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Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.
Tree patterns are used in some programming languages as a general tool to process data based on its structure, e.g. C#, [1] F#, [2] Haskell, [3] Java [4], ML, Python, [5] Ruby, [6] Rust, [7] Scala, [8] Swift [9] and the symbolic mathematics language Mathematica have special syntax for expressing tree patterns and a language construct for ...
This originates in ed, where / is the editor command for searching, and an expression /re/ can be used to specify a range of lines (matching the pattern), which can be combined with other commands on either side, most famously g/re/p as in grep ("global regex print"), which is included in most Unix-based operating systems, such as Linux ...
The first is whether a variable-column pair t.a is bound to the column of a relation or a constant, and the second is whether two variable-column pairs are directly or indirectly equated (denoted t.v == s.w). For deriving boundedness we introduce the following reasoning rules: in " v.a = w.b" no variable-column pair is bound,
Explicit table captions (or titles) are recommended for data tables as a best practice; the Wikipedia Manual of Style considers them a high priority for accessibility reasons (screen readers), as a caption is explicitly associated with the table, unlike a normal wikitext heading or introductory sentence. All data tables on Wikipedia require ...
For example, if you need to load data into two databases, you can run the loads in parallel (instead of loading into the first – and then replicating into the second). Sometimes processing must take place sequentially. For example, dimensional (reference) data are needed before one can get and validate the rows for main "fact" tables.
The remarkable thing about the BWT is not that it generates a more easily encoded output—an ordinary sort would do that—but that it does this reversibly, allowing the original document to be re-generated from the last column data. The inverse can be understood this way. Take the final table in the BWT algorithm, and erase all but the last ...
The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich GreenBiz