Memorative art of Streams - stream

I'm trying to understand Streams.
How comparable is a stream (computer science) with a stream (water). This is how I picture them in my mind:
Now, I was wondering whether this thought is correct. If it's not a correct way, why isn't this a correct way?

In information science, there is a specific meaning attached to the notation of two adjacent boxes, one with a value and another with an arrow pointing to another box pair. It stands for a node of a singly-linked list (or just "linked list".) This is an object which contains a value (otherwise known as payload) and a pointer to the next node of the list.
Linked lists have very little in common with streams. True, both linked lists and streams are structures that can only be traversed sequentially, but the similarities end there. Linked lists are not implemented as streams, and although in theory a stream may be implemented as a linked list, it would be inefficient, so it is usually not done this way. When reading from a stream you can at any time only see the payload of the item that you have just read, you have no notion of a pointer to another item, and you cannot rearrange items by manipulating pointers.
So, no, this is not a correct way of picturing a stream in information science.
Generally, real-world metaphors are not useful at all for understanding information science entities. You need to understand the definition of the entity exclusively in information science terms, and once you have achieved this, then you can use a real-world metaphor as a name for it, nothing more.
Take for example a "file". Before computers, a file was a folder made of manila paper, containing papers. With the advent of computers, a file is an array of bytes stored on the disk, representing data or code or both, following a format which may or may not be known, and which may be standard or it may only be interpretable by specialized software. Knowing the old meaning of the word "file" does not help you at all in figuring out what a file is for computers. We just use the word "file" for convenience. We might even imagine a manila folder in our mind. But it is just a visual mnemonic, bearing no relation to reality.

Related

Sharing atoms between http-connected erlang clusters

We have a few non-erlang-connected clusters in our infrastructure and currently use term_to_binary to encode erlang terms for messages between the clusters. On the receiving side we use binary_to_term(Bin, [safe]) to only convert to existing atoms (should there be any in the message).
Occasionally (especially after starting a new cluster/stack), we run into the problem that there are partially known atoms encoded in the message, i.e. the sending cluster knows this atom, but the receiving does not. This can be for various reasons, most common is that the receiving node simply has not loaded a module containing some record definition. We currently employ some nasty work-arounds which basically amount to maintaining a short-ish list of potentially used atoms, but we're not quite happy with this error-prone approach.
Is there a smart way to share atoms between these clusters? Or is it recommended to not use the binary format for such purposes?
Looking forward to your insights.
I would think hard about why non-Erlang nodes are sending atom values in the first place. Most likely there is some adjustment that can be made to the protocol being used to communicate -- or most often there is simply not a real protocol defined and the actual protocol in use evolved organically over time.
Not knowing any details of the situation, there are two solutions to this:
Go deep and use an abstract serialization technique like ASN.1 or JSON or whatever, using binary strings instead of atoms. This makes the most sense when you have a largish set of well understood, structured data to send (which may wrap unstructured or opaque data).
Remain shallow and instead write a functional API interface for the processes/modules you will be sending to/calling first, to make sure you fully understand what your protocol actually is, and then back that up by making each interface call correspond to a matching network message which, when received, dispatches the same procedures an API function call would have.
The basic problem is the idea of non-Erlang nodes being able to generate atoms that the cluster may not be aware of. This is a somewhat sticky problem. In many cases the places where you are using atoms you can instead use binaries to similar effect and retain the same semantics without confusing the runtime. Its the difference between {<<"new_message">>, Data} and {new_message, Data}; matching within a function head works the same way, just slightly more noisy syntactically.

How to extract entities from html using natural language processing or other technique

