Abstract: A system for write optimization in transactional data management systems is described. The system stores a tree data structure that comprises a root, a plurality of internal nodes, and a plurality of leaf nodes. Each internal node comprises a pivot key and a child pointer. Each leaf node stores key-value pairs sorted by a corresponding key. The system forms a plurality of hybrid nodes. The hybrid nodes comprise a layer of internal nodes that are immediate parents of the plurality of leaf nodes. A buffer is formed only for each internal node of the plurality of hybrid nodes. The buffer is used to store a message that encodes an operation. The message is to be applied to the corresponding leaf nodes of the plurality of hybrid nodes.

Abstract: A system for write optimization in transactional data management systems is described. The system stores a tree data structure that comprises a root, a plurality of internal nodes, and a plurality of leaf nodes. Each internal node comprises a pivot key and a child pointer. Each leaf node stores key-value pairs sorted by a corresponding key. The system forms a plurality of hybrid nodes. The hybrid nodes comprise a layer of internal nodes that are immediate parents of the plurality of leaf nodes. A buffer is formed only for each internal node of the plurality of hybrid nodes. The buffer is used to store a message that encodes an operation. The message is to be applied to the corresponding leaf nodes of the plurality of hybrid nodes.

Abstract: Histograms formed based on samples of a population, such as histograms created from random page-level samples of a data store, are intelligently scaled to histograms estimating distribution of the entire population of the data store. As an optional optimization, where a threshold number of duplicate samples are observed during page-level sampling, the number of distinct values in the overall population data is presumed to be the number of distinct values in the sample data. Also, during estimation of distinct values of an overall population, a “Chao” estimator can optionally be utilized as a lower bound of the estimate. The resulting estimate is then used when scaling, which can take domain knowledge of the data being scaled into account in order to prevent scaled estimates from exceeding the limits of the domain.

Abstract: A query execution system is provided. The system includes a monitor component that detects data value changes in a database. An adjustment component initiates an intermediate query in view of detected data value changes, the intermediate query employed to adjust statistics related to a query plan optimization.

Abstract: Histograms formed based on samples of a population, such as histograms created from random page-level samples of a data store, are intelligently scaled to histograms estimating distribution of the entire population of the data store. As an optional optimization, where a threshold number of duplicate samples are observed during page-level sampling, the number of distinct values in the overall population data is presumed to be the number of distinct values in the sample data. Also, during estimation of distinct values of an overall population, a “Chao” estimator can optionally be utilized as a lower bound of the estimate. The resulting estimate is then used when scaling, which can take domain knowledge of the data being scaled into account in order to prevent scaled estimates from exceeding the limits of the domain.

Abstract: Histograms formed based on samples of a population, such as histograms created from random page-level samples of a data store, are intelligently scaled to histograms estimating distribution of the entire population of the data store. As an optional optimization, where a threshold number of duplicate samples are observed during page-level sampling, the number of distinct values in the overall population data is presumed to be the number of distinct values in the sample data. Also, during estimation of distinct values of an overall population, a “Chao” estimator can optionally be utilized as a lower bound of the estimate. The resulting estimate is then used when scaling, which can take domain knowledge of the data being scaled into account in order to prevent scaled estimates from exceeding the limits of the domain.

Abstract: A query execution system is provided. The system includes a monitor component that detects data value changes in a database. An adjustment component initiates an intermediate query in view of detected data value changes, the intermediate query employed to adjust statistics related to a query plan optimization.

Abstract: Histograms formed based on samples of a population, such as histograms created from random page-level samples of a data store, are intelligently scaled to histograms estimating distribution of the entire population of the data store. As an optional optimization, where a threshold number of duplicate samples are observed during page-level sampling, the number of distinct values in the overall population data is presumed to be the number of distinct values in the sample data. Also, during estimation of distinct values of an overall population, a “Chao” estimator can optionally be utilized as a lower bound of the estimate.