$skip and $limit in aggregation frameworkMongoDB PHP Aggregate with $group and $matchNoSQL (MongoDB) vs Lucene (or Solr) as your databaseMongoDB row index limit query like SQLmongoDB $sort inconsistent resultsNoSQL (MongoDB) vs Lucene (or Solr) as your database“Large data” work flows using pandasHow do you tell Mongo to sort a collection before limiting the results?Mongodb aggregation $group followed by $limit for paginationHow to apply correctly $limit and $skip in subfields?Should I use the “allowDiskUse” option in a product environment?MongoDB Mgo Sort Skip Limit Aggregation Pipeline - Results out of ordersort() operation exceeds max memory in MongoDB Stitch function despite limit()Mongodb aggregation skip and limit with sorting bring duplicate records in paginationMongo DB skip and limit

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$skip and $limit in aggregation framework


MongoDB PHP Aggregate with $group and $matchNoSQL (MongoDB) vs Lucene (or Solr) as your databaseMongoDB row index limit query like SQLmongoDB $sort inconsistent resultsNoSQL (MongoDB) vs Lucene (or Solr) as your database“Large data” work flows using pandasHow do you tell Mongo to sort a collection before limiting the results?Mongodb aggregation $group followed by $limit for paginationHow to apply correctly $limit and $skip in subfields?Should I use the “allowDiskUse” option in a product environment?MongoDB Mgo Sort Skip Limit Aggregation Pipeline - Results out of ordersort() operation exceeds max memory in MongoDB Stitch function despite limit()Mongodb aggregation skip and limit with sorting bring duplicate records in paginationMongo DB skip and limit






.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;








29















When I read the document I found the following notes:




When a $sort immediately precedes a $limit in the pipeline, the $sort operation only maintains the top n results as it progresses, where n is the specified limit, and MongoDB only needs to store n items in memory. This optimization still applies when allowDiskUse is true and the n items exceed the aggregation memory limit.




If I'm right about this, it applies only when I use the $sort and $limit together like



db.coll.aggregate([
...,
$sort: ...,
$limit: limit,
...
]);


However, I think most of the time we would have



db.coll.aggregate([
...,
$sort: ...,
$skip: skip,
$limit: limit,
...
]);


Question 1: Does it mean the rule above doesn't apply if I use $skip here?



I ask this question because theoretically MongoDB can still calculate the top n records and enhance performance by sorting only top n records. I didn't find any document about this though. And if the rule doesn't apply,



Question 2: Do I need to change my query to the following to enhance performance?



db.coll.aggregate([
...,
$sort: ...,
$limit: skip + limit,
$skip: skip,
$limit: limit,
...
]);


EDIT: I think explains my use case would make the question above makes more sense. I'm using the text search feature provided by MongoDB 2.6 to look for products. I'm worried if the user inputs a very common key word like "red", there will be too many results returned. Thus I'm looking for better ways to generate this result.



EDIT2: It turns out that the last code above equals to



db.coll.aggregate([
...,
$sort: ...,
$limit: skip + limit,
$skip: skip,
...
]);


Thus I we can always use this form to make the top n rule apply.










share|improve this question






























    29















    When I read the document I found the following notes:




    When a $sort immediately precedes a $limit in the pipeline, the $sort operation only maintains the top n results as it progresses, where n is the specified limit, and MongoDB only needs to store n items in memory. This optimization still applies when allowDiskUse is true and the n items exceed the aggregation memory limit.




    If I'm right about this, it applies only when I use the $sort and $limit together like



    db.coll.aggregate([
    ...,
    $sort: ...,
    $limit: limit,
    ...
    ]);


    However, I think most of the time we would have



    db.coll.aggregate([
    ...,
    $sort: ...,
    $skip: skip,
    $limit: limit,
    ...
    ]);


    Question 1: Does it mean the rule above doesn't apply if I use $skip here?



