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sql editor  (LabKey Corporation)

 
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    Structured Review

    LabKey Corporation sql editor
    LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A <t>SQL</t> query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.
    Sql Editor, supplied by LabKey Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/sql editor/product/LabKey Corporation
    Average 90 stars, based on 1 article reviews
    sql editor - by Bioz Stars, 2026-05
    90/100 stars

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    1) Product Images from "LabKey Server: An open source platform for scientific data integration, analysis and collaboration"

    Article Title: LabKey Server: An open source platform for scientific data integration, analysis and collaboration

    Journal: BMC Bioinformatics

    doi: 10.1186/1471-2105-12-71

    LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A SQL query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.
    Figure Legend Snippet: LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A SQL query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.

    Techniques Used: Sequencing

    Example of creating a custom SQL view . This figure demonstrates how a custom SQL view can add a calculated column to a joined view and label the column using custom metadata. Part A of this figure shows LabKey Server's schema browser, which allows a developer to view, add or edit custom queries. Part B shows how the SQL source editor has been used to add a calculated column to a table as part of a custom query. It also shows how the table metadata editor has been used to edit the column's properties and add a custom title. The grid view produced by this custom query is shown in C.
    Figure Legend Snippet: Example of creating a custom SQL view . This figure demonstrates how a custom SQL view can add a calculated column to a joined view and label the column using custom metadata. Part A of this figure shows LabKey Server's schema browser, which allows a developer to view, add or edit custom queries. Part B shows how the SQL source editor has been used to add a calculated column to a table as part of a custom query. It also shows how the table metadata editor has been used to edit the column's properties and add a custom title. The grid view produced by this custom query is shown in C.

    Techniques Used: Produced



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    LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A <t>SQL</t> query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.
    Sql Editor, supplied by LabKey Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/sql editor/product/LabKey Corporation
    Average 90 stars, based on 1 article reviews
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    Image Search Results


    LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A SQL query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.

    Journal: BMC Bioinformatics

    Article Title: LabKey Server: An open source platform for scientific data integration, analysis and collaboration

    doi: 10.1186/1471-2105-12-71

    Figure Lengend Snippet: LabKey Server query service . The query service can be called on by LabKey Server's APIs or web-based interface. In either case, the service receives a request for one of the following: • A table and a column list. A column list can include columns from the requested table or columns from related tables. • A SQL query based on pseudo-tables known to the query service. For an API call, the following sequence of events occurs: 1. When the request is received by the server's API layer, the layer checks folder security and translates the request into calls to the query service. 2. The query service then uses schema information describing physical tables and pseudo-tables to translate the input query into a SQL query of physical tables. The query is formulated in the dialect understood by the underlying relational database. Schema information is supplied by other LabKey modules. 3. The database returns a tabular result. 4. The tabular result is annotated with additional information about the columns ( e.g . user-friendly label, description and formatting hints). 5. The appropriate LabKey client library converts this standard data/metadata into a form easily understood by the client language. For example, an R dataset would be returned as the result of a call by an R client API.

    Article Snippet: Figure shows how LabKey Server's SQL editor enables the construction of more sophisticated queries, including the inclusion of calculated columns and custom metadata.

    Techniques: Sequencing

    Example of creating a custom SQL view . This figure demonstrates how a custom SQL view can add a calculated column to a joined view and label the column using custom metadata. Part A of this figure shows LabKey Server's schema browser, which allows a developer to view, add or edit custom queries. Part B shows how the SQL source editor has been used to add a calculated column to a table as part of a custom query. It also shows how the table metadata editor has been used to edit the column's properties and add a custom title. The grid view produced by this custom query is shown in C.

    Journal: BMC Bioinformatics

    Article Title: LabKey Server: An open source platform for scientific data integration, analysis and collaboration

    doi: 10.1186/1471-2105-12-71

    Figure Lengend Snippet: Example of creating a custom SQL view . This figure demonstrates how a custom SQL view can add a calculated column to a joined view and label the column using custom metadata. Part A of this figure shows LabKey Server's schema browser, which allows a developer to view, add or edit custom queries. Part B shows how the SQL source editor has been used to add a calculated column to a table as part of a custom query. It also shows how the table metadata editor has been used to edit the column's properties and add a custom title. The grid view produced by this custom query is shown in C.

    Article Snippet: Figure shows how LabKey Server's SQL editor enables the construction of more sophisticated queries, including the inclusion of calculated columns and custom metadata.

    Techniques: Produced