My Postgres crosstab query reads:
SELECT mthreport.*
FROM crosstab
('SELECT
to_char(ipstimestamp, ''mon DD HH24h'') As row_name,
varid::text || log.varid || ''_'' || ips.objectname::text As bucket,
COUNT(*)::integer As bucketvalue
FROM loggingdb_ips_boolean As log
INNER JOIN IpsObjects As ips
ON log.Varid=ips.ObjectId
GROUP BY to_char(ipstimestamp, ''yyyy MM DD HH24h''), row_name, bucket
ORDER BY to_char(ipstimestamp, ''yyyy MM DD HH24h''), row_name, bucket')
As mthreport(item_name text,
jan3 integer, feb4 integer, mar5 integer)
Is there any way that I can pull the three items enumerated in the last line (jan3 integer etc.) from an ancillary query? I tried to substitute the last line with SELECT xyz FROM zyx, but that doesn't work.
In the basic form of the query, you have to spell out the column names and types in the calling SELECT.
There are the crosstabN(text) variants that use a pre-defined return types.
For full automation you'll have to wrap each individual query into a function where you can predefine the return type. I posted a detailed example here.
Related
how are you?
I needed to store an array of numbers as JSONB in PostgreSQL.
Now I'm trying to calculate stats moments from this JSON, I'm facing some issues.
Sample of my data:
I already was able to convert a JSON into a float array.
I used a function to convert jsonb to float array.
CREATE OR REPLACE FUNCTION jsonb_array_castdouble(jsonb) RETURNS float[] AS $f$
SELECT array_agg(x)::float[] || ARRAY[]::float[] FROM jsonb_array_elements_text($1) t(x);
$f$ LANGUAGE sql IMMUTABLE;
Using this SQL:
with data as (
select
s.id as id,
jsonb_array_castdouble(s.snx_normalized) as serie
FROM
spectra s
)
select * from data;
I found a function that can do these calculations and I need to pass an array for that: https://github.com/ellisonch/PostgreSQL-Stats-Aggregate/
But this function requires an array in another way: unnested
I already tried to use unnest, but it will get only one value, not the entire array :(.
My goal is:
Be able to apply stats moment (kurtosis, skewness) for each row.
like:
index
skewness
1
21.2131
2
1.123
Bonus: There is a way to not use this 'with data', use the transformation in the select statement?
snx_wavelengths is JSON, right? And also you provided it as a picture and not text :( the data looks like (id, snx_wavelengths) - I believe you meant id saying index (not a good idea to use a keyword, would require identifier doublequotes):
1,[1,2,3,4]
2,[373,232,435,84]
If that is right:
select id, (stats_agg(v::float)).skewness
from myMeasures,
lateral json_array_elements_text(snx_wavelengths) v
group by id;
DBFiddle demo
BTW, you don't need "with data" in the original sample if you don't want to use and could replace with a subquery. ie:
select (stats_agg(n)).* from (select unnest(array[16,22,33,24,15])) data(n)
union all
select (stats_agg(n)).* from (select unnest(array[416,622,833,224,215])) data(n);
EDIT: And if you needed other stats too:
select id, "count","min","max","mean","variance","skewness","kurtosis"
from myMeasures,
lateral (select (stats_agg(v::float)).* from json_array_elements_text(snx_wavelengths) v) foo
group by id,"count","min","max","mean","variance","skewness","kurtosis";
DBFiddle demo
Source data
I am working on an ELT project to load data from CSV files into PostgreSQL where I will transform it. The CSV files have many columns that are consistent across files, but also contain activity columns that are inconsistent with names like Date (05/19/2020), Type (05/19/2020), etc.
In the loading script I am merging all of the columns with dates in the column name into one jsonb column so I don't have to constantly add new columns to the raw data table.
