SYSTEMS AND METHODS FOR ASYNCHRONOUS DISTRIBUTED DATABASE MANAGEMENT

Abstract

Embodiments of the present disclosure include systems and methods for asynchronous distributed database management. In one embodiment, the systems and methods wait to execute or update a database transaction or command until specific conditions are satisfied, essentially divorcing the read-time from update-time in evaluation of a single expression. Accordingly, the systems and methods described herein can, in some instances, resolve the temporary inconsistencies without aborting and/or otherwise terminating a database transaction that would otherwise be aborted.

Description

CLAIM OF PRIORITY

This application claims priority to U.S. Provisional Patent Application No. 61/513,932 entitled “Reconciling a Distributed Database from Hierarchical Viewpoints,” which was filed on Aug. 1, 2011, Attorney Docket No. 58520-8006.US00, the contents of which are expressly incorporated by reference herein.

CROSS-REFERENCE TO RELATED APPLICATION

This application is related to co-pending U.S. patent application Ser. No. ______, entitled “Reconciling a Distributed Database from Hierarchical Viewpoints,” also by Jason Lucas, which was filed on Aug. 1, 2012, Attorney Docket No. 58520-8006.US01, the contents of which are expressly incorporated by reference herein.

This application is related to co-pending U.S. patent application Ser. No. ______, entitled “Generalized Reconciliation in a Distributed Database,” also by Jason Lucas, which was filed on Aug. 1, 2012, Attorney Docket No. 58520-8007.US01, the contents of which are expressly incorporated by reference herein.

TECHNICAL FIELD

Embodiments of the present disclosure generally relate to database management techniques and, more particularly to asynchronous distributed database management.

BACKGROUND

A distributed database is a database in which storage devices are not all attached to a common central processing unit (CPU). A distributed database may be stored in multiple computers located in the same physical location, or may be dispersed over a network of interconnected computers at multiple physical locations. The locations or sites of a distributed system may be spread over a large area (such as the United States or the world) or over a small area (such as a building or campus). The collections of data in the distributed database can also be distributed across multiple physical locations.

Typically, it is an object of a distributed database system to allow many users (clients or applications) use of the same information within the collection of data at the same time while making it seem as if each user has exclusive access to the entire collection of data. The distributed database system should provide this service with minimal loss of performance (latency) and maximal transaction throughput. That is, a user at location A must be able to access (and perhaps update) data at location B. If the user updates information, the updates must be propagated throughout the resources of the distributed database system to maintain consistency in the distributed database system.

The updates (or database transactions) must be serialized in the distributed database system to maintain consistency. If transactions were executed in serial order, concurrency conflicts would never occur because each transaction would be the only transaction executing on the system at a given time and would have exclusive use of the system's resources. The new transactions would see the results of previous transactions, plus changes made by that transaction, but would never see the results of transactions that had not yet started. In operation, transactions typically execute concurrently and require simultaneous access and modification to the same resources. Thus, maintaining consistency in a distributed database system can be very complex and often results in unacceptable response times.

Various concurrency control schemes currently exist such as, for example, optimistic concurrency control schemes, which operate by detecting invalid use after the fact. The basic idea of these types of schemes is to divide a database transaction's lifetime into three phases: read, validate and publish. During the read phase, a transaction acquires resources without regard to conflict or validity, but it maintains a record of the set of resources it has used (a ReadSet) and the set of resources it has modified (a WriteSet). During the validation phase, the optimistic concurrency control scheme examines the ReadSet of the transaction and decides whether the current state of those resources has since changed. If the ReadSet has not changed, then the optimistic assumptions of the transaction are proved to have been right, and the system publishes the WriteSet, committing the transaction's changes. If the ReadSet has changes, then the optimistic assumption of the transaction are proved to be wrong, and the system aborts the transaction resulting in a loss of all changes.

Unfortunately, in some highly distributed databases remote events and continuous asynchronous reconciliation can create temporary inconsistencies that lead to the unnecessary abortion of transactions whose assumptions are proven to be temporarily wrong.

SUMMARY

Embodiments of the present disclosure include systems and methods for asynchronous distributed database management. In one embodiment, the systems and methods wait to execute and/or update a database transaction or command until specific conditions are satisfied, divorcing the read-time from update-time in evaluation of a single expression. Accordingly, the systems and methods described herein can, in some instances, resolve the temporary inconsistencies without aborting and/or otherwise terminating a database transaction that would otherwise be aborted.

In accordance with various embodiments, a database management system (DBMS) asynchronously manages a distributed database by receiving a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions, polling a plurality of database resources regarding the validity of the one or more assertions included within the database transaction to achieve a consensus, and updating the database transaction in the distributed database system upon achieving the consensus if the consensus is achieved within a timeout interval, wherein the consensus is not initially achieved among the plurality of database resources.

In one embodiment, the DBMS asynchronously manages a distributed database by notifying the client in the distributed database that the database transaction has been aborted if the consensus is not achieved within the timeout interval.

In one embodiment, the database transaction is initiated by an application running on the client.

In one embodiment, the DBMS asynchronously manages a distributed database by, prior to updating the distributed database system, notifying the client that the database transaction has completed successfully.

In one embodiment, the timeout interval comprises a duration of time between one half of a second and three seconds or a duration of time less than one half of a second.

In one embodiment, updating the distributed database system further comprises asynchronously reconciling the database transaction with one or more other database transactions in the distributed database system.

In one embodiment, the DBMS asynchronously manages a distributed database by prior to updating the distributed database system, reading information related to the database transaction from the distributed database system, and transferring the information to the client regardless of whether the consensus has been achieved.

In one embodiment, the DBMS asynchronously manages a distributed database by receiving, at the database management system, a second database transaction associated with a second transaction sequence from a second client in the distributed database system, wherein the second database transaction includes one or more second assertions, and wherein the one or more second assertions require reading the information related to the database transaction.

In one embodiment, updating the distributed database system further comprises committing the database transaction to a global transaction sequence, and replicating the global transaction sequence across the plurality of database resources of the distributed database.

In one embodiment, the DBMS asynchronously manages a distributed database by determining a likelihood that the consensus can be achieved.

In one embodiment, the DBMS asynchronously manages a distributed database by setting the timeout interval based upon the likelihood that the consensus can be achieved.

In one embodiment, the plurality of database resources comprise one or more of other database management systems in the distributed database system or one or more storage management systems in the distributed database system.

In accordance with various embodiments, a DBMS asynchronously manages a distributed database by receiving a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions, processing the database transaction to identify the one or more assertions, wherein the one or more assertions must have a specific configuration in order to update the database transaction in the distributed database system, determining a first configuration among a plurality of database resources regarding the one or more assertions at a first time, wherein the first configuration is different than the specific configuration, and updating the database transaction in the distributed database system at a second time if a second configuration among the plurality of database resources regarding the one or more assertions is the same as the specific configuration at the second time.

