International Business Machines Corporation

Couchbase, Inc.

Sap Se

Sap Ag

Bingjie Miao

Marco Greco

Raghupathi Keshava Murthy

Prathibha Bisarahalli Prabhakar

Srinivasan R Mottupalli

Vincent Corvinelli

John Frederick Hornibrook

Scott David Lashley

Nita Dembla

Kevin Leo Beck

Paul Michael Brett

Keith G Billings

A document-oriented database system generates an optimal query execution plan for database queries on an untyped field included in a collection of documents. Each untyped field is configured to store one or more scalar data values. The system generates histograms for scalar data values stored in untyped fields. Responsive to receiving a query statement for fetching or updating data value stored in one of the untyped fields, the system assigns a cost to each operator associated with the query statement based on the histogram, compares the costs assigned to the operators, and generates a query execution plan based on the comparison, and query the database using the query execution plan.

Cost-based query optimization for untyped fields in database systems

A document-oriented database system generates an optimal query execution plan for database queries on an untyped data field included in a collection of documents. The system generates histograms for multiple types of data stored by the untyped data field and uses the histograms to assign costs to operators usable to execute the database query. The system generates the optimal query execution plan by selecting operators based on the assigned costs. In various embodiments, the untyped data field stores scalars, arrays, and objects.

Cost-based query optimization for array fields in database systems

Cost-based optimization for document-oriented database queries on arrays

Cost-based optimization for document-oriented database queries

In a method for table statistics update, in response to a request to modify a row in a target table, a database management system inspects a log record for the modified row in the target table, determines that the target table is configured for continuous statistics evaluation, and determines whether a mini-bin related to the modified row exists. When the mini-bin related to the modified row does not exist, the database management system creates the mini-bin. When the mini-bin related to the modified row exists, the database management system aggregates the modified row into the mini-bin, and when the mini-bin is determined to have reached a threshold size, stores the mini-bin to a disk. The database management system then consolidates a plurality of mini-bins stored in the disk and corresponding to the target table into a set of bins.

Continuous automatic update statistics evaluation using change data capture techniques

A method and system for accurately estimating a result size of a Group-By operation in a relational database. The estimate utilizes the probability of union of the columns involved in the operation, as well as the relative cardinality of each column with respect to the other columns in the operation. In addition, the estimate incorporates the use of table filters when indicated such that table filters are applied prior to determining the size of the tables in the operation, as well as including equivalent columns into the list of columns that are a part of the Group-By operation. Accordingly, the estimate of the result size of the operation includes influencing factors that provide an accurate estimation of system memory requirements.

Group-by size result estimation

An approach is provided in which a sample point system allocates sample point identifiers to a root node included an index tree that includes multiple leaf nodes. The sample point system distributes the sample point identifiers to the root node's child nodes, and recursively traverses through the index tree's hierarchical index levels and distributes the sample point identifiers from the child nodes to a subset of the index tree's leaf nodes. In turn, the sample point system collects sample data from the subset of the plurality of leaf nodes corresponding to the distributed sample point identifiers.

Gathering index statistics using sampling

In accordance with aspects of the present invention, provided are systems and computer program products for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Systems and computer program product for cost estimation using partially applied predicates

In accordance with aspects of the present invention, provided are methods for incrementally estimating the cardinality of a derived relation including statistically correlated partially applicable predicates for a range-partitioned table. During the generation of a QEP a cardinality estimate is calculated in which one or more partially applicable predicates is correlated to another partially applicable predicate and/or to one or more fully applicable predicates. The cardinality includes a number of rows expected to be returned by the QEP and is computed in an incremental fashion for each operator of the QEP.

Methods of cost estimation using partially applied predicates

Group-By result size estimation

A choose tree is generated at compile time to facilitate a determination if any partition of a range partitioned database table includes a particular key at runtime. To generate the choose tree at compile time, a query compiler receives a source code indicative of each partition of the range partitioned database table, and generates the choose tree from the source code at compile time where the choose tree is representative of a pre-computed binary search of the range partitioned database table. Thereafter, the choose tree can be interpreted/executed at runtime to facilitate a traversal of the choose tree for determining if any partition of the range partitioned database table includes the particular key.

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Tigard, OR, United States of America

Bingjie Miao