Postgresql how to return select as array - sql

IN POSTGRESQL:
Say I have a table of Users and I do:
SELECT "EyeColor" FROM "Users" WHERE "Age" = 32
And this returns:
[
{"EyeColor": "blue"},
{"EyeColor": "green"},
{"EyeColor": "blue"}
]
Then I want to put blue, green, blue into an array and use that. This is the closest I can get but it is not working:
SELECT * FROM "Eyes" WHERE "Color" IN
(SELECT array_agg("EyeColor") FROM "Users" WHERE "Age" = 32)
I want the anpve query to work the same as this:
SELECT * FROM "Eyes" WHERE "Color" IN ('blue', 'green')

You do not need to aggregate the subquery result into an array. You can use IN (subquery):
SELECT *
FROM "Eyes"
WHERE "Color" IN (
SELECT "Eyes"
FROM "Users"
WHERE "Age" = 32)
or ANY (subquery):
SELECT *
FROM "Eyes"
WHERE "Color" = ANY(
SELECT "Eyes"
FROM "Users"
WHERE "Age" = 32)

Related

Combine conditions in table expression?

I am using the line_index function and would like to search for two values, not only for carrid but also for connid. Is it possible? If so, in what way?
Because right now, this works:
lv_index = line_index( lt[ carrid = 'LH' ] ).
But after adding the code [ connid = '2407' ] like this:
lv_index = line_index( lt[ carrid = 'LH' ][ connid = '2407' ] ).
I get a syntax error:
LT[ ] is not an internal table
All fields (conditions) just one after the other inside one bracket:
lv_index = line_index( lt[ carrid = 'LH'
connid = '2407' ] ).
I'd like to comment about the chaining of Table Expressions.
So the answer corresponding to the OP example is that a single Table Expression must be used (itab[...]) with as many components as needed, and not a chain of table expressions as was done (itab[...][...]).
lt[ carrid = 'LH' ][ connid = '2407' ] can never be valid (because connid = '2407' would imply that each line of LT is itself an internal table but carrid = 'LH' is contradictory as it means that each line of LT is a structure).
But other syntaxes of chained table expressions can be valid, like e.g. (provided that the internal tables are defined adequately)
itab[ 1 ][ comp1 = 'A' ]
itab[ comp1 = 'A' ][ 1 ]
itab[ comp1 = 'A' ]-itabx[ compx = 42 ]
Here is an example that you can play with:
TYPES: BEGIN OF ty_structure,
connid TYPE c LENGTH 4,
END OF ty_structure,
ty_table TYPE STANDARD TABLE OF ty_structure WITH EMPTY KEY,
BEGIN OF ty_structure_2,
carrid TYPE c LENGTH 2,
table TYPE ty_table,
END OF ty_structure_2,
ty_table_2 TYPE STANDARD TABLE OF ty_structure_2 WITH EMPTY KEY,
ty_table_3 TYPE STANDARD TABLE OF ty_table_2 WITH EMPTY KEY.
DATA(lt) = VALUE ty_table_3( ( VALUE #( ( carrid = 'LH' table = VALUE #( ( connid = '2407' ) ) ) ) ) ).
DATA(structure) = lt[ 1 ][ carrid = 'LH' ]-table[ connid = '2407' ].