I am trying to parse entities from web pages that contain a time, a place, and a name. I read a little about natural language processing, and entity extraction, but I am not sure if I am heading down the wrong path, so I am asking here.
I haven't started implementing anything yet, so if certain open source libraries are only suitable for a specific language, that is ok.
A lot of times the data would not be found in sentences, but instead in html structures like lists (e.g. 2013-02-01 - Name of Event - Arena Name).
The structure of the webpages will be vastly different (some might use lists, some might put them in a table, etc.).
What topics can I research to learn more about how to achieve this?
Are there any open source libraries that take into account the structure of html when doing entity extraction?
Would extracting these (name, time, place) entities from html be better (or even possible) with machine vision where the CSS styling might make it easier to differentiate important parts (name, time, location) of the unstructured text?
Any guidance on topics/open source projects that I can research would help I think.
Many programming languages have external libraries that generate canonical date-stamps from various formats (e.g. in Java, using the SimpleDateFormat). As you say, the structure of the web-pages will be vastly different, but date can be expressed using a small number of variations only, so writing down the regular expressiongs for a few (let's say, half-a-dozen) formats will enable extraction of dates from most, if not all, HTML pages.
Extraction of places and names is harder, however. This is where natural language processing will have to come in. What you are looking for is a Named Entity Recognition system. One of the best open source NER systems is the Standford NER. Before using, you should check out their online demo. The demo has three classifiers (for English) that you can choose from. For most of my tasks, I find their english.all.3class.distsim classifier to be quite accurate.
Note that an NER performs well when the places and names you extract are occurring in sentences. If they are going to occur in HTML labels, this approach is probably not going to be very helpful.

File Path Name or URL analysis

I am looking for information on tools, methods, techniques for analysis of file path names. I am not talking file size, read/write times, or file types, but analysis of the path or URL it self.
I am only aware of basic word frequency text tools or methods, but I am wondering if there is something more advanced that people use/apply to this to try and mine extra information out of them.
Thanks!
UPDATE:
Here is the most narrow example of what I would want. OK, so I have some full path names as strings like this:
F:\Task_Order_Projects\TO_01_NYS\Models\MapShedMaps\Random_File1.doc
F:\Task_Order_Projects\TO_01_NYS\Models\MapShedMaps\Random_File2.doc
F:\Task_Order_Projects\TO_01_NYS\Models\MapShedMaps\Random_File3.doc
F:\Task_Order_Projects\TO_01_NYS\Models\MapShedMaps\Random_File4.doc
F:\Task_Order_Projects\TO_01_NYS\Models\MapShedMaps\Random_File5.doc
F:\Task_Order_Projects\TO_02_NYS\Models\MapShedMaps\Random_File1.doc
F:\Task_Order_Projects\TO_02_NYS\Models\MapShedMaps\Random_File2.doc
F:\Task_Order_Projects\TO_02_NYS\Models\MapShedMaps\Random_File3.doc
F:\Task_Order_Projects\TO_02_NYS\Models\MapShedMaps\Random_File4.doc
F:\Task_Order_Projects\TO_02_NYS\Models\MapShedMaps\Random_File5.doc
What I want to know is that the folder MapShedMaps appears "uniquely" 2 times. If I do frequency on the strings I would get 10 appearances. The issues is that I don’t know what level in the directory this is important, so I would like a unique count at each level of the directory based on what I am describing.
This is an extremely broad question so it is difficult for me to give you a per say "Answer" but I will give you my first thoughts on this.
First,
the Regular expression class of .NET is extremely useful for parsing large amounts of information. It is so powerful that it will easily confuse the impatient, however once mastered it can be used across text editors, .NET and pretty much any other respectable language I believe. This would allow you to search strings and separate it into directories. This could be overkill depending on how you use it, but its a thought. Here is a favorite link of mine to try out some regular expressions.
Second,
You will need a database, I prefer to use SQL. Look into how to connect to databases and create databases. With this database you can store all the fields abstracted from your original path entered. Such as a parent directory, child directory, common file types accessed. Just have a field for each one of these and through queries you can form a hypothesis as to redundancy.
Third,
I don't know if its easily accessible but you might look into whether windows stores accessed file history. It seems to have some inkling as to which files have been opened in the past. So there may be a resource in windows which already stores much of the information you would be storing in your database. If you could find a way to access this information. Parse it with regular expressions and resubmit it to the database of your application. You could control the WORLD! j/k... You could get a pretty good prediction as to user access patterns though.
Fourth,
I always try to stick with what I have available. If .NET is sitting in front of you, hammer away at what your trying to do. If you reach a wall. At least your making forward progress. In today's motion towards object orientated programming, you can usually change data collected by one program into an acceptable format for another. You just gotta dig a little.
Oh and btw, Coursera.com is actually doing a free class on machine learning and algorithms. You might want to check it out or reference it for prediction formulas.
Good Luck.
I wanted to post this as a comment but SO kept editing the double \ to \ and it is important there are two because \ is a key character, without another \ to escape it, regex will interpret it as a command.
Hey I just wanted to let you know I've been playing with some regex... I know a pretty easy way to code this up in VB.net and I'll post that as my second answer but I wanted you to check out back-references. If the part between parenthesis matches it captures that text and moves on to the second query for instance....
F:\\(directory1)?(directory2)?(directory3)?
You could use these matches to find out how many directories each parent directory has under it. Are you following me? Here is a reference.

