My dataset looks like the following:
( A, (1,2) )
( B, (2,9) )
I would like to "flatten" the tuples in Pig, basically repeating each record for each value found in the inner-tuple, such that the expected output is:
( A, 1 )
( A, 2 )
( B, 2 )
( B, 9 )
I know this is possible when the tuples (1,2) and (2,9) are bags instead.
Your insight is good; it's possible by transforming the tuple in a bag. The schema we want to aim for is: {a: chararray,{(chararray)}} for example: (A,{(1),(2)})
Here is the solution to your problem:
A = LOAD 'data.txt' AS (a:chararray,b:(b1:chararray,b2:chararray));
B = FOREACH A GENERATE a, TOBAG(b.b1,b.b2);
C = FOREACH B GENERATE a, FLATTEN($1);
The magic part is the TOBAG operator.
You can use DataFu's UDF TransposeTupleToBag (http://datafu.incubator.apache.org/docs/datafu/1.1.0/datafu/pig/util/TransposeTupleToBag.html) and then flatten the bag to get a row per item in the bag.
I know this is an old thread but I could not get the above method to work. Thought I will share my findings.
input: (1-2-3, abc)
(4-5-6, xyz)
desired output:
(1, abc)
(2, abc)
(3, abc)
(4, xyz)
(5, xyz)
(6, xyz)
Initially, I used STRSPLIT that generates a tuple resulting in the similar input as above but was unsuccessful.
output = FOREACH input GENERATE FLATTEN(TOBAG(STRSPLIT($0, '-'))), $1
This resulted in the output as:
(1,2,3,abc)
(4,5,6,xyz)
However, when I used tokenize and replace functions I got the desired output.
output = FOREACH input GENERATE FLATTEN(TOKENIZE(REPLACE($0,'-', ' '))), $1;
Related
I am trying to create the following format of relation using Pig Latin:
userid, day, {(pid,fulldate, x,y),(pid,fulldate, x,y), ...}
Relation description: Each user (userid) in each day (day) has purchased multiple products (pid)
I am Loading the data into:
A= LOAD '**from a HDFS URL**' AS (pid: chararray,userid:
chararray,day:int,fulldate: chararray,x: chararray,y:chararray);
B= GROUP A BY (userid, day);
Describe B;
B: {group: (userid: chararray,day: int),A: {(pid: chararray,day: int,fulldate: chararray,x: chararray,userid: chararray,y: chararray)}}
C= FOREACH B FLATTEN(B) AS (userid,day), $1.pid, $1.fulldate,$1.x,$1.y;
Describe C;
C: {userid: chararray,day: int,{(pid: chararray)}},{(fulldate: chararray)},{(x: chararray)},{(y: chararray)}}
The result of Describe C does not give the format I want ! What I am doing wrong?
You are correct till the GROUP BY part. After that however you are trying to do something messy. I'm actually not sure what is happening for your alias C. To arrive at the format you are looking for, you will need a nested foreach.
C = FOREACH B {
data = A.pid, A.fulldate, A.x, A.y;
GENERATE FLATTEN(group), data;
}
This allows C to have one record for each (userid, day) and all the corresponding (pid,fulldate, x, y) tuples in a bag.
You can read more about nested foreach here: https://www.safaribooksonline.com/library/view/programming-pig/9781449317881/ch06.html (Search for nested foreach in that link).
My understanding is that B is almost what you're looking for, except you would like the tuple containing userid and day to be flattened, and you would like only pid, fulldate, x, and y to appear in the bag.
First, you want to flatten the tuple group which has fields userid and day, not the bag A which contains multiple tuples. Flattening group unnests the tuple, which only has 1 set of unique values for each row, whereas flattening the bag A would effectively ungroup your previous GROUP BY statement since the values in the bag A are not unique. So the first part should read C = FOREACH B GENERATE FLATTEN(group) AS (userid, day);
Next, you want to keep pid, fulldate, x, and y in separate tuples for each record, but the way you've selected them essentially makes a bag of all the pid values, a bag of all the fulldate values, etc. Instead, try selecting these fields in a way that keeps the tuples nested in the bag:
C = FOREACH B GENERATE
FLATTEN(group) AS (userid, day),
A.(pid, fulldate, x, y) AS A;
I am creating a "temporary" (transition) table : "Abis" which must be the copy (identical structure) of a table "A" with the addition of data and the update of several fields via other tables more recent (B, C, D, E).
