Information processing method and device, electronic equipment and storage medium

Abstract

The invention provides an information processing method and device, electronic equipment and a storage medium, and relates to the field of data processing, in particular to the technical field of big data and the like, and the information processing method comprises the steps that the flow information of articles in a first time period and the full-amount article snapshot information in a second time period are obtained, and the second time period is adjacent to the first time period; the time period is earlier than the first time period; performing time sequence bucket separation on the pipeline information to obtain a plurality of time buckets; determining the latest state record of the article in the sub-barrel at the time to which the article belongs; and according to the latest state record of the article in the barrel at the time to which the article belongs and the full-amount article snapshot information of the second time period, determining the state record of the article appearing in the first time period and the corresponding life cycle information.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, specifically to the field of big data and other related technologies, and particularly to an information processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] In related technologies, when dealing with massive amounts of data, data aggregation can be used to process the data. However, when facing high-frequency changes in business status and the need for refined operations, there are problems such as low computing efficiency, poor data timeliness, and huge resource consumption. Summary of the Invention

[0003] This disclosure provides an information processing method, apparatus, electronic device, storage medium, and computer program product.

[0004] According to a first aspect of this disclosure, an information processing method is proposed, comprising: acquiring item flow information within a first time period and full item snapshot information within a second time period, wherein the second time period is adjacent to and earlier than the first time period; performing time-series binning on the flow information to obtain multiple time bins; determining the latest status record of an item within its respective time bin; and determining the status record of the item within the first time period and its corresponding lifecycle information based on the latest status record of the item within its respective time bin and the full item snapshot information within the second time period.

[0005] According to a second aspect of this disclosure, an information processing apparatus is proposed, comprising: an acquisition module for acquiring flow information of items within a first time period and full item snapshot information within a second time period, wherein the second time period is adjacent to and earlier than the first time period; a time-series binning module for performing time-series binning on the flow information to obtain multiple time bins; a first determination module for determining the latest status record of an item within its respective time bin; and a second determination module for determining, based on the latest status record of the item within its respective time bin and the full item snapshot information of the second time period, the status record of the item appearing within the first time period and the corresponding lifecycle information.

[0006] According to a third aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the information processing method proposed in the first aspect above.

[0007] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to perform the information processing method proposed in the first aspect above.

[0008] According to a fifth aspect of this disclosure, a computer program product is proposed, comprising a computer program that, when executed by a processor, implements the information processing method proposed in the first aspect above.

[0009] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0010] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 This is a schematic flowchart of an information processing method according to an embodiment of the present disclosure; Figure 2 This is a schematic flowchart of an information processing method according to an embodiment of the present disclosure; Figure 3 This is a schematic diagram illustrating the lifecycle information corresponding to the state record of an item within a first time period, according to an embodiment of this disclosure. Figure 4 This is a schematic flowchart of an information processing method according to an embodiment of the present disclosure; Figure 5 This is a schematic diagram of the structure of an information processing apparatus according to an embodiment of the present disclosure; Figure 6 This is a schematic block diagram of an electronic device according to an embodiment of the present disclosure. Detailed Implementation

[0011] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0012] Data processing is the acquisition, storage, retrieval, processing, transformation, and transmission of data. The fundamental purpose of data processing is to extract and derive valuable and meaningful data from large, potentially disorganized, and difficult-to-understand datasets.

[0013] Big data, also known as massive data, refers to information that is so large in scale that it cannot be captured, managed, processed, and organized into information that helps businesses make more proactive business decisions within a reasonable timeframe using mainstream software tools.

