torchtext TabularDataset returns ValueError: too many values to unpack (expected - torchtext

I just exported a dataset with
df[['src', 'trg']].to_csv('dataset.csv', index=False, quoting=csv.QUOTE_ALL)
I checked that there are no commas at all in the cells of the table. However, when I try to read the file with
from torchtext.data import TabularDataset
dataset = TabularDataset(os.path.abspath('dataset.csv'), format='csv', fields=['src', 'trg'])
I get:
ValueError: too many values to unpack (expected 2)
The data looks like this:
$ head dataset.csv
"src","trg"
"S( CC) /C(=N\ [H] ) N","[H] /N=C(/ N) S CC"
"[CH2:0] 1 [CH2:0] [N:0] ( [CH2:0] [CH:0] 2 [CH2:0] [N:0] ( [C:0] ( [O:0] [CH3:0] ) = [O:0] ) [CH2:0] [CH2:0] [N:0] 2 [C:0] ( [CH2:0] [c:0] 2 [cH:0] [c:0] ( [Cl:0] ) [c:0] ( [Cl:0] ) [cH:0] [cH:0] 2) = [O:0] ) [CH2:0] [CH2:0] 1","[CH3:0] [O:0] [C:0] ( = [O:0] ) [N:0] 1 [CH2:0] [CH2:0] [N:0] ( [C:0] ( = [O:0] ) [CH2:0] [c:0] 2 [cH:0] [cH:0] [c:0] ( [Cl:0] ) [c:0] ( [Cl:0] ) [cH:0] 2) [CH:0] ( [CH2:0] [N:0] 2 [CH2:0] [CH2:0] [CH2:0] [CH2:0] 2) [CH2:0] 1"
Notably, the cells contain \'s.


from torchtext.data import TabularDataset, Field
dataset = TabularDataset('dataset.csv', format='csv', fields=[('src', Field()), ('trg', Field())])
worked. For fields a list of tuples had to be provided.

Related

Iterate through records to build hierarchy

Please consider the following tables. They describe a schools' hierarchy and the notes per student.
users
-------------------------------------------------------------
root_id obj_id obj_type obj_ref_id obj_role
-------------------------------------------------------------
1 2 student 7 learn
1 3 student 7 learn
1 1 principal 1 lead
1 4 mentor 1 train teachers
1 5 trainee 4 learn teaching
1 6 trainee 4 learn teaching
1 7 teacher 1 teach
2 8 student 9 learn
2 9 principal 9 lead
notes
--------------------------------------------------------------
note_id obj_id note
--------------------------------------------------------------
1 2 foo
2 2 bar
3 2 baz
4 3 lorem
5 8 ipsum
I need to write out the hierarchy and number of notes per user as follows:
-------------------------------------------------------------------------------------------
obj_id notes obj_path
-------------------------------------------------------------------------------------------
1 0 principal 1 (lead)
2 3 student 2 (learn) > teacher 7 (teach) > principal 1 (lead)
3 1 student 3 (learn) > teacher 7 (teach) > principal 1 (lead)
4 0 mentor 4 (train teachers) > principal 1 (lead)
5 0 trainee 5 (learn teaching) > mentor 4 (train teachers) > principal 1 (lead)
6 0 trainee 6 (learn teaching) > mentor 4 (train teachers) > principal 1 (lead)
7 0 teacher 7 (teach) > principal 1 (lead)
8 1 student 8 (learn) > principal 2 (lead)
9 0 principal 9 (lead)
For this, I understand that I need to use a loop as follows:
declare cur cursor for
select obj_id from users order by root_id
open cur
declare #obj_id int
fetch next from cur into #id
while (##FETCH_STATUS = 0)
begin
select obj_role from users where obj_id = #obj_id
fetch next from cur into #obj_id
end
close cur
deallocate cur
This is what I have until now, but I do not understand how to go from here. Can someone help me on my way?

