JP2020504867A - System and method for aggregating, filtering, and presenting streaming data - Google Patents

Abstract

Disclosed are systems and methods for aggregating, filtering, and presenting streaming data. In one embodiment, a method for presenting streaming data includes: (1) receiving, from a client, a query including a plurality of parameters at a web services layer for a server including at least one computer processor; 2) including a data caching layer for a server that receives streaming data from at least one predefined streaming data source; (3) the data caching layer fuses the streaming data for each of the plurality of parameters; The data caching layer aggregates the fused data, (5) the data caching layer generates a snapshot of the fused data by concurrently executing queries on the fused data, and (6) snaps. Shots It may include outputting the Ant.

Description

  [0001] The present disclosure relates generally to systems and methods for aggregating, filtering, and presenting streaming data.

  [0002] Both public and private clouds are becoming increasingly common computing environments. However, these environments do not support streaming data due to variable latency between the host system and the remote operating system. In addition, the cost of pushing (transferring) as much as terabytes of streaming market data into various clouds incurs very high “transit” charges from providers, thus using the cloud for data-driven applications. Decrease value proposal.

  [0003] Systems and methods for aggregating, filtering, and presenting streaming data are disclosed. In one embodiment, a method for presenting streaming data comprises: (1) receiving a query including a plurality of parameters from a client at a web services layer for a server including at least one computer processor; 2) the data caching layer for the server receives the streaming data from at least one predefined streaming data source; (3) the data caching layer fuses the streaming data for each of the plurality of parameters; The caching layer aggregates the fused data, (5) the data caching layer generates a snapshot of the fused data by simultaneously executing a query on the fused data, and (6) the snapshot. The client It may include outputting the.

[0004] In one embodiment, the parameters may include specific descriptors for securities and / or investments.
[0005] In one embodiment, the query may further include the identity of the streaming data source.

[0006] In one embodiment, the streaming data may include market data.
[0007] In one embodiment, the web services layer may output a snapshot that is delayed by a predetermined amount of time, wherein the time period is based on one or more rules associated with the streaming data.

  [0008] In one embodiment, the method may further include the step of the entitlement service layer for the server verifying that the client is authorized to access the information in response to the query.

  [0009] In one embodiment, the method may further include authenticating the client based on at least one client credential received from the client.

[0010] In one embodiment, the snapshot may be accurate for securities and / or investments for a period of time.
[0011] In one embodiment, the snapshot may include appropriate states for securities and / or investments for a period of time.

  [0012] According to another embodiment, a system for presenting streaming data is a plurality of streaming data sources and a data loader for each streaming data source for receiving streaming data from the streaming data sources. , A data loader, a data caching layer receiving streaming data from the data loader, and a web services layer including at least one computer processor in communication with the data caching layer. The web service layer may receive a query including a plurality of parameters from the client, the data caching layer may consolidate the streaming data for each of the plurality of parameters, and the data caching layer may consolidate the merged data. Can be aggregated and the data caching layer can generate a snapshot of the fused data by executing queries on the fused data simultaneously and output the snapshot to the client .

[0013] In one embodiment, the parameters may include specific descriptors for securities and / or investments.
[0014] In one embodiment, the query may include the identity of the streaming data source.

[0015] In one embodiment, the streaming data may include market data.
[0016] In one embodiment, the web services layer can output a snapshot that is delayed by a predetermined amount of time.

[0017] In one embodiment, the time period may be based on one or more rules associated with the streaming data.
[0018] In one embodiment, the query may be received from at least one of a cloud application and a local application.

  [0019] In one embodiment, the system may further include an entitlement service layer for the server that verifies that the client is authorized to access the information in response to the query. The entitlement service layer may further authenticate the client based on at least one client credential received from the client.

[0020] In one embodiment, the snapshot may be accurate for securities and / or investments for a period of time.
[0021] In one embodiment, the snapshot may indicate an appropriate state for securities and / or investments for a period of time.

  [0022] For a more complete understanding of the present invention, its objects and advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings.

[0023] FIG. 3 illustrates a system for aggregating, filtering, and presenting streaming data according to one embodiment. [0024] FIG. 9 illustrates a method for aggregating, filtering, and presenting streaming data according to one embodiment. [0025] FIG. 7 illustrates a strategic flow provided in accordance with one embodiment. 6 is an exemplary process flow according to one embodiment.

[0027] Some embodiments of the present invention and their advantages can be understood by reference to FIGS.
[0028] Embodiments are directed to systems and methods for aggregating, filtering, and presenting streaming data.

