摘要:
Data source queries may be specified in various languages, such as SQL, XQuery, and object-oriented languages, and each language may have various linguistic features that enable different types of queries. It may be advantageous to formulate mixed language queries having portions specified in a first language and portions specified in a second language, and to provide mixed language query evaluation components that can parse portions of queries of different languages. It may also be advantageous to permit the translation of single language queries into multiple languages to be parsed by such mixed language query evaluation components. Such techniques may permit queries to utilize linguistic features and processing techniques of one language that are less efficient, less direct, or simply unavailable in another language.
摘要:
Data source queries may be specified in various languages, such as SQL, XQuery, and object-oriented languages, and each language may have various linguistic features that enable different types of queries. It may be advantageous to formulate mixed language queries having portions specified in a first language and portions specified in a second language, and to provide mixed language query evaluation components that can parse portions of queries of different languages. It may also be advantageous to permit the translation of single language queries into multiple languages to be parsed by such mixed language query evaluation components. Such techniques may permit queries to utilize linguistic features and processing techniques of one language that are less efficient, less direct, or simply unavailable in another language.
摘要:
Queries targeting various data sources are processed in a query processing pipeline that parses the query into a set of operations (e.g., an expression tree or a translated SQL query) using a set of query operators, each handling a particular type of operation. The query operators are often designed in an unspecialized manner, such that each query operator handles one query operation in an atomic, generic manner (e.g., sorting generic data items for an ORDER BY clause.) More efficient queries may be devised by including specialized queries that operate in common but special cases, such as a sorting of a particular data type (e.g., a floating-point number sort) or a sequence of two or more operations that are often performed together (e.g., a WHERE test of an attribute followed by a SELECT of the same attribute.) The use of specialized operators may result in the formulation of more efficient queries.
摘要:
Queries targeting various data sources are processed in a query processing pipeline that parses the query into a set of operations (e.g., an expression tree or a translated SQL query) using a set of query operators, each handling a particular type of operation. The query operators are often designed in an unspecialized manner, such that each query operator handles one query operation in an atomic, generic manner (e.g., sorting generic data items for an ORDER BY clause.) More efficient queries may be devised by including specialized queries that operate in common but special cases, such as a sorting of a particular data type (e.g., a floating-point number sort) or a sequence of two or more operations that are often performed together (e.g., a WHERE test of an attribute followed by a SELECT of the same attribute.) The use of specialized operators may result in the formulation of more efficient queries.
摘要:
The utilization of data services (such as web services) may involve the invocation of services, which may reduce performance and overburden the server. In some scenarios, the invocation may be specified in a language that does not support batch invocation, but it may not be feasible to re-code the invocations in a language that supports batching. Instead, the service invocations may be automatically translated into a batch logic specified in a batch-capable language and sent to the service as a batch. For example, a local proxy may receive a language-integrated query having two or more service invocations, compile the query into an expression tree including the two or more invocations, and send the expression tree to the service host to achieve the batch processing of the service invocations.
摘要:
An operation (such as a relational query) may be processed on a processing engine (such as a relational database server) on behalf of a client. A conventional processing involves the delivery of the operation to the processing engine, which executes the entire operation to completion and returns a result data set. It may be more efficient to allocate part of the operation to be performed on the client, but a developer may be unable or unavailable to rewrite the operation in a distributed manner. Instead, the operation may be automatically partitioned into a pre-engine client portion, a processing engine portion, and a client portion, and the instructions of each portion may be automatically allocated respectively to the client, the server, and the client. The partitioning may be adjusted to conserve computing resources, such as bandwidth and storage, and the instructions may be reordered to improve the processing of the operation.
摘要:
An operation (such as a relational query) may be processed on a processing engine (such as a relational database server) on behalf of a client. A conventional processing involves the delivery of the operation to the processing engine, which executes the entire operation to completion and returns a result data set. It may be more efficient to allocate part of the operation to be performed on the client, but a developer may be unable or unavailable to rewrite the operation in a distributed manner. Instead, the operation may be automatically partitioned into a pre-engine client portion, a processing engine portion, and a client portion, and the instructions of each portion may be automatically allocated respectively to the client, the server, and the client. The partitioning may be adjusted to conserve computing resources, such as bandwidth and storage, and the instructions may be reordered to improve the processing of the operation.
摘要:
The utilization of data services (such as web services) may involve the invocation of services, which may reduce performance and overburden the server. In some scenarios, the invocation may be specified in a language that does not support batch invocation, but it may not be feasible to re-code the invocations in a language that supports batching. Instead, the service invocations may be automatically translated into a batch logic specified in a batch-capable language and sent to the service as a batch. For example, a local proxy may receive a language-integrated query having two or more service invocations, compile the query into an expression tree including the two or more invocations, and send the expression tree to the service host to achieve the batch processing of the service invocations.
摘要:
Queries against data sources (such as language-integrated queries to be applied against relational databases) may be prepared for processing by a query processing pipeline. This pipeline performs services including transforming the query into a form more easily applied by the data source, e.g., into SQL, by matching query terms with query operators configured to handle various query operations. Many query processing pipelines include single-item query operators that perform individual operations (e.g., an updating query operator that specifies an updating of individual records of a table.) An integrated query pipeline may be devised that includes both single-item query operators and multiple-item query operators that specify operations on sets of data items. An integrated query processing pipeline may analyze the query to determine whether a single-item or multiple-item operation is specified in order to select an appropriate query operator, which may improve the efficiency and performance of the data source querying.
摘要:
Queries against data sources (such as language-integrated queries to be applied against relational databases) may be prepared for processing by a query processing pipeline. This pipeline performs services including transforming the query into a form more easily applied by the data source, e.g., into SQL, by matching query terms with query operators configured to handle various query operations. Many query processing pipelines include single-item query operators that perform individual operations (e.g., an updating query operator that specifies an updating of individual records of a table.) An integrated query pipeline may be devised that includes both single-item query operators and multiple-item query operators that specify operations on sets of data items. An integrated query processing pipeline may analyze the query to determine whether a single-item or multiple-item operation is specified in order to select an appropriate query operator, which may improve the efficiency and performance of the data source querying.