In one embodiment, the specific configuration requires that the one or more assertions be valid.

In accordance with various embodiments, a DBMS can asynchronously manage a distributed database. The DBMS can include a processing unit, an interface, and a memory unit. The interface can receive a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions. The memory unit can have instructions stored thereon, wherein the instructions, when executed by the processing unit, cause the processing unit to process the database transaction to identify the one or more assertions, wherein the one or more assertions must have a specific configuration in order to update the database transaction in the distributed database system, determine a first configuration among a plurality of database resources regarding the one or more assertions at a first time, wherein the first configuration is different than the specific configuration, and update the database transaction in the global transaction sequence at a second time if a second configuration among the plurality of database resources regarding the one or more assertions is the same as the specific configuration at the second time.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a block diagram of an example distributed database environment illustrating a plurality of distributed database sites and client systems within which various features of the present invention may be utilized, according to one embodiment.

FIG. 2 depicts a block diagram of an example node in a distributed database environment within which various features of the present invention may be utilized, according to an embodiment.

FIG. 3 depicts a block diagram of the components of a database management system for asynchronous distributed database management, according to an embodiment.

FIG. 4 depicts a flow diagram illustrating an example process for asynchronous distributed database management, according to an embodiment.

FIG. 5 depicts a flow diagram illustrating an example process for asynchronous distributed database management, according to one embodiment.

FIG. 6 depicts a flow diagram illustrating an example process for asynchronous distributed database management, according to an embodiment.

FIG. 7 depicts a sequence diagram illustrating example operations of components of a distributed database environment, according to one embodiment.

FIG. 8 shows a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed, according to one embodiment.

DETAILED DESCRIPTION

Systems and methods of asynchronous distributed database management are described herein. In particular, a database command or transaction is typically predicated on a specific set of conditions existing. If the conditions exist, the command can successfully be implemented. However, if the conditions don't immediately exist, the command is terminated and error code is generated. Immediate termination of a command or database transaction is particularly problematic in large, highly distributed databases where remote events and continuous reconciliation often create temporary inconsistencies. Accordingly, the systems and methods described herein wait to execute or update a database transaction until the specific set of conditions is satisfied.

In one embodiment, the database transaction can include one or more assertions upon which the database transaction relies. Typically, the assertions must have specific configurations or be valid in order to be updated and/or reconciled into a global transaction sequence. Invalid assertions result in inconsistencies within the database that can be temporary. Advantageously, the systems and methods described herein can, in some instances, resolve the temporary inconsistencies without aborting and/or otherwise terminating the database transaction.

In one embodiment, this object can be accomplished by divorcing the read-time from update-time in evaluation of a single expression. It is appreciated that in some embodiments the command or database transaction may time out for other reasons.

The following description and drawings are illustrative and are not to be construed as limiting. Numerous specific details are described to provide a thorough understanding of the disclosure. However, in certain instances, well-known or conventional details are not described in order to avoid obscuring the description. References to one or an embodiment in the present disclosure can be, but not necessarily are, references to the same embodiment; and, such references mean at least one of the embodiments.

Reference in this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosure. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not other embodiments.

The terms used in this specification generally have their ordinary meanings in the art, within the context of the disclosure, and in the specific context where each term is used. Certain terms that are used to describe the disclosure are discussed below, or elsewhere in the specification, to provide additional guidance to the practitioner regarding the description of the disclosure. For convenience, certain terms may be highlighted, for example using italics and/or quotation marks. The use of highlighting has no influence on the scope and meaning of a term; the scope and meaning of a term is the same, in the same context, whether or not it is highlighted. It will be appreciated that the same thing can be said in more than one way.

Consequently, alternative language and synonyms may be used for any one or more of the terms discussed herein, nor is any special significance to be placed upon whether or not a term is elaborated or discussed herein. Synonyms for certain terms are provided. A recital of one or more synonyms does not exclude the use of other synonyms. The use of examples anywhere in this specification including examples of any terms discussed herein is illustrative only, and is not intended to further limit the scope and meaning of the disclosure or of any exemplified term. Likewise, the disclosure is not limited to various embodiments given in this specification.

Without intent to further limit the scope of the disclosure, examples of instruments, apparatus, methods and their related results according to the embodiments of the present disclosure are given below. Note that titles or subtitles may be used in the examples for convenience of a reader, which in no way should limit the scope of the disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In the case of conflict, the present document, including definitions will control.

Embodiments of the present disclosure include various steps, which will be described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, the steps may be performed by a combination of hardware, software and/or firmware.

Embodiments of the present disclosure may be provided as a computer program product, which may include a machine-readable medium having stored thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, ROMs, random access memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), vehicle identity modules (VIMs), magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing electronic instructions.

Moreover, embodiments of the present invention may also be downloaded as a computer program product or data to be used by a computer program product, wherein the program, data, and/or instructions may be transferred from a remote computer or mobile device to a requesting computer or mobile device by way of data signals embodied in a carrier wave or other propagation medium via a communication link (e.g., a modem or network connection). In some cases, parts of the program, data, or instructions may be provided by external networks such as the telephony network (e.g., Public Switched Telephony Network, cellular, Wi-Fi, and other voice, data, and wireless networks) or the Internet. The communications link may be comprised of multiple networks, even multiple heterogeneous networks, such as one or more border networks, voice networks, broadband networks, service provider networks, Internet Service Provider (ISP) networks, and/or Public Switched Telephone Networks (PSTNs), interconnected via gateways operable to facilitate communications between and among the various networks.

Terminology

Brief definitions of terms used throughout this application are given below.

The terms “connected” or “coupled” and related terms are used in an operational sense and are not necessarily limited to a direct connection or coupling.

The term “embodiments,” phrases such as “in some embodiments,” “in various embodiments,” and the like, generally mean the particular feature(s), structure(s), method(s), or characteristic(s) following or preceding the term or phrase is included in at least one embodiment of the present invention, and may be included in more than one embodiment of the present invention. In addition, such terms or phrases do not necessarily refer to the same embodiments.

If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.

The term “module” refers broadly to a software, hardware, and/or firmware (or any combination thereof) component. Modules are typically functional components that can generate useful data or other output using specified input(s). A module may or may not be self-contained. An application program (also called an “application”) may include one or more modules, and/or a module can include one or more application programs.

The term “responsive” includes completely and partially responsive.

Example Distributed Database Environment

An example of a distributed database environment 100, representing a plurality of distributed database sites and client systems, within which various features of the present invention may be utilized, will now be described with reference to FIG. 1. In this example, the distributed database environment 100 comprises a plurality of nodes 10, a plurality of client systems 25, and a network 150. Each node 10 may be located at a different site or geographic location. Similarly, each client system 25 may be located anywhere within connectivity of network 150.

