Abstract: A production cluster executes a workload, such that jobs associated with the executed workload are allocated, according to a first configuration. A cluster monitor extracts production cluster information from the production cluster, monitors configuration information during execution of the workload, and transmits each to a cluster tuner. The cluster tuner receives the information and determines a first recommended configuration for the production cluster. The cluster tuner causes the test cluster to execute a simulated workload according to the first recommended configuration. In response to determining that the first recommended configuration results in a decrease in resource consumption, the cluster tuner causes the production cluster to operate according to the first recommended configuration.

Abstract: The disclosed systems and methods may receive a data record from either a legacy data source or a modern data source and determine whether the record satisfies a first set of validation rules. When the record fails to satisfy the first set of rules, reject the record for storage in a data store. When the record satisfies the first set of rules, determine whether the record satisfies a second set of validation rules. When the record satisfies the second set of rules, store the record in the data store with an indicator that the record satisfies the all rules. When the record fails to satisfy the second set of rules, if the source was a modern data source reject the record, and if the source was a legacy data source store the record in the data store with an indicator that it fails to satisfy the second set of rules.

Abstract: This disclosure is directed to systems and methods for selecting or eliminating candidate targeted communications. A method may include receiving candidate identifiers and traits associated with the candidate identifiers. A method may further include generating a candidate index including one or more dimensions associated with candidate traits. A method may further include intersecting the dimensions to determine if one or more candidates appear in dimensions associated with the desired candidate traits. A method may further include generating a result set based on the results of the intersecting computation. A method may further include selecting or eliminating candidates based on the results of the intersecting computation.

Abstract: A method comprises: generating, at a first computing device, a first set of gradient values associated with a data block processed by nodes of a machine learning model, the first set of gradient values being in a first data format; determining a first shared factor from the first set of gradient values, the first shared factor being in a second data format of a lower a precision than that of the first data format; and scaling the first set of gradient values with the first shared factor, to obtain a second set of gradient values having the second data format. In addition, the method comprises sending the second set of gradient values and the first shared factor to a second computing device; and, in response to receiving a third set of gradient values and a second shared factor from the second computing device, adjusting parameters of the machine learning model.

Abstract: A method for identifying a component part includes receiving a digital image of an object and textual information about the object and accessing images of component parts and textual information about the component parts. The method further includes applying the digital image to a first classifier trained on the images of the component parts to classify the object as a first of the component parts and applying the textual information about the object to a second classifier trained on the textual information about the component parts to recognize the textual information as information about the first of the component parts or a second of the component parts. The method further includes identifying the object as a component part that is the first of the component parts or the second of the component parts and accessing a data record with information about the component part.

Abstract: An approach to exchanging information between data storage devices (DSDs) within a secure data center and an external fleet health manager (FHM) application includes querying one or more DSDs for data to be analyzed, including providing a unique query identifier, whereby a particular DSD responsively provides (i) a device identifier identifying itself, (ii) a random key code for authentication and integrity purposes, (iii) the data to be analyzed, and (iv) the query identifier for the FHM application to verify. The FHM application can then digitally sign a corrective action payload, using the key code from the particular DSD, including the query identifier and the device identifier and a recommended corrective action, and transmit the signed corrective action payload to the data center for application to the particular DSD, whereby the DSD can execute pre-defined fundamental repair action operation(s) corresponding to the corrective action for in-situ repair.

Abstract: The disclosure herein describes writing data to a log-structured merge (LSM) tree file system on an object storage platform. Write data instructions indicating data for writing to the LSM tree file system are received. Based on the received instructions, the data is written to the first data cache. Based on an instruction to transfer data in the live data cache to the LSM tree file system, the first data cache is converted to a stable cache. A second data cache configured as a live data cache is then generated based on cloning the first data cache. The data in the first data cache is then written to the LSM tree file system. Use of a stable cache and a cloned live data cache enables parallel writing data to the file system by the stable cache and handling write data instructions by the live data cache.

Abstract: A method for clustering data elements stored in a data storage system includes reading data elements from the data storage system. Clusters of data elements are formed with each data element being a member of at least one cluster. At least one data element is associated with two or more clusters. Membership of the data element belonging to respective ones of the two or more clusters is represented by a measure of ambiguity. Information is stored in the data storage system to represent the formed clusters.