  [0029] In one embodiment, data from internal and external sources can be pushed into the high speed data aggregation engine. The client can make a simple web service request and specify the client's credentials, source of information, and a list of requested information. For example, at a financial institution, a client may submit a list of securities and fields. The client then receives a single response with the information needed by the client. This reduces or eliminates the high-speed stream management that all applications need to support, as well as the required infrastructure and development.

  [0030] In one embodiment, any suitable aggregation engine may be used as needed and / or desired. In one embodiment, the aggregation engine enables Structured Query Language ("SQL") style content filtering on individual fields within the data payload, allowing near real-time analysis for a wide range of products. be able to.

  [0031] Embodiments may provide some or all of the following: These include: (1) increased price advantage of cloud-based applications due to lower data transit costs; (2) significant increase in technology costs due to reduced infrastructure requirements and shorter development cycles for data-driven applications. (3) more replaceable developer workforce through simplification of APIs and integration using spreadsheets; (4) advanced content filtering across disparate sources has been cost prohibitive in the past for real-time application features (5) facilitate analysis of variance by merging external and internal data; and (6) reduce the cost of data by sending real-time data to individuals who do not need it in real time. Change Or the ability to delay. Other benefits can be provided as well.

  [0032] In the financial industry, because market data and messaging involve large amounts of data, clients are expected to perform considerable work associated with handling payloads emanating from a ticker plant. Clients often deal with hardware and software issues related to large amounts of information, such as allowing users to fuse information to profit, aggregate across many threads and systems to support portfolio management, etc. There is a need to do. Embodiments address these and other issues while providing end users and developers with an interface to filtering.

[0033] Referring to FIG. 1, a system for aggregating, filtering, and presenting streaming data is disclosed in accordance with one embodiment. System 100 includes a plurality of client access points 110, web service layer 120, a data caching layer 130, the data loader _{140 1,} 140 2, ..., 140 _n, and data sources _{150 1,} 150 2, ..., a 150 _n Can be included. Data source 150 may receive data from one or more streaming data sources, such as the Internet, as well as external market data, industry news, and the like.

  [0034] Although three data loaders 140 and data sources 150 are shown in FIG. 1, more or fewer data loaders 140 and data sources 150 may be provided as needed and / or desired. It should be recognized that

  [0035] Data loader 140 may receive data from data source 150. In one embodiment, each data loader 140 can “feed” streaming data from one or more data sources 150 into the data caching layer 130. Each data loader 140 may be in further communication with the web services layer 120. For example, each data loader 140 can communicate with a control plane service 126, which instructs one or more data loaders 140 to create a new subscription, retry a failure, etc. Can be ordered.

  [0036] The data caching layer 130 may service requests from the web services layer 120. In one embodiment, the data caching layer 130 can function as both a database and a message bus.

  [0037] In one embodiment, the data caching layer 130 may also filter the data and provide a "snapshot" of the requested data.

  [0038] An example of a suitable data caching layer 130 is an Advanced Message Processing System (AMPS) from 60 East Technologies.

  [0039] Web services layer 120 may interface with clients using one or more client access points 110. In one embodiment, the web services layer may provide services such as a configuration management service 122, a monitoring service 124, a control plane layer 126, and an entitlement service 128. Other services can be provided as needed and / or desired.

  [0040] In one embodiment, the configuration management service 122 provides configuration data for one or more data loaders 140, such as what data source 150 to connect to and how to connect to the data source 150. be able to. In one embodiment, the configuration management service 122 loads runtime configuration information, such as data loader 140, web services layer 120, connection information (eg, host: port) for the entitlement service 128, and what data feed to load. , What web connection is supported (http or https), SSL certificate location, connection and thread poll sizing, logging interval, environment (dev / test / prod), etc. can be provided.

  [0041] In one embodiment, the monitoring service 124 can monitor the status of one or more data sources 150 and can re-route requests if the data sources become unavailable.

  [0042] The control plane service 150 may interface with one or more data loaders 140. In one embodiment, the control plane service 150 passes directives between services, and the automation instructions (eg, the monitoring device 124 notices the failure of the data loader and switches the web service layer to switch the server within the data aggregation layer 130). 120, and manual directives (eg, the operations team would like to take the service offline).

[0043] In one embodiment, the entitlement service 128 may verify that the client is authorized to access the requested data.
[0044] In one embodiment, the client access point 110 may include, for example, a cloud application, a local application, a user interface, an API, etc. In one embodiment, the client access point 110 can provide a spreadsheet, for example, as output to the client.

  [0045] In one embodiment, the system 100 may include the ability to provide a "subscription" for clients to receive updates. In one embodiment, updates to a complex query may be smaller than resubmitting the query and receiving the entire result set several times a second.