The resulting jsonb column in the raw data table looks like this:
id
activity
12345678
{"Date (05/19/2020)": null, "Type (05/19/2020)": null, "Date (06/03/2020)": "06/01/2020", "Type (06/03/2020)": "E"}
98765432
{"Date (05/19/2020)": "05/18/2020", "Type (05/19/2020)": "B", "Date (10/23/2020)": "10/26/2020", "Type (10/23/2020)": "T"}
JSON to columns
Using the amazing create_jsonb_flat_view function from this post I can convert the jsonb to columns like this:
id
Date (05/19/2020)
Type (05/19/2020)
Date (06/03/2020)
Type (06/03/2020)
Type (10/23/2020
Date (10/23/2020)
Type (10/23/2020)
10629465
null
null
06/01/2020
E
98765432
05/18/2020
B
10/26/2020
T
Need to move part of column name to row
Now, this is where I'm stuck. I need to remove the portion of the column name that is the Activity Date (e.g. (05/19/2020)) and create a row for each id and ActivityDate with additional columns for Date and Type like this:
id
ActivityDate
Date
Type
12345678
05/19/2020
null
null
12345678
06/03/2020
06/01/2020
E
98765432
05/19/2020
05/18/2020
B
98765432
10/23/2020
10/26/2020
T
I followed your link to the create_jsonb_flat_view article yesterday and then forgot this question. While I thank you for pointing me there, I think that mentioning it worked against you.
A more conventional approach using regexp_replace() works here. I left the date values as strings, but you can convert them with to_date() if needed:
with parse as (
select id, e.k, e.v,
regexp_replace(e.k, '\s+\([0-9/]{10}\)', '') as k_no_date,
regexp_replace(e.k, '^.+([0-9/]{10}).+', '\1') as k_date_only
from rawinput
cross join lateral jsonb_each_text(activity) as e(k, v)
)
select id,
k_date_only as activity_date,
min(v) filter (where k_no_date = 'Date') as date,
min(v) filter (where k_no_date = 'Type') as type
from parse
group by id, k_date_only;
db<>fiddle here
#Mike-Organek's Answer works beautifully!
However, I was curious if the regexp_replace() calls might be slowing the query down a bit and it seemed I could get the same results using a simpler function.
Since Mike gave me a great example to start with I modified it to split on the space between Date and (05/19/2020).
For 20,000 rows, it went from taking an avg of 7 sec on my local machine to an avg of .9 sec.
Here is the resulting query:
with parse as (
select id, e.k, e.v,
split_part(e.k, ' ', 1) as k_no_date,
trim(split_part(e.k, ' ', 2),'()') as k_date_only
from rawinput
cross join lateral jsonb_each_text(activity) as e(k, v)
)
select id,
k_date_only as activity_date,
min(v) filter (where k_no_date = 'Date') as date,
min(v) filter (where k_no_date = 'Type') as type
from parse
group by id, k_date_only;
I'm using postgresql 11, I have a jsonb which represent a row of that table, it's look like
{"userid":"test","rolename":"Root","loginerror":0,"email":"superadmin#ae.com",...,"thirdpartyauthenticationkey":{}}
is there any method that I could gather all the "values" of the jsonb into a string which is separated by ',' and without the keys?
The string I want to obtain with the jsonb above is like
(test, Root, 0, superadmin#ae.com, ..., {})
I need to keep the ORDER of those values as what their keys were in the jsonb. Could I do that with postgresql?
You can use the jsonb_populate_record function (assuming your json data does match the users table). This will force the text value to match the order of your users table:
Schema (PostgreSQL v13)
CREATE TABLE users (
userid text,
rolename text,
loginerror int,
email text,
thirdpartyauthenticationkey json
)
Query #1
WITH d(js) AS (
VALUES
('{"userid":"test", "rolename":"Root", "loginerror":0, "email":"superadmin#ae.com", "thirdpartyauthenticationkey":{}}'::jsonb),
('{"userid":"other", "rolename":"User", "loginerror":324, "email":"nope#ae.com", "thirdpartyauthenticationkey":{}}'::jsonb)
)
SELECT jsonb_populate_record(null::users, js),
jsonb_populate_record(null::users, js)::text AS record_as_text,
pg_typeof(jsonb_populate_record(null::users, js)::text)
FROM d
;
jsonb_populate_record
record_as_text
pg_typeof
(test,Root,0,superadmin#ae.com,{})
(test,Root,0,superadmin#ae.com,{})
text
(other,User,324,nope#ae.com,{})
(other,User,324,nope#ae.com,{})
text
Note that if you're building this string to insert it back into postgresql then you don't need to do that, since the result of jsonb_populate_record will match your table:
Query #2
WITH d(js) AS (
VALUES
('{"userid":"test", "rolename":"Root", "loginerror":0, "email":"superadmin#ae.com", "thirdpartyauthenticationkey":{}}'::jsonb),
('{"userid":"other", "rolename":"User", "loginerror":324, "email":"nope#ae.com", "thirdpartyauthenticationkey":{}}'::jsonb)
)
INSERT INTO users
SELECT (jsonb_populate_record(null::users, js)).*
FROM d;
There are no results to be displayed.
