I have inherited a uniVerse database (link to Rocketsoftware site) and would like to know if it's possible to read/parse the underlying data files (which I believe are hash tables?) into 'R'?
I'm aware there are ODBC drivers as well as .NET libraries, but I'm interested in parsing the files in R (if possible) without these drivers?
(I've searched and seen a few topics on parsing hash tables in Java and C#, but nothing in R yet)
It's a propriety format, so unless you want to reverse engineer it and re-implement in R that isn't the path forward. Also note that it isn't a single hash-table format either, aside from the standard modulo and bucket sizes, there are several different formats you'll encounter.
If you don't want work with any of the native APIs of the database to read the data, you can issue database commands that will dump it to CSV or XML flat files. Take a look into the RetrieVe query language manuals to learn more.
This is really stumping me. I'm trying to recover some lost information (for reasons I cannot disclose) from a dump of an Android phone's free space. I have no lookup table for the disk, so all I have is the raw dump of the flash.
Basically, I'm trying to pick out SQLite files from this huge 350 megabyte mess. I can find the SQLite file header easy enough, it's 100 bytes and described here. Everything seems to be in place. However, I can find entries, but I'm currently stumped as to how to determine where the entries stop and the file ends and other sectors of the disk are filled.
Any suggestions? I'm at a dead end currently, other than kind of manually going through and trying to eyeball it, but I'm a programmer here, trying to find some sort of methodical way through this.
I appreciate you guys in advance!
I've always had luck recovering data using PhotoRec which, despite its name, supports many file formats including sqlite.
http://www.cgsecurity.org/wiki/File_Formats_Recovered_By_PhotoRec
I've never tried it on a dump of flash memory so I don't know how successful it would be. It depends on how the file is layed out in memory and PhotoRec bets on the fact that most files are stored in contiguous blocks (i.e. not fragmented).
I'm exploring a database from a third-party application and I was wondering if it is possible to infer how to decode a BLOB in a SQLite database if you don't know what is stored inside the BLOB?
Is there any way or are there tools to solve this?
Is there any way or are there tools to solve this?
A BLOB is binary data. There are ways to reconstruct the data format (these reverse engineering methods are related to those you use for deciphering unknown file formats), but without further information what is stored in the binary BLOB it is rather difficult, so I can only give some vague hints:
think about: if you were the programmer to encode the data that is stored in the BLOB - how would you do it? Often the way that is used is similar
look at the first bytes of the data - often it tells what file format it could be/is (there are documentations of those "magic numbers" for many file formats available); also don't forget to look whether the data could be compressed (i. e. look for zlib header, since zlib is often used for compression)
if legal (depends on your country), it is often helpful to apply reverse engineering tools like IDA Pro or if not available a good debugger to have a look what the program does with the BLOB data after reading
If you save the BLOB to a file, you can use the Unix file command to determine what kind of data is stored in it.
use
sqlite3 db.sqlite 'select writefile('data.bin', value) from Record limit 1;'
(assuming value volumn contains type BLOB, like in IndexedDB)
then you can print contents of this file with cat data.bin
I'm trying to start using plain text files to store data on a server, rather than storing them all in a big MySQL database. The problem is that I would likely be generating thousands of folders and hundreds of thousands of files (if I ever have to scale).
What are the problems with doing this? Does it get really slow? Is it about the same performance as using a Database?
What I mean:
Instead of having a database that stores a blog table, then has a row that contains "author", "message" and "date" I would instead have:
A folder for the specific post, then *.txt files inside that folder than has "author", "message" and "date" stored in them.
This would be immensely slower reading than a database (file writes all happen at about the same speed--you can't store a write in memory).
Databases are optimized and meant to handle such large amounts of structured data. File systems are not. It would be a mistake to try to replicate a database with a file system. After all, you can index your database columns, but it's tough to index the file system without another tool.
Databases are built for rapid data access and retrieval. File systems are built for data storage. Use the right tool for the job. In this case, it's absolutely a database.
That being said, if you want to create HTML files for the posts and then store those locales in a DB so that you can easily get to them, then that's definitely a good solution (a la Movable Type).
But if you store these things on a file system, how can you find out your latest post? Most prolific author? Most controversial author? All of those things are trivial with a database, and very hard with a file system. Stick with the database, you'll be glad you did.
It is really depends:
What is file size
What durability requirements do you have?
How many updates do you perform?
What is file system?
It is not obvious that MySQL would be faster:
I did once such comparison for small object in order to use it as sessions storage for CppCMS. With one index (Key Only) and Two indexes (primary key and secondary timeout).
File System: XFS ext3
-----------------------------
Writes/s: 322 20,000
Data Base \ Indexes: Key Only Key+Timeout
-----------------------------------------------
Berkeley DB 34,400 1,450
Sqlite No Sync 4,600 3,400
Sqlite Delayed Commit 20,800 11,700
As you can see, with simple Ext3 file system was faster or as fast as Sqlite3 for storing data because it does not give you (D) of ACID.
On the other hand... DB gives you many, many important features you probably need, so
I would not recommend using files as storage unless you really need it.
Remember, DB is not always the bottle neck of the system
Forget about long-winded answers, here's the simplest reasons why storing data in plaintext files is a bad idea:
It's near-impossible to query. How would you sort blog posts by date? You'd have to read all the files and compare their date, or maintain your own index file (basically, write your own database system.)
