Go back 'n' lines in file using Stream.lines

Go back 'n' lines in file using Stream.lines - java

I need to build an application which scans through a large amount of files. These files contain blocks with some data about a sessions, in which each line has a different value. E.g.: "=ID: 39487".
At that point I have that line, but the problem I now face is that I need the value n lines above that ID. I was thinking about an Iterator but it only has forward methods. I also thought about saving the results in a List but that defies the reason to use Stream and some files are huge so that would cause memory problems.
I was wondering if something like this is possible using the Stream API (Files)? Or perhaps a better question, is there a better way to approach this?
Stream<String> lines = Files.lines(Paths.get(file.getName()));
Iterator<String> search = lines.iterator();

You can't arbitrarily read backwards and forwards through the file with the same reader (no matter if you're using streams, iterators, or a plain BufferedReader.)
If you need:
m lines before a given line
n lines after the given line
You don't know the value of m and n in advance, until you reach that line
...then you essentially have three options:
Read the whole file once, keep it in memory, and then your task is trivial (but this uses the most memory.)
Read the whole file once, mark the line numbers that you need, then do a second pass where you extract the lines you require.
Read the whole file once, storing some form of metadata about line lengths as you go, then use a RandomAccessFile to extract the specific bits you need without having to read the whole file again.
I'd suggest given the files are huge, the second option here is probably the most realistic. The third will probably give you better performance, but will require much more in the way of development effort.
As an alternative if you can guarantee that both n and m are below a certain value, and that value is a reasonable size - you could also just keep a certain number of lines in a buffer as you're processing the file, and read through that buffer when you need to read lines "backwards".

Try my library. abacus-util
try(Reader reader = new FileReader(yourFile)) {
StreamEx.of(reader)
.sliding(n, n, ArrayList::new)
.filter(l -> l.get(l.size() - 1).contains("=ID: 39487"))
./* then do your work */
}
No matter how big your file is. as long as n is small number, not millions

Related

Count duplicates in huge text files collection

I have this collection of folders:
60G ./big_folder_6
52G ./big_folder_8
61G ./big_folder_7
60G ./big_folder_4
58G ./big_folder_5
63G ./big_folder_2
54G ./big_folder_9
61G ./big_folder_3
39G ./big_folder_10
74G ./big_folder_1
Each folder contains 100 txt files, with one sentence per line. For example, the file ./big_folder_6/001.txt:
sentence ..
sentence ..
...
Each file in the folder is between 4 and 6 GB (as you can see from the totals reported above) with 40-60 million of sentences more or less. One single file fits in memory.
I need to deduplicate and count the sentences globally unique, so as to obtain a new collection of files where the lines are counted:
count ...unique sentence...
The collection is huge.
My first implementation (using Java) was a "merge sort" approach ordering the lines in a new collection of 500 files (dispatching each line in the right file using the first N characters), then order and aggregate duplicates on the single files.
I know it is a wordcount map-reduce problem but I would prefer to avoid it. The question is: am I using the right approach to solve this kind of problem or I should consider other tool/approach beside MapReduce?

You mean delete duplicated lines of each file? or among all files?
in any case, you cant read the whole file, you need to read line by line or a memory exception will be thrown. Use BufferedReader (example here), use a map storing the string with the count of the repeated line as a value, when you read a line, put in the map incrementing the value if it exist.
After read the file, write all the lines and theirs counts to a new file and release memory.
UPDATE 1
the problem is that you have a lot of gigas. So you cant keep in memory each line because it can thrown a memory exception, but at the same time you have to keep them in memory to quickly validate if they are duplicated. What comes to may mind is instead of having a string representing the key value, put a hash of the string (usgin string.toHash()), and when it was the first, write it to the new file, but flush every 100 lines or more to lower the time writing to the disk. After you processed all the files and write unique lines in the file and you have only integers in the map (hashcode of the string as a key and count as a value), you start reading the file containing only unique lines, then create a new file writing the line and the count values.

How to parse large files using flatpack

I need to parse files that may be quite large, possibly 100s of megabytes and millions of lines. I have been trying to do this using FlatPack. I would think the way to do this would be to use the buffered parsers and the new stream methods. But, despite that dataset.next() returns true for the correct number of records, the Optional returned by dataset.getRecord() never contains a value.
I have looked at this example/test but it only counts the number of record and does not actually do anything with the content.
example/test

You can use the class BuffReaderParseFactory instead of DefaultParserFactory.
It will read one record from the input file only when you call "next()".

