JP2017050012A - Index constitution for retrievable data in network - Google Patents

Abstract

PROBLEM TO BE SOLVED: To automatically generate a retrieval index for retrievable data received from a computing device.SOLUTION: Data to be received in a network service may include a plurality of data fields and each data field has one or more related values. The data fields and their related values are analyzed, thereby discriminating a data field type for the data fields and a retrieval option that should be validated for the data fields. At least partially based on the data field type and the retrieval option, a retrieval index constitution/schemer is generated. At least partially based on the generated retrieval index constitution/schemer, a retrieval index for data is generated. The network service may also convert the data into a format that can be compared with the retrieval index.SELECTED DRAWING: Figure 5

Description

  Computing devices are often used to communicate over networks such as the Internet. Network-based services provided by service providers are becoming increasingly commonplace. To network-based services that can provide services such as storing searchable data that will be used / read by a computing device or providing additional processing power to a computing device Computing devices are frequently used to connect. With respect to storing searchable data on a network basis, computing device users typically need to select the configuration and / or format for those data so that the data can be sent by network-based services. Can be indexed and stored. Conventional approaches typically require the user to determine the appropriate configuration for their data. Conventional approaches may also require a format that the user's data needs to follow, thereby requiring the user to convert the data to that format. This can be inconvenient, cumbersome or difficult for users who want to use network-based services for storage and retrieval, thereby reducing the overall user experience.

Various embodiments in accordance with the present disclosure are described with reference to the following drawings.
FIG. 6 illustrates an example environment in which aspects of various embodiments can be utilized. FIG. 2 illustrates an exemplary system embodiment for indexing for searchable data in a networked environment. FIG. 1 illustrates an example web browsing environment that can utilize an index structure for searchable data in a networked environment. FIG. 6 illustrates an exemplary search index that can be generated in accordance with various embodiments. FIG. 4 illustrates an example method embodiment for indexing for searchable data in a networked environment. FIG. 11 illustrates an example device that can be used to implement aspects of various embodiments. FIG. 7 illustrates exemplary components of a client device such as the device shown in FIG. FIG. 6 illustrates an environment in which various embodiments can be implemented.

  Systems and methods for generating an index configuration that can be used to generate a search index for data received on at least one network are described. At least some embodiments allow a computing device to upload data over a network (eg, the Internet) and over a storage allocation provided by a network service (ie, a network service provider). . The network service can analyze the uploaded data to determine the data field type (ie, data field type) for each data field in the plurality of data fields. The network service can analyze the uploaded data and determine whether to enable one or more search options for each data field in the plurality of data fields included in the uploaded data.

  At least some embodiments allow a computing device to upload data over a network (eg, the Internet) and over a storage allocation provided by a network service (ie, network service provider, network-based service, etc.) Make it possible to do. One or more users / entities (eg, using one or more computing devices) search for uploaded data on the network using a search index that can be provided by a network service. Can do.

  In some embodiments, the uploaded data can include multiple data fields. The network service can analyze the uploaded data to determine the data field type (ie, data field type) for each data field in the plurality of data fields. For example, each data field can be a field of a type including an integer type, a text type, or a literal type.

  In addition, the network service can analyze the uploaded data to determine whether to enable one or more search options for each data field in the plurality of data fields included in the uploaded data. . For example, the network service can determine for each respective data field whether to enable an option that includes the respective data field in the search index to be generated. The network service can also determine for each respective data field whether to enable the option of calculating the number of facets for each data field. Further, the network service may determine for each respective data field whether to enable an option to return / provide values associated with the respective data field in response to the search query.

  In some embodiments, the network service may configure the index configuration (ie, search index) for the data based at least in part on the determined data field type (s) and the search option (s) to be enabled. Configuration, schema, index settings, etc.). The network service may generate a search index for the data based at least in part on the index configuration.

  Various other features and advantages are described and proposed below, as provided in accordance with various embodiments.

  FIG. 1 illustrates an exemplary environment 100 in which aspects of various embodiments can be utilized. The exemplary environment 100 includes at least one computing device 102, a network 104 (eg, the Internet, an intranet, a local network, a local area network, etc.), and a network service 106 (ie, a network service provider, network-based service, etc.). Can be provided. At least one computing device 102 may be communicatively connected to the network service 106 over the network 104. In some embodiments, the computing device 102 can communicate with the network service 106 without the network 104, such as the Internet. As shown in FIG. 1, there may also be a user 108 of at least one computing device 102, or other entity 108 (eg, an individual, a company, an organization, a group, etc.). A user or entity 108 can communicate data 110 from the at least one computing device 102 to the network service 106 over the network 104 (and vice versa).

  In some embodiments, the network service 106 may comprise and / or utilize one or more hosts or servers connected to the network 104. For example, the network service 106 may lease storage space to a customer, such as a user of the device 102 or another entity (s) (eg, a company, organization, group, individual, etc.) 108. Accordingly, the user / entity 108 of the computing device 102 can use the network 104 to store data from the device 102 on the network service 106. In other words, user / entity 108 and / or device 102 can utilize network-based computing storage via network service 106.

  In one example, as shown in FIG. 1, computing device 102 may transmit data 110 over network 104 to be stored on network service 106. Data 110 may be any data utilized in network-based computing, such as for searching, database storage, application execution, virtual machine execution, operating system execution, and the like. The computing device 102 can transmit the data 110 to be stored on the storage allocation provided by the service 106. For example, the user / entity 108 can purchase or rent storage space on the service 106, and storage allocations can be assigned and allocated to the user / entity 108. In some embodiments, a user / entity 108 may have a specific account and / or storage allocation on the service 106 and storage space allocated and allocated to the entity 108 (eg, storage allocation) ) Can be associated with an account for entity 108.

  The entity 108 may also wish to provide the network service 106 with a search index for the data 110. Conventional approaches typically require that entity 108 first provide a configuration (ie, index configuration, schema, index settings, etc.) for data 110 to be indexed, or conventional approaches May require a configuration / format (e.g., Search Data Format (SDF)) that the data 110 needs to comply with, thus requiring the entity 110 to convert the data 110 into the required configuration. To do. However, this can be inconvenient, cumbersome or difficult for the entity 108.

  In some embodiments, the entity 108 can send the data 110 to the network service 106, as well as the network service 106 automatically (ie, without a command or request from the entity 108) to send the data 110. Analyzing and generating an index configuration (eg, search index configuration, search index schema, etc.) for data 110. For example, in some embodiments, network service 106 determines the type of data field 112 for one or more data fields included in data 110 and for one or more data fields included in data 110. Data 110 can be analyzed by determining search options 114 to be enabled.

  With respect to determining the type of the data field 112, the data 110 (eg, document, file, etc.) can be associated with a data field integer type, a data field literal type, or a data field text type, etc. There can be data field types. In some embodiments, the data 110 may include a plurality of data fields, and each data field may include a value (eg, the data field “name” may include a value of “ABCD brand shirt”). Data field “price” may have a value of “$ 20”, etc.). The network service 106 can analyze a plurality of data fields included in the data 110 to determine a data field type for each data field in the plurality.

  For example, for each data field, the network service 106 determines whether each respective data field contains an integer whose amount exceeds a specified integer amount threshold (eg, the value of the data field “price” is all integers). And if so, each of the data fields can be determined to be an integer data field type. The network service 106 may also be, for example, a value associated with a data field that has an alphabetic character with an amount that is above the specified lower literal amount threshold but less than the specified upper literal amount threshold, less than the specified literal difference amount threshold. A number of different values associated with a data field that is, a percentage of different values that are less than a specified literal difference percentage threshold, or a length that is less than a specified literal length threshold By determining at least one of the values, it can be determined whether the data field is a literal data field type field. In some embodiments, the network service 106 is a text-type field, taking into account, for example, the length of the value of the data field, the frequency and / or percentage of different values in the value of the data field. If a data field can be identified, there are many different values in the value of the data field, and the value of the data field is very long (eg, has a number of alphanumeric characters above a threshold), the data field Is likely a text-type field. In some embodiments, if the data field is not an integer, literal type field, the data field can be a text type field.

  With respect to determining the search option 114, the network service 106 may determine one or more search options 114 to be enabled for the data 110 (data field thereof). For example, once the data field type for the data field included in the data 110 is determined, the network service 106 determines whether to enable the option to include the data field in the search index to be generated, and determines the number of facets for the data field. It can be determined whether to enable the option to calculate and / or whether to enable the option to return / provide search values for the data type.