In this example, the nodes 10 are in communication with other nodes 10 via network 150. The nodes 10 may be centralized database systems such as data warehouses or data marts, remote sites such as desktop personal computers, portable computers or other mobile computing devices, or any other type of data processors. As shown in this example, the nodes 10 include database management systems 18 in communication with distributed databases 20. The database management systems 18 may be in communication with a database 20 via any communication means for communicating data and/or control information. Although not shown for simplicity, database management system 18 may also include both a distributed database management system and a local database management system. Similarly, although not shown, database 20 may include both a distributed database and a local database.

In some embodiments, one or more of the database distributed database management systems 18 may be designated the master management system or host server system. The master management system may, in some cases, be responsible for reconciling database transactions and/or database transaction sequences as disclosed herein; although alternative configurations are possible.

The network 150, over which client systems 25 and nodes 10 communicate, may be a local area network, a metropolitan area network, a wide area network, a global data communications network such as the Internet, a private “intranet” or “extranet” network or any other suitable data communication medium—including combinations or variations thereof. For example, the Internet can provide file transfer, remote log in, email, news, RSS, and other services through any known or convenient protocol, such as, but is not limited to the TCP/IP protocol, Open System Interconnections (OSI), FTP, UPnP, iSCSI, NSF, ISDN, PDH, RS-232, SDH, SONET, etc.

Alternatively or additionally, the network 150 can be any collection of distinct networks operating wholly or partially in conjunction to provide connectivity to the client systems 25 and nodes 10 and may appear as one or more networks to the serviced systems and devices. In one embodiment, communications to and from client systems 25 can be achieved by, an open network, such as the Internet, or a private network, such as an intranet and/or the extranet. In one embodiment, communications can be achieved by a secure communications protocol, such as secure sockets layer (SSL), or transport layer security (TLS).

In addition, communications can be achieved via one or more wireless networks, such as, but is not limited to, one or more of a Local Area Network (LAN), Wireless Local Area Network (WLAN), a Personal area network (PAN), a Campus area network (CAN), a Metropolitan area network (MAN), a Wide area network (WAN), a Wireless wide area network (WWAN), Global System for Mobile Communications (GSM), Personal Communications Service (PCS), Digital Advanced Mobile Phone Service (D-Amps), Bluetooth, Wi-Fi, Fixed Wireless Data, 2G, 2.5G, 3G networks, enhanced data rates for GSM evolution (EDGE), General packet radio service (GPRS), enhanced GPRS, messaging protocols such as, TCP/IP, SMS, MMS, extensible messaging and presence protocol (XMPP), real time messaging protocol (RTMP), instant messaging and presence protocol (IMPP), instant messaging, USSD, IRC, or any other wireless data networks or messaging protocols.

The client systems (or clients) 25 are in communication with one or more nodes 10 via network 150. Client systems 25 can be any system and/or device, and/or any combination of devices/systems that is able to establish a connection with another device, a server and/or other systems. The client systems 25 typically include display or other output functionalities to present data exchanged between the devices to a user. For example, the client systems 25 can be, but are not limited to, a server desktop, a desktop computer, a computer cluster, a mobile computing device such as a notebook, a laptop computer, a handheld computer, a mobile phone, a smart phone, a PDA, a Blackberry device, a Treo, and/or an iPhone, etc. In one embodiment, client systems are coupled to the network 150. In some embodiments, the client systems may be directly connected to one another or to nodes 10.

The client systems 25 include a query interface 22 and one or more applications 26. An application 26 may execute on client 25 and may include functionality for invoking query interface 22 for transferring a database query to a database server for processing. The application 26 may invoke the query interface 22 for reading data from or writing data to a database table of a distributed database 20. In general, application 26 and query interface 22 may be any type of interpreted or executable software code such as a kernel component, an application program, a script, a linked library, or an object with method, including combinations or variations thereof. In one example, the application 26 comprises a multi-user interactive game; however, it is appreciated that other applications are also possible.

In some embodiments, one or more of the database management systems 18 maintain one or more transaction sequences for each client system 25 by asynchronously and concurrently reconciling the database transactions. The transaction sequences can comprise one or more database transactions. In operation, the database transactions may be generated by an application 26 within client system 25 and transferred to the associated database management system 18 via a query generated by query interface 22. As shown in the example of FIG. 1, the query is transferred over network 150 and received at one of the database management systems 18.

In some embodiments, each transaction sequence may be a continuous independent sequence or a linear time model that indicates database transactions from a personal point of view. The personal point of view may be, for example, the point of view of one or more applications running on a client and/or the point of view of a client system or an operator (e.g., user or player) of the client system.

In some embodiments, the transaction sequences may be represented by a graph such as a causality graph or a serialization graph. Causality graphs and serialization graphs contain information about current and historic database transactions or operations, such as database queries received from a client system.

In some embodiments, the database management system 18 maintains the associated transaction sequences for the client systems 25 and asynchronously and concurrently reconciles the database transactions within the transaction sequences with other relevant database transactions in other transactions sequences received within the distributed database system.

In some embodiments, each database transaction operates with a set of assumptions upon which the database transaction relies. As described herein, the assumptions are controlled with assertions that can be used in lieu of locks to permit interleaving of operations and increased concurrency. In some embodiments, the assertions enforce consistency using various mechanisms such as, for example, a multi-version concurrency control (MVCC) mechanism. As described herein, the concurrency control mechanisms facilitate the ability to seek a time in the past during which assertions are true. This process is referred to herein as “time traveling,” and is discussed in greater detail with reference to FIG. 6.

In some embodiments, database 20 includes a global transaction sequence containing the committed database transactions. In some embodiments, the global transaction sequence is replicated across some or all of the databases 20 in the distributed database environment 100.

FIG. 2 depicts a block diagram of an example node 210 in a distributed database environment 200, according to an embodiment. The distributed database environment 200 may be similar to the distributed database environment 100 of FIG. 1, although alternative configurations are possible.

In this example, node 210 includes a database management system 218 in communication with databases 220-D and 220-L (distributed and local, respectively), and a network 250. The network 250 may be any network such as, for example, network 150 of FIG. 1. The node 210 may be similar to the nodes 10 of FIG. 1; although alternative configurations are possible. In some embodiments, while each node includes a local database management system 219-L, only one master distributed database system 219-D exists. In this case, the distributed database system 219-D controls the interaction across database.

The database management system 218 further includes a distributed database management system 219-D, a local database management system 219-L, optional application programs 219-A. The distributed database management system 219-D coordinates access to the data at the various nodes. The distributed database management system 219-D may perform some or all of the following functions:

1. Keep track of where data is located in a distributed data dictionary. This includes presenting one logical database and schema to developers and users.

2. Determine the location from which to retrieve requested data and the location at which to process each part of a distributed query without any special actions by the developer or user.