Create subquery using peewee, using `.select` on the subquery results

I have a rather complex peewee query that looks like that:
SolutionAlias = Solution.alias()
fields = [
SolutionAlias.id.alias('solution_id'),
SolutionAlias.solver.id.alias('solver_id'),
SolutionAlias.exercise.id.alias('exercise_id'),
]
query = (
User
.select(*fields)
.join(Exercise, JOIN.CROSS)
.join(Course, JOIN.LEFT_OUTER, on=(Exercise.course == Course.id))
.join(SolutionAlias, JOIN.LEFT_OUTER, on=(
(SolutionAlias.exercise == Exercise.id)
& (SolutionAlias.solver == User.id)
))
.where(
(Exercise.id << self.get_exercise_ids()),
(User.id << self.get_user_ids()),
)
.group_by(Exercise.id, User.id, SolutionAlias.id)
.having(
(SolutionAlias.id == fn.MAX(SolutionAlias.id))
| (SolutionAlias.id.is_null(True))
)
.alias('solutions_subquery')
)
full_query_fields = [
query.c.solver_id,
query.c.exercise_id,
Solution.id.alias('solution_id'),
SolutionAssessment.icon.alias('assessment_icon'),
]
solutions = (
Solution
.select(*full_query_fields)
.join(query, JOIN.RIGHT_OUTER, on=(
Solution.id == query.c.solution_id
))
.join(SolutionAssessment, JOIN.LEFT_OUTER, on=(
(Solution.assessment == SolutionAssessment.id)
))
)
This one actually works, generating the following SQL query:
SELECT
"solutions_subquery"."solver_id",
"solutions_subquery"."exercise_id",
"t1"."id" AS "solution_id",
"t2"."icon" AS "assessment_icon"
FROM
"solution" AS "t1"
RIGHT OUTER JOIN (
SELECT
"t3"."id" AS "solution_id",
"t4"."id" AS "solver_id",
"t5"."id" AS "exercise_id"
FROM
"user" AS "t4" CROSS
JOIN "exercise" AS "t5"
LEFT OUTER JOIN "course" AS "t6" ON ("t5"."course_id" = "t6"."id")
LEFT OUTER JOIN "solution" AS "t3" ON (
("t3"."exercise_id" = "t5"."id")
AND ("t3"."solver_id" = "t4"."id")
)
WHERE
(
(
"t5"."id" IN (155, 156, 157)
)
AND (
"t4"."id" IN (1, 24, 25, 26, 27, 28)
)
)
GROUP BY
"t5"."id",
"t4"."id",
"t3"."id"
HAVING
(
(
"t3"."id" = MAX("t3"."id")
)
OR ("t3"."id" IS NULL)
)
) AS "solutions_subquery" ON (
"t1"."id" = "solutions_subquery"."solution_id"
)
LEFT OUTER JOIN "solutionassessment" AS "t2" ON ("t1"."assessment_id" = "t2"."id")
But I don't really want to use RIGHT_JOIN as it isn't supported by SQLite.
When trying to query using the subquery query and JOINing the Solution table into the subquery's result, I get an error from peewee.
The new query:
solutions = (
query
.select(*full_query_fields)
.join(Solution, JOIN.LEFT_OUTER, on=(
Solution.id == query.c.solution_id
))
.join(SolutionAssessment, JOIN.LEFT_OUTER, on=(
(Solution.assessment == SolutionAssessment.id)
))
)
The generated query:
SELECT
"solutions_subquery"."solver_id",
"solutions_subquery"."exercise_id",
"t1"."id" AS "solution_id",
"t1"."checker_id",
"t1"."state",
"t1"."submission_timestamp",
"t2"."name" AS "assessment",
"t2"."icon" AS "assessment_icon"
FROM
"user" AS "t3" CROSS
JOIN "exercise" AS "t4"
LEFT OUTER JOIN "course" AS "t5" ON ("t4"."course_id" = "t5"."id")
LEFT OUTER JOIN "solution" AS "t6" ON (
("t6"."exercise_id" = "t4"."id")
AND ("t6"."solver_id" = "t3"."id")
)
LEFT OUTER JOIN "solution" AS "t1" ON (
"t1"."id" = "solutions_subquery"."solution_id"
)
LEFT OUTER JOIN "solutionassessment" AS "t2" ON ("t1"."assessment_id" = "t2"."id")
WHERE
(
(
"t4"."id" IN (155, 156, 157)
)
AND (
"t3"."id" IN (1, 24, 25, 26, 27, 28)
)
)
GROUP BY
"t4"."id",
"t3"."id",
"t6"."id"
HAVING
(
(
"t6"."id" = MAX("t6"."id")
)
OR ("t6"."id" IS NULL)
)
Which results in:
psycopg2.errors.UndefinedTable: missing FROM-clause entry for table "solutions_subquery"
LINE 1: ...EFT OUTER JOIN "solution" AS "t1" ON ("t1"."id" = "solutions...
During handling of the above exception, another exception occurred:
[Truncated for readability...]
loguru.logger.critical(str(list(solutions.dicts().execute())))
[Truncated for readability...]
peewee.ProgrammingError: missing FROM-clause entry for table "solutions_subquery"
LINE 1: ...EFT OUTER JOIN "solution" AS "t1" ON ("t1"."id" = "solutions...
Why does peewee flatten the query? Is there another way to use LEFT_JOIN?
Eventually found the Select function in the documentation, which allows me to kind of wrap the previous query:
solutions = (
Select(columns=full_query_fields)
.from_(query)
.join(Solution, JOIN.LEFT_OUTER, on=(
Solution.id == query.c.solution_id
))
.join(SolutionAssessment, JOIN.LEFT_OUTER, on=(
(Solution.assessment == SolutionAssessment.id)
))
)
This solution works.