[0014] Among the related technologies, (1) full calculation based on daily snapshot: that is, processing the full amount of item snapshot data of the previous day once at midnight every day, calculating the daily aggregate indicators (such as the number of items listed on the day). The processing flow is: obtaining the Hive daily full table of items, extracting, transforming and loading the data in the Hive daily full table, and importing it into the Online Analytical Processing (OLAP) engine for front-end display; however, this solution is coarse-grained and cannot meet business needs. It cannot capture the drastic fluctuations in product status at the half-hour level during the promotion period, and the basis for operational decision-making is seriously lagging behind, resulting in low commercial value. (2) Incremental calculation with fixed time window: In order to obtain finer time granularity, the calculation cycle is shortened to half an hour or one hour. The system schedules a task once every half hour. The processing flow is: obtain the Hive hourly full table of items, perform ETL calculation on the data in the Hive daily full table, and import it into the OLAP engine for front-end display. However, this solution consumes huge computing resources. The full-link scheduling and calculation once every half hour or one hour puts periodic pressure on the cluster resources, resulting in a bulky system and high cost. (3) Data inflation based on time dimension table: In order to support queries for any time period, the basic data of items is associated with a time dimension table (containing 48 half-hours in a day) by Cartesian product, generating 48 records for each item. Each record represents a half-hour window. Then, complex logic is used to determine which window the item is valid in. The processing flow is: based on the full item table, incremental binary log (Binlog) data, and JOIN the time dimension table, an expanded intermediate table is generated, and the expanded intermediate table is imported into the OLAP engine. However, this solution is seriously wasteful in terms of storage and computation. For an item whose state does not change throughout the day, 47 redundant records will be generated meaninglessly. When processing billions of item data per day, the resulting data inflation is disastrous, greatly increasing storage costs and computation time.

[0015] Figure 1 This is a schematic flowchart of an information processing method according to an embodiment of this disclosure. Figure 1 As shown, the method includes: S101, obtain the item flow information within the first time period and the full item snapshot information within the second time period, wherein the second time period is adjacent to the first time period and is earlier than the first time period.

[0016] It should be noted that the execution entity of the information processing method in this embodiment can be a hardware device with data information processing capabilities and / or the necessary software to drive the hardware device to work. Optionally, the execution entity may include a workstation, server, computer, user terminal, and other intelligent devices. Among them, the user terminal includes, but is not limited to, mobile phones, computers, intelligent voice interaction devices, smart home appliances, vehicle terminals, etc.

[0017] The first time period can be day T-1, and the second time period can be day T-2.

[0018] The flow information can be understood as all the change data information of the item within the first time period, reflecting the dynamic changes of the item within the first time period in chronological order.

[0019] Among them, the full item snapshot information can be understood as all the data information of the item in the second time period.

[0020] It should be noted that this disclosure does not limit the specific methods for obtaining the transaction information of items in the first time period and the full snapshot information of items in the second time period, and the appropriate methods can be selected according to the actual situation.

[0021] Optionally, offline Binlog transaction data of the item's core table can be obtained, and information can be extracted from the offline Binlog transaction data to obtain the transaction information of the item within the first time period.

[0022] For example, by extracting information from offline Binlog transaction data, transaction information such as item status changes, price adjustments, and inventory updates can be obtained within the first time period.

[0023] Optionally, full item snapshot information for the second time period can be obtained from the full item snapshot table.

[0024] It should be noted that after obtaining the item flow information for the first time period, the time field in the item flow information for the first time period can be standardized to lay the foundation for subsequent time-series binning of the flow information.

[0025] S102, perform time-series bucketing on the flow information to obtain multiple time buckets.

[0026] In this embodiment of the disclosure, the status record of the item in the flow information and the update time of the status record are determined. Based on the update time of the status record, the status record of the item is time-series binned to obtain multiple time bins.

[0027] Optionally, preset time-series binning rules can be obtained, and the status records of items can be binned according to the update time of the status records based on the time-series binning rules to obtain multiple time bins.

[0028] For example, the time-series binning rule is the number of hours + the number of minutes / 60 (rounded down to 0.5). The day is divided into 48 time bins in half-hour increments. For example, the first time bin 0.0 represents the time 00:00-0:29.

[0029] S103, Determine the latest status record of the item within its assigned time bucket.

[0030] In this embodiment of the disclosure, the latest status record of an item in its respective time bucket can be determined based on the update time of the status record of the item in its respective time bucket.

