Download Cloud Data Management by Liang Zhao PDF

By Liang Zhao

ISBN-10: 3319047647

ISBN-13: 9783319047645

ISBN-10: 3319047655

ISBN-13: 9783319047652

In perform, the layout and structure of a cloud varies between cloud companies. We current a accepted assessment framework for the functionality, availability and reliability features of varied cloud systems. We describe a widely used benchmark structure for cloud databases, particularly NoSQL database as a provider. It measures the functionality of replication hold up and fiscal fee. carrier point Agreements (SLA) signify the agreement which captures the agreed upon promises among a merchant and its shoppers. The necessities of latest provider point agreements (SLA) for cloud prone aren't designed to flexibly deal with even rather simple functionality and technical necessities of patron functions. We current a unique technique for SLA-based administration of cloud-hosted databases from the shopper viewpoint and an end-to-end framework for consumer-centric SLA administration of cloud-hosted databases. The framework enables adaptive and dynamic provisioning of the database tier of the software program functions in accordance with application-defined guidelines for pleasurable their very own SLA functionality standards, fending off the price of any SLA violation and controlling the financial price of the allotted computing assets. during this framework, the SLA of the shopper purposes are declaratively outlined by way of pursuits that are subjected to a couple of constraints which are particular to the applying necessities. The framework continually screens the application-defined SLA and immediately triggers the execution of worthy corrective activities (scaling out/in the database tier) while required. The framework is database platform-agnostic, makes use of virtualization-based database replication mechanisms and calls for 0 resource code adjustments of the cloud-hosted software program purposes.

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The advantage of this approach is that HBase does not need to worry about data replication, data consistency and resiliency because HDFS already considers and deals with them. However, the downside is that it becomes constrained by the characteristics of HDFS, which is that it is not optimized for random read access. In the HBase architecture, data is stored in a farm of Region Servers. A key-toserver mapping is used to locate the corresponding server. The in-memory data storage is implemented using a distributed memory object caching system called Memcache [35] while the on-disk data storage is implemented as a HDFS file residing in the Hadoop data node server.

In general, an application can choose between two read policies: (1) a read policy of strong consistency which always reads from the primary storage location. (2) a policy of eventual consistency [226] which will read from an alternate location when the primary location is unavailable. The AppEngine datastore provides a Python interface which includes a rich data modeling API and a SQL-like query language called GQL [24]. 5 depicts the basic syntax of GQL. A GQL query returns zero or more entities or Keys of the requested kind.

In the Dynamo system, each data item is replicated at N hosts where N is a parameter configured “per-instance”. Each key k is assigned to a coordinator node. The coordinator is in charge of the replication of the data items that fall within its range. N 1/ clockwise successor nodes in the ring. This results in a system where each node is responsible for the region of the ring between it and its N th predecessor. As illustrated in Fig. 4, node B replicates the key k at nodes C and D in addition to storing it locally.

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