Download PDF Q For Mortals: A Tutorial In Q Programming, by Jeffry A. Borror
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Q For Mortals: A Tutorial In Q Programming, by Jeffry A. Borror
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Learn the powerful q programming language used in the kdb+ database system developed by Kx Systems, Inc. Based on courses taught by the author at major financial institutions, this tutorial is a tested way to learn the features of q. It assumes no specific programming knowledge and presents this complex language with understandable explanations and many hands-on examples. You will be able to read and write q programs when you finish this book. The q language is both a functional programming language and a vector programming language derived from APL. It is particularly well suited to processing very large time series data. Topics covered include: data types; operations and functions; the basic data structures, lists and dictionaries; tables and keyed tables; joins and queries; commands. There is a special section demonstrating typical queries against trade data. There is also a complete reference to all the built-in functions.
- Sales Rank: #1314487 in Books
- Published on: 2008-03-26
- Dimensions: 10.00" h x 1.08" w x 7.00" l,
- Binding: Paperback
- 478 pages
About the Author
Jeffry Borror has been developing technology solutions in Financial Services for 30 years. After completing his doctorate in mathematics at Columbia University and an initial stint at IBM, Jeff began a managerial career on Wall Street and has worked for a number of major firms in the financial sector. After the 9/11 tragedy he took a year off to perform volunteer work at a not-for-profit organization in lower Manhattan and then founded the consulting firm, Continuux LLC. He began writing a tutorial for the q programming language in 2006, which evolved into the current book. It is the basis of training in q and kdb+ offered by Continuux LLC.
Most helpful customer reviews
8 of 8 people found the following review helpful.
I wish it went beyond syntax
By Dimitri Shvorob
The book is available on the Kx Systems site, so you can make up your mind on whether you like it, and whether the convenience of having a hardcopy is worth the price. I like Borror's writing, but I wish the book gave more space to examples illustrating programming rather than syntax. ('Q Idioms' page on kx.com is what I have in mind). Trying one's hand on code snippets from the Kx site makes the gap painfully obvious.
1 of 1 people found the following review helpful.
Everything you need to get started with KDB+ Q
By Amazon Customer
This book is highly technical in nature and removes the fluff that other tech books often use to fill pages. This book includes everything you needs to know to get started with KDB+ Q and also includes includes more advanced topics that can be used to improve your system already using KDB+ Q. Readers of this book will benefit the most if they are implementing a solution to capture and manage financial tick data in a way that it can be analyzed in real-time analysis or back testing trading strategies. It would help the reader, but is not required, if they have a strong knowledge/education in some or all of the following: quantitative methods, computer science, and financial markets so they can visualize scenarios where KDB+ will be the most advantageous. Personally, I have used this book as a reference on consulting assignments many times. All joking aside, I view this book as being so important to my development, I have two copies. One copy that I carry with me when consulting and the other at home just in case anything happens to the first copy. If you want to stand out in financial IT KDB+ is the niche skill to learn.
5 of 8 people found the following review helpful.
Excellent for handling tick data
By Breno Neri
If you have a massive data set of tick data (Trades and Quotes, for instance), you'll need KDB to store and organize it. KDB is not a relational data base as SQL is, because the data is sorted (Date, then Symbol, then Time Stamp are the natural fields you should use to sort TAQ data). This makes querying the data extremely efficient, which allows you to run very large simulations (backtesting trading strategies, for instance) in viable time. Q is the language that naturally talks to KDB, and it makes writing such large simulations a relatively easy job.
However, Q is somewhat cryptic, so the entry cost is quite high, actually. You'll nee a lot of time practicing it in order to master it well. It's worth, though.
Beware that documentation on Q is scarce. This is not the most well written book, but it's all you got.
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