[0046] Referring to FIG. 2, a method for aggregating, filtering, and presenting streaming data is disclosed in accordance with one embodiment.
[0047] At step 210, the client may request information of interest via an interface, such as a cloud application, a local application, an upload, and the like. Also, in one embodiment, the client can provide credentials and identify the source of the information and the list of requested information. In another embodiment, machine learning can be used to identify sources based on past queries.

[0048] In one embodiment, a client may use a web services protocol to request information. Web services protocols can use, for example, SQL-like syntax to filter information. Exemplary queries that may be filed, ^{"(/ BID // ASK> = (} 0.05 * / TRDPRC_1)) " was 5% of the value of the value of BID divided by the value of "ASK is TRDPRC_1 That is all. "

  [0049] In a financial system, a query may include identifying information such as stocks, industries, fields / areas of interest, and the like. Queries can be used in filters.

  [0050] In one embodiment, the request may be a subscription (e.g., for a stock, industry, etc.). In one embodiment, the request may specify a period or condition for which each snapshot will be provided.

  [0051] At step 220, the client may be authorized to access the requested data. In one embodiment, this may involve an entitlement check to determine whether the client is allowed access to the requested information.

[0052] In one embodiment, the client can be further authenticated based on credentials that can be provided as part of the request.
[0053] At step 230, the request may be provided to a data caching layer, which may filter the data received from the streaming data source at step 240. Also, the data caching layer can "snapshot" the data, i.e., provide a data state at a particular moment in time.

[0054] In one embodiment, business logic may reduce the number of data fields presented to the client.
[0055] At step 250, the filtered data may be fused. For example, data from more than one filtered source can be aggregated. For example, immediately, a stock may change in price from 70.00 to 70.05, back to 69.90, and then to 70.01. With the fused source, the client will only receive 70.01. The reason is that the value was in the proper state of the price at the end of that time. However, this value will not be the final value, especially since it is not always the appropriate data point for datasets for multiple fields such as Bid and Ask.

  [0056] At step 260, a data snapshot of the data may be generated. In one embodiment, the snapshot is for a security collection and may be accurate over that collection at that time. For example, queries may be performed concurrently over aggregated data (eg, securities of interest) rather than sequentially.

  [0057] At step 270, the snapshot can be output to the client via a web application, a local application, an API, a spreadsheet, or the like.

  [0058] In one embodiment, the delivery of the snapshot may be delayed by a predetermined amount of time to "age" the data. For example, the timing for data transmission can determine whether data can be transmitted free of charge or whether there is a fee for data. Not all clients require real-time data; for example, an investment manager may not need real-time data when meeting a prospective client.

  [0059] Thus, in one embodiment, the system can determine how long to delay the output of the snapshot, which can be based on the rules associated with the data and / or data sources, and reduce the snapshot by at least This amount of time can be delayed. In one embodiment, an audit trail of the aging of the data in the snapshot may be maintained.

  [0060] Embodiments disclosed herein may separate various line of business-implemented process schemes from content related to solving a problem. To treat the content, such as changes resulting from various lots, transactions, remittances, repurchases, refunds, etc., in the client's portfolio as general-purpose internal publication data, anonymize, aggregate, filter and present streaming data To one or more systems / methods. An example of such a system / method is disclosed in U.S. Patent Application No. 15 / 378,501, the disclosure of which is incorporated herein by reference in its entirety.

  [0061] In embodiments, market data from various establishments may be fused within one or more systems / methods for aggregating, filtering, and presenting streaming data, and portfolio information. And can be merged. As the data passes through several merging stages, each lot is priced against real-time market data and then aggregated into a real-time portfolio view.

  [0062] In embodiments, a customer may use a custom rules engine to apply for "alerts" related to a business. For example, the system may determine when a particular stock reaches a price threshold, when the concentration risk of a particular property breaks through a predefined level, when a lot or portfolio valuation goes up / down a certain percentage, etc. A notification can be sent to the client.

  [0063] Referring to FIG. 3, a strategic flow is provided according to one embodiment. Strategic flows include customer, financial institution interface, gateway service, one or more graphical user interfaces, perimeter gateway, complex event processor (CEP) engine, internal data platform (eg, publishing and consumer interaction) An internal data platform that can provide secure and secure messaging between. It can provide access using the OpenMAMA API.) One or more market data feeds (eg, NASDAQ and NYSE market data NASDAQBasic to hold.Commercial feed handlers: OPRA, Pink Sheets, TradeWeb, etc. can be used.), Anonyma The data injector, securities master, portfolio management system, daytime Activity Monitor (e.g., activity during the day, order management systems, and cash flow system) may include an alarm engine, and notification platform.