Abstract: Techniques describes herein include using software tools and feature vector comparisons to analyze and recommend images, text content, and other relevant media content from a content repository. A digital content recommendation tool may communicate with a number of back-end services and content repositories to analyze text and/or visual input, extract keywords or topics from the input, classify and tag the input content, and store the classified/tagged content in one or more content repositories. Input text and/or input images may be converted into vectors within a multi-dimensional vector space, and compared to a plurality of feature vectors within a vector space to identify relevant content items within a content repository. Such comparisons may include exhaustive deep searches and/or efficient tag-based filtered searches. Relevant content items (e.g., images, audio and/or video clips, links to related articles, etc.

Abstract: A computer-implemented method for database management is provided. The method comprises: receiving, from a client device , first data to be stored in a database system that comprises first data storage configured to store a data table and a deletion history table; storing the first data in second data storage that is external to the database system and that is in communication with the database system via a network; obtaining a link that enables access, via the network, to the first data stored in the second data storage; storing the link in the data table; and performing a deletion operation of the first data, in response to a request from the client device to delete the first data from the database system, wherein the deletion operation comprises: deleting the link from the data table without deleting the first data from the second data storage; and storing the link in the deletion history table with a timestamp corresponding to a point in time when the link is deleted from the data table.

Abstract: A method and apparatus for mining a competition relationship between POIs. An embodiment of the method includes: acquiring a graphlet mining result obtained by mining map retrieval data of users which encompasses attribute information of retrieved target POIs, the graphlet mining result encompassing occurrence frequencies of respective preset situations, and a preset situation comprising: conforming to attribute information of POIs represented by a corresponding preset graphlet and a preset association relationship between attribute information of at least two POIs; for a first and second POI, determining an occurrence frequency of a preset situation corresponding to a preset graphlet where attribute information of the first and second POI co-occur, and generating a relationship feature of the first and second POI; and inputting the relationship feature into a pre-trained relationship prediction model to obtain a competition relationship prediction result of the first POI and the second POI.

Abstract: Extending access to a data model in a data analytics computer data processing system includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Abstract: A database contains a corpus of incident reports, a machine learning (ML) model trained to calculate paragraph vectors of the incident reports, and a look-up set table that contains a list of paragraph vectors respectively associated with sets of the incident reports. A plurality of ML worker nodes each store the look-up set table and are configured to execute the ML model. An update thread is configured to: determine that the look-up set table has expired; update the look-up set table by: (i) adding a first set of incident reports received since a most recent update of the look-up set table, and (ii) removing a second set of incident reports containing timestamps that are no longer within a sliding time window; store, in the database, the look-up set table as updated; and transmit, to the ML worker nodes, respective indications that the look-up set table has been updated.

Abstract: One or more computing devices, systems, and/or methods for generating and providing recommendations of products are provided. For example, content is extracted from a message sent to a user. The content is evaluated to identify a product identifier corresponding to a product title of a product. If the product identifier is a truncated version of the product title, then a database of product titles and frequencies of occurrence of the product titles is used to complete the product title. A model is used to infer a product category for the product title. Matching scores are assigned to products within a product category based upon weighted attributes. A recommendation is provided to the user for a product having a matching score greater than a matching threshold.

Abstract: Techniques for creating a user network based on user interest in a product are described. For example, a first search query is received from a first client device. The first client device is associated with a first user. A second search query is received from a second client device. The second client device is associated with a second user. The first search query is matched to a product. The second search query is matched to the product. A user network corresponding to the product is created. The first user is added to the user network based on the matching of the first search query to the product. The second user is added to the user network based on the matching of the second search query to the product.

Abstract: A system for playback of messages. Context appropriate messages for an environment may be played back. Messages may be user behavior interactive and subject to user behavior initiated message playback conditions. User generated environment events may be automatically analyzed and user behavior interactive messages may be automatically coordinated. An automated themed message playback apparatus may have a self-contained housing within which a stored themed message, an in situ user generated environment event sensor, and an automated themed message playback device are housed. User generated environment events may be automatically sensed in situ.

