Patent Publication Number: US-2023161755-A1

Title: Cross row consistent data accessing

Description:
CLAIM OF PRIORITY 
     This application is a continuation of U.S. patent application Ser. No. 16/729,247, filed on Dec. 27, 2019, which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     Non-relational database provides mechanism for data storage and retrieval that is modeled in means other than the tabular relations used in traditional relational database. It is increasingly used in big data and real-time web applications. Many non-relational databases compromise data consistency in favor of scalability, flexible data schema, sparse data storage, etc. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced. 
         FIG.  1    is a diagrammatic representation of a networked environment in which the present disclosure may be deployed in accordance with some example embodiments. 
         FIG.  2    illustrates a diagrammatic representation of further details of the data processing system of a network environment  200  in accordance with one embodiment. 
         FIG.  3 A- 3 B  illustrate flow diagrams of processes in accordance with one embodiment. 
         FIG.  4    illustrates an example of an index table in accordance with one embodiment. 
         FIG.  5    illustrates an example of an index table in accordance with one embodiment. 
         FIG.  6    illustrates a block diagram of an example of an index tree in accordance with one embodiment. 
         FIG.  7    illustrates an example of index tree in three version stages in accordance with one embodiment. 
         FIG.  8    illustrates an example of a stats table in accordance with one embodiment. 
         FIG.  9    illustrates an example of the stats table in a first data version (e.g., data version 1) in accordance with one embodiment. 
         FIG.  10    illustrates an example of the stats table in a second data version (e.g., data version 2) in accordance with one embodiment. 
         FIG.  11    illustrates an example of the stats table in a third data version (e.g., data version 3) in accordance with one embodiment. 
         FIG.  12    illustrates a block diagram of the data processing system caching index data in accordance with one embodiment. 
         FIG.  13    is block diagram showing a software architecture within which the present disclosure may be implemented, in accordance with some example embodiments. 
         FIG.  14    is a diagrammatic representation of a machine, in the form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed, in accordance with some example embodiments. 
         FIG.  15    is a diagrammatic representation of a processing environment, in accordance with some example embodiments. 
         FIG.  16    is a diagrammatic representation of a data structure as maintained in a database, in accordance with some example embodiments. 
         FIG.  17    is a diagrammatic representation of a message, in accordance with some example embodiments. 
         FIG.  18    is a diagrammatic representation of a messaging client application, in accordance with some example embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     Current systems using a non-relation database such as a typical key value store only guarantees single row consistency, such that during data input and output, the data is only in consistent state within one row. When there is a need to output data in cross rows during data update, the output is usually incomplete because a typical key value store does not guarantee cross row data consistency during data update. As results, when data is being updated in multiple rows, reader could only get partial view of the newly updated data since the cross rows data update is not transactional. The present disclosure relates to a system and method of providing a cross row consistent data output using a non-relational database. The present disclosure enables consistent data access between cross rows during data update, and single operation look up regardless how the data grows. Specifically, the system implements simultaneously or sequentially both a data update process and a data query response process in order to allow for a cross row consistent data accessing. 
     For the data update process, the system can write data rows in a stats table at a regular interval of time (e.g., hourly, daily, monthly, etc.) and can update an index table based on the data rows that were written. The index table can be an index row that includes data (e.g., index value) that comprise pointers to the most current data in the stats table. The index table can provide a layer of version index control that can be used to quickly identify and locate the latest stats row that stores the most current data. Since the system can perform the data update process periodically, the system can optimize data scalability and the periodically updated index row can operate as a snapshot of the stats table. For the data query response process, the system can receive a query for data pertaining to an entity (e.g., an advertisement) at any given time during the data update process. The system can retrieve the index value from the index row. The index value can then be used to fetch the current value associated with the entity from the stats table. Using the index table, the data access between cross rows in the stats table during the data update process is always consistent and up-to-date. 
     Because of the one hierarchy index stays within one row, the system utilizes the index to make sure the index updates and outputs are always transactional. Therefore, the system gets consistent data version from the index with which the system can get consistent data. 
     Various aspects and examples will now be described. The following description provides specific details for a thorough understanding and enabling description of these examples. Those skilled in the art will understand, however, that the disclosure may be practiced without many of these details. Additionally, some well-known structures or functions may not be shown or described in detail, so as to avoid unnecessarily obscuring the relevant description. 
       FIG.  1    is a diagrammatic representation of a network environment  100  for exchanging data (e.g., messages and associated content) over a network according to some embodiments. The network environment  100  can include multiple instances of client device  102 , each of which hosts a number of applications including a messaging client application  108 . Each messaging client application  108  is communicatively coupled to other instances of the messaging client application  108  and a data processing system  110  via a network  106  (e.g., the Internet). The network environment  100  can also include multiple instances of an advertiser device  104 . The multiple instances of advertiser device  104  are communicatively coupled to the data processing system  110  via the network  106 . 
     A messaging client application  108  is able to communicate and exchange data with another messaging client application  108  and with the data processing system  110  via the network  106 . The data exchanged between messaging client application  108 , and between a messaging client application  108  and the data processing system  110 , includes functions (e.g., commands to invoke functions) as well as payload data (e.g., text, audio, video or other multimedia data). 
     The data processing system  110  provides server-side functionality via the network  106  to a particular messaging client application  108 . While certain functions of the diagrammatic representation of a network environment  100  are described herein as being performed by either a messaging client application  108  or by the data processing system  110 , the location of certain functionality either within the messaging client application  108  or the data processing system  110  is a design choice. For example, it may be technically preferable to initially deploy certain technology and functionality within the data processing system  110 , but to later migrate this technology and functionality to the messaging client application  108  where a client device  102  has a sufficient processing capacity. 
     The data processing system  110  supports various services and operations that are provided to the messaging client application  108 . Such operations include transmitting data to, receiving data from, and processing data generated by the messaging client application  108 . This data may include, message content, client device information, geolocation information, media annotation and overlays, message content persistence conditions, social network information, and live event information, advertisements information, as examples. Data exchanges within the messaging system  100  are invoked and controlled through functions available via user interfaces (UIs) of the messaging client application  108 . 