3. If necessary, translate the request at one node using a local DBMS into the proper request to another node using a different DBMS and data model and return data to the requesting node in the format accepted by that node.

4. Provide data management functions such as security, concurrency and deadlock control, global query optimization, and automatic failure recording and recovery.

5. Provide consistency among copies of data across the remote sites (e.g., by using multiphase commit protocols).

6. Present a single logical database that is physically distributed. One ramification of this view of data is global primary key control, meaning that data about the same business object are associated with the same primary key no matter where in the distributed database the data are stored, and different objects are associated with different primary keys.

7. Be scalable. Scalability is the ability to grow, reduce in size, and become more heterogeneous as the needs of the business change. Thus, a distributed database must be dynamic and be able to change within reasonable limits without having to be redesigned. Scalability also means that there are easy ways for new sites to be added (or to subscribe) and to be initialized (e.g., with replicated data).

8. Replicate both data and stored procedures across the nodes of the distributed database. The need to distribute stored procedures is motivated by the same reasons for distributing data.

9. Transparently use residual computing power to improve the performance of database processing. This means, for example, the same database query may be processed at different sites and in different ways when submitted at different times, depending on the particular workload across the distributed database at the time of query submission.

10. Permit different nodes to run different DBMSs. Middleware (see Chapter 9) can be used by the distributed DBMS and each local DBMS to mask the differences in query languages and nuances of local data.

11. Allow different versions of application code to reside on different nodes of the distributed database. In a large organization with multiple, distributed servers, it may not be practical to have each server/node running the same version of software.

In one embodiment, each node includes both a local database system 219-L and a distributed database management system 219-D. In the example of FIG. 2, each site has a local DBMS 219-L that manages the local database 220-L stored at that site and a copy of the distributed DBMS database 220-D and the associated distributed data dictionary/directory (DD/D). The distributed DD/D contains the location of all data in the network, as well as data definitions.

Requests for data by users or application programs are first processed by the distributed DBMS 219-D, which determines whether the transaction is local or global. A local transaction is one in which the required data are stored entirely at the local site. A global transaction requires reference to data at one or more non-local sites to satisfy the request. For local transactions, the distributed DBMS 219-D passes the request to the local DBMS 219-L. For global transactions, the distributed DBMS 219-D routes the request to other sites as necessary. The distributed DBMSs at the participating sites exchange messages as needed to coordinate the processing of the transaction until it is completed (or aborted, if necessary).

FIG. 3 depicts a block diagram of the components of a database management system 350 for asynchronous distributed database management, according to an embodiment. The database management system 350 may be the database management system 18 of FIG. 1, although alternative configurations are possible.

The database management system 350 includes a network interface 302, a communications module 305, a database transaction reception module 310, a database transaction history module 315, a causality graph generation module 320, an assertion identification/extraction module 325, and a global transactions sequence module 330. In one embodiment, the database management system 350 is also coupled to a database 345. The database 345 can be the database 20 of FIG. 1, although alternative configurations are possible. Additional or less modules can be included without deviating from the novel art of this disclosure. Furthermore, each module in the example of FIG. 3 can include any number and/or combination of sub-modules and/or systems, implemented with any combination of hardware and/or software.

The database management system 350, although illustrated as comprised of distributed components (physically distributed and/or functionally distributed), could be implemented as a collective element. In some embodiments, some or all of the modules, and/or the functions represented by each of the modules can be combined in any convenient or known manner. Furthermore, the functions represented by the modules can be implemented individually or in any combination thereof, partially or wholly, in hardware, software, or a combination of hardware and software.

In the example of FIG. 3, the network interface 302 can be a networking device that enables the database management system 350 to mediate data in a network with an entity that is external to the database management system 350, through any known and/or convenient communications protocol supported by the host and the external entity. The database management system 350 can include one or more of a network adaptor card, a wireless network interface card, a router, an access point, a wireless router, a switch, a multilayer switch, a protocol converter, a gateway, a bridge, bridge router, a hub, a digital media receiver, and/or a repeater.

One embodiment of the database management system 350 includes the communications module 305. The communications module 305 can be any combination of software agents and/or hardware modules able to identify, detect, track, manage, receive, record, and/or process data access requests. The communications module 305, when in operation, is able to communicate with the network interface 302 to identify, detect, track, manage, receive, record, and/or process data access requests including, but not limited to, database queries and/or database transactions from client systems and/or other nodes in the distributed database system.

One embodiment of the database management system 350 includes the database transaction reception module 310. The database transaction reception module 310 can be any combination of software agents and/or hardware components able to receive and process data requests from the client devices and other nodes. For example, the database transaction reception module 310 is configured to receive and process database queries from the client devices and other data requests from other nodes in the system. The database transaction reception module 310 may then segment, route, and/or otherwise process the requests and/or identify the database transactions with the data requests or queries.

One embodiment of the database management system 350 includes the database transaction history module 315. The database transaction history module 315 can be any combination of software agents and/or hardware components able to track and store historical transactions. For example, the history may include transaction order, assumptions/assertions relied upon, etc. Advantageously, schemas do not need to include histories because the database keeps track of this information.

One embodiment of the database management system 350 includes the causality graph generation module 320. The causality graph generation module 320 can be any combination of software agents and/or hardware components able to interact with the transaction history module 315 to generate a causality graph for one or more database transactions in or indicated by a transaction sequence. For example, the causality graph generation module 320 can identify transaction sequences based on received database queries. As discussed, the database queries indicate one or more database transactions. The causality graph generation module 320 can use the database transaction information to interact with the database transaction history module 315 in order to identify the historical transactions upon which the current database transaction relies and build a causality graph based on this history information.

In one embodiment, the causality graph generation module 320 generates a causality graph indicating the one or more assertions upon which each database transaction relies. For example, in some embodiments, concurrency control schemes control concurrency by detecting invalid use after the fact. These concurrency controls may divide a transaction's existence into read, validate and publish phases. During the read phase, the scheme acquires assumptions from one or more distributed database resources regarding the underlying values of the assumptions upon which the transaction relies without regard to conflict or validity of those assumptions. The transaction sequences themselves and/or the database transaction history module may indicate the set of resources and/or assumptions relied upon for each database transaction in transaction sequence. In some embodiments, assertions may be, for example, database key values; although alternative configurations are possible.

One embodiment of the database management system 350 includes the assertion identification/extraction module 325. The assertion identification/extraction module 325 can be any combination of software agents and/or hardware components able to identify and/or extract the assertions associated with one or more database transactions. For example, the assertion identification/extraction module 325 may process database transactions, transaction sequences, and/or database queries to identify and/or extract the underlying assertions upon which the database transactions rely.

