The present application is a national stage filing under 35 U.S.C. § 371 of international application number PCT/CN2020/094941, filed Jun. 8, 2020, which claims the priority of Chinese Patent Application No. 201910690727. X filed on Jul. 29, 2019. The content of these application are incorporated herein for reference in their entirety.
Embodiments of the present disclosure relates to the field of distributed databases, in particular to a method for sending a service request message, a distributed database architecture and a computer-readable storage medium.
All distributed databases have only one tier of computing nodes, which need to create links with all storage nodes, so obviously, when the computing nodes create links with all storage nodes, the number of back-end links is too large. For example, in case that there are 40 storage nodes in a distributed network, and a computing node receives 1,000 concurrent tasks (service request messages) from a client, the computing nodes may need to create 40*1000 back-end links which will be underutilized (services are generally read and written randomly, and some storage nodes may not be busy at the same moment, so a connection pool may recover links, and the recovered links may need to be re-created at a next moment). In this case, even if there is a connection pool (the recovery and recreating operations of the connection pool also increase the time delay), it is difficult for the computing nodes to maintain these links.
With the expansion of network services, the amount of service data and the number of concurrent tasks from the client will continue to increase, which will probably increase the number of storage nodes to 400. Upon receipt of 10,000 concurrent tasks, one computing node may need to create 4 million (400*10000) back-end links. Therefore, the created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from the client.
According to embodiments of the present disclosure, a method for sending a service request message, a distributed database architecture and a computer-readable storage medium are provided to at least solve one of the technical problems in related technologies to a certain extent, e.g., created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from a client.
In view of this, according to an embodiment of the present disclosure, a method for sending a service request message applied to distributed databases is provided, including: receiving a service request message; and sending the service request message to a corresponding storage unit through N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is.
According to an embodiment of the present disclosure, a distributed database architecture is further provided, including N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is; and in response to receiving a service request message, the architecture sends the service request message to a corresponding storage unit through the N tiers of computing nodes.
According to an embodiment of the present disclosure, a computer-readable storage medium storing a computer program for executing the method for sending a service request message is further provided.
Other features and corresponding beneficial effects of the present disclosure are described below in the specification, and it should be understood that at least some of the beneficial effects become apparent from the description of the specification of the present disclosure.
The present disclosure will be further described below in conjunction with embodiments and the accompanying drawings, in which:
In order to make the objective, technical schemes and advantages of the present disclosure clearer, embodiments of present disclosure will be further described in detail below with reference to the accompanying drawings by embodiments. It should be understood that the embodiments described herein are used merely for explaining the present disclosure, rather than limiting the present disclosure.
In order to solve at least one of the technical problems in related technologies to a certain extent, (e.g., created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from a client), according to an embodiment of the present disclosure, a method for a sending service request message is provided, including receiving a service request message and sending the received service request message to a corresponding storage unit through N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is.
At step S101, a service request message is received.
At step S102, the service request message is sent to a corresponding storage unit through N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is.
The terms used in this embodiment will be described first.
Computing node refers to a message broker node responsible for SQL optimizing and routing, load balancing of child nodes, scheduling of distributed transactions, etc.
Storage cluster refers to a collection of storage nodes in a distributed database, where service databases are regularly distributed on the storage nodes in the storage cluster.
Storage unit refers to a subset in the storage cluster, and contains a plurality of storage nodes.
Storage node refers to a DB node in the distributed database which may be relational databases such as Mysql, Oracle and PostgreSQL.
It should be understood that the computing nodes in this embodiment are divided into at least two tiers, i.e., there are at least two tiers of computing nodes, where the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is, i.e., the computing nodes in all tiers are of a pyramidal structure as a whole.
In some examples, as shown in
In some examples, as shown in
It should be noted that N is not limited to 3 or 2 in the present disclosure. In practical application, the number N of tiers of computing nodes may be determined based on the amount of service data and the number of concurrent tasks from the client.
In some examples of this embodiment, before the service request message is sent to the corresponding storage unit through N tiers of computing nodes, the method further includes the following step.
The storage cluster is divided into at least two storage units each containing at least one storage node.
For example, as shown in
It should be noted that, in practical application, the number of storage units into which a storage cluster is divided and the number of storage nodes contained in each storage unit may be flexibly adjusted based on specific service data.
It should be understood that, after the storage cluster is divided into at least two storage units, the addition/deletion (capacity expansion/reduction) of all storage nodes will not affect each other, so that it is easier to implement the addition/deletion (capacity expansion/reduction) of all storage nodes, the capacity change is more flexible and the maintenance cost is reduced to a certain extent.