     Turning now specifically to the data processing system  110 , an Application Program Interface (API) server  112  is coupled to, and provides a programmatic interface to, an application server  114 . The application server  114  is communicatively coupled to a database server  120 , which facilitates access to a database  122  in which is stored data associated with messages processed by the application server  114 . 
     The Application Program Interface (API) server  112  receives and transmits data such as message data (e.g., commands and message payloads) and advertisement data between the client device  102  and the application server  114 . The Application Program Interface (API) server  112  also receives and transmits data such as queries requesting status of advertisements performed in client device  102  between advertiser device  104  and the application server  114 . 
     Specifically, the Application Program Interface (API) server  112  provides a set of interfaces (e.g., routines and protocols) that can be called or queried by the messaging client application  108  and advertiser device  104  in order to invoke functionality of the application server  114 . The Application Program Interface (API) server  112  exposes various functions supported by the application server  114 , including account registration, login functionality, the sending of messages, via the application server  114 , from a particular messaging client application  108  to another messaging client application  108 , the sending of media files (e.g., images or video) from a messaging client application  108  to the messaging server application  116 , and for possible access by another messaging client application  108 , the setting of a collection of media data (e.g., story), the retrieval of a list of friends of a user of a client device  102 , the retrieval of such collections, the retrieval of messages and content, the adding and deletion of friends to a social graph, the location of friends within a social graph, and opening an application event (e.g., relating to the messaging client application  108 ). 
     The Application Program Interface (API) server  112  also exposes functions supported by the application server  114 , including account registration, login functionality, the sending and receiving of messages or queries, via the application server  114 , to the log events reporting system  126 , and for possible access by another advertiser device  104 . 
     The application server  114  hosts a number of applications and subsystems, including a messaging server application  116 , an image processing system  118 , a social network system  124 , and a log events reporting system  126 . The messaging server application  116  implements a number of message processing technologies and functions, particularly related to the aggregation and other processing of content (e.g., textual and multimedia content) included in messages received from multiple instances of the messaging client application  108 . As will be described in further detail, the text and media content from multiple sources may be aggregated into collections of content (e.g., called stories or galleries). These collections are then made available, by the messaging server application  116 , to the messaging client application  108 . Other processor and memory intensive processing of data may also be performed server-side by the messaging server application  116 , in view of the hardware requirements for such processing. 
     The application server  114  also includes an image processing system  118  that is dedicated to performing various image processing operations, typically with respect to images or video received within the payload of a message at the messaging server application  116 . 
     The social network system  124  supports various social networking functions services, and makes these functions and services available to the messaging server application  116 . To this end, the social network system  124  maintains and accesses an entity graph  1604  (as shown in  FIG.  16   ) within the database  122 . Examples of functions and services supported by the social network system  124  include the identification of other users of the messaging system  100  with which a particular user has relationships or is “following”, and also the identification of other entities and interests of a particular user. 
     The log events reporting system  126  supports functions such as periodically receiving log events generated by client device  102 , aggregating log events and populating the aggregated data into database  122  via database server  120 , receiving queries from advertiser device  104  via application server  114 , processing queries via database server  120 , and providing results to advertiser device  104  via application server  114 . Log events may include user interaction events, such as viewing, spending, and interactions, generated by user interactions with advertisements showing in client device  102 . 
     The application server  114  is communicatively coupled to a database server  120 , which facilitates access to a database  122  in which is stored data associated with messages processed by the messaging server application  116  and log events processed by log events reporting system  126 . 
       FIG.  2    illustrates a diagrammatic representation of further details of the data processing system  110  of a network environment  200  in accordance with one embodiment. As shown in  FIG.  2   , the data processing system  110  can communicate with at least one client device  102  and at least one advertiser device  104 . The data processing system  110  includes an ad server  202 , a log events database  204 , a log events reporting server  210 , a stats database  206 , and a stats API  208 . In some embodiment, the log events reporting server  210  may reside in the log events reporting system  126 . In one embodiment, the log events reporting system  126  in application server  114  in  FIG.  1    comprises the ad server  202  and the log events reporting server  210 . In one embodiment, the database  122  in  FIG.  1    comprises the log events database  204  and the stats database  206 . The stats database  206  can include a stats table  1608  and an index table  1610  as shown in  FIG.  16   . In one embodiment, the API server  112  in  FIG.  1    comprises the stats API  208 . In another embodiment, the database server  120  comprises the ad server  202 . 
     In some embodiments, a key value store database comprises the stats table  1608  and the index table  1610 . The ad server  202  delivers advertisements (or ads) to the client device  102 . The ad server  202  can also cause the advertisements to be displayed on a display of the client device  102 . Based on user interactions with the advertisements, client device  102  generates a series of log events. Each of the log events can be generated by the client device  102  at a predetermined time period, such as an hour, a day, a month, etc. Accordingly, a log event can be generated every hour, every day, every month, etc. As shown in  FIG.  2   , ad server  202  receives the log events from the client device  102  and stores the log events in log events database  204 . The ad server  202  can also transmit the log events to the database server  120  ( FIG.  1   ). In this embodiment, the database server  120  processes the log events and stores the log events in the log events database  204 . 
     In one embodiment, log events reporting server  210  aggregates log events data based on each predetermined time period, and stores the aggregated data (e.g., aggregated log events) in the stats database  206 . It is understood by persons of ordinary skills in the art that aggregating data refers to data being combined from several measurements. When data is aggregated, groups of observations are replaced with summary statistics based on those observations. 
     Referring to  FIG.  9 - 11   ,  FIG.  9    illustrates an example of the stats table in a first data version (e.g., data version 1) in accordance with one embodiment;  FIG.  10    illustrates an example of the stats table in a second data version (e.g., data version 2) in accordance with one embodiment;  FIG.  11    illustrates an example of the stats table in a third data version (e.g., data version 3) in accordance with one embodiment. The stats table in the first data version can correspond to the first predetermined time period, the stats table in the second data version can corresponds to the second predetermined time period, and the stats table in the third data version can corresponds to the third predetermined time period. 