Abstract: The present disclosure discloses a control device of data storage system, including a host interface, a peer interface, a storage unit interface, a processor and a local data management module. The host interface is connected and communicated with a storage server for data interaction with the storage server. The peer interface is configured for data communication connection with a storage unit of an adjacent control device in the data storage system. The storage unit interface is configured to connect a storage unit. The local data management module is configured for local data management of the data in the storage unit according to the data management instruction via the processor. The host interface is configured to send result data of local data management to the storage server.

Abstract: According to another aspect, a computer system is provided. The computer system includes a memory; at least one processor in data communication with the memory; and a reporting component executable by the at least processor and configured to execute a user interface component configured to receive schedule information, the schedule information including a company-wide schedule specifying an expense report generation date and at least one reminder; store the schedule information in a data store; send the at least one reminder to a plurality of users prior to the expense report generation date; and generate, on the expense report generation date, a plurality of expense reports respectively corresponding to the plurality of users.

Abstract: An intelligent hotspot scattering method includes learning request quantity curves of a plurality of URLs based on an artificial intelligence learning model and performing request quantity prediction on the plurality of URLs, determining a first URL from the plurality of URLs, determining a second URL from the plurality of URLs, and performing a hotspot scattering operation on the URLs. A predicted request quantity of the first URL is greater than or equal to a first predetermined request quantity threshold corresponding to the first URL. A request quantity of the second URL is not predictable and an actual request quantity of the second URL is greater than or equal to a second predetermined request quantity threshold corresponding to the second URL.

Abstract: A system and methods for efficiently and consistently creating and delivering content tailored to a user's specific needs and channel of distribution. The system generates coherent, precise, and logical content that is in full compliance with the relevant policies, rules, regulations, and laws of users of the system. The content created and delivered by the system may be in any form, such as, but not limited to a video, a script, a press release, a social media post, and a keynote speech.

Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for blockchain data storage. One of the methods includes receiving a transaction associated with a blockchain network; determining, after the transaction is performed, an updated account state of a blockchain account involved in the transaction; adding, to a history state object database and after a current block is appended to a blockchain associated with the blockchain network based on performing a consensus algorithm, the updated account state, a hash value of the updated account state, an account identifier (ID) of the blockchain account, and a block ID of the current block; and updating, based on the hash value of the account state, the account ID, and the block ID, a state tree stored in a history state database.

Abstract: Two streams of data items are received. A first estimated processing time for the first stream of data items and a second estimated processing time for the second stream of data items are determined. Data items of the first stream and data items of the second stream are dynamically maintained in a first buffer and a second buffer respectively. The data items of the second stream maintained in the second buffer have associated event times that are within a first join window based on the first estimated processing time for the first stream. A selected data item of the first stream maintained in the first buffer is joined with one or more data items of the second stream maintained in the second buffer that have associated event times that are within a second join window based on an event time associated with the selected data item of the first stream.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that creates a machine learning model with k-means clustering. In some implementations, an instruction to create a model is obtained. A data set including geographic data and non-geographic data is received. The data set includes multiple data entries. Geographic centroids are determined from the geographic data. The data set is analyzed to obtain statistics of the data set. Transformed data is generated from the data set, the statistics, and the geographic centroids. A model is generated with the transformed data, the model indicating multiple data groupings.

Abstract: Various implementations of the invention store and retrieve data via a computing processor. The data is comprised of a plurality of data records with a sequentially changing data value and an other data value. For each data record in the plurality of data records, the computing processor causes the data record to be aggregated and stored with other data records in a first data storage container corresponding to a first data storage space based on the sequentially changing data value of the data record (i.e., sequential data space), and causes the data record to be aggregated and stored with other data records in a second data storage container corresponding to a second data storage space (i.e., finite data space). The data records in the second data storage container are stored based on the other data value. When a query is made against the data, the computing processor determines whether the query is best evaluated in the sequential data space or the finite data space.

Abstract: Systems and techniques for data tagging and task dataset generation are described herein. A set of context elements may be obtained for a data element in a data source. The set of context elements may be evaluated using a machine learning processor to embed one or more tags into the data element. A task to be completed by the user may be identified. A set of task tags may be determined that correspond to the task. The data source may be searched using the set of task tags to select the data element. A task dataset may be generated that includes the data element in response to the search.

