Abstract: A data set may be partitioned according to relative differences indicated by a cover tree. A cover tree may be generated for a data set. Items in the data set may be stored at the same or different nodes according to the relative difference between the items indicated in the cover tree. Portions of the cover tree may be assigned to different nodes storing the data set. Access requests for the data set may be performed by sending the access requests to nodes identified according to the assigned portions of the cover tree.

Abstract: A storage engine may selectively maintain a spatial index for accessing spatial data. A spatial query may be received and the portions of the spatial index to evaluate may be determined by replacing those portions associated with regions identified for the query that do not exist in the spatial index with portions that do exist in the spatial index and are associated with a region that includes the identified regions. When inserting spatial objects into the spatial index, a determination may be made whether to create a new portion in the index if none currently exist that match a spatial index value for a new spatial object or to modify the spatial index value of the spatial object to insert the spatial object into an existing portion of the spatial index.

Abstract: A system that implements a scalable data storage service may maintain tables in a data store on behalf of storage service clients. The service may maintain table data in multiple replicas of partitions that are stored on respective computing nodes in the system. In response to detecting an anomaly in the system, detecting a change in data volume on a partition or service request traffic directed to a partition, or receiving a service request from a client to split a partition, the data storage service may create additional copies of a partition replica using a physical copy mechanism. The data storage service may issue a split command defined in an API for the data store to divide the original and additional replicas into multiple replica groups, and to configure each replica group to maintain a respective portion of the table data that was stored in the partition before the split.

Abstract: A database service may provide multi-tenant and single-tenant environments in which tables may be maintained on behalf of clients. The service (or underlying system) may create database instances and tables in either or both types of environments (e.g., by default or according to various parameter values specified in requests to create the instances or tables). When receiving and servicing requests directed to a table hosted in a single-tenant environment, the system may elide at least some of the authentication or metering operations that would be performed when servicing requests directed to tables hosted in a multi-tenant environment. Tables may be moved from a single-tenant environment to a multi-tenant environment, or vice versa, automatically by the system (e.g., dependent on an observed, expected, or desired throughput) or in response to an explicit request from a client to do so (e.g., to increase throughput or reduce cost).

Abstract: A distributed data store may provide continuous backup for data stored in the distributed data store. Updates to data may be replicated amongst storage nodes according to a peer-to-peer replication scheme. A backup node may participate in the peer-to-peer replication scheme to identify additional updates to be applied to a backup version of the data in a separate data store. The backup node may obtain the updates according to the peer-to-peer replication scheme and update the backup version of the data. In some embodiments, configuration changes to the data in the distributed data store may be detected via the peer-to-peer replication scheme such that a backup node can adapt performance of backup operations in conformity with the configuration change.

Abstract: A data set may be partitioned according to relative differences indicated by a cover tree. A cover tree may be generated for a data set. Items in the data set may be stored at the same or different nodes according to the relative difference between the items indicated in the cover tree. Portions of the cover tree may be assigned to different nodes storing the data set. Access requests for the data set may be performed by sending the access requests to nodes identified according to the assigned portions of the cover tree.

Abstract: Techniques for hosting machine learning models are described. In some instances, a method of receiving a request to perform an inference using a particular machine learning model; determining a group of hosts to route the request to, the group of hosts to host a plurality of machine learning models including the particular machine learning model; determining a path to the determined group of hosts; determining a particular host of the group of hosts to perform an analysis of the request based on the determined path, the particular host having the particular machine learning model in memory; routing the request to the particular host of the group of hosts; performing inference on the request using the particular host; and providing a result of the inference to a requester is performed.

Abstract: Techniques for hosting adding and warming a host are described. In some instances, a method of determining that at least one group of hosts is to be increased by adding an additional host to the group of hosts; sending a request to the group of hosts for a list of machine learning models loaded per host of the group of hosts; receiving, from each host, the list of loaded machine learning models; loading at least a proper subset of list of loaded machine learning models into random access memory of the at least one group; receiving a request to perform an inference; routing the request to the additional host of the group of hosts; performing an inference using the additional host of the group of hosts; and providing a result of the inference to an external entity is described.

Abstract: Disclosed are various embodiments for reducing locking in a distributed data store that includes a primary data store and one or more secondary data stores. An update to a data item that is to be applied to the distributed data store is obtained in one or more computing devices. The update is applied to a cached version of the data item when a lock is held. The update is replicated to the one or more data stores after the lock is released. A replication confirmation is obtained from each of at least a predetermined number of the secondary data stores.

Abstract: A query optimizer may receive a query block that includes a hint. The hint may include a unique object identifier to specify an object to which the hint applies. In some instances, the object may correspond to a nested query block. A query optimization plan may be determined based, at least in part, on the hint. The query execution plan may then be executed to query a data store.