In some examples of this embodiment, the computing nodes closest to the storage unit are called bottom-tier computing nodes configured to manage and maintain all storage nodes in the storage unit connected thereto, so that there is no need to provide a separate management and maintenance module for managing and maintaining all storage nodes in the storage unit. The bottom-tier computing nodes may manage and maintain all storage nodes in the storage unit connected thereto, thereby saving the cost. Moreover, because there are fewer storage nodes that create links with the computing nodes in the storage unit, it is also easy for management and maintenance.
In some examples of this embodiment, the computing nodes in other tiers other than the bottom-tier computing nodes may enable a function of load balancing.
The top-tier computing nodes may create links with any one of the next-tier computing nodes. In case of busy concurrent services, a plurality of top-tier computing nodes may be enabled. The top-tier computing nodes are independent of each other (independent) and peer-to-peer (sharing metadata information), and have a function of load balancing (or may be integrated with a third-party load balancing module).
The middle-tier computing nodes may be divided by regions. The computing nodes in different regions are independent of each other and not peer-to-peer (with some differences in metadata information). There may be a plurality of computing nodes which are independent of each other and peer-to-peer in each region. The middle-tier computing nodes create links with the computing nodes belonging thereto in the next tier, not with all computing nodes in the next tier. The middle tier may include a plurality of tiers with the same region division rules. The middle-tier computing nodes also have the function of load balancing (or may be integrated with a third-party load balancing module).
It should be understood that the bottom-tier computing nodes only create links with a single storage unit, and the computing nodes in different storage units are independent of each other and not peer-to-peer (with some differences in metadata information). Each storage unit may be provided with a plurality of bottom-tier computing nodes which are independent of each other and peer-to-peer. Because both the top-tier computing nodes and the middle-tier computing nodes have the function of load balancing, and the bottom-tier computing nodes only create links with a single storage unit, the link load on the bottom-tier computing nodes is greatly reduced.
In some examples of this embodiment, the computing nodes in the N tiers may adopt a same distribution policy. For example, the computing nodes in the first, second and third tiers all adopt a distribution policy 1, or a distribution policy 2, or a distribution policy 3.
In some examples of this embodiment, the computing nodes in the N tiers may adopt different distribution policies. For example, the computing nodes in the first tier adopt the distribution policy 1, the computing nodes in the second tier adopt the distribution policy 2 and the computing nodes in the third tier adopt the distribution policy 3.
In some examples of this embodiment, the distribution policy in this embodiment includes at least one of hash distribution policy, range distribution policy, list distribution policy and duplicate distribution policy. It should be noted that the distribution policies listed herein are only a few common ones, which may be flexibly adjusted according to actual needs in practical application.
In the method for sending a service request message according to the embodiment of the present disclosure, upon receipt of a service request message, the service request message is sent to the corresponding storage unit through the N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier to the storage unit, the larger the number of computing nodes in that tier is, thereby at least solving one of the technical problems in related technologies to a certain extent, e.g., created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from the client. That is to say, with the method for sending a service request message according to the embodiment of the present disclosure, firstly the computing nodes are divided into tiers (at least two tiers), and the storage cluster is divided into a plurality of (at least two) storage units (each containing at least one storage node), then the number of back-end links of each computing node is greatly reduced by “balancing link load”, and finally the service request message is sent to the corresponding storage node through “the computing nodes in each tier using respective distribution policy”, thereby avoiding difficulty in maintaining too many back-end links at the same computing node, greatly improving the maintainability of the back-end links at the computing node and greatly reducing the maintenance difficulty.
In the embodiment of the present disclosure, a process of sending a service request message in a distributed database architecture having three tiers of computing nodes is described as an example, as shown in
The computing nodes are divided into three tiers, where top-tier computing nodes may create links with all middle-tier computing nodes, and the middle-tier computing nodes are divided into two regions. It should be understood that the middle-tier computing nodes may be divided into a plurality of regions with computing nodes in the same region being peer-to-peer, and bottom-tier computing nodes may only create links with a single storage unit.
A storage cluster is divided into K storage units each containing M storage nodes, where K is an integer greater than or equal to 2 and M is an integer greater than or equal to 1.
A specific link load division mechanism will be described.
1. A top-tier computing node 1 receives 4,000 concurrent requests from a client 1.
It should be understood that there may be a plurality of clients and a plurality of top-tier computing nodes.
