I am intersted in replacing my current data format that I use with GTFS, but I hear and read from here and there that there are flaws in GTFS file format.
Most of the time I see that you can't somehow predict some things such as delays or some real-time stuff. They say you can't get the "whole picture" with them.
So what I am asking is there anyone more experienced with GTFS , since I am seeing them only for first time, that could have possibly used GTFS in some kind of application and could tell the problems they have faced while developing?
Maybe someone has a suggestion about a better kind of file format? Or a combination of some formats?
It's hard to say whether GTFS is a good fit or not for your application without knowing what your application's requirements are, but I can offer a few remarks.
If your goal is to provide real-time data to users you should take a look at GTFS-realtime, a complementary data format designed specifically for issuing real-time updates. For most public-transit applications, using a GTFS and a GTFS-realtime feed together does indeed give the "whole picture" about a transit network, or near enough.
In terms of GTFS itself, my main complaint is that it seems designed specifically for route-planning applications and using data in this format for any other purpose can be difficult. For example, while a GTFS feed records information about transit stops and routes, there is no requirement that each of these have a single, canonical entry—if the data spans multiple board periods, there will almost always be (seemingly) duplicate entries for each.
This doesn't matter if you're plotting a route based on where and when a person is travelling, since the links between objects ensure you'll always generate the right result. If you're starting with only a person's location and want to know, "What transit resources are available nearby?", reliably producing an accurate answer requires some contortions.
It depends on your needs for importing existing feeds. If yes, then you need to be able to handle it anyhow. In my case, import was required, so I use the same for data that stems from other formats like PDF timetables. Otherwise you need to supoprt two formats. If you do not need it for import (or export) you may consider your own format : I find GTFS does not reveal the actual network.
GTFS needs quite some interpretation and digesting in order to end up with the whole picture that you can answer planning questions on.
I merge stops together if they are close, like a few meters apart, and assume 'trivial walk' if 10-50 meters. That automatically handles combining multipe feeds.
Apart from that, I turn the stop_times roughly inside-out to create a 'link' table'. The end result is that for each stop you have a list of departures and their destinations.
Biggest problem until now is that GTFS feeds can record the trips from an operator point of view. Passengers can remain sitting in the bus if it flips the headsign from 351 to 285, takes a new driver onboard and continues. That means you need to know what trips actually need to be seen as joined in passenger terms.
I solved minor problem for manual feed entry by having my GTFS parser accept a handful of constructs that ease editing, such as leaving out the sequence numbers to have it generated incrementally, and recognising 02.13+1 as 26.13.
Related
I am collecting a large amount of data which is most likely going to be a format as follows:
User 1: (a,o,x,y,z,t,h,u)
Where all the variables dynamically change with respect to time, except u - this is used to store the user name. What I am trying to understand since my background is not very intense in "big data", is when I end up with my array, it will be very large, something like 108000 x 3500, since I will be preforming analysis on each timestep, and graphing it, what would be an appropriate database to manage this in is what I am trying to determine. Since this is for scientific research I was looking at CDF and HDF5, and based on what I read here NASA I think I will want to use CDF. But is this the correct way to manage such data for speed and efficiency?
The final data set will have all the users as columns, and the rows will be timestamped, so my analysis program would read row by row to interpret the data. And make entries into the dataset. Maybe I should be looking at things like CouchDB and RDBMS, I just don't know a good place to start. Advice would be appreciated.
This is an extended comment rather than a comprehensive answer ...
With respect, a dataset of size 108000*3500 doesn't really qualify as big data these days, not unless you've omitted a unit such as GB. If it's just 108000*3500 bytes, that's only 3GB plus change. Any of the technologies you mention will cope with that with ease. I think you ought to make your choice on the basis of which approach will speed your development rather than speeding your execution.
But if you want further suggestions to consider, I suggest:
SciDB
Rasdaman, and
Monet DB
all of which have some traction in the academic big data community and are beginning to be used outside that community too.
