I have to generate a 4 char unique string from a long value

I got a requirment
I have to generate a 4 char unique string from a long value
Eeach char can be any of 32 character defined has below.
private static final char char_map[] = new char[]{'7','2','6','9','5','3','4','8','X','M','G','D','A','E','B','F','C','Q','J','Y','H','U','W','V','S','K','R','L','N','P','Z','T'};
So for 4 char string the possible combination can be 32 * 32 * 32 * 32 = 1048576
If any one passes a long value between 0 - 1048576 , it should generate a unique 4 char string.
Any one with idea will be a great help.

Well, a long is 64 bits. A char is 16 bits. Once you determine how you want to map the long's bits to your char bits, go google for "java bitwise operators".

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Hello everyone
I am relative novice to Java, I have procedural C programming background.
I am reading many very large (many GB) comma/double-quote separated ASCII CSV text files and performing various kinds of pre-processing on them, prior to loading into the database.
I am using Java7 (the latest) and using NIO.2.
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I read a file, one line/record at a time and then I process it. The regex is not an option (too slow and can not handle all cases I need to cover).
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>
Once I took that String.length() method out of the 'for loop' and used integer length local variable, as you have in your code, the performance is very close between array of char and String charAt() approaches.
>
You are still worrying about something that is irrevelant in the greater scheme of things.
It doesn't matter how fast the CPU processing of the data is if it is faster than you can write the data to the sink. The process is:
1. read data into memory
2. manipulate that data
3. write data to a sink (database, file, network)
The reading and writing of the data are going to be tens of thousands of times slower than any CPU you will be using. That read/write part of the process is the limiting factor of your throughput; not the CPU manipulation of step #2.
Step #2 can only go as fast as steps #1 and #3 permit.
Like I said above:
>
The best 'file to database' performance you could hope to achieve would be loading simple, 'known to be clean', record of a file into ONE table column defined, perhaps, as VARCHAR2(1000); that is, with NO processing of the record at all to determine column boundaries.
That performance would be the standard you would measure all others against and would typically be in the hundreds of thousands or millions of records per minute.
What you would find is that you can perform one heck of a lot of processing on each record without slowing that 'read and load' process down at all.
>
Regardless of the sink (DB, file, network) when you are designing data transport services you need to identify the 'slowest' parts. Those are the 'weak links' in the data chain. Once you have identified and tuned those parts the performance of any other step merely needs to be 'slightly' better to avoid becoming a bottleneck.
That CPU part for step #2 is only rarely, if every the problem. Don't even consider it for specialized tuning until you demonstrate that it is needed.
Besides, if your code is properly designed and modularized you should be able to 'plug n play' different parse and transform components after the framework is complete and in the performance test stage.
>
The only thing that is fixed is that all input files are ASCII (not Unicode) characters in range of 'space' to '~' (decimal 32-126) or common control characters like CR,LF,etc.
>
Then you could use byte arrays and byte processing to determine the record boundaries even if you then use String processing for the rest of the manipulation.
That is what my framework does. You define the character set of the file and a 'set' of allowable record delimiters as Strings in that character set. There can be multiple possible record delimiters and each one can be multi-character (e.g. you can use 'XyZ' if you want.
The delimiter set is converted to byte arrays and the file is read using RandomAccessFile and double-buffering and a multiple mark/reset functionality. The buffers are then searched for one of the delimiter byte arrays and the location of the delimiter is saved. The resulting byte array is then saved as a 'physical record'.
Those 'physical records' are then processed to create 'logical records'. The distinction is due to possible embedded record delimiters as you mentioned. One logical record might appear as two physical records if a field has an embedded record delimiter. That is resolved easily since each logical record in the file MUST have the same number of fields.
So a record with an embedded delimiter will have few fields than required meaning it needs to be combined with one, or more of the following records.
>
My files have no metadata, some are comma delimited and some comma and double quote delimited together, to protect the embedded commas inside columns.
>