     At each of the predetermined time periods, as shown in  FIG.  9 - 11   , log events reporting server  210  writes data rows based on the aggregated log events in the stats table  1608 . The data rows stored in the stats table  1608  comprise a first row key and a plurality of data labels. The plurality of data labels comprises counters which include the value of log events such as viewing, spending and interaction as the results of data aggregation by log events reporting server  210 . Each log event in each row indicates the number of events occurred associated with each entity type, entity identity and each time stamp as indicated by the first row key. For example, in row 3 of  FIG.  9   , the first row indicates ad1 had 1000 viewing, $5 of spending, and 100 interactions with users within the first predetermined time period (e.g., the first hour). 
     The log events reporting server  210  can also aggregates log events data based on each predetermined time period and stores the aggregated data via the database server  120  ( FIG.  1   ). In some embodiments, the stats database  206  can include a stats table  1608  and an index table  1610 . 
     According to some embodiments, at least one advertiser device  104  generates a query and transmits the query to a stats API  208 . In some embodiments, stats API  208  may be a Representational State Transfer (REST) API. In one embodiment, stats API  208  transmits the query to the database server  120  for processing. Database server  120  can retrieve and read the data from stats database  206  corresponding to the query, and generates results based on the data corresponding to the query. In some embodiments, the log events reporting ad server  202  generates the results based on the data corresponding to the query in the stats database  206 . In one embodiment, the results include the data corresponding to the query in the stats database  206 . The database server  120  (or log events reporting server  210 ) can return the results to stats API  212 . Stats API  212  receives the results and transmits the results to the advertiser device  104 . 
     In some embodiments, the advertiser device  104  can transmit a query to the data processing system  110  at any time. For example, the advertiser device  104  can transmit the query while the log events reporting server  210  is writing data rows based on aggregated data stored in the stats table  1608  in the stats database  206 . 
     While not shown, it is understood that the client device  102  and the advertiser device  104  can be communicatively coupled to the data processing system  110  in  FIG.  2    via the network  106  in  FIG.  1   . 
       FIG.  3 A  is a flow diagram  300  of a data update process  324  in accordance with one embodiment, and  FIG.  3 B  is a flow diagram of a data query response process  322  according to some example embodiments. 
     By implementing both the data update process  324  and the data query response process  322 , the data processing system  110  in the networked environment  200  can implement a cross row consistent data accessing. For illustrative purposes, the processes  324  and  322  are described with respect to the data processing system  110  in the networked environment  200  in  FIG.  2   . It is to be understood that the processes  324  and  322  may be practiced with other system configurations in other embodiments. For example, the processes  324  and  322  can be performed by a processor. In one embodiment, the data processing system  110  can perform the data update process  324  and data query response process  322  concurrently or sequentially. 
     Referring to the data update process  324  in  FIG.  3 A , the data processing system  110  starts, at operation  302 , by initializing an index i. For example, the index i can be set to 0 as shown in  FIG.  3 A  (e.g., i=0). At operation  312 , the data processing system  110  can write a plurality of data rows in a stats table  1608  for predetermined time period i. For example, in the first iteration after the initialization at operation  302 , the predetermined time period i is the first predetermined time period 0. The predetermined time period can be an hour, a day, a month, a year, etc. Accordingly, when the predetermined time period set as an hour, at operation  312 , the data processing system  110  can write a plurality of data rows in the stats table  1608  that correspond to the predetermined time period i (e.g., hour i). Referring to  FIG.  9   , an example of the written plurality of data rows in the stats table  1608  for the first predetermined time period 0 is shown. As shown in  FIG.  9   , the data rows stored in the stats table  1608  comprise a first row key and a plurality of data labels. The plurality of data labels comprises counters which include the value of log events such as viewing, spending and interaction. 
     At operation  314 , the data processing system  110  updates an index table  1610  based on the plurality of data rows written in the stats table  1608  for the predetermined time period i. For example,  FIG.  4 - 5    illustrate examples of the index table  1610 . As shown in  FIG.  5   , the index table  1610  can include a current version data of each of the entities in the stats table in a single row (index row). Accordingly, the index row in the index table  1610  can be referred to, at any given time, to provide the current version data. Specifically, the index row include data (e.g., index value) that comprise pointers used to fetch queried entities value from the stats table  1608 . For example, the single index row included in the index table  1610  can be row 3 as shown in  FIG.  5   . It is understood that the row 1 and the row 2 as shown in  FIG.  5    merely provide labels and explanations regarding the contents of the single index row (row 3) and are included herein for illustration purpose only. 
     At operation  304 , the data processing system  110  determines whether the next predetermined time period (i+1) is reached. In the example where the predetermined time period is an hour, the next predetermined time period (i+1) is reached when the predetermined time period i (e.g., hour i) is lapsed. In other words, the next predetermined time period i+1 (e.g., next hour) is reached. If the data processing system  110  determines that the next predetermined time period i+1 is not reached, the data processing system  110  waits and repeats the operation  304  until the next predetermined time period i+1 is reached. 
     If the data processing system  110  determines that the next predetermined time period (i+1) is reached, the data processing system  110  increases the index i at operation  306  (e.g., i=i+1) and performs operation  312  having updated the predetermined time period. 
     In some embodiment, since key value stores can be non-relational databases that only guarantee single row atomic transaction, the index row in the index table  1610  can be referred to, at any given time, to provide the current version data. Specifically, given that the index row is one single row and a consistent data read is a guaranteed single row atomic transaction, the index row can include data acting as pointers to fetch queried entities value from the stats table  1608 . This allows for the data read to be complete and consistent at any given time that there is a query. Particularly, the index table  1610  provides for complete and consistent data reads during data update process  324 . 