In one embodiment, each database transaction operates with a set of assumptions on which the database transaction relies. As described herein, the assumptions are controlled with assertions that can be used in lieu of locks to permit interleaving of operations and increased concurrency. The assertions can enforce consistency using various mechanisms such as, for example, a multi-version concurrency control (MVCC) mechanism as described herein.

One embodiment of the database management system 350 includes the global transaction sequence module 330. The global transaction sequence module 330 can be any combination of software agents and/or hardware components able to maintain, reconcile, and commit database transactions to a global transaction sequence. The global transaction sequence module 330 may maintain, reconcile, and commit database transactions from individual transaction sequences (e.g., from private sequences). In this example, the global transaction sequence module 330 includes a consensus engine 332, a polling engine 333, a reconciliation engine 334, a notification engine 335, and an update/commit engine 336.

In one embodiment the consensus engine 332 is configured to achieve consensus among a plurality of database resources of the distributed database system regarding the validity of each assertion. The plurality of resources or system may comprise, for example, nodes or database management systems in the distributed database system. In one embodiment, the systems and methods described herein can operate according to the CAP theorem, also known as Brewer's theorem. The CAP theorem states that it is impossible for a distributed computer system to simultaneously guarantee consistency, availability, and partition tolerance.

Consistency guarantees that all nodes of the distributed database see the same data at the same time. Availability guarantees that every request receives a response about whether the request was successful or failed. Partition tolerance guarantees that the system continues to operate despite arbitrary message loss. According to the CAP theorem, a distributed system can satisfy any two of the above guarantees at the same time, but not all three.

There are certain limitations on database system that maintain a distributed scalable state due, at least in part, to unreliable processors. One solution is allowing consensus. Consensus is the process of agreeing on a single result among a group of participants (or resources). Consensus protocols are the basis for the state machine approach to distributed computing. The state machine approach is a technique for converting an algorithm into a fault-tolerant, distributed implementation. Every potential fault must have a way to be dealt with and ad-hoc techniques often leave important cases of failures unresolved.

In some embodiments, the systems and methods described herein use consensus protocols such as, for example, the Paxos algorithm. The Paxos algorithm describes protocols for solving consensus in a network of unreliable processors. This problem becomes difficult when the participants or their communication medium experience failures. The Paxos approach provides a technique to ensure that all cases are handled safely. However, these cases may still need to be individually coded.

The Paxos protocols define a number of roles and describes the actions of the processes by their roles in the protocol: client, acceptor, proposer, learner, and leader. In typical implementations, a single processor may play one or more roles at the same time. This does not affect the correctness of the protocol—it is usual to coalesce roles to improve the latency and/or number of messages in the protocol.

The Paxos protocols include a spectrum of trade-offs between the number of processors, number of message delays before learning the agreed value, the activity level of individual participants, number of messages sent, and types of failures. However, no fault-tolerant consensus protocol can guarantee progress.

Clients: Clients issue requests to the distributed system, and wait for a response. For instance, a write request on a file in a distributed file server. Acceptors: Acceptors act as the fault-tolerant “memory” of the protocol. Acceptors are collected into groups called Quorums. Any message sent to an Acceptor must be sent to a Quorum of Acceptors, and any message received from an Acceptor is ignored unless a copy is received from each Acceptor in a Quorum. Proposers: Proposers advocate a client request, attempt to convince the Acceptors to agree on it, and act as a coordinator to move the protocol forward when conflicts occur. Learners: Learners act as the replication factor for the protocol. Once a Client request has been agreed on by the Acceptors, the Learner may take action (i.e., execute the request and send a response to the client). To improve availability of processing, additional Learners can be added. Leaders: Leaders are distinguished Proposers that are required to make progress. Many processes may believe they are leaders, but the protocol only guarantees progress if one of them is eventually chosen. If two processes believe they are leaders, it is possible to stall the protocol by continuously proposing conflicting updates. The safety properties are preserved regardless.

In one embodiment the polling engine 333 is configured to poll or otherwise continuously, repeatedly (e.g., more than once), and/or periodically generate a trigger that is sent to the consensus engine 332 to poll the database resources regarding the validity of one or more assertions included within the database transaction.

In one embodiment the reconciliation engine 334 is configured to maintain the global transaction sequence by continuously and asynchronously reconciling the plurality of transaction sequences. For example, the reconciliation engine 334 may reconcile database transactions according to the underlying assertions. That is, the assertions can be used in lieu of locks to permit interleaving of database transactions and increase concurrency.

In one embodiment the notification engine 335 is configured to notify clients when database transactions have been aborted (failed) or when database transactions have successfully completed. For example, the notification engine 335 notifies a client in the distributed database when a database transaction has been aborted if consensus is not achieved within a timeout interval or timeout period. Similarly, the notification engine 335 can provide an early indication to a client system or application on a client system (e.g., prior to updating the distributed database system with the database transaction) that the database transaction has completed successfully. Advantageously, providing the early notification divorces the read-time from update-time in the evaluation an expression or database transaction by leading a client system to believe that the transaction is completed when, in fact, the transaction is not complete.

In one embodiment the update/commit engine 336 is configured to commit database transactions to the global transaction sequence. To ensure data integrity for real-time, distributed update operations, the cooperating transaction managers can execute a commit protocol. The commit protocol is a well-defined procedure (involving an exchange of messages) to ensure that a global transaction is either successfully completed at each site or else aborted.

The most widely used protocol is called a two-phase commit. A two-phase commit protocol ensures that concurrent transactions at multiple sites are processed as though they were executed in the same, serial order at all sites. A two-phase commit works in two phases. To begin, the site originating the global transaction or an overall coordinating site sends a request to each of the sites that will process some portion of the transaction. Each site processes the subtransaction (if possible), but does not immediately commit (or store) the result to the local database. Instead, the result is stored in a temporary file. Additionally, each site locks (or prohibits others from updating) its portion of the database being updated and notifies the originating site when it has completed its subtransaction. When all sites have responded, the originating site now initiates the two-phase commit protocol.

In a prepare phase, a message is broadcast to every participating site (or node), asking whether that site is willing to commit its portion of the transaction at that site. Each site returns an “OK” or “not OK” message. An “OK” indicates that the remote site promises to allow the initiating request to govern the transaction at the remote database. Next, in a commit phase, the originating site collects the messages from all sites. If all are “OK,” it broadcasts a message to all sites to commit the portion of the transaction handled at each site. However, if one or more responses are “not OK,” it broadcasts a message to all sites to abort the transaction.

A limbo transaction can be identified by a timeout or polling. With a timeout (no confirmation of commit for a specified time period), it is not possible to distinguish between a busy or failed site. Polling can be expensive in terms of network load and processing time. With a two-phase commit strategy for synchronizing distributed data, committing a transaction is slower than if the originating location were able to work alone.