Understand that using a cursor is going to process each individual record one by one.
Recursive CTE would be a better solution:
Sql server CTE and recursion example
CTE Recursion to get tree hierarchy
How does a Recursive CTE run, line by line?
Something like:
DECLARE #User TABLE
(
[root_id] INT
, [obj_id] INT
, [Obj_type] NVARCHAR(100)
, [obj_ref_id] INT
, [obj_role] NVARCHAR(100)
);
DECLARE #Notes TABLE
(
[note_id] INT
, [obj_id] INT
, [note] NVARCHAR(255)
);
INSERT INTO #Notes (
[note_id]
, [obj_id]
, [note]
)
VALUES ( 1, 2, 'foo ' )
, ( 2, 2, 'bar ' )
, ( 3, 2, 'baz ' )
, ( 4, 3, 'lorem' )
, ( 5, 8, 'ipsum' );
INSERT INTO #User (
[root_id]
, [obj_id]
, [Obj_type]
, [obj_ref_id]
, [obj_role]
)
VALUES ( 1, 2, 'student', 7, 'learn' )
, ( 1, 3, 'student', 7, 'learn' )
, ( 1, 1, 'principal', 1, 'lead' )
, ( 1, 4, 'mentor', 1, 'train teachers' )
, ( 1, 5, 'trainee', 4, 'learn teaching' )
, ( 1, 6, 'trainee', 4, 'learn teaching' )
, ( 1, 7, 'teacher', 1, 'teach' )
, ( 2, 8, 'student', 9, 'learn' )
, ( 2, 9, 'principal', 9, 'lead' );
WITH [Hierarchy]
AS ( SELECT [obj_id] AS [root_obj]
, [obj_ref_id] AS [root_obj_ref]
, [obj_id]
, [obj_ref_id]
, CONVERT(
NVARCHAR(MAX)
, [Obj_type] + ' ' + CONVERT(NVARCHAR, [obj_id]) + ' ('
+ [obj_role] + ')'
) AS [obj_path]
FROM #User
UNION ALL
SELECT [a].[root_obj]
, [a].[root_obj_ref]
, [b].[obj_id]
, [b].[obj_ref_id]
, [a].[obj_path] + ' > ' + [b].[Obj_type]
+ CONVERT(NVARCHAR, [b].[obj_id]) + ' (' + [b].[obj_role] + ')' AS [obj_path]
FROM [Hierarchy] [a]
INNER JOIN #User [b]
ON [b].[obj_id] = [a].[obj_ref_id]
WHERE [a].[obj_id] <> [a].[obj_ref_id] ) --Here, basically continue the recursion while the record isn't referencing itself. The final will include that self referencing record.
SELECT [Hierarchy].[root_obj] AS [obj_id]
, (
SELECT COUNT(*)
FROM #Notes
WHERE [obj_id] = [Hierarchy].[root_obj]
) AS [notes] --Here we'll go out and get the count of notes.
, [Hierarchy].[obj_path]
FROM [Hierarchy]
WHERE [Hierarchy].[obj_id] = [Hierarchy].[obj_ref_id] --Then we only went those records built up to the final record that was referencing itself.
ORDER BY [Hierarchy].[root_obj];