Abstract: A system and method are presented that analyze evaluation data concerning a subject using attributes that are logically arranged in a geometric structure such as a rectangular array. A plurality of dimension layers is laid on top of the logical arrangement of data. Each dimension layers assigns values to a plurality of dimensions based on the value of neighboring attribute groups. Each dimension layer can be associated with one or more reporting configurations that contain descriptors for the defined dimensions as well as formatting instructions for report-like output.

Abstract: An information retrieval system is provided.

Abstract: In an example embodiment, a solution is provided that allows for intelligent demand-driven data replication. Only the data that is needed has to be replicated, and this data can be kept only as long as needed. This allows cloud-based applications to be built that integrate deeper with the existing customer landscape with the most efficient data footprint. It allows data types that could not be used before to be integrated into an application. There are additional savings due to the reduced data footprint in the database, compared to a full data replication, without giving up resilience or response time.

Abstract: According to one embodiment, a computer-implemented method includes obtaining a sensory profile, identifying an occurrence of a sensory aspect event affecting a user, comparing the sensory aspect event to the sensory profile, determining from comparing the sensory profile, whether the sensory aspect event is a positive sensory aspect, and countering and/or adjusting the sensory aspect event in response to determining the sensory aspect event is not a positive sensory aspect.

Abstract: Technology is disclosed herein for enhanced similarity search. In an implementation, a search environment includes one or more computing hardware, software, and/or firmware components in support of enhanced similarity search. The one or more components identify a modality for a similarity search with respect to a query object. The components generate an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in a graph. The embedding for the query object provides the basis for the search for similar objects.

Abstract: Techniques for entity and relationship detect from unstructured text as a service are described. A service may receive a request to identify entities within a provided unstructured text element, and the service may segment and tokenize the unstructured text and send the result to multiple services implementing multiple deep machine learning models trained to identify particular entities. The service may send additional requests to an additional service or services implementing additional deep machine learning models to identify relationships between detected attributes and ones of the detected entities. The outputs from all services can be analyzed and consolidated into a single result that identifies the entities, any attributes of the entities, and confidence scores indicating the confidence in each detected entity.

Abstract: Techniques described herein are directed to determining an effective tag for data assets. For instance, each tag associated with a data asset may be associated with certain attributes. Non-limiting examples for such attributes may include a confidence level associated with a source that applied the tag, an applied date at which the tag was applied to the data asset, and/or a hierarchical depth of the data asset to which the tag was applied, as well as additional and/or alternative types of attributes. When a request to determine a tag for a data asset is received, the attributes for all the tags applied to the data asset may be retrieved and/or analyzed to determine which of such tags effectively classifies the data asset. The determined effective tag may be returned to the requesting entity.

Abstract: An image processing apparatus includes a document area extracting module configured to extract a document area from the captured image, the document area being an area of the document, a note area extracting module configured to extract a first note area from the captured image, the first note area being an area of the first note positioned at a first position of the document area of the first page, a character determining module configured to determine the first character included in the first note area by optical character recognition, a document image generating module configured to mask the first note area included in the document area, and generate a document image, a file name generating module configured to generate a file name including the first character, and a file generating module configured to generate an electronic file of the document image having the file name.

Abstract: This application relates to apparatus and methods for automatically determining and providing item reviews to users. In some examples, a computing device obtains review data identifying one or more reviews for each of a plurality of items. The computing device determines keywords for each of the items based on parsing the review data corresponding to each of items. The computing device may obtain data identifying engagement of items for a user during a browsing session, such as items a user has clicked on. The computing device may also obtain data identifying previous purchase transactions, or previous review postings, for the user. The computing device then determines, based on the obtained data, which keywords may be of interest the user. In some examples, the keywords are used to identify reviews of an item for the user. In some examples, summaries of the reviews are generated and displayed to the user.

