Teradata Us, Inc.

Ncr Corporation

Cockroach Labs, Inc.

Mark Sirek

Paul Laurence Sinclair

Douglas Paul Brown

Yu Xu

Kuorong Chiang

Heng Yuan

Jeetendra Chaware

Pekka Kostamaa

Andrew E Kimball

Rebecca Taft

Xiaorong Luo

Lawrence H Higa

Methods and systems for locality-aware query planning in a distributed computing system are provided. A query is received from a client device at a gateway node geographically located in a first database region. A plurality of query plans for execution of the query are generated at the gateway node. A first query plan of the query plans is configured to cause communication between the gateway node and a subset of computing nodes that are geographically located in a first external database region that is external to the first database region. A respective cost for each of the query plans is determined. The respective cost for the first query plan is based on an indication of a latency between the first database region and the first external database region. An optimal query plan from the query plans is determined and executed based on each respective cost for the query plans.

Systems and methods for locality-aware query optimization

A database system comprises a processing module, and a storage device communicatively coupled with the processing module and allocated thereto. The storage device stores a base table allocated to the processing module. The processing module receives a database query from a client computer system, and generates a spool based upon a number of columns of a table, and partitions at least one column of the spool based upon the database query received from the client computer system.

System, method, and computer-readable medium for optimizing database queries which use spools during query execution

A method of searching a multilevel partitioned database includes receiving a query data from the multilevel partitioned database. At least for one level partitions are dynamically included. For some levels, partitions may also be statically included for execution of the query. The query is the executed over the partitions that are both dynamically and statically included. In one example, the cost of joining two tables in a multilevel partitioned database includes determining level partitions that can be statically included, estimating level partitions that will be dynamically considered for the join, and determining a cost as a function of the estimated statically included level partitions and estimated dynamically included level partitions.

Product join dynamic partition elimination for multilevel partitioning

A system, method, and computer-readable medium for dynamic detection and management of data skew in parallel join operations are provided. Receipt of an excessive number of redistributed rows by a processing module is detected thereby identifying the processing module as a hot processing module. Other processing modules then terminate redistribution of rows to the hot processing module and maintain rows of a skewed table of the join operation that would be redistributed to the hot processing module in a local spool. Rows of a smaller table that would be redistributed to the hot processing module are duplicated to each processing module involved in the join operation. Rows of tables that are to be redistributed by a processing module to any processing module excluding the hot processing module are redistributed accordingly and maintained locally by the processing module. The join operation is completed by merging results of local join data sets of each processing module.

System, method, and computer-readable medium for dynamic detection and management of data skew in parallel join operations

A database system is able to receive a query that specifies an inequality join involving at least a first relation and a second relation. A plurality of segments of the first relation are sorted in the cache. Each sorted segment of the first relation in the cache is compared with the second relation.

Efficiently performing inequality joins

A method and apparatus provides for the extraction of environment information from a target database system. The environment information includes at least one of cost-related information and random sample statistics. The cost-related information and/or random sample statistics are imported to a test system, where the cost-related information and/or random sample statistics are used in query plan analysis by an optimizer.

Emulating a database system

A method of performing a join includes identifying a join that identifies a first table and a second table. The first table includes a plurality of first table rows. Each of the plurality of first table rows are grouped into one of a plurality of first table partitions. The second table includes one or more second table rows. Each of the plurality of second table rows are grouped into one or more second table partitions. A determination is made as to whether the first table and the second table are joined on equality constraints. The one or more first table rows are joined with the one or more second table rows using a rowkey merge join where equality exists.

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San Diego, CA, United States of America

Mark Sirek