     Referring to the data query response process  322  in  FIG.  3 B , the data processing system  110  can start by receiving at operation  308  from an electronic device, via an interface, a query corresponding to an entity. In one embodiment, the query includes an identification of the entity. An entity can be, for example, a single advertisement (e.g., ad 1, in  FIG.  9 - 11   ), an advertising squad (e.g., squad 1, in  FIG.  9 - 11   ), an advertising campaign (e.g., campaign 1, in  FIG.  9 - 11   ), or an advertiser account (e.g., account 1, in  FIG.  9 - 11   ). The advertiser account can be associated with a plurality of single advertisements, squads, campaigns. 
     For example, in  FIG.  7   , an advertiser device  104  may operates multiple advertiser accounts that associated with a plurality of advertising campaigns, advertising squads, and advertisement associated under each advertiser accounts. An advertisement (e.g., ad 1 (v1)  738 ) may be an advertisement shown on an electronic device viewed by a user. An advertising squad (e.g., squad 1 (v1)  736 ) can be a collection of advertisements. An advertising campaign (e.g., campaign 1 (v1)  708 ) can be a collection of advertising squads that comprise a collection of advertisements. An advertiser account (e.g., account 1 (v1)  702 ) can be a collection of advertising campaigns that comprise a collection of advertising squads that comprise a collection of advertisements, etc. 
     According to some embodiments as shown in  FIG.  7   , a first advertising squad (e.g., squad 1) is associated with a first advertisement (e.g., ad 1) and a second advertisement (e.g., ad 2). A second advertising squad (e.g., squad 2) is associated with a third advertisement (e.g., ad 3). A first advertising campaign (e.g., campaign 1) is associated with the first advertising squad (e.g., squad 1). A second advertising campaign (e.g., campaign 2) is associated with the second advertising squad (e.g., squad 2). An advertiser account (e.g., account 1) is associated with the first advertising campaign (e.g., campaign 1) and the second advertising campaign (e.g., campaign 2). An advertiser device  104  may operates multiple advertiser accounts that associated with a plurality of advertising campaigns, advertising squads, and advertisement associated under each advertiser accounts. 
     At operation  310 , the data processing system  110  retrieves an index value from an index row in the index table  1610 . In one embodiment, the data processing system  110  retrieves the index value from the index row that corresponds to a current value associated with the entity. As discussed above, the index table  1610  can include a current version data of each of the entities in the stats table in a single row (index row). The index row can be referred to, at any given time, to provide the current version data. Specifically, the index row includes data (e.g., index value) that comprise pointers used to fetch queried entities value from the stats table  1608 . 
     In this embodiment, the data processing system  110  retrieves the index value that corresponds to a current value associated with the entity identified in the query. The data processing system  110  then retrieves at operation  316  the current value from the stats table using the index value. 
     At operation  318 , the data processing system  110  generates a response to the query using the index value and the current value. The response can include a plurality of counter values associated with the entity. As shown in  FIG.  9 - 11   , the counter values can include a number of viewings of the entity, an amount spent corresponding to the entity, a number of interactions with the entity, etc. 
     For example, when the entity identified in the query is advertisement 1 (e.g., ad 1) and the index version identified in the index row is V1 (e.g.,  FIG.  5   ), the counter values can include a number of viewings of the entity (e.g., 1000 viewings of ad 1), an amount spent corresponding to the entity (e.g., $5 spent on ad 1), a number of interactions with the entity (e.g., 100 interactions with ad 1), as shown in  FIG.  9 - 11   . 
     At operation  320 , the data processing system  110  causes the response to be displayed on a display of the electronic device. 
       FIG.  4    illustrates an example of an index table in accordance with an embodiment. The index table  400  comprises one index row in row 2. The index row comprises a second row key and a set of index values. The second row key comprises a data category, an entity type, and an index root identity. The data category may be a type of data where only the latest version of the data has value, such as lifetime data. An entity types may refer to an account, a campaign, a squad, or an ad. An index root identity may refer to the identity of the root node of an index tree data structure which is discussed in  FIG.  6   . 
     The set of index values may include index version (e.g., timestamp) of the index root identity, and the data versions of each entity types. The data version may refer to the time stamp of each predetermined time period according to some embodiments. 
       FIG.  5    illustrates an example of an index table in accordance with an embodiment. The index row in  FIG.  5    is row 3 which shows the second row key and the set of index values in index version 1, such as in time stamp  1  as in hour 1 in some embodiments. The second row key comprises lifetime as the data category, account as the entity type, and account id as the index root identity. The set of index values comprises hour 1 as the index version of the index root identity showing as account, and each pointer map&lt;id, version&gt; pointing to the respective versions of campaign, squad, and ad as the entity types other than the root entity as account. The pointers are used to fetch the entities value from the stats table  1608  requested by the query which may come in at any given time according to some embodiments. 
       FIG.  6    illustrates a block diagram showing an index tree  600  in accordance with an embodiment. The index row is constructed based on the index tree comprising a root node as entity type 4 in level 0 (block  602 ), two entity type 3 intermediate level nodes in level 1 (block  606  and block  604 ), two entity type 2 lower level nodes in level 2 (block  616  and block  614 ), and three entity type 1 leaf nodes in level 3 (block  612 , block  610 , and block  608 ). 
     In some embodiments, it is understood by persons of ordinary skills in the art that each node, except for nodes in the lowest level (e.g., leaf nodes), has a key information referencing to one or more nodes in the immediate lower level nodes. For example, the root node entity type 4 level o (block  602 ) has a key information referencing to nodes entity type 3 identity 1 level 1 (block  606 ) and entity type 3 identity 2 level 1 (block  604 ). The key information can be version attributes of the one or more nodes in the immediate lower level, so that once a leaf node updates to a new version, all upper nodes in the same branch updates to the new version. 