The explanations for both DefaultParserFactory and BuffReaderParseFactory are not exactly helpful. Both libraries said to return PZParser (from newDelimitedParser) but only one of them returns an actual value from a record. Based on the examples I've seen, I think BuffReaderParseFactory is just for checking performance (hence should be faster) and DefaultParserFactory on the other hand contains all the records.

best way of loading a large text file in java

I have a text file, with a sequence of integer per line:
47202 1457 51821 59788
49330 98706 36031 16399 1465
...
The file has 3 million lines of this format. I have to load this file into the memory and extract 5-grams out of it and do some statistics on it. I do have memory limitation (8GB RAM). I tried to minimize the number of objects I create (only have 1 class with 6 float variables, and some methods). And each line of that file, basically generates number of objects of this class (proportional to the size of the line in temrs of #ofwords). I started to feel that Java is not a good way to do these things when C++ is around.
Edit:
Assume that each line produces (n-1) objects of that class. Where n is the number of tokens in that line separated by space (i.e. 1457). So considering the average size of 10 words per line, each line gets mapped to 9 objects on average. So, there will be 9*3*10^6 objects.So, the memory needed is: 9*3*10^6*(8 bytes obj header + 6 x 4 byte floats) + (a map(String,Objects) and another map (Integer,ArrayList(Objects))). I need to keep everything in the memory, because there will be some mathematical optimization happening afterwards.

Reading/Parsing the file:
The best way to handle large files, in any language, is to try and NOT load them into memory.
In java, have a look at MappedByteBuffer. it allows you to map a file into process memory and access its contents without loading the whole thing into your heap.
You might also try reading the file line-by-line and discarding each line after you read it - again to avoid holding the entire file in memory at once.
Handling the resulting objects
For dealing with the objects you produce while parsing, there are several options:
Same as with the file itself - if you can perform whatever it is you want to perform without keeping all of them in memory (while "streaming" the file) - that is the best solution. you didnt describe the problem youre trying to solve so i dont know if thats possible.
Compression of some sort - switch from Wrapper objects (Float) to primitives (float), use something like the flyweight pattern to store your data in giant float[] arrays and only construct short-lived objects to access it, find some pattern in your data that allows you to store it more compactly
Caching/offload - if your data still doesnt fit in memory "page it out" to disk. this can be as simple as extending guava to page out to disk or bringing in a library like ehcache or the likes.
a note on java collections and maps in particular
For small objects java collections and maps in particular incur a large memory penalty (due mostly to everything being wrapped as Objects and the existence of the Map.Entry inner class instances). at the cost of a slightly less elegant API, you should probably look at gnu trove collections if memory consumption is an issue.

Optimal would be to hold only integers and line ends.
To that end, one way would be: convert the file to two files:
one binary file of integers (4 bytes)
one binary file with indexes where the next line would start.
For this one can use a Scanner to read, and a DataOutputStream+BufferedOutputStream to write.
Then you can load those two files in arrays of primitive type:
int[] integers = new int[(int)integersFile.length() / 4];
int[] lineEnds = new int[(int)lineEndsFile.length() / 4];
Reading can be done with a MappedByteBuffer.toIntBuffer(). (You then would not even need the arrays, but it would become a bit COBOL like verbose.)

Java compiler error: lookup table exceeds 65535 limit

I'm running into this compiler error due to my extremely large lookup table based on this definition:
//92 X 182 array
private static final double[][] lookUpTable = new double[][]
{
{ numbers....}
};
As i understand it, dividing it up is a solution, but it would be extremely difficult to split this array up accurately. I also believe i could move it out to a file, but i don't know if i could format it in a way to help me, plus i don't want file reads every second.
Are there any other suggestions to help me get around this?

Convert your table to a file, embed the file as a resource, read it once in a static initialization block, and store it in a lookUpTable array. It will not be distinguishable from an array initialized through an aggregate, except there would be no 65535 limit. Storing in a static variable will help you avoid "reads every second".
As far as the format is concerned, you can put each row of the matrix in a separate line of the resource file. Reading and maintaining this file would be simple, because there would be no other mark-up around your numbers.
Here is a link to an answer explaining how to read a file from a resource.

Read the file once on demand.
As you have a table/matrix, I suggest having one line per row. Read each line and split the numbers and parse them individually.

You could keep the rows in a string (thus reducing the number of objects for java to handle) as comma separated values, and on program start, split each row and so build up your table of longs.

using java to parse a csv then save in 2D array

Okay so i am working on a game based on a Trading card game in java. I Scraped all of the game peices' "information" into a csv file where each row is a game peice and each column is a type of attribute for that peice. I have spent hours upon hours writing code with Buffered reader and etc. trying to extract the information from my csv file into a 2d Array but to no avail. My csv file is linked Here: http://dl.dropbox.com/u/3625527/MonstersFinal.csv I have one year of computer science under my belt but I still cannot figure out how to do this.
So my main question is how do i place this into a 2D array that way i can keep the rows and columns?