  [0064] In one embodiment, the CEP engine may process the data for applications that require market data and one or more of the following. The following are: (1) being in a configuration that cannot support high-rate streaming data; (2) only requiring prices several times a day, but having very little hysteresis. Need; (3) need to submit multiple symbols at a single time (as opposed to streaming subscriptions each employing a single symbol): (4) several sources Aggregation of market and analytics data (eg, Reuters RMDS, Direct Feed, Internal Data, LOB market analytics); or (5) Dynamic consideration of one or more field values You need the ability to filter data for queries, or The market data that is delayed by a predetermined time to reduce the cost of use is.

  [0065] In one embodiment, the anonymizer component can remove the client's identity from the portfolio content before injecting it into the CEP engine. The reverse process allows the process to look up the ID associated with a particular client's portfolio of interest.

  [0066] A data injector may provide a single interface to one or more technology assets. Data injectors map reference data (eg, symbology) between systems, internal data platforms (eg, send portfolio information) and CEP engines (eg, ensure that the product of interest is on the watchlist). Can communicate with both.

  [0067] In one embodiment, the portfolio management system may be a source of portfolio content data about client property. The portfolio management system can issue daily portfolio refreshes of interest, publish portfolios on demand, and maintain "official" day-of-day prices for all lots / portfolios. .

  [0068] In one embodiment, a daytime activity monitor may monitor activities, such as activities from an order management system, a cash flow engine, and the like. The intraday activity monitor can publish updates in the CEP engine as portfolio changes since the beginning of the day to reflect changes in ratings in real time.

  [0069] The alert engine can translate client instructions from the financial institution website into subscriptions to the CEP engine and other back-end systems. Persisting alerts for multiple days, hearing a signal from the CEP engine that a condition has been met, performing the desired action, disabling the alert upon which an action has been taken, and the like.

  [0070] FIG. 4 illustrates an exemplary process flow according to one embodiment. In one embodiment, a data source layer can receive market data (eg, a market data stream) and provide data to a data loader layer, where the data uses one or more data loaders. Can be loaded into the data caching layer. The CEP engine can access data from the data caching layer and can provide configuration management, data filtering, monitoring services, control plane services, entitlement services, and the like. In one embodiment, the CEP engine can provide services to customers via a customer access layer.

[0071] Example
[0072] A non-limiting example is provided below.
[0073] Data Set 1: Equity instruments from direct feed:
<SnapSymbol> JPM. N </ snapSymbol>
<SnapStatus> ok </ snapStatus>
<WBidPrice> 87.7900000 <// wBidPrice>
[0077] <wBidSize> 18 <// wBidSize>
<WAskPrice> 87.80000000 <// wAskPrice>
<WAskSize> 4 <// wAskSize>
[0080] <wInstrumentType> Stock </ wInstrumentType>
[0081] <wOpenPrice> 90.360000 </ wOpenPrice>
<WAdjPrevClose> 90.070000 <// wAdjPrevClose>
[0083] <wPrevClosePrice> 90.070000 <// wPrevClosePrice>
[0084] <wBidOpen> 90.3400000 </ wBidOpen>
[0085] <wAskOpen> 90.400000 </ wAskOpen>
[0086] The product price is the average of wBitPrice and wAskPrice.

[0087] Data Set 2: Commodity Futures Trading from Direct Feed:
<SnapSymbol> CLJ7. NYM </ snapSymbol>
<SnapStatus> ok </ snapStatus>
<WIssueSymbol> CLJ7. NYM </ wissueSymbol>
[0091] <wBidHigh> 48.620000 </ wBidHigh>
[0092] <wAskLow> 47.400000 </ wAskLow>
[0093] <wAskPrice> 47.4100000 </ wAskPrice>
[0094] <wAskSize> 5 <// wAskSize>
[0095] <wBidPrice> 47.390000 </ wBidPrice>
[0096] <wBidSize> 52 </ wBidSize>
[0097] <wBidLow> 47.3400000 </ wBidLow>
[0098] <wAskHigh> 48.750000 </ wAskHigh>
[0099] <wOpenPrice> 47.930000 </ wOpenPrice>
[00100] <wOpenTime>2017-03-21; 17: 45: 27.2229603 </ wOpenTime>
[00101] <wCfiCode> FCMXSX <// wCfiCode>
[00102] <wCurency> USD </ wCurrency>
[00103] <wEntryStatus> 0 </ wEntryStatus>
[00104] Same rules for price apply
[00105] Dataset 3: Government Bonds from Vendor Feed:
<SnapSymbol> ISIN_USN82008AK46_MODEL. FUSE </ snapSymbol>
[00107] <snapStatus> ok </ snapStatus>
[00108] <CLIENT_OFFER> 0.000000 </ CLIENT_OFFER>
[00109] <CLIENT_BID> 0.000000 </ CLIENT_BID>
[00110] <POSITION> 0.000000 </ POSITION>
[00111] <COUPON_RATE> 2.000000 </ COUPON_RATE>
<STRING2> HG-Industrials / Defense / Chemicals </ STRING2>
[00113] <MKT_PRICE_2> 10000000.0000 </ MKT_PRICE_2>
[00114] <MKT_PRICE_1> 10000000.0000 </ MKT. PRICE_1>
[00115] <MATURDATE> 15 Sep 2023 </ MATURDATE>
[00116] <ISIN_BENCHMARK> US912828W556 <// ISIN_BENCHMARK>
[00117] <CURVE_TYPE> EMEA <CURVE_TYPE>
<UPDATE_TM> 12: 31: 15,000 </ UPDATE_TM>
[00119] <lTEM_ID />
[00120] Price is in field MKT_PRICE_1
[00121] The data sets need not be in the same CEP instance. For example, datasets 1 and 3 can be on the same CEP instance where the portfolio view is created. Dataset 2 can be on another instance depending on the demand of the ingestion.