[0031] Optionally, multiple status records can be sorted according to their update time to determine the latest status record of an item within its data bucket.

[0032] For example, for item X, if the time bucket to which item X belongs is 10.5, the status of item X at 10:35 is recorded as "normally available for sale", the status of item X at 10:45 is recorded as "out of stock and removed from shelves", and the status of item X at 10:55 is recorded as "normally available for sale", then the latest status record within the time bucket 10.5 to which item X belongs is "normally available for sale".

[0033] S104. Based on the latest status record of the item in its time bucket and the full item snapshot information of the second time period, determine the status record and corresponding lifecycle information of the item in the first time period.

[0034] Among them, the lifecycle information corresponding to the status record can be understood as the validity period of the status record.

[0035] Optionally, after obtaining the latest status record of an item within its time bucket, the latest status record of the item within its time bucket can be merged with the full item snapshot information of the second time period to determine the status record of the item in the first time period. The merged result is sorted according to the item identifier (Identification, or Id) and the LEAD window function is used to determine the lifecycle information [start_time, end_time] corresponding to the status record of the item in the first time period.

[0036] The information processing method proposed in this disclosure obtains the item flow information within a first time period and a full item snapshot information within a second time period, wherein the second time period is adjacent to and earlier than the first time period. The flow information is then time-series-divided into multiple time buckets. The latest status record of each item within its respective time bucket is determined. Based on the latest status record of each item within its respective time bucket and the full item snapshot information of the second time period, the status record of the item within the first time period and its corresponding lifecycle information are determined. Thus, this disclosure, by time-series-dividing the flow information into multiple time buckets and determining the status record of the item within the first time period and its corresponding lifecycle information, enables the backtracking and querying of item status records at any time granularity without requiring data expansion or high-frequency computation. This solves the problems of low computational efficiency, poor data timeliness, and huge resource consumption when facing high-frequency item status changes and refined operational needs. While reducing resource consumption, it further improves the efficiency and timeliness of information processing.

[0037] Figure 2 This is a flowchart illustrating an information processing method according to a second embodiment of the present disclosure.

[0038] like Figure 2 As shown, in Figure 2 Based on the illustrated embodiments, the information processing method of this disclosure may specifically include the following steps: S201, Obtain the item flow information within the first time period and the full item snapshot information for the second time period.

[0039] Optionally, step S102 in the above embodiment, "performing time-series bucketing of the flow information to obtain multiple time buckets", may specifically include the following steps S202-S203.

[0040] S202, determine the status record of the item in the flow information and the update time of the status record.

[0041] S203, based on the update time of the status record, perform time-series bucketing on the status record to obtain multiple time buckets.

[0042] In this embodiment of the disclosure, the update time of the determined status record is rounded down to obtain the bin identifier corresponding to the status record of the item. The status records of items corresponding to the same bin identifier are divided into the time bins identified by the same bin identifier.

[0043] Optionally, the update time of the status record can be divided into hours and minutes, and the minutes divided by 60 can be rounded down to 0.5. Based on the hours and the rounded result, the bucket identifier corresponding to the status record of the item can be obtained.

[0044] For example, if the update time of the status record for item A is 10:20 and the hour is 10, then rounding down from 60 to 0.5 gives 0.0, and the corresponding bucket identifier for the status record of item A is 10.0; if the update time of the status record for item B is 11:40 and the hour is 11, then rounding down from 60 to 0.5 gives 0.5, and the corresponding bucket identifier for the status record of item B is 11.5.

[0045] Optionally, step S103 "determine the latest status record of the item in its time bin" in the above embodiments may specifically include the following step S204.

[0046] S204. Determine the latest status record of the item in its time bucket based on the update time of the status record in the time bucket to which the item belongs.

[0047] In this embodiment of the disclosure, in response to the multiple status records of an item being included in the time bucket to which the item belongs, the multiple status records are sorted according to the update time of the status records to determine the latest status record of the item in its data bucket.

[0048] Optionally, a window-based sequence generation function can be called to reverse the order of multiple states according to their update time.