2. The top-tier computing node 1 creates links with two peer-to-peer middle-tier computing nodes in a region 1, with 2,000 links created for each middle-tier computing node by load balancing. At the same time, the top-tier computing node 1 may also create links with the middle-tier computing nodes in other regions, such as middle-tier computing nodes in a region 2, by the same connection mode as in the region 1.
It should be understood that, in some examples of this embodiment, the top-tier computing node 1 creates links with two peer-to-peer middle-tier computing nodes in the region 1, with 1,600 links created for one middle-tier computing node and 2,400 links created for the other one, which may be flexibly adjusted according to actual needs in practical application.
3. The middle-tier computing nodes in the region 1 create links with two peer-to-peer bottom-tier computing nodes, with 1,000 links created for each bottom-tier computing node by load balancing. The bottom-tier computing node may only create links with a single storage unit.
It should be understood that in some examples of this embodiment, a first middle-tier computing node in the region 1 creates links with two peer-to-peer bottom-tier computing nodes, with 600 links created for one bottom-tier computing node and 1,000 links created for the other one, which may be flexibly adjusted according to actual needs in practical application.
4. The bottom-tier computing nodes create links with all the storage nodes in the storage unit. There are 1000*M back-end links (excluding links from other middle-tier computing nodes).
In case that the top-tier computing node directly creates links with all storage nodes in the existing way, there are 4000*M*K back-end links.
From the above, the method for sending a service request message according to the embodiment of the present disclosure has the following beneficial effects.
1. The number of back-end links at multi-tier computing nodes is greatly reduced, thereby reducing the “recovery-recreating operations” of links and solving the bottleneck problem of the number of links loaded at each computing node.
2. The multi-tier computing nodes are more flexible in structure, and the number of tiers of computing nodes, which ranges from 2 to N, may be adjusted according to the number of storage nodes, where N is an integer greater than or equal to 2.
3. After the storage cluster is divided into a plurality of storage units, the maintenance cost of storage units becomes lower and the capacity change is more flexible.
In the embodiment of the present disclosure, a process of sending service request messages in a distributed database architecture having two tire computing nodes is described as an example, as shown in
The computing nodes are divided into two tiers. The two top-tier computing nodes are relatively independent and peer-to-peer, and may create links with all the bottom-tier computing nodes.
The storage cluster is divided into K storage units each containing M storage nodes, where K is an integer greater than or equal to 2 and M is an integer greater than or equal to 1. The bottom-tier computing nodes on a storage unit 1 and those on a storage unit K are not peer-to-peer, with some differences in metadata (The difference is that the former is bound to the storage unit 1, while the latter is bound to the storage unit 2).
The bottom-tier computing nodes only create links with a single storage unit. According to an example of the number of nodes in
In the embodiment of the present disclosure, a process of adding and deleting storage nodes is described as an example.
When there is an increase in the amount of service data and the storage nodes may be added, they may be added in appropriate storage units. As shown in
When there is a decrease in the amount of service data and the storage nodes may be deleted, they may be deleted from the appropriate storage units. As shown in
In order to solve at least one of the technical problems in related technologies, (e.g., created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from a client), according to the embodiment of the present disclosure, a distributed database architecture is provided, including N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage, the larger the number of computing nodes in that tier is. Upon receipt of a service request message, the service request message is sent to a corresponding storage unit through the N tiers of computing nodes.
It should be understood that the computing nodes in this embodiment are divided into at least two tiers, i.e., there are at least two tiers of computing nodes, where the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is, i.e., the number of tiers of computing nodes is of a pyramidal structure.
In some examples, also as shown in
In some examples, also as shown in
It should be noted that N is not limited to 3 or 2 in the present disclosure. In practical application, the number N of tiers of computing nodes may be determined based on the amount of service data and the number of concurrent tasks from the client.
In some examples of this embodiment, the storage cluster includes at least two storage units each containing at least one storage node.
For example, also as shown in
It should be noted that, in practical application, the number of storage units into which a storage cluster is divided and the number of storage nodes contained in each storage unit may be flexibly adjusted based on specific service data.
It should be understood that, after the storage cluster is divided into at least two storage units, the addition/deletion (capacity expansion/reduction) of all storage nodes will not affect each other, so that it is easier to implement the addition/deletion (capacity expansion/reduction) of all storage nodes, the capacity change is more flexible and the maintenance cost is reduced to a certain extent.