[00122] An example profile design is provided. The portfolio can be stored in its own table called Portfolio.
[00123]:
[00124] ｛
[00125] "portfolio": "12345"
[00126] "version": 3.2.6.
[00127] “holdings”: [
[00128] {"source": "Data Set 1", "security": "JPM.N", "weight": 150},
[00129] {"source": "Data Set 2", "security": "CLJ7.NYM", "weight": 200},
[00130] {"source": "Data Set 3", "security": "ISIN_USN82008AK46_MODEL.FUSE", "weight": 2}
[00131]]
[00132]｝
[00133] For example, portfolio pricing may use the following pseudo code:
[00134] For a particular portfolio ID,
[00135] About each asset identifier
[00136] Total price = Total price + (Asset weight ^* Asset_Price [Asset identifier])
[00137] Returns the total price
[00138] In other words, a single value can be returned that represents the real-time price of the portfolio that will change as the data changes.

[00139] In one embodiment, there may be four layers of tables defined for both instances.
[00140] The first tier may receive data from market data publishers. For example, there may be one table per data feed / source for both portfolio pricing and commodity futures trading. For portfolio pricing, they can be named "Equity" and "Bond", and for commodity futures trading, they can be named "Comm". These tables are neither transaction logged nor transaction replicated, and the "shape" of the data in these tables is whatever the data source defines.

  [00141] At the next tier, there is a replicated table that can be called "AllPrices" and can act as a normalized union of price data from all sources. Data can be normalized and published to AllPrices from the Comm, Equity, and Bond tables. In embodiments, this information may be fused to reduce the maximum data rate.

  [00142] The first step in the action chain is to analyze the underlying data and extract the values of interest into variable quantities. The extraction of the value can be specified as a projective representation. For example, when processing a message from Equity, the line <Value> price = (/ price / wBidPrice + / price / wAskPrice) / 2 </ Value> calculates the average of / wBidPrice and / wAskPrice and changes the result. Place in quantity {price}.

  [00143] The next step in the action is to issue a new message containing the {symbol} and the normalized {price}, along with a "source" field indicating the source of the pricing data. This message can be issued to the AllPrices table and can be formatted as JSON.

  [00144] At this point, the incoming market data has been normalized and converted into a single AllPrices table. Conflation and replication must be used to handle portfolio pricing instances while giving portfolio pricing a complete view of all of the security prices needed to price a portfolio. The overall amount of messages that must be minimized.

  [00145] The portfolio may then be modeled as a table "Portfolio" with one column per portfolio for one security. Each message in a portfolio may have a portfolio ID, a security, and the weight of that security in the portfolio. This table is essentially input data for a portfolio of interest, and the system dynamically re-creates portfolio prices as portfolio content is adjusted, added, and / or removed. Can be calculated.

  [00146] This calculation is performed in the next layer, aggregation. This layer can be modeled as two views. The first view is a combination of Portfolio and AllPrices, called “PricedPortfolio”. There may be one message here for every message in Portfolio, but Join allows you to include the current price for each security.

[00147] The top PricedPortfolio can be a second view "PricedPortfolioAgg" that calculates the portfolio price. This is essentially the pseudo-code of a view over (and beyond) a view containing one message for one portfolio, with a portfolio ID, a count of the securities in the portfolio, and a SUM of / price ^* / weight of the securities in the portfolio. Conversion.

  [00148] Thus, in embodiments, the system receives portfolio data (e.g., by push), and then receives queries / subscriptions to PricedPortfolio and PricedPortfolioAgg when underlying market data changes. You can see the dynamically updated portfolio price.

