This is my design. Now let me try and code it in Spark.
rdd1.txt =========1~4,5,6,72~4,53~6,7
rdd2.txt
========4~1001,1000,1002,10035~1004,1001,1006,10076~1007,1009,1005,10087~1011,1012,1013,1010
TRANSFORM 1===========map each value to key (like an inverted
index)4~15~16~17~15~24~26~37~3
TRANSFORM 2===========Join keys in transform 1 and
rdd24~1,1001,1000,1002,10034~2,1001,1000,1002,10035~1,1004,1001,1006,10075~2,1004,1001,1006,10076~1,1007,1009,1005,10086~3,1007,1009,1005,10087~1,1011,1012,1013,10107~3,1011,1012,1013,1010
TRANSFORM 3===========Split key in transform 2 with "~" and keep key(1) i.e.
1,2,31~1001,1000,1002,10032~1001,1000,1002,10031~1004,1001,1006,10072~1004,1001,1006,10071~1007,1009,1005,10083~1007,1009,1005,10081~1011,1012,1013,10103~1011,1012,1013,1010
TRANSFORM 4===========join by key
1~1001,1000,1002,1003,1004,1001,1006,1007,1007,1009,1005,1008,1011,1012,1013,10102~1001,1000,1002,1003,1004,1001,1006,10073~1007,1009,1005,1008,1011,1012,1013,1010
From: dcmovva <dilip.mo...@gmail.com>
To: user@spark.apache.org
Sent: Saturday, January 3, 2015 10:10 AM
Subject: Joining by values
I have a two pair RDDs in spark like this
rdd1 = (1 -> [4,5,6,7])
(2 -> [4,5])
(3 -> [6,7])
rdd2 = (4 -> [1001,1000,1002,1003])
(5 -> [1004,1001,1006,1007])
(6 -> [1007,1009,1005,1008])
(7 -> [1011,1012,1013,1010])
I would like to combine them to look like this.
joinedRdd = (1 ->
[1000,1001,1002,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013])
(2 -> [1000,1001,1002,1003,1004,1006,1007])
(3 -> [1005,1007,1008,1009,1010,1011,1012,1013])
Can someone suggest me how to do this.
Thanks Dilip
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