Patent Application
20180270605
The publish-subscribe (or “PubSub”) pattern is a data communication messaging arrangement implemented by software systems where so-called publishers publish messages to topics and so-called subscribers receive the messages pertaining to particular topics to which they are subscribed. There can be one or more publishers per topic and publishers generally have no knowledge of what subscribers, if any, will receive the published messages. Because publishers may publish large volumes of messages, and subscribers may subscribe to many topics (or “channels”) the overall volume of messages directed to a particular channel and/or subscriber may be difficult to manage.
As described herein, a PubSub messaging system may provide messages including geographical or other location-based data associated with one or more users or entities associated with the system. Real-time geolocation information may be useful in many applications. For example, real-time location sharing between large numbers of client devices can be provided to various applications providing location-based services. Such location-based services can access and interact with location-based data using application programming interface (API) commands to subscribe to channels, publish data on channels, or otherwise use location-based data communicated through a PubSub messaging system.
In some embodiments, a PubSub system can provide real-time location data for an expanded number of client devices that are not supported by other systems. Providing a highly-scalable PubSub system improves capabilities and operation of large-scale applications. For example, nation-wide taxi locator services, global flight location tracking, user flow analytics for large-size chain shopping malls, location-based messaging systems, and various other applications may be improved using message publishing on a Pub Sub system to communicate and interact with location-based data.
Described herein is a real-time geolocation sharing platform to handle communications between a highly-scalable number of client devices with minimal latency. Using the PubSub system, the present disclosure describes protocols and APIs for location-based services developers, among others. Client devices and other entities can then execute one or more applications that use the described protocols and APIs to provide location-based services to users.
For purposes of illustration and not limitation, examples of applications implemented on a PubSub platform to provide various location-based solutions are provided and discussed below. However, the PubSub platform described herein can be used for any location-based application in which geolocation information can be shared among a pool of users. In addition, for purposes of illustration and not limitation, various details of a PubSub platform are described below. However, the present disclosure can be implemented using any suitable real-time platform that is capable of transmitting and processing large amounts of data in or near real-time with low latency.
A location analysis platform allows real-time sharing of geolocations, so that users can see the geolocations of other users who are sharing their geolocations at the same time. The platform is based on a PubSub platform, which provides real-time messaging services between multiple entities and users. In some embodiments, the platform can allow users to create or subscribe to channels, on which real-time geolocations of end users are published. The platform may also provide location data associated with different users to a number of applications operating with access to the information provided on one or more channels of the platform.
In some embodiments, a location analysis platform may have multiple layers, through which interaction and use of location-based data can be performed. For example, A PubSub layer may provide a massive real-time messaging platform, which enables developers to create or publish new messaging channels or subscribe to existing channels, where messages are delivered in real-time (e.g., with low latency). An API layer can provide access and control of information by applications based on the location analysis platform. The API layer may provide access to channels containing location-based data for various programming languages such that software developers can generate applications to share geolocations with minimum effort. An application layer may contain various software applications that are built based on the PubSub platform and related APIs. In some embodiments, the applications can be deployed on devices that can provide real-time geolocation information (e.g., smart phones or tablets with GPS units). For example, different client devices may have different hardware to provide various location-based data. Some client devices may include a GPS device to provide a global position. Some client devices may alternatively or additionally provide location-based information including local wireless networks, IP addresses, or other information that can provide an indication of the client device's location. These client devices can then execute applications that perform one or more tasks for the user based on received location-based data. An analytics layer may also analyze the geolocation data shared on the PubSub platform, and then provide statistics and automatic decisions to users. These analytics may be provided to particular applications, particular users, or other entities based on the subscribers to particular channels. In some embodiments, the analytics layer may include one or more machine learning models or other analytics engines for developing actionable analytics for applications based on the received data.
In some embodiments, the PubSub platform is a general platform, on which any application can subscribe to and publish to various channels. Users can create their own channels, which could be either public or private, to share the location-based data they would like to share. The location-based data of the user can be obtained using any suitable technology. For example, the user's mobile device may include a GPS, an IP translation device to translate a device IP to a geographical location, cell phone tower triangulation, and so forth, which can then be shared with any number of other users using the PubSub platform. Users can also choose to subscribe to existing channels to get real-time, location-based data on those channels, or publish on existing channels to share their real-time, location-based data on those channels. The flexibility provided by the PubSub platform thus encourages the sharing of user location information and generation of user-created applications.
In the PubSub platform architecture above, the client devices can publish and/or subscribe to channels 1 . . . N (where N can be any suitable number) in the PubSub platform. As discussed previously, the API layer encapsulates the PubSub layer, which can allow software developers to create programs that can access and utilize shared locations of each of the client devices and send such location-based data to any other device. In some embodiments, the client devices can also be configured to communicate with a location analysis management system that can provide information and functionality such as, for example, updated channel lists, channel list control, the ability to create channels, and other like information and functionality for use by those client devices. The location analysis management system can be configured to communicate with a suitable application (e.g., built using the APIs of the API layer to encapsulate the PubSub platform) through, for example, one or more subscribed channels (e.g., channels 1 . . . N) to monitor existing channels created by or for the client devices, maintain a log of such transactions/events, and the like.
The location analysis management system can also include an analytics system. The analytics system can subscribe to and read data from any or all of the channels (e.g., channels 1 . . . N), and use the data to, for example, generate and provide data statistics and analytics. For purposes of illustration and not limitation, with car geolocation data, the analytics system can provide better route planning for drivers. As another example, the analytics system can aggregate all of the taxi geolocation information and then balance the distribution of taxis on a map by giving taxi drivers suggested directions. The analytics system can also provide the taxi drivers with hints or suggestions showing the places where many customers are waiting for taxis, when taxi customers are also using the PubSub platform to view the real-time geolocations of the taxis. In the present example, the analytics system can link taxi drivers with customers. Moreover, the analytics system can use machine learning or other suitable techniques to analyze historic data to predict which place(s) will have more or the most customers in the next period of time (e.g., the next few hours) so that the appropriate number of taxis can be allocated to the appropriate location(s) before traffic jams occur.
In some embodiments, example applications can include, but are not limited to, sharing location-based data while in a wilderness with park rangers/patrols in case of disaster/incident, sharing shuttle geolocation information within a company, sharing location-based data among friends for a gathering, providing a geolocation alarm when users reach a given place or destination, sharing taxi geolocation information in a taxi company to serve taxi orders more efficiently, sharing geolocations of cars in a live racing event, or sharing other location-based data of one or more client devices to provide a location-based service to a user. Other example applications are possible.
Depending on the configuration, a PubSub system can be categorized as follows:
There is no separate operation needed to create a named channel. A channel is created implicitly when the channel is subscribed to or when a message is published to the channel. In some implementations, channel names can be qualified by a name space. A name space comprises one or more channel names. Different name spaces can have the same channel names without causing ambiguity. The name space name can be a prefix of a channel name where the name space and channel name are separated by a dot or other suitable separator. In some implementations, name spaces can be used when specifying channel authorization settings. For instance, the messaging system 100 may have app1.foo and app1.system.notifications channels where “app1” is the name of the name space. The system can allow clients to subscribe and publish to the app1.foo channel. However, clients can only subscribe to, but not publish to the app1.system.notifications channel.