One embodiment of the database management system 350 includes the database 345. The database 345 can store any data items/entries including, but not limited to, software, descriptive data, images, system information, drivers, and/or any other data item utilized by the database management system and/or any other systems for operation. The database 345 may be coupled to the database management system 350. The database 345 may be managed by a database management system (DBMS), for example but not limited to, Oracle, DB2, Microsoft Access, Microsoft SQL Server, PostgreSQL, MySQL, FileMaker, etc. The user data repository 128 can be implemented via object-oriented technology and/or via text files, and can be managed by a distributed database management system, an object-oriented database management system (OODBMS) (e.g., ConceptBase, FastDB Main Memory Database Management System, JDOInstruments, ObjectDB, etc.), an object-relational database management system (ORDBMS) (e.g., Informix, OpenLink Virtuoso, VMDS, etc.), a file system, and/or any other convenient or known database management package.

FIG. 4 depicts a flow diagram illustrating an example process 400 asynchronous distributed database management, according to an embodiment. One or more database management systems, such as, for example, the database management systems 18 of FIG. 1, among other functions, control transaction consistency including maintaining and/or reconciling database transaction in the distributed database system and the asynchronous distributed database management features described herein. In one embodiment, each transaction sequence indicates one or more uncommitted database transactions and each uncommitted database transaction includes one or more assertions that require consensus among a plurality of resources in the distributed database system to reconcile.

In a reception operation 410, the database management system receives a database transaction associated with a transaction sequence from a client in a distributed database system. As discussed, the database transaction can include one or more assertions that require consensus among a plurality of resources in the distributed database system to reconcile.

In one embodiment, the database transactions may be received as a result of one or more client queries that include the one or more database transactions. In some embodiments, a database query can indicate one or more database transactions initiated by an application running on one of a plurality of clients in the distributed database system. The database queries can be received at any number of database management systems in the distributed database system; however, the example of FIG. 4 is discussed with reference to a single database management system.

In some embodiments, each transaction sequence may be a continuous independent sequence or a linear time model that indicates database transactions from a personal point of view or the point of view of one or more applications running on a client. The personal point of view may be, for example, the point of view of a client system or an operator of the client system.

In some embodiments, the transaction sequences may be represented by a graph such as a causality graph or a serialization graph. Causality graphs and serialization graphs contain information about current and historic database transactions or operations, such as database queries received from a client system.

In some embodiments, serialization graph algorithms (SGAs) control the concurrent operation of temporally overlapping transactions by computing an equivalent serial ordering. SGAs try to “untangle” a convoluted sequence of operations by multiple transactions into a single cohesive thread of execution. SGAs function by creating a serialization graph. The nodes in the graph correspond to transactions in the system. The arcs of the graph correspond to equivalent serial ordering. As arcs are added to the graph, the algorithms look for cycles. If there are no cycles, then the transactions have an equivalent serial order and consistency is assured. If a serialization cycle were found, however, then consistency would be compromised if all transactions in the cycle were allowed to commit. In this case, the SGA would restore consistency by aborting one or more of the transactions forming the cycle.

In some embodiments, each causality graph represents the point of view of a client system, and thus the transaction sequence indicates all transaction initiated from that client. In other embodiments, each client system may have any number of associated transaction sequences. For example, a causality graph may represent the database transactions as perceived from an individual player of an online interactive game. Thus, the individual transaction sequences provide for the ability to eventually overlap database transactions by temporarily (during the read phase) taking into consideration only those database transactions relevant to that individual transaction sequence.

In an identification operation 420, the database management system processes the database transactions to identify the assertions that require consensus among a plurality of resources in the distributed database system to reconcile. As discussed above, database transaction can include one or more assertions upon which the transaction relies.

In a polling operation 430, the database management system polls the database resources regarding the validity of one or more assertions. For example, the database management system may poll a plurality of database resources regarding the validity of the one or more assertions included within the database transaction to achieve a consensus.

In an update operation 440, the database management system updates the database transaction upon achieving consensus if the consensus is achieved within a specified period of time. For example, the database management system can update the database transaction in the distributed database system upon achieving the consensus if the consensus is achieved within a timeout interval. In this example, the consensus is not initially achieved among the plurality of database resources and thus, the database management system must achieve consensus subsequent to the failure to achieve consensus. Failure to achieve consensus can occur as a result of the plurality of resources disagreeing as to the validity of one or more assertions. Similarly, failure to achieve consensus can occur as a result of the assertion not being valid with respect to the consensus achieved by the plurality of resources. For example, the assertion is not valid with respect to the consensus achieved by the plurality of resources if the assertion believes that “X=1,” and the plurality of resources believe that “X=3.”

In a notification operation 450, the database management system, notifies the client system that the database transaction has been successfully completed prior to the updating operation 440. For example, the database management system can notify the client in the distributed database that the database transaction has been aborted if the consensus is not achieved within the timeout interval. Advantageously, providing the early notification divorces the read-time from update-time, in the evaluation an expression or database transaction, by leading a client system to believe that the transaction is completed when, in fact, the transaction has not been updated in the distributed database system.

FIG. 5 depicts a flow diagram illustrating an example process 500 for controlling transaction consistency in a distributed database system, according to one embodiment. More specifically, process 500 illustrates an example of asynchronous distributed database management. One or more database management systems, such as, for example, the database management systems 18 of FIG. 1, among other functions, control transaction consistency including maintaining and/or reconciling database transaction in the distributed database system and the asynchronous distributed database management features described herein.

In operation 502, a database management system receives a query from a client system. The query can indicate one or more database transactions initiated by an application running on the client system. The distributed database system can receive any number of queries from any number of applications running on any number of client systems in the distributed database system; however, operation and handing of a single query is discussed in example process 500.

In operation 504, the database management system processes the query to identify one or more assertions that require consensus among a plurality of machines (i.e., database resources or database management systems) within the distributed database in order to reconcile.

In operation 506, the database management system optionally sets a timeout interval. The timeout interval generally indicates the interval during which consensus must be achieved in order to commit, update, or otherwise complete the database transaction. If the timeout interval expires, the database transaction will time not be completed (i.e., the database transaction will fail). In some cases, the database management system will have to take certain measures to undo other database transactions that depend on the uncompleted database transaction and indicate that the database transaction (which may have been indicated to a client system as completing normally) did not complete normally.

In one embodiment, the database management system determines the likelihood that the consensus can be achieved. This likelihood may be based on, for example, the difference in the database key values, the type of assertion, the key value of an assertion, etc. The database management system can set the timeout interval based upon the likelihood that the consensus can be achieved. In one embodiment, the timeout interval comprises a duration or range of time between one half of a second and three seconds. The database management system may dynamically set this value or this may be a pre-determined value such as, for example, pre-determined by an application developer. In other embodiments, the timeout interval comprises a duration or range of time less than one half of a second.