       FIG.  7    illustrates an example of index tree in three version stages in accordance with an embodiment. In a predetermined time period, such as version 1 or the first hour, ad 1 and ad 2 are active due to occurrence of certain user interactions, such as the user viewed, interacted, or made spending on an advertisement 1 (ad 1) and advertisement 2 (ad 2) sent by the ad server  202  onto the client device  102 . The index version of ad 1 and ad 2 thereby changes to V1, indicating both entities were active in the first hour. Since squad 1, campaign 1 and account 1 are the upper nodes referring to respective lower nodes with the same version attributes, the index version of squad 1, campaign 1 and account 1 changes to V1 as well. Because ad 3 were inactive in the first hour, therefore there is no index version assigned to ad 3 and its upper level nodes including squad 2 and campaign 2. 
     According to some embodiments, in a subsequent predetermined time period, such as version 2, or the second hour, ad 1 is active due to user interactions with advertisement 3. As explained above, the index version of its upper nodes including squad 1, campaign 1 and account 1 change to V2. In the second hour, ad 2 is inactive, hence its index version remains V1. Ad 3 remains inactive. Therefore, no index version is assigned. 
     According to some embodiments, in a next subsequent predetermined time period, such as version 3, or the third hour, ad 1 and ad 2 are inactive, but ad 3 is active, therefore index version V3 is assigned to ad 3 and squad 2, campaign 2 and account 1. 
     According to some embodiments, the index version is incorporated into the index values of the index row shown in  FIG.  4 - 5   . 
       FIG.  8    illustrates an example of a stats table  1608  in accordance with one embodiment. Each data rows in the first data table  800  comprises a first row key and a plurality of data labels. The first row key comprises an entity type, an entity identity and a data version. The entity types may include account, campaign, squad, and ad. Each entity within each entity type may be identified by entity identity, such as campaign 1, campaign 2, squad 1, squad 2, etc. 
     The data version may be time stamp in some embodiment. The data version may reflect each predetermined time period, for example, when a predetermined time period is one hour, data version of the first hour is labeled as V1 and the data version of the second hour is labeled as V2, etc. The plurality of data labels may comprise metrics, such as counters associated with each log events (e.g. viewing, spending, and interaction) as illustrated in  FIG.  9   - FIG.  11   . 
       FIG.  9    illustrates an example of the stats table in a first data version (e.g., data version 1 or V1) in accordance with one embodiment. The plurality of data labels comprises counters which include the value of log events such as viewing, spending and interaction as the results of data aggregation by log events reporting server  210 . Each log event in each row indicates the number of events occurred associated with each entity type, entity identity and each time stamp as indicated by the first row key. For example, in row 3, the first row indicates ad1 had 1000 viewing, $5 of spending, and 100 interactions with users within the first predetermined time period, such as the first hour. 
     Referring back to the  FIG.  7   , the index tree is updated as shown in the data version 1 after the first data table is populated with the data rows 3-11 shown in  FIG.  9    where the data rows record all the aggregated log events associated with the entities active in the first hour, such as, ad1, ad2, and their respective upper level entities such as squad 1, campaign 1 and account 1 based on the same version attributes. 
       FIG.  10    illustrates an example of the stats table in a second data version (e.g., data version 2 or V2) in accordance with one embodiment. The index tree is updated as shown in data version 2 in  FIG.  7    after the first data table is populated with data rows 4, 7, 9 and 11 recording all aggregated log events associated with the entities active in the second hour, including ad2 and its upper level entities squad 1, campaign 1 and account 1 based on the same version attributes. 
       FIG.  11    illustrates an example of the stats table in a third data version (e.g., data version 3 or V3) in accordance with one embodiment. The index tree is updated as shown in data version 3 in  FIG.  7    after the stats table is populated with data rows 6, 9, 12, 15 recording all aggregated log events associated with the entities active in the third hour, including ad3 and its upper level entities squad 2, campaign 2 and account 1 based on the same version attributes. 
       FIG.  12    illustrates a block diagram of the data processing system caching index data in accordance with one embodiment. Based on each predetermined time period, such as hourly, aggregated data of log events is exported (block  1202 ) in the index table  1208 . The index table  1208  asyncs with the cache  1206  and loads the index table  1208  into the cache  1206  periodically, such as in every 15 minutes. Subsequently when a query  1204  is received by server  1210 , the server  1210  may access the index table  1208  directly from the cache  1206  instead of having to reload the index table  1208  to the server  1210  again. The data processing system caching index data helps to improve the performance and scalability of data read, and further improve query efficiency. 
     In some embodiments, a query  1204  is sent by advertiser device  104  and received by database server  120  or ad server  202 . In some embodiments, the stats database  206  comprises the index table  1208 . In some embodiments, database server  120  comprises server  1210 . 
       FIG.  13    is a block diagram  1300  illustrating a software architecture  1304 , which can be installed on any one or more of the devices described herein. The software architecture  1304  is supported by hardware such as a machine  1302  that includes processors  1320 , memory  1326 , and I/O components  1338 . In this example, the software architecture  1304  can be conceptualized as a stack of layers, where each layer provides a particular functionality. The software architecture  1304  includes layers such as an operating system  1312 , libraries  1310 , frameworks  1308 , and applications  1306 . Operationally, the applications  1306  invoke API calls  1350  through the software stack and receive messages  1352  in response to the API calls  1350 . 
     The operating system  1312  manages hardware resources and provides common services. The operating system  1312  includes, for example, a kernel  1314 , services  1316 , and drivers  1322 . The kernel  1314  acts as an abstraction layer between the hardware and the other software layers. For example, the kernel  1314  provides memory management, processor management (e.g., scheduling), component management, networking, and security settings, among other functionality. The services  1316  can provide other common services for the other software layers. The drivers  1322  are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  1322  can include display drivers, camera drivers, BLUETOOTH® or BLUETOOTH® Low Energy drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), WI-FI® drivers, audio drivers, power management drivers, and so forth. 
     The libraries  1310  provide a low-level common infrastructure used by the applications  1306 . The libraries  1310  can include system libraries  1318  (e.g., C standard library) that provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries  1310  can include API libraries  1324  such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as Moving Picture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries (e.g., an OpenGL framework used to render in two dimensions (2D) and three dimensions (3D) in a graphic content on a display), database libraries (e.g., SQLite to provide various relational database functions), web libraries (e.g., WebKit to provide web browsing functionality), and the like. The libraries  1310  can also include a wide variety of other libraries  1328  to provide many other APIs to the applications  1306 . 