Abstract: The present invention is a method and process for accurately and efficiently coding documents in electronic discovery. The method, if used by highly experienced and motivated document reviewers in a collegial and harmonic environment, has the potential to increase adjusted review consistency, reduce coding errors, eliminate duplicate efforts, increase review speed, decrease the risks of exposure, and dramatically improve review performance. The method will also result in useful case history files, which are useful in every phrase of litigation, including motion argument, merit trial, appeal, and future litigation.

Abstract: Systems and methods are provided to implement a key overloaded database table that stores multiple instances of a data item using different key attributes to facilitate different types of queries. In embodiments, different partition or sorting keys are specified in different table facets schemas, for the table or for individual items. In embodiments, when an item is inserted into the table, the insertion operation copies values from appropriate attributes of the item into overloaded partition key and sort key fields of the instances to be inserted. In embodiments, when a primary instance of an item is updated, the secondary instances are found using facet schemas stored with the primary instance and overwritten in asynchronous fashion to reflect the state of the primary instance. Advantageously, the disclosed key overloading technique reduces the need for separate index objects for the table and simplifies query planning for the table.

Abstract: A graphical user interface generates a control pane and a diagram pane. The control pane graphically depicts control objects that are each associated with a different viewpoint of digital products. The diagram pane displays graphical representations based upon a user-selected control object in the control pane. In use, a hierarchical view of digital products is presented in the diagram pane. A user can select a digital product from the hierarchical view, and then graphically navigate the digital product, whereby the graphical user interface presents aspects of the digital product, represented as nodes and interconnecting lines in different views defined by the viewpoint associated with user-selected control objects available in the control pane.

Abstract: In one embodiment, a method includes receiving a query from a user from a client system associated with the user, accessing a knowledge graph comprising a plurality of nodes and edges connecting the nodes, wherein each node corresponds to an entity and each edge corresponds to a relationship between the entities corresponding to the connected nodes, determining one or more initial entities associated with the query based on the query, selecting one or more candidate nodes by a conversational reasoning model from the knowledge graph corresponding to one or more candidate entities, respectively, wherein each candidate node is selected based on the nodes corresponding to the initial entities, dialog states associated with the query, and a context associated with the query, generating a response based on the initial entities and the candidate entities, and sending instructions for presenting the response to the client system in response to the query.

Abstract: A public cloud is owned by a first entity and a cloud vault target is owned by a second entity, different from the first entity. A data moving micro-service is deployed to the public cloud and another data moving micro-service is deployed to the cloud vault target. A request is issued to the public cloud for a snapshot of data to vault to the cloud vault target. The snapshot is accessed to write the data to a cloud volume in the public cloud. The data moving micro-service at the public cloud and the other data moving micro-service at the cloud vault target coordinate to read the data in the cloud volume, and deduplicate and replicate the data in the cloud volume from the public cloud to the cloud vault target.

Abstract: A computer-implemented method and computer processing system are provided. The method includes identifying, by a processor, atomic operations within a sequence of data elements and metadata associated with the atomic operations. The sequence of data elements is related to an interaction between a user and a user interface of a computer system that includes the processor. The method also includes calculating, by the processor, correlation indexes from the metadata. A respective correlation index is calculated for various atomic operation groups formed from the atomic operations. The method additionally includes identifying, by the processor, a macro operation from at least one of the correlation indexes. The macro operation includes multiple correlated atomic operations from among the atomic operations identified within the sequence.

Abstract: A method is described for processing keyed data items that are each associated with a value of a key, the keyed data items being from a plurality of distinct data streams, the processing including collecting the keyed data items, determining, based on contents of at least one of the keyed data items, satisfaction of one or more specified conditions for execution of one or more actions and causing execution of at least one of the one or more actions responsive to the determining.

Abstract: Functionalities of new data types are enabled for data stored using native data types (“recognized data types”) supported by DBMSs. Values having a latent data type may be stored using a recognized data type of a DBMS. That is, a value stored in a database table may be recognized by a DBMS as having a recognized data type (e.g., character string) but the value may also include information that indicates the value conforms to a particular latent data type. DBMSs compile database statements. The database statement can contain multiple expressions that may specify a latent data type or that may have a recognized data type but that also imply latent data types. By determining that various expressions have latent data types, operations that rely on the expressions as having a latent data type may be validated in a query and executed accordingly.