I have been using CDF for some similarly sized data and I think it should work nicely. You will need to keep a few things in mind though. Considering I don't really know the details of your project, this may or may not be helpful...
3GB of data is right around the file size limit for the older version of CDF, so make sure you are using an up-to-date library.
While 3GB isn't that much data, depending on how you read and write it, things may be slow going. Make sure you use the hyper read/write functions whenever possible.
CDF supports meta-data (called global/variable attributes) that can hold information such as username and data descriptions.
It is easy to break data up into multiple files. I would recommend using one file per user. This will mean that you can write the user name just once for the whole file as an attribute, rather than in each record.
You will need to create an extra variable called epoch. This is well defined timestamp for each record. I am not sure if the time stamp you have now would be appropriate, or if you will need to process it some, but it is something you need to think about. Also, the epoch variable needs to have a specific type assigned to it (epoch, epoch16, or TT2000). TT2000 is the most recent version which gives nanosecond precision and handles leap seconds, but most CDF readers that I have run into don't handle it well yet. If you don't need that kind of precision, I recommend epoch16 as that has been the standard for a while.
Hope this helps, if you go with CDF, feel free to bug me with any issues you hit.
How do you go about collecting and storing data which was not part of the initial database and software design? For example, if you've come up with a pointing system, you have to collect the points for every user which has already been registered. For new users, that would be easy, because the changes of the business logic will reflect the pointing system ... but the old ones?
In general, how does one deal with data, which should have been there from the beginning, but wasn't? Writing manual queries to collect the missing pieces? Using crons?
Well, you are asking for something that is by definition not possible, I think.
deal with data hich should have been there from the beginning, but wasn't?
Because if you are able to deduce the number of points from the existing data in the database. If that were possible, there is obviously no missing data.... Storing the points separately would make it redundant (still a fine option in case you need that for performance).
For example: stackoverflow rewards number of consecutive visits. Let's say they did not do that from the start. If they were logging date-of-visit already, you can recalc the points. So no missing data.
So if that is not possible, you need another solution: either get data from other sources (parse a webserver log) or get the business to draft some extra business rules for the determination of the default values for the existing users (difficult in this particular example).
Writing manual queries to collect the missing pieces? Using crons?
I would populate that in a conversion script or even in a special conversion application if very complex.
The question title is probably not correct because part of my question is to try and get some more understanding on the problem.
I am looking for the advantages of making sure data that is imported to a database (simple example: Excel table to Access database) should be given using the same schema and should also be valid to the business requirements.
I have an Excel table containing none normalised data and an Access database with normalised tables.
The Excel table comes from multiple third parties, none of which stick to the same format as each other or the database.
Some of the sources also do not supply all the relevant data.
Example of what could be supplied
contact_key, date, contact_title, reject_name, reject_cost, count_of_unique_contact
count_of_unique_contact is derived from distinct contact_title's and should not be imported.
contact_key is sometimes not supplied.
title is sometimes unknown and passed in as such "n/a", "name = ??1342", "#N/A" etc. rather random.
reject_name is often miss spelled.
the fields are sometimes not even supplied, e.g. date and contact_key are missing.
I am trying to find information to help explain the issues with the above.
Issues only related to incorrect data or fields making it difficult to have useful data in the database such as not being able to report a trend on reject costs in a month when the date is not supplied. Normalising the excel file is not an option available to me.
Requesting the values and fields in the Excel files to match the business requirements and the format to be the same for every third party that sends them is what I want to do but the request is falling on deaf ears.
I want to explain to the client that inputting fake data and checking for invalid/existing rejects/contacts all the time is wrong and doing it is going to fail or at the best be difficult without constant maintenance of a poor system.
Does anyone have any information on this problem?
Thanks
This is a common problem; this gets referred to in data processing circles as "garbage in, garbage out". Essentially, what you're running up against is that the data as given is of poor quality; you're correct to recognize that the problem is that it will be hard (if not impossible) to use this data to extract any useful information.