     The frameworks  1308  provide a high-level common infrastructure that is used by the applications  1306 . For example, the frameworks  1308  provide various graphical user interface (GUI) functions, high-level resource management, and high-level location services. The frameworks  1308  can provide a broad spectrum of other APIs that can be used by the applications  1306 , some of which may be specific to a particular operating system or platform. 
     In an example embodiment, the applications  1306  may include a home application  1336 , a contacts application  1330 , a browser application  1332 , a book reader application  1334 , a location application  1342 , a media application  1344 , a messaging application  1346 , a game application  1348 , and a broad assortment of other applications such as third-party applications  1340 . The applications  1306  are programs that execute functions defined in the programs. Various programming languages can be employed to create one or more of the applications  1306 , structured in a variety of manners, such as object-oriented programming languages (e.g., Objective-C, Java, or C++) or procedural programming languages (e.g., C or assembly language). In a specific example, the third-party applications  1340  (e.g., applications developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or another mobile operating system. In this example, the third-party applications  1340  can invoke the API calls  1350  provided by the operating system  1312  to facilitate functionality described herein. 
       FIG.  14    is a diagrammatic representation of a machine  1400  within which instructions  1408  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  1400  to perform any one or more of the methodologies discussed herein may be executed. For example, the instructions  1408  may cause the machine  1400  to execute any one or more of the methods described herein. The instructions  1408  transform the general, non-programmed machine  1400  into a particular machine  1400  programmed to carry out the described and illustrated functions in the manner described. The machine  1400  may operate as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  1400  may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine  1400  may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a PDA, an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions  1408 , sequentially or otherwise, that specify actions to be taken by the machine  1400 . Further, while only a single machine  1400  is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions  1408  to perform any one or more of the methodologies discussed herein. 
     The machine  1400  may include processors  1402 , memory  1404 , and I/O components  1442 , which may communicate with each other via a bus  1444 . In an example embodiment, the processors  1402  (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor  1406  and a processor  1410  that execute the instructions  1408 . The term “processor” is intended to include multi-core processors that may comprise two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. Although  FIG.  14    shows multiple processors  1402 , the machine  1400  may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof. 
     The memory  1404  includes a main memory  1412 , a static memory  1414 , and a storage unit  1416 , both accessible to the processors  1402  via the bus  1444 . The main memory  1404 , the static memory  1414 , and storage unit  1416  store the instructions  1408  embodying any one or more of the methodologies or functions described herein. The instructions  1408  may also reside, completely or partially, within the main memory  1412 , within the static memory  1414 , within machine-readable medium  1418  within the storage unit  1416 , within at least one of the processors  1402  (e.g., within the processor&#39;s cache memory), or any suitable combination thereof, during execution thereof by the machine  1400 . 
     The I/O components  1442  may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components  1442  that are included in a particular machine will depend on the type of machine. For example, portable machines such as mobile phones may include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components  1442  may include many other components that are not shown in  FIG.  14   . In various example embodiments, the I/O components  1442  may include output components  1428  and input components  1430 . The output components  1428  may include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components  1430  may include alphanumeric input components (e.g., a keyboard, a touch screen receiving alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point-based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or another pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. 
     In further example embodiments, the I/O components  1442  may include biometric components  1432 , motion components  1434 , environmental components  1436 , or position components  1438 , among a wide array of other components. For example, the biometric components  1432  include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram-based identification), and the like. The motion components  1434  include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environmental components  1436  include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometers that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  1438  include location sensor components (e.g., a GPS receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like. 
     Communication may be implemented using a wide variety of technologies. The I/O components  1442  further include communication components  1440  operable to couple the machine  1400  to a network  1420  or devices  1422  via a coupling  1424  and a coupling  1426 , respectively. For example, the communication components  1440  may include a network interface component or another suitable device to interface with the network  1420 . In further examples, the communication components  1440  may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices  1422  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a USB). 
     Moreover, the communication components  1440  may detect identifiers or include components operable to detect identifiers. For example, the communication components  1440  may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components  1440 , such as location via Internet Protocol (IP) geolocation, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth. 
     The various memories (e.g., memory  1404 , main memory  1412 , static memory  1414 , and/or memory of the processors  1402 ) and/or storage unit  1416  may store one or more sets of instructions and data structures (e.g., software) embodying or used by any one or more of the methodologies or functions described herein. These instructions (e.g., the instructions  1408 ), when executed by processors  1402 , cause various operations to implement the disclosed embodiments. 
     The instructions  1408  may be transmitted or received over the network  1420 , using a transmission medium, via a network interface device (e.g., a network interface component included in the communication components  1440 ) and using any one of a number of well-known transfer protocols (e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions  1408  may be transmitted or received using a transmission medium via the coupling  1426  (e.g., a peer-to-peer coupling) to the devices  1422 . 
       FIG.  15    shows a diagrammatic representation of a processing environment  1500 , which includes the processor  1506 , the processor  1508 , and a processor  1502  (e.g., a GPU, CPU or combination thereof). 
     The processor  1502  is shown to be coupled to a power source  1504 , and to include (either permanently configured or temporarily instantiated) modules, namely a log event reporting component  1510 , and an R/W component  1512 . The log event reporting component  1510  operationally generates data such as aggregated data (e.g., aggregated log events) to populate the stats table  1608  and index data to update index table  1610 , and the R/W component  1512  operationally generates data such as entities value based on query. As illustrated, the processor  1502  is communicatively coupled to both the processor  1506  and processor  1508 , and receives query from the processor  1506 , as well as log events based on each predetermined time period from the processor  1508 . 
       FIG.  16    is a schematic diagram illustrating data structures  1600  which may be stored in the database  122  of the data processing system  110 , according to certain example embodiments. While the content of the database  122  is shown to comprise a number of tables, it will be appreciated that the data could be stored in other types of data structures (e.g., as an object-oriented database). 