In operation 508, the database management system queries passive learners in the system to identify a history of the assertions as perceived from the passive learners. In some embodiments, the history of the assertions from the perspective of each of the passive learners represents, for example, the value they believe a database key to be for a time series (before and/or after specific database transactions). The history of changes to the assertion is kept by the passive learners so that the system can eventually determine the last time that there was a consensus among the machines (or database resources) on the value of an assertion or database key. This is discussed in greater detail with respect to operation 512.

In operation 510, the database management system determines whether or not a consensus exists among the resources with respect to the assertions relied upon by the one or more database transactions indicated in the query. If a consensus exists then, in operation 512, the database transaction is updated and, in operation 514, the assertions are drained into or toward the next transaction sequence at the next (or a higher) hierarchical level. In this example, the next transaction sequence is the global transaction sequence that is replicated across all of the machines in the distributed database system; although alternative configurations are possible.

If a consensus does not exist then, in operation 512, the database management system determines whether the time interval has expired. If the timeout interval has expired, then, in operation 518, the database transaction is aborted or otherwise terminated. However, if the time interval has not expired then the database management system again queries the passive learners for a current history of the assertions.

FIG. 6 depicts a flow diagram illustrating an example process 600 for controlling transaction consistency in a distributed database system, according to one embodiment. Process 600 of FIG. 6 is similar to process 500 of FIG. 5; however, process 600 additionally includes the ability to time travel in order to reconcile database transactions.

In particular, if a consensus does not exist and the timeout interval has expired then, in operation 618, the database management system falls back consistently across all assertions in the history of the passive learners until a consensus can be achieved. This process is referred to herein as “time traveling.” In operation 514, the system determines whether or not consensus is achieved among the resources with respect to the assertions relied upon by the one or more database transactions indicated in the query. If a consensus is achieved during the time traveling, then in operation 516 the database transactions that have a consensus are drained toward the next sequence and the other transaction sequences are removed.

FIG. 7 depicts a sequence diagram 700 illustrating example operations of components of a distributed database environment, according to one embodiment. More specifically, sequence diagram 700 illustrates an example of essentially divorcing the read-time from update-time in the evaluation of an expression or database transaction.

As shown, the distributed database system environment includes a client #1, and database management systems (DBMS) A-D. A single client, client #1, is shown in this example; however, as discussed above, any number of clients may be active and/or present at any number of locations in a distributed database system. In this example, the database management systems are all located at different sites, although some or all of the database management system can be co-located.

To begin, client #1 sends a database transaction A to database management system A. Database management system A then identifies a specific configuration required for the database transaction. For example, the database management system may process the database transaction to identify the one or more assertions, wherein the one or more assertions must have a specific configuration in order to update the database transaction in the distributed database system. The specific configuration may indicate for example, one or more assertions that have keys or database entries that must be specific values. That is, the database management system makes certain assumptions (based on previously read values) about the assertions (e.g., keys or database entries). The specific configuration may take additional and/or alternative forms.

The database management system may then determine a first configuration among a plurality of database resources regarding the one or more assertions at a first time. In this example, the first configuration is initially different than the specific configuration. The first configuration may result, for example, by way of querying passive learners (i.e, DBMS C-D); although alternative configurations and/or variations are possible.

In this example, the database management system determines that the first configuration is different than the specific configuration. The first configuration can be different than the specific configuration for any number of reasons. For example, in some embodiments, the first configuration will be different than the specific configuration if a consensus is not achieved among the passive learners with respect to the validity (or value) of the assertions. This may result is undetermined first configuration which will always be different than the specific configuration. Alternatively or additionally, the first configuration can be different than the specific configuration if the specific configuration (e.g., assertions from client #1) is different than the consensus achieved from the passive learners.

Because the first configuration is different than the specific configuration, the database management system may wait before polling or otherwise querying the passive learners again. In this example, the second query results in a first configuration that is the same as the specific configuration. Accordingly, the database transaction can be updated and/or otherwise committed globally to the distributed database system.

FIG. 8 shows a diagrammatic representation of a machine in the example form of a computer system 700 within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.

In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment.

The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.

While the machine-readable medium is shown in an exemplary embodiment to be a single medium, the term “machine-readable 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 “machine-readable 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 any one or more of the methodologies of the present invention.

In general, the routines executed to implement the embodiments of the disclosure, may be implemented as part of an operating system or a specific application, component, program, object, module or sequence of instructions referred to as “computer programs.” The computer programs typically comprise one or more instructions set at various times in various memory and storage devices in a computer, and that, when read and executed by one or more processors in a computer, cause the computer to perform operations to execute elements involving the various aspects of the disclosure.

Moreover, while embodiments have been described in the context of fully functioning computers and computer systems, those skilled in the art will appreciate that the various embodiments are capable of being distributed as a program product in a variety of forms, and that the disclosure applies equally regardless of the particular type of machine or computer-readable media used to actually effect the distribution.

Further examples of machine or computer-readable media include but are not limited to recordable type media such as volatile and non-volatile memory devices, floppy and other removable disks, hard disk drives, optical disks (e.g., Compact Disk Read-Only Memory (CD ROMS), Digital Versatile Disks, (DVDs), etc.), among others, and transmission type media such as digital and analog communication links.

Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to.” As used herein, the terms “connected,” “coupled,” or any variant thereof, means any connection or coupling, either direct or indirect, between two or more elements; the coupling of connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word “or,” in reference to a list of two or more items, covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list.

The above detailed description of embodiments of the disclosure is not intended to be exhaustive or to limit the teachings to the precise form disclosed above. While specific embodiments of, and examples for, the disclosure are described above for illustrative purposes, various equivalent modifications are possible within the scope of the disclosure, as those skilled in the relevant art will recognize. For example, while processes or blocks are presented in a given order, alternative embodiments may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified to provide alternative or subcombinations. Each of these processes or blocks may be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed in parallel, or may be performed at different times. Further, any specific numbers noted herein are only examples: alternative implementations may employ differing values or ranges.

The teachings of the disclosure provided herein can be applied to other systems, not necessarily the system described above. The elements and acts of the various embodiments described above can be combined to provide further embodiments.

Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the disclosure can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further embodiments of the disclosure.

These and other changes can be made to the disclosure in light of the above Detailed Description. While the above description describes certain embodiments of the disclosure, and describes the best mode contemplated, no matter how detailed the above appears in text, the teachings can be practiced in many ways. Details of the system may vary considerably in its implementation details, while still being encompassed by the subject matter disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the disclosure should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the disclosure with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the disclosure to the specific embodiments disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the disclosure encompasses not only the disclosed embodiments, but also all equivalent ways of practicing or implementing the disclosure under the claims.

While certain aspects of the disclosure are presented below in certain claim forms, the inventors contemplate the various aspects of the disclosure in any number of claim forms. For example, while only one aspect of the disclosure is recited as a means-plus-function claim under 35 U.S.C. §112, ¶6, other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer-readable medium. (Any claims intended to be treated under 35 U.S.C. §112, ¶6 will begin with the words “means for”.) Accordingly, the applicant reserves the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the disclosure.

