PostgreSQL query and data caching












1















I have this SQL query:



SELECT p.timestamp,
COUNT(*) as total,
date_part('hour', p.timestamp) as hour
FROM parties as p
WHERE p.timestamp >= TIMESTAMP 'today' AND p.timestamp < TIMESTAMP 'tomorrow'
AND p.member_id = 1
GROUP BY p.timestamp, hour;


which will grouped how many people by hour:



+-------------------------+-------+------+
| Timestamp | Total | Hour |
+-------------------------+-------+------+
| 2018-11-21 12:00:00+07 | 10 | 12 |
| 2018-11-21 13:00:00+07 | 2 | 13 |
| 2018-11-21 14:00:00+07 | 2 | 14 |
| 2018-11-21 16:00:00+07 | 1 | 16 |
| 2018-11-21 17:00:00+07 | 21 | 17 |
| 2018-11-21 19:00:00+07 | 18 | 19 |
| 2018-11-21 20:00:00+07 | 8 | 20 |
| 2018-11-21 21:00:00+07 | 1 | 21 |
+-------------------------+-------+------+


My question is, if I refetch some API end point that will query above statement, would it be the data in the past hour cached automatically? because in my case, if there is a new data, it will update the last hour's row only.



If not how to cache it? Thanks in advance










share|improve this question

























  • Why are you concerned about caching? How long does it take the query to run?

    – Gordon Linoff
    Nov 21 '18 at 12:02











  • @GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

    – Kris MP
    Nov 21 '18 at 12:04






  • 1





    What if new data is inserted into the table? what if the value of todaychanges overnight?

    – wildplasser
    Nov 21 '18 at 12:05






  • 1





    2.752 ms is really, really fast.

    – Gordon Linoff
    Nov 21 '18 at 12:42






  • 3





    PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

    – JustMe
    Nov 21 '18 at 12:44


















1















I have this SQL query:



SELECT p.timestamp,
COUNT(*) as total,
date_part('hour', p.timestamp) as hour
FROM parties as p
WHERE p.timestamp >= TIMESTAMP 'today' AND p.timestamp < TIMESTAMP 'tomorrow'
AND p.member_id = 1
GROUP BY p.timestamp, hour;


which will grouped how many people by hour:



+-------------------------+-------+------+
| Timestamp | Total | Hour |
+-------------------------+-------+------+
| 2018-11-21 12:00:00+07 | 10 | 12 |
| 2018-11-21 13:00:00+07 | 2 | 13 |
| 2018-11-21 14:00:00+07 | 2 | 14 |
| 2018-11-21 16:00:00+07 | 1 | 16 |
| 2018-11-21 17:00:00+07 | 21 | 17 |
| 2018-11-21 19:00:00+07 | 18 | 19 |
| 2018-11-21 20:00:00+07 | 8 | 20 |
| 2018-11-21 21:00:00+07 | 1 | 21 |
+-------------------------+-------+------+


My question is, if I refetch some API end point that will query above statement, would it be the data in the past hour cached automatically? because in my case, if there is a new data, it will update the last hour's row only.



If not how to cache it? Thanks in advance










share|improve this question

























  • Why are you concerned about caching? How long does it take the query to run?

    – Gordon Linoff
    Nov 21 '18 at 12:02











  • @GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

    – Kris MP
    Nov 21 '18 at 12:04






  • 1





    What if new data is inserted into the table? what if the value of todaychanges overnight?

    – wildplasser
    Nov 21 '18 at 12:05






  • 1





    2.752 ms is really, really fast.