Query #3
SELECT * FROM users;
userid
rolename
loginerror
email
thirdpartyauthenticationkey
test
Root
0
superadmin#ae.com
[object Object]
other
User
324
nope#ae.com
[object Object]
View on DB Fiddle
You can use jsonb_each_text() to get a set of a text representation of the elements, string_agg() to aggregate them in a comma separated string and concat() to put that in parenthesis.
SELECT concat('(', string_agg(value, ', '), ')')
FROM jsonb_each_text('{"userid":"test","rolename":"Root","loginerror":0,"email":"superadmin#ae.com","thirdpartyauthenticationkey":{}}'::jsonb) jet (key,
value);
db<>fiddle
You didn't provide DDL and DML of a (the) table the JSON may reside in (if it does, that isn't clear from your question). The demonstration above therefore only uses the JSON you showed as a scalar. If you have indeed a table you need to CROSS JOIN LATERAL and GROUP BY some key.
Edit:
If you need to be sure the order is retained and you don't have that defined in a table's structure as #Marth's answer assumes, then you can of course extract every value manually in the order you need them.
SELECT concat('(',
concat_ws(', ',
j->>'userid',
j->>'rolename',
j->>'loginerror',
j->>'email',
j->>'thirdpartyauthenticationkey'),
')')
FROM (VALUES ('{"userid":"test","rolename":"Root","loginerror":0,"email":"superadmin#ae.com","thirdpartyauthenticationkey":{}}'::jsonb)) v (j);
db<>fiddle
My query looks like this:
SELECT mthreport.*
FROM crosstab
('SELECT
to_char(ipstimestamp, ''mon DD HH24h'') As row_name,
varid::text || log.varid || ''_'' || ips.objectname::text As bucket,
COUNT(*)::integer As bucketvalue
FROM loggingdb_ips_boolean As log
INNER JOIN IpsObjects As ips
ON log.Varid=ips.ObjectId
WHERE ((log.varid = 37551)
OR (log.varid = 27087)
OR (log.varid = 50876)
OR (log.varid = 45096)
OR (log.varid = 54708)
OR (log.varid = 47475)
OR (log.varid = 54606)
OR (log.varid = 25528)
OR (log.varid = 54729))
GROUP BY to_char(ipstimestamp, ''yyyy MM DD HH24h''), row_name, objectid, bucket
ORDER BY to_char(ipstimestamp, ''yyyy MM DD HH24h''), row_name, objectid, bucket' )
As mthreport(item_name text, varid_37551 integer,
varid_27087 integer ,
varid_50876 integer ,
varid_45096 integer ,
varid_54708 integer ,
varid_47475 integer ,
varid_54606 integer ,
varid_25528 integer ,
varid_54729 integer ,
varid_29469 integer)
the query can be tested against a test table with this connection string:
"host=bellariastrasse.com port=5432 dbname=IpsLogging user=guest password=guest"
The query is syntactically correct and runs fine. My problem is that it the COUNT(*) values are always filling the leftmost column. however, in many instances the left columns should have a zero, or a NULL, and only the 2nd (or n-th) column should be filled. My brain is melting and I cannot figure out what is wrong!
The solution for your problem is to use the crosstab() variant with two parameters.
The second parameter (another query string) produces the list of output columns, so that NULL values in the data query (the first parameter) are assigned correctly.
