Abstract: A method is provided for processing a query. In some embodiments, the method includes creating a historical schema defining an ordered set of fields based on a current schema of an object and a field modification of the current schema. The method includes inserting, based on the field modification, a new field at an end of the historical schema and archiving records into a second storage device. The method includes receiving a query, which includes a command specifying a subset of fields and which indicates a non-current field. The method includes searching in the second storage device for archive records having a second schema including the subset of fields and the non-current field. The first and second schemas follow the field order in accordance with the historical schema. The method further includes accessing the subset of fields and the non-current field in accordance with the command.

Abstract: Systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database via an efficient delete operation are described herein. The new delete operation (or method) may be configured to identify one or more records to be deleted within a data structure such as an object. In order to ensure that the operation is efficient, the mechanism may determine characteristics of a data store and determine whether the information provided within the data structure provides an efficient identification of the data to be deleted. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating metadata-based statistics-oriented query processing for large datasets in an on-demand services environment. In one embodiment and by way of example, a method comprises evaluating metadata associated with a query placed on behalf of a tenant in a multi-tenant environment, and computing process statistics for the query based on the metadata, where the process statistics reveal an estimation of resources needed for execution of the query within a predictable amount of time and using fewer than or equal to an allocated number of scans of a database. The method may further include associating, based on the process statistics, a set of rules and the estimated resources to process the query, and executing the query based on the set of rules and using the estimated resources such that the query is processed within the predictable amount of time and using fewer than or equal to the allocated number of scans of the database.

Abstract: A method is provided for processing a query. In some embodiments, the method includes creating a historical schema defining an ordered set of fields based on a current schema of an object and a field modification of the current schema. The method includes inserting, based on the field modification, a new field at an end of the historical schema and archiving records into a second storage device. The method includes receiving a query, which includes a command specifying a subset of fields and which indicates a non-current field. The method includes searching in the second storage device for archive records having a second schema including the subset of fields and the non-current field. The first and second schemas follow the field order in accordance with the historical schema. The method further includes accessing the subset of fields and the non-current field in accordance with the command.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database. Described is a mechanism for performing operations such as an efficient delete operation by introducing a new delete operation (or method) that is configured to allow a data structure such as an object to identify one or more records to be deleted. In order to ensure that the operation is efficient, the mechanism may determine characteristics of a data store and determine whether the information provided within the data structure provides an efficient identification of the data to be deleted. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamic selection and application for rules for query processing for large datasets in an on-demand services environment according to one embodiment. In one embodiment and by way of example, a method comprises determining processing patterns of a query based on historical performances associated with the query placed on behalf of a tenant in a multi-tenant environment, and dynamically applying one or more rules to the query for processing of the query within a predictable amount of time, where the one or more rules are dynamically selected from sets of rules based on the processing patterns. The method may further include executing the query based on the one or more rules by scanning one or more portions of a database having contents pertinent to the query and generating results by processing the query based on the contents and within the predictable amount of time.

Abstract: A method is provided for processing a query. In some embodiments, the method includes creating a historical schema defining an ordered set of fields based on a current schema of an object and a field modification of the current schema. The method includes inserting, based on the field modification, a new field at an end of the historical schema and archiving records into a second storage device. The method includes receiving a query, which includes a command specifying a subset of fields and which indicates a non-current field. The method includes searching in the second storage device for archive records having a second schema including the subset of fields and the non-current field. The first and second schemas follow the field order in accordance with the historical schema. The method further includes accessing the subset of fields and the non-current field in accordance with the command.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database. Described is a mechanism for performing operations such as an efficient delete operation by introducing a new delete operation (or method) that is configured to allow a data structure such as an object to identify one or more records to be deleted. In order to ensure that the operation is efficient, the mechanism may determine characteristics of a data store and determine whether the information provided within the data structure provides an efficient identification of the data to be deleted. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database. Described is a mechanism for performing operations such as an efficient delete operation by introducing a new delete operation (or method) that is configured to allow a data structure such as an object to identify one or more records to be deleted. In order to ensure that the operation is efficient, the mechanism may perform a validation of the values provided to the delete operation based on the type of data store used for storing the records. For example, the validation may ensure that the values provided to the method correspond to a composite primary key when records are stored in a non-relational data store. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: A method is provided for processing a query. In some embodiments, the method includes creating a historical schema defining an ordered set of fields based on a current schema of an object and a field modification of the current schema. The method includes inserting, based on the field modification, a new field at an end of the historical schema and archiving records into a second storage device. The method includes receiving a query, which includes a command specifying a subset of fields and which indicates a non-current field. The method includes searching in the second storage device for archive records having a second schema including the subset of fields and the non-current field. The first and second schemas follow the field order in accordance with the historical schema. The method further includes accessing the subset of fields and the non-current field in accordance with the command.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database. Described is a mechanism for performing operations such as an efficient delete operation by introducing a new delete operation (or method) that is configured to allow a data structure such as an object to identify one or more records to be deleted. In order to ensure that the operation is efficient, the mechanism may determine characteristics of a data store and determine whether the information provided within the data structure provides an efficient identification of the data to be deleted. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for deleting data of an object within a multi-tenant database. Described is a mechanism for performing operations such as an efficient delete operation by introducing a new delete operation (or method) that is configured to allow a data structure such as an object to identify one or more records to be deleted. In order to ensure that the operation is efficient, the mechanism may perform a validation of the values provided to the delete operation based on the type of data store used for storing the records. For example, the validation may ensure that the values provided to the method correspond to a composite primary key when records are stored in a non-relational data store. Upon a successful validation, an initial delete request may be translated to an appropriate delete operation for the underlying database.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamic selection and application for rules for query processing for large datasets in an on-demand services environment according to one embodiment. In one embodiment and by way of example, a method comprises determining processing patterns of a query based on historical performances associated with the query placed on behalf of a tenant in a multi-tenant environment, and dynamically applying one or more rules to the query for processing of the query within a predictable amount of time, where the one or more rules are dynamically selected from sets of rules based on the processing patterns. The method may further include executing the query based on the one or more rules by scanning one or more portions of a database having contents pertinent to the query and generating results by processing the query based on the contents and within the predictable amount of time.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating metadata-based statistics-oriented query processing for large datasets in an on-demand services environment. In one embodiment and by way of example, a method comprises evaluating metadata associated with a query placed on behalf of a tenant in a multi-tenant environment, and computing process statistics for the query based on the metadata, where the process statistics reveal an estimation of resources needed for execution of the query within a predictable amount of time and using fewer than or equal to an allocated number of scans of a database. The method may further include associating, based on the process statistics, a set of rules and the estimated resources to process the query, and executing the query based on the set of rules and using the estimated resources such that the query is processed within the predictable amount of time and using fewer than or equal to the allocated number of scans of the database.