 00:03:34.0,Saudi Arabia
8443DD2B-8A11-4C59-A72C-F9CCA22A5D98,46085077,ar,2018-10-08 00:00:11.0,2018-10-08 00:00:23.0,Saudi Arabia
B49E4117-4BE6-46E0-A7C5-40E99CAD580B,0,ar,2018-10-08 00:00:12.0,2018-10-08 00:00:17.0,Saudi Arabia
3E144DB2-9BA9-4E2E-854A-59FF52AD91DC,10715907,ar,2018-10-08 00:00:14.0,2018-10-08 00:00:20.0,Saudi Arabia
d312445e-3a7d-4678-85f3-076353ffd13c,0,en,2018-10-08 00:00:15.0,2018-10-08 00:00:15.0,Kuwait

另一个rdd类似：

39250E6B-DB60-496E-8770-225EDB29A85F
2b98d4f4-0c55-4906-82ec-cfc7c5380652

---

如何选择第二个rdd中不包含的第一个rdd

一种方法是将rdd转换为数据帧并应用

左反

连接，如下所示：

val rdd1 = sc.parallelize(Seq(
  ("39250E6B-DB60-496E-8770-225EDB29A85F",0,"ar","2018-10-09 00:00:00.0","2018-10-09 00:00:04.0","United Arab Emirates"),
  ("2b98d4f4-0c55-4906-82ec-cfc7c5380652",40967837,"en","2018-10-09 00:00:01.0","2018-10-09 00:00:31.0","Qatar"),
  ("5bb587bc-54a0-4873-b0ba-2da38458ba1c",0,"en","2018-10-09 00:00:03.0","2018-10-09 00:04:02.0","United Arab Emirates"),
  ("466B96B5-DC12-4A35-8865-3A8702037A23",0,"ar","2018-10-09 00:00:04.0","2018-10-09 00:00:06.0","Saudi Arabia")
))

val rdd2 = sc.parallelize(Seq(
  ("39250E6B-DB60-496E-8770-225EDB29A85F"),
  ("2b98d4f4-0c55-4906-82ec-cfc7c5380652")
))

val dfResult = rdd1.toDF.join(rdd2.toDF("_1"), Seq("_1"), "left_anti")

dfResult.show
// +--------------------+---+---+--------------------+--------------------+--------------------+
// |                  _1| _2| _3|                  _4|                  _5|                  _6|
// +--------------------+---+---+--------------------+--------------------+--------------------+
// |5bb587bc-54a0-487...|  0| en|2018-10-09 00:00:...|2018-10-09 00:04:...|United Arab Emirates|
// |466B96B5-DC12-4A3...|  0| ar|2018-10-09 00:00:...|2018-10-09 00:00:...|        Saudi Arabia|
// +--------------------+---+---+--------------------+--------------------+--------------------+

如果希望结果数据集采用RDD格式，只需将

RDD

应用于连接的数据帧：

val rddResult = dfResult.rdd

另一种方法是将RDD转换为pairRDD，并应用

leftOuterJoin

过滤掉具有公共键的任何行：

val rddKV1 = rdd1.map(r => (r._1, (r._2, r._3, r._4, r._5, r._6)))
val rddKV2 = rdd2.map(r => (r, 1))

val rddResult = rddKV1.leftOuterJoin(rddKV2).
  filter(r => r._2._2 == None).
  map{ case (k, (v, _)) => (k, v._1, v._2, v._3, v._4, v._5) }

[更新]

根据@Archer的评论，

subtractByKey

似乎是采用PairRDD转换方法时最直接的解决方案：

val rddResult = rddKV1.subtractByKey(rddKV2)

---

这能做到吗？不解析到数据帧？@Archer，请看扩展的答案。我找到了一种方法：val rddres=rdd1。filter（x=>！（rdd2包含x（0））@Archer，据我所知，RDD没有方法

包含
。如果您的rdd2足够小，您可以先
将其收集为Scala集合，然后再应用
contains
。很抱歉，它应该是val rddres=rdd1.filter（x=>！（rdd2.collect（）.toList包含x（0））。是否可以不使用dataframe？