Check the manual for the tablefunc extension, and in particular crosstab(text, text):
The main limitation of the single-parameter form of crosstab is that
it treats all values in a group alike, inserting each value into the
first available column. If you want the value columns to correspond to
specific categories of data, and some groups might not have data for
some of the categories, that doesn't work well. The two-parameter form
of crosstab handles this case by providing an explicit list of the
categories corresponding to the output columns.
Emphasis mine. I posted a couple of related answers recently here or here or here.
I am trying to create the following select statement in a stored proc
#dealerids nvarchar(256)
SELECT *
FROM INVOICES as I
WHERE convert(nvarchar(20), I.DealerID) in (#dealerids)
I.DealerID is an INT in the table. and the Parameter for dealerids would be formatted such as
(8820, 8891, 8834)
When I run this with parameters provided I get no rows back. I know these dealerIDs should provided rows as if I do it individually I get back what I expect.
I think I am doing
WHERE convert(nvarchar(20), I.DealerID) in (#dealerids)
incorrectly. Can anyone point out what I am doing wrong here?
Use a table values parameter (new in SQl Server 2008). Set it up by creating the actual table parameter type:
CREATE TYPE IntTableType AS TABLE (ID INTEGER PRIMARY KEY)
Your procedure would then be:
Create Procedure up_TEST
#Ids IntTableType READONLY
AS
SELECT *
FROM ATable a
WHERE a.Id IN (SELECT ID FROM #Ids)
RETURN 0
GO
if you can't use table value parameters, see: "Arrays and Lists in SQL Server 2005 and Beyond, When Table Value Parameters Do Not Cut it" by Erland Sommarskog, then there are many ways to split string in SQL Server. This article covers the PROs and CONs of just about every method. in general, you need to create a split function. This is how a split function can be used:
SELECT
*
FROM YourTable y
INNER JOIN dbo.yourSplitFunction(#Parameter) s ON y.ID=s.Value
I prefer the number table approach to split a string in TSQL but there are numerous ways to split strings in SQL Server, see the previous link, which explains the PROs and CONs of each.
For the Numbers Table method to work, you need to do this one time table setup, which will create a table Numbers that contains rows from 1 to 10,000:
SELECT TOP 10000 IDENTITY(int,1,1) AS Number
INTO Numbers
FROM sys.objects s1
CROSS JOIN sys.objects s2
ALTER TABLE Numbers ADD CONSTRAINT PK_Numbers PRIMARY KEY CLUSTERED (Number)
Once the Numbers table is set up, create this split function:
CREATE FUNCTION [dbo].[FN_ListToTable]
(
#SplitOn char(1) --REQUIRED, the character to split the #List string on
,#List varchar(8000)--REQUIRED, the list to split apart
)
RETURNS TABLE
AS
RETURN
(
----------------
--SINGLE QUERY-- --this will not return empty rows
----------------
SELECT
ListValue
FROM (SELECT
LTRIM(RTRIM(SUBSTRING(List2, number+1, CHARINDEX(#SplitOn, List2, number+1)-number - 1))) AS ListValue
FROM (
SELECT #SplitOn + #List + #SplitOn AS List2
) AS dt
INNER JOIN Numbers n ON n.Number < LEN(dt.List2)
WHERE SUBSTRING(List2, number, 1) = #SplitOn
) dt2
WHERE ListValue IS NOT NULL AND ListValue!=''
);
GO
You can now easily split a CSV string into a table and join on it:
Create Procedure up_TEST
#Ids VARCHAR(MAX)
AS
SELECT * FROM ATable a
WHERE a.Id IN (SELECT ListValue FROM dbo.FN_ListToTable(',',#Ids))
You can't use #dealerids like that, you need to use dynamic SQL, like this:
#dealerids nvarchar(256)
EXEC('SELECT *
FROM INVOICES as I
WHERE convert(nvarchar(20), I.DealerID) in (' + #dealerids + ')'
The downside is that you open yourself up to SQL injection attacks unless you specifically control the data going into #dealerids.
There are better ways to handle this depending on your version of SQL Server, which are documented in this great article.
Split #dealerids into a table then JOIN
SELECT *
FROM INVOICES as I
JOIN
ufnSplit(#dealerids) S ON I.DealerID = S.ParsedIntDealerID
Assorted split functions here (I'd probably a numbers table in this case for a small string