The operating system 108 layer comprises the operating system software on the client 102. In various implementations, messages can be sent and received to/from the system 100 using persistent or non-persistent connections. Persistent connections can be created using, for example, network sockets. A transport protocol such as TCP/IP layer 112 implements the Transport Control Protocol/Internet Protocol communication with the system 100 that can be used by the messaging layer 106 to send messages over connections to the system 100. Other communication protocols are possible including, for example, User Datagram Protocol (UDP). In further implementations, an optional Transport Layer Security (TLS) layer 110 can be employed to ensure the confidentiality of the messages.
In the example messaging system 100, one or more client devices (publishers and/or subscribers) establish respective persistent connections (e.g., TCP connections) to an MX node (e.g., MX node 204). The MX node serves as a termination point for these connections. For instance, external messages (e.g., between respective client devices and the MX node) carried by these connections can be encoded based on an external protocol (e.g., JSON). The MX node terminates the external protocol and translates the external messages to internal communication, and vice versa. The MX nodes publish and subscribe to streamlets on behalf of clients. In this way, an MX node can multiplex and merge requests of client devices subscribing for or publishing to the same channel, thus representing multiple client devices as one, instead of one by one.
In the example messaging system 100, a Q node (e.g., Q node 208) can store one or more streamlets of one or more channel streams. A streamlet is a data buffer for a portion of a channel stream. A streamlet will close to writing when its storage is full. A streamlet will close to reading and writing and be de-allocated when its time-to-live (TTL) has expired. By way of illustration, a streamlet can have a maximum size of 1 MB and a TTL of three minutes. Different channels can have streamlets limited by different sizes and/or by different TTLs. For instance, streamlets in one channel can exist for up to three minutes, while streamlets in another channel can exist for up to 10 minutes. In various implementations, a streamlet corresponds to a computing process running on a Q node. The computing process can be terminated after the streamlet's TTL has expired, thus freeing up computing resources (for the streamlet) back to the Q node, for example.
When receiving a publish request from a client device, an MX node (e.g., MX node 204) makes a request to a configuration manager (e.g., configuration manager 214) to grant access to a streamlet to write the message being published. Note, however, that if the MX node has already been granted write access to a streamlet for the channel (and the channel has not been closed to writing), the MX node can write the message to that streamlet without having to request a grant to access the streamlet. Once a message is written to a streamlet for a channel, the message can be read by MX nodes and provided to subscribers of that channel.
Similarly, when receiving a channel subscription request from a client device, an MX node makes a request to a configuration manager to grant access to a streamlet for the channel from which messages are read. If the MX node has already been granted read access to a streamlet for the channel (and the channel's TTL has not been closed to reading), the MX node can read messages from the streamlet without having to request a grant to access the streamlet. The read messages can then be forwarded to client devices that have subscribed to the channel. In various implementations, messages read from streamlets are cached by MX nodes so that MX nodes can reduce the number of times needed to read from the streamlets.
By way of illustration, an MX node can request a grant from the configuration manager that allows the MX node to store a block of data into a streamlet on a particular Q node that stores streamlets of the particular channel. Example streamlet grant request and grant data structures are as follows:
The StreamletGrantRequest data structure stores the name of the stream channel and a mode indicating whether the MX node intends on reading from or writing to the streamlet. The MX node sends the StreamletGrantRequest to a configuration manager node. The configuration manager node, in response, sends the MX node a StreamletGrantResponse data structure. The StreamletGrantResponse contains an identifier of the streamlet (streamlet-id), the maximum size of the streamlet (limit-size), the maximum number of messages that the streamlet can store (limit-msgs), the TTL (limit-life), and an identifier of a Q node (q-node) on which the streamlet resides. The StreamletGrantRequest and StreamletGrantResponse can also have a position field that points to a position in a streamlet (or a position in a channel) for reading from the streamlet.
A grant becomes invalid once the streamlet has closed. For example, a streamlet is closed to reading and writing once the streamlet's TTL has expired and a streamlet is closed to writing when the streamlet's storage is full. When a grant becomes invalid, the MX node can request a new grant from the configuration manager to read from or write to a streamlet. The new grant will reference a different streamlet and will refer to the same or a different Q node depending on where the new streamlet resides.
The MX node then sends a prepare-publish message with an identifier of a streamlet that the MX node wants to write to the Q node (304). The streamlet identifier and Q node identifier can be provided by the configuration manager in the write grant as described earlier. The Q node hands over the message to a handler process 301 (e.g., a computing process running on the Q node) for the identified streamlet (306). The handler process can send to the MX node an acknowledgement (308). After receiving the acknowledgement, the MX node starts writing (publishing) messages (e.g., 310, 312, 314, and 318) to the handler process, which in turn stores the received data in the identified streamlet. The handler process can also send acknowledgements (316, 320) to the MX node for the received data. In some implementations, acknowledgements can be piggy-backed or cumulative. For instance, the handler process can send to the MX node an acknowledgement for every predetermined amount of data received (e.g., for every 100 messages received) or for every predetermined time period (e.g., for every one millisecond). Other acknowledgement scheduling algorithms, such as Nagle's algorithm, can be used.
If the streamlet can no longer accept published data (e.g., when the streamlet is full), the handler process sends a Negative-Acknowledgement (NAK) message (330) indicating a problem, following by an EOF (end-of-file) message (332). In this way, the handler process closes the association with the MX node for the publish grant. The MX node can then request a write grant for another streamlet from a configuration manager if the MX node has additional messages to store.
The MX node then sends to the Q node a subscribe message (354) with the identifier of the streamlet (in the Q node) and the position in the streamlet from which the MX node wants to read (356). The Q node hands over the subscribe message to a handler process 351 for the streamlet (356). The handler process can send to the MX node an acknowledgement (358). The handler process then sends messages (360, 364, 366), starting at the position in the streamlet, to the MX node. In some implementations, the handler process can send all of the messages in the streamlet to the MX node. After sending the last message in a particular streamlet, the handler process can send a notification of the last message to the MX node. The MX node can send to the configuration manager another request for another streamlet containing a next message in the particular channel.
If the particular streamlet is closed (e.g., after its TTL has expired), the handler process can send an unsubscribe message (390), followed by an EOF message (392), to close the association with the MX node for the read grant. The MX node can close the association with the handler process when the MX node moves to another streamlet for messages in the particular channel (e.g., as instructed by the configuration manager). The MX node can also close the association with the handler process if the MX node receives an unsubscribe message from a corresponding client device.
In various implementations, a streamlet can be written into and read from at the same time instance. For example, there can be a valid read grant and a valid write grant at the same time instance. In various implementations, a streamlet can be read concurrently by multiple read grants (e.g., for channels subscribed to by multiple publisher clients). The handler process of the streamlet can order messages from concurrent write grants based on, for example, time-of-arrival, and store the messages based on the order. In this way, messages published to a channel from multiple publisher clients can be serialized and stored in a streamlet of the channel.
