Abstract: Techniques and structures for tuning database queries. Actual statistics associated with data stored are retrieved from at least one memory device. The data is associated with one or more tenants of the multi-tenant database system. The actual statistics include at least one type of statistic maintained for the data. A subset of the actual statistics is selected based on a data trait targeted for optimization. A statistical value is calculated for each actual statistic from the subset of actual statistics across one or more tenants having the data trait targeted for optimization. An optimal query plan is determined based on the original query and the calculated statistical values.

Abstract: Techniques and structures for tuning database queries. Actual statistics associated with data stored are retrieved from at least one memory device. The data is associated with one or more tenants of the multi-tenant database system. The actual statistics include at least one type of statistic maintained for the data. A subset of the actual statistics is selected based on a data trait targeted for optimization. A statistical value is calculated for each actual statistic from the subset of actual statistics across one or more tenants having the data trait targeted for optimization. An optimal query plan is determined based on the original query and the calculated statistical values.

Abstract: In accordance with embodiments, there are provided methods and systems for providing multiple column custom indexes in a multi-tenant database environment. A method embodiment provides defining a multi-tenant data structure having a plurality of data columns data fields and a plurality of rows for each of multiple tenants, each row including a data column for a tenant identifier, defining a first data field for a tenant, the first data field having a first data type, defining a second data field for the tenant, the second field having a second data type, and defining an index table including a tenant identifier for the tenant, a copy of data from the first data field and the second data field, and a key to the corresponding rows of the multi-tenant data structure.

Abstract: In a method, system, and computer-readable medium having instructions for executing a query in a database system, a query request is received with a query predicate to filter data returned in response to the query request and the query predicate has a formula, the query request is transformed to a transformed query request by preprocessing the formula in the query predicate, and the query request is optimized using the transformed query request.

Abstract: Methods and systems are described for creating a custom index in a multi-tenant database environment. In one embodiment, a method includes obtaining query for a multi-tenant database that is recommended as a candidate for creating an additional filter, evaluating the query against criteria to determine whether to select the query for creating the additional filter, and creating the additional filter for the query, if the query is selected.

Abstract: In an on demand database system, a query engine applies a custom index for inner queries. The query engine receives a query and determines that the query has an inner query nested within the primary query. The query engine identifies that a custom index exists for a client associated with the query, and applies the custom index to filter results for the query. The custom index includes a subset of information of a table that includes accounts for multiple different clients. By using the custom index, the query engine can filter the results more efficiently that if solely using the multiple client table.

Abstract: Methods and systems are described for creating a custom index in a multi-tenant database environment. In one embodiment, a method includes obtaining query for a multi-tenant database that is recommended as a candidate for creating an additional filter, evaluating the query against criteria to determine whether to select the query for creating the additional filter, and creating the additional filter for the query, if the query is selected.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for query optimization in a database system. These mechanisms and methods for query optimization in a database system can enable embodiments to optimize OR expression filters referencing different logical tables. The ability of embodiments to optimize OR expression filters referencing different logical tables can enable optimization that is dynamic and specific to the particular tenant for whom the query is run and improve the performance and efficiency of the database system in response to query requests.

Abstract: Techniques and structures for tuning database queries. Actual statistics associated with data stored are retrieved from at least one memory device. The data is associated with one or more tenants of the multi-tenant database system. The actual statistics include at least one type of statistic maintained for the data. A subset of the actual statistics is selected based on a data trait targeted for optimization. A statistical value is calculated for each actual statistic from the subset of actual statistics across one or more tenants having the data trait targeted for optimization. An optimal query plan is determined based on the original query and the calculated statistical values.

Abstract: In some embodiments, a computer-implemented method for tuning queries for a multi-tenant database system is provided. A processor retrieves actual statistics associated with data stored on one or more servers in the multi-tenant database system. The data may be associated with one or more tenants of the multi-tenant database system. A subset of the actual statistics is selected, wherein the subset of the actual statistics is related to tenants having a data trait targeted for optimization. The processor determines synthetic statistics based on the subset of the actual statistics. An original query is received at the multi-tenant database system, wherein the original query operates upon data associated with a tenant that has the data trait targeted for optimization. The processor determines an optimal query plan based on the original query and synthetic statistics. Finally, the processor executes the original query based on the optimal query plan.