  [00149] In embodiments, the official day-of-day assessment of each portfolio can be submitted in the PortfolioRef table as part of the daily load. This allows the PricedPortfolioAgg view to include the unrealized start-of-day gain / loss calculations by comparing the current rating with the reference data submitted in the PortfolioRef table. In one embodiment, the percentage change from the portfolio rating at the beginning of the day can be calculated.

  [00150] In embodiments, the alerting engine may set up a subscription in a CEP engine that maps human identifiable concepts to underlying data structures. Arithmetic expressions and formulas in the SQL language can be used to define when the alert engine should receive notification of an event. When data relating to a particular subscription is received, the alerting engine may send the data to the desired action (eg, sending a message such as an email or SNS, popping up a window on the advisor's user interface, etc.). , And the action can be performed. The alert engine can be further configured to remain as an active alert or to disable itself by deleting a subscription.

[00151] Non-limiting examples of alerts include portfolio gain / loss above / below an amount or percentage of amount, value of a particular property above a particular threshold, and the like.
[00152] An advisor representing multiple clients may maintain alerts covering multiple portfolios of interest for a holistic view of the client's property.

[00153] At the organizational level, all property possessions can be holistically analyzed in the CEP engine to facilitate hedging, cross-account lending, risk management, and the like.
[00154] In one embodiment, cash may be represented in a portfolio as a number of units of an underlying currency, such as the United States dollar. Market data for currencies may be static (such as for US dollars for dollar-denominated accounts) or may represent the current exchange rate.

  [00155] In another embodiment, a similar mechanism can be used for hypothetical modeling of portfolio changes. A separate CEP engine or side table can be used to store the final representation of the hypothetical content of the portfolio, while the same aggregation mechanism can be used to price the portfolio.

  [00156] In one embodiment, a separate table in the CEP engine can store stock-sector relationships that can be used to build dynamic risk models that help customers manage risk. . Multiple risk models can be defined to facilitate different risk appetite.

  [00157] In one embodiment, separate subscriptions can be set up on a table containing the aggregated views, which can then be extracted and stored in a database. This history record can be used as an audit trail or to train a machine learning system that generates automated investment advice for customers and advisors.

  [00158] In one embodiment, a CEP engine can be used for real-time margin management. This is because the CEP engine knows the current assessment status of portfolio lots as well as the availability of financial instruments.

[00159] Although several embodiments have been disclosed, it should be recognized that these embodiments are not mutually exclusive.
[00160] In the following, general aspects of implementations of the systems and methods of the present invention will be described.

  [00161] The system of the present invention or certain portions of the system of the present invention may be in the form of a "processing machine", such as, for example, a general-purpose computer. As used herein, the term "processing machine" is understood to include at least one processor that uses at least one memory. At least one memory stores a set of instructions. The instructions may be stored permanently or temporarily in one or more memories of the processing machine. A processor executes instructions stored in one or more memories to process the data. The set of instructions may include various instructions for performing a particular task or tasks, such as those described above. Such a set of instructions for performing a particular task can be characterized as a program, a software program, or simply software.

[00162] In one embodiment, the processing machine may be a specialized processor.
[00163] As noted above, the processing machine executes instructions stored in one or more memories to process the data. This processing of the data may be, for example, responsive to commands by one or more users of the processing machine, responsive to previous processing, responsive to requests by another processing machine and / or any other input. it can.

  [00164] As noted above, the processing machine used to implement the invention may be a general-purpose computer. However, the processing machines described above can utilize any of a variety of other technologies as well. Various other technologies include dedicated computers, eg, microcomputers, minicomputers, or computer systems including mainframes, programmable microprocessors, microcontrollers, peripheral integrated circuit elements, CSICs (Customer Specific Integrated Circuits, customer-specific integrated circuits). ) Or an Application Specific Integrated Circuit (ASIC) or other integrated circuit, a logic circuit, a digital signal processor, a programmable logic device such as an FPGA, PLD, PLA, or PAL, or a step of the process of the present invention. Any other device or device configuration that is capable of implementing No.

  [00165] The processing machine used to implement the present invention may utilize a suitable operating system. Therefore, embodiments of the present invention are based on an iOS operating system, an OS X operating system, an Android operating system, a Microsoft Windows (trademark) operating system, a Unix operating system, a Linux (registered trademark) operating system, a Xenix operating system, and an IBM AIX (trademark). ) Operating systems, Hewlett-Packard UX ™ operating system, Novell Network ™ operating system, Sun Microsystems Solaris ™ operating system, OS / 2 ™ operating system, BeOS operating system, Macin osh operating system may include a processing machine to perform Apache operating system, OpenStep (TM) operating system or another operating system or platform.