In some examples of this embodiment, the computing nodes closest to the storage unit are called bottom-tier computing nodes configured to manage and maintain all storage nodes in the storage unit connected thereto, so that there is no need to provide a separate management and maintenance module for managing and maintaining all storage nodes in the storage unit. The bottom-tier computing nodes may manage and maintain all storage nodes in the storage unit connected thereto, thereby saving the cost. Moreover, because there are fewer storage nodes that create links with the computing nodes in the storage unit, it is also easy for management and maintenance.
In some examples of this embodiment, the computing nodes in other tiers other than the bottom-tier computing nodes may enable a function of load balancing.
The top-tier computing nodes may create links with any one of the next-tier computing nodes. In case of busy concurrent services, a plurality of top-tier computing nodes may be enabled. The top-tier computing nodes are independent of each other (independent) and peer-to-peer (sharing metadata information), and have a function of load balancing (or may be integrated with a third-party load balancing module).
The middle-tier computing nodes may be divided by regions. The computing nodes in different regions are independent of each other and not peer-to-peer (with some differences in metadata information). There may be a plurality of computing nodes which are independent of each other and peer-to-peer in each region. The middle-tier computing nodes create links with the computing nodes belonging thereto in the next tier, not with all computing nodes in the next tier. The middle tier may include a plurality of tiers with the same region division rules. The middle-tier computing nodes also have the function of load balancing (or may be integrated with a third-party load balancing module).
It should be understood that the bottom-tier computing nodes only create links with a single storage unit, and the computing nodes in different storage units are independent of each other and not peer-to-peer (with some differences in metadata information). Each storage unit may be provided with a plurality of bottom-tier computing nodes which are independent of each other and peer-to-peer. Because both the top-tier computing nodes and the middle-tier computing nodes have the function of load balancing, and the bottom-tier computing nodes only create links with a single storage unit, the link load on the bottom-tier computing nodes is greatly reduced.
In some examples of this embodiment, the computing nodes in the N tiers may adopt a same distribution policy. For example, the computing nodes in the first, second and third tiers all adopt a distribution policy 1, or a distribution policy 2, or a distribution policy 3.
In some examples of this embodiment, the computing nodes in the N tiers may adopt different distribution policies. For example, the computing nodes in the first tier adopt the distribution policy 1, the computing nodes in the second tier adopt the distribution policy 2 and the computing nodes in the third tier adopt the distribution policy 3.
In some examples of this embodiment, the distribution policy in this embodiment includes at least one of hash distribution policy, range distribution policy, list distribution policy and duplicate distribution policy. It should be noted that the distribution policies listed herein are only a few common ones, which may be flexibly adjusted according to actual needs in practical application.
According to an embodiment of the present disclosure, a computer-readable storage medium storing a computer program for implementing the method for sending a service request message is further provided.
The distributed database architecture according to the embodiment of the present disclosure includes N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is. Upon receipt of a service request message, the service request message is sent to a corresponding storage unit through the N tiers of computing nodes, thereby at least solving the technical problems in related technologies to a certain extent, e.g., created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from the client. That is to say, in the distributed database architecture according to the embodiment of the present disclosure, firstly the computing nodes are divided into tiers (at least two tiers), and the storage cluster is divided into a plurality of (at least two) storage units (each containing at least one storage node), then the number of back-end links of each computing node is greatly reduced by “balancing link load”, and finally the service request message is sent to the corresponding storage node through “the computing nodes in each tier using respective distribution policy”, thereby avoiding difficulty in maintaining too many back-end links at the same computing node, greatly improving the maintainability of the back-end links at the computing node and greatly reducing the maintenance difficulty.
In the method for sending a service request message and the distributed database architecture according to the embodiments of the present disclosure, upon receipt of a service request message, the service request message is sent to the corresponding storage unit through N tiers of computing nodes, where N is an integer greater than or equal to 2, and the closer the tier is to the storage unit, the larger the number of computing nodes in that tier is, thereby solving the problem in related technologies that created back-end links are unthinkable and more difficult to maintain with the continuous increase of the amount of service data and the number of concurrent tasks from the client. That is to say, in the method for sending a service request message and the distributed database architecture according to the embodiments of the present disclosure, the service request messages are sequentially sent to the corresponding storage nodes through N tiers of computing nodes (a pyramidal structure) to reduce the back-end links of the computing nodes tier by tier, thereby avoiding difficulty in maintaining too many back-end links at the same computing node.