To some extent, this is a problem that should be fixed at the source; whatever your source of your data is, they need to be convinced that the data quality must improve. In the short term, you can sanitize your data; the term refers to removing or cleaning the bad entries to make the remainder of the data (the "good" data) importable into your database. Depending on just what percentage of your data is bad, you may or may not be able to do useful things with the sanitized data once you import it.
At some point, since you're not getting traction with management about the quality of the data, you will simply have to show them that the system is not working as intended because the quality of the data is bad. They'll need to improve their processes at that point to improve the quality of the data you get in at that point. Until then, though, keep pressing for better data; investigate the process of sanitizing the data and see what you can do with the remaining data. Good luck!
I don't see an answer to this question here on SO which makes me afraid that it's incredibly simple and I'm just missing something but here goes.
Background, feel free to skip: I need a single course for my bachelor's degree that I skipped out on years ago. Theoretically it's Computer Graphics, but since I left it has become more Game Development. And that's great because to me it's more interesting than the fill algorithms and translations and whatnot that it used to be. It's a 4th year course only offered every other year, but I've managed to talk the department into letting me take a 4th year independent study on the same topic and call that good enough.
The prof "running" the independent study doesn't teach the actual Computer Graphics course so while he's a smart guy this isn't really his field. So most of my questions are left to me, a text book and the internet. You know...like an independent study should be. :)
/Background
I've got a buddy that likes to develop game systems for fun. I plan to take one of his table top games and make it into a computer game using XNA.
I don't foresee any insurmountable challenges with the game mechanics but one thing I'm curious about is how do most games save their content? I mean that in a couple of ways and hopefully I can express them clearly.
Take the case of any RPG you've ever played. You can hit the "Save" button and save the world, your character's information and whatever other information is necessary. Then later on you can hit the "Load" button and bring it back.
Or the case of NPC dialogue. When I bump into Merchant #853 he randomly spits out one of 3 different greetings.
There are others that I can think of but they're really just variations on the same theme. Even with those two examples it seems to me the same mechanic could be used, but what is that mechanic?
I've been doing web development for years so my mind automatically jumps to "databases!". A database is the solution to any problem. And I can see how it could work here but the overhead seems pretty steep. "Here's my 6mb compiled game...oh and 68mb MySQL installation." Or even worse since I'm using XNA, maybe I'd need to find a way to bundle SQL Server. :)
I thought maybe XML but that doesn't feel right to me either. How would it work if I wanted to run on the XBox? Or Zune? (Those aren't necessary for what I'm doing, but there must be a solution somewhere that takes them into account.)
Anyone know the secret? Or have some ideas anyway?
Thanks
Jeff
There are two main ways how games are saved, a simple one and a complex one. The first way is to simply stores the current level, the current score and a handful of other stats. This is seen in games such as Super Mario Galaxy and most earlier console module based games. The save game doesn't restore your exact position, but just which levels you have completed. These save games are generally very simple and require very little memory.
The second way not only stores your overall progress, but stores each and every little detail, such as enemy positions, their current animation frame and so on, so that loading a save game will place you at the exact spot where you stopped, with all the enemies right in place, instead of back at the start of a level. These savegames tend to get much bigger than the other version and thus are mostly seen on PC games.
Databases are used in neither of these schemes, as the purpose of databases is to provide the ability to dynamically query data structures, what the game however needs isn't a way to query individual pieces, but just a way to statically store them. When a savegame is loaded, it is loaded completly into memory and from there on the game engine does its thing with the data. There are a handful of exceptions, such as MMORPGs which might work on a database, but single player games generally don't.
How the data is actually stored depends on the game. Most common seem to be simple binary data formats, as they are much better in terms of disk space than XML. In older games those binary formats where often raw dumps of a pieces of memory of the games process, so they didn't have any well thought out structure and often broke when a patch or a different version of a game got released, in some modern games that's still the case. XML can be used as too, as well as any other text based file format.