Collapse elements of array of structs in BigQuery

I have an array of structs in BigQuery that looks like:
"categories": [
{
"value": "A",
"question": "Q1",
},
{
"value": "B",
"question": "Q2",
},
{
"value": "C",
"question": "Q3",
}
]
I'd like to collapse the values "A", "B" and "C" into a separate column, and the value for this particular row should be something like "A - B - C".
How can I do this with a query in BigQuery?
Consider below
select id,
( select string_agg(value, ' - ')
from t.questions_struct) values
from questions t
if applied to sample data in your question/answer -
with questions as (
SELECT 1 AS id,
[
STRUCT("A" as value, "Q1" as question),
STRUCT("B" as value, "Q2" as question),
STRUCT("C" as value, "Q3" as question)
] AS questions_struct
)
output is
Assuming this is an array of structs, you can use:
select (select q.value from unnest(ar) q where q.question = 'q1') as q1,
(select q.value from unnest(ar) q where q.question = 'q2') as q2,
(select q.value from unnest(ar) q where q.question = 'q3') as q3
from t;
I think it can be done with the following code:
with questions as (
SELECT 1 AS id,
[
STRUCT("A" as value, "Q1" as question),
STRUCT("B" as value, "Q2" as question),
STRUCT("C" as value, "Q3" as question)
] AS questions_struct
), unnested as (
select * from questions, unnest(questions_struct) as questions_struct
) select id, string_agg(value, ' - ') from unnested group by 1

python- how to join two seperate queries based on common value

I have two queries which links to different databases
query = "select name ,ctry from xxxx where xxxx"
cursor.execute(query)
results1 = list(cursor.fetchall())
for row in results1:
query1 = "SELECT sessionname, country FROM xxx where and sessions.sessionname = '"+row[0] +"'"
cur.execute(query1)
results2.append(cur.fetchall())
How to connect them if they have common value(sessionname and name) and save it's output to file. Both queries are located in different dbo (oracle, postgresql)
My code is here :
try:
query = """select smat.s_name "SQLITE name" ,smed.m_ctry as "Country", smed.m_name "HDD Label" from smart.smed2smat ss, smart.smed smed, smart.smat smat where ss.M2S_SMAT=smat.s_id and ss.m2s_smed=smed.m_id and smed.m_name like '{0}%' order by smat.s_name""" .format(line_name)
cursor.execute(query)
columns = [i[0] for i in cursor.description]
results1 = cursor.fetchall()
for row in results1:
query1 = "SELECT sessions.sessionname, projects.country , projects.projectname FROM momatracks.sessions, momatracks.projects, momatracks.sessionsgeo where sessions.projectid = projects.id and sessionsgeo.sessionname = sessions.sessionname and sessions.sessionname = '"+row[0] +"' order by sessions.sessionname"
cur.execute(query1)
results2 =cur.fetchall()
print "results1 -----> \n:", row
tmp=[]
output_items = []
for tmp in results2:
print "---> \n", tmp
try:
stations_dict = dict([(item[0], item[1:]) for item in tmp])
for item in row:
output_item = list(item) + stations_dict.get(item[0], [])
output_items.append(output_item)
except Exception, f:
print str (f)
cursor.close()
cur.close()
except Exception, g:
print str ( g )
except Exception, e:
print str ( e )
My results from row and tmp are :
row - WE246JP_2015_10_11__14_53_33', 'NLD', '031_025_SQLITE_NLD1510_03INDIA
and
tmp - WE246JP_2015_10_11__14_53_33', 'NLD', 'NLD15_N2C1-4_NL'
How to properly connect them? I want output look like this :
output_items - WE246JP_2015_10_11__14_53_33', 'NLD', '031_025_SQLITE_NLD1510_03INDIA', 'NLD15_N2C1-4_NL'
At the moment i get this error :
can only concatenate list (not "str") to list
Also value station_dict looks like this :( And this is not what i intended to do
'W': 'E246JP_2015_10_11__15_23_33', 'N': 'LD15_N2C1-4_NL3'
I know there is something wrong with my code which is simmilar to join. Can anyone explain this to me ? I used method below :
http://forums.devshed.com/python-programming-11/join-arrays-based-common-value-sql-left-join-943177.html
If the sessions are exactly the same in both databases then just zip the results:
query = """
select
smat.s_name "SQLITE name",
smed.m_ctry as "Country",
smed.m_name "HDD Label"
from
smart.smed2smat ss
inner join
smart.smed smed on ss.M2S_SMAT = smat.s_id
inner join
smart.smat smat on ss.m2s_smed = smed.m_id
where smed.m_name like '{0}%'
order by smat.s_name
""".format(line_name)
cursor.execute(query)
results1 = cursor.fetchall()
query1 = """
select
sessions.sessionname,
projects.country,
projects.projectname
from
momatracks.sessions,
inner join
momatracks.projects on sessions.projectid = projects.id
inner join
momatracks.sessionsgeo on sessionsgeo.sessionname = sessions.sessionname
where sessions.sessionname in {}
order by sessions.sessionname
""".format(tuple([row[0] for row in results1]))
cur.execute(query1)
results2 = cur.fetchall()
zipped = zip(results1, results2)
output_list = [(m[0][0], m[0][1], m[0][2], m[1][2]) for m in zipped]
If the sessions are different then make each result a dictionary to join.
I think you can use a subquery here. There's no way for me to test it, but I think it should look like this:
SELECT *
FROM (SELECT smat.s_name "SQLITE name" ,
smed.m_ctry as "Country",
smed.m_name "HDD Label"
FROM smart.smed2smat ss,
smart.smed smed,
smart.smat smat
WHERE ss.M2S_SMAT=smat.s_id
AND ss.m2s_smed=smed.m_id
AND smed.m_name like '{0}%'
ORDER BY smat.s_name) t1,
(SELECT sessions.sessionname,
projects.country ,
projects.projectname
FROM momatracks.sessions,
momatracks.projects,
momatracks.sessionsgeo
WHERE sessions.projectid = projects.id
AND sessionsgeo.sessionname = sessions.sessionname
AND sessions.sessionname = '"+row[0] +"'
ORDER BY sessions.sessionname) t2
WHERE t1."SQLITE name" = t2.sessionname ;