     The database  122  includes message data stored within a message table  1618 . The entity table  1602  stores entity data, including an entity graph  1604 . Entities for which records are maintained within the entity table  1602  may include individuals, corporate entities, organizations, objects, places, events, etc. Regardless of type, any entity regarding which the data processing system  110  stores data may be a recognized entity. Each entity is provided with a unique identifier, as well as an entity type identifier (not shown). 
     The entity graph  1604  furthermore stores information regarding relationships and associations between entities. Such relationships may be social, professional (e.g., work at a common corporation or organization) interested-based or activity-based, merely for example. 
     The database  122  also stores annotation data, in the example form of filters, in an annotation table  1616 . Filters for which data is stored within the annotation table  1616  are associated with and applied to videos (for which data is stored in a video table  1614 ) and images (for which data is stored in an image table  1612 ). Filters, in one example, are overlays that are displayed as overlaid on an image or video during presentation to a recipient user. Filters may be of varies types, including user-selected filters from a gallery of filters presented to a sending user by the messaging client application  108  when the sending user is composing a message. Other types of filters include geolocation filters (also known as geo-filters) which may be presented to a sending user based on geographic location. For example, geolocation filters specific to a neighborhood or special location may be presented within a user interface by the messaging client application  108 , based on geolocation information determined by a GPS unit of the client device  102 . Another type of filer is a data filer, which may be selectively presented to a sending user by the messaging client application  108 , based on other inputs or information gathered by the client device  102  during the message creation process. Example of data filters include current temperature at a specific location, a current speed at which a sending user is traveling, battery life for a client device  102 , or the current time. 
     Other annotation data that may be stored within the image table  1612  is so-called “Lenses” data. “Lenses” may be a real-time special effect and sound that may be added to an image or a video. 
     As mentioned above, the video table  1614  stores video data which, in one embodiment, is associated with messages for which records are maintained within the message table  1618 . Similarly, the image table  1612  stores image data associated with messages for which message data is stored in the entity table  1602 . The entity table  1602  may associate various annotations from the annotation table  1616  with various images and videos stored in the image table  1612  and the video table  1614 . 
     A story table  1606  stores data regarding collections of messages and associated image, video, or audio data, which are compiled into a collection (e.g., a story or a gallery). The creation of a particular collection may be initiated by a particular user (e.g., each user for which a record is maintained in the entity table  1602 ). A user may create a “personal story” in the form of a collection of content that has been created and sent/broadcast by that user. To this end, the user interface of the messaging client application  108  may include an icon that is user-selectable to allow a sending user to add specific content to his or her personal story. 
     A collection may also constitute a “live story,” which is a collection of content from multiple users that is created manually, automatically, or using a combination of manual and automatic techniques. For example, a “live story” may constitute a curated stream of user-submitted content from varies locations and events. Users whose client devices have location services enabled and are at a common location event at a particular time may, for example, be presented with an option, via a user interface of the messaging client application  108 , to contribute content to a particular live story. The live story may be identified to the user by the messaging client application  108 , based on his or her location. The end result is a “live story” told from a community perspective. 
     A further type of content collection is known as a “location story”, which enables a user whose client device  102  is located within a specific geographic location (e.g., on a college or university campus) to contribute to a particular collection. In some embodiments, a contribution to a location story may require a second degree of authentication to verify that the end user belongs to a specific organization or other entity (e.g., is a student on the university campus). 
       FIG.  17    is a schematic diagram illustrating a structure of a message  1700 , according to some in some embodiments, generated by a messaging client application  108  for communication to a further messaging client application  108  or the messaging server application  116 . The content of a particular message  1700  is used to populate the message table  1618  stored within the database  122 , accessible by the messaging server application  116 . Similarly, the content of a message  1700  is stored in memory as “in-transit” or “in-flight” data of the client device  102  or the application server  114 . The message  1700  is shown to include the following components:
         A message identifier  1702 : a unique identifier that identifies the message  1700 .   A message text payload  1704 : text, to be generated by a user via a user interface of the client device  102  and that is included in the message  1700 .   A message image payload  1706 : image data, captured by a camera component of a client device  102  or retrieved from a memory component of a client device  102 , and that is included in the message  1700 .   A message video payload  1708 : video data, captured by a camera component or retrieved from a memory component of the client device  102  and that is included in the message  1700 .   A message audio payload  1710 : audio data, captured by a microphone or retrieved from a memory component of the client device  102 , and that is included in the message  1700 .   A message annotation  1712 : annotation data (e.g., filters, stickers or other enhancements) that represents annotations to be applied to message image payload  1706 , message video payload  1708 , or message audio payload  1710  of the message  1700 .   A message duration parameter  1714 : parameter value indicating, in seconds, the amount of time for which content of the message (e.g., the message image payload  1706 , message video payload  1708 , message audio payload  1710 ) is to be presented or made accessible to a user via the messaging client application  108 .   A message geolocation parameter  1716 : geolocation data (e.g., latitudinal and longitudinal coordinates) associated with the content payload of the message. Multiple message geolocation parameter  1716  values may be included in the payload, each of these parameter values being associated with respect to content items included in the content (e.g., a specific image into within the message image payload  1706 , or a specific video in the message video payload  1708 ).   A message story identifier  1718 : identifier values identifying one or more content collections (e.g., “stories”) with which a particular content item in the message image payload  1706  of the message  1700  is associated. For example, multiple images within the message image payload  1706  may each be associated with multiple content collections using identifier values.   A message tag  1720 : each message  1700  may be tagged with multiple tags, each of which is indicative of the subject matter of content included in the message payload. For example, where a particular image included in the message image payload  1706  depicts an animal (e.g., a lion), a tag value may be included within the message tag  1720  that is indicative of the relevant animal. Tag values may be generated manually, based on user input, or may be automatically generated using, for example, image recognition.   A message sender identifier  1722 : an identifier (e.g., a messaging system identifier, email address, or device identifier) indicative of a user of the client device  102  on which the message  1700  was generated and from which the message  1700  was sent   A message receiver identifier  1724 : an identifier (e.g., a messaging system identifier, email address, or device identifier) indicative of a user of the client device  102  to which the message  1700  is addressed.       