Well, as mentioned before, some of your strings contain commas, so initially you're starting from a bad place, but I do have a solution and it's this:
--------- If possible, rescrape the site, but perform a simple encoding operation when you do. You'll want to do something like what you'll notice tends to be done in autogenerated XML files which contain HTML; reserve a 'control character' (a printable character works best, here, for reasons of debugging and... well... sanity) that, once encoded, is never meant to be read directly as an instance of itself. Ampersand is what I like to use because it's uncommon enough but still printable, but really what character you want to use is up to you. What I would do is write the program so that, at every instance of ",", that comma would be replaced by "&c" before being written to the CSV, and at every instance of an actual ampersand on the site, that "&" would be replaced by "&a". That way, you would never have the issue of accidentally separating a single value into two in the CSV, and you could simply decode each value after you've separated them by the method I'm about to outline in...
-------- Assuming you know how many columns will be in each row, you can use the StringTokenizer class (look it up- it's awesome and built into Java. A good place to look for information is, as always, the Java Tutorials) to automatically give you the values you need in the form of an array.
It works by your passing in a string and a delimiter (in this case, the delimiter would be ','), and it spitting out all the substrings which were separated by those commas. If you know how many pieces there are in total from the get-go, you can instantiate a 2D array at the beginning and just plug in each row the StringTokenizer gives them to you. If you don't, it's still okay, because you can use an ArrayList. An ArrayList is nice because it's a higher-level abstraction of an array that automatically asks for more memory such that you can continue adding to it and know that retrieval time will always be constant. However, if you plan on dynamically adding pieces, and doing that more often than retrieving them, you might want to use a LinkedList instead, because it has a linear retrieval time, but a much better relation than an ArrayList for add-remove time. Or, if you're awesome, you could use a SkipList instead. I don't know if they're implemented by default in Java, but they're awesome. Fair warning, though; the cost of speed on retrieval, removal, and placement comes with increased overhead in terms of memory. Skip lists maintain a lot of pointers.
If you know there should be the same number of values in each row, and you want them to be positionally organized, but for whatever reason your scraper doesn't handle the lack of a value for a row, and just doesn't put that value, you've some bad news... it would be easier to rewrite the part of the scraper code that deals with the lack of values than it would be to write a method that interprets varying length arrays and instantiates a Piece object for each array. My suggestion for this would again be to use the control character and fill empty columns with &n (for 'null') to be interpreted later, but then specifics are of course what will individuate your code and coding style so it's not for me to say.
edit: I think the main thing you should focus on is learning the different standard library datatypes available in Java, and maybe learn to implement some of them yourself for practice. I remember implementing a binary search tree- not an AVL tree, but alright. It's fun enough, good coding practice, and, more importantly, necessary if you want to be able to do things quickly and efficiently. I don't know exactly how Java implements arrays, because the definition is "a contiguous section of memory", yet you can allocate memory for them in Java at runtime using variables... but regardless of the specific Java implementation, arrays often aren't the best solution. Also, knowing regular expressions makes everything much easier. For practice, I'd recommend working them into your Java programs, or, if you don't want to have to compile and jar things every time, your bash scripts (if your using *nix) and/or batch scripts (if you're using Windows).