Abstract: A method including generating an index comprising (a) question-answer pairs generated based at least in part on a set of ingested source documents and (b) respective location metadata associated with each of the question-answer pairs. The respective location metadata can include a source document identifier of a first ingested source document of the set of ingested source documents and one or more location delimiters indicating a location of target text in the first ingested source document. The target text can correspond to a stored answer of a respective one of the question-answer pairs associated with the respective location metadata. The method also can include receiving a user question from a user. The user question can correspond to a question of a first question-answer pair of the question-answer pairs of the index.

Abstract: A computerized-method for determining a storage class of a media file is provided herein. The computerized-method includes: (i) aggregating data from the plurality of data sources; (ii) operating a pre-built machine learning File Access Frequency Score (FAFS) model to calculate an accessibility score for a media file; (iii) sending the media file to archive storage when the accessibility score is below a preconfigured threshold; (iv) calculating Predicted Active Lifetime Span (PALS) score of the media file, when the accessibility score is above the preconfigured threshold; (v) repeating the calculating of the PALS score of the media file every preconfigured period of time, when the media file is in active storage, until the calculated PALS score of the media file is lower than or equals zero; and (vi) sending the media file to the archive storage.

Abstract: Provided are a data storage method, a storage device, a server and a storage medium, the method includes: obtaining, by a server, image data of different dimensions (S11); according to the association identity carried by each of the image data, determining, by the server, the image data of the different dimensions with the same association identity as association data (S12); sending the image data of the different dimensions included in the association data to target data tables of databases with different dimensions for storage, respectively (S13), wherein, the databases of different dimensions are located in the same storage apparatus, regarding the target data tables of the database of different dimensions, the table name prefixes of the target data tables are different, but the table name suffixes are the same. This method can store image data in association, meanwhile, when performing associated query, the loss of associated data can be avoided.

Abstract: An example method includes receiving, by a user device, authorization to engage in autofill for an application displayed on the user interface (UI) of the user device. The method further includes detecting an autofill trigger event and determining a subset of content excluding user-specific information. The method also includes transmitting a request containing the subset to a remote provider for candidate data for use in autofill. The method further includes receiving a response from the remote provider containing one or more candidate values for use in autofill. The method additionally includes filling the one or more text input fields displayed on the UI with the corresponding one or more candidate values.

Abstract: A memory stores a first cache and a second cache. A processor copies a first portion of data from a first table stored in a database into a second table. The processor further determines that a second portion of data from the first table will be overwritten and copies the second portion into a third table. The processor further determines that a probability that a user will access a third portion of the first table is greater than a threshold and copies the third portion into the first cache. The processor further determines a fourth portion of the first table that the user accesses at a frequency greater than a set frequency and copies the fourth portion into the second cache.

Abstract: A system and method for processing data by accessing data sets for a plurality of variables in at least one data store; associating a plurality of the data sets as at least one variable type; storing in a data store a plurality of operation definitions defining a plurality of operations on at least one of said at least one variable type; receiving from a user interface a selection of at least one operation definition and at least one data set of said at least one variable type operated on by the selected at least one operation definition; and processing the at least one data set in response to the selection according to the at least one operation definition to generate a derived data set.

Abstract: The present disclosure is related to a method of geo-clustering of data for de-identification of a dataset. The method includes generating a plurality of geoclusters based on a plurality of geocodes. The geocodes may include ZIP codes or postal codes. The method further includes identifying the geoclusters having the smallest population. The geocluster having the smallest population is iteratively merged with the nearest geocluster until a minimum population threshold is met. Once the smallest geocluster meets the minimum population threshold, the plurality of geoclusters can be used to cluster the geocodes within a dataset to be de-identified.

Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for blockchain data storage. One of the methods includes receiving a transaction associated with a blockchain network; determining, after the transaction is performed, an updated account state of a blockchain account involved in the transaction; adding, to a history state object database and after a current block is appended to a blockchain associated with the blockchain network based on performing a consensus algorithm, the updated account state, a hash value of the updated account state, an account identifier (ID) of the blockchain account, and a block ID of the current block; and updating, based on the hash value of the account state, the account ID, and the block ID, a state tree stored in a history state database.