Amazon Technologies, Inc.

Yogesh Kansal

Akhilesh Mritunjai

Wan Man Ryan Chan

Tushar Rakheja

Jason Kroll

Xi Huang

Richard David Krog

Adel Gawdat

Various embodiments are described for tracking and enabling access to information about key access patterns for database tables managed by a database service of a service provider network. Storage nodes can store data as key-value pairs (or key-document pairs), where the records or documents of a database are addressed by a unique key for each record. The storage nodes over time receive requests to perform various operations (for example, to get, put, update, or delete data in a table) associated with records stored by the storage nodes. Key access information extractors collect information regarding the keys accessed and send the information to a key tracking service. Key tracker nodes of the service can collect the data and send it to aggregator nodes. The aggregator nodes can determine a frequency with which such requests are received for keys of a partition or table to which the aggregator node is assigned.

Remote tracking and identification of key access patterns for databases

A non-relational database system may handle requests to access separately stored items in different data stores. An access request for an item may be received that is stored in a table of a non-relational database. If the item is determined to be stored at a data store not implemented as part of the non-relational database, then an instruction to access the item may be sent to a query engine that can access the data store. A result from the second query engine may be used to respond to the access request for the item.

Handling requests to access separately stored items in a non-relational database

Techniques are described for monitoring and enabling access to information about key access patterns for nonrelational database tables managed by a nonrelational database service of a service provider network. Storage nodes store data as key-value pairs (or key-document pairs), where the records or documents of a database are addressed by a unique key for each record. The storage nodes over time receive requests to perform various operations (for example, to get, put, update, or delete data in a table) associated with records stored by the storage nodes. The storage nodes collect information indicating a frequency with which such requests are received for each key for which a storage node is responsible. This frequency information for each key can be normalized relative to a maximum frequency supported by the storage nodes to obtain an access frequency score, where the maximum frequency indicates a frequency at which additional requests to the storage node may be throttled.

Monitoring key access patterns for nonrelational databases

Growing community of inventors

Bellevue, WA, United States of America

Yogesh Kansal