In the messaging system 100, one or more C nodes (e.g., C node 220) can offload data transfers from one or more Q nodes. For instance, if there are many MX nodes requesting streamlets from Q nodes for a particular channel, the streamlets can be offloaded and cached in one or more C nodes. The MX nodes (e.g., as instructed by read grants from a configuration manager) can read the streamlets from the C nodes instead.
As described above, messages for a channel in the messaging system 100 are ordered in a channel stream. A configuration manager (e.g., configuration manager 214) splits the channel stream into fixed-sized streamlets that each reside on a respective Q node. In this way, storing a channel stream can be shared among many Q nodes; each Q node stores a portion (one or more streamlets) of the channel stream. More particularly, a streamlet can be stored in, for example, registers and/or dynamic memory elements associated with a computing process on a Q node, thus avoiding the need to access persistent, slower storage devices such as hard disks. This results in faster message access. The configuration manager can also balance load among Q nodes in the messaging system 100 by monitoring respective workloads of the Q nodes and allocating streamlets in a way that avoids overloading any one Q node.
In various implementations, a configuration manager maintains a list identifying each active streamlet, the respective Q node on which the streamlet resides, an identification of the position of the first message in the streamlet, and whether the streamlet is closed for writing. In some implementations, Q nodes notify the configuration manager and/or any MX nodes that are publishing to a streamlet that the streamlet is closed due to being full or when the streamlet's TTL has expired. When a streamlet is closed, the streamlet remains on the configuration manager's list of active streamlets until the streamlet's TTL has expired so that MX nodes can continue to retrieve messages from the streamlet.
When an MX node requests a write grant for a given channel and there is not a streamlet for the channel that can be written to, the configuration manager allocates a new streamlet on one of the Q nodes and returns the identity of the streamlet and the Q node in the StreamletGrantResponse. Otherwise, the configuration manager returns the identity of the currently open for writing streamlet and corresponding Q node in the StreamletGrantResponse. MX nodes can publish messages to the streamlet until the streamlet is full or the streamlet's TTL has expired, after which a new streamlet can be allocated by the configuration manager.
When an MX node requests a read grant for a given channel and there is not a streamlet for the channel that can be read from, the configuration manager allocates a new streamlet on one of the Q nodes and returns the identity of the streamlet and the Q node in the StreamletGrantResponse. Otherwise, the configuration manager returns the identity of the streamlet and Q node that contains the position from which the MX node wishes to read. The Q node can then begin sending messages to the MX node from the streamlet beginning at the specified position until there are no more messages in the streamlet to send. When a new message is published to a streamlet, MX nodes that have subscribed to that streamlet will receive the new message. If a streamlet's TTL has expired, the handler process 351 can send an EOF message (392) to any MX nodes that are subscribed to the streamlet.
In some implementations, the messaging system 100 can include multiple configuration managers (e.g., configuration manager 214 plus one or more other configuration managers). Multiple configuration managers can provide resiliency and prevent single point of failure. For instance, one configuration manager can replicate lists of streamlets and current grants it maintains to another “slave” configuration manager. As another example, multiple configuration managers can coordinate operations between them using distributed consensus protocols, such as, for example, Paxos or Raft protocols.
By way of illustration, each publish request (e.g., in JSON key/value pairs) from a publisher to an MX node includes a channel name and a message. The MX node (e.g., MX node 202) can assign the message in the publish request to a distinct channel in the messaging system 100 based on the channel name (e.g., “foo”) of the publish request. The MX node can confirm the assigned channel with the configuration manager 214. If the channel (specified in the subscribe request) does not yet exist in the messaging system 100, the configuration manager can create and maintain a new channel in the messaging system 100. For instance, the configuration manager can maintain a new channel by maintaining a list identifying each active streamlet of the channel's stream, the respective Q node on which the streamlet resides, and identification of the positions of the first and last messages in the streamlet as described earlier.
For messages of a particular channel, the MX node can store the messages in one or more buffers or streamlets in the messaging system 100. For instance, the MX node 202 receives from the publishers 402 requests to publish messages M11, M12, M13, and M14 to a channel foo. The MX node 206 receives from the publishers 404 requests to publish messages M78 and M79 to the channel foo. The MX node 204 receives from the publishers 406 requests to publish messages M26, M27, M28, M29, M30, and M31 to the channel foo.
The MX nodes can identify one or more streamlets for storing messages for the channel foo. As described earlier, each MX node can request a write grant from the configuration manager 214 that allows the MX node to store the messages in a streamlet of the channel foo. For instance, the MX node 202 receives a grant from the configuration manager 214 to write messages M11, M12, M13, and M14 to a streamlet 4101 on the Q node 212. The MX node 206 receives a grant from the configuration manager 214 to write messages M78 and M79 to the streamlet 4101. Here, the streamlet 4101 is the last one (at the moment) of a sequence of streamlets of the channel stream 430 storing messages of the channel foo. The streamlet 4101 has messages (421) of the channel foo that were previously stored in the streamlet 4101, but is still open, i.e., the streamlet 4101 still has space for storing more messages and the streamlet's TTL has not expired.
The MX node 202 can arrange the messages for the channel foo based on the respective time that each message was received by the MX node 202, e.g., M11, M13, M14, M12 (422), and store the received messages as arranged in the streamlet 4101. That is, the MX node 202 receives M11 first, followed by M13, M14, and M12. Similarly, the MX node 206 can arrange the messages for the channel foo based on their respective time that each message was received by the MX node 206, e.g., M78, M79 (423), and store the received messages as arranged in the streamlet 4101. Other arrangements or ordering of the messages for the channel are possible.
The MX node 202 (or MX node 206) can store the received messages using the method for writing data to a streamlet described earlier in reference to
In various implementations, the Q node 212 (e.g., a handler process) stores the messages of the channel foo in the streamlet 4101 in the order as arranged by the MX node 202 and MX node 206. The Q node 212 stores the messages of the channel foo in the streamlet 4101 in the order the Q node 212 receives the messages. For instance, assume that the Q node 212 receives messages M78 (from the MX node 206) first, followed by messages M11 and M13 (from the MX node 202), M79 (from the MX node 206), and M14 and M12 (from the MX node 202). The Q node 212 stores in the streamlet 4101 the messages in the order as received, e.g., M78, M11, M13, M79, M14, and M12, immediately after the messages 421 that are already stored in the streamlet 4101. In this way, messages published to the channel foo from multiple publishers (e.g., 402, 404) can be serialized in a particular order and stored in the streamlet 4101 of the channel foo. Different subscribers that subscribe to the channel foo will receive messages of the channel foo in the same particular order, as will be described in more detail in reference to
In the example of
By way of illustration, assume that the message M26 is stored to the last available position of the streamlet 4101. As the streamlet 4101 is now full, the Q node 212 sends to the MX node 204 a NAK message, following by an EOF message, to close the association with the MX node 204 for the write grant, as described earlier in reference to
The configuration manager 214 can monitor available Q nodes in the messaging system 100 for their respective workloads (e.g., how many streamlets are residing in each Q node). The configuration manager 214 can allocate a streamlet for the write request from the MX node 204 such that overloading (e.g., too many streamlets or too many read or write grants) can be avoided for any given Q node. For instance, the configuration manager 214 can identify a least loaded Q node in the messaging system 100 and allocate a new streamlet on the least loaded Q node for write requests from the MX node 204. In the example of
When the configuration manager 214 allocates a new streamlet (e.g., streamlet 4102) for a request for a grant from an MX node (e.g., MX node 204) to write to a channel (e.g., foo), the configuration manager 214 assigns to the streamlet its TTL, which will expire after TTLs of other streamlets that are already in the channel's stream. For instance, the configuration manager 214 can assign to each streamlet of the channel foo's channel stream a TTL of 3 minutes when allocating the streamlet. That is, each streamlet will expire 3 minutes after it is allocated (created) by the configuration manager 214. Since a new streamlet is allocated after a previous streamlet is closed (e.g., filled entirely or expired), in this way, the channel foo's channel stream comprises streamlets that each expires sequentially after its previous streamlet expires. For instance, as shown in an example channel stream 430 of the channel foo in
A subscriber (e.g., subscriber 480) can subscribe to the channel foo of the messaging system 100 by establishing a connection (e.g., 462) and sending a request for subscribing to messages of the channel foo to an MX node (e.g., MX node 461). The request (e.g., in JSON key/value pairs) can include a channel name, such as, for example, “foo.” When receiving the subscribe request, the MX node 461 can send to the configuration manager 214 a request for a read grant for a streamlet in the channel foo's channel stream.
