Abstract:
A relational database server may concurrently execute many relational queries, but a complex relational query may cause performance delays in the fulfillment of other relational queries. Instead, the relational database server may generate a query plan for the relational query, and may endeavor to partition the relational query between a spool operator and a scan operator into two or more query slices, where each query slice may be executed within a query slice threshold. Many alternative candidate query plans may be considered, such as inserting spool and scan operators after various operators and parameterizing operators in order to partition the records of a relation into two or more ranges based on an attribute of the relation. A large search space of candidate query plans may be reviewed in order to select a query plan that respects the query slice threshold while efficiently executing the logic of the relational query.
Abstract:
A database server may be configured to compute distinct page counts of pages accessed to execute operands of respective queries. The queries may be executed against a table comprised of the pages and having an index managed by the database server. The distinct page counts may be obtained by counting, as a part of the executing of the queries, distinct pages accessed during the execution of the queries.
Abstract:
A keyword search is executed on a view of a database based on a Boolean keyword query. The view includes multiple text columns, and the keyword search is executed on each of the multiple text columns in the view. The output results from the keyword search on each of the text columns include tuple identifiers of one or more relevant tuples and a relevancy score for ranking the results of the keyword query.
Abstract:
The claimed subject matter relates to incorporating a skyline operator within a relational database engine, and more particularly to a database engine that utilizes novel techniques to determine the lowest cost of generating the skyline produced by the skyline operator. The database engine receives queries and associated preferences and, based on a cardinality estimate and a cost estimate, an appropriate skyline generating technique is utilized to produce a skyline representative of the received queries and its associated preferences.
Abstract:
Various embodiments are disclosed relating to database configuration refinement. In an example embodiment, a method is provided that may include determining a size limitation for a database configuration, determining a workload of the database configuration, and making a determination that a size of the database configuration is greater than a size limit. The method may also include applying either a merge process or a reduction process to decrease the size of the database configuration. The merge process may merge a first index/view with a second index/view to produce a merged index/view, for example. The reduction process may delete a first portion of a first view to produce a reduced view.
Abstract:
A database server supports weighted and unweighted sampling of records or tuples in accordance with desired sampling semantics such as with replacement (WR), without replacement (WoR), or independent coin flips (CF) semantics, for example. The database server may perform such sampling sequentially not only to sample non-materialized records, such as those produced as a stream by a pipeline in a query tree for example, but also to sample records, whether materialized or not, in a single pass. The database server also supports sampling over a join of two relations of records or tuples without requiring the computation of the full join and without requiring the materialization of both relations and/or indexes on the join attribute values of both relations.
Abstract:
Assignment algorithm for automatically making assignments between documents and document reviewers for a review process. If the automated assignments need adjusting, a coordinator can manually refine the assignment(s). The assignment algorithm facilitates the automated assignment process based on inputs related to a constraint and/or a preference. The constraints and preferences include, but are not limited to, a conflict of interest, a minimum number of reviews, a maximum number of submissions, a partial assignment, bidding preferences, and health metrics. Once the assignments have been made, histograms can be generated that present an overview of certain health metrics, further allowing refinement of the assignment process.
Abstract:
At least one implementation, described herein, detects fuzzy duplicates and eliminates such duplicates. Fuzzy duplicates are multiple, seemingly distinct tuples (i.e., records) in a database that represent the same real-world entity or phenomenon.
Abstract:
Index structures and query processing framework that enforces a given threshold on the overhead of computing conjunctive keyword queries. This includes a keyword processing algorithm, logic to determine which indexes to materialize, and a probabilistic approach to reducing the overhead for determining which indexes to build. The index structures leverage the fact that the frequency distribution of natural-language text follows a power law. Given a document collection, a set of indexes is proposed for materialization so that the time for intersecting keywords does not exceed a given threshold Δ. When considering the associated space requirement, the additional indexes are limited. Materialization of such a set of indexes for reasonable values of Δ (e.g., the time required to scan 20% of the largest inverted index), at least for a collection of short documents is distributed by the power law.
Abstract:
A method of estimating results of a database query, the results are estimated by performing a sampling of weighted tuples in a database based on a probability of usage of tuples required in executing a workload. A probability is associated with each tuple sampled. An aggregate is computed over values in each sampled tuple while multiplying by the inverses of the probabilities associated with each tuple sampled.