Obviously, those having ordinary skill in the art should understand that all or some of the steps in the methods, systems, and functional modules/units in the devices disclosed above may be implemented as software (which may be implemented by computer program codes executable by a computing device), firmware, hardware and appropriate combinations thereof. In the implementations by hardware, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components. For example, a physical component may have a plurality of functions, or a function or step may be implemented cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as CPU, a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transient medium) and a communication medium (or transient medium), executed by a computing device, and in some cases, the steps shown or described may be implemented in a different order than herein. It is well known to those having ordinary skill in the art that the computer storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information, such as computer readable instructions, data structures, program modules or other data. Furthermore, it is well known to those having ordinary skill in the art that the communication medium typically contains computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery media. Therefore, the present disclosure is not limited to any particular combination of hardware and software.
The above descriptions are further detailed descriptions of the embodiments of the present disclosure with reference to specific implementation ways, and it cannot be assumed that the specific implementation ways of the present disclosure are limited to these descriptions. For those having ordinary skill in the art to which the present disclosure belongs, a number of simple derivations or substitutions may also be made without departing from the concept of the present disclosure, all of which should be regarded as falling into the protection scope of the present disclosure.
Number | Date | Country | Kind |
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201910690727.X | Jul 2019 | CN | national |
Filing Document | Filing Date | Country | Kind |
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PCT/CN2020/094941 | 6/8/2020 | WO |
Publishing Document | Publishing Date | Country | Kind |
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WO2021/017646 | 2/4/2021 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
10230544 | McDowell | Mar 2019 | B1 |
10296258 | Richardson | May 2019 | B1 |
10303390 | Colgrove | May 2019 | B1 |
10310760 | Dreier | Jun 2019 | B1 |
10365982 | Brooks | Jul 2019 | B1 |
10402266 | Kirkpatrick | Sep 2019 | B1 |
10425473 | Patel | Sep 2019 | B1 |
10452444 | Jibaja | Oct 2019 | B1 |
10454498 | Mao | Oct 2019 | B1 |
10454810 | Driscoll | Oct 2019 | B1 |
10459664 | Dreier | Oct 2019 | B1 |
10467107 | Abrol | Nov 2019 | B1 |
10484174 | Bernat | Nov 2019 | B1 |
10496330 | Bernat | Dec 2019 | B1 |
10509581 | Abrol | Dec 2019 | B1 |
10514978 | Lee | Dec 2019 | B1 |
10516645 | Patel | Dec 2019 | B1 |
10521151 | Fay | Dec 2019 | B1 |
10528488 | Lee | Jan 2020 | B1 |
10545687 | Bernat | Jan 2020 | B1 |
10620830 | Donlan | Apr 2020 | B2 |
10671302 | Aggarwal | Jun 2020 | B1 |
10671439 | Frandzel | Jun 2020 | B1 |
10671494 | Abrol | Jun 2020 | B1 |
10678433 | Kirkpatrick | Jun 2020 | B1 |
10678436 | Jiang | Jun 2020 | B1 |
10705732 | Bernat | Jul 2020 | B1 |
10733053 | Miller | Aug 2020 | B1 |
10756816 | Dreier | Aug 2020 | B1 |
10776046 | Dreier | Sep 2020 | B1 |
10776202 | Sanvido | Sep 2020 | B1 |
10789211 | Miller | Sep 2020 | B1 |
10795598 | Vohra | Oct 2020 | B1 |
