Difference between revisions of "Programming/Kdb/History"

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Brian Conlon, Chief Executive Officer of FD, commented: "Since we acquired a controlling interest in Kx Systems in October 2014 we have invested heavily across our business to target multiple new industries. The agreement to acquire 100% of Kx Systems provides certainty for the Group and its shareholders as we seek to realise the considerable potential we see for further growth."
Brian Conlon, Chief Executive Officer of FD, commented: "Since we acquired a controlling interest in Kx Systems in October 2014 we have invested heavily across our business to target multiple new industries. The agreement to acquire 100% of Kx Systems provides certainty for the Group and its shareholders as we seek to realise the considerable potential we see for further growth."
</blockquote>
=Shakti=
On 27 November 2018 <span class="plainlinks">[https://www.efinancialcareers.co.uk/news/author/sarahbutcher Sarah Butcher]</span> wrote an article in <span class="plainlinks">[https://www.efinancialcareers.co.uk/ eFinancialCareers]</span> entitled <span class="plainlinks">[https://www.efinancialcareers.co.uk/news/2019/11/shakti-arthur-whitney The new data platform from the reclusive genius of banking IT]</span>:
<blockquote>
Released last month, Whitney's new creation is called Shakti (after the name for primordial cosmic energy in Hinduism). According to Whitney, Shakti boasts a level of sophistication that will make it, "a new standard for data storage and analysis within financial services and beyond."
Whitney is reclusive these days and doesn't talk to the press, so Shakti's New York-based director of engineering (and ex-Nomura and Barclays kdb specialist) Fintan Quill is flying the flag in public. "High-data capture rates, combined with low-latency query response times make Shakti the perfect platform for trade signal calculation, pre/post-trade risk, real-time surveillance, back-testing among other things," enthuses Quill.
The new platform is also optimal for cloud computing: "The small memory footprint allows for fast deployment and processing of distributed elastic workloads." It can work with all kinds of datasets, including numerical, temporal and text data, whether structured or not.
Shakti's secret is parallelism, which enables it to work faster than predecessors. Parallelism is built into most of its primitive functions and can expand to multiple jobs and machines via what Quill describes as, "a custom-built interprocess communication protocol as well as a native fork-execution model."
These allow it to function in highly distributed high performance computing (HPC) workloads, while single instruction, multiple data (SIMD) technology allows Shakti to function within the 256 or 512-bit register widths of most modern computers. As a result (says Quill), the platform boasts a combination of low cost and very high performance.
If you think you might want to work with Shakti, it will help to be proficient at programming in Python&mdash;The system comes with a Python interface that merges those two interpreters into a single process. "This allows Python developers access to the extremely fast data-handling capabilities of Shakti," says Quill, who says the interface means there's "zero-copy" between the two systems, which reduces processing time.
Shakti is very new and it's not clear who&mdash;if anyone&mdash;has bought into it already. But after a display of its abilities in London and New York in the past six months, the platform may yet get some takers. Last week, it added a COO, Abby Gruen, who joined from Kx.
Quill suggests that any system involving Arthur Whitney should not go ignored. Morgan Stanley, after all, is still using A+ years after Whitney left. "The simple yet intelligent ideas underlying the APL-derived languages inspired by Ken Iverson have shown the robustness to pass the test of time," says Quill. Shakti is only just starting out, but Whitney's history suggests it might be around for a while to come.
</blockquote>
</blockquote>

Revision as of 08:35, 30 June 2021

Kdb+ is a database built on top of an interpreter for a programming language, q, created by Arthur Whitney with the aim of addressing the inability of traditional relational databases to keep up with increasing volumes of data and speed requirements.

APL

Born and raised in Canada, Iverson received his doctorate in 1954 from Harvard University. There he served as Assistant Professor of Applied Mathematics from 1955 to 1960. He then joined International Business Machines Corp. and in 1970 was named an IBM Fellow in honour of his contribution to the development of APL.

Applied mathematics is largely concerned with the design and analysis of explicit procedures for calculating the exact or approximate values of various functions. Such explicit procedures are called algorithms or programs. Because an effective notation for the description of programs exhibits considerable syntactic structure, it is called a programming language.

In 1979, Iverson received the Turing Award for his work on APL.

The importance of nomenclature, notation, and language as tools of thought has long been recognized. In chemistry and in botany, for example, the establishment of systems of nomenclature by Lavoisier and Linnaeus did much to stimulate and to channel later investigation. Concerning language, George Boole in his Laws of Thought asserted "That language is an instrument of human reason, and not merely a medium for the expression of thought, is a truth generally admitted."

Mathematical notation provides perhaps the best-known and best-developed example of language used consciously as a tool of thought. Recognition of the important role of notation in mathematics is clear from the quotations from mathematicians given in Cajori's A History of Mathematical Notations. They are well worth reading in full, but the following excerpts suggest the tone:

By relieving the brain of all unnecessary work, a good notation sets it free to concentrate on more advanced problems, an in effect increases the mental power of the race.