[0049] For example, in response to multiple status records of an item within its time bucket, it can be understood that the same product falling into the same time bucket has multiple status records. By calling the ROW_NUMBER() window function, the multiple statuses are sorted in reverse order according to the update time, and only the latest status record is retained. This ensures that each item has only one final status (the latest status record) within its time bucket, which can effectively remove duplicates.

[0050] Optionally, step S104 in the above embodiment, "determining the status record and corresponding lifecycle information of the item in the first time period based on the latest status record of the item in its time bin and the full item snapshot information of the second time period", may specifically include the following steps S205-S206.

[0051] S205, Based on the full item snapshot information of the second time period, determine the baseline state record of the item.

[0052] In this embodiment of the disclosure, each piece of data in the full item snapshot information of the second time period is used as the baseline state record of the item in the first time period.

[0053] S206. Based on the baseline state record of the item and the latest state record of the item within its respective time bucket, determine the state record of the item and the corresponding lifecycle information that appeared in the first time period.

[0054] In this embodiment of the disclosure, the status records of the item in the first time period are determined based on the latest status records of the item in its respective time bin. Based on the baseline status records of the item, the status records of the item in the first time period are supplemented and updated. Based on the start time and end time corresponding to the status records, the lifecycle information corresponding to the status records is determined.

[0055] For example, for item B, the latest status record of item B at 4:00 (within time bin 4.0) is "out of stock". The latest status record of item B at 12:10 (within time bin 12.0) is "available for sale". The latest status record of item B at 20:25 (within time bin 20.0) is "out of stock". By summarizing the latest status records of item B in each time bin, we can obtain the status records of item B in the first time period.

[0056] In this embodiment of the disclosure, a first state record is determined among the state records that appear in the first time period, wherein the first state record has the earliest start time. Based on the baseline state record and the first state record, the first state record that appears in the first time period is generated, wherein the first state record is sequential with the first state record in time and is located before the first state record. The state records that appear in the first time period of the item are completed based on the first state record.

[0057] For example, for item B, the first status record is that item B is out of stock at 4:00 (within the time bucket 4.0). Based on the baseline status record and the first status record, the first status record of the item from 0:00 to 4:00 is generated as the normal selling status. The status records of the item during the first time period are supplemented based on the first status record.

[0058] In this embodiment of the disclosure, after completing the status records of the item within the first time period based on the first status record, the bin identifier of the first time bin corresponding to the first time period is determined as the start time of the first status record, and the bin identifier of the time bin to which the first status record belongs is determined as the end time corresponding to the first status record. Based on the start time and end time corresponding to the status record, the life cycle information corresponding to the status record is determined.

[0059] For example, such as Figure 3As shown, for item B, the status record of item B changes multiple times within the first time period. The lifecycle information corresponding to the normal on-sale status record of item B is [0, 4), that is, 00:00-4:29. The lifecycle information corresponding to the off-stock status record of item B is [4, 12), that is, 4:29-12:29. The lifecycle information corresponding to the normal on-sale status record of item B is [12, 20), that is, 12:29-20:29. The lifecycle information corresponding to the off-stock status record of item B is [20, 23.5], that is, 20:29-23:29.

[0060] In this embodiment of the disclosure, the start time corresponding to the latest status record is determined according to the bin identifier of the time bin to which the latest status record belongs, the next time bin to which the item belongs within the first time period is determined, and the end time corresponding to the latest status record is determined according to the bin identifier of the next time bin to which the item belongs.

[0061] Optionally, the start time (start_time) corresponding to the latest status record is determined based on the bucket identifier of the time bucket to which the latest status record belongs. In response to the existence of the next time bucket to which the item belongs within the first time period, the end time (end_time) corresponding to the latest status record is determined based on the bucket identifier of the next time bucket to which the item belongs.

[0062] Optionally, in response to the fact that there is no next time bucket to which the item belongs within the first time period, the last bucket identifier corresponding to the first time period is determined to be 23.5, which means that the latest status record of the item in its time bucket continues until the end of the first time period.