LWP::UserAgent memory usage while saving content

EDIT: The issue below was produced on stock Perl 5.16.3 on an AWS ec2 micro instance. It was ultimately solved by installing and switching to Perl 5.24.3 with perlbrew.
LWP::UserAgent seems to be causing some kind of memory leak when saving content.
use v5.10;
use strict;
use warnings;
use IO::Socket::SSL;
use LWP::UserAgent;
use Memory::Usage;
use Time::HiRes 'usleep';
my $ua = LWP::UserAgent->new;
my $mu = Memory::Usage->new;
$ua->ssl_opts(SSL_ocsp_mode => SSL_OCSP_NO_STAPLE); ## disable OCSP stapling
for (1..50) {
$mu->record("before request: $_");
$ua->get('http://www.wikipedia.org/wiki/Special:Random', ':content_file' => 'temp.html');
usleep 50000;
}
$mu->dump();
Output:
time vsz ( diff) rss ( diff) shared ( diff) code ( diff) data ( diff)
0 213964 ( 213964) 25112 ( 25112) 7532 ( 7532) 8 ( 8) 17976 ( 17976) before request: 1
0 225744 ( 11780) 31428 ( 6316) 8120 ( 588) 8 ( 0) 23580 ( 5604) before request: 2
0 226824 ( 1080) 32500 ( 1072) 8120 ( 0) 8 ( 0) 24660 ( 1080) before request: 3
0 227920 ( 1096) 33596 ( 1096) 8120 ( 0) 8 ( 0) 25756 ( 1096) before request: 4
0 229016 ( 1096) 34692 ( 1096) 8120 ( 0) 8 ( 0) 26852 ( 1096) before request: 5
1 230112 ( 1096) 35784 ( 1092) 8120 ( 0) 8 ( 0) 27948 ( 1096) before request: 6
1 231204 ( 1092) 36880 ( 1096) 8120 ( 0) 8 ( 0) 29040 ( 1092) before request: 7
1 232296 ( 1092) 37968 ( 1088) 8120 ( 0) 8 ( 0) 30132 ( 1092) before request: 8
1 233388 ( 1092) 39060 ( 1092) 8120 ( 0) 8 ( 0) 31224 ( 1092) before request: 9
1 234484 ( 1096) 40152 ( 1092) 8120 ( 0) 8 ( 0) 32320 ( 1096) before request: 10
1 235572 ( 1088) 41248 ( 1096) 8120 ( 0) 8 ( 0) 33408 ( 1088) before request: 11
2 236668 ( 1096) 42344 ( 1096) 8120 ( 0) 8 ( 0) 34504 ( 1096) before request: 12
2 237764 ( 1096) 43440 ( 1096) 8120 ( 0) 8 ( 0) 35600 ( 1096) before request: 13
2 238864 ( 1100) 44536 ( 1096) 8120 ( 0) 8 ( 0) 36700 ( 1100) before request: 14
2 239956 ( 1092) 45632 ( 1096) 8120 ( 0) 8 ( 0) 37792 ( 1092) before request: 15
2 241044 ( 1088) 46720 ( 1088) 8120 ( 0) 8 ( 0) 38880 ( 1088) before request: 16
3 242140 ( 1096) 47816 ( 1096) 8120 ( 0) 8 ( 0) 39976 ( 1096) before request: 17
3 243240 ( 1100) 48916 ( 1100) 8120 ( 0) 8 ( 0) 41076 ( 1100) before request: 18
3 244336 ( 1096) 50008 ( 1092) 8120 ( 0) 8 ( 0) 42172 ( 1096) before request: 19
3 245428 ( 1092) 51096 ( 1088) 8120 ( 0) 8 ( 0) 43264 ( 1092) before request: 20
3 246516 ( 1088) 52196 ( 1100) 8120 ( 0) 8 ( 0) 44352 ( 1088) before request: 21
4 247612 ( 1096) 53288 ( 1092) 8120 ( 0) 8 ( 0) 45448 ( 1096) before request: 22
4 248704 ( 1092) 54380 ( 1092) 8120 ( 0) 8 ( 0) 46540 ( 1092) before request: 23
4 249796 ( 1092) 55476 ( 1096) 8120 ( 0) 8 ( 0) 47632 ( 1092) before request: 24
4 250892 ( 1096) 56568 ( 1092) 8120 ( 0) 8 ( 0) 48728 ( 1096) before request: 25
4 251988 ( 1096) 57660 ( 1092) 8120 ( 0) 8 ( 0) 49824 ( 1096) before request: 26