    – Gordon Linoff
    Nov 21 '18 at 12:42






  • 3





    PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

    – JustMe
    Nov 21 '18 at 12:44
















1












1








1


2






I have this SQL query:



SELECT p.timestamp,
COUNT(*) as total,
date_part('hour', p.timestamp) as hour
FROM parties as p
WHERE p.timestamp >= TIMESTAMP 'today' AND p.timestamp < TIMESTAMP 'tomorrow'
AND p.member_id = 1
GROUP BY p.timestamp, hour;


which will grouped how many people by hour:



+-------------------------+-------+------+
| Timestamp | Total | Hour |
+-------------------------+-------+------+
| 2018-11-21 12:00:00+07 | 10 | 12 |
| 2018-11-21 13:00:00+07 | 2 | 13 |
| 2018-11-21 14:00:00+07 | 2 | 14 |
| 2018-11-21 16:00:00+07 | 1 | 16 |
| 2018-11-21 17:00:00+07 | 21 | 17 |
| 2018-11-21 19:00:00+07 | 18 | 19 |
| 2018-11-21 20:00:00+07 | 8 | 20 |
| 2018-11-21 21:00:00+07 | 1 | 21 |
+-------------------------+-------+------+


My question is, if I refetch some API end point that will query above statement, would it be the data in the past hour cached automatically? because in my case, if there is a new data, it will update the last hour's row only.



If not how to cache it? Thanks in advance










share|improve this question
















I have this SQL query:



SELECT p.timestamp,
COUNT(*) as total,
date_part('hour', p.timestamp) as hour
FROM parties as p
WHERE p.timestamp >= TIMESTAMP 'today' AND p.timestamp < TIMESTAMP 'tomorrow'
AND p.member_id = 1
GROUP BY p.timestamp, hour;


which will grouped how many people by hour:



+-------------------------+-------+------+
| Timestamp | Total | Hour |
+-------------------------+-------+------+
| 2018-11-21 12:00:00+07 | 10 | 12 |
| 2018-11-21 13:00:00+07 | 2 | 13 |
| 2018-11-21 14:00:00+07 | 2 | 14 |
| 2018-11-21 16:00:00+07 | 1 | 16 |
| 2018-11-21 17:00:00+07 | 21 | 17 |
| 2018-11-21 19:00:00+07 | 18 | 19 |
| 2018-11-21 20:00:00+07 | 8 | 20 |
| 2018-11-21 21:00:00+07 | 1 | 21 |
+-------------------------+-------+------+


My question is, if I refetch some API end point that will query above statement, would it be the data in the past hour cached automatically? because in my case, if there is a new data, it will update the last hour's row only.



If not how to cache it? Thanks in advance







sql postgresql






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 21 '18 at 12:17







Kris MP

















asked Nov 21 '18 at 12:00









Kris MPKris MP

56811024




56811024













  • Why are you concerned about caching? How long does it take the query to run?

    – Gordon Linoff
    Nov 21 '18 at 12:02











  • @GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

    – Kris MP
    Nov 21 '18 at 12:04






  • 1





    What if new data is inserted into the table? what if the value of todaychanges overnight?

    – wildplasser
    Nov 21 '18 at 12:05






  • 1





    2.752 ms is really, really fast.

    – Gordon Linoff
    Nov 21 '18 at 12:42






  • 3





    PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

    – JustMe
    Nov 21 '18 at 12:44





















  • Why are you concerned about caching? How long does it take the query to run?

    – Gordon Linoff
    Nov 21 '18 at 12:02











  • @GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

    – Kris MP
    Nov 21 '18 at 12:04






  • 1





    What if new data is inserted into the table? what if the value of todaychanges overnight?

    – wildplasser
    Nov 21 '18 at 12:05






  • 1





    2.752 ms is really, really fast.

    – Gordon Linoff
    Nov 21 '18 at 12:42






  • 3





    PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

    – JustMe
    Nov 21 '18 at 12:44



















Why are you concerned about caching? How long does it take the query to run?

– Gordon Linoff
Nov 21 '18 at 12:02





Why are you concerned about caching? How long does it take the query to run?

– Gordon Linoff
Nov 21 '18 at 12:02













@GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

– Kris MP
Nov 21 '18 at 12:04





@GordonLinoff 2.752 ms in average, what if the data is too large to count in every hour?

– Kris MP
Nov 21 '18 at 12:04




1




1





What if new data is inserted into the table? what if the value of todaychanges overnight?