  For example, if the data field type for the data field is determined to be text (eg, the data field is “Product Description” and the value is a long clause), the network service 106 includes the data field ( And options that do not include values). In another example, for a data field having an integer data field type (eg, the data field is “Production Year” and the value is 1 year), the network service 106 includes the data field in the generated search index. And the service 106 can enable the option of calculating the number of facets for the data field. The number of facets can be the number of search results that fall into a certain category for the data field. For example, if the data field is “year of manufacture”, the network service 106 may determine whether it makes sense to provide a facet number that indicates how many search results are associated with a category. For example, “1984 (23), 2002 (12), 2010 (18)” has 23 search results associated with “1984” and 12 search results “2002” with respect to the “year of manufacture” data field. And an example of the number of facets associated with 18 and the 18 search results associated with “2010”.

  In some embodiments, the network service 106 may also decide to enable returning a value for the data field. For example, not all searchable data fields (and values) need be returned (eg, read and presented) in response to a search request. The network service 106 can determine whether to return a value for the data field.

  Here, looking at generating a configuration for data 110, the network service automatically generates a configuration for data 110 (eg, search index configuration, schema, etc.) automatically (ie, without instruction from entity 108). can do. In some embodiments, the configuration can help determine, at least in part, how to index the data 110, and the index configuration at least in part how the data can be indexed. It can be determined whether 110 is indexed. The configuration or schema can specify a data field type for each data field included in the data 110, indicates whether each data field is searchable, and whether each data field can be ranked (eg, sorted) Possible) and other similar information useful for building the index. Subsequent to generating a configuration for data 110 to be indexed, network service 106 may generate a search index for data 110 based at least in part on the generated configuration.

  FIG. 2 illustrates an exemplary web browsing environment 200 that can utilize an index structure for searchable data in a networked environment. The example web browsing environment 200 may comprise an example web page 202 being rendered by an application, such as a web browser. In this example, the web page 202 is assigned to the domain ABCD. com can be provided by a network service associated with the com.

  A user / entity (eg, a customer of a network service) can be a retailer and can upload data related to, for example, selling a shirt. Data can be indexed and stored by network services, and can be searchable by others such as potential customers of the user / entity. The network service can analyze the data to determine the type of data field (ie, data field type) for each of the data fields included in the data. For example, data associated with selling a shirt may include data fields such as “color” 206, “size” 208, “price” 210, “description” and other fields. The network service can analyze the value for each data field to determine the type for each respective data field. The network service may also determine whether one or more options (eg, search options) are enabled for each data field. The network service can then generate a configuration / schema for the data to be indexed. The network service can then generate an index for the data based on the configuration / schema.

  For example, the network service can identify the data field “color” and determine that its value (eg, “red”, “blue”, “white”, “green”, etc.) is alphabetic / literal. And the type of the “color” data field can be identified as a literal type. (In this example, data and values (eg, “red”, “blue”, “white”, “green”, etc.) associated with the “color” data field can be uploaded by the entity). In another example, the network service may identify a “size” data field in at least a portion of the uploaded data and determine that the value contained in the “size” data field is a number. Can do. In this example, the network service may determine that the “size” data field is of integer type. In a further example, the network service can identify a value for the “description” data field in at least a portion of the uploaded data, as well as that the value contains both numbers and alphabetic characters, It may be determined that the number is long and / or includes terms / phrases / symbols with different values. In this example, the network service may determine that the “description” data field is text type.

  With respect to search options, the network service can determine for each of the data fields whether to enable the option to include the respective data field in the search index to be generated. For example, in some embodiments, the “description” data field (and corresponding value) can be excluded from the search index. If so, when the query is run on the search index, the query does not search the “description” data field. However, some embodiments can and do include “description” data fields and values in the search index.

  Further, the network service can determine whether to enable the option of calculating the number of facets for each data field. As described above, the facet number indicates how many results matching the search query have a value (or range of values) for a particular data field. For example, as shown in FIG. 2, a “color” data field having a value of “red” has a facet number of 23 (ie, 23 search results for a “red” shirt) and “color” A “blue” value in the data field has 28 facet numbers (ie, 28 search results for a “blue” shirt), and so on. In some embodiments, the values may overlap (ie, they may not match exactly). For example, a shirt with blue and red stripes can be associated with both “blue” and “red” values and / or can be associated with other values. In some embodiments, the network service may determine that the facet number should be calculated for some of the data fields, but not necessarily for all of the data fields. For example, the network service may determine that there should be facet numbers for “color”, “size” and “price” but not for “description”.

  Further, the network service can determine whether to enable returning a value for the data field. For example, the data field “Internal Product Identification Number” included in the data, that is, the product identification number internal to the entity, and there may be a value for the data field that is not intended to be seen by the entity customer. The network service can therefore decide not to validate returning a value for such a data field.

  There may be data relating to additional options, as well as other items recognized by those skilled in the art. For example, the network service may determine whether to enable an option that enables data fields to be ranked (eg, sortable). Referring to FIG. 2, in some embodiments, the “Price” data field may be ranked / sorted by its value (eg, from lowest price to highest price, highest price to lowest price, etc.). And “color” data fields can be sorted alphabetically (not shown in FIG. 2), and so on. In another example (not shown), there can be data associated with media files such as music, videos, books, photos, and the like. Exemplary data fields for a media file can include, but are not limited to, “title”, “artist / author”, “creation year”, “price”, “rating”, and the like.

  Once the type of data field included in the data and one or more search options for the data field included in the data are determined, the network service can generate a configuration for the data (ie, search index configuration, schema, etc.). Generating the configuration is based at least in part on the determined data field type and search options.

  Following generating the configuration, the network service may generate a search index for the data based at least in part on the generated configuration. Thus, data provided by an entity can be stored in a network service and can be stored with a search index for data generated by the network service.

  FIG. 3 illustrates an exemplary system embodiment 300 for index configuration for searchable data in a networked environment. The exemplary system embodiment 300 includes a system controller 302, at least one communication transceiver 304, a data field type analyzer 306, a search option analyzer 308, an index configuration generator 310, an index generator 312, and at least one storage allocation 314. Can be provided.

  The system controller 302 can facilitate performing various operations on the index configuration for searchable data in a networked environment. System controller 302 communicates with at least one communication transceiver 304 to facilitate data transmission to and / or data reception from one or more sources external to system 300, and data communication between systems. Can be promoted.

  Data (eg, from an entity) received by system 300 via communication transceiver 304 can be analyzed by data field type analyzer 306 to determine the type associated with each of the data fields included in the data. . The data can also be analyzed by a search option analyzer 308 to determine whether to enable one or more search options for each of the data fields included in the data. Based at least in part on the determined data field type and the one or more determined search options, the index configuration generator 310 can generate a search index configuration / schema. Based at least in part on the generated search index configuration / schema, the index generator 312 can generate a search index for the data. Data and search indexes generated for the data can be stored on one or more storage allocations 314.

  It is contemplated that various components and / or portions of exemplary system 300 may be implemented as hardware, software, or a combination of both. For example, various portions of system 300 may be implemented via circuits, processors, applications, portions of programming code, algorithms, or any combination thereof. Also, FIG. 3 is an example and is intended to be used merely for illustrative purposes. For example, the various components need not be configured according to FIG. In some embodiments, the various components need not be tightly coupled to each other, but instead can be distributed across additional distributed systems. For example, a component such as an index generator can exist on a separate / different network and / or system, but can still maintain communicable connection (s) to other components.

  FIG. 4 illustrates an exemplary search index 400 that can be generated in accordance with various embodiments of the present disclosure. Referring to FIG. 4, a root node 402 can exist in the search index. In the example of FIG. 4, data may be uploaded by an entity such as a T-shirt retailer. The data may correspond to information about a T-shirt (root node 402) that the entity has made available for sale. There may be a parent node (eg, 404, 406, 408) that represents a data field for data related to the T-shirt. For example, a T-shirt can have a color data field 404, a size data field 406, and a price data field 408.

  Continuing with the example of FIG. 4, a data field may have child nodes (eg, 410, 412, 414, 416, 418) that represent the values in each respective data field. For example, there can be at least two colors (red 410 and blue 412), one size (medium 414), and two price ranges (less than $ 10 416 and $ 10 to $ 20 418). There may also be search result / item pairs (eg, T-shirts 420, 422, 424, 426, 428, 430) that may correspond to one or more of the data fields and values.

  In this example, all three data fields (color 404, size 406, and price 408) will be included in the search index, may have facet numbers, and in response to the associated search query, A value can be provided / returned. For example, as shown in FIG. 4, the color: red 410 can have a facet number of 3, and the color: blue 412 can have a facet number of 2. Size: Medium 414 can have a facet number of two. Price: less than $ 10 416 can have a facet number of 1, and price: $ 10- $ 20 418 can have a facet number of 2. Further, the search query for color: red 410 returns, for example, T-shirts 422, 424, and 428, searches for red 410 and blue 412, returns, for example, T-shirt 422, and so on. Although the exemplary search index 400 is shown as a tree structure, it is contemplated that the search index can be generated in many other ways and / or in other structures.