By way of illustration, assume that at the current moment the channel foo's channel stream 431 includes active streamlets 4102, 4103, and 4104, as shown in
The MX node 461 can request a read grant for all available messages in the channel foo, for example, when the subscriber 480 is a new subscriber to the channel foo. Based on the request, the configuration manager 214 provides the MX node 461 a read grant to the streamlet 4102 (on the Q node 208) that is the earliest streamlet in the active streamlets of the channel foo (i.e., the first in the sequence of the active streamlets). The MX node 461 can retrieve messages in the streamlet 4102 from the Q node 208, using the method for reading data from a streamlet described earlier in reference to
After receiving the last message in the streamlet 4102, the MX node 461 can send an acknowledgement to the Q node 208, and send to the configuration manager 214 another request (e.g., for a read grant) for the next streamlet in the channel stream of the channel foo. Based on the request, the configuration manager 214 provides the MX node 461 a read grant to the streamlet 4103 (on Q node 472) that logically follows the streamlet 4102 in the sequence of active streamlets of the channel foo. The MX node 461 can retrieve messages stored in the streamlet 4103, e.g., using the method for reading data from a streamlet described earlier in reference to
The MX node 461 can send the retrieved messages of the channel foo to the subscriber 480 (via the connection 462) while receiving the messages from the Q nodes 208, 472, or 474. In various implementations, the MX node 461 can store the retrieved messages in a local buffer. In this way, the retrieved messages can be provided to another subscriber (e.g., subscriber 482) when the other subscriber subscribes to the channel foo and requests the channel's messages. The MX node 461 can remove messages stored in the local buffer that each has a time of publication that has exceeded a predetermined time period. For instance, the MX node 461 can remove messages (stored in the local buffer) with respective times of publication exceeding 3 minutes. In some implementations, the predetermined time period for keeping messages in the local buffer on MX node 461 can be the same as or similar to the time-to-live duration of a streamlet in the channel foo's channel stream, since at a given moment, messages retrieved from the channel's stream do not include those in streamlets having respective times-to-live that had already expired.
The messages retrieved from the channel stream 431 and sent to the subscriber 480 (by the MX node 461) are arranged in the same order as the messages were stored in the channel stream, although other arrangements or ordering of the messages are possible. For instance, messages published to the channel foo are serialized and stored in the streamlet 4102 in a particular order (e.g., M27, M31, M29, M30, and so on), then stored subsequently in the streamlet 4103 and the streamlet 4104. The MX node retrieves messages from the channel stream 431 and provides the retrieved messages to the subscriber 480 in the same order as the messages are stored in the channel stream: M27, M31, M29, M30, and so on, followed by ordered messages in the streamlet 4103, and followed by ordered messages in the streamlet 4104.
Instead of retrieving all available messages in the channel stream 431, the MX node 461 can request a read grant for messages stored in the channel stream 431 starting from a message at particular position, e.g., position 47202. For instance, the position 47202 can correspond to an earlier time instance (e.g., 10 seconds before the current time) when the subscriber 480 was last subscribing to the channel foo (e.g., via a connection to the MX node 461 or another MX node of the messaging system 100). The MX node 461 can send to the configuration manager 214 a request for a read grant for messages starting at the position 47202. Based on the request, the configuration manager 214 provides the MX node 461 a read grant to the streamlet 4104 (on the Q node 474) and a position on the streamlet 4104 that corresponds to the channel stream position 47202. The MX node 461 can retrieve messages in the streamlet 4104 starting from the provided position, and send the retrieved messages to the subscriber 480.
As described above in reference to
In various implementations, a streamlet stores messages in a set of blocks of messages. Each block stores a number of messages. For instance, a block can store two hundred kilobytes of messages (although other sizes of blocks of messages are possible). Each block has its own time-to-live, which can be shorter than the time-to-live of the streamlet holding the block. Once a block's TTL has expired, the block can be discarded from the streamlet holding the block, as described in more detail below in reference to
By way of illustration, the streamlet 4104 (e.g., a computing process running on the Q node 474 shown in
When the streamlet 4104 was created (e.g., by a write grant), a first block (sub-buffer) 492 was created to store messages, e.g., from channel positions 47010 to 47100. Later on, after the block 492 had reached its capacity, another block 493 was created to store messages, e.g., from channel positions 47111 to 47300. Blocks 494 and 495 were subsequently created to store additional messages. Afterwards, the streamlet 4104 was closed for additional message writes, and the streamlet 4105 was created with additional blocks for storing additional messages of the channel foo.
In this example, the respective TTL's of blocks 492 and 493 had expired. The messages stored in these two blocks (from channel positions 47010 to 47300) are no longer available for reading by subscribers of the channel foo. The streamlet 4104 can discard these two expired blocks, e.g., by de-allocating the memory space for the blocks 492 and 493. The blocks 494 or 495 could become expired and be discarded by the streamlet 4104, before the streamlet 4104 itself becomes invalid. Alternatively, streamlet 4104 itself could become invalid before the blocks 494 or 495 become expired. In this way, a streamlet can hold one or more blocks of messages, or contain no block of messages, depending on respective TTLs of the streamlet and blocks, for example.
A streamlet, or a computing process running on a Q node in the messaging system 100, can create a block for storing messages of a channel by allocating a certain size of memory space from the Q node. The streamlet can receive, from an MX node in the messaging system 100, one message at a time and store the received message in the block. Alternatively, the MX node can assemble (i.e., buffer) a group of messages and send the group of messages to the Q node. The streamlet can allocate a block of memory space (from the Q node) and store the group of messages in the block. The MX node can also perform compression on the group of messages, e.g., by removing a common header from each message or performing other suitable compression techniques.
As described above, a streamlet (a data buffer) residing on a Q node stores messages of a channel in the messaging system 100. To prevent failure of the Q node (a single point failure) that can cause messages being lost, the messaging system 100 can replicate messages on multiple Q nodes, as described in more detail below.