    I ask this question because theoretically MongoDB can still calculate the top n records and enhance performance by sorting only top n records. I didn't find any document about this though. And if the rule doesn't apply,



    Question 2: Do I need to change my query to the following to enhance performance?



    db.coll.aggregate([
    ...,
    $sort: ...,
    $limit: skip + limit,
    $skip: skip,
    $limit: limit,
    ...
    ]);


    EDIT: I think explains my use case would make the question above makes more sense. I'm using the text search feature provided by MongoDB 2.6 to look for products. I'm worried if the user inputs a very common key word like "red", there will be too many results returned. Thus I'm looking for better ways to generate this result.



    EDIT2: It turns out that the last code above equals to



    db.coll.aggregate([
    ...,
    $sort: ...,
    $limit: skip + limit,
    $skip: skip,
    ...
    ]);


    Thus I we can always use this form to make the top n rule apply.










    share|improve this question


























      29












      29








      29


      13






      When I read the document I found the following notes:




      When a $sort immediately precedes a $limit in the pipeline, the $sort operation only maintains the top n results as it progresses, where n is the specified limit, and MongoDB only needs to store n items in memory. This optimization still applies when allowDiskUse is true and the n items exceed the aggregation memory limit.




      If I'm right about this, it applies only when I use the $sort and $limit together like



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: limit,
      ...
      ]);


      However, I think most of the time we would have



      db.coll.aggregate([
      ...,
      $sort: ...,
      $skip: skip,
      $limit: limit,
      ...
      ]);


      Question 1: Does it mean the rule above doesn't apply if I use $skip here?



      I ask this question because theoretically MongoDB can still calculate the top n records and enhance performance by sorting only top n records. I didn't find any document about this though. And if the rule doesn't apply,



      Question 2: Do I need to change my query to the following to enhance performance?



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: skip + limit,
      $skip: skip,
      $limit: limit,
      ...
      ]);


      EDIT: I think explains my use case would make the question above makes more sense. I'm using the text search feature provided by MongoDB 2.6 to look for products. I'm worried if the user inputs a very common key word like "red", there will be too many results returned. Thus I'm looking for better ways to generate this result.



      EDIT2: It turns out that the last code above equals to



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: skip + limit,
      $skip: skip,
      ...
      ]);


      Thus I we can always use this form to make the top n rule apply.










      share|improve this question
















      When I read the document I found the following notes:




      When a $sort immediately precedes a $limit in the pipeline, the $sort operation only maintains the top n results as it progresses, where n is the specified limit, and MongoDB only needs to store n items in memory. This optimization still applies when allowDiskUse is true and the n items exceed the aggregation memory limit.




      If I'm right about this, it applies only when I use the $sort and $limit together like



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: limit,
      ...
      ]);


      However, I think most of the time we would have



      db.coll.aggregate([
      ...,
      $sort: ...,
      $skip: skip,
      $limit: limit,
      ...
      ]);


      Question 1: Does it mean the rule above doesn't apply if I use $skip here?



      I ask this question because theoretically MongoDB can still calculate the top n records and enhance performance by sorting only top n records. I didn't find any document about this though. And if the rule doesn't apply,



      Question 2: Do I need to change my query to the following to enhance performance?



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: skip + limit,
      $skip: skip,
      $limit: limit,
      ...
      ]);


      EDIT: I think explains my use case would make the question above makes more sense. I'm using the text search feature provided by MongoDB 2.6 to look for products. I'm worried if the user inputs a very common key word like "red", there will be too many results returned. Thus I'm looking for better ways to generate this result.



      EDIT2: It turns out that the last code above equals to



      db.coll.aggregate([
      ...,
      $sort: ...,
      $limit: skip + limit,
      $skip: skip,
      ...
      ]);


      Thus I we can always use this form to make the top n rule apply.







      mongodb aggregation-framework






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Jun 12 '14 at 2:00







      yaoxing

















      asked Jun 11 '14 at 10:01









      yaoxingyaoxing

      2,49821326




      2,49821326






















          1 Answer
          1






          active

          oldest

          votes


















          41














          Since this is a text search query we are talking about then the most optimal form is this:





          db.collection.aggregate([
          "$match":
          "$text": "$search": "cake tea"
          ,
          { "$sort": "score": "$meta": "textScore" ,
          "$limit": skip + limit ,
          "$skip": skip
          ])


          The rationale on the memory reserve from the top "sort" results will only work within it's own "limits" as it were and this will not be optimal for anything beyond a few reasonable "pages" of data.