I have a primary key based on 2 fields in "A" (A.a and A.b) that is present in "Abis" (Abis.a and Abis.b) as well as in "B" (B.a and B.b).
I made a full join between A and B: A.a = B.a and A.b = B.b.
What mapping I have to put to feed my "Abis" table on Abis.a and Abis.b, recovering all key combinations of A (A.a + A.b) as well as all key combinations of B (B.a + B.b) that aren't present in A.
I tested with
"Case When A.a Not In B.a Than A.a Else B.a End"
But the query turns indefinitely.
To sum up:
Target Datastore: Abis
Diagram: A, B, C, D, E
Join: A.a = B.a and A.b = B.b (Full join)
Number of row: Table A ~ 6000, Table B ~ 40000
Software: ODI 10.1.3.5 (Oracle Data Integrator)
Thanks :)
Ok I almost solved my problem with the DECODE function
I tried the NVL function but it did not give exactly what I wanted.
The similar function to NVL is DECODE.
https://www.techonthenet.com/oracle/functions/decode.php
Mapping on Abis.a > Decode (A.a, 0, B.a, A.a)
Mapping on Abis.b > Decode (A.b, 0, B.b, A.b)
I want to Union/Merge two files using pig. But, this is a different union than a usual union. Following are my files (h* are header of files) :
F1 :
h1,h2,h3,h4
a01,a02,a03,a04
a11,a12,a13,a14
F2 :
h3,h4,h5,h6
a23,a24,b01,b02
a33,a34,b11,b12
The resulting output must be a Union of these files like this :
FR :
h1,h2,h3,h4,h5,h6
a01,a02,a03,a04,,
a11,a12,a13,a14,,
,,a23,a24,b01,b02
,,a33,a34,b11,b12
One more difficulty is I want to make it generic so that it works for dynamic number of common columns. Currently there are two common columns, it could have 3 or 1 common column or even no common column at all. For example :
F1 :
h1,h2,h3,h4
a1,a2,a3,a4
F2
h5,h6,h7,h8
b1,b2,b3,b4
FR
a1,a2,a3,a4
,,,,b1,b2,b3,b4
Any hint/help is appreciable.
Here is how you can do it statically:
F1full = FOREACH F1 GENERATE h1,h2,h3,h4, NULL as h5, NULL as h6;
F2full = FOREACH F2 GENERATE NULL as h1,NULL as h2,h3,h4, h5, h6;
FR = F1full UNION F2full;
Pig is not very flexible, so I don't think it is possible to generate this dynamically/for the generic case.
If you would want a solution for the generic case, you could use a language like python to build the required command based on metadata of stored tables/files.
I tried to solve the problem using following approach :
1) Load both of the files.
2) Add counter to generate a unique field (ID).
3) Start the counter for file B where counter for A ended.
4) Cogroup both files with common columns, including counteer.
5) Take all group columns in a different schema.
6) Generate uncommon columns from both files, along with the counter.
7) First join uncommon columns from file A with group columns on counter.
8) Join the result of step 7 with uncommon columns from file B on counter.
Following is the pig script to do the same. As this script is generic, I have mentioned what all parameters will be required before running the script.
-- Parameters required : $file1_path, $file2_path, $file1_schema, $file2_schema, $COUNT_A (number of rows in file A), $CMN_COLUMN_A (common columns in A), $CMN_COLUMN_B, $UNCMN_COLUMN_A(Unique columns in file A), $UNCMN_COLUMN_B.