  [00166] It will be appreciated that it is not necessary for the processor and / or memory of the processing machine to be physically located at the same geographic location to implement the method of the invention described above. That is, each of the processor and the memory used by the processing machine can be located at geographically distinct locations and connected to communicate in any suitable manner. Further, it is recognized that each of the processor and / or memory can be comprised of a different physical piece of equipment. Thus, it is not necessary that the processor be one single piece of equipment at one location and that the memory be another single piece of equipment at another location. That is, it is contemplated that the processor can be two pieces of equipment at two different physical locations. The two separate pieces of equipment can be connected in any suitable way. Further, memory may include more than one portion of memory at more than one physical location.

  [00167] To further illustrate, the processes are implemented by various components and various memories, as described above. However, it will be appreciated that the processing performed by the two separate components as described above can be performed by a single component according to further embodiments of the present invention. Further, the processing performed by one separate component as described above can be performed by two separate components. Similarly, memory storage implemented by two separate memory portions as described above can be implemented by a single memory portion, according to a further embodiment of the present invention. Further, the memory storage implemented by one separate memory portion as described above can be implemented by two memory portions.

  [00168] Further, various techniques may be provided, for example, to provide communication between various processors and / or memories, and for the processors and / or memories of the present invention to communicate with any other entities. It can be used to enable, i.e. to get further instructions or to access and use a remote memory store. Such technologies used to provide such communications include, for example, wireless communications via a network, the Internet, an intranet, an extranet, a LAN, Ethernet, a cell tower or satellite, or any client that provides communications. May include server systems. Such communication techniques may use any suitable protocol, such as, for example, TCP / IP, UDP, or OSI.

  [00169] As mentioned above, a set of instructions can be used in the processing of the present invention. The set of instructions may be in the form of a program or software. The software may be, for example, in the form of system software or application software. Software may also be in the form of, for example, a collection of separate programs, a program module within a larger program, or a portion of a program module. The software used may also include modular programming in the form of object-oriented programming. The software tells the processing machine what to do with the data to be processed.

  [00170] Further, it will be appreciated that the instructions or set of instructions used in the implementation and operation of the present invention are in a form suitable for a processing machine to read the instructions. For example, the instructions that form a program may be in the form of a suitable programming language that is translated into machine language or object code to enable one or more processors to read the instructions. That is, a written line of programming code or source code in a particular programming language is converted to machine language using a compiler, assembler, or interpreter. A machine language is, for example, a binary encoding machine instruction that is specific to a particular type of processing machine, ie, a particular type of computer. Computers understand machine language.

  [00171] Any suitable programming language may be used in accordance with various embodiments of the present invention. Illustratively, the programming languages used are, for example, assembly language, Ada, APL, Basic, C, C ++, COBOL, dBase, Forth, Fortran, Java, Modula-2, Pascal, Prolog, REXX, Visual Basic and / or JavaScript can be included. Further, it is not necessary that a single type of instruction or a single programming language be utilized in connection with the operation of the systems and methods of the present invention. Rather, any number of different programming languages can be utilized as needed and / or desired.

  [00172] Similarly, the instructions and / or data used in the practice of the invention can utilize any compression or encryption techniques or algorithms as desired. An encryption module may be used to encrypt data. Further, files or other data can be decrypted, for example, using a suitable decryption module.

  [00173] As noted above, the invention can be illustratively embodied in the form of a processing machine that includes a computer or computer system that includes, for example, at least one memory. For example, a set of instructions that enable a computer operating system to perform the operations described above, ie, software, may be included on any of a variety of one or more media, as desired. Is recognized. Further, the data processed by the set of instructions may also be included on any of a variety of one or more media. That is, the particular medium or memory within the processing machine utilized to hold the set of instructions and / or data used in the present invention may be, for example, any of various physical forms or transmission media. You can take things. Illustratively, the medium is paper, transparent paper, compact disk, DVD, integrated circuit, hard disk, floppy disk, optical disk, magnetic tape, RAM, ROM, PROM, EPROM, wire, cable, fiber, communication channel, satellite transmission medium. , A memory card, a SIM card, or other remote transmission medium, as well as any other data medium or source readable by the processor of the present invention.

  [00174] Further, one or more memories used in a processing machine implementing the invention may have various forms of enabling the memory to hold instructions, data, or other information as desired. It can be in any of these forms. Therefore, the memory may be in the form of a database that holds data. The database may use any desired file arrangement, such as, for example, a flat file arrangement or a relational database arrangement.

