Extended computerized query language syntax for analyzing multiple tabular data arrangements in data-driven collaborative projects
Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform configured to provide one or more computerized tools that facilitate development and management of data projects, including implementation of extended computerized query language syntax to analyze, for example, multiple tabular data arrangements in data-driven collaborative projects. For example, a method may include generating data to present a query editor in a data project interface, receiving data representing a first query command to select one or more subsets of data, identifying in the data representing a second query command a subset of datasets from which to extract the data, and applying a query based on a first query command and a second query command.
1. A method comprising:
generating data to present a query editor in a data project interface;
receiving data representing a first query command to select one or more subsets of data;
receiving data representing a second query command to extract data associated with the one or more subsets of data;
identifying in the data representing the second query command a subset of datasets from which to extract the data;
applying a query based on the first query command and the second query command to the subset of datasets, at least one subset of the datasets including a graph data arrangement formatted as a triple-based data formatted dataset; and
presenting query results in the data projects interface.
2. The method of claim 1 wherein generating the data to present the query editor comprises:
forming the query editor to accept commands configured to access relational data models.
3. The method of claim 2 wherein forming the query editor to accept the commands comprises:
presenting user inputs to form a relational-based query in an SQL-equivalent query language.
4. The method of claim 1 further comprising:
retrieving data for each of the datasets from graph data arrangements, the data originating in multiple tabular data arrangements.
5. The method of claim 4 wherein the multiple tabular data arrangements are independent data arrangements.
6. The method of claim 1 wherein identifying in the data representing the second query command comprises:
determining a data source with which to query.
7. The method of claim 6 wherein determining the data source identifier comprises:
detecting multiple dataset identifiers, each of which is associated with a different dataset.
8. The method of claim 7 wherein detecting the multiple dataset identifiers comprises:
receiving the multiple dataset identifiers associated with a single second query command.
9. The method of claim 6 further comprising:
receiving the data representing the second query command as an instruction to access the data from multiple tabular data arrangements.
10. The method of claim 9 wherein receiving the data as the instruction to access the data from multiple tabular data arrangements comprises:
receiving the instruction to access the data from multiple tabular data arrangements in-situ.
11. The method of claim 1 further comprising:
receiving one or more characters to implement a multi-table syntax.
12. The method of claim 1 wherein identifying in the data representing the second query command comprises:
identifying a portion of multiple file identifiers including a data pattern associated with each of the datasets.
13. The method of claim 12 further comprising:
implementing one or more variable characters as variables for the portion of multiple file identifiers.
14. The method of claim 1 wherein identifying in the data representing the second query command comprises:
detecting one or more explicit selections to target subsets of data in the subset of datasets.
15. The method of claim 14 wherein detecting one or more explicit selections comprises:
detecting one or more column identifiers.
16. The method of claim 1 further comprising:
generating mappings between the data values in an ingested tabular data arrangement and a graph data arrangement;
identifying the datasets as blocks of data; and
applying a graph-based query to the blocks of data.
17. The method of claim 1 wherein presenting the query results in the data projects interface comprises:
presenting the query results in a common interface coextensive with presentation of the query editor.
18. An apparatus comprising:
a memory including executable instructions; and
a processor, responsive to executing the instructions, is configured to:
generate data to present a query editor in a data project interface;
receive data representing a first query command to select one or more subsets of data;
receive data representing a second query command to extract data associated with the one or more subsets of data;
identify in the data representing the second query command a subset of datasets from which to extract the data;
apply a query based on the first query command and the second query command to the subset of datasets, at least one subset of the datasets including a graph data arrangement formatted as a triple-based data formatted dataset; and
present query results in the data projects interface.
19. The apparatus of claim 18 wherein a subset of the instructions to cause the processor to generate data to present the query editor further causes the processor to:
form the query editor to accept commands configured to access relational data models.
20. The apparatus of claim 18 wherein the processor is further configured to:
receive the data representing the second query command as an instruction to access data from multiple tabular data arrangements contemporaneously during query formation.