By way of illustration, the configuration manager 214 allocates Q nodes 208, 502, 504, and 506 in the messaging system 100 to store copies of the streamlet 4102. The configuration manager 214 instructs the MX node 204 to transmit the messages for the channel foo (e.g., messages M27, M31, M29, M30, and M28) to the Q node 208 (512). A computing process running on the Q node 208 stores the messages in the first copy (copy #1) of the streamlet 4102. Instead of sending an acknowledgement message to the MX node 204 after storing the messages, the Q node 208 forwards the messages to the Q node 502 (514). A computing process running on the Q node 502 stores the messages in another copy (copy #2) of the streamlet 4102. Meanwhile, the Q node 502 forwards the messages to the Q node 504 (516). A computing process running on the Q node 504 stores the messages in yet another copy (copy #3) of the streamlet 4102. The Q node 504 also forwards the message to the Q node 506 (518). A computing process running on the Q node 506 stores the messages in yet another copy (copy #4) of the streamlet 4102. The Q node 506 can send an acknowledgement message to the MX node 204, indicating that all the messages (M27, M31, M29, M30, and M28) have been stored successfully in streamlet copies #1, #2, #3 and #4.
In some implementations, after successfully storing the last copy (copy #4), the Q node 506 can send an acknowledgement to its upstream Q node (504), which in turns sends an acknowledgement to its upstream Q node (502), and so on, until the acknowledgement is sent to the Q node 208 storing the first copy (copy #1). The Q node 208 can send an acknowledgement message to the MX node 204, indicating that all messages have been stored successfully in the streamlet 4102 (i.e., in the copies #1, #2, #3 and #4).
In this way, four copies of the streamlet 4102 (and each message in the streamlet) are stored in four different Q nodes. Other numbers (e.g., two, three, five, or other suitable number) of copies of a streamlet are also possible. In the present illustration, the four copies form a chain of copies including a head copy in the copy #1 and a tail copy in the copy #4. When a new message is published to the streamlet 4102, the message is first stored in the head copy (copy #1) on the Q node 208. The message is then forwarded downstream to the next adjacent copy, the copy #2 on the Q node 502 for storage, then to the copy #3 on the Q node 504 for storage, until the message is stored in the tail copy the copy #4 on the Q node 506.
In addition to storing and forwarding by messages, the computing processes running on Q nodes that store copies of a streamlet can also store and forward messages by blocks of messages, as described earlier in reference to
Messages of the streamlet 4102 can be retrieved and delivered to a subscriber of the channel foo from one of the copies of the streamlet 4102.
A Q node storing a particular copy in a chain of copies of a streamlet may fail, e.g., a computing process on the Q node storing the particular copy may freeze. Other failure modes of a Q node are possible. An MX node can detect a failed node (e.g., from non-responsiveness of the failed node) and report the failed node to a configuration manager in the messaging system 100 (e.g., configuration manager 214). A peer Q node can also detect a failed Q node and report the failed node to the configuration manager. For instance, an upstream Q node may detect a failed downstream Q node when the downstream Q node is non-responsive, e.g., fails to acknowledge a message storage request from the upstream Q node as described earlier. It is noted that failure of a Q node storing a copy of a particular streamlet of a particular channel stream does not have to be for publish or subscribe operations of the particular streamlet or of the particular channel stream. Failure stemming from operations on another streamlet or another channel stream can also alert a configuration manager about failure of a Q node in the messaging system 100.
When a Q node storing a particular copy in a chain of copies of a streamlet fails, a configuration manager in the messaging system 100 can repair the chain by removing the failed node, or by inserting a new node for a new copy into the chain, for example.
Here, a failed node can also be the node storing the head copy or the tail copy of the chain of copies. For instance, if the Q node 208 fails, the configuration manager 214 can instruct the MX node 204 first to send the message to the Q node 502 for storage in the copy #2 of the streamlet 4102. The message is then forwarded to the next adjacent copy in the chain for storage, until the message is stored in the tail copy.
If the Q node 506 fails, the configuration manager 214 can repair the chain of copies of the streamlet 4102 such that the copy #3 on the Q node 504 becomes the tail copy of the chain. A message is first stored in the copy #1 on the Q node 208, then subsequently stored in the copy #2 on the Q node 502, and the copy #3 on the Q node 504. The Q node 504 then can send an acknowledgement message to the configuration manager 214 indicating that the message has been stored successfully.
In
A filter 606 can be created by providing suitable query instructions at, for example, the time the subscriber 602 subscribes to the channel 608. The filter 606 that is specified can be applied to all messages published to the channel 608 (e.g., one message at a time), and can be evaluated before the subscriber 602 receives the messages (e.g., see Step 2 in
The query instructions can implement real-time searches and queries, aggregate or summarize data, or transform data for use by a subscriber application. In some embodiments, including those implementing JSON formatted messages, the messages can be generated, parsed and interpreted using the query instructions, and the lack of a pre-defined schema (unlike conventional RDBMS/SQL-based applications) means that the query instructions can adapt to changing business needs without the need for schema or application layer changes. This allows the query instructions to be applied selectively at the message level within a channel, thus filtering and/or aggregating messages within the channel. In some instances, the queries may be applied at the publisher level—meaning channels that receive messages from more than one publisher may apply certain filters against messages from specific publishers. The query instructions may be applied on a going-forward basis, that is on only newly arriving messages, and/or in some cases, the query instructions may be applied to historical messages already residing in the channel queue.
The query instructions can be applied at either or both of the ingress and egress side of the PubSub service. On the egress side, the query instructions act as a per-connection filter against the message channels, and allow each subscriber to manage their own set of unique filters. On the ingress side, the query instructions operate as a centralized, system-wide filter that is applied to all published messages.
For purposes of illustration and not limitation, examples of query instructions that may be applied during message ingress include:
For purposes of illustration and not limitation, examples of query instructions that may be applied during message egress include:
In some embodiments, the query instructions may be used to define an index or other suitable temporary data structure, which may then be applied against the messages as they are received into the channel to allow for the reuse of the data element(s) as searchable elements. In such cases, a query frequency may be maintained to describe the number of times (general, or in a given period) that a particular data element is referred to or how that element is used. If the frequency that the data element is used in a query exceeds some threshold, the index may be stored for subsequent use on incoming messages, whereas in other instances in which the index is used only once (or infrequently) it may be discarded. In some instances, the query instruction may be applied to messages having arrived at the channel prior to the creation of the index. Thus, the messages are not indexed according to the data elements described in the query instructions but processed using the query instructions regardless, whereas messages arriving after the creation of the index may be filtered and processed using the index. For queries or other subscriptions that span the time at which the index may have been created, the results of applying the query instructions to the messages as they are received and processed with the index may be combined with results of applying the query instructions to non-indexed messages received prior to receipt of the query instructions.
For purposes of illustration and not limitation, one use case for such a filtering application is a mapping application that subscribes to public transportation data feeds, such as the locations of all buses across a city. The published messages may include, for example, geographic data describing the location, status, bus agency, ID number, route number, and route name of the buses. Absent pre-defined query instructions, the client application would receive individual messages for all buses. However, query instructions may be provided that filter out, for example, inactive routes and buses and aggregate, for example, a count of buses by agency. The subscriber application receives the filtered bus data in real time and can create reports, charts and other user-defined presentations of the data. When new data is published to the channel, the reports can be updated in real time based on a period parameter (described in more detail below).