  FIG. 5 illustrates an example method embodiment 500 for indexing for searchable data in a networked environment. There may be additional, some, or alternative steps performed in a similar or alternative order or in parallel, within the scope of various embodiments, unless otherwise noted. Should be understood again. In step 502, exemplary method embodiment 500 may receive data to be indexed. For example, the method 500 can receive data uploaded by an entity to be indexed and the data can include multiple data fields (or at least one data field). In some embodiments, the example method can also determine a name for the data field associated with the data. In step 504, the example method 500 can determine the type of data field associated with the data. For example, the method can determine a field type of a plurality of field types associated with each data field in the plurality of data fields. The plurality of field types can include (but are not limited to) at least one of an integer type, a literal type, or a text type. The type of data field can be determined from multiple types of data fields. In some embodiments, multiple data fields and their types and / or names can be identified based on tags, signals, or other indications. The method 500 may determine at step 506 one or more search options to be enabled for the data field associated with the data. For example, one or more search options may include an option to include each data field in the search index to be generated, an option to calculate the number of facets for each data field, or one or more associated with each data field At least one of options providing multiple values may be included. Step 508 may include generating an index configuration for the data based at least in part on the type of data field and the one or more search options. Then, at step 510, the method 500 can generate a search index for the data based at least in part on the index configuration for the data. In some embodiments, a search index can be generated based on whether the data is structured data, free text data, or a combination of both. In some embodiments, the exemplary method may also provide at least one of data, an index configuration, or an index that is searchable by one or more search queries.

  Various other information can be included in the index configuration. For example, the configuration can determine whether a data field can be faceted (ie, whether the number of facets should be calculated for the data field), whether the data field can be ranked (ie, Information about whether or not search result values having data fields should be sorted.

  In some embodiments, the network service can convert data received / uploaded in a first format to a second format, the second format conforms to a search index, and the second The data converted to the format can be stored on one or more storage allocations. For example, a network service can receive data from an entity and the data can be. PDF,. DOC,. DOCX,. CSV,. JSON,. It is possible to have any one or more of several different formats, such as XML. The network service can automatically convert the data into a format compatible with the network service, such as a search data format (SDF) (eg, recognizable by the network service and executable by the network service).

  In some embodiments, the network service compares the first format with the second format and modifies at least one data field associated with the first format to associate with the second format. The data can be converted based on corresponding to at least one data field provided. For example, the network service can compare the format (s) of data received from the entity and can change / update the format to suit the network service. This can include identifying whether one or more data fields in the format are to be added, removed, or changed.

  In some embodiments, the network service determines the type of the data field based on determining whether the value associated with the data field has an amount of integer characters that exceeds a specified integer amount threshold. It can be determined that it is an integer type. Also, the network service is less than the specified literal difference threshold that is greater than the specified lower literal amount threshold but is associated with a data field having an amount of alphabetic characters that is less than the specified literal amount threshold. At least one of several different values associated with the data field, the percentage of different values that are less than a specified literal difference percentage threshold, or the length of a value that is less than a specified literal length threshold The data field type can be determined to be a literal type. In addition, the network service may provide integers and alphabetic characters whose value associated with the data field exceeds the specified text amount threshold, some different characters that exceed the specified text difference threshold, the specified text. The data field type is text based on determining whether it has at least one of the percentage of different characters above the difference percentage threshold or the length of the characters above the specified text length threshold It can be determined that

  In some embodiments, the network service can determine to enable the option to include a data field in the search index that will be generated, and the determination will result in the data field being included in the search index. Is based at least in part on receiving a signal included in the data field. The network service can also determine to enable the option to calculate the number of facets for the data field, and the determination is that the amount for at least one value associated with the data field exceeds the specified facet number lower threshold. , And determining that the facet number is less than a specified upper limit threshold value. The network service may further determine to enable an option to provide a value associated with the data field in response to an associated search query, the determination being provided with a value associated with the data field. Is based at least in part on receiving a signal included in the data field, indicating that

  In some embodiments, one or more search queries (eg, words in a search query) can be utilized by a network service. For example, the network service can infer from the search query that the searcher is faceting a particular data field. As a result, the network service can determine, for example, that the data field should be a literal field.

  In some embodiments, when a searcher enters a query term and requests a search, one or more search results are presented in a particular rank expression (eg, order of results), such as by relevance. be able to. The present disclosure allows for the creation of more complex rank expressions that take into account other factors such as factors that do not depend on the query (eg, popular data fields can be included in the data). The present disclosure may also allow analysis to suggest rank expressions that can be used by referring to the data and determining that the data field is important in terms of popularity. For example, a text field data field type may exist, its length (eg, or the inverse of its length may be considered), and its length provides useful information for rank expressions. Can be provided.

  In some embodiments, the data field type can also include a geographic location type, a time type, a date type, or a floating point number type.

  Various embodiments consistent with this disclosure may also utilize sample data. For example, a user / entity can initially provide sample data to a network service. The network service can analyze the sample data to determine the data field type and search options. Based on the data field type and search options for the sample data, the network service can generate an index configuration, and subsequently generate a search index based on the generated index configuration.

  FIG. 6 illustrates an exemplary electronic user device 600 that can be used in accordance with various embodiments. Although a portable computing device (eg, an electronic book reader or tablet computer) is shown, input can be received, determined, and / or processed according to various embodiments discussed herein. Any electronic device can be used and it is understood that the device can include, for example, a desktop computer, notebook computer, personal digital assistant, smartphone, video game console, television set top box, and portable media player Should do. In some embodiments, computing device 600 may be an analog device, such as a device that can perform signal processing using an operational amplifier. In this example, the computing device 600 has a display screen 602 on the front surface and, in normal operation, provides information to a user facing the display screen (eg, on the same side as the display screen of the computing device). Is displayed. The computing device in this example includes at least one camera 604 or other imaging element that captures still or video image information on at least the field of view of at least one camera. In some embodiments, the computing device may simply include only one imaging element, and in other embodiments, the computing device may include several imaging elements. Each image capture element may be, for example, a charge coupled device (CCD), a motion detection sensor, or an infrared sensor, among many other possibilities. Where there are multiple image capture elements on a computing device, the image capture elements may be of different types. In some embodiments, the at least one imaging element can include at least one wide-angle optical element that allows the camera to capture images over a wide range of angles, such as 180 degrees or more, such as a fisheye lens. Further, each image capture element can include a digital still camera configured to capture subsequent frames in rapid succession, or a video camera capable of capturing streaming video.

  The exemplary computing device 600 also includes at least one microphone 606 or other audio capture device that can capture audio data, such as words or commands issued by a user of the device. In this example, the microphone 606 is placed on the same side as the display screen 602 of the device, which allows the microphone to better capture words that are typically emitted by the user of the device. In at least some embodiments, the microphone may be a directional microphone that captures audio information substantially immediately from the front of the microphone and picks up only a limited amount of audio from other directions. The microphones may be located on any suitable surface of the device, in any region, face, or boundary in different embodiments, and multiple microphones are used for purposes such as audio recording and filtering You should understand what you can do.

  The exemplary computing device 600 also includes at least one orientation sensor 608, such as a position and / or motion determination element. Such sensors can include, for example, accelerometers or gyroscopes operable to detect device orientation and / or orientation changes, as well as small movements of the computing device. The orientation sensor can also include an electronic or digital compass that can indicate the direction (eg, north or south) that the device is determined to be facing (eg, with respect to the major axis or other such surface). . The orientation sensor also includes or comprises a global positioning system (GPS) or similar positioning element operable to determine relative coordinates relative to the position of the device, as well as relatively large movements of the computing device. be able to. Various embodiments can include one or more such elements in any suitable combination. As should be appreciated, the algorithm or mechanism used to determine relative position, orientation, and / or movement can depend at least in part on the selection of elements available to the device.

  FIG. 7 illustrates a logical arrangement of a general set of components of an exemplary computing device 700, such as the device 600 described with respect to FIG. In this example, the device includes a processor 702 that executes instructions that can be stored in a memory device or element 704. As will be apparent to those skilled in the art, the device may be a first storage for program instructions for execution by processor 702, a separate storage for images or data, or a removable memory for sharing information with other devices. Many types of memory, data storage devices, or non-transitory computer readable storage media can be included. Devices typically include some type of display element 706, such as a touch screen or a liquid crystal display (LCD), but devices such as portable media players carry information via other means, such as through an audio speaker. Also good. As discussed, the device in many embodiments is at least one image capture element 708, such as a camera or an infrared sensor, that can image a projected image or other object in the vicinity of the device. including. Methods for capturing images or videos using camera elements at a computing device are known in the art and will not be discussed in detail herein. It should be understood that image capture can be performed using a single image, multiple images, periodic imaging, sequential image capture, image streaming, and the like. Further, the device can include the ability to start and / or stop capturing images, such as when a command is received from a user, application, or other device. Exemplary devices also include at least one audio capture component 712 that is operable to capture audio information from at least one primary direction, such as a mono or stereo microphone or a microphone array. The macrophone can be a unidirectional or omnidirectional microphone that is known for such devices.