– wildplasser
Nov 21 '18 at 12:05





What if new data is inserted into the table? what if the value of todaychanges overnight?

– wildplasser
Nov 21 '18 at 12:05




1




1





2.752 ms is really, really fast.

– Gordon Linoff
Nov 21 '18 at 12:42





2.752 ms is really, really fast.

– Gordon Linoff
Nov 21 '18 at 12:42




3




3





PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

– JustMe
Nov 21 '18 at 12:44







PostgreSQL caches data automaticlly based on LRU algorithm (check this link: madusudanan.com/blog/understanding-postgres-caching-in-depth). What you're doing is premature optimization here ;)

– JustMe
Nov 21 '18 at 12:44














1 Answer
1






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oldest

votes


















2














PSQL can not cache result of query itself. The solution is cache the result at API application layer.

I prefer using redis to cache it. Using a hash with fields is year+month+day+hour and value is total online user of each hour. Example:



 hash: useronline
field: 2018112112 - value: 10
field: 2018112113 - value: 2


You also set a timeout on key. After the timeout has expired, the key will automatically be deleted. I will set 1 hour in here.



EXPIRE useronline 3600


When have API request we will get result in redis cache first. If do not exist or expired call query to database layer to get result, save to redis cache again. Reponse result to client.

Here is list of redis clients suitable for programing language.






share|improve this answer























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    PSQL can not cache result of query itself. The solution is cache the result at API application layer.

    I prefer using redis to cache it. Using a hash with fields is year+month+day+hour and value is total online user of each hour. Example:



     hash: useronline
    field: 2018112112 - value: 10
    field: 2018112113 - value: 2


    You also set a timeout on key. After the timeout has expired, the key will automatically be deleted. I will set 1 hour in here.



    EXPIRE useronline 3600


    When have API request we will get result in redis cache first. If do not exist or expired call query to database layer to get result, save to redis cache again. Reponse result to client.

    Here is list of redis clients suitable for programing language.






    share|improve this answer




























      2














      PSQL can not cache result of query itself. The solution is cache the result at API application layer.

      I prefer using redis to cache it. Using a hash with fields is year+month+day+hour and value is total online user of each hour. Example:



       hash: useronline
      field: 2018112112 - value: 10
      field: 2018112113 - value: 2


      You also set a timeout on key. After the timeout has expired, the key will automatically be deleted. I will set 1 hour in here.



      EXPIRE useronline 3600


      When have API request we will get result in redis cache first. If do not exist or expired call query to database layer to get result, save to redis cache again. Reponse result to client.

      Here is list of redis clients suitable for programing language.






      share|improve this answer


























        2












        2








        2







        PSQL can not cache result of query itself. The solution is cache the result at API application layer.

        I prefer using redis to cache it. Using a hash with fields is year+month+day+hour and value is total online user of each hour. Example:



         hash: useronline
        field: 2018112112 - value: 10
        field: 2018112113 - value: 2


        You also set a timeout on key. After the timeout has expired, the key will automatically be deleted. I will set 1 hour in here.



        EXPIRE useronline 3600


        When have API request we will get result in redis cache first. If do not exist or expired call query to database layer to get result, save to redis cache again. Reponse result to client.

        Here is list of redis clients suitable for programing language.






        share|improve this answer













        PSQL can not cache result of query itself. The solution is cache the result at API application layer.

        I prefer using redis to cache it. Using a hash with fields is year+month+day+hour and value is total online user of each hour. Example:



         hash: useronline
        field: 2018112112 - value: 10
        field: 2018112113 - value: 2


        You also set a timeout on key. After the timeout has expired, the key will automatically be deleted. I will set 1 hour in here.



        EXPIRE useronline 3600


        When have API request we will get result in redis cache first. If do not exist or expired call query to database layer to get result, save to redis cache again. Reponse result to client.

        Here is list of redis clients suitable for programing language.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 21 '18 at 14:00









        KibGzrKibGzr

        1,496611




        1,496611
































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