Nec Laboratories America, Inc.

Nec Corporation

Ziyang Liu

Vahit Hakan Hacigumus

Systems and methods are disclosed for query processing in a big data analytics platform by enumerating plans for a current query using a processor; building a dominance graph for the current query; for each plan, determining a regret value and a score for the plan based on the regret value and cost; and selecting query plans in an online fashion for query processing in big data analytics platforms where intermediate results are materialized and can be reused later.

Visionary query processing in Hadoop utilizing opportunistic views

A method for database consolidation includes generating a model for expected penalty estimation; determining a tenant's value as a function of query arrival rate and SLA penalty; placing a tenant to minimize a total expected cost in the order of the tenant value; and progressively using additional servers to prevent any server from being saturated to guarantee a tenant placement that costs no more than four times the cost of any other placement.

Tenant placement in multitenant databases for profit maximization

A method for tenant placement in a multi-tenant system is shown that includes creating a weighted graph of tenants and sharing relationships between tenants, where a weight for each tenant and each sharing relationship represents an associated degree of resource consumption; and adding one or more tenants to a database using a processor based on said weighted graph and a database capacity, such that the combined weight of the added tenants and the sharing relationships belonging to the added tenants are within the database capacity. If a tenant cannot be added to the database without exceeding the database capacity, a new database is created and the one or more tenants are added to the new database, subject to a new database capacity. The adding and creating steps are repeated until all tenants have been added to a database.

Tenant placement in multitenant cloud databases with data sharing

Methods for generating a data fetching plan in a multi-tenant system include placing tenants in consecutively allocated databases according to a weighted graph of tenants and sharing relationships between tenants, where at least one sharing relationship includes multiple accessing tenants accessing a given set of data from a provider tenant. For each sharing relationship, if a current database has one or more accessing tenants and does not have the provider tenant, data is fetched from the latest-allocated database prior to the current database that has accessing tenants, if such a database exists; if a current database has the provider tenant, data is provided to the earliest-allocated database after the current database that has accessing tenants if such a database exists. The fetching and providing steps are repeated for each allocated database.

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Santa Clara, CA, United States of America

Ziyang Liu