  In some embodiments, the computing device 700 of FIG. 7 includes one or more communication elements (not shown), such as Wi-Fi®, Bluetooth®, RF, wired or wireless communication systems. Can be included. Devices in many embodiments can communicate with a network, such as the Internet, and may be able to communicate with other such devices. In some embodiments, the device can include at least one additional input device capable of receiving conventional input from a user. This conventional input can be, for example, a push button, touchpad, touch screen, wheel, joystick, keyboard, mouse, keypad, or any other such that allows the user to enter commands to the device Various devices or elements. However, in some embodiments, such a device may not include any buttons and may only be controlled through a combination of visual and voice commands so that the user contacts the device. The device can be controlled without need.

  The device 700 can also include at least one orientation or motion sensor 710. As discussed, such a sensor can indicate an orientation and / or an accelerometer or gyro sensor operable to detect orientation changes, or a direction in which the device is determined to be oriented. An electronic or digital compass can be included. The mechanism (s) is also (or alternatively) a global positioning system (GPS) or similar that is operable to determine relative coordinates relative to the position of the device, as well as relatively large movements of the computing device. Positioning elements may be included or provided. The device can also include other elements such as position determination can be enabled through trigonometry or another such approach. These mechanisms can communicate with the processor 702 so that the device can perform any number of operations described or suggested herein.

  By way of example, a computing device as described with respect to FIG. 6 can capture and / or track various information for a user over time. This information can include location, action (eg, sending a message or creating a document), user behavior (eg, how often the user performs the task, how much time the user takes for the task, Any appropriate, such as how the user navigates through the interface), user preferences (eg, how the user wants to receive information), open applications, placed requests, and received calls Information can be included. As described above, information can be stored in such a way that the information is linked or associated so that the user can access the information using any suitable manner or collection of manners. can do.

  As discussed, different approaches can be implemented in various environments in accordance with the described embodiments. For example, FIG. 8 illustrates an example environment 800 for implementing aspects in accordance with various embodiments. As will be appreciated, a web-based environment is used for illustrative purposes, but different environments may be used to implement various embodiments, if desired. The system may include any suitable device operable to send and receive requests, messages, or information over the appropriate network 804 and to carry the information back to the user of the device. 802. Examples of such client devices include personal computers, mobile phones, handheld messaging devices, laptop computers, set top boxes, personal digital assistants, electronic book readers, and the like. The network can include any suitable network including an intranet, the Internet, a cellular network, a local area network, or any other such network, or combinations thereof. The components used in such a system may depend at least in part on the type of network and / or the environment selected. Protocols and components for communicating over such networks are known and will not be discussed in detail herein. Communication over the network can be enabled via a wired or wireless connection, and combinations thereof. In this example, the network includes the Internet because the environment includes a web server 806 that receives the request and supplies content in response thereto, but, as will be apparent to those skilled in the art, for other networks, the same Alternative devices that serve the purpose will be used.

  An exemplary environment includes at least one application server 808 and data store 810. There can be several application servers, hierarchies or other elements, processes, or components that can interact to perform tasks such as retrieving data from the appropriate data store, It may be chained or composed. As used herein, the term “data store” refers to any device or combination of devices capable of storing, accessing, and retrieving data, and any standard, distributed, or clustered Any combination and number of data servers, databases, data storage devices, and data storage media in a given environment may be included. The application server interacts with the data store as needed to perform one or more aspects of the application to the client device and any suitable hardware and data processing and most of the business logic for the application. Software can be included. The application server cooperates with the data store to provide access control services and in this example can be provided to the user by the web server in the form of HTML, XML or another suitable structured language. It is possible to generate content such as text, graphics, audio, and / or video that will be transferred to. The processing of all requests and responses and the distribution of content between client device 802 and application server 808 can be handled by web server 806. Since the structured code discussed herein can be executed on any suitable device or host machine discussed elsewhere herein, web and application servers are not required, and they It should be understood that these are merely exemplary components.

  Data store 810 may include a number of separate data tables, databases, or other data storage mechanisms and media for storing data associated with a particular aspect. For example, the illustrated data store includes a mechanism for storing manufacturing data 812 and user information 816 that can be used to supply content to the manufacturing side. The data store is also shown to include a mechanism for storing log or session data 814. It should be understood that there can be many other aspects needed to be stored in the data store, such as page image information and access rights information, which can be , Or any of the additional mechanisms in the data store 810. Data store 810 is operable to receive instructions from application server 808 through logic associated therewith and to obtain, update, or process data in response thereto. In one example, a user may submit a search request for a particular type of element. In this example, the data store may access user information to confirm the identity of the user, and access catalog detail information to obtain information about that type of element. The user can then return information to the user, such as listing the results on a web page that can be referenced via a browser on the user device 802. Information for a particular element of interest can be referenced in a dedicated page or browser window.

  Each server typically includes an operating system that provides executable program instructions for the overall management and operation of that server, and when each server is typically executed by the server's processor, the server is intended for it. Including a computer readable medium having instructions stored thereon for performing functions. Suitable implementations for the overall functionality of the operating system and server are known or commercially available, and are readily implemented by those skilled in the art, especially in light of the present disclosure.

  The environment in one embodiment is a distributed computing environment that utilizes several computer systems and components that are interconnected via communication links using one or more computer networks or direct connections. . However, it will be appreciated by those skilled in the art that such a system will operate similarly in a system having a greater or lesser number of components than shown in FIG. Accordingly, the description of the system 800 in FIG. 8 should be regarded as exemplary in nature and is not intended to limit the scope of the present disclosure.

  As described above, various embodiments can be implemented in a wide variety of operating environments, which in some instances can be used to run any of a number of applications. One or more user computers, computing devices, or processing devices that can be included. A user or client device can run any of a number of general purpose personal computers such as desktop or laptop computers running standard operating systems, as well as mobile software, and support several networking and messaging protocols. Possible cellular, wireless, and handheld devices can be included. Such a system can also include a number of workstations running any of a variety of commercially available operating systems and other known applications for purposes such as development and database management. . These devices can also include dummy terminals, thin clients, gaming systems, and other devices that can communicate over a network.

  Various aspects may also be implemented as part of at least one service or web service, such as may be part of a service-oriented architecture. Services such as web services use messages in Extensible Markup Language (XML) format and use appropriate protocols such as SOAP (derived from "Simple Object Access Protocol") Can be communicated using any suitable type of messaging, such as The processing provided or performed by such services can be described in any suitable language, such as a web service description language (WSDL). Using a language such as WSDL allows functionality such as automatic code generation on the client side in various SOAP frameworks.

  Most embodiments are known to those skilled in the art that support communication using any of a variety of commercially available protocols such as TCP / IP, OSI, FTP, UPnP, NFS, CIFS, and AppleTalk. Use at least one network. The network can be, for example, a local area network, a wide area network, a virtual private network, the Internet, an intranet, an extranet, a public switched telephone network, an infrared network, a wireless network, and any combination thereof.

  In embodiments using a web server, the web server can be any of a variety of server or middle tier applications, including HTTP servers, FTP servers, CGI servers, data servers, Java servers, and business application servers. Can be executed. The server (s) can also be written in any programming language such as Java, C, C #, or C ++, or any scripting language such as Perl, Python, or TCL, and combinations thereof. It is possible to execute a program or script in response to a request from a user device, such as by executing one or more web applications that can be implemented as one or more scripts or programs May be. The server (s) are also databases including but not limited to those commercially available from Oracle (R), Microsoft (R), Sybase (R), and IBM (R). A server may be included.

  The environment can include the various data stores and other memories or storage media described above. These can be at various locations, such as on a storage medium that is local to (and / or resides in) one or more computers, or remote from any or all of the computers across the network. In a particular set of embodiments, the information may reside in a storage area network (“SAN”) known to those skilled in the art. Similarly, any necessary files for performing functions attributable to a computer, server, or other network device may be stored locally or remotely as required. Where the system includes computerized devices, each such device can include hardware elements that can be electronically coupled via a bus, for example, at least one central processing unit. A device (CPU), at least one input device (eg, mouse, keyboard, controller, touch screen, or keypad) and at least one output device (eg, display device, printer, or speaker). Such systems also include solid-state storage, such as random access memory (“RAM”) or read-only memory (“ROM”), along with disk drives, optical storage devices, and removable media devices, memory cards, flash memory. One or more storage devices, such as devices, may be included.