[0063] In this embodiment of the disclosure, in response to the fact that no status record appears for the item in the first time period, the baseline status record is determined to be a global status record that can cover the first time period. The lifecycle information of the global status record is determined based on the bin identifier of the first time bin corresponding to the first time period and the bin identifier of the last time bin corresponding to the first time period.

[0064] For example, for item A, item A exists in the full item snapshot information of the second time period. Item A did not have any status record update in the first time period. The bucket identifier of the first time bucket corresponding to the first time period is 0, the bucket identifier of the last time bucket corresponding to the first time period is 23.5, and the lifecycle information of the global status record is [0, 23.5]. Therefore, item A remains valid in the first time period.

[0065] For example, continuing as Figure 3 As shown, for item A, the status record of item A remains unchanged during the first time period. The lifecycle information of the global status record of item A is [0, 23.5]. Item A is in a normal on-sale state during the first time period.

[0066] Optionally, after determining the status records and corresponding lifecycle information of the items within the first time period, the status records and corresponding lifecycle information of the items within the first time period can be imported into a high-performance OLAP database. Through the data service interface, the status records and corresponding lifecycle information of the items within the first time period can be provided to the front-end heatmap application. The front-end performs efficient queries in the OLAP database according to the time range selected by the user, and quickly aggregates the grid indicators within the corresponding time period.

[0067] The information processing method proposed in this disclosure acquires the flow information of items within a first time period and the full snapshot information of items within a second time period. It determines the status records and update times of the items in the flow information. Based on the update times of the status records, it performs time-series bucketing on the status records of the items, resulting in multiple time buckets. Based on the full snapshot information of items in the second time period, it determines the baseline status record of the items. Based on the baseline status record of the items and the latest status record of the items within their respective time buckets, it determines the status records and corresponding lifecycle information of the items that appeared in the first time period. Thus, this disclosure constructs an information processing method based on time-series bucketing and lifecycle information marking corresponding to status records. Through time-series bucketing, status record merging, and determination of status records and corresponding lifecycle information, it transforms the continuously changing data stream of items into a state sequence with a clear time validity range. Therefore, without data expansion and high-frequency computation, it can accurately and efficiently determine the status records and corresponding lifecycle information of items that appeared in the first time period, reducing the computational and storage resources required for information processing. It enables accurate status backtracking and querying at any time granularity, improving the user experience.

[0068] The following explanation uses an e-commerce application scenario to illustrate the specific process of the information processing method in this disclosure.

[0069] For example, such as Figure 4As shown, for the first time period of day T-1 and the second time period of day T-2, (1) obtain the data source: obtain the Binlog transaction data of the goods in day T-1 from the database, synchronize it to the Hive table through data collection, and obtain the full Hive product table (full product snapshot) for day T-2; (2) process it through Spark: input the Hivebinlog transaction data into the time series bucketing module, and perform time series bucketing on the transaction data through the processing logic (hours + minutes / 60 (rounded down to 0.5)) in the time series bucketing module, and put each transaction data into the time bucket of the corresponding bucket identifier; input the time bucket into the bucket merging module, and perform time series bucketing on the window-based sequence generation function (ROW_NUMBER()... PARTITION BY item_id, The `time_bucket` function operates on the row number to determine the latest status record of the product within its respective time bucket. The latest status record of the product within its time bucket and a full product snapshot for day T-2 are input into the expiration date marking module. Through the processing logic in the expiration date marking module, specifically using the LEAD function (LEAD(...) OVER (...)), the start and end times [start_time, end_time] corresponding to the status record of the product appearing on day T-1 are determined, and the resulting data fields and expiration date identifier are output. Further, after obtaining the status record of the item appearing on day T-1 and its corresponding lifecycle information, the status record of the item appearing on day T-1 and its corresponding lifecycle information are connected to the OLAP database. Data is queried based on the expiration date identifier, and the query results are provided to the operations monitoring platform.