Abstract: A database engine may maintain a collection of data on a first storage device. A workflow manager node may receive a request to bulk load data into the collection. The workflow manager may instruct a control plane node to allocate and configure a secondary database node and to make operable thereon a second database using a second storage device. Data may be bulk loaded to the second storage device using a schema and storage unit format compatible with the collection of data. Storage units from the second storage device may be transferred to the first storage device and integrated into the collection of data.

Abstract: A distributed data store may provide continuous backup for data stored in the distributed data store. Updates to data may be replicated amongst storage nodes according to a peer-to-peer replication scheme. A backup node may participate in the peer-to-peer replication scheme to identify additional updates to be applied to a backup version of the data in a separate data store. The backup node may obtain the updates according to the peer-to-peer replication scheme and update the backup version of the data. In some embodiments, configuration changes to the data in the distributed data store may be detected via the peer-to-peer replication scheme such that a backup node can adapt performance of backup operations in conformity with the configuration change.

Abstract: Techniques for analyzing stored video upon a request are described. For example, a method of receiving a first application programming interface (API) request to analyze a stored video, the API request to include a location of the stored video and at least one analysis action to perform on the stored video; accessing the location of the stored video to retrieve the stored video; segmenting the accessed video into chunks; processing each chunk with a chunk processor to perform the at least one analysis action, each chunk processor to utilize at least one machine learning model in performing the at least one analysis action; joining the results of the processing of each chunk to generate a final result; storing the final result; and providing the final result to a requestor in response to a second API request is described.

Abstract: A data-collecting device acquires data associated with a real-time data stream and transmits the data to a data-consuming service hosted on a server computer system in the form of a multipart response. The multipart response includes one or more data content parts and at least one authentication content part. Each of the one or more data content parts contains data representing part of the real-time data stream. Each authentication content part includes authentication information usable to verify the integrity of the data transmitted in the data content parts transmitted prior to the authentication content part.

Abstract: A system that implements a scaleable data storage service may maintain tables in a non-relational data store on behalf of clients. Each table may include multiple items. Each item may include one or more attributes, each containing a name-value pair. Attribute values may be scalars or sets of numbers or strings. The system may provide an API usable to request that values of one or more of an item's attributes be updated. An update request may be conditional on expected values of one or more item attributes (e.g., the same or different item attributes). In response to a request to update the values of one or more item attributes, the previous values and/or updated values may be optionally returned for the updated item attributes or for all attributes of an item targeted by an update request. Items stored in tables may be indexed using a simple or composite primary key.

Abstract: Techniques for automated speech recognition (ASR) are described. A user can upload an audio file to a storage location. The user then provides the ASR service with a reference to the audio file. An ASR engine analyzes the audio file, using an acoustic model to divide the audio data into words, and a language model to identify the words spoken in the audio file. The acoustic model can be trained using audio sentence data, enabling the transcription service to accurately transcribe lengthy audio data. The results are punctuated and normalized, and the resulting transcript is returned to the user.

Abstract: A distributed data store may implement passive distribution encryption keys to enable access to encrypted data stored in the distributed data store. Keys to encrypt a data volume stored in the distributed data store may be encrypted according to a distribution key and provided to a client of the distributed data store. Storage nodes that maintain portions of the data volume may receive the encrypted key from a client to enable access to the data volume. The storage nodes may decrypt the key according to the distribution key and enable access to the data volume at the storage nodes. In some embodiments, a key hierarchy may be implemented to encrypt the keys that provide access to the encrypted data. The key hierarchy may include a user key.

Abstract: Methods and apparatus for configurable-capacity time-series tables are disclosed. A schedule of database table management operations, including at least an operation to change a throughput constraint associated with a table in response to a triggering event, is generated. The table is instantiated with an initial throughput constraint in accordance with the schedule. Work requests directed to the table are accepted based on the initial throughput constraint. The throughput constraint is modified in response to the triggering event. Subsequent work requests are accepted based on the modified throughput constraint.

Abstract: Methods, systems, and computer-readable media for exporting dialog-driven applications to digital communication platforms are disclosed. A launch condition is received from a user. The launch condition is caused to be registered with one or more digital communication platforms. Detection of the launch condition is to cause a natural language input to be routed from at least one of the digital communication platforms to an application management service.

Abstract: Techniques are disclosed for splitting a database partition into two partitions. In embodiments, where the partition is a hash partition, the partition is split at its logical midpoint, so that half of the partition's rows are placed in each split partition. Where the partition is a hash-range partition, a number of rows of the partition are sampled. Where enough samples fall on each side of the logical midpoint, the logical midpoint is again used as the split point. Where not enough samples fall on one side of the logical midpoint, then the median of the samples is used as the split point.