multiple aggregates and subquery in slick 3.1

I am trying to translate this sql into a slick 3.1 style collection query (single call). This sql (postgres) returns what I am looking for:
select
minDate.min as lastModified,
(select count("id") from "Items" where "orderId" = 1) as totalItemCount,
(select count("id") from "Items" where "orderId" = 1 and "dateModified" >= minDate.min) as addedCount
from
(select min("dateModified") as "min" from "Items" where "orderId" = 1 and "state" = 'new') as minDate
Returns: for a specified set of Items (from orderId), returns:
date of item last modified
total number of items
number of items added since the lastModified
But after many attempts, I can't figure out how to translate this to a single slick-style query
This codes
import scala.slick.driver.PostgresDriver
case class Item(id: Int, orderId: Int, state: String, dateModified: Int)
object SlickComplexQuery {
def main(args: Array[String]) = {
val driver = PostgresDriver
import driver.simple._
class ItemsTable(tag: Tag) extends Table[Item](tag, "Items"){
def id = column[Int]("id")
def orderId = column[Int]("orderId")
def state = column[String]("state")
def dateModified = column[Int]("dateModified")
def * = (id, orderId, state, dateModified) <> (Item.tupled, Item.unapply)
}
val items = TableQuery[ItemsTable]
val query1 = items
.filter(i => i.orderId === 1 && i.state === "new")
.map(_.dateModified)
.min
val query2 = items
.filter(_.orderId === 1)
.map(_.id)
.length
val query3 = items
.filter(i => i.orderId === 1 && i.dateModified >= query1)
.map(_.id)
.length
val query = Query(query1, query2, query3)
results in such query:
select x2.x3, x4.x5, x6.x7
from (select min(x8.x9) as x3
from (select x10."dateModified" as x9
from "Items" x10
where (x10."orderId" = 1) and (x10."state" = 'new')) x8) x2,
(select count(1) as x5
from (select x11."id" as x12
from "Items" x11
where x11."orderId" = 1) x13) x4,
(select count(1) as x7
from (select x14."id" as x15
from "Items" x14, (select min(x16.x17) as x18
from (select x19."dateModified" as x17
from "Items" x19
where (x19."orderId" = 1) and (x19."state" = 'new')) x16) x20
where (x14."orderId" = 1) and (x14."dateModified" >= x20.x18)) x21) x6
This query is much alike yours, slick 2.0 was used.