The query instructions can be provided (e.g., at the time the subscriber subscribes to the channel) in any suitable format or syntax. For example, the following illustrates the structure of several fields of a sample subscription request Protocol Data Unit (PDU) with the PDU keys specific to adding a filter to a subscription request:
One example of a query instruction is a “select” filter, which selects the most recent (or “top”) value for all (e.g., “select.*”) or selected (e.g., “select.name”) data elements. In the example below, the Filter column shows the filter value sent in the query instructions as part of a subscription as the filter field. The Message Data column lists the input of the channel message data and the message data sent to the client as output. In this example, the value for the “extra” key does not appear in the output, as the “select” filter can return only the first level of results and does not return any nested key values.
For aggregative functions, all messages can be combined that satisfy the query instructions included in the GROUP BY clause. The aggregated values can then be published as a single message to the subscriber(s) at the end of the aggregation period. The number of messages that are aggregated depends on, for example, the number of messages received in the channel in the period value for the filter. For instance, if the period parameter is set to 1, and 100 messages are received in one second, all 100 messages are aggregated into a single message for transmission to the subscriber(s). As an example, a query instruction as shown below includes a filter to aggregate position data for an object, grouping it by obj_id, with a period of 1:
In some embodiments, a MERGE(*) function can be used to change how aggregated message data is merged. The MERGE(*) function can return a recursive union of incoming messages over a period of time. The merge function may be used, for example, to track location data for an object, and the subscriber is interested in the most recent values for all key/value pairs contained in a set of aggregated messages. The following statement shows an exemplary syntax for the MERGE(*) function:
The following examples illustrate how the MERGE(*) function may be applied within query instructions to various types of channel messages. In the following examples, the Filter column shows the filter value included in the query instructions as part of a subscription request as the FILTER field. The Message Data column lists the Input channel message data and the resulting message data sent to the subscriber as Output. The filter returns the most recent values of the keys identified in the input messages, with the string MERGE identified as the column name in the output message data. The first example below shows the MERGE(*) function in a filter with a wildcard, for the message data is returned using the keys from the input as column names in the output.
The next example illustrates the use of the MERGE(*) function in a filter using a wildcard and the “AS” statement with a value of MERGE. The output data includes MERGE as the column name.
Generally, for aggregative functions and for filters that only include a SELECT(expr) statement, only the latest value for any JSON key in the message data from the last message received can be stored and returned. Therefore, if the most recent message received that satisfies the filter statement is missing a key value identified in a previously processed message, that value is not included in the aggregate, which could result in data loss. However, filters that also include the MERGE(*) function can retain the most recent value for all keys that appear in messages to an unlimited JSON object depth. Accordingly, the most recent version of all key values can be retained in the aggregate.
The MERGE(*) function can be used to ensure that associated values for all keys that appear in any message during the aggregation period also appear in the final aggregated message. For example, a channel may track the physical location of an object in three dimensions: x, y, and z. During an aggregation period of one second, two messages are published to the channel, one having only two parameters: OBJ{x:1, y:2, z:3} and OBJ{x:2, y:3}. In the second message, the z value did not change and was not included in the second message. Without the MERGE(*) function, the output result would be OBJ{x:2, y:3}. Because the z value was not present in the last message in the aggregation period, the z value was not included in the final aggregate. However, with the MERGE(*) function, the result is OBJ{x:2, y:3, z:3}.
The following table shows one set of rules that may be used to aggregate data in messages, depending on the type of data. For arrays, elements need not be merged, but instead JSON values can be overwritten for the array in the aggregate with the last array value received.
The query instructions can be comprised of one or more suitable filter commands, statements, functions, or syntax. For purposes of illustration and not limitation, in addition to the SELECT and MERGE functions, the query instructions can include filter statements or functions, such as, for example, ABS(expr), AVG(expr), COALESCE(a[, b . . . ]), CONCAT(a[, b . . . ]), COUNT(expr), COUNT_DISTINCT(expr), IFNULL(expr1, expr2), JSON(expr), MIN(expr[, expr1, . . . ]), MAX(expr[, expr1, . . . ]), SUBSTR(expr, expr1[, expr2]), SUM(expr), MD5(expr), SHA1(expr), FIRST_VALUE(expr) OVER (ORDER BY expr1), and/or LAST_VALUE(expr) OVER (ORDER BY expr1), where “expr” can be any suitable expression that is capable of being processed by a filter statement or function, such as, for example, a SQL or SQL-like expression. Other suitable filter commands, statements, functions, or syntax are possible for the query instructions.
According to the present invention, non-filtered queries can translate to an immediate copy of the message to the subscriber, without any JSON or other like processing. Queries that include a SELECT filter command (without aggregation) can translate into an immediate filter. In instances in which the messages are formatted using JSON, each message may be individually parsed and any WHERE clause may be executed directly on the individual message as it arrives, without the need for creating indices or other temporary data structures. If the messages pass the WHERE clause filter, the SELECT clause results in a filtered message that can be converted back to its original format or structure (e.g., JSON) and sent to the subscriber.
Aggregative functions, such as, for example, COUNT( ), SUM( ), AVG( ), and the like, can translate into an immediate aggregator. In instances in which the messages are formatted using JSON, each message may be individually parsed and any WHERE clause may be executed directly on the individual message as it arrives, without the need for creating indices or other temporary data structures. If a WHERE clause is evaluated, messages passing such criteria are aggregated (e.g., aggregates in the SELECT clause are executed, thereby accumulating COUNT, SUM, AVG, and so forth) using the previous accumulated value and the value from the individual message. Once per aggregation period (e.g., every 1 second), the aggregates are computed (e.g., AVG=SUM/COUNT), and the SELECT clause outputs the aggregated message, which can be converted to its original format or structure (e.g., JSON) and sent to the subscriber.
More complex aggregative functions, such as, for example, GROUP BY, JOIN, HAVING, and the like, can be translated into a hash table aggregator. Unlike SELECT or other like functions that can use a constant memory, linearly expanding memory requirements can be dependent upon the results of the GROUP BY clause. At most, grouping by a unique value (e.g., SSN, etc.) can result in a group for each individual message, but in most cases grouping by a common data element (e.g., user_id or other repeating value) can result in far fewer groups. In practice, each message is parsed (from its JSON format, for example). The WHERE clause can be executed directly on the individual message as it arrives, without creating indices or other temporary structures. If the WHERE clause is satisfied, the GROUP BY expressions can be computed directly and used to build a hash key for the group. The aggregative functions in the SELECT clause can be executed, accumulating COUNT, SUM, AVG, or other functions using the previous accumulated value specific for the hash key (group) and the value from the individual message. Once per aggregation period (e.g., every 1 second), the aggregates are computed (e.g., AVG=SUM/COUNT) for each hash key (group), and the SELECT clause can output the aggregated message for each hash key to be converted back to its original format or structure (e.g., JSON) and sent to the subscriber (e.g., one message per hash key (group)).