Claims

1. A method of asynchronous distributed database management, the method comprising:

receiving, at a database management system, a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions;

polling, at the database management system, a plurality of database resources regarding the validity of the one or more assertions included within the database transaction to achieve a consensus; and

updating, at the database management system, the database transaction in the distributed database system upon achieving the consensus if the consensus is achieved within a timeout interval, wherein the consensus is not initially achieved among the plurality of database resources.

2. The method of claim 1, further comprising:

notifying, at the database management system, the client in the distributed database that the database transaction has been aborted if the consensus is not achieved within the timeout interval.

3. The method of claim 1, wherein the database transaction is initiated by an application running on the client.

4. The method of claim 1, further comprising:

prior to updating the distributed database system, notifying the client that the database transaction has completed successfully.

5. The method of claim 1, wherein the timeout interval comprises a duration of time between one half of a second and three seconds.

6. The method of claim 1, wherein the timeout interval comprises a duration of time less than one half of a second.

7. The method of claim 1, wherein updating the distributed database system further comprises:

asynchronously reconciling the database transaction with one or more other database transactions in the distributed database system.

8. The method of claim 1, further comprising:

prior to updating the distributed database system, reading information related to the database transaction from the distributed database system; and

transferring the information to the client regardless of whether the consensus has been achieved.

9. The method of claim 1, further comprising:

receiving, at the database management system, a second database transaction associated with a second transaction sequence from a second client in the distributed database system, wherein the second database transaction includes one or more second assertions, and wherein the one or more second assertions require reading the information related to the database transaction.

10. The method of claim 1, wherein updating the distributed database system further comprises:

committing the database transaction to a global transaction sequence; and

replicating the global transaction sequence across the plurality of database resources of the distributed database.

11. The method of claim 1, further comprising:

determining, at the database management system, a likelihood that the consensus can be achieved.

12. The method of claim 11, further comprising:

setting, at the database management system, the timeout interval based upon the likelihood that the consensus can be achieved.

13. The method of claim 1, wherein the plurality of database resources comprise one or more of other database management systems in the distributed database system or one or more storage management systems in the distributed database system.

14. A method of asynchronous distributed database management, the method comprising:

receiving, at a database management system, a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions;

processing, at the database management system, the database transaction to identify the one or more assertions, wherein the one or more assertions must have a specific configuration in order to update the database transaction in the distributed database system;

determining, at the database management system, a first configuration among a plurality of database resources regarding the one or more assertions at a first time, wherein the first configuration is different than the specific configuration; and

updating, at the database management system, the database transaction in the distributed database system at a second time if a second configuration among the plurality of database resources regarding the one or more assertions is the same as the specific configuration at the second time.

15. The method of claim 14, wherein the specific configuration requires that the one or more assertions be valid.

16. The method of claim 14, further comprising:

notifying, at the database management system, the client in the distributed database that the database transaction has been aborted if the second configuration is different than the specific configuration at the second time.

17. The method of claim 14, wherein the database transaction is initiated by an application running on the client.

18. The method of claim 17, further comprising:

prior to updating the distributed database system, notifying the application that the database transaction has completed successfully.

19. The method of claim 14, wherein updating the distributed database system further comprises:

asynchronously reconciling the database transaction with one or more other database transactions in the distributed database system.

20. The method of claim 14, further comprising:

prior to updating the distributed database system, reading information related to the database transaction from the distributed database system; and

transferring the information to the client regardless of whether the consensus has been achieved.

21. The method of claim 14, further comprising:

receiving, at the database management system, a second database transaction associated with a second transaction sequence from a second client in the distributed database system, wherein the second database transaction includes one or more second assertions, and wherein the one or more second assertions require reading the information related to the database transaction.

22. The method of claim 14, wherein updating the distributed database system further comprises:

committing the database transaction to a global transaction sequence; and

replicating the global transaction sequence across the plurality of database resources of the distributed database.

23. The method of claim 14, further comprising:

determining, at the database management system, a likelihood that the consensus can be achieved.

24. The method of claim 23, further comprising:

setting, at the database management system, the timeout interval based upon the likelihood that the consensus can be achieved.

25. The method of claim 14, wherein the resources comprise one or more of other database management systems in the distributed database system or storage management systems in the distributed database system.

26. A database management system comprising:

a processing unit;

an interface configured to receive a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions;

a memory unit having instructions stored thereon, wherein the instructions, when executed by the processing unit, cause the processing unit to process the database transaction to identify the one or more assertions, wherein the one or more assertions must have a specific configuration in order to update the database transaction in the distributed database system, determine a first configuration among a plurality of database resources regarding the one or more assertions at a first time, wherein the first configuration is different than the specific configuration, and update the database transaction in the global transaction sequence at a second time if a second configuration among the plurality of database resources regarding the one or more assertions is the same as the specific configuration at the second time.

27. The database management system of claim 26, wherein the specific configuration requires that the one or more assertions be valid.

28. The database management system of claim 26, wherein the instructions, when executed by the processing unit, further cause the processing unit to notify the client in the distributed database system that the database transaction has been aborted if the second configuration is different than the specific configuration at the second time.

29. The database management system of claim 26, wherein the database transaction is initiated by an application running on the client.

30. The database management system of claim 29, wherein the instructions, when executed by the processing unit, further cause the processing unit to notify the application that the database transaction has completed successfully prior to updating the distributed database system.

31. The database management system of claim 26, wherein the instructions, when executed by the processing unit, further cause the processing unit to determine a likelihood that the consensus can be achieved.

32. The database management system of claim 31, wherein the instructions, when executed by the processing unit, further cause the processing unit to set a timeout interval, wherein the second time is less than or equal to the timeout interval.

33. A database management system comprising:

a processing unit;

an interface configured to receive a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions;

a memory unit having instructions stored thereon, wherein the instructions, when executed by the processing unit, cause the processing unit to repeatedly query database resources regarding the validity of one or more assertions included within the database transaction to achieve a consensus, and update the database transaction in the distributed database system upon achieving the consensus if the consensus is achieved within a timeout interval, wherein the consensus is not initially achieved among the plurality of resources, and notify the client in the distributed database that the database transaction has been aborted if the consensus is not achieved within the timeout interval.

34. A database management system comprising:

means for receiving a database transaction associated with a transaction sequence from a client in a distributed database system, wherein the database transaction includes one or more assertions;

means for polling a plurality of database resources regarding the validity of the one or more assertions included within the database transaction to achieve a consensus; and

means for updating the database transaction in the distributed database system upon achieving the consensus if the consensus is achieved within a timeout interval, wherein the consensus is not initially achieved among the plurality of database resources.