A = LOAD '$file1_path' USING org.apache.pig.piggybank.storage.CSVExcelStorage('~', 'NO_MULTILINE', 'NOCHANGE', 'SKIP_INPUT_HEADER') as ($file1_schema);
B = LOAD '$file2_path' USING org.apache.pig.piggybank.storage.CSVExcelStorage('~', 'NO_MULTILINE', 'NOCHANGE', 'SKIP_INPUT_HEADER') as ($file2_schema);
RANK_A = RANK A;
RANK_B = RANK B;
COUNT_RANK_B = FOREACH RANK_B GENERATE ($0+(long)'$COUNT_A') as rank_B, $1 ..;
COGRP_RANK_AB = COGROUP RANK_A BY($CMN_COLUMN_A), COUNT_RANK_B BY ($CMN_COLUMN_B);
CMN_COGRP_RANK_AB = FOREACH COGRP_RANK_AB GENERATE FLATTEN(group) AS ($CMN_COLUMN_A);
UNCMN_RB = FOREACH COUNT_RANK_B GENERATE $UNCMN_COLUMN_B;
JOIN_CMN_UNCMN_A = JOIN CMN_COGRP_RANK_AB BY(rank_A) LEFT OUTER, UNCMN_RA by rank_A;
JOIN_CMN_UNCMN_B = JOIN JOIN_CMN_UNCMN_A BY(CMN_COGRP_RANK_AB::rank_A) LEFT OUTER, UNCMN_RB by rank_B;
STORE FINAL_DATA INTO '$store_path' USING org.apache.pig.piggybank.storage.CSVExcelStorage('~', 'NO_MULTILINE', 'UNIX', 'WRITE_OUTPUT_HEADER');
I have a table which contain sample CDR data in that column A and column B having calling person and called person mobile number
I need to find whose having maximum number of calls made(column A)
and also need to find to which number(column B) called most
the table structure is like below
calling called
889578226 77382596
889582256 77382596
889582256 7736368296
7785978214 782987522
in the above table 889578226 have most number of outgoing calls and 77382596 is most called number in such a way need to get the output
in hive i run like below
SELECT calling_a,called_b, COUNT(called_b) FROM cdr_data GROUP BY calling_a,called_b;
what might be the equalent code for the above query in pig?
Anas, Could you please let me know this is what you are expecting or something different?
input.txt
a,100
a,101
a,101
a,101
a,103
b,200
b,201
b,201
c,300
c,300
c,301
d,400
PigScript:
A = LOAD 'input.txt' USINg PigStorage(',') AS (name:chararray,phone:long);
B = GROUP A BY (name,phone);
C = FOREACH B GENERATE FLATTEN(group),COUNT(A) AS cnt;
D = GROUP C BY $0;
E = FOREACH D {
SortedList = ORDER C BY cnt DESC;
top = LIMIT SortedList 1;
GENERATE FLATTEN(top);
}
DUMP E;
Output:
(a,101,3)
(b,201,2)
(c,300,2)
(d,400,1)
I have raw data in bag:
{(id,35821),(lang,en-US),(pf_1,us)}
{(path,/ybe/wer),(id,23481),(lang,en-US),(intl,us),(pf_1,yahoo),(pf_3,test)}
{(id,98234),(lang,ir-IL),(pf_1,il),(pf_2,werasdf|dfsas)}
How could I extract the tuples whose column 1 matches id and pf_*?
The output I want:
{(id,35821),(pf_1,us)}
{(id,23481),(pf_1,yahoo),(pf_3,test)}
{(id,98234),(pf_1,il),(pf_2,werasdf|dfsas)}
Any suggestion would be appreciated. Thanks!
In order to process the inner bag (a bag in a format like OUTER_BAG: {INNER_BAG: {(e:int)}}) you are going to have to use a nested FOREACH. This will allow you to preform operations over the tuples in the inner bag.
For example, you are going to want to do something like:
-- A: {inner_bag: {(val1: chararray, val2: chararray)}}
B = FOREACH A {
filtered_bags = FILTER inner_bag BY val1 matches '^(id|pf_).*' ;
GENERATE filtered_bags ;
}