          Beyond what is reasonable for memory consumption, the additional stage will likely have a negative effect rather than positive.



          These really are the practical limitations of the text search capabilities available to MongoDB in the current form. But for anything more detailed and requiring more performance, then just as is the case with many SQL "full text" solutions, you are better off using an external "purpose built" text search solution.






          share|improve this answer

























          • You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

            – John Powell
            Jun 11 '14 at 11:19












          • @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

            – Neil Lunn
            Jun 11 '14 at 11:35











          • Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

            – John Powell
            Jun 11 '14 at 12:09












          • @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

            – yaoxing
            Jun 11 '14 at 13:34







          • 1





            I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

            – yaoxing
            Jun 12 '14 at 2:03











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          1 Answer
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          oldest

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          41














          Since this is a text search query we are talking about then the most optimal form is this:





          db.collection.aggregate([
          "$match":
          "$text": "$search": "cake tea"
          ,
          { "$sort": "score": "$meta": "textScore" ,
          "$limit": skip + limit ,
          "$skip": skip
          ])


          The rationale on the memory reserve from the top "sort" results will only work within it's own "limits" as it were and this will not be optimal for anything beyond a few reasonable "pages" of data.



          Beyond what is reasonable for memory consumption, the additional stage will likely have a negative effect rather than positive.



          These really are the practical limitations of the text search capabilities available to MongoDB in the current form. But for anything more detailed and requiring more performance, then just as is the case with many SQL "full text" solutions, you are better off using an external "purpose built" text search solution.






          share|improve this answer

























          • You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

            – John Powell
            Jun 11 '14 at 11:19












          • @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

            – Neil Lunn
            Jun 11 '14 at 11:35











          • Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

            – John Powell
            Jun 11 '14 at 12:09












          • @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

            – yaoxing
            Jun 11 '14 at 13:34







          • 1





            I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

            – yaoxing
            Jun 12 '14 at 2:03















          41














          Since this is a text search query we are talking about then the most optimal form is this:





          db.collection.aggregate([
          "$match":
          "$text": "$search": "cake tea"
          ,
          { "$sort": "score": "$meta": "textScore" ,
          "$limit": skip + limit ,
          "$skip": skip
          ])


          The rationale on the memory reserve from the top "sort" results will only work within it's own "limits" as it were and this will not be optimal for anything beyond a few reasonable "pages" of data.



          Beyond what is reasonable for memory consumption, the additional stage will likely have a negative effect rather than positive.



          These really are the practical limitations of the text search capabilities available to MongoDB in the current form. But for anything more detailed and requiring more performance, then just as is the case with many SQL "full text" solutions, you are better off using an external "purpose built" text search solution.






          share|improve this answer

























          • You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

            – John Powell
            Jun 11 '14 at 11:19












          • @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

            – Neil Lunn
            Jun 11 '14 at 11:35











          • Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

            – John Powell
            Jun 11 '14 at 12:09












          • @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

            – yaoxing
            Jun 11 '14 at 13:34







          • 1





            I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

            – yaoxing
            Jun 12 '14 at 2:03













          41












          41








          41







          Since this is a text search query we are talking about then the most optimal form is this:





          db.collection.aggregate([
          "$match":
          "$text": "$search": "cake tea"
          ,
          { "$sort": "score": "$meta": "textScore" ,
          "$limit": skip + limit ,
          "$skip": skip
          ])


          The rationale on the memory reserve from the top "sort" results will only work within it's own "limits" as it were and this will not be optimal for anything beyond a few reasonable "pages" of data.