[0070] In summary, the information processing method proposed in this disclosure (1) achieves "near real-time" and "refined" operational decision-making: it can observe the dynamic changes in the supply and demand of goods nationwide at a granular level of half an hour, enabling operators to discover best-selling products, identify out-of-stock areas, and perceive the competitive situation almost synchronously with the market, thereby accelerating operational actions from "day-level" response to "hour-level"; (2) it has a powerful "historical situation retrospective" capability: since the underlying data model fully records the life cycle information of each state record corresponding to the goods, it can support users to flexibly query the supply and demand situation of any day or time period in history, which is helpful for analyzing the effect of specific marketing activities and advancing the analysis of the supply and demand situation of any day or time period in history. (2) Provided unprecedented data support for in-depth review and trend analysis, greatly enhancing the value of analysis; (3) Ensured the smoothness and stability of information processing: Solved the efficiency bottleneck of data calculation from the bottom layer, avoided the delay risk caused by frequent task scheduling, made the data output of the front-end heat map more timely and the query faster, and provided users with a stable interactive experience; (4) Reduced the overall technical cost of information processing: By avoiding data expansion and high-frequency calculation, a large amount of computing and storage resources were saved, so that under the same resources, a larger amount of data can be processed and more complex business logic can be supported, laying a solid foundation for subsequent long-term iteration and functional expansion.

[0071] It should be noted that the information (including but not limited to Q&A information, user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the source, use and processing of the relevant data comply with relevant laws, regulations and standards, and do not violate public order and good morals.

[0072] According to embodiments of this disclosure, this disclosure also provides an information processing apparatus for implementing the above-described information processing method.

[0073] Figure 5 This is a block diagram of an information processing apparatus according to an embodiment of the present disclosure.

[0074] like Figure 5 As shown, the information processing device 500 includes: an acquisition module 501, a time-series binning module 502, a first determination module 503, and a second determination module 504.

[0075] The acquisition module 501 is used to acquire the flow information of items in a first time period and the full item snapshot information in a second time period, wherein the second time period is adjacent to the first time period and is earlier than the first time period. The time-series bucketing module 502 is used to perform time-series bucketing on the flow information to obtain multiple time buckets; The first determination module 503 is used to determine the latest status record of an item within its respective time bucket. The second determining module 504 is used to determine the status record and corresponding lifecycle information of the item in the first time period based on the latest status record of the item in its time bucket and the full item snapshot information of the second time period.

[0076] In one embodiment of this disclosure, the first determining module 503 is configured to: determine the latest status record of the item in its time bucket based on the update time of the status record of the item in its time bucket.

[0077] In one embodiment of this disclosure, the first determining module 503 is configured to: in response to a plurality of status records including the item in the time bucket to which the item belongs, sort the plurality of status records according to the update time of the status records to determine the latest status record of the item in the data bucket to which it belongs.

[0078] In one embodiment of this disclosure, the time-series binning module 502 is used to: determine the status record of an item in the flow information and the update time of the status record; and perform time-series binning on the status record of the item according to the update time of the status record to obtain multiple time bins.

[0079] In one embodiment of this disclosure, the time-series binning module 502 is used to: determine the update time of the status record and round it down to obtain the bin identifier corresponding to the status record of the item; and divide the status records of items corresponding to the same bin identifier into the time bins identified by the same bin identifier.

[0080] In one embodiment of this disclosure, the second determining module 504 is configured to: determine the baseline state record of the item based on the full item snapshot information of the second time period; and determine the state record and corresponding lifecycle information of the item in the first time period based on the baseline state record of the item and the latest state record of the item in its respective time bucket.

[0081] In one embodiment of this disclosure, the second determining module 504 is configured to: determine the status record of the item within a first time period based on the latest status record of the item within its time bin; complete and update the status record of the item within the first time period based on the baseline status record of the item; and determine the lifecycle information corresponding to the status record based on the start and end times corresponding to the status record.