It's a nightmare to backup. tar cjf won't cut it, and if you try you may end up with an inconsistent snapshot.
There's probably a dozen other good reasons not to use files, it's hard to monitor performance, very hard to debug, near impossible to recover in case of error, there's no tools to handle them, etc...
I think the key here is that there will be NO indexing on your data. SO to retrieve anything in say a search would be rediculously slow compared to an indexed database. Also, IO operations are expensive, a database could be (partially) in memory, which makes the data available much faster.
You don't really say why you won't use a database yourself... But in the scenario you are describing I would definitely use a DB over folder any day, for a couple of reasons. First of all, the blog scenario seems very simple but it is very easy to imagine that you, someday, would like to expand it with more functionality such as search, more post details, categories etc.
I think that growing the model would be harder to do in a folder structure than in a DB.
Also, databases are usually MUCH faster that file access due to indexing and memory caching.
IIRC Fudforum used the file-storage for speed reasons, it can be a lot faster to grab a file than to search a DB index, retrieve the data from the DB and send it to the user. You're trading the filesystem interface with the DB and DB-library interfaces.
However, that doesn't mean it will be faster or slower. I think you'll find writing is quicker on the filesystem, but reading faster on the DB for general issues. If, like fudforum, you have relatively immutable data that you want to show several posts in one, then a file-basd approach may be a lot faster: eg they don't have to search for every related post, they stick it all in 1 text file and display it once. If you can employ that kind of optimisation, then your file-based approach will work.
Also, mail servers work in the file-based approach too, the Maildir format stores each email message as a file in a directory, not in a database.
one thing I would say though, you'll be better storing everything in 1 file, not 3. The filesystem is better at reading (and caching) a single file than it is with multiple ones. So if you want to store each message as 3 parts, save them all in a single file, read it to get any of the parts and just display the one you want to show.
...and then you want to search all posts by an author and you get to read a million files instead of a simple SQL query...
Databases are NOT faster. Think about it: In the end they store the data in the filesystem as well. So the question if a database is faster depends strongly on the access path.
If you have only one access path, which correlates with your file structure the file system might be way faster then a database. Just make sure you have some caching available for the filesystem.
Of course you do loose all the nice things of a database:
- transactions
- flexible ways to index data, and therefore access data in a flexible way reasonably fast.
- flexible (though ugly) query language
- high recoverability.
The scaling really depends on the filesystem used. AFAIK most file system have some kind of upper limit for number of files (totally or per directory), though on the new ones this is often very high. For hundreds and thousands of files with some directory structure to keep directories to a reasonable size it should be possible to find a well performing file system.
#Eric's comment:
It depends on what you need. If you only need the content of exact on file per query, and you can determine the location and name of the file in a deterministic way the direct access is faster than what a database does, which is roughly:
access a bunch of index entries, in order to
access a bunch of table rows (rdbms typically read blocks that contain multiple rows), in order to
pick a single row from the block.
If you look at it: you have indexes and additional rows in memory, which make your caching inefficient, where is the the speedup of a db supposed to come from?
Databases are great for the general case. But if you have a special case, there is almost always a special solution that is better in some sense.
if you are preferred to go away with RDBMS, why dont u try the other open source key value or document DBs (Non- relational Dbs)..
From ur posting i understand that u r not goin to follow any ACID properties of relational db.. it would be better to adapt other key value dbs (mongodb,coutchdb or hyphertable) instead of your own file system implementation.. it will give better performance than the existing approaches..
Note: I am not also expert in this.. just started working on MongoDB and find useful in similar scenarios. just wanted to share in case u r not aware of these approaches
I have been given a set of COBOL DAT, IDX and KEY files and I need to read the data in them and export it into Access, XLS, CSV, etc. I do not know the version, vendor of the COBOL code as I only have the windows executable that created the files.
I have tried Easysoft and Parkway ODBC drivers but I have not been successful in reading the data from the files.
I do not have access to the source code as the company that was distributing this product shut down.
I have successfully read some of the dat files using http://www.cobolproducts.com/datafile just now which I came to know through another forum. Most probably I will work with them to help me read the rest of the files that I am having an issue with.
A few possibilities.
1/ See if you can find the names of the people that worked for the company. They may be helpful.
2/ Open the DAT file in a text editor. The data may be decodable from that. If the basic format can be discerned, quick'n'dirty code can be written to extract it.
3/ Open up the executable in an editor, there may be strings in there that indicate which compiler was used, then you can search for info on its file formats. If it's a DOS application, there's a good chance it was either Microsoft or Fujitsu COBOL.
4/ Consider placing job requests on work sites like elance or rentacoder; I don't think there's a cost if the work can't be done successfully.
5/ Hire someone to examine it and advise on the likelihood of recovery.
6/ Get a screen dump of the record contents for every active record and re-construct it from that.
Some of these are pretty hard so your mileage may vary.
Good luck.
I have read COBOL DAT files only with FD, when I do not have the FD, I open the file in a Text Editor, and try to guess the columns, and try again, until I have this working, the big problem with this approach is when the DAT file have COMP columns, that can be any kind of COMP type, but with a litthe patience I cold get this done.
I had tryed Parkway ODBC, but without success.
for anyone going through this journey, I found this in sourceforge: Cobol and RPG data reader and converter
http://sourceforge.net/projects/cobol2j/
Im about to try it, sounds kind of promising