Amazon Technologies, Inc.

Wan Man Ryan Chan

Akhilesh Mritunjai

Yogesh Kansal

Tushar Rakheja

Jason Kroll

Xi Huang

Somasundaram Perianayagam

Richard David Krog

Mostafa Elhemali

Sroaj Sosothikul

Adel Gawdat

Jhansi Lakshmi Kolla

Jiancheng Wang

Omendra Pratap Singh

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

Selective application of log records may be performed. A target storage node for a new replica being added to a replica group for a database may obtain a paginated result of a scan of ordered items of the database from a source. The paginated result may have a log sequence number that corresponds to a replica log consistent with the paginated result. The target storage node may obtain log records from the replication log after the log sequence number for the paginated result. The target storage node may selectively apply the log records from the replication log according to one or more application rules that determine whether to ignore a change described in a log record.

Selectively applying a replication log for logical database replica creation

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

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Seattle, WA, United States of America

Wan Man Ryan Chan