[0082] In one embodiment of this disclosure, the second determining module 504 is configured to: determine the start time corresponding to the latest status record based on the bin identifier of the time bin to which the latest status record belongs; determine the next time bin to which the item belongs within a first time period; and determine the end time corresponding to the latest status record based on the bin identifier of the next time bin to which the item belongs.

[0083] In one embodiment of this disclosure, the second determining module 504 is configured to: in response to the fact that no next time bucket to which the item belongs exists within a first time period, determine the last bucket identifier corresponding to the first time period as the end time corresponding to the latest status record.

[0084] In one embodiment of this disclosure, the second determining module 504 is configured to: determine a first state record among the state records appearing in the first time period, wherein the first state record has the earliest start time; generate a first state record of the item appearing in the first time period based on the baseline state record and the first state record, wherein the first state record is temporally continuous with the first state record and is located before the first state record; and complete the state records of the item appearing in the first time period based on the first state record.

[0085] In one embodiment of this disclosure, after the device 500 completes the status records of the item within a first time period based on the first status record, it is configured to: determine the bin identifier of the first time bin corresponding to the first time period as the start time of the first status record; and determine the bin identifier of the time bin to which the first status record belongs as the end time corresponding to the first status record.

[0086] In one embodiment of this disclosure, the device 500 is configured to: in response to the fact that no status record appears for the item during a first time period, determine that the baseline status record is a global status record that can cover the first time period; and determine the lifecycle information of the global status record based on the bin identifier of the first time bin corresponding to the first time period and the bin identifier of the last time bin corresponding to the first time period.

[0087] The information processing device proposed in this disclosure acquires the flow information of items within a first time period and a full snapshot of items within a second time period, wherein the second time period is adjacent to and earlier than the first time period. It then performs time-series binning on the flow information to obtain multiple time bins, determines the latest state record of each item within its respective time bin, and, based on the latest state record of each item within its respective time bin and the full snapshot of items within the second time period, determines the state record of the item within the first time period and its corresponding lifecycle information. Thus, by performing time-series binning on the flow information to obtain multiple time bins and determining the state record of items within the first time period and its corresponding lifecycle information, this disclosure achieves the backtracking and querying of item state records at any time granularity without requiring data expansion or high-frequency computation. This solves the problems of low computational efficiency, poor data timeliness, and huge resource consumption when facing high-frequency state changes of items and the need for refined operations. While reducing resource consumption, it further improves the efficiency and timeliness of information processing.

[0088] According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0089] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0090] like Figure 6 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded into random access memory (RAM) 603 from storage unit 608. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0091] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0092] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as information processing methods. For example, in some embodiments, the information processing method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the information processing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform information processing methods by any other suitable means (e.g., by means of firmware).

[0093] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0094] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0095] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0096] To initiate interaction with a user account, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user account; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user account can submit input to the computer. Other types of devices can also be used to initiate interaction with the user account; for example, feedback submitted to the user account can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user account can be received in any form (including voice input, speech input, or tactile input).

[0097] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user account computer with a graphical user interface or web browser through which a user account can interact with the implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0098] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0099] According to embodiments of this disclosure, this disclosure also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, it implements the steps of the information processing method described in the above embodiments of this disclosure.

[0100] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0101] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An information processing method, wherein, The method includes: Obtain the item flow information within a first time period and the full item snapshot information within a second time period, wherein the second time period is adjacent to the first time period and is earlier than the first time period; The flow information is divided into time-series buckets to obtain multiple time buckets; Determine the latest status record of the item within its assigned time bin; Based on the latest status record of the item within its respective time bucket and the full item snapshot information of the second time period, determine the status record of the item and its corresponding lifecycle information during the first time period.

2. The method according to claim 1, wherein, The determination of the latest status record of an item within its respective time bucket includes: Based on the update time of the status record of the item within its respective time bucket, determine the latest status record of the item within its respective time bucket.

3. The method according to claim 2, wherein, Determining the latest status record of an item within its respective time bucket based on the update time of its status record within that time bucket includes: In response to the multiple status records of the item within the time bucket to which the item belongs, the multiple status records are sorted according to the update time of the status records to determine the latest status record of the item within its data bucket.