In large part this is more a game design issue than a programming one, as they way a game can be saved can drastically change how its played. The simple way, where you just save the level number and some stats, is however a lot easier to implement, as its just a few lines of of code. While the second one requires serialization of most of your classes, which for a complex game can be quite a tricky issue and lead to many subtle bugs.
One approach is to use .net serialization.
Make sure the state of you game is a fully connected graph and that each class in that graph is marked as Serializable (with the SerializableAttribute), the for saving (and loading) you can use normal .net serialization.
You can look at the codebase for Project Xenocide (open source XNA game) to see how it was done there.
You could use an SQLite database, with the SQLite.NET wrapper. I've used this, and found it quite simple. The whole DLL is only 850KB, and the database itself sits in a single file (with temp files created as needed). So your users shouldn't have an issue.
But you could also use a simple XML file, or a home-grown binary format. It all depends on how you're going to be querying the data, and how much data is involved. There is no one answer.
As others have noted, serialization is the way to go. And Gamasutra just published an article on data baking.
From my limited experience developing games, save games really don't use much storage. As tvanfosson said, you normally store most things in memory while playing the game, so saving state to disk isn't a problem.
Here's a short example. Assuming a single person RPG, if you needed to save your character's location only, you'd have perhaps a level number, xyz coordinates and maybe the direction you're facing. That's just a few bytes.
Now assume you need to save the state/location of things like health packs, crates, enemies, character's health and picked up items, etc. You could have a few hundred of these at most which would easily be less than 10KB.
Obviously things can get very complicated with more complex games. The trick is to only store what is truly necessary to recreate the player's experience. A lot of games only let you save at certain places, like the end of a level. In this case you only need to store the new level number plus the outcome of previous levels (e.g. health remaining, picked up items).
Even if you allow arbitrary save points you can ignore the state of any places/levels that you cannot return to. And you probably wouldn't want the user to be able to save mid-jump.
EDIT: With regard to file format... use any way that's convenient for the data type! XML is quite a nice way of doing things. Not sure how effective a database would be since for an RPG each fragment of data can be very different; You might end up with a bunch of tables with one row each.
Most games use their own, binary, file formats. Firstly this reduces the storage amount dramatically. Secondly, it helps prevent users cheating by editing the save game manually - if you have XML like <health value="10"/> it's very easy to edit the file to read <health value="100"/>. The downside of binary is that it's much more difficult for debugging.
While the game is running, I'd try to keep everything relating to the current context in memory. Your initialization can be kept in some suitable serialized format and read in on start up. XML would work, but it's somewhat verbose. A custom compact binary format is probably more appropriate. The same is true of the saved state. Whatever objects need to be reinitialized when the saved game is loaded should be serialized to a custom binary format and then reconstituted on load. If you run into memory problems, a small custom database optimized for speed would be another alternative. It could be pre-populated on installation.
I have a variety of time-series data stored on a more-or-less georeferenced grid, e.g. one value per 0.2 degrees of latitude and longitude. Currently the data are stored in text files, so at day-of-year 251 you might see:
251
12.76 12.55 12.55 12.34 [etc., 200 more values...]
13.02 12.95 12.70 12.40 [etc., 200 more values...]
[etc., 250 more lines]
252
[etc., etc.]
I'd like to raise the level of abstraction, improve performance, and reduce fragility (for example, the current code can't insert a day between two existing ones!). We'd messed around with BLOB-y RDBMS hacks and even replicating each line of the text file format as a row in a table (one row per timestamp/latitude pair, one column per longitude increment -- yecch!).
We could go to a "real" geodatabase, but the overhead of tagging each individual value with a lat and long seems prohibitive. The size and resolution of the data haven't changed in ten years and are unlikely to do so.
I've been noodling around with putting everything in NetCDF files, but think we need to get past the file mindset entirely -- I hate that all my software has to figure out filenames from dates, deal with multiple files for multiple years, etc.. The alternative, putting all ten years' (and counting) data into a single file, doesn't seem workable either.