In embodiments in which the aggregation period is limited (e.g., 1 second-60 seconds) and the network card or other hardware/throughput speeds may be limited (e.g., 10/gbps), the overall maximal memory consumption can be calculated as time*speed (e.g., 1 GB per second, or 60 GB per minute). Hence, the upper bound is independent of the number of subscribers. In certain implementations, each message only need be parsed once (e.g., if multiple filters are set by multiple clients) and only if needed based on the query instructions, as an empty filter does not require parsing the message.
Referring to
In some cases, the process defaults to sending only new, incoming messages that meet the query instructions on to the subscriber. However, a subscriber can subscribe with history and use a filter, such that the first message or messages sent to the subscriber can be the historical messages with the filter applied. Using the period of max_age and/or a “next” parameter provides additional functionality that allows for retrieval and filtering of historical messages.
More particularly, a max_age parameter included with the query instructions can facilitate the retrieval of historical messages that meet this parameter.
When a subscriber subscribes with a “next” parameter to a channel with a filter, the filter can be applied to all messages from the next value up to the current message stream position for the channel, and the results can be sent to the subscriber in, for example, a single batch. For example, as illustrated in
When a subscriber subscribes with a next parameter, chooses to receive historical messages on a channel, and includes a filter in the subscription, the subscriber can be updated to the current message stream position in multiple batches.
The query instructions can define how one or more filters can be applied to the incoming messages in any suitable manner. For example, the resulting filter(s) can be applied to any or all messages arriving in each period, to any or all messages arriving across multiple periods, to any or all messages arriving in select periods, or to any or all messages arriving on a continuous or substantially continuous basis (i.e., without the use of a period parameter such that messages are not retained before returning them to the subscriber). Such filtered messages can be batched in any suitable manner or sent individually (e.g., one message at a time) to subscribers. In particular, the filtered messages can be sent to the subscriber in any suitable format or syntax. For example, the following illustrates the structure of several fields of a sample channel PDU that contains the message results from a filter request:
In the above channel PDU, the “channel” field can be a value (e.g., string or other appropriate value or designation) of the channel name to which the subscriber has subscribed. The “next” field can provide the channel stream position of the batch of messages returned in the channel PDU. The “messages” field provides the channel data of the messages resulting from application of the specified filter. One or more messages can be returned in the “messages” field in such a channel PDU. It is noted that a channel PDU can include any other suitable fields, parameters, values, or data.
The client devices 810 can also include location devices 830, such as a GPS or other location aware system that provides an indication of the location of the client device 810 based on surrounding characteristics. The client devices 810 may publish and receive messages on one or more channels 842A-842N through the PubSub system 840 as well as additional information from the location analysis management system 850. In some embodiments, the information received from the location analysis management system 850 may also be received through one of channels 842A-842N of PubSub system 840.
The PubSub system 840 may be the same or similar to system 100 as described above. The PubSub system 840 may include a number of channels such as channel 1 842A through channel N 842N as shown in
In some embodiments, the PubSub system 840 may be encapsulated by an API layer that provides access to location-based data and location analysis on various channels 842A-842N of the PubSub system 840. For example, the PubSub system 840 can include an application interface 845 that provides data regarding location of one or more client devices 810 over the PubSub system 840. The application interface 845 may provide information regarding different client devices 810 in response to requests of particular information by the client device 810 or the location analysis management system 850.
The location analysis management system 850 may include an analysis service 855 that generates analysis data in response to location data provided by client devices 810 over the PubSub system 840. For example, there may be many client devices 810 providing location-based information over PubSub system 840 on one or more channels 842A-842N. The analysis service 855 may subscribe to one or more of the channels 842A-842N, on which one or more of the client devices 810 publish location-based data. The analysis service 855 may then generate analysis data based on the received location-based data. For example, the analysis service 855 may provide analysis of the number of client devices 810 in a given geographic area, the activity associated with client devices 810 in a geographic area, the proximity between users of an application 820 within a geographic area, or other analysis of client devices 810 publishing location-based data on one or more channels 842A-842N of the PubSub system 840.
In some embodiments, the location analysis management system 850 may publish results of analysis on the PubSub system 840 to one or more channels 842A-842N to which client devices 810 subscribe. In some embodiments, the location analysis management system 850 can provide analysis information to one or more applications 820 of client device 810 directly over a different network or communication system rather than over a channel of PubSub system 840. In some embodiments, the location analysis management system 850 may provide the results generated by analysis service 855 in response to a request by a client device 810 through an application interface 845 encapsulating underlying channels 842A-842N of a PubSub system 840.
The applications 820 included in client devices 810 can include any applications using location-based data generated by location devices 830, as well as location-based data accessed over one or more channels 842A-842N of the PubSub system 840. For example, either the client devices 810 or a specific application 820 may subscribe to one or more channels 842A-842N of the PubSub system 840 to receive information regarding nearby devices, local devices, or all devices on a particular channel of channels 842A-842N. In some embodiments, the application 820 or client device 810 may also publish location-based data to the same or a different channel of channels 842A-842N of the PubSub system 840. The client devices 810 or applications 820 may also receive analysis from analysis service 855 either on a subscribed channel 842A-842N of the PubSub system 840 or directly over a different network mechanism. For example, the analysis service 855 may provide analysis to client devices 810 or applications 820 over a private network connections 856 rather than over a channel 842A-842N of the PubSub system 840. Example applications and associated communication over PubSub system 840 are described below.
In some embodiments, the application can use the PubSub platform to obtain the location-based data of individual users and subscribe a client device to particular channels based on their location. For example, as users of the application enter a shopping mall or a particular store, they can be automatically subscribed to the channels related to that particular location. The information of subscribed users can be made available to the store owners who could then create new sales at any time for distribution to the potential buyers. For example, an owner or manager may view a user interface 1050 that provides options for generating particular deals based on current traffic of users. In some embodiments, the user interface may use information from an analysis service on another entity of a location system. For example, an analysis service may determine that many potential consumers are near a store, but are not entering. Accordingly, the analysis service can recommend incentives to a store owner to offer to subscribers. In some embodiments, the analysis service can automatically generate and provide incentives on a channel to subscribers.
Depending on traffic on the channels, the owners or managers can publish dynamic deals to a particular user base to attract additional users. For example, a graphical illustration of how such real-time deals can be pushed and displayed to users is shown by user interface 1000 of
In some embodiments, owners or managers may also create different deal groups, which they can activate and deactivate dynamically in the case where they want to introduce or stop any specific deal(s). For example, the user interface 1050 shows how such deal groups can be created, as shown on the right in the image. The user interface 1050 can include a listing of various deals that can be managed by the owners or managers through a store deals management interface, such as on a mobile or desktop computing device of the store owner. For example, each store deal can be comprised of various fields, such as “item group,” “discount,” “validity,” and the like. The item group field can provide a dropdown menu of item groups (e.g., sport shoes, XL t-shirts, or the like) on which sales can be run. The discount field can provide the amount of sale discount that is applied to the item group. The validity field can specify the amount of time the sale is to run (e.g., from a first date/time to a second date/time). By selecting an appropriate user interface element, the sale can be published to those channels of the store to which users are subscribed, to all mall channels, or to custom channels created for certain select users. Additionally, generic marketing channels can be provided, to which consumers in that particular locality can subscribe, and the stores can push their deals to such channels to get more or otherwise improve outreach. The store deals management interface can also allow the store owner to manage item groups (e.g., create, edit, modify and delete such groups), update existing deals, or create, view, or modify the settings for one or more store channels.