4 253076 ( 1088) 58752 ( 1092) 8120 ( 0) 8 ( 0) 50912 ( 1088) before request: 27
5 254168 ( 1092) 59852 ( 1100) 8120 ( 0) 8 ( 0) 52004 ( 1092) before request: 28
5 255272 ( 1104) 60940 ( 1088) 8120 ( 0) 8 ( 0) 53108 ( 1104) before request: 29
5 256360 ( 1088) 62036 ( 1096) 8120 ( 0) 8 ( 0) 54196 ( 1088) before request: 30
5 257456 ( 1096) 63132 ( 1096) 8120 ( 0) 8 ( 0) 55292 ( 1096) before request: 31
5 258556 ( 1100) 64236 ( 1104) 8120 ( 0) 8 ( 0) 56392 ( 1100) before request: 32
6 259652 ( 1096) 65324 ( 1088) 8120 ( 0) 8 ( 0) 57488 ( 1096) before request: 33
6 260740 ( 1088) 66416 ( 1092) 8120 ( 0) 8 ( 0) 58576 ( 1088) before request: 34
6 261832 ( 1092) 67504 ( 1088) 8120 ( 0) 8 ( 0) 59668 ( 1092) before request: 35
6 262928 ( 1096) 68600 ( 1096) 8120 ( 0) 8 ( 0) 60764 ( 1096) before request: 36
6 264016 ( 1088) 69692 ( 1092) 8120 ( 0) 8 ( 0) 61852 ( 1088) before request: 37
7 265120 ( 1104) 70796 ( 1104) 8120 ( 0) 8 ( 0) 62956 ( 1104) before request: 38
7 266212 ( 1092) 71888 ( 1092) 8120 ( 0) 8 ( 0) 64048 ( 1092) before request: 39
7 267304 ( 1092) 72980 ( 1092) 8120 ( 0) 8 ( 0) 65140 ( 1092) before request: 40
7 268396 ( 1092) 74072 ( 1092) 8120 ( 0) 8 ( 0) 66232 ( 1092) before request: 41
7 269484 ( 1088) 75168 ( 1096) 8120 ( 0) 8 ( 0) 67320 ( 1088) before request: 42
7 270584 ( 1100) 76260 ( 1092) 8120 ( 0) 8 ( 0) 68420 ( 1100) before request: 43
8 271676 ( 1092) 77356 ( 1096) 8120 ( 0) 8 ( 0) 69512 ( 1092) before request: 44
8 272776 ( 1100) 78448 ( 1092) 8120 ( 0) 8 ( 0) 70612 ( 1100) before request: 45
8 273868 ( 1092) 79540 ( 1092) 8120 ( 0) 8 ( 0) 71704 ( 1092) before request: 46
8 274964 ( 1096) 80632 ( 1092) 8120 ( 0) 8 ( 0) 72800 ( 1096) before request: 47
8 276052 ( 1088) 81728 ( 1096) 8120 ( 0) 8 ( 0) 73888 ( 1088) before request: 48
9 277144 ( 1092) 82816 ( 1088) 8120 ( 0) 8 ( 0) 74980 ( 1092) before request: 49
9 278232 ( 1088) 83912 ( 1096) 8120 ( 0) 8 ( 0) 76068 ( 1088) before request: 50
Perl version is 5.16.3 ; Modules versions below using cpan -D
CPAN: Module::CoreList loaded ok (v5.20170923)
(no description)
S/SU/SULLR/IO-Socket-SSL-2.056.tar.gz
/home/ec2-user/perl5/lib/perl5/IO/Socket/SSL.pm
Installed: 2.056
CPAN: 2.056 up to date
Steffen Ullrich (SULLR)
Steffen_Ullrich#genua.de
...
CPAN: Module::CoreList loaded ok (v5.20170923)
(no description)
M/MI/MIKEM/Net-SSLeay-1.85.tar.gz
/home/ec2-user/perl5/lib/perl5/x86_64-linux-thread-multi/Net/SSLeay.pm
Installed: 1.85
CPAN: 1.85 up to date
Mike McCauley (MIKEM)
mikem#airspayce.com
...
CPAN: Module::CoreList loaded ok (v5.20170923)
(no description)
O/OA/OALDERS/libwww-perl-6.33.tar.gz
/home/ec2-user/perl5/lib/perl5/LWP/UserAgent.pm
Installed: 6.33
CPAN: 6.33 up to date
Olaf Alders (OALDERS)
olaf#wundersolutions.com
...
CPAN: Module::CoreList loaded ok (v5.20170923)
(no description)
O/OA/OALDERS/LWP-Protocol-https-6.07.tar.gz
/home/ec2-user/perl5/lib/perl5/LWP/Protocol/https.pm
Installed: 6.07
CPAN: 6.07 up to date
Olaf Alders (OALDERS)
olaf#wundersolutions.com

