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Count number of episodes that has a hash



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30 pm US/Eastern)
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1















I would like some help with a sql query, i'm using SQLAlchemy but I don't even understand how i can express the query in raw sql.



Im phashing every frames of all videos in a season and adding them to the db.
My goal is to find intros the videos checking for the same reaccuring frames in the videos.



My table looks like:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42
---+------+-----+------+-------+-------
|2 |1337 |a1a1a|1 |1 |68
---+------+-----+------+-------+-------
|3 |1337 |a1a1b|1 |2 |92
---+------+-----+------+-------+-------
|4 |1337 |a1a1a|1 |2 |116
---+------+-----+------+-------+-------
|5 |1337 |a1a1a|1 |3 |42
---+------+-----+------+-------+-------
|6 |1337 |a1a1a|1 |3 |42


The result im looking for a is a list of rows where the hash matches in n number of episodes(it can only match on episode at the time) and has the same tvdbid and season number.



At the moment i'm doing:



import sqlalchemy as sa 
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class Hashes(Base):
__tablename__ = 'hashes'

id = sa.Column(sa.Integer, primary_key=True)
season = sa.Column(sa.Integer)
episode = sa.Column(sa.Integer)
tvdbid = sa.Column(sa.Text(length=100))
hash = sa.Column(sa.Text(length=16))
offset = sa.Column(sa.Integer)

h = Hashes.__table__

async def some_web_request(request):

# I need to use raw sql or core as the db library requires it.
# my cli tool uses a sync method to insert the rows in the db.
query = h.select().where(sa.and_(h.c.tvdbid ==
request.path_params['tvdbid'],
h.c.season == request.path_params['season'])).group_by('hash', 'episode')
result = await DB.fetch_all(query)
return result


This seems to work just fine, but it isn't exactly what I want so I have to clean up up with python and it will not be viable in the long run. The table will have have between 5 - 500 million rows.



My current "work around":



from collections import defaultdict

def clean_up(result):
d = defaultdict(set)
for row in result:
d[row.hash].add(row.episode)

final_result = []
for k, v in d.items():
if (l) > 4: # 4 is the number of episodes.
final_result.append(k)

return final_result



The desired output should have been:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42



as the hash needs to present in atleast 50% of the episodes.
or it could simply be a1a1a i dont really need to entire rows now. (this will needed laster to check for recaps etc.)










share|improve this question
























  • I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

    – reportgunner
    Mar 22 at 15:00











  • could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

    – Haleemur Ali
    Mar 22 at 15:12











  • I have updated what im trying to do, with more sample data and the desired output. Thanks!

    – steffen fredriksen
    Mar 22 at 15:36

















1















I would like some help with a sql query, i'm using SQLAlchemy but I don't even understand how i can express the query in raw sql.



Im phashing every frames of all videos in a season and adding them to the db.
My goal is to find intros the videos checking for the same reaccuring frames in the videos.



My table looks like:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42
---+------+-----+------+-------+-------
|2 |1337 |a1a1a|1 |1 |68
---+------+-----+------+-------+-------
|3 |1337 |a1a1b|1 |2 |92
---+------+-----+------+-------+-------
|4 |1337 |a1a1a|1 |2 |116
---+------+-----+------+-------+-------
|5 |1337 |a1a1a|1 |3 |42
---+------+-----+------+-------+-------
|6 |1337 |a1a1a|1 |3 |42


The result im looking for a is a list of rows where the hash matches in n number of episodes(it can only match on episode at the time) and has the same tvdbid and season number.



At the moment i'm doing:



import sqlalchemy as sa 
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class Hashes(Base):
__tablename__ = 'hashes'

id = sa.Column(sa.Integer, primary_key=True)
season = sa.Column(sa.Integer)
episode = sa.Column(sa.Integer)
tvdbid = sa.Column(sa.Text(length=100))
hash = sa.Column(sa.Text(length=16))
offset = sa.Column(sa.Integer)

h = Hashes.__table__

async def some_web_request(request):

# I need to use raw sql or core as the db library requires it.
# my cli tool uses a sync method to insert the rows in the db.
query = h.select().where(sa.and_(h.c.tvdbid ==
request.path_params['tvdbid'],
h.c.season == request.path_params['season'])).group_by('hash', 'episode')
result = await DB.fetch_all(query)
return result


This seems to work just fine, but it isn't exactly what I want so I have to clean up up with python and it will not be viable in the long run. The table will have have between 5 - 500 million rows.



My current "work around":



from collections import defaultdict

def clean_up(result):
d = defaultdict(set)
for row in result:
d[row.hash].add(row.episode)

final_result = []
for k, v in d.items():
if (l) > 4: # 4 is the number of episodes.
final_result.append(k)

return final_result



The desired output should have been:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42



as the hash needs to present in atleast 50% of the episodes.
or it could simply be a1a1a i dont really need to entire rows now. (this will needed laster to check for recaps etc.)










share|improve this question
























  • I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

    – reportgunner
    Mar 22 at 15:00











  • could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

    – Haleemur Ali
    Mar 22 at 15:12











  • I have updated what im trying to do, with more sample data and the desired output. Thanks!

    – steffen fredriksen
    Mar 22 at 15:36













1












1








1


1






I would like some help with a sql query, i'm using SQLAlchemy but I don't even understand how i can express the query in raw sql.



Im phashing every frames of all videos in a season and adding them to the db.
My goal is to find intros the videos checking for the same reaccuring frames in the videos.