  Such devices can also include a computer readable storage media reader, a communication device (eg, a modem, a network card (wireless or wired), an infrared communication device, etc.), and a working memory, as described above. A computer-readable storage medium reader that represents a remote, local, fixed and / or removable storage device and a storage medium for storing, storing, transmitting and retrieving computer-readable information temporarily and / or more permanently It can be connected to a storage medium or configured to receive it. The system and various devices also typically include a number of software applications, modules, services, or other elements located within at least one working memory device, including an operating system and application programs such as client applications or web browsers. Including. It should be understood that alternative embodiments may have numerous variations from those described above. For example, customized hardware may also be used and / or certain elements may be implemented in hardware, software (including portable software such as applets), or both. In addition, connections to other computing devices, such as network input / output devices, may be employed.

  Storage media and computer readable media for containing code or portions of code include, but are not limited to, storage and / or transmission of information such as computer readable instructions, data structures, program modules, or other data. Including any suitable media known and used in the art, including storage media and communication media, such as volatile and non-volatile, removable and non-removable media implemented in any method or technique of Can be RAM, ROM, EEPROM®, flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage device, magnetic cassette, magnetic tape, magnetic disc Storage device or other magnetic storage device or store desired information It can be used to, and any other media that can be accessed by the system device. Based on the disclosure and teachings provided herein, one of ordinary skill in the art will recognize other suitable schemes and / or methods for implementing various embodiments.

  The specification and drawings are accordingly to be regarded in an illustrative rather than a restrictive sense. However, it will be apparent that various modifications and changes may be made thereto without departing from the broader spirit and scope as set forth in the claims.

Various embodiments of the present disclosure are described in view of the following sections.
A1. A computer-implemented method for index construction for searchable data in a networked environment, comprising:
Receiving data to be indexed, the data comprising a plurality of data fields;
Determining a name associated with each data field in the plurality of data fields;
Determining a field type of a plurality of field types associated with each data field in the plurality of data fields, wherein the plurality of field types include at least one of an integer type, a literal type, or a text type. Including
Determining whether to enable one or more search options for each of the data fields, wherein the one or more search options include an option to include each data field in a search index to be generated Including at least one of an option for calculating the number of facets for each of the data fields, or an option for providing one or more values associated with the respective data fields;
Generating a search index configuration for the data based at least in part on the field type of each data field included in the data and the determination of whether to enable the one or more search options. ,
Generating a search index for the data based at least in part on the search index configuration for the data;
A computer-implemented method comprising:
A2. The data is data in the first format,
Converting the data from the first format to a second format, wherein the second format is comparable to the search index; and
Storing the data converted to the second format on one or more storage allocations;
The computer-implemented method of paragraph A1, further comprising:
A3. Converting the data from the first format to the second format,
Comparing the first format to the second format; and
Modifying at least one data field associated with the first format to correspond to at least one data field associated with the second format;
A computer-implemented method according to paragraph A2, comprising:
A4. The method executed by the computer according to item A2, wherein the second format is a search data format (SDF).
A5. Receiving data to be indexed;
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options; and
Generating a search index for the data based at least in part on the index configuration for the data;
A computer-implemented method comprising:
A6. The data is data in the first format,
Converting the data from the first format to a second format, the second format being adapted to the search index; and
Storing the data converted to the second format on one or more storage allocations;
A computer-implemented method according to paragraph A5, further comprising:
A7. Converting the data from the first format to the second format,
Comparing the first format to the second format; and
Changing at least one data tag associated with the first format to correspond to at least one data tag associated with the second format;
A computer-implemented method according to paragraph A6, comprising:
A8. The plurality of types of data fields is implemented by the computer of paragraph A5, including at least one of an integer type, a text type, a literal type, a geographic location type, a time type, a date type, or a floating point number type Method.
A9. Determining the type of the data field is
Determining that the value associated with the data field has an amount of integer characters greater than a specified integer amount threshold; and
Determining that the type of the data field is the integer type;
A computer-implemented method according to paragraph A8, comprising:
A10. Determining the type of the data field is
A value associated with the data field having an amount of alphanumeric characters greater than the specified text amount threshold, a number of different values associated with the data field exceeding the specified text difference threshold, specified Determining at least one of a percentage of different values above a text difference percentage threshold, or a length of a value above a specified text length threshold; and
Determining that the type of the data field is the text type;
A computer-implemented method according to paragraph A8, comprising:
A11. Determining the type of the data field is
A value associated with the data field that has an amount of alphabetic characters that exceeds the specified lower literal amount threshold but is less than the specified upper literal amount threshold, and the data field that is less than the specified literal difference amount threshold. Determine at least one of several associated different values, the percentage of different values that are less than a specified literal difference percentage threshold, or the length of a value that is less than a specified literal length threshold And
Determining that the type of the data field is the literal type;
A computer-implemented method according to paragraph A8, comprising:
A12. The one or more search options include an option to include the data field in the search index to be generated, an option to calculate the number of facets for the data field, or to the data field in response to an associated search query. The computer-implemented method of paragraph A5, comprising at least one of an option that provides an associated value.
A13. Determining the one or more search options to be enabled comprises determining to enable the option to include the data field in the search index to be generated, the determination comprising: At least one of receiving a signal included in the data field indicating that the data field should be included in the search index, or determining that the type of the data field is a literal type A computer-implemented method of paragraph A12, based at least in part.
A14. The determining of the one or more search options to be enabled comprises determining to enable the option of calculating the facet number for the data field, the determination being associated with the data field. The computer-implemented method of paragraph A12, wherein the amount for the plurality of distributions of values specified is based at least in part on determining that the amount is less than a specified facet count upper threshold.
A15. Determining the one or more search options to be enabled determines to enable the option to provide the value associated with the data field in response to the associated search query. The determination includes receiving a signal included in the data field, indicating that the value associated with the data field is provided, or the length of the value associated with the data field is The computer-implemented method of paragraph A12, based at least in part on determining that the return value length is less than a specified return value length threshold.
A16. The computer-implemented method of paragraph A5, further comprising providing at least one of the data, the index configuration, or the index that is searchable by one or more search queries.
A1. The computer-implemented method of paragraph A5, further comprising changing the index configuration based at least in part on input initiated by one or more users.
A18. At least one communication transceiver;
One or more storage allocations;
At least one processor, and
A memory device containing instructions and
When the instructions are executed by the at least one processor, the system includes:
Receiving data to be indexed via the at least one communication transceiver;
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options; and
A system that generates a search index for the data based at least in part on the index configuration for the data.
A19. The data is data in a first format, and the instructions are further passed to the system,
Converting the data from the first format to a second format, the second format being adapted to the search index; and
The system according to A18, wherein the data converted into the second format is stored on the one or more storage allocations.
A20. The instructions cause the system to compare the first format with the second format and change at least one data field associated with the first format to the second format. The system of clause A19, wherein the data is converted from the first format to the second format based on corresponding to at least one associated data field.
A21. A non-transitory computer readable storage medium containing instructions for identifying an element, the instructions being executed by a processor of the computing system,
Receive data to be indexed,
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options; and
Generating a search index for the data based at least in part on the index configuration for the data;
A non-transitory computer-readable storage medium.
A22. The non-transitory computer readable item of paragraph A21, wherein the plurality of types of data fields include at least one of an integer type, a text type, a literal type, a geographic location type, a time type, a date type, or a floating point number type. Storage medium.
A23. The instruction causes the computing system to have a value associated with the data field having an amount of alphabetic characters that exceeds the specified lower literal amount threshold but less than the specified upper literal amount threshold, the specified literal. Several different values associated with the data field that are less than the difference threshold, the percentage of different values that are less than the specified literal difference percentage threshold, or the length of the value that is less than the specified literal length threshold The non-transitory computer readable storage medium of paragraph A22, wherein the non-transitory computer-readable storage medium causes the type of the data field to be determined to be the literal type based on determining at least one of:
A24. The one or more search options include the option to include the data field in the search index to be generated, the option to calculate the number of facets for the data field, or the data field in response to an associated search query. The non-transitory computer readable storage medium of paragraph A21, comprising at least one of an option that provides a value associated with.
A25. The determining of the one or more search options to be enabled comprises determining to enable the option of calculating the facet number for the data field, the determination being associated with the data field. A non-transitory of paragraph A24, wherein the amount for the at least one value specified is at least partially based on determining that the amount is greater than the specified facet count lower threshold and less than the specified facet count upper threshold Computer-readable storage medium.
B1. A computer-implemented method for dynamic search partitioning comprising:
Monitoring at least one of the amount of stored data or the rate at which data is being manipulated on a first partition provided by a network service, the first partition comprising the network service Included in the storage allocation provided by
Detecting that said at least one of said amount or said ratio exceeds each of a specified amount threshold or a specified ratio threshold;
Responsive to the detecting, performing at least one of increasing the size of the first partition, or adding at least a second partition to the storage allocation, the increasing or The additional at least one is based at least in part on the amount of stored data or the rate at which the data is being manipulated;
Directing network traffic associated with the storage allocation to the cache provided by the network service during the increase or the additional at least one; and
Directing the network traffic to the storage allocation when completing the at least one of the increase or the additional; and
A computer-implemented method comprising:
B2. Monitoring a search index for the storage allocation;
Detecting that the size of the search index exceeds a specified index size threshold; and
Updating the search index for the storage allocation to reflect the increase or the additional at least one of the storage allocation;
The computer-implemented method of paragraph B1, further comprising:
B3. The increase to the size of the first partition is performed when the size of the first partition is less than a maximum partition size threshold, and at least the addition of the second partition is The computer implemented method of paragraph B1, executed when the size of the first partition is at the maximum partition size threshold.
B4. Monitoring data usage on storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Changing at least one of the size of the at least one partition or the number of several partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with the size or the number of the at least one of the changing, and
Directing the network traffic to the portion of the storage allocation associated with the change when the change is complete;
A computer-implemented method comprising:
B5. Detecting that the size of the search index for the storage allocation exceeds a specified index size threshold; and
Updating the search index for the storage allocation based on changing the size of the at least one partition or the at least one of the number of partitions included in the storage allocation. When,
A computer-implemented method according to paragraph B4, comprising:
B6. The updating the search index reflects the changing the size of the at least one partition or the at least one of the number of partitions included in the storage allocation, Reconstructing the search index for the storage allocation, the computer-implemented method of paragraph B5.
B7. The data usage is performed by the computer of paragraph B4, including at least one of an amount of data stored on the storage allocation, or a rate at which data is being manipulated on the storage allocation. Method.
B8. The specified threshold includes at least one of a specified amount threshold or a specified ratio threshold, and the amount of stored data exceeds the specified amount threshold, or data The computer-implemented method of paragraph B7, wherein the data usage exceeds the specified threshold when at least one of the ratio being manipulated exceeds the specified ratio threshold.
B9. The computer-implemented method of paragraph B8, wherein the specified threshold is calculated based at least in part on information relating to historical data usage.
B10. Determining that the amount of network traffic directed to the storage allocation is above a specified traffic threshold; and
Changing the storage allocation based on the amount of network traffic;
The computer-implemented method of paragraph B4, further comprising:
B11. The computer implemented method of paragraph B10, wherein the network traffic includes search query traffic for searching data stored on the storage allocation.
B12. Changing the storage allocation based on the amount of network traffic includes changing the size of the at least one partition, changing the number of partitions, or included in the number of partitions The computer-implemented method of paragraph B10, comprising replacing at least one partition with at least one partition having a different specification.
B13. The computer implemented method of paragraph B12, wherein the different specifications include at least one of different CPU power, different RAM capacity, different hard disk space capacity, or different bandwidth capacity.
B14. Changing the size of the at least one partition, or the at least one of the number of the several partitions, changes the size of the at least one partition, or the number of the several partitions, the at least one. And increasing the size of the at least one partition is performed when the size of the at least one partition is less than a maximum partition size threshold, and the number of the partitions. The computer implemented method of paragraph B4, wherein the increasing the number is performed when the size of the at least one partition is at a maximum partition size threshold.
B15. Changing the size of the at least one partition, or the at least one of the number of the several partitions, is changing the size of the at least one partition or the number of the several partitions. Reducing the number of the some of the partitions is performed when the number of the partitions is greater than 1, and reducing the size of the at least one partition. Is executed by the computer of paragraph B4, which is executed when the number of partitions is one.
B16. Determining the CPU usage of the storage allocation, and changing the at least one of the size or the number is the data usage on the storage allocation, or the determined The computer-implemented method of paragraph B4, wherein the method is based on at least one of the CPU usage of the storage allocation.
B17. The computer-implemented method of paragraph B4, further comprising changing the configuration of the storage allocation based on at least one of a configuration associated with the data usage or an input initiated by a user. .
B18. Executed by the computer of paragraph B4, further comprising: determining when to perform the change to the size or the number of the at least one based on resources available for the storage allocation. Method.
B19. A storage allocation having several partitions, including at least one partition;
At least one processor, and
A memory device containing instructions and
When the instructions are executed by the at least one processor, the system includes:
Monitor the data usage on the above storage allocation,
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Change the size of the at least one partition, or the number of the several partitions included in the storage allocation,
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with the size or number of the at least one of the changing; and
A system that directs the network traffic to the portion of the storage allocation associated with the change when the change is complete.
B20. Changing the network traffic directed away from the portion of the storage allocation and the size or the number of the at least one while changing the size or the number of the at least one The system of paragraph B19, further comprising: at least one load balancer configured to facilitate the network traffic directed to the portion of the storage allocation when completed.
B21. The system of paragraph B20, wherein the at least one load balancer is configured to direct the network traffic across the number of partitions included in the storage allocation.
B22. Facilitating the monitoring of the data usage on the storage allocation and determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold The system of paragraph B19, further comprising at least one monitoring module configured to:
B23. A non-transitory computer readable storage medium containing instructions for identifying an element, the instructions being executed by a processor of the computing system,
Monitor data usage on storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Change at least one of the size of the at least one partition or the number of the several partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with the size or number of the at least one of the changing; and
A non-transitory computer readable storage medium that directs the network traffic to the portion of the storage allocation associated with the change when the change is complete.
B24. The instructions further detect in the computing system that a size of a search index for the storage allocation exceeds a size threshold for a specified index, and the size of the at least one partition, or the storage allocation. The non-transitory computer readable storage medium of paragraph B23, wherein the search index for the storage allocation is updated based on the change of the at least one of the several partitions included in the storage.
B25. Updating the search index to reflect the size of the at least one partition or the change of the at least one of the number of the partitions included in the storage allocation. The non-transitory computer readable storage medium of paragraph B24, comprising reconstructing the search index for storage allocation.