     The contents (e.g., values) of the various components of message  1700  may be pointers to locations in tables within which content data values are stored. For example, an image value in the message image payload  1706  may be a pointer to (or address of) a location within an image table  1612 . Similarly, values within the message video payload  1708  may point to data stored within a video table  1614 , values stored within the message annotations  1712  may point to data stored in an annotation table  1616 , values stored within the message story identifier  1718  may point to data stored in a story table  1606 , and values stored within the message sender identifier  1722  and the message receiver identifier  1724  may point to user records stored within an entity table  1602 . 
     In some embodiments, entity table  1602  comprises entity type and entity identity indicated by the first row key and the second row key as shown in  FIG.  4 - 5    and  FIG.  8 - 11   . For example, an advertiser device  104  may operates multiple advertiser accounts that associated with a plurality of advertising campaigns, advertising squads, and advertisement associated under each advertiser accounts. An advertisement (e.g., ad 1 (v1)  738 ) may be an advertisement shown on an electronic device viewed by a user. An advertising squad (e.g., squad 1 (v1)  736 ) can be a collection of advertisements. An advertising campaign (e.g., campaign 1 (v1)  708 ) can be a collection of advertising squads that comprise a collection of advertisements. An advertiser account (e.g., account 1 (v1)  702 ) can be a collection of advertising campaigns that comprise a collection of advertising squads that comprise a collection of advertisements, etc. 
     According to some embodiments as shown in  FIG.  7   , a first advertising squad (e.g., squad 1) is associated with a first advertisement (e.g., ad 1) and a second advertisement (e.g ad 2). A second advertising squad (e.g., squad 2) is associated with a third advertisement (e.g., ad 3). A first advertising campaign (e.g., campaign 1) is associated with the first advertising squad (e.g., squad 1). A second advertising campaign (e.g., campaign 2) is associated with the second advertising squad (e.g., squad 2). An advertiser account (e.g., account 1) is associated with the first advertising campaign (e.g., campaign 1) and the second advertising campaign (e.g., campaign 2). 
       FIG.  18    is block diagram illustrating further details regarding the diagrammatic representation of a network environment  100 , according to example embodiments. Specifically, the diagrammatic representation of a network environment  100  is shown to comprise the messaging client application  108  and the application server  114 , which in turn embody a number of some subsystems, namely an ephemeral timer system  1802 , a collection management system  1804  and an annotation system  1806 . 
     The ephemeral timer system  1802  is responsible for enforcing the temporary access to content permitted by the messaging client application  108  and the messaging server application  116 . To this end, the ephemeral timer system  1802  incorporates a number of timers that, based on duration and display parameters associated with a message, or collection of messages (e.g., a story), selectively display and enable access to messages and associated content via the messaging client application  108 . Further details regarding the operation of the ephemeral timer system  1802  are provided below. 
     The collection management system  1804  is responsible for managing collections of media (e.g., collections of text, image video and audio data). In some examples, a collection of content (e.g., messages, including images, video, text and audio) may be organized into an “event gallery” or an “event story.” Such a collection may be made available for a specified time period, such as the duration of an event to which the content relates. For example, content relating to a music concert may be made available as a “story” for the duration of that music concert. The collection management system  1804  may also be responsible for publishing an icon that provides notification of the existence of a particular collection to the user interface of the messaging client application  108 . 
     The collection management system  1804  furthermore includes a curation interface  1808  that allows a collection manager to manage and curate a particular collection of content. For example, the curation interface  1808  enables an event organizer to curate a collection of content relating to a specific event (e.g., delete inappropriate content or redundant messages). Additionally, the collection management system  1804  employs machine vision (or image recognition technology) and content rules to automatically curate a content collection. In certain embodiments, compensation may be paid to a user for inclusion of user-generated content into a collection. In such cases, the curation interface  1808  operates to automatically make payments to such users for the use of their content. 
     The annotation system  1806  provides various functions that enable a user to annotate or otherwise modify or edit media content associated with a message. For example, the annotation system  1806  provides functions related to the generation and publishing of media overlays for messages processed by the diagrammatic representation of a network environment  100 . The annotation system  1806  operatively supplies a media overlay or supplementation (e.g., an image filter) to the messaging client application  108  based on a geolocation of the client device  102 . In another example, the annotation system  1806  operatively supplies a media overlay to the messaging client application  108  based on other information, such as social network information of the user of the client device  102 . A media overlay may include audio and visual content and visual effects. Examples of audio and visual content include pictures, texts, logos, animations, and sound effects. An example of a visual effect includes color overlaying. The audio and visual content or the visual effects can be applied to a media content item (e.g., a photo) at the client device  102 . For example, the media overlay may include text that can be overlaid on top of a photograph taken by the client device  102 . In another example, the media overlay includes an identification of a location overlay (e.g., Venice beach), a name of a live event, or a name of a merchant overlay (e.g., Beach Coffee House). In another example, the annotation system  1806  uses the geolocation of the client device  102  to identify a media overlay that includes the name of a merchant at the geolocation of the client device  102 . The media overlay may include other indicia associated with the merchant. The media overlays may be stored in the database  122  and accessed through the database server  120 . 
     In one example embodiment, the annotation system  1806  provides a user-based publication platform that enables users to select a geolocation on a map, and upload content associated with the selected geolocation. The user may also specify circumstances under which a particular media overlay should be offered to other users. The annotation system  1806  generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geolocation. 
     In another example embodiment, the annotation system  1806  provides a merchant-based publication platform that enables merchants to select a particular media overlay associated with a geolocation via a bidding process. For example, the annotation system  1806  associates the media overlay of a highest bidding merchant with a corresponding geolocation for a predefined amount of time.