          Beyond what is reasonable for memory consumption, the additional stage will likely have a negative effect rather than positive.



          These really are the practical limitations of the text search capabilities available to MongoDB in the current form. But for anything more detailed and requiring more performance, then just as is the case with many SQL "full text" solutions, you are better off using an external "purpose built" text search solution.






          share|improve this answer















          Since this is a text search query we are talking about then the most optimal form is this:





          db.collection.aggregate([
          "$match":
          "$text": "$search": "cake tea"
          ,
          { "$sort": "score": "$meta": "textScore" ,
          "$limit": skip + limit ,
          "$skip": skip
          ])


          The rationale on the memory reserve from the top "sort" results will only work within it's own "limits" as it were and this will not be optimal for anything beyond a few reasonable "pages" of data.



          Beyond what is reasonable for memory consumption, the additional stage will likely have a negative effect rather than positive.



          These really are the practical limitations of the text search capabilities available to MongoDB in the current form. But for anything more detailed and requiring more performance, then just as is the case with many SQL "full text" solutions, you are better off using an external "purpose built" text search solution.







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Jun 12 '14 at 6:00

























          answered Jun 11 '14 at 11:11









          Neil LunnNeil Lunn

          102k23183189




          102k23183189












          • You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

            – John Powell
            Jun 11 '14 at 11:19












          • @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

            – Neil Lunn
            Jun 11 '14 at 11:35











          • Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

            – John Powell
            Jun 11 '14 at 12:09












          • @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

            – yaoxing
            Jun 11 '14 at 13:34







          • 1





            I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

            – yaoxing
            Jun 12 '14 at 2:03

















          • You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

            – John Powell
            Jun 11 '14 at 11:19












          • @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

            – Neil Lunn
            Jun 11 '14 at 11:35











          • Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

            – John Powell
            Jun 11 '14 at 12:09












          • @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

            – yaoxing
            Jun 11 '14 at 13:34







          • 1





            I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

            – yaoxing
            Jun 12 '14 at 2:03
















          You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

          – John Powell
          Jun 11 '14 at 11:19






          You say in the current form. Is there work underway to enhance MongoDB text search, do you know? There are some great comments here on using Solr in conjunction with MongoDB stackoverflow.com/questions/3215029/…,

          – John Powell
          Jun 11 '14 at 11:19














          @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

          – Neil Lunn
          Jun 11 '14 at 11:35





          @JohnBarça The answer you seek is actually more "official" and slightly loaded in nature. IMO MongoDB admittedly does not try to be an "optimal" key/value store nor does it try to implement every feature of a traditional relational system as a "database" goes. The extension of this is that a general purpose "database" generally does not "go in for" specialized areas such as "text search". But that is an opinion, and perspectives are often subject to change. By all means, use what works best.

          – Neil Lunn
          Jun 11 '14 at 11:35













          Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

          – John Powell
          Jun 11 '14 at 12:09






          Interesting. I have been dabbling in Mongo and really like certain features. But I hear what you are saying. I'm a GIS guy and I like the geojson stuff that has been done and the aggregation spatial enhancements, but in terms of functionality still a long way from being able to leave Postgres/Postgis. I accept this is a very niche area, though.

          – John Powell
          Jun 11 '14 at 12:09














          @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

          – yaoxing
          Jun 11 '14 at 13:34






          @JohnBarça I agree with you guys. This is only a temp solution with which I can do it quick and simple. We did think of integrating a search engine. But not until the next phase because it would have brought too much extra work load now. And it has been much better than the "like" search we are using now:)

          – yaoxing
          Jun 11 '14 at 13:34





          1




          1





          I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

          – yaoxing
          Jun 12 '14 at 2:03





          I kept thinking about this and I think I understood why MongoDB only allow $limit other than $skip to apply the top n rule. Because skip+limit can always be turned to limit+skip. I edit my question.

          – yaoxing
          Jun 12 '14 at 2:03



















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