In an example embodiment, a user can prepare their grocery/shopping list using a first user interface 1100. For example, the user can enter an itemized list of groceries or other goods directly into the application using any suitable method (e.g., typing each item into the application, selecting an item from a dropdown menu or other list of items, and so forth). As the list is entered (e.g., as each item is entered or after all or a group of items are entered), the user interface may be updated to provide the user with a list of suggestions of where those items can be located in both online and nearby stores, the price of each item in each store, where each item is located in each store, directions to each store, and other like information. For example, the user interface 1150 shows an example of information generated based on location information of a user and a list provided by the user in user interface 1100. In some embodiments, real-time inventory of the store and the geolocation of the items may also be published on a channel of a PubSub platform for use by the application or an analysis service. Based on such data, directions can be computed and optimal plans for shopping (e.g., minimizing travel within a store and between stores) can be computed by the application. Locations of the buyers, stores, and store inventories are shared through the PubSub platform. Any number of buyers, stores, and store inventories can be managed using the PubSub platform, such as, for example, all buyers, stores, and store inventories in a large metropolitan city, state, or even country.
A ride hailing service application built on the PubSub system as described above can provide additional options for negotiating rates through the service. For example, rather than charges for a taxi trip being computed by an automated system which can cause losses to taxi drivers or users, the application can improve alignment of goals of clients and ride providers. For example, a driver makes a trip to a location B from location A, and desires a trip back to location A and is willing to sacrifice some money to accomplish the location-based goal. There is another rider from location B who wants to get back to location A, but the rider is thinking of using a taxi only if it meets a specified price target. Additionally, he can wait some more time to pay less money and/or he is okay with sharing a taxi (thereby increasing the travel time) for lesser money. The user may then request a cheaper ride through the PubSub application to determine if a ride is available.
As illustrated in the user interface 1200, the example bidding framework can let the rider bid the amount of money that they are willing to spend on a taxi ride from their location to a set location. Consequently, they can be given options based on different metrics, such as, for example, increased waiting time, increased travel time, taxi sharing and so forth. On the other end, as illustrated in the example user interface 1250, the taxi drivers can also be given choices to select one or more bids for a trip. This can allow drivers to select higher or lower prices in return for a time tradeoff. The various bids can each list, for example, the destination, reach time (i.e., time to reach the rider), trip time, amount of the trip, an “accept” button, and a “reject/re-bid” button. Thus, the driver can reject any one or more of the bids, which can require the rider to place another bid for the trip until a mutually agreed upon amount for the trip has been obtained or to seek bids with other drivers. In other words, based on their current locations and target locations of the current taxi trip and other like information, the riders can be matched against specific drivers, and they can potentially negotiate the pricing for that particular trip. Locations of the taxis and riders are shared through the PubSub platform. Any number of taxis and riders can be managed using the PubSub platform, such as, for example, all taxis and riders in a large metropolitan city, state, or even country
Moving on to block 1304, a PubSub system may publish the geographical locations of the users to a first of a plurality of channels. For example, the geographical locations received from a plurality of users may be published on one or more channels associated with various applications of different client devices. In some embodiments, the channels to which the geographic location data is published may be dependent on locations from which the location data is received.
In block 1306, an analysis service may determine, based on a geographic location associated with a first user of the plurality of users, an analysis result associated with the first user. For example, the geographic locations of the first user, potentially in context of other users, may be analyzed to determine a number of users in a location, engagements of the user in a location, or other information about the user that can be used by an application.
In block 1308, analysis results determined based on location data of the user may be published to a second channel. For example, the analysis results can be published to a channel to which an application associated with the user is subscribed. In block 1310, the analysis results may be provided as an output to the first user in response to the analysis result associated with the first user. Accordingly, the application can receive information associated with location-based data of the user and other users, and provide additional information to the user based on the received data. For example, the received data may be provided to the user in accordance with one of the user interfaces as described above.
The example computing device 1400 may include a computer processing device (e.g., a general purpose processor, ASIC, etc.) 1402, a main memory 1404, a static memory 1406 (e.g., flash memory and a data storage device 1408), which may communicate with each other via a bus 1410. The computer processing device 1402 may be provided by one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. In an illustrative example, computer processing device 1402 may comprise a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The computer processing device 1402 may also comprise one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The computer processing device 1402 may be configured to execute the operations described herein, in accordance with one or more aspects of the present disclosure, for performing the operations and steps discussed herein.
The computing device 1400 may further include a network interface device 1412, which may communicate with a network 1414. The data storage device 1408 may include a computer-readable or computer-readable storage medium 1416 on which may be stored one or more sets of instructions 1418, e.g., instructions for carrying out the operations described herein, in accordance with one or more aspects of the present disclosure. Instructions 1418 may also reside, completely or at least partially, within main memory 1404 and/or within computer processing device 1402 during execution thereof by the computing device 1400, main memory 1404 and computer processing device 1402 also constituting computer-readable media. The instructions may further be transmitted or received over the network 1414 via the network interface device 1412.
While computer-readable storage medium 1416 is shown in an illustrative example to be a single medium, the term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform the methods described herein. The term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media and magnetic media.
Embodiments of the subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or in addition, the program instructions can be encoded on an artificially-generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. A computer storage medium can be, or be included in, a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Moreover, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially-generated propagated signal. The computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices).
The operations described in this specification can be implemented as operations performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources.
The term “computer processing device” encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing. Although referred to as a computer processing device, use of the term also encompasses embodiments that include one or more computer processing devices. The computer processing device can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). The computer processing device can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The computer processing device and execution environment can realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.
A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative, procedural, or functional languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language resource), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
The processes and logic flows described in this specification can be performed by one or more computer processing device executing one or more computer programs to perform actions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).
Processing devices suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processing device will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic disks, magneto-optical disks, optical disks, or solid state drives. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a smart phone, a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few. Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including, by way of example, semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processing device and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
To provide for interaction with a user, embodiments of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse, a trackball, a touchpad, or a stylus, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending resources to and receiving resources from a device that is used by the user; for example, by sending web pages to a web browser on a user's client device in response to requests received from the web browser.
Embodiments of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).
The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some embodiments, a server transmits data (e.g., an HTML page) to a client device (e.g., for purposes of displaying data to and receiving user input from a user interacting with the client device). Data generated at the client device (e.g., a result of the user interaction) can be received from the client device at the server.
A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions.
While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any inventions or of what may be claimed, but rather as descriptions of features specific to particular embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub combination or variation of a sub combination.
Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Thus, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.
This application claims the benefit of U.S. Provisional Application No. 62/473,727, filed on Mar. 20, 2017, the entire contents of which are hereby incorporated by reference.
| Number | Date | Country | |
|---|---|---|---|
| 62473727 | Mar 2017 | US | |
| 62473727 | Mar 2017 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15925493 | Mar 2018 | US |
| Child | 15926869 | US |
