I have a huge amount of data which I would like to stream row by row. I thought calling workbook.write(stream) after changing the value of each row would append each write onto the output stream, but I was wrong. As it is, the file size suggests/matches the amount of rows I have, but there is only 1 row inside the file itself (which is the first row written).
Is there a way to accomplish this? Much like I would be able to using a text file?
I've taken a look at the BigGrid implementation, and it looks a bit overkill for what I'm trying to do.
Thanks!
You can't do a streaming write of the whole file in one go, the file format doesn't work like that. There are references between different parts of the file that preclude it. The file format just isn't like a CSV!
Instead, what you can do is hold a few small parts in memory, do a streaming write of the large parts of the spreadsheet to a temporary file, then re-assemble it in a low memory manner for output. To do that, look at the (fairly new) SXSSF usermodel code in POI.
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I am a peculiar problem where I have to work on data given in a spreadsheet (xls,csv). I would be using that data in my java program.
The spreadsheet data is generated elsewhere and I have no control on it. In it, there are a few columns which have a system-peculiar formatting and I should have an option to choose "programmatically" on how to convert each of this to the format I need.
Simple approach in my project would have been to
a) read the spreadsheet and apply transformations in place while reading.
b) read each row as a java object and iterate over this list and do the modifications
c) use some in-memory DB like H2 and apply some **user-defined functions** (dont know how) either while reading into the memory or transforming it later.
At this point of time, I really do not have all 3 options figured out in detail. So please excuse the vagueness.
Is there any other option of doing it? And more importantly, because i can have thousands of records where more than 5 columns may need to be transformed, what is the quickest approach?
First you can check if the the file is excel or spreadsheet.
If its excel you can use Apache poi,its really useful to parse the excel file.In this case you can apply transformation while reading.
Spreadsheet is comma separated so you can use the split function and parse it.In this case you cannot apply transformation while reading, but collect in an Array and do the same.
Performance depends upon how you optimize the code.You can use Java 8 Streams to stream line and make effective use of code.
I need to order a huge csv file (10+ million records) with several algorithms in Java but I've some problem with memory amount.
Basically I have a huge csv file where every record has 4 fields, with different type (String, int, double).
I need to load this csv into some structure and then sort it by all fields.
What was my idea: write a Record class (with its own fields), start read csv file line by line, make a new Record object for every line and then put them into an ArrayList. Then call my sorter algorithms for each field.
It doesn't work.. I got and OutOfMemoryException when I try lo load all Record object into my ArrayList.
In this way I create tons of object and I think that is not a good idea.
What should I do when I have this huge amount of data? Which method/data structure can ben less expensive in terms of memory usage?
My point is just to use sort algs and look how they work with big set of data, it's not important save the result of sorting into a file.
I know that there are some libs for csv, but I should implements it without external libs.
Thank you very much! :D
Cut your file into pieces (depending on the size of the file) and look into merge sort. That way you can sort even big files without using a lot of memory, and it's what databases use when they have to do huge sorts.
I would use an in memory database such as h2 in in-memory-mode (jdbc:h2:mem:)
so everything stays in ram and isn't flushed to disc (provided you have enough ram, if not you might want to use the file based url). Create your table in there and write every row from the csv. Provided you set up the indexes properly sorting and grouping will be a breeze with standard sql
I am writing a software which has a part dealing with read and write operaions. I am wondering how costly these operations are on a csv file. Is there are any other file formats that consume less time? Because I have to do write and read on csv files at the end of every cycle.
Read and write operations depend on the file system, hardware, software configuration, memory, mermory setup and size of the file to read. But not on the format. A different problem related with this is the cost of parsing the file that surely must relative low as csv is very simple.
The point is that CSV is a good format for tables of data but not for nested data. If your data has a lot of nested information you can separate it into different csv files or you will have some information redundancy that will penalize your performance. But other formats might have other kind of redundancy.
And do not optimize prematurily. If you are reading and writing from the file very frecuently this file will surely be kept on RAM. JSON or a zipped file might save size and be read faster but would have a higher parsing time and could be even slower at the end. And the parsing time depends also on the implemenation of the library (Gson vs Jackson) and version.
It will be nice to know the reasons behind your problem to give better ansewrs.
The cost of reading / writing to a CSV file, and whether it is suitable for your application, depend on the details of your use case. Specifically, if you are simply reading from the beginning of the file and writing to the end of the file, then the CSV format is likely to work fine. However, if you need to access particular records in the middle of your file then you probably wish to choose another format.