There is a memory leak in the OCSP handling which is relevant if the target site uses OCSP stapling (only in this case is revocation checking done by default). A first leak in this area was fixed in Net::SSLeay1 1.83. But I've found a second leak which is not fixed yet although a patch is available (since a few minutes). See issue 125273 for details of the problem and the patch.
It is also possible to work around this problem by disabling OCSP stapling:
use IO::Socket::SSL;
use LWP::UserAgent;
my $ua = LWP::UserAgent->new;
$ua->ssl_opts(SSL_ocsp_mode => SSL_OCSP_NO_STAPLE); ## disable OCSP stapling
$ua->get('http://www.wikipedia.org', ':content_file' => 'save.txt') for 0..500;
1 Net::SSLeay is the underlying library for IO::Socket::SSL which itself provides SSL functionality to LWP.

Optimize SQL statement for this Query?

I have two tables T1 and T2.
T1 have ID,F1,F2,F3,F4,F5,F6,F7,F8
T2 have ID,T1_ID,F1,F2,F3,F4,F5,F6,F7,F8,SUM
Examples Data for T1 and T2
T1
ID,F1,F2,F3,F4,F5,F6,F7,F8
1, 1, 2, 3, 0, 0, 5, 0, 0
2, 0, 0, 0, 1, 0, 4, 5, 0
3, 4, 1, 3, 2, 0, 0, 0, 5
4, 1 ,3, 4, 0, 0 ,0, 0, 0
5, 7, 2, 1, 3, 0, 0, 0, 0
.
.
.
T2
ID,T1_ID,F1,F2,F3,F4,F5,F6,F7,F8,SUM
1, 1, 2, 3, 5, 0, 0, 3, 0, 0,100
2, 5, 9, 8, 8, 1, 0, 0, 0, 0,200
3, 2, 0, 0, 0, 5, 0, 6, 6, 0,300
4, 1 ,3, 4, 2, 0 ,0, 3, 0, 0,255
5, 4, 8, 8, 8, 0, 0, 0, 0, 0,155
.
.
Select * from T2 where T1.F1....T1.F8 have (1 and 2 and 3)
query must return records 1,2,4
1, 1, 2, 3, 5, 0, 0, 3, 0, 0,100
2, 5, 9, 8, 8, 1, 0, 0, 0, 0,200
4, 1 ,3, 4, 2, 0 ,0, 3, 0, 0,255
I create this query
Select T2.ID,T2.F1,T2.F2,T2.F3,T2.F4.T2.F5,T2.F6,T2.F7,T2.F8,T2.SUM,T1.ID
from T2
join T1 on T1.ID = T2.T1_ID
where
(CASE WHEN ( T1_ID.F1 = 1 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 2 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
or
(CASE WHEN ( T1_ID.F1 = 1 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F2 = 2 ) THEN T2.F2 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
or
(CASE WHEN ( T1_ID.F1 = 1 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F3 = 2 ) THEN T2.F3 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
or
(CASE WHEN ( T1_ID.F1 = 1 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F4 = 2 ) THEN T2.F4 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
.
.
.
or
(CASE WHEN ( T1_ID.F2 = 1 ) THEN T2.F2 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 2 ) THEN T2.F1 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
or
(CASE WHEN ( T1_ID.F2 = 1 ) THEN T2.F2 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F2 = 2 ) THEN T2.F2 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
or
(CASE WHEN ( T1_ID.F2 = 1 ) THEN T2.F2 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F3 = 2 ) THEN T2.F3 between 0 and 1000 end)
and(CASE WHEN ( T1_ID.F1 = 3 ) THEN T2.F1 between 0 and 1000 end)
.
.
.
this is too big statement.
How can I optimize statement ?

SELECT * FROM T2
WHERE EXISTS ( SELECT N.ID
FROM( SELECT T1.ID , T1.F1 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F2 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F3 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F4 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F5 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F6 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F7 AS F
FROM T1
UNION ALL
SELECT T1.ID , T1.F8 AS F
FROM T1
UNION ALL
) N
WHERE N.F IN ( 1, 2, 3 )
AND N.ID = T2.T1_ID
GROUP BY N.ID
HAVING COUNT(DISTINCT N.F) = 3
);

Finding chronological age on Filemaker to be used in equation

I'm trying to calculate a chronological age based on a person's birth date (DOB) and the date of evaluation (DOE). I need the answer to be expressed as a numerical number that can be put in an equation. For example if a person's DOB is 12/26/07 and the DOE is 10/13/15 the chronological age will be 7.75, NOT 7;9 (7 years, 9 months). The decimal place needs to be a function out of 12, not simply representing the age in months. I have accurately calculated this but every time the chronological age is configured to be an even age (9 years 0 months) the calculation shows up as 90, I really need this "90" to be a "9.0" is there anything I can do to configure this into my calculation? The current calculation that is working for every other age is:
Year ( GetAsNumber ( DOE )) - Year ( DOB ) - If ( GetAsNumber ( DOE ) < Date ( Month ( DOB ) ; Day ( DOB ) ; Year ( GetAsNumber ( DOE ) ) ); 1 ; 0 ) & ( Mod ( Month ( GetAsNumber ( DOE ) ) - Month ( DOB ) + 12 - If ( Day ( GetAsNumber ( DOE ) ) < Day ( DOB ) ; 1 ; 0 ) ; 12 ) / 12)
Thank you!