I think the way you've scraped the data makes this problem more difficult than it needs to be. Your scrape seems inconsistent and difficult to work with given that most values are surrounded by quotes inconsistently, some data already has commas in it, and not each card is on its own line.
Try re-scraping the data in a much more consistent format, such as:
R1C1|R1C2|R1C3|R1C4|R1C5|R1C6|R1C7|R1C8
R2C1|R2C2|R2C3|R2C4|R2C5|R2C6|R2C7|R3C8
R3C1|R3C2|R3C3|R3C4|R3C5|R3C6|R3C7|R3C8
R4C1|R4C2|R4C3|R4C4|R4C5|R4C6|R4C7|R4C8
A/D Changer|DREV-EN005|Effect Monster|Light|Warrior|100|100|You can remove from play this card in your Graveyard to select 1 monster on the field. Change its battle position.
Where each line is definitely its own card (As opposed to the example CSV you posted with new lines in odd places) and the delimiter is never used in a data field as something other than a delimiter.
Once you've gotten the input into a consistently readable state, it becomes very simple to parse through it:
BufferedReader br = new BufferedReader(new FileReader(new File("MonstersFinal.csv")));
String line = "";
ArrayList<String[]> cardList = new ArrayList<String[]>(); // Use an arraylist because we might not know how many cards we need to parse.
while((line = br.readLine()) != null) { // Read a single line from the file until there are no more lines to read
StringTokenizer st = new StringTokenizer(line, "|"); // "|" is the delimiter of our input file.
String[] card = new String[8]; // Each card has 8 fields, so we need room for the 8 tokens.
for(int i = 0; i < 8; i++) { // For each token in the line that we've read:
String value = st.nextToken(); // Read the token
card[i] = value; // Place the token into the ith "column"
}
cardList.add(card); // Add the card's info to the list of cards.
}
for(int i = 0; i < cardList.size(); i++) {
for(int x = 0; x < cardList.get(i).length; x++) {
System.out.printf("card[%d][%d]: ", i, x);
System.out.println(cardList.get(i)[x]);
}
}
Which would produce the following output for my given example input:
card[0][0]: R1C1
card[0][1]: R1C2
card[0][2]: R1C3
card[0][3]: R1C4
card[0][4]: R1C5
card[0][5]: R1C6
card[0][6]: R1C7
card[0][7]: R1C8
card[1][0]: R2C1
card[1][1]: R2C2
card[1][2]: R2C3
card[1][3]: R2C4
card[1][4]: R2C5
card[1][5]: R2C6
card[1][6]: R2C7
card[1][7]: R3C8
card[2][0]: R3C1
card[2][1]: R3C2
card[2][2]: R3C3
card[2][3]: R3C4
card[2][4]: R3C5
card[2][5]: R3C6
card[2][6]: R3C7
card[2][7]: R4C8
card[3][0]: R4C1
card[3][1]: R4C2
card[3][2]: R4C3
card[3][3]: R4C4
card[3][4]: R4C5
card[3][5]: R4C6
card[3][6]: R4C7
card[3][7]: R4C8
card[4][0]: A/D Changer
card[4][1]: DREV-EN005
card[4][2]: Effect Monster
card[4][3]: Light
card[4][4]: Warrior
card[4][5]: 100
card[4][6]: 100
card[4][7]: You can remove from play this card in your Graveyard to select 1 monster on the field. Change its battle position.
I hope re-scraping the information is an option here and I hope I haven't misunderstood anything; Good luck!
On a final note, don't forget to take advantage of OOP once you've gotten things worked out. a Card class could make working with the data even simpler.

I'm working on a similar problem for use in machine learning, so let me share what I've been able to do on the topic.
1) If you know before you start parsing the row - whether it's hard-coded into your program or whether you've got some header in your file that gives you this information (highly recommended) - how many attributes per row there will be, you can reasonably split it by comma, for example the first attribute will be RowString.substring(0, RowString.indexOf(',')), the second attribute will be the substring from the first comma to the next comma (writing a function to find the nth instance of a comma, or simply chopping off bits of the string as you go through it, should be fairly trivial), and the last attribute will be RowString.substring(RowString.lastIndexOf(','), RowString.length()). The String class's methods are your friends here.
2) If you are having trouble distinguishing between commas which are meant to separate values, and commas which are part of a string-formatted attribute, then (if the file is small enough to reformat by hand) do what Java does - represent characters with special meaning that are inside of strings with '\,' rather than just ','. That way you can search for the index of ',' and not '\,' so that you will have some way of distinguishing your characters.
3) As an alternative to 2), CSVs (in my opinion) aren't great for strings, which often include commas. There is no real common format to CSVs, so why not make them colon-separated-values, or dash-separated-values, or even triple-ampersand-separated-values? The point of separating values with commas is to make it easy to tell them apart, and if commas don't do the job there's no reason to keep them. Again, this applies only if your file is small enough to edit by hand.
4) Looking at your file for more than just the format, it becomes apparent that you can't do it by hand. Additionally, it would appear that some strings are surrounded by triple double quotes ("""string""") and some are surrounded by single double quotes ("string"). If I had to guess, I would say that anything included in a quotes is a single attribute - there are, for example, no pairs of quotes that start in one attribute and end in another. So I would say that you could:
Make a class with a method to break a string into each comma-separated fields.
Write that method such that it ignores commas preceded by an odd number of double quotes (this way, if the quote-pair hasn't been closed, it knows that it's inside a string and that the comma is not a value separator). This strategy, however, fails if the creator of your file did something like enclose some strings in double double quotes (""string""), so you may need a more comprehensive approach.

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