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:
Disclosed are various embodiments for distributing data items within a plurality of nodes. A data item that is subject to a data item update request is updated from a master node to a plurality of slave notes. The update of the data item is determined to be locality-based durable based at least in part on acknowledgements received from the slave nodes. Upon detection that the master node has failed, a new master candidate is determined via an election among the plurality of slave nodes.
Abstract:
A system that implements a data storage service may maintain tables in a data store on behalf of clients. The service may maintain table data in multiple replicas of partitions of the data that are stored on respective computing nodes in the system. In response to detecting a failure or fault condition, or receiving a service request from a client to move or copy a partition replica, the data store may copy a partition replica to another computing node using a physical copy mechanism. The physical copy mechanism may copy table data from physical storage locations in which it is stored to physical storage locations allocated to a destination replica on the other computing node. During copying, service requests to modify table data may be logged and applied to the replica being copied. A catch-up operation may be performed to apply modification requests received during copying to the destination replica.
Abstract:
A system that implements a data storage service may store data in multiple replicated partitions on respective storage nodes. The selection of the storage nodes (or storage devices thereof) on which to store the partition replicas may be performed by administrative components that are responsible for partition management and resource allocation for respective groups of storage nodes (e.g., based on a global view of resource capacity or usage), or the selection of particular storage devices of a storage node may be determined by the storage node itself (e.g., based on a local view of resource capacity or usage). Placement policies applied at the administrative layer or storage layer may be based on the percentage or amount of provisioned, reserved, or available storage or IOPS capacity on each storage device, and particular placements (or subsequent operations to move partition replicas) may result in an overall resource utilization that is well balanced.
Abstract:
A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.
Abstract:
A system that implements a data storage service may store data on behalf of clients in multiple replicas on respective computing nodes. The system may employ an external service to select a master replica for a replica group. The master replica may service consistent read operations and/or write operations that are directed to the replica group (or to a data partition stored by the replica group). The master replica may employ a quorum based mechanism for performing replicated write operations, and a local lease mechanism for determining the replica authorized to perform consistent reads, even when the external service is unavailable. The master replica may propagate local leases to replica group members as replicated writes. If another replica assumes mastership for the replica group, it may not begin servicing consistent read operations that are directed to the replica group until the lease period for a current local lease expires.
Abstract:
A system that implements a data storage service may store data on behalf of storage service clients. The system may maintain data in multiple replicas of various partitions that are stored on respective computing nodes in the system. The system may employ a single master failover protocol, usable when a replica attempts to become the master replica for a replica group of which it is a member. Attempting to become the master replica may include acquiring a lock associated with the replica group, and gathering state information from the other replicas in the group. The state information may indicate whether another replica supports the attempt (in which case it is included in a failover quorum) or stores more recent data or metadata than the replica attempting to become the master (in which case synchronization may be required). If the failover quorum includes enough replicas, the replica may become the master.
Abstract:
A platform for data analytics may be provided in a hosted environment on a multi-tenant system. The platform provider may also provide transactional processing services. Data obtained from processing the transactional services may be stored in an n-dimensional cube with which analytics may be performed. A dimension and hierarchy model may be identified based on correlations between hierarchy dimensions and levels in a dataset, or in schema and queries related to the dataset. Correlations may be further based on data received from a data stream. Priority for calculating a hierarchy may be based on data received from a data stream.
Abstract:
Methods and apparatus for conditional master election in a distributed database are described. A plurality of replicas of a database object are stored by a distributed database service. Some types of operations corresponding to client requests directed at the database object are to be coordinated by a master replica. Client access to the database object is enabled prior to election of a master replica. In response to a triggering condition, a particular replica is elected master. The master coordinates implementation of operations with one or more other replicas in response to client requests.
Abstract:
A system that implements a data storage service may store data on behalf of storage service clients. The system may maintain data in multiple replicas of various partitions that are stored on respective computing nodes in the system. The system may employ a single master failover protocol, usable when a replica attempts to become the master replica for a replica group of which it is a member. Attempting to become the master replica may include acquiring a lock associated with the replica group, and gathering state information from the other replicas in the group. The state information may indicate whether another replica supports the attempt (in which case it is included in a failover quorum) or stores more recent data or metadata than the replica attempting to become the master (in which case synchronization may be required). If the failover quorum includes enough replicas, the replica may become the master.