Your Calculation is ok, but you are concatenating the 2 parts rather than adding them. That's why you get a "90" instead of a "9"
Also, if you want it to be "9.0", the calculation result must be numeric; and in layout mode set the format to decimal with a fixed number of decimals.
Round (
Year ( GetAsNumber ( DOE )) - Year ( DOB ) -
If (
GetAsNumber ( DOE ) < Date ( Month ( DOB ) ; Day ( DOB ) ; Year ( GetAsNumber ( DOE )));
1 ;
0)
+
( Mod (
Month ( GetAsNumber ( DOE ) ) - Month ( DOB ) + 12 -
If (
Day ( GetAsNumber ( DOE ) ) < Day ( DOB );
1;
0)
; 12 )
/ 12)
; 2 )

I would suggest a simpler approach:
Let (
elapsedMonths = 12 * ( Year ( DOE ) - Year ( DOB ) ) + Month ( DOE ) - Month ( DOB ) - ( Day ( DOE ) < Day ( DOB ) )
;
Div ( elapsedMonths ; 12 ) + Mod ( elapsedMonths ; 12 ) / 12
)
Note that this counts only fully elapsed months.

sql window function to detect change in column values

I'd like to detect changes in column values in this (example) db
WITH events(id, row,event) AS (
VALUES
(1,1, 0 )
,(1,2, 0 )
,(1,3, 1 )
,(1,4, 0 )
,(1,5, 1 )
,(2,1, 0 )
,(2,2, 1 )
,(3,1, 0 )
,(3,2, 0 )
)
select * from events
What I am looking for is code for a new column 'code' which switches to 1 AFTER
de event column shows a 1. Within the same id the code stays 1.
For this example this new column wil look like this
WITH events2(id, row,event, code) AS (
VALUES
(1,1, 0, 0 )
,(1,2, 0, 0 )
,(1,3, 1, 0 )
,(1,4, 0, 1 ) -- notice the switch here
,(1,5, 1, 1 ) --
,(2,1, 0, 0 )
,(2,2, 1, 0 )
,(3,1, 0, 0 )
,(3,2, 0, 0 )
)
select * from events2
I have a hunch that the answer will be related to the answer on this question : PostgreSQL window function: partition by comparison
Somehow I cannot figure this out myself..
Peter

COALESCE over a scalar subquery:
WITH events(id, zrow, zevent) AS (
VALUES
(1,1, 0 ) ,(1,2, 0 ) ,(1,3, 1 ) ,(1,4, 0 ) ,(1,5, 1 )
,(2,1, 0 ) ,(2,2, 1 )
,(3,1, 0 ) ,(3,2, 0 )
)
SELECT id, zrow, zevent
, COALESCE((SELECT 1 FROM events ex WHERE ex.id = ev.id AND ex.zrow < ev.zrow AND ex.zevent> 0),0) AS oevent
FROM events ev
;
Or, avoid the COALESCE() by typecasting the boolean EXISTS() to INTEGER:
WITH events(id, zrow,event) AS (
VALUES
(1,1, 0 ) ,(1,2, 0 ) ,(1,3, 1 ) ,(1,4, 0 ) ,(1,5, 1 )
,(2,1, 0 ) ,(2,2, 1 )
,(3,1, 0 ) ,(3,2, 0 )
)
SELECT id, zrow, event
, EXISTS(SELECT 1 FROM events ex WHERE ex.id = ev.id AND ex.zrow < ev.zrow AND ex.event> 0)::integer AS oevent
FROM events ev
;
Find the MAX() value over the previous records within the same group (frame):
WITH events(id, zrow,event) AS (
VALUES
(1,1, 0 ) ,(1,2, 0 ) ,(1,3, 1 ) ,(1,4, 0 ) ,(1,5, 1 )
,(2,1, 0 ) ,(2,2, 1 )
,(3,1, 0 ) ,(3,2, 0 )
)
, drag AS (
SELECT id, zrow, event, MAX(event)
OVER (PARTITION BY id
ORDER BY zrow
ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
) AS lagged
FROM events ev
)
SELECT id, zrow, event
, COALESCE(lagged,0) AS oevent
FROM drag dr
;
The same without the extra CTE:
WITH events(id, zrow,event) AS (
VALUES
(1,1, 0 ) ,(1,2, 0 ) ,(1,3, 1 ) ,(1,4, 0 ) ,(1,5, 1 )
,(2,1, 0 ) ,(2,2, 1 )
,(3,1, 0 ) ,(3,2, 0 )
)
SELECT id, zrow, event, COALESCE(MAX(event) OVER (PARTITION BY id
ORDER BY zrow
ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
),0) AS lagged
FROM events ev
;
Another way to perform the self-join would be to use a recursive query.