My table looks like:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42
---+------+-----+------+-------+-------
|2 |1337 |a1a1a|1 |1 |68
---+------+-----+------+-------+-------
|3 |1337 |a1a1b|1 |2 |92
---+------+-----+------+-------+-------
|4 |1337 |a1a1a|1 |2 |116
---+------+-----+------+-------+-------
|5 |1337 |a1a1a|1 |3 |42
---+------+-----+------+-------+-------
|6 |1337 |a1a1a|1 |3 |42


The result im looking for a is a list of rows where the hash matches in n number of episodes(it can only match on episode at the time) and has the same tvdbid and season number.



At the moment i'm doing:



import sqlalchemy as sa 
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class Hashes(Base):
__tablename__ = 'hashes'

id = sa.Column(sa.Integer, primary_key=True)
season = sa.Column(sa.Integer)
episode = sa.Column(sa.Integer)
tvdbid = sa.Column(sa.Text(length=100))
hash = sa.Column(sa.Text(length=16))
offset = sa.Column(sa.Integer)

h = Hashes.__table__

async def some_web_request(request):

# I need to use raw sql or core as the db library requires it.
# my cli tool uses a sync method to insert the rows in the db.
query = h.select().where(sa.and_(h.c.tvdbid ==
request.path_params['tvdbid'],
h.c.season == request.path_params['season'])).group_by('hash', 'episode')
result = await DB.fetch_all(query)
return result


This seems to work just fine, but it isn't exactly what I want so I have to clean up up with python and it will not be viable in the long run. The table will have have between 5 - 500 million rows.



My current "work around":



from collections import defaultdict

def clean_up(result):
d = defaultdict(set)
for row in result:
d[row.hash].add(row.episode)

final_result = []
for k, v in d.items():
if (l) > 4: # 4 is the number of episodes.
final_result.append(k)

return final_result



The desired output should have been:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42



as the hash needs to present in atleast 50% of the episodes.
or it could simply be a1a1a i dont really need to entire rows now. (this will needed laster to check for recaps etc.)










share|improve this question
















I would like some help with a sql query, i'm using SQLAlchemy but I don't even understand how i can express the query in raw sql.



Im phashing every frames of all videos in a season and adding them to the db.
My goal is to find intros the videos checking for the same reaccuring frames in the videos.



My table looks like:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42
---+------+-----+------+-------+-------
|2 |1337 |a1a1a|1 |1 |68
---+------+-----+------+-------+-------
|3 |1337 |a1a1b|1 |2 |92
---+------+-----+------+-------+-------
|4 |1337 |a1a1a|1 |2 |116
---+------+-----+------+-------+-------
|5 |1337 |a1a1a|1 |3 |42
---+------+-----+------+-------+-------
|6 |1337 |a1a1a|1 |3 |42


The result im looking for a is a list of rows where the hash matches in n number of episodes(it can only match on episode at the time) and has the same tvdbid and season number.



At the moment i'm doing:



import sqlalchemy as sa 
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class Hashes(Base):
__tablename__ = 'hashes'

id = sa.Column(sa.Integer, primary_key=True)
season = sa.Column(sa.Integer)
episode = sa.Column(sa.Integer)
tvdbid = sa.Column(sa.Text(length=100))
hash = sa.Column(sa.Text(length=16))
offset = sa.Column(sa.Integer)

h = Hashes.__table__

async def some_web_request(request):

# I need to use raw sql or core as the db library requires it.
# my cli tool uses a sync method to insert the rows in the db.
query = h.select().where(sa.and_(h.c.tvdbid ==
request.path_params['tvdbid'],
h.c.season == request.path_params['season'])).group_by('hash', 'episode')
result = await DB.fetch_all(query)
return result


This seems to work just fine, but it isn't exactly what I want so I have to clean up up with python and it will not be viable in the long run. The table will have have between 5 - 500 million rows.



My current "work around":



from collections import defaultdict

def clean_up(result):
d = defaultdict(set)
for row in result:
d[row.hash].add(row.episode)

final_result = []
for k, v in d.items():
if (l) > 4: # 4 is the number of episodes.
final_result.append(k)

return final_result



The desired output should have been:



|id|tvdbid|hash |season|episode|offset
---+------+-----+------+-------+------
|1 |1337 |a1a1a|1 |1 |42



as the hash needs to present in atleast 50% of the episodes.
or it could simply be a1a1a i dont really need to entire rows now. (this will needed laster to check for recaps etc.)







python sqlalchemy






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Mar 22 at 15:35







steffen fredriksen

















asked Mar 22 at 14:58









steffen fredriksensteffen fredriksen

62




62












  • I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

    – reportgunner
    Mar 22 at 15:00











  • could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

    – Haleemur Ali
    Mar 22 at 15:12











  • I have updated what im trying to do, with more sample data and the desired output. Thanks!

    – steffen fredriksen
    Mar 22 at 15:36

















  • I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

    – reportgunner
    Mar 22 at 15:00











  • could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

    – Haleemur Ali
    Mar 22 at 15:12











  • I have updated what im trying to do, with more sample data and the desired output. Thanks!

    – steffen fredriksen
    Mar 22 at 15:36
















I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

– reportgunner
Mar 22 at 15:00





I'm sorry if I didn't understand your data well, but wouldn't it be enough to just SELECT DISTINCT ? Or rather make a SELECT DISTINCT out of your SELECT results ?

– reportgunner
Mar 22 at 15:00













could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

– Haleemur Ali
Mar 22 at 15:12





could you please update the question by adding some more rows of sample data & the desired result. That would help in understanding the problem better

– Haleemur Ali
Mar 22 at 15:12













I have updated what im trying to do, with more sample data and the desired output. Thanks!

– steffen fredriksen
Mar 22 at 15:36





I have updated what im trying to do, with more sample data and the desired output. Thanks!

– steffen fredriksen
Mar 22 at 15:36












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