Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to restore a given table that was backed up in a remote storage system (e.g., key-value durable storage system), the service may create a new table, and may import a copy of each of the partitions of the given table from the remote storage system into the new table. The request to restore the table may specify a modified value for a configuration parameter for the table or for one of its partitions. The service may apply the new configuration parameter value to the table or its partitions during the restore operation. The new configuration parameter value may indicate an increase or decrease in storage capacity or throughput capacity, and its application may automatically trigger a partition split or move operation.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: In response to determining that a secondary index is to be created for a particular table of a non-relational database service, a service component verifies that automated transmission of change records of the table to a log-structured journal has been configured. A given change record comprises a before-image and an after-image associated with a committed database write, and is assigned a unique sequence number. A change record propagator for the secondary index examines change records stored in the journal, and transmits selected change records to an index storage node. The index storage node builds the secondary index using the selected change records.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.

Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.

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: 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: In response to determining that continuous data protection is to be enabled for a particular table of a database service, a service component verifies that automated transmission of change records of the table to a log-structured journal has been configured. A given change record comprises a before-image and an after-image associated with a committed database write, and is assigned a unique sequence number. In response to a determination to restore the table as of a specified point in time, a restore record set is identified from the journal with respect to a selected snapshot of the table. The restore record set includes change records which are not represented in the snapshot and are to be represented in the restored table. A restore result table is created using the selected snapshot and the restore record set.

Abstract: In response to determining that continuous data protection is to be enabled for a particular table of a database service, a service component verifies that automated transmission of change records of the table to a log-structured journal has been configured. A given change record comprises a before-image and an after-image associated with a committed database write, and is assigned a unique sequence number. In response to a determination to restore the table as of a specified point in time, a restore record set is identified from the journal with respect to a selected snapshot of the table. The restore record set includes change records which are not represented in the snapshot and are to be represented in the restored table. A restore result table is created using the selected snapshot and the restore record set.

Abstract: A natural language understanding model is trained using respective natural language example inputs corresponding to a plurality of applications. A determination is made as to whether a value of a first parameter of a first application is to be obtained using a natural language interaction. Using the natural language understanding model, at least a portion of the first application is generated.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to restore a given table that was backed up in a remote storage system (e.g., key-value durable storage system), the service may create a new table, and may import a copy of each of the partitions of the given table from the remote storage system into the new table. The request to restore the table may specify a modified value for a configuration parameter for the table or for one of its partitions. The service may apply the new configuration parameter value to the table or its partitions during the restore operation. The new configuration parameter value may indicate an increase or decrease in storage capacity or throughput capacity, and its application may automatically trigger a partition split or move operation.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to restore a given table that was backed up in a remote storage system (e.g., key-value durable storage system), the service may create a new table, and may import a copy of each of the partitions of the given table from the remote storage system into the new table. The request to restore the table may specify a modified value for a configuration parameter for the table or for one of its partitions. The service may apply the new configuration parameter value to the table or its partitions during the restore operation. The new configuration parameter value may indicate an increase or decrease in storage capacity or throughput capacity, and its application may automatically trigger a partition split or move operation.

Abstract: A natural language understanding model is trained using respective natural language example inputs corresponding to a plurality of applications. A determination is made as to whether a value of a first parameter of a first application is to be obtained using a natural language interaction. Using the natural language understanding model, at least a portion of the first application is generated.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may export individual partitions of the table from the database and package them to be independently uploaded (e.g., in parallel) to a remote storage system (e.g., a key-value durable storage system). Prior to uploading the exported and packaged partitions to the remote storage system, the service may verify that the exported and packaged partitions can be subsequently restored, which may include unpackaging and/or re-inflating the exported and packaged partitions to create additional unpackaged copies of the partitions, re-importing the additional unpackaged copies of the partitions into the database (e.g., as additional replicas), and/or comparing checksums generated for the exported partitions with checksums generated for the additional unpackaged copies of the partitions.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may export individual partitions of the table from the database and package them to be independently uploaded (e.g., in parallel) to a remote storage system (e.g., a key-value durable storage system). Prior to uploading the exported and packaged partitions to the remote storage system, the service may verify that the exported and packaged partitions can be subsequently restored, which may include unpackaging and/or re-inflating the exported and packaged partitions to create additional unpackaged copies of the partitions, re-importing the additional unpackaged copies of the partitions into the database (e.g., as additional replicas), and/or comparing checksums generated for the exported partitions with checksums generated for the additional unpackaged copies of the partitions.

Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.