Abstract: In a method, system, and computer-readable medium having instructions for executing a query in a database system, a query request is received with a query predicate to filter data returned in response to the query request and the query predicate has a formula, the query request is transformed to a transformed query request by preprocessing the formula in the query predicate, and the query request is optimized using the transformed query request.

Abstract: In a method, system, and computer-readable medium having instructions for optimizing a query in a database system, a query request is received with a query predicate to filter data returned in response to the query request and the query predicate has a formula, the query request is transformed to a transformed query request by preprocessing the formula in the query predicate, and the query request is optimized using the transformed query request.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for query optimization in a database system. These mechanisms and methods for query optimization in a database system can enable embodiments to optimize OR expression filters referencing different logical tables. The ability of embodiments to optimize OR expression filters referencing different logical tables can enable optimization that is dynamic and specific to the particular tenant for whom the query is run and improve the performance and efficiency of the database system in response to query requests.

Abstract: In an on demand database system, a query engine applies a custom index for inner queries. The query engine receives a query and determines that the query has an inner query nested within the primary query. The query engine identifies that a custom index exists for a client associated with the query, and applies the custom index to filter results for the query. The custom index includes a subset of information of a table that includes accounts for multiple different clients. By using the custom index, the query engine can filter the results more efficiently that if solely using the multiple client table.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for query optimization in a database system. These mechanisms and methods for query optimization in a database system can enable embodiments to optimize OR expression filters referencing different logical tables. The ability of embodiments to optimize OR expression filters referencing different logical tables can enable optimization that is dynamic and specific to the particular tenant for whom the query is run and improve the performance and efficiency of the database system in response to query requests.

Abstract: In a method, system, and computer-readable medium having instructions for optimizing a query in a database system, a database statistic is generated for a number of related records for one or more entities for at least one tenant and a related record is a record with a relationship to a shared record in a database table for an entity from the one or more entities, a first cost is calculated for accessing the number of related records for at least one tenant, a second cost is calculated for accessing a number of related records accessible to a user, a comparison of the first cost to the second cost is performed to determine a data access path for retrieving accessible related records, and the data access path for retrieving accessible related records is determined based upon the comparison.

Abstract: Methods and systems are described for creating a custom index in a multi-tenant database environment. In one embodiment, a method includes obtaining query for a multi-tenant database that is recommended as a candidate for creating an additional filter, evaluating the query against criteria to determine whether to select the query for creating the additional filter, and creating the additional filter for the query, if the query is selected.

Abstract: In some embodiments, a computer-implemented method for tuning queries for a multi-tenant database system is provided. A processor retrieves actual statistics associated with data stored on one or more servers in the multi-tenant database system. The data may be associated with one or more tenants of the multi-tenant database system. A subset of the actual statistics is selected, wherein the subset of the actual statistics is related to tenants having a data trait targeted for optimization. The processor determines synthetic statistics based on the subset of the actual statistics. An original query is received at the multi-tenant database system, wherein the original query operates upon data associated with a tenant that has the data trait targeted for optimization. The processor determines an optimal query plan based on the original query and synthetic statistics. Finally, the processor executes the original query based on the optimal query plan.

Abstract: In a method, system, and computer-readable medium having instructions for optimizing a query in a database system, a query request is received with a query predicate to filter data returned in response to the query request and the query predicate has a formula, the query request is transformed to a transformed query request by preprocessing the formula in the query predicate, and the query request is optimized using the transformed query request.

Abstract: In a method, system, and computer-readable medium having instructions for optimizing a query in a database system, a database statistic is generated for a number of related records for one or more entities for at least one tenant and a related record is a record with a relationship to a shared record in a database table for an entity from the one or more entities, a first cost is calculated for accessing the number of related records for at least one tenant, a second cost is calculated for accessing a number of related records accessible to a user, a comparison of the first cost to the second cost is performed to determine a data access path for retrieving accessible related records, and the data access path for retrieving accessible related records is determined based upon the comparison.