Various embodiments of the present disclosure are described in view of the following sections.
A1. A computer-implemented method for index construction for searchable data in a networked environment, comprising:
Receiving data to be indexed, the data comprising a plurality of data fields;
Determining a name associated with each data field in the plurality of data fields;
Determining a field type of a plurality of field types associated with each data field in the plurality of data fields, wherein the plurality of field types include at least one of an integer type, a literal type, or a text type. Including
Determining whether to enable one or more search options for each of the data fields, wherein the one or more search options include an option to include each data field in a search index to be generated Including at least one of an option for calculating the number of facets for each of the data fields, or an option for providing one or more values associated with the respective data fields;
Generating a search index configuration for the data based at least in part on the field type of each data field included in the data and the determination of whether to enable the one or more search options. ,
Generating a search index for the data based at least in part on the search index configuration for the data;
A computer-implemented method comprising:
A2. The data is data in the first format,
Converting the data from the first format to a second format, wherein the second format is comparable to the search index, and on one or more storage allocations, Storing the data converted to the second format;
The computer-implemented method of paragraph A1, further comprising:
A3. Converting the data from the first format to the second format,
Comparing the first format with the second format, and changing at least one data field associated with the first format to at least one data associated with the second format Corresponding to the field,
A computer-implemented method according to paragraph A2, comprising:
A4. The method executed by the computer according to item A2, wherein the second format is a search data format (SDF).
A5. Receiving data to be indexed;
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options, and based at least in part on the index structure for the data, Generating a search index on the data;
A computer-implemented method comprising:
A6. The data is data in the first format,
Converting the data from the first format to a second format, wherein the second format is compatible with the search index, and on one or more storage allocations, Storing the data converted to the second format;
A computer-implemented method according to paragraph A5, further comprising:
A7. Converting the data from the first format to the second format,
Comparing the first format with the second format, and changing at least one data tag associated with the first format to at least one data associated with the second format Corresponding to the tag,
A computer-implemented method according to paragraph A6, comprising:
A8. The plurality of types of data fields is implemented by the computer of paragraph A5, including at least one of an integer type, a text type, a literal type, a geographic location type, a time type, a date type, or a floating point number type Method.
A9. Determining the type of the data field is
Determining that the value associated with the data field has an amount of integer characters greater than a specified integer amount threshold; and determining that the type of the data field is the integer type. And
A computer-implemented method according to paragraph A8, comprising:
A10. Determining the type of the data field is
A value associated with the data field having an amount of alphanumeric characters greater than the specified text amount threshold, a number of different values associated with the data field exceeding the specified text difference threshold, specified Determining at least one of a percentage of different values above a text difference percentage threshold, or a length of a value above a specified text length threshold, and the type of the data field as the text type To determine that
A computer-implemented method according to paragraph A8, comprising:
A11. Determining the type of the data field is
A value associated with the data field that has an amount of alphabetic characters that exceeds the specified lower literal amount threshold but is less than the specified upper literal amount threshold, and the data field that is less than the specified literal difference amount threshold. Determine at least one of several associated different values, the percentage of different values that are less than a specified literal difference percentage threshold, or the length of a value that is less than a specified literal length threshold And determining that the type of the data field is the literal type;
A computer-implemented method according to paragraph A8, comprising:
A12. The one or more search options include an option to include the data field in the search index to be generated, an option to calculate the number of facets for the data field, or to the data field in response to an associated search query. The computer-implemented method of paragraph A5, comprising at least one of an option that provides an associated value.
A13. Determining the one or more search options to be enabled comprises determining to enable the option to include the data field in the search index to be generated, the determination comprising: At least one of receiving a signal included in the data field indicating that the data field should be included in the search index, or determining that the type of the data field is a literal type A computer-implemented method of paragraph A12, based at least in part.
A14. The determining of the one or more search options to be enabled comprises determining to enable the option of calculating the facet number for the data field, the determination being associated with the data field. The computer-implemented method of paragraph A12, wherein the amount for the plurality of distributions of values specified is based at least in part on determining that the amount is less than a specified facet count upper threshold.
A15. Determining the one or more search options to be enabled determines to enable the option to provide the value associated with the data field in response to the associated search query. The determination includes receiving a signal included in the data field, indicating that the value associated with the data field is provided, or the length of the value associated with the data field is The computer-implemented method of paragraph A12, based at least in part on determining that the return value length is less than a specified return value length threshold.
A16. The computer-implemented method of paragraph A5, further comprising providing at least one of the data, the index configuration, or the index that is searchable by one or more search queries.
A1. The computer-implemented method of paragraph A5, further comprising changing the index configuration based at least in part on input initiated by one or more users.
A18. At least one communication transceiver;
One or more storage allocations;
A system comprising: at least one processor; and a memory device including instructions, wherein when the instructions are executed by the at least one processor, the system includes:
Receiving data to be indexed via the at least one communication transceiver;
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options, and for the data based at least in part on the index structure for the data A system that generates a search index.
A19. The data is data in a first format, and the instructions are further passed to the system,
Converting the data from the first format to a second format, the second format being adapted to the search index, and the second format on the one or more storage allocations The system according to A18, wherein the data converted into the data is stored.
A20. The instructions cause the system to compare the first format with the second format and change at least one data field associated with the first format to the second format. The system of clause A19, wherein the data is converted from the first format to the second format based on corresponding to at least one associated data field.
A21. A non-transitory computer readable storage medium containing instructions for identifying an element, the instructions being executed by a processor of the computing system,
Receive data to be indexed,
Determining a type of a data field associated with the data, wherein the type of the data field is determined from a plurality of types of data fields;
Determining one or more search options to be enabled for the data field associated with the data;
Generating an index structure for the data based at least in part on the type of the data field and the one or more search options, and for the data based at least in part on the index structure for the data Generate search index,
A non-transitory computer-readable storage medium.
A22. The non-transitory computer readable item of paragraph A21, wherein the plurality of types of data fields include at least one of an integer type, a text type, a literal type, a geographic location type, a time type, a date type, or a floating point number type. Storage medium.
A23. The instruction causes the computing system to have a value associated with the data field having an amount of alphabetic characters that exceeds the specified lower literal amount threshold but less than the specified upper literal amount threshold, the specified literal. Several different values associated with the data field that are less than the difference threshold, the percentage of different values that are less than the specified literal difference percentage threshold, or the length of the value that is less than the specified literal length threshold The non-transitory computer readable storage medium of paragraph A22, wherein the non-transitory computer-readable storage medium causes the type of the data field to be determined to be the literal type based on determining at least one of:
A24. The one or more search options include the option to include the data field in the search index to be generated, the option to calculate the number of facets for the data field, or the data field in response to an associated search query. The non-transitory computer readable storage medium of paragraph A21, comprising at least one of an option that provides a value associated with.
A25. The determining of the one or more search options to be enabled comprises determining to enable the option of calculating the facet number for the data field, the determination being associated with the data field. A non-transitory of paragraph A24, wherein the amount for the at least one value specified is at least partially based on determining that the amount is greater than the specified facet count lower threshold and less than the specified facet count upper threshold Computer-readable storage medium.
B1. A computer-implemented method for dynamic search partitioning comprising:
Monitoring at least one of the amount of stored data or the rate at which data is being manipulated on a first partition provided by a network service, the first partition comprising the network service Included in the storage allocation provided by
Detecting that said at least one of said amount or said ratio exceeds each of a specified amount threshold or a specified ratio threshold;
Responsive to the detecting, performing at least one of increasing the size of the first partition, or adding at least a second partition to the storage allocation, the increasing or The additional at least one is based at least in part on the amount of stored data or the rate at which the data is being manipulated;
Directing network traffic associated with the storage allocation to the cache provided by the network service during the increase or the additional at least one, and the increase or the additional at least one Directing the network traffic to the storage allocation when execution is complete;
A computer-implemented method comprising:
B2. Monitoring a search index for the storage allocation;
Detecting that the size of the search index exceeds a specified index size threshold, and reflecting the search index for the storage allocation to the increase or the additional at least one of the storage allocation To update to
The computer-implemented method of paragraph B1, further comprising:
B3. The increase to the size of the first partition is performed when the size of the first partition is less than a maximum partition size threshold, and at least the addition of the second partition is The computer implemented method of paragraph B1, executed when the size of the first partition is at the maximum partition size threshold.
B4. Monitoring data usage on storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Changing at least one of the size of the at least one partition or the number of several partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a part of the storage allocation associated with the size or the number of the at least one of the changing, and the changing Directing the network traffic to the portion of the storage allocation associated with the modification when
A computer-implemented method comprising:
B5. Detecting that the size of the search index for the storage allocation exceeds a specified index size threshold; and the size of the at least one partition, or the number of partitions included in the storage allocation. Updating the search index for the storage allocation based on changing the at least one of the numbers;
A computer-implemented method according to paragraph B4, comprising:
B6. The updating the search index reflects the changing the size of the at least one partition or the at least one of the number of partitions included in the storage allocation, Reconstructing the search index for the storage allocation, the computer-implemented method of paragraph B5.
B7. The data usage is performed by the computer of paragraph B4, including at least one of an amount of data stored on the storage allocation, or a rate at which data is being manipulated on the storage allocation. Method.
B8. The specified threshold includes at least one of a specified amount threshold or a specified ratio threshold, and the amount of stored data exceeds the specified amount threshold, or data The computer-implemented method of paragraph B7, wherein the data usage exceeds the specified threshold when at least one of the ratio being manipulated exceeds the specified ratio threshold.
B9. The computer-implemented method of paragraph B8, wherein the specified threshold is calculated based at least in part on information relating to historical data usage.
B10. Determining that the amount of network traffic directed to the storage allocation exceeds a specified traffic threshold; and changing the storage allocation based on the amount of network traffic;
The computer-implemented method of paragraph B4, further comprising:
B11. The computer implemented method of paragraph B10, wherein the network traffic includes search query traffic for searching data stored on the storage allocation.
B12. Changing the storage allocation based on the amount of network traffic includes changing the size of the at least one partition, changing the number of partitions, or included in the number of partitions The computer-implemented method of paragraph B10, comprising replacing at least one partition with at least one partition having a different specification.
B13. The computer implemented method of paragraph B12, wherein the different specifications include at least one of different CPU power, different RAM capacity, different hard disk space capacity, or different bandwidth capacity.
B14. Changing the size of the at least one partition, or the at least one of the number of the several partitions, changes the size of the at least one partition, or the number of the several partitions, the at least one. And increasing the size of the at least one partition is performed when the size of the at least one partition is less than a maximum partition size threshold, and the number of the partitions. The computer implemented method of paragraph B4, wherein the increasing the number is performed when the size of the at least one partition is at a maximum partition size threshold.
B15. Changing the size of the at least one partition, or the at least one of the number of the several partitions, is changing the size of the at least one partition or the number of the several partitions. Reducing the number of the some of the partitions is performed when the number of the partitions is greater than 1, and reducing the size of the at least one partition. Is executed by the computer of paragraph B4, which is executed when the number of partitions is one.
B16. Determining the CPU usage of the storage allocation, and changing the at least one of the size or the number is the data usage on the storage allocation, or the determined The computer-implemented method of paragraph B4, wherein the method is based on at least one of the CPU usage of the storage allocation.
B17. The computer-implemented method of paragraph B4, further comprising changing the configuration of the storage allocation based on at least one of a configuration associated with the data usage or an input initiated by a user. .
B18. Executed by the computer of paragraph B4, further comprising: determining when to perform the change to the size or the number of the at least one based on resources available for the storage allocation. Method.
B19. A storage allocation having several partitions, including at least one partition;
A system comprising: at least one processor; and a memory device including instructions, wherein when the instructions are executed by the at least one processor, the system includes:
Monitor the data usage on the above storage allocation,
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Change the size of the at least one partition, or the number of the several partitions included in the storage allocation,
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with the size or number of the at least one of the changing and completing the changing And directing the network traffic to the portion of the storage allocation associated with the changing.
B20. Changing the network traffic directed away from the portion of the storage allocation and the size or the number of the at least one while changing the size or the number of the at least one The system of paragraph B19, further comprising: at least one load balancer configured to facilitate the network traffic directed to the portion of the storage allocation when completed.
B21. The system of paragraph B20, wherein the at least one load balancer is configured to direct the network traffic across the number of partitions included in the storage allocation.
B22. Facilitating the monitoring of the data usage on the storage allocation and determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold The system of paragraph B19, further comprising at least one monitoring module configured to:
B23. A non-transitory computer readable storage medium containing instructions for identifying an element, the instructions being executed by a processor of the computing system,
Monitor data usage on storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Change at least one of the size of the at least one partition or the number of the several partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with the size or number of the at least one of the changing and completing the changing A non-transitory computer readable storage medium that directs the network traffic to the portion of the storage allocation associated with the modification.
B24. The instructions further detect in the computing system that a size of a search index for the storage allocation exceeds a size threshold for a specified index, and the size of the at least one partition, or the storage allocation. The non-transitory computer readable storage medium of paragraph B23, wherein the search index for the storage allocation is updated based on the change of the at least one of the several partitions included in the storage.
B25. Updating the search index to reflect the size of the at least one partition or the change of the at least one of the number of the partitions included in the storage allocation. The non-transitory computer readable storage medium of paragraph B24, comprising reconstructing the search index for storage allocation.
Hereinafter, the invention described in the scope of claims of the present application will be appended.
[1] monitoring data usage for storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Changing at least one of the size of the at least one partition or the number of the partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with changing at least one of the size or number;
Directing the network traffic to the portion of the storage allocation associated with the change when the change is complete;
A computer-implemented method comprising:
[2] detecting that the size of the search index for the storage allocation exceeds a specified index size threshold; and
Updating the search index for the storage allocation based on changing at least one of the size of the at least one partition or the number of several partitions included in the storage allocation;
A computer-implemented method according to [1], comprising:
[3] The updating of the search index reflects the change of the size of the at least one partition or the number of partitions included in the storage allocation. The computer-implemented method of [2], comprising rebuilding the search index for the storage allocation.
[4] The data usage includes at least one of an amount of data stored on the storage allocation or a rate at which data is operated on the storage allocation. A method performed by a computer.
[5] The specified threshold includes at least one of a specified quantity threshold or a specified ratio threshold, and the amount of stored data exceeds the specified quantity threshold, or The computer implemented in [4], wherein the data usage exceeds the specified threshold when at least one of the ratios at which data is manipulated exceeds the specified ratio threshold occurs. Method.
[6] The computer-implemented method according to [5], wherein the specified threshold value is calculated based at least in part on information relating to historical data usage.
[7] Determining that an amount of network traffic directed to the storage allocation exceeds a specified traffic threshold; and changing the storage allocation based on the amount of network traffic;
The method executed by the computer according to [1], further comprising:
[8] The computer-implemented method of [7], wherein the network traffic includes search query traffic for searching data stored on the storage allocation.
[9] Changing the storage allocation based on the amount of network traffic, changing the size of the at least one partition, changing the number of the several partitions, or how many The computer-implemented method of [7], comprising at least one of replacing at least one partition included in the partition with at least one partition having a different specification.
[10] The computer-implemented method of [9], wherein the different specifications include at least one of different CPU power, different RAM capacity, different hard disk space capacity, or different bandwidth capacity. .
[11] Changing at least one of the size of the at least one partition or the number of the several partitions is at least one of the size of the at least one partition or the number of the several partitions Increasing the size of the at least one partition is performed when the size of the at least one partition is less than a maximum partition size threshold, and the number of the some partitions is The computer-implemented method of [1], wherein the increasing is performed when the size of the at least one partition is at a maximum partition size threshold.
[12] Changing at least one of the size of the at least one partition or the number of the several partitions is at least one of the size of the at least one partition or the number of the several partitions Reducing the number of partitions is performed when the number of the number of partitions is greater than 1, and reducing the size of the at least one partition, The method executed by the computer according to [1], which is executed when the number of some partitions is one.
[13] The method further comprises determining a CPU usage rate of the storage allocation, and changing at least one of the size or the number is the data usage related to the storage allocation or the determined The computer-implemented method of [1], based on at least one of the CPU usage rates of the storage allocation.
[14] The computer according to [1], further comprising changing the configuration of the storage allocation based on at least one of a configuration associated with the data usage or an input initiated by a user. The method performed by.
[15] The computer according to [1], further comprising determining when to change the size or the number at least one based on resources available for the storage allocation The method that is performed.