Any bright ideas or products?
I've assembled your comments here:
I'd like to do all this "w/o writing my own file I/O code"
I need access from "Java Ruby MATLAB" and "FORTRAN routines"
When you add these up, you definitely don't want a new file format. Stick with the one you've got.
If we can get you to relax your first requirement - ie, if you'd be willing to write your own file I/O code, then there are some interesting options for you. I'd write C++ classes, and I'd use something like SWIG to make your new classes available to the multiple languages you need. (But I'm not sure you'd be able to use SWIG to give you access from Java, Ruby, MATLAB and FORTRAN. You might need something else. Not really sure how to do it, myself.)
You also said, "Actually, if I have to have files, I prefer text because then I can just go in and hand-edit when necessary."
My belief is that this is a misguided statement. If you'd be willing to make your own file I/O routines then there are very clever things you could do... And as an ultimate fallback, you could give yourself a tool that converts from the new file format to the same old text format you're used to... And another tool that converts back. I'll come back to this at the end of my post...
You said something that I want to address:
"leverage 40 yrs of DB optimization"
Databases are meant for relational data, not raster data. You will not leverage anyone's DB optimizations with this kind of data. You might be able to cram your data into a DB, but that's hardly the same thing.
Here's the most useful thing I can tell you, based on everything you've told us. You said this:
"I am more interested in optimizing my time than the CPU's, though exec speed is good!"
This is frankly going to require TOOLS. Stop thinking of it as a text file. Start thinking of the common tasks you do, and write small tools - in WHATEVER LANGAUGE(S) - to make those things TRIVIAL to do.
And if your tools turn out to have lousy performance? Guess what - it's because your flat text file is a cruddy format. But that's just my opinion. :)
I'd definitely change from text to binary but keep each day in a separate file still. You could name them in such a way that insertions in between don't cause any strangeness with indices, such as by including the date and possible time in the filename. You could also consider the file structure if you have several fields per location for example. Is it common to look for a small tile from a large number of timesteps? In that case you might want to store them as tiles containing data from several days. You didn't mention how the data is accessed which plays a big role in how to organise it efficiently.
Clarifications:
I'm surprised you added "database" as one of the tags, and considered it as an option. Why did you do this?
Essentially, you have a 2D, single component floating point image at every time step. Would you agree with this way of viewing your data?
You also mentioned the desire to insert a day between two existing ones - which seems to be a very odd thing to do. Why would you need to do that? Is there a new day between May 4 and May 5 that I don't know about?
Is "compression" one of the things you care about, or are you just sick of flat files?
Would a float or a double be sufficient to store your data, or do you feel you need more arbitrary precision?
Also, what programming language(s) do you want to access this data with?
your answer on how to store the data depends entirely on what you're going to do with the data. for example, if you only ever need to retrieve by specifying the date or a date range, then storing in a database as a BLOB makes some sense. but if you need to find records that have certain values, you'll need to do something different.
please describe how you need to be able to access the data/
Matt, thanks very much, and likewise longneck and jirv.
This post was partly an experiment, testing the quality of stackoverflow discourse. If you guys/gals/alien lifeforms are representative, I'm sold.
And on point, you've clarified my thinking considerably. Mind, I still might not necessarily implement your advice, but know that I will be thinking about it very seriously. >;-)
I may very well leave the file format the same, add to the extant C and/or Ruby routines to tack on the few low-level features I lack (e.g. inserting missing timesteps), and hang an HTTP front end on the whole thing so that the data can be consumed by whatever box needs it, in whatever language is currently hoopy. While it's mostly unchanging legacy software that construct these data, we're always coming up with new consumers for it, so the multi-language/multi-computer requirement (gee, did I forget that one?) applies to the reading side, not the writing side. That also obviates a whole slew of security issues.
Thanks again, folks.