I didn't mean the files themselves needed to contain metadata. I just meant that YOU need to know what metadata to use. For example you need to know that there should ultimately be 10 fields for each record. The file itself may have fewer physical fields due to TRAILING NULLCOS whereby all consecutive NULL fields at the of a record do not need to be present.
>
The number of columns in a file is variable and each line in any one file can have a different number of columns. Ragged columns.
There may be repeated null columns in any like ,,, or "","","" or any combination of the above.
There may also be spaces between delimiters.
The files may be UNIX/Linux terminated or Windows Server terminated (CR/LF or CR or LF).
>
All of those are basic requirements and none of them present any real issue or problem.
>
To make it even harder, there may be embedded LF characters inside the double quoted columns too, which need to be caught and weeded out.
>
That only makes it 'harder' in the sense that virtually NONE of the standard software available for processing delimited files take that into account. There have been some attempts (you can find them on the net) for using various 'escaping' techniques to escape those characters where they occur but none of them ever caught on and I have never found any in widespread use.
The main reason for that is that the software used to create the files to begin with isn't written to ADD the escape characters but is written on the assumption that they won't be needed.
That read/write for 'escaped' files has to be done in pairs. You need a writer that can write escapes and a matching reader to read them.
Even the latest version of Informatica and DataStage cannot export a simple one column table that contains an embedded record delimiter and read it back properly. Those tools simply have NO functionality to let you even TRY to detect that embedded delimiters exist let alone do any about it by escaping those characters. I gave up back in the '90s trying to convince the Informatica folk to add that functionality to their tool. It would be simple to do.
>
Some numeric columns will also need processing to handle currency signs and numeric formats that are not valid for the database inpu.
It does not feel like a job for RegEx (I want to be able to maintain the code and complex Regex is often 'write-only' code that a 9200bpm modem would be proud of!) and I don't think PL/SQL will be any faster or easier than Java for this sort of character based work.
>
Actually for 'validating' that a string of characters conforms (or not) to a particular format is an excellent application of regular expressions. Though, as you suggest, the actual parsing of a valid string to extract the data is not well-suited for RegEx. That is more appropriate for a custom format class that implements the proper business rules.
You are correct that PL/SQL is NOT the language to use for such string parsing. However, Oracle does support Java stored procedures so that could be done in the database. I would only recommend pursuing that approach if you were already needing to perform some substantial data validation or processing the DB to begin with.
>
I have no control over format of the incoming files, they are coming from all sorts of legacy systems, many from IBM mainframes or AS/400 series, for example. Others from Solaris and Windows.
>
Not a problem. You just need to know what the format is so you can parse it properly.
>
Some files will be small, some many GB in size.
>
Not really relevant except as it relates to the need to SINK the data at some point. The larger the amount of SOURCE data the sooner you need to SINK it to make room for the rest.
Unfortunately, the very nature of delimited data with varying record lengths and possible embedded delimiters means that you can't really chunk the file to support parallel read operations effectively.
You need to focus on designing the proper architecture to create a modular framework of readers, writers, parsers, formatters, etc. Your concern with details about String versus Array are way premature at best.
My framework has been doing what you are proposing and has been in use for over 20 years by three different major nternational clients. I have never had any issues with the level of detail you have asked about in this thread.
Throughout is limited by the performance of the SOURCE and the SINK. The processing in-between has NEVER been an issu.
A modular framework allows you to fine-tune or even replace a component at any time with just 'plug n play'. That is what Interfaces are all about. Any code you write for a parser should be based on an interface contract. That allows you to write the initial code using the simplest possible method and then later if, and ONLY if, that particular module becomes a bottlenect, replace that module with one that is more performant.
Your intital code should ONLY use standard well-established constructs until there is a demonstrated need for something else. For your use case that means String processing, not byte arrays (except for detecting record boundaries).

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I have to generate a 4 char unique string from a long value

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