The main issue with a CSV file is that it is not a good format choice for random access, since each record (row) is of variable size, so you cannot simply seek to a particular record offset in the file, and instead need to read every row (well, you could still jump and sample, but you cannot seek directly by record offset). Other formats with fixed sized records would allow you to seek directly to a particular record in the file, making updating of an entry in the middle of the file possible without needing to re-read and re-write the entire file.
I've got a RandomAccessFile in Java where i manage some data. Simplified:
At the start of the file i have an index. (8 byte long value per dataset which represents the offset where the real data can be found).
So if i want to now where i can find the data of dataset no 3 for example. I read 8 Bytes at offset (2*8). (Indexing starts with 0).
A dataset itsself consists of 4 Bytes which represents the size of the dataset and then all the bytes belonging to the dataset.
So that works fine in case i always rewrite the whole file.
It's pretty important here, that Dataset no 3 could have been written as the first entry in the file so the index is ordered but not the data itsself.
If i insert a new dataset, i always append it to the end of the file. But the number of datasets that could be i n one file is limited. If i can store 100 datasets in the file there will be always 100 entries in the index. If the offset read from the index of a dataset is 0 the dataset is new and will be appended to the file.
Bu there's one case which is not working for me yet. If i read dataset no. 3 from the file and i add some data to it in my application and i want to update it in the file i have no idea how to do this.
If it has the same length as befor i can simply overwrite the old data. But if the new dataset has more bytes than the old one i'll have to move all the data in the file which is behind this dataset and update the indexes for these datasets.
Any idea how to do that?
Or is there maybe a better way to manage storing these datasets in a file?
PS: Yes of course i thought of using a database but this is not applicable for my project. I really do need simple files.
You can't easily insert data into the middle of a file. You'd basically have to read all the remaining data, write the "new" data and then rewrite the "old" data. Alternatively, you could potentially invalidate the old "slow" (potentially allowing it to be reused later) and then just write the whole new record to the end of the file. Your file format isn't really clear to me to be honest, but fundamentally you need to be aware that you can't insert (or delete) in the middle of a file.
I've got a RandomAccessFile in Java where i manage some data.
Stop right there. You have a file. You are presently accessing it via RandomAccessFile in Java. However your entire question relates to the file itself, not to RandomAccessFile or Java. You have a major file design problem, as you are assuming facilities like inserting into the middle of a file that don't exist in any filesystem I have used since about 1979.
As the others answered too, there's no real possibility to make the file longer/shorter without rewriting the whole. There are some workarounds and maybe one solution would work after all.
Limit all datasets to a fixed length.
Delete by changing/removing the index and add by always adding to the end of the file. Update by removing the old dataset and adding the new dataset to the end if the new dataset is longer. Compress the file from time to time by actually deleting the "ignored datasets" and moving all valid datasets together (rewriting everything).
If you can't limit the dataset to a fixed length and you intend to update a dataset making it longer, you can also leave a pointer at the end of the first part of a dataset and continue it later in the file. Thus you get a structure like a linked list. If a lot of editing takes place it would make here sense too, to rearrange & compress the file.
Most solutions have a data overhead but file size is usually not the problem and as mentioned you can let some method "clean it up".
PS: I hope it's ok to answer such old questions - I couldn't find anything about it in the help center and I'm relatively new here.
I want to make a GUI application that contains three functions as follows:
Add a record
Edit a record
Delete a record
A record contains two fields - Name and Profession
There are two restrictions for the application
You can't use database to store info. You have to use a flat file.
Total file should not be re-written for every add/delete operation.
So, my questions are mentioned below:
Q1. Which file format would be better? (.xml or .csv or .txt or any other)
Q2. How can we perform the add/delete operation without the whole file being re-written?
The second part of your question is answered here : Best Way to Write Bytes in the Middle of a File in Java
As for the format - I would go with something as simple as possible. You don't want to have to deal with a bunch of markup processing, as using RandomAccessFile, you will going directly to a byte position. A fixed width style format would be good, so that based on the record number, you can calculate the starting position of a record or field in the file, without having to read everything in the file. The fields would then be padded out to the fixed width with spaces or some other suitable character.
I would go with CSV, zipped. it is both readable, and editable externally.
If CSV is your choice, this can help: http://javacsv.sourceforge.net/
Did you look at this? http://sourceforge.net/projects/flatworm/
Also consider Apache Derbi and HSQLDB
Another solution is this http://www.coyotegulch.com/products/jisp/index.html
You can reinvent the wheel, but that is only required if this is an academic assigment...
Given that the whole file must not be rewritten, I would suggest using RandomAccessFile that allow you to read and write only the record you want.
For the file format, a binary file, using fixed length for the record : ex: Name on 20 characters, Profession on 30.
This will allow you to use the seek() method of RandomAccessFile to directly access your data.