10817392 | McAuliffe | Oct 2020 | B1 |
10838833 | Jibaja | Nov 2020 | B1 |
10884636 | Abrol | Jan 2021 | B1 |
10908835 | Patel | Feb 2021 | B1 |
10917471 | Karumbunathan | Feb 2021 | B1 |
10924548 | Karumbunathan | Feb 2021 | B1 |
10929226 | Miller | Feb 2021 | B1 |
10931450 | Chellappa | Feb 2021 | B1 |
10936191 | Lakshminarayanan | Mar 2021 | B1 |
10942650 | Fay | Mar 2021 | B1 |
10963189 | Neelakantam | Mar 2021 | B1 |
10970395 | Bansal | Apr 2021 | B1 |
10976948 | Lee | Apr 2021 | B1 |
10990282 | Lee | Apr 2021 | B1 |
10990480 | Bernat | Apr 2021 | B1 |
10990566 | Lee | Apr 2021 | B1 |
11003369 | Bernat | May 2021 | B1 |
11010233 | Golden | May 2021 | B1 |
11016667 | Sears | May 2021 | B1 |
11016824 | Wells | May 2021 | B1 |
11024390 | Aster | Jun 2021 | B1 |
11032259 | Bernat | Jun 2021 | B1 |
11036596 | Coleman | Jun 2021 | B1 |
11036677 | Grunwald | Jun 2021 | B1 |
11042452 | McNutt | Jun 2021 | B1 |
11048590 | Sapuntzakis | Jun 2021 | B1 |
11068162 | Meister | Jul 2021 | B1 |
11086553 | Fisher | Aug 2021 | B1 |
11086713 | Sapuntzakis | Aug 2021 | B1 |
11089105 | Karumbunathan | Aug 2021 | B1 |
11093139 | Karr | Aug 2021 | B1 |
11095706 | Ankam | Aug 2021 | B1 |
11112990 | Bernat | Sep 2021 | B1 |
11128448 | Bernat | Sep 2021 | B1 |
11144358 | Noble | Oct 2021 | B1 |
11146564 | Ankam | Oct 2021 | B1 |
11150834 | Fay | Oct 2021 | B1 |
11169727 | Doucette | Nov 2021 | B1 |
11171950 | Zhuravlev | Nov 2021 | B1 |
11194473 | Zhao | Dec 2021 | B1 |
11210009 | Freilich | Dec 2021 | B1 |
11210133 | Barker, Jr. | Dec 2021 | B1 |
11221778 | Miller | Jan 2022 | B1 |
11275509 | Colgrove | Mar 2022 | B1 |
11281577 | Karumbunathan | Mar 2022 | B1 |
11288138 | Freilich | Mar 2022 | B1 |
11294588 | Miller | Apr 2022 | B1 |
11301152 | Sillifant | Apr 2022 | B1 |
11321006 | Grunwald | May 2022 | B1 |
11327676 | Fernandez | May 2022 | B1 |
11340800 | Sanvido | May 2022 | B1 |
11340837 | Vohra | May 2022 | B1 |
11340939 | Barker, Jr. | May 2022 | B1 |
11360689 | Grunwald | Jun 2022 | B1 |
11360844 | Dodsley | Jun 2022 | B1 |
11392553 | Power | Jul 2022 | B1 |
11397545 | Hamid | Jul 2022 | B1 |
11403000 | Barker, Jr. | Aug 2022 | B1 |
11416298 | Barker, Jr. | Aug 2022 | B1 |
11422731 | Potashnik | Aug 2022 | B1 |
11431488 | Sapuntzakis | Aug 2022 | B1 |
11436344 | Juch | Sep 2022 | B1 |
11442652 | Dailey | Sep 2022 | B1 |
11442669 | Frandzel | Sep 2022 | B1 |
11455168 | Potyraj | Sep 2022 | B1 |
11461273 | Kleinerman | Oct 2022 | B1 |
11467913 | Karr | Oct 2022 | B1 |
11477280 | Irwin | Oct 2022 | B1 |
11481261 | Frandzel | Oct 2022 | B1 |
11487715 | Karr | Nov 2022 | B1 |
11494109 | Sears | Nov 2022 | B1 |
11494692 | Watkins | Nov 2022 | B1 |
11503031 | Hu | Nov 2022 | B1 |
11520907 | Borowiec | Dec 2022 | B1 |
11526405 | Fisher | Dec 2022 | B1 |
11531577 | Bernat | Dec 2022 | B1 |
11556280 | Gold | Jan 2023 | B2 |
20070203910 | Ferguson et al. | Aug 2007 | A1 |
20110145286 | LaRowe | Jun 2011 | A1 |
20150205818 | Darcy | Jul 2015 | A1 |
20160314409 | Bittencourt | Oct 2016 | A1 |
Number | Date | Country |
---|---|---|
105608144 | May 2016 | CN |
105975378 | Sep 2016 | CN |
110018817 | Jul 2019 | CN |
Entry |
---|
European Patent Office. Extended European Search Report for EP Application No. 20847973.3, dated Aug. 8, 2022, pp. 1-9. |
Sheth, et al. “Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases,” ACM Computer Surveys, vol. 22, No. 3, Sep. 1990, pp. 183-236. |
International Searching Authority. International Search Report and Written Opinion for PCT Application No. PCT/CN2020/094941 and English translation, dated Sep. 9, 2020, pp. 1-9. |
Number | Date | Country | |
---|---|---|---|
20220286498 A1 | Sep 2022 | US |