4. The method according to claim 3, wherein, The step of sorting the status records according to their update time includes: Call the window-based sequence generation function; Based on the window-based sequence generation function, the multiple states are arranged in reverse order according to the update time.

5. The method according to claim 1, wherein, The process of performing time-series bucketing on the flow information yields multiple time buckets, including: Determine the status record of the items in the flow information and the update time of the status record; Based on the update time of the status record, the status record of the item is divided into time-series buckets to obtain multiple time buckets.

6. The method according to claim 5, wherein, The step involves performing time-series bucketing on the item's status records based on their update time, resulting in multiple time buckets, including: The update time of the status record is determined and rounded down to obtain the bin identifier corresponding to the status record of the item; The status records of items corresponding to the same bin identifier are assigned to the time bin identified by the same bin identifier.

7. The method according to any one of claims 1-6, wherein, The step of determining the status records and corresponding lifecycle information of the item within the first time period based on the latest status record of the item within its respective time bucket and the full item snapshot information of the second time period includes: Based on the full item snapshot information of the second time period, determine the baseline state record of the item; Based on the baseline state record of the item and the latest state record of the item within its respective time bucket, determine the state record of the item and its corresponding lifecycle information within the first time period.

8. The method according to claim 7, wherein, The step of determining the status records and corresponding lifecycle information of the item within the first time period based on the item's baseline status record and the item's latest status record within its respective time bucket includes: Based on the latest status record of the item within its respective time bin, determine the status record of the item during the first time period; Based on the baseline state record of the item, the state record of the item during the first time period is completed and updated. Based on the start and end times corresponding to the status record, the lifecycle information corresponding to the status record is determined.

9. The method according to claim 8, wherein, The process of determining the start and end times corresponding to the state record includes: The start time corresponding to the latest status record is determined based on the bucket identifier of the time bucket to which the latest status record belongs; Determine the next time bucket for the item within the first time period; The end time corresponding to the latest status record is determined based on the bucket identifier of the next time bucket.

10. The method according to claim 9, wherein, The method further includes: In response to the fact that no next time bucket belongs to the item within the first time period, the last bucket identifier corresponding to the first time period is determined as the end time corresponding to the latest status record.

11. The method according to claim 8, wherein, The step of completing the state record of the item within the first time period based on the item's baseline state record includes: Determine the first state record among the state records that appear within the first time period, wherein the first state record has the earliest start time; Based on the baseline state record and the first state record, the first state record of the item appearing in the first time period is generated, wherein the first state record is temporally consecutive with the first state record and is located before the first state record. Based on the first state record, the state records of the item during the first time period are completed.

12. The method according to claim 11, wherein, After completing the state records of the item within the first time period based on the first state record, the method further includes: Determine the bucket identifier of the first time bucket corresponding to the first time period, and use it as the start time of the first status record; The bucket identifier of the time bucket to which the first state record belongs is determined, which is the end time corresponding to the first state record.

13. The method according to claim 7, wherein, The method further includes: In response to the fact that no status record appears for the item during the first time period, the baseline status record is determined to be a global status record that can cover the first time period. The lifecycle information of the global state record is determined based on the bucket identifier of the first time bucket corresponding to the first time period and the bucket identifier of the last time bucket corresponding to the first time period.

14. An information processing apparatus, wherein, The device includes: The acquisition module is used to acquire the item flow information within a first time period and the full item snapshot information within a second time period, wherein the second time period is adjacent to the first time period and is earlier than the first time period. The time-series bucketing module is used to perform time-series bucketing on the flow information to obtain multiple time buckets; The first determination module is used to determine the latest status record of an item within its respective time bucket. The second determining module is used to determine the status records and corresponding lifecycle information of the item in the first time period based on the latest status record of the item in its time bucket and the full item snapshot information of the second time period.

15. An electronic device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the method as described in any one of claims 1-13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-13.

17. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-13.

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