Claims (15)

Monitoring data usage related to storage allocation in a networked environment, the storage allocation having several partitions including at least one partition;
Determining whether the data usage on the at least one partition included in the storage allocation exceeds a specified threshold;
Changing at least one of the size of the at least one partition or the number of the partitions included in the storage allocation;
Directing network traffic associated with the storage allocation away from a portion of the storage allocation associated with changing at least one of the size or number;
Directing the network traffic to the portion of the storage allocation associated with the change when the change is complete. Detecting that the size of the search index for the storage allocation exceeds a specified index size threshold; and the size of the at least one partition or the number of some partitions included in the storage allocation The computer-implemented method of claim 1, comprising updating the search index for the storage allocation based on changing at least one of the following.   The storage to reflect the updating of the search index reflects the size of the at least one partition, or the at least one of the number of partitions included in the storage allocation. The computer-implemented method of claim 2, comprising reconstructing the search index for area allocation.   The computer-implemented method of claim 1, wherein the data usage includes at least one of an amount of data stored on the storage allocation or a rate at which data is being manipulated on the storage allocation. How to be.   The specified threshold includes at least one of a specified quantity threshold or a specified ratio threshold, and the amount of stored data exceeds the specified quantity threshold, or the data is manipulated The computer-implemented method of claim 4, wherein the data usage exceeds the specified threshold when at least one of the ratio being exceeded exceeds the specified ratio threshold.   The computer-implemented method of claim 5, wherein the specified threshold is calculated based at least in part on information relating to historical data usage. Further comprising: determining that an amount of network traffic directed to the storage allocation exceeds a specified traffic threshold; and changing the storage allocation based on the amount of network traffic. A method executed by the computer according to Item 1.   8. The computer-implemented method of claim 7, wherein the network traffic includes search query traffic for searching data stored on the storage allocation.   Changing the storage allocation based on the amount of network traffic, changing the size of the at least one partition, changing the number of the some partitions, or the some partitions The computer-implemented method of claim 7, comprising at least one of replacing at least one partition comprised in at least one partition having a different specification.   The computer-implemented method of claim 9, wherein the different specifications include at least one of different CPU power, different RAM capacity, different hard disk space capacity, or different bandwidth capacity.   Changing the size of the at least one partition, or at least one of the number of the several partitions, increases the size of the at least one partition, or at least one of the number of the several partitions And increasing the size of the at least one partition is performed when the size of the at least one partition is less than a maximum partition size threshold, and increasing the number of the some partitions The computer-implemented method of claim 1, wherein is performed when the size of the at least one partition is at a maximum partition size threshold.   Changing at least one of the size of the at least one partition, or the number of the several partitions, reduces the size of the at least one partition, or at least one of the number of the several partitions Reducing the number of partitions is performed when the number of the number of partitions is greater than 1, and reducing the size of the at least one partition The computer-implemented method of claim 1, wherein the method is performed when the number of partitions is one.   Determining the CPU usage of the storage allocation, wherein changing at least one of the size or the number is the data usage related to the storage allocation, or the determined storage The computer-implemented method of claim 1, wherein the method is based on at least one of CPU usage of area allocation.   The computer-implemented method of claim 1, further comprising changing the configuration of the storage allocation based on at least one of a configuration associated with the data usage or a user initiated input. Method.   The computer-implemented method of claim 1, further comprising determining when to change the size or the number at least one based on resources available for the storage allocation. Method.

Images