Functions
A q function is delimited with open and closed curly brackets. All predefined q functions can be used in both infix or prefix notations, whereas user‐defined functions must be called using a prefix notation. Using a consistent namespace also prevents us from naming conflicts and accidentally overrid...
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description | A q function is delimited with open and closed curly brackets. All predefined q functions can be used in both infix or prefix notations, whereas user‐defined functions must be called using a prefix notation. Using a consistent namespace also prevents us from naming conflicts and accidentally overriding existing functions one may have. Adverbs are higher‐order functions that modify the behaviour of functions applied to lists. The verbs @ and . apply a multivariate mapping to a list of arguments, written in prefix or infix form. The chapter describes the differences between the two notations. The concept of try‐catch, or protected evaluation, is implemented with the same @ and . verbs as for the apply functions covered. The chapter presents a few more native functions which cover basic time series operations. The functions are divided into two classes: aggregators and uniform functions. The chapter concludes by summarising the conventions user‐defined functions. |
doi_str_mv | 10.1002/9781119404729.ch3 |
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All predefined q functions can be used in both infix or prefix notations, whereas user‐defined functions must be called using a prefix notation. Using a consistent namespace also prevents us from naming conflicts and accidentally overriding existing functions one may have. Adverbs are higher‐order functions that modify the behaviour of functions applied to lists. The verbs @ and . apply a multivariate mapping to a list of arguments, written in prefix or infix form. The chapter describes the differences between the two notations. The concept of try‐catch, or protected evaluation, is implemented with the same @ and . verbs as for the apply functions covered. The chapter presents a few more native functions which cover basic time series operations. The functions are divided into two classes: aggregators and uniform functions. The chapter concludes by summarising the conventions user‐defined functions.</description><identifier>ISBN: 9781119404750</identifier><identifier>ISBN: 1119404754</identifier><identifier>EISBN: 111940472X</identifier><identifier>EISBN: 9781119404729</identifier><identifier>DOI: 10.1002/9781119404729.ch3</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>adverbs ; aggregators ; apply functions ; namespace ; protected evaluation ; uniform functions ; user‐defined functions</subject><ispartof>Machine Learning and Big Data with kdb+/q, 2019, p.57-79</ispartof><rights>2020 Jan Novotny, Paul A. Bilokon, Aris Galiotos and Frédéric Délèze.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>779,780,784,793,27925</link.rule.ids></links><search><contributor>Novotny, Jan</contributor><contributor>Galiotos, Aris</contributor><contributor>Bilokon, Paul A</contributor><contributor>Délèze, Frédéric</contributor><title>Functions</title><title>Machine Learning and Big Data with kdb+/q</title><description>A q function is delimited with open and closed curly brackets. All predefined q functions can be used in both infix or prefix notations, whereas user‐defined functions must be called using a prefix notation. Using a consistent namespace also prevents us from naming conflicts and accidentally overriding existing functions one may have. Adverbs are higher‐order functions that modify the behaviour of functions applied to lists. The verbs @ and . apply a multivariate mapping to a list of arguments, written in prefix or infix form. The chapter describes the differences between the two notations. The concept of try‐catch, or protected evaluation, is implemented with the same @ and . verbs as for the apply functions covered. The chapter presents a few more native functions which cover basic time series operations. The functions are divided into two classes: aggregators and uniform functions. The chapter concludes by summarising the conventions user‐defined functions.</description><subject>adverbs</subject><subject>aggregators</subject><subject>apply functions</subject><subject>namespace</subject><subject>protected evaluation</subject><subject>uniform functions</subject><subject>user‐defined functions</subject><isbn>9781119404750</isbn><isbn>1119404754</isbn><isbn>111940472X</isbn><isbn>9781119404729</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2019</creationdate><recordtype>book_chapter</recordtype><sourceid/><recordid>eNpjYJA0NNAzNDAw0rc0tzA0NLQ0MTAxN7LUS84wZmTgggtEMDPwIikwNeBg4C0uzjIAajQyNrU0NuBk4HQrzUsuyczPK-ZhYE1LzClO5YXS3AyGbq4hzh665Zk5qZXxqUn5-dnF8YYG8SB741HsjQfaC8LG3Ay6WPSgqq3KLACrL0hJMybHDgDuv0H3</recordid><startdate>20191104</startdate><enddate>20191104</enddate><general>John Wiley & Sons, Ltd</general><scope/></search><sort><creationdate>20191104</creationdate><title>Functions</title></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-wiley_ebooks_10_1002_9781119404729_ch3_ch33</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2019</creationdate><topic>adverbs</topic><topic>aggregators</topic><topic>apply functions</topic><topic>namespace</topic><topic>protected evaluation</topic><topic>uniform functions</topic><topic>user‐defined functions</topic><toplevel>online_resources</toplevel></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Novotny, Jan</au><au>Galiotos, Aris</au><au>Bilokon, Paul A</au><au>Délèze, Frédéric</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Functions</atitle><btitle>Machine Learning and Big Data with kdb+/q</btitle><date>2019-11-04</date><risdate>2019</risdate><spage>57</spage><epage>79</epage><pages>57-79</pages><isbn>9781119404750</isbn><isbn>1119404754</isbn><eisbn>111940472X</eisbn><eisbn>9781119404729</eisbn><abstract>A q function is delimited with open and closed curly brackets. All predefined q functions can be used in both infix or prefix notations, whereas user‐defined functions must be called using a prefix notation. Using a consistent namespace also prevents us from naming conflicts and accidentally overriding existing functions one may have. Adverbs are higher‐order functions that modify the behaviour of functions applied to lists. The verbs @ and . apply a multivariate mapping to a list of arguments, written in prefix or infix form. The chapter describes the differences between the two notations. The concept of try‐catch, or protected evaluation, is implemented with the same @ and . verbs as for the apply functions covered. The chapter presents a few more native functions which cover basic time series operations. The functions are divided into two classes: aggregators and uniform functions. The chapter concludes by summarising the conventions user‐defined functions.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/9781119404729.ch3</doi><tpages>23</tpages></addata></record> |
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identifier | ISBN: 9781119404750 |
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language | eng |
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source | Ebook Central - Academic Complete; O'Reilly Online Learning: Academic/Public Library Edition |
subjects | adverbs aggregators apply functions namespace protected evaluation uniform functions user‐defined functions |
title | Functions |
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