Abstract: A method includes parsing a query to determine a plurality of data processing operations associated with the query and including an AS OF JOIN operation between first time series data in a first table and second time series data in a second table. A query plan of the query is generated. The query plan includes a plurality of nodes corresponding to the plurality of data processing operations. At least one of the plurality of nodes corresponding to the AS OF JOIN operation is modified to generate a modified query plan of the query. The modifying is based on applying a UNION operation on at least a first portion of column data in the first table and the second table to obtain a combined table. Execution of the query by at least one of a plurality of computing nodes is scheduled based on the modified query plan.

Abstract: The subject technology receives a query, the query including a set of statements for performing the query. The subject technology populates a compilation context based at least in part the query. The subject technology invokes a compiler to perform a compilation process based on the compilation context. The subject technology performs a lookup operation on a stored plan cache for an exact match based on information from the compilation context. The subject technology, in response to determining an exact match, determines whether the particular query plan requires re-compilation based on a data dependent optimization. The subject technology determines whether a plan cache entry corresponding to the particular query plan includes a data property constraint. The subject technology determines whether the data property constraint still holds based on a set of data properties.

Abstract: The subject technology receives a query, the query including a set of statements for performing the query. The subject technology populates a compilation context based at least in part the query. The subject technology invokes a compiler to perform a compilation process based on the compilation context. The subject technology performs a lookup operation on a stored plan cache for an exact match based on information from the compilation context. The subject technology, in response to determining an exact match, determines whether the particular query plan requires re-compilation based on a data dependent optimization. The subject technology determines whether a plan cache entry corresponding to the particular query plan includes a data property constraint. The subject technology determines whether the data property constraint still holds based on a set of data properties.

Abstract: Queries executed against a materialized view can execute up to orders of magnitude faster than equivalent queries on a source (or base) table. However, although a query can reference a materialized view directly, a user (e.g., query author) may not know about a relevant materialized view. Moreover, if a source table has multiple materialized views generated, the user may not know which materialized view to reference in the query. Thus, embodiments of the present disclosure provide techniques for automatically rewriting queries directed to a source table to utilize existing materialized views.

Abstract: Queries executed against a materialized view can execute up to orders of magnitude faster than equivalent queries on a source (or base) table. However, although a query can reference a materialized view directly, a user (e.g., query author) may not know about a relevant materialized view. Moreover, if a source table has multiple materialized views generated, the user may not know which materialized view to reference in the query. Thus, embodiments of the present disclosure provide techniques for automatically rewriting queries directed to a source table to utilize existing materialized views.

Abstract: Provided is a system and method for reconstructing and visualizing transformation steps that are performed to an optimized database query. In one example, the method may include receiving a database query including an initial set of execution steps, generating a plurality of alternative sets of execution steps for the database query based on transformations to the initial set of execution steps, selecting an alternative set of execution steps from among the plurality of alternative sets of execution steps based on a performance of the alternative set of execution steps, identifying transformations that are used to transform the initial set of execution steps into the selected alternative set of execution steps, and displaying information about the identified transformations via a user interface.

Abstract: The subject technology receives a query, the query including a set of statements for performing the query. The subject technology populates a compilation context based at least in part the query. The subject technology provides the compilation context to a compiler. The subject technology invokes the compiler to perform a compilation process based on the compilation context, the compilation process comprising performing a lookup operation on a stored plan cache for an exact match based on information from the compilation context, the stored plan cache including a set of stored query plans, and determining whether the exact match of a particular query plan is found in the stored plan cache to avoid compiling the query using the compilation context.

Abstract: Queries executed against a materialized view can execute up to orders of magnitude faster than equivalent queries on a source (or base) table. However, although a query can reference a materialized view directly, a user (e.g., query author) may not know about a relevant materialized view. Moreover, if a source table has multiple materialized views generated, the user may not know which materialized view to reference in the query. Thus, embodiments of the present disclosure provide techniques for automatically rewriting queries directed to a source table to utilize existing materialized views.

Abstract: Queries executed against a materialized view can execute up to orders of magnitude faster than equivalent queries on a source (or base) table. However, although a query can reference a materialized view directly, a user (e.g., query author) may not know about a relevant materialized view. Moreover, if a source table has multiple materialized views generated, the user may not know which materialized view to reference in the query. Thus, embodiments of the present disclosure provide techniques for automatically rewriting queries directed to a source table to utilize existing materialized views.

Abstract: Provided is a system and method for reconstructing and visualizing transformation steps that are performed to an optimized database query. In one example, the method may include receiving a database query including an initial set of execution steps, generating a plurality of alternative sets of execution steps for the database query based on transformations to the initial set of execution steps, selecting an alternative set of execution steps from among the plurality of alternative sets of execution steps based on a performance of the alternative set of execution steps, identifying transformations that are used to transform the initial set of execution steps into the selected alternative set of execution steps, and displaying information about the identified transformations via a user interface.

Abstract: A window operator can be processed according to a variety of techniques that introduce parallelism. Window function sub-results can be calculated separately on different nodes. Overall superior performance can result. Skewness in input data can be accounted for by controlling a degree of parallelism at nodes.

Abstract: According to various embodiments, systems and methods for performing unit conversion operations in a database system are provided. According to embodiments, a database operation will require unit conversion. A number of unit conversions that might be required both before and after performance of the operation can then be estimated. At least some of the data entries implicated by the operation can then be converted from a first unit to a second unit depending on the result of the estimation.

Abstract: Partition-aware calculation of a window operator can be supported. Different nodes can calculate window function sub-results on database partitions locally, in parallel and independently. Recognition of scenarios in which such parallelism is permissible can be performed. Overall superior performance can result.

Abstract: In accordance with aspects of the disclosure, systems and methods are provided for query optimization including generating a knowledge based container for one or more new operators, building a generic operator structure for the knowledge based container generated for each new operator, and applying optimization rules to each new operator based on the generic operator structure built for each new operator to thereby increase extensibility of the query optimizer using a structured query language (SQL).

Abstract: According to various embodiments, systems and methods for performing unit conversion operations in a database system are provided. According to embodiments, a database operation will require unit conversion. A number of unit conversions that might be required both before and after performance of the operation can then be estimated. At least some of the data entries implicated by the operation can then be converted from a first unit to a second unit depending on the result of the estimation.

Abstract: Partition-aware calculation of a window operator can be supported. Different nodes can calculate window function sub-results on database partitions locally, in parallel and independently. Recognition of scenarios in which such parallelism is permissible can be performed. Overall superior performance can result.

Abstract: A window operator can be processed according to a variety of techniques that introduce parallelism. Window function sub-results can be calculated separately on different nodes. Overall superior performance can result. Skewness in input data can be accounted for by controlling a degree of parallelism at nodes.

Abstract: In accordance with aspects of the disclosure, systems and methods are provided for query optimization including generating a knowledge based container for one or more new operators, building a generic operator structure for the knowledge based container generated for each new operator, and applying optimization rules to each new operator based on the generic operator structure built for each new operator to thereby increase extensibility of the query optimizer using a structured query language (SQL).