  [00175] In the systems and methods of the present invention, various "user interfaces" allow a user to interface with one or more processing machines used to implement the present invention. Can be used for As used herein, a user interface includes any hardware, software, or combination of hardware and software used by a processing machine that allows a user to interact with the processing machine. The user interface may be, for example, in the form of a dialog screen. The user interface may be a mouse, touch screen, keyboard, keypad, voice reader, voice recognizer, dialog screen, menu box, list, check box, toggle switch, push button, or any other device, optionally Any of any other devices that allow a user to receive information regarding the operation of the processing machine when the other device processes the set of instructions and / or provides information to the processing machine. Can be included as well. Thus, a user interface is any device that provides communication between a user and a processing machine. The information provided by the user to the processing machine through the user interface may be, for example, in the form of a command, a selection of data, or some other input.

  [00176] As discussed above, the user interface is utilized by a processing machine that implements a set of instructions, whereby the processing machine processes data for a user. User interfaces are typically used by processing machines to interact with, communicate information to, or receive information from a user. However, it should be appreciated that, according to some embodiments of the systems and methods of the present invention, it is not necessary for a human user to actually interact with the user interface used by the processing machine of the present invention. . Rather, it is similarly contemplated that the user interface of the present invention may interact with other processing machines, ie, communicate and receive information, rather than with a human user. Thus, other processing machines may be characterized as users. Further, it is contemplated that the user interface utilized in the systems and methods of the present invention may partially interact with another one or more processing machines while partially interacting with a human user. Is done.

  [00177] It will be readily appreciated by those skilled in the art that the present invention embraces a wide range of utilities and applications. Many embodiments and adaptations of the invention other than those described herein, as well as many variations, modifications, and equivalents, may be made without departing from the spirit or scope of the invention. It will be apparent from the above description, or will be reasonably suggested thereby.

  [00178] Thus, while the present invention has been described in detail herein with reference to exemplary embodiments thereof, the present disclosure is merely illustrative and exemplary of the present invention and is provided as a practical disclosure of the invention. It is understood that this is done to provide Accordingly, the above disclosure is not intended to be construed as limiting, or otherwise excluding, the invention, any other such embodiments, adaptations, variations, modifications, or equivalents.

Claims (20)

A method for presenting streaming data, the method comprising:
Receiving, from a client, a query including a plurality of parameters at a web services layer for a server including at least one computer processor;
A data caching layer for the server receiving streaming data from at least one predefined streaming data source;
The data caching layer fusing the streaming data for each of the plurality of parameters;
Said data caching layer aggregating said fused data;
The data caching layer concurrently executing the query on the fused data to generate a snapshot of the fused data;
Outputting the snapshot to the client.   The method of claim 1, wherein the parameters include specific descriptors for securities and / or investments.   The method of claim 1, wherein the query further comprises identification information of a streaming data source.   The method of claim 1, wherein the streaming data includes market data.   The method of claim 1, wherein the web services layer outputs the snapshot that is delayed by a predetermined amount of time, wherein the time period is based on one or more rules associated with the streaming data.   The method of claim 1, further comprising the step of an entitlement service layer for the server verifying that the client is authorized to access information in response to the query.   The method of claim 1, further comprising authenticating the client based on at least one client credential received from the client.   3. The method of claim 2, wherein the snapshot is accurate for at least one of the security and the investment for a period of time.   3. The method of claim 2, wherein the snapshot includes an appropriate state for at least one of the security and the investment for a period of time. A system for presenting streaming data,
Multiple streaming data sources,
A data loader for each streaming data source, the data loader receiving streaming data from the streaming data source;
A data caching layer for receiving the streaming data from the data loader;
A web services layer including at least one computer processor in communication with the data caching layer;
The web service layer receives a query including a plurality of parameters from a client,
The data caching layer fuses the streaming data for each of the plurality of parameters;
The data caching layer aggregates the fused data;
The data caching layer generates a snapshot of the fused data by simultaneously executing the query on the fused data;
The system wherein the snapshot is output to the client.   The system of claim 10, wherein the parameters include specific descriptors for securities and / or investments.   The system of claim 10, wherein the query further comprises an identification of a streaming data source.   The system of claim 10, wherein the streaming data comprises market data.   The system of claim 10, wherein the web services layer outputs the snapshot delayed by a predetermined amount of time.   The system of claim 14, wherein the time period is based on one or more rules associated with the streaming data.   The system of claim 10, wherein the query is received from at least one of a cloud application and a local application.   The system of claim 10, further comprising an entitlement service layer for the server that verifies that the client is authorized to access information in response to the query.   The system of claim 17, wherein the entitlement service layer further authenticates the client based on at least one client credential received from the client.   12. The system of claim 11, wherein the snapshot is accurate for at least one of the security and the investment for a period of time.   The system of claim 11, wherein the snapshot includes a state appropriate for at least one of the security and the investment for a period of time.

Images