A. N. Whitehead

The quantity of meaning compressed into small space by algebraic signs, is another circumstance that facilitates the reasonings we are accutomed to carry on by their aid.

Charles Babbage

Nevertheless, mathematical notation has serious deficiencies. In particular, it lacks universality, and must be interpreted differently according to the topic, according to the author, and even according to the immediate context. Programming languages, because they were designed for the purpose of directing computers, offer important advantages as tools of thought. Not only are they universal (general-purpose), but they are also executable and unambiguous. Executability makes it possible to use computers to perform extensive experiments on ideas expressed in a programming language, and the lack of ambiguity makes possible precise thought experiments. In other respects, however, most programming languages are decidedly inferior to mathematical notation and are little used as tools of thought in ways that would be considered significant by, say, an applied mathematician.

The thesis of the present paper is that the advantages of executability and universality found in programming languages can be effectively combined, in a single coherent language, with the advantages offered by mathematical notation.

J

In one of the essays on the J website Roger Hui tells the story of the J programming language.

One summer weekend in 1989, Arthur Whitney visited Ken Iverson at Kiln Farm and produced—on one page and in one afternoon—an interpreter fragment on the AT&T 3B1 computer. I studied this interpreter for about a week for its organization and programming style; and on Sunday, August 27, 1989, at about four o'clock in the afternoon, wrote the first line of code that became the implementation described in this document.

The essay then goes on to quote Whitney's one-page interpreter fragment:

typedef char C;typedef long I;
typedef struct a{I t,r,d[3],p[2];}*A;
#define P printf
#define R return
#define V1(f) A f(w)A w;
#define V2(f) A f(a,w)A a,w;
#define DO(n,x) {I i=0,_n=(n);for(;i<_n;++i){x;}}
I *ma(n){R(I*)malloc(n*4);}mv(d,s,n)I *d,*s;{DO(n,d[i]=s[i]);}
tr(r,d)I *d;{I z=1;DO(r,z=z*d[i]);R z;}
A ga(t,r,d)I *d;{A z=(A)ma(5+tr(r,d));z->t=t,z->r=r,mv(z->d,d,r);
 R z;}
V1(iota){I n=*w->p;A z=ga(0,1,&n);DO(n,z->p[i]=i);R z;}
V2(plus){I r=w->r,*d=w->d,n=tr(r,d);A z=ga(0,r,d);
 DO(n,z->p[i]=a->p[i]+w->p[i]);R z;}
V2(from){I r=w->r-1,*d=w->d+1,n=tr(r,d);
 A z=ga(w->t,r,d);mv(z->p,w->p+(n**a->p),n);R z;}
V1(box){A z=ga(1,0,0);*z->p=(I)w;R z;}
V2(cat){I an=tr(a->r,a->d),wn=tr(w->r,w->d),n=an+wn;
 A z=ga(w->t,1,&n);mv(z->p,a->p,an);mv(z->p+an,w->p,wn);R z;}
V2(find){}
V2(rsh){I r=a->r?*a->d:1,n=tr(r,a->p),wn=tr(w->r,w->d);
 A z=ga(w->t,r,a->p);mv(z->p,w->p,wn=n>wn?wn:n);
 if(n-=wn)mv(z->p+wn,z->p,n);R z;}
V1(sha){A z=ga(0,1,&w->r);mv(z->p,w->d,w->r);R z;}
V1(id){R w;}V1(size){A z=ga(0,0,0);*z->p=w->r?*w->d:1;R z;}
pi(i){P("%d ",i);}nl(){P("\n");}
pr(w)A w;{I r=w->r,*d=w->d,n=tr(r,d);DO(r,pi(d[i]));nl();
 if(w->t)DO(n,P("< ");pr(w->p[i]))else DO(n,pi(w->p[i]));nl();}

C vt[]="+{~<#,";
A(*vd[])()={0,plus,from,find,0,rsh,cat},
 (*vm[])()={0,id,size,iota,box,sha,0};
I st[26]; qp(a){R  a>='a'&&a<='z';}qv(a){R a<'a';}
A ex(e)I *e;{I a=*e;
 if(qp(a)){if(e[1]=='=')R st[a-'a']=ex(e+2);a= st[ a-'a'];}
 R qv(a)?(*vm[a])(ex(e+1)):e[1]?(*vd[e[1]])(a,ex(e+2)):(A)a;}
noun(c){A z;if(c<'0'||c>'9')R 0;z=ga(0,0,0);*z->p=c-'0';R z;}
verb(c){I i=0;for(;vt[i];)if(vt[i++]==c)R i;R 0;}
I *wd(s)C *s;{I a,n=strlen(s),*e=ma(n+1);C c;
 DO(n,e[i]=(a=noun(c=s[i]))?a:(a=verb(c))?a:c);e[n]=0;R e;}

main(){C s[99];while(gets(s))pr(ex(wd(s)));}

A+

The A+ website tells the story of the A+ programming language:

A+ is a descendent of the language "A" created in 1988 by Arthur Whitney at Morgan Stanley. At the time, various departments had a significant investment in APL applications and talent, APL being a language well-suited to the manipulation of large arrays of numbers. As technology was moving from the mainframe to distributed systems, there was a search for a suitable APL implementation to run on SunOS, the distributed platform of the period. Not happy with the systems evaluated, Arthur, motivated by management, wrote one geared to the business: large capacity, high performance. He was joined in his efforts as the language took on graphics, systems' interfaces, utility support, and an ever-widening user community. Over the course of the next few years, as the business began to reap tangible value from the efforts, the pieces were shaped into a consistent whole and became A+. The "+" referred to the electric graphical user interface. An A+ development group was formally created in 1992.

A+ soon became the language of choice for development of Fixed Income applications. It offered familiarity to the APL programmers, the advantages of an interpreter in a fast-paced development arena and admirable floating-point performance. A significant driver was that many of Morgan Stanley's best and brightest were the developers and supporters of the language. Through their practical application of technical values, they instilled fervent enthusiasm in talented programmers, regardless of their programming language backgrounds.

FD

On 2 July 2018, First Derivatives plc announced that it was to buy out minority Kx Systems shareholders:

FD (AIM:FDP.L, ESM:DFP.I) announces that it has reached agreement with the minority shareholders of Kx Systems, Inc. ("Kx Systems"), a subsidiary of the Group, regarding the acquisition by FD of their entire remaining shareholding (the "Transaction"). Upon completion of the Transaction, which is expected to take place on or before 29 June 2019, FD will own 100% of the issued share capital of Kx Systems.

Terms of the Transaction

FD has agreed to acquire the remaining 600,022 Kx Systems shares that it doesn't already own from the minority shareholders, namely Arthur Whitney and Janet Lustgarten, who are co-founders and current directors of Kx Systems, and their associated persons. The aggregate consideration is $53.8m in cash, to be financed from FD's available facilities. The terms of the transaction are in line with those agreed between FD and the minority shareholders in October 2014, and include a payment of $12.0m in lieu of anticipated dividends to the minority shareholders for the period up to 31 October 2021.

Brian Conlon, Chief Executive Officer of FD, commented: "Since we acquired a controlling interest in Kx Systems in October 2014 we have invested heavily across our business to target multiple new industries. The agreement to acquire 100% of Kx Systems provides certainty for the Group and its shareholders as we seek to realise the considerable potential we see for further growth."

Shakti

On 27 November 2018 Sarah Butcher wrote an article in eFinancialCareers entitled The new data platform from the reclusive genius of banking IT:

Released last month, Whitney's new creation is called Shakti (after the name for primordial cosmic energy in Hinduism). According to Whitney, Shakti boasts a level of sophistication that will make it, "a new standard for data storage and analysis within financial services and beyond."

Whitney is reclusive these days and doesn't talk to the press, so Shakti's New York-based director of engineering (and ex-Nomura and Barclays kdb specialist) Fintan Quill is flying the flag in public. "High-data capture rates, combined with low-latency query response times make Shakti the perfect platform for trade signal calculation, pre/post-trade risk, real-time surveillance, back-testing among other things," enthuses Quill.

The new platform is also optimal for cloud computing: "The small memory footprint allows for fast deployment and processing of distributed elastic workloads." It can work with all kinds of datasets, including numerical, temporal and text data, whether structured or not.

Shakti's secret is parallelism, which enables it to work faster than predecessors. Parallelism is built into most of its primitive functions and can expand to multiple jobs and machines via what Quill describes as, "a custom-built interprocess communication protocol as well as a native fork-execution model."

These allow it to function in highly distributed high performance computing (HPC) workloads, while single instruction, multiple data (SIMD) technology allows Shakti to function within the 256 or 512-bit register widths of most modern computers. As a result (says Quill), the platform boasts a combination of low cost and very high performance.

If you think you might want to work with Shakti, it will help to be proficient at programming in Python—The system comes with a Python interface that merges those two interpreters into a single process. "This allows Python developers access to the extremely fast data-handling capabilities of Shakti," says Quill, who says the interface means there's "zero-copy" between the two systems, which reduces processing time.

Shakti is very new and it's not clear who—if anyone—has bought into it already. But after a display of its abilities in London and New York in the past six months, the platform may yet get some takers. Last week, it added a COO, Abby Gruen, who joined from Kx.

Quill suggests that any system involving Arthur Whitney should not go ignored. Morgan Stanley, after all, is still using A+ years after Whitney left. "The simple yet intelligent ideas underlying the APL-derived languages inspired by Ken Iverson have shown the robustness to pass the test of time," says Quill. Shakti is only just starting out, but Whitney's history suggests it might be around for a while to come.