What's a succinct, useful and efficient way to store large time-series in F#?

I'm currently learning F# and I'm exploring using it to analyse financial time-series. Can anyone recommend a good data structure to store time-series data in?
F# offers a rich selection of native types and I'm looking for a some simple combination that would provide an elegant, succinct and efficient solution.
I'm looking store tick data, which consists of millions of records each with a time stamp, and several (~5-20) fields of numerical and textual data, with possible missing values.
My first thoughts are perhaps a sequence of tuples or records, but I was wondering if someone could kindly suggest something that has worked well in the real world.
EDIT:
A few extra points for clarification:
The common operations that I'm likely to require are:
Time based lookup - i.e. find the most recent data point at a given time
Time based joins
Appends
(Updates and deletes are going to be rare. )
I should make it clear I'm exploring using F# primarily as an interactive tool for research, with the ability to compile as a (really big) added bonus.
ANOTHER EDIT:
I should also have mentioned, my role/use of F# and this data is purely within research not development. The intention being that once we understand the data (and what we want to do with it) better then we can later specify tools that our developers would build. Such as data warehouses etc. at which we'd start using their data structures etc.
Although, I am concerned that our models are computationally intensive, use a lot of memory and can't always be coded in a recursive manner. So we many end up having to query out large chunks anyway.
I should also say that I've always used Matlab or R for these sorts of tasks before but I'm now interested in F# as it offers that interactive, high level flexibility for Research but the same code can be used in production.
My apologies for not giving this context information at the start (It's my first question), I can see now that it helps people form their answers.
My thanks again to everyone that's taken the time to help me.
It really sounds like your data should be stored and queried in a relational database (where is it currently stored?: loading millions of records with several fields into memory must be an expensive operation, and could leave you with stale data and difficulty persisting changes). And then you could use the F# LINQ to SQL implementation (which I believe you can find in the Power Pack) to have F# expressions translated to SQL expressions.
Here's a link from Don Syme about LINQ Support in F# Power Pack: http://blogs.msdn.com/b/dsyme/archive/2009/10/23/a-quick-refresh-on-query-support-in-the-f-power-pack.aspx
The best choice of data structure depends upon what operations you want to do on it.
The simplest would be an array of structs. This has the advantages of fast random lookup, good space efficiency for an uncompressed representation and good locality. If there is sharing between substructures (like the strings) then intern them to make sure they get shared.
Alternatives might be a seq that is loaded from disk on-demand, a singly-linked list that allows you to prepend elements quickly or a balanced binary trees that allows operations like insertion at random locations efficiently.

Generic Linked List for Delphi 2009

I was looking in Generics.Collections and noticed there was no linked list. Sure they are simple to make, but I thought it was odd there was not one (or I just missed it). Are linked lists just outdated when compared to new modern data structures, or is there a need for a general generic linked list? Does anyone know of one?
Do you know the DeHL?
I think the TLinkedList<T> from the DeHL.Collections.LinkedList.pas unit is exactly what you are looking for.
In the old days, almost any piece of serious software contained linked lists or trees.
I haven't used linked lists alot, but trees are another story.
With the introduction of dynamic arrays, there is not that much need for linked lists. But I can imagine that you want to use it if your datastructure is changed often (add + delete).
You can easily create a generic linked list yourself, using a container class and records for the elements.
I don't know of any generic, linked list in the existing Delphi RTL.
They are still very useful as a data structure, however. Especially if you include variants on a linked list such as a b-tree or a binary tree. Unlike a regular list, a linked list can be expanded, edited, or modified without moving data in memory. They are very easy to version, and work well in purely functional code which does not allow mutating existing data. So it is still a very useful data structure.
Isn't that what tStringList is for?
(ducking)
Actually, any generic tList works fine as a linked list, and supplies most of the functionality needed. The ancient technique passed down from our ancestors of storing a pointer to memory in each record, and navigating to that has been easily replaced by dynamic arrays and doing things...more generically.

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