I have a flat file tables say, student.tbl and employee.tbl. Both files are fixed length files. I have a supporting files for both files with the information field code, field description, field Offset and field size.
for example,
ename string 0 10
eage number 10 2
ecity string 12 10
I wrote code to fetch data from the flat files using STL in c++. I am using vector to load those data.
My simple algorithm to load data from Fixed Length file.
1) Read Supporting file.
2) Load supporting file data into a 2D vector string say,
column_records;
3) Read Table file.
4) Get First Line from the Table File, say Data Line.
5) Get First Column Information from the supporting Table Which is
First Row of column_records.
6) Chop Data Line based on the column_record
7) Push the chopped data into a One Dimensional Vector say,
record_vector.
8) Do Step 5, Until the Last Column Information has processed.
9) Push record_vector into 2D vector say,Table_Vector.
10) Do Step 4, Until the last line of the Fixed File has reached.
Well. I did it well. It works fine. But my problem is, in Step 5.
For every fixed length data, I feel there was some repeat Iterations.
I know for a fact, First Fixed Length data itself can have retain the column descriptions for other fixed length data. But I repeatedly doing the Iteration N*M. I wish to my iteration should be 1*M.
I know that I can store my column description in a Structure array. But I have many type of tables. say students.tbl and employee.tbl. Both have different set of columns. So I think it will be bad Idea to have 'N'-struct declaration to load 'N'-supporting Tables.
I wish to use same routine to fetch data from the both tables or 'N' tables. My supporting table format will not be changed. It is in tab delimited format. This is my case.
How do I fetch data from table with 1*M iteration?
I hope I can use enumeration to do this. But I don't know how to do that? will using enumeration or macro solve this issue?
I hope my working source code will not be needed for this Question. If you think source code are needed to answer this question, definitely I will update this question with that source code. I have medium level of English Knowledge. So Sorry for Inconvenience.
Thank You.
Related
Is there a way, where I can open a file that contains a large amount of data, and retrieve only one specific row or index, without getting the rest of the content as well?
Update:
Based on what others have mentioned here in the comments, I have some follow-up questions.
Can anyone give me an example of how to put a fixed width on the rows/linebreaks(whatever you want to call it), or show me a good source where I can read more about it?
So if I set this up correctly, I will be able to get a specific line from the file superfast, even if it contains several million rows?
If you want to access a file by records or rows, and the rows are not fixed length, you'll have to create a structure that you can associate (or map) file positions to row indices.
I recommend using std::vector<std::streampos>.
Read through the file.
When the file is at the beginning of a row, read the file position and append to the vector.
If you need to access a row in the file:
1) Use the vector to get the file position of the row.
2) Seek to the row using the file position.
This technique will work with fixed length and variable length rows.
I have a .CSV file that's storing data from a laser. It records the height of the laser beam every second.
The .CSV file ends up having rows for each measurement that are all in this format:
DR,04,#
where the # is the height reading.
For example, if the beam is at a height of 10, the reading would say:
DR,04,10.
I want my program in C++ to read only the height (third column of the .CSV) from each row and put it into an array. I do not want the first two columns at all. That way I end up with an array with just a bunch of height values from each measurement.
How do I do that?
You can use strtok() to separate out the three columns. And then just get the last value.
You could also just take the string and scan for the first comma, and then scan from there for the second comma. What follows is the value you are after.
You could also use sscanf() to parse out the individual values.
This really isn't a difficult problem, and there are many ways to approach it. That is why people are complaining that you probably should've tried something and then ask a question here when you get stuck on a specific question.
I have a file as follows:
The file consists of 2 parts: header and data.
The data part is separated into equally sized pages. Each page holds data for a specific metric. Multiple pages (needs not to be consecutive) might be needed to hold data for a single metric. Each page consists of a page header and a page body. A page header has a field called "Next page" that is the index of the next page that holds data for the same metric. A page body holds real data. All pages have the same & fixed size (20 bytes for header and 800 bytes for body (if data amount is less than 800 bytes, 0 will be filled)).
The header part consists of 20,000 elements, each element has information about a specific metric (point 1 -> point 20000). An element has a field called "first page" that is actually index of the first page holding data for the metric.
The file can be up to 10 GB.
Requirement: Re-order data of the file in the shortest time, that is, pages holding data for a single metric must be consecutive, and from metric 1 to metric 20000 according to alphabet order (header part must be updated accordingly).
An apparent approach: For each metric, read all data for the metric (page by page), write data to new file. But this takes much time, especially when reading data from the file.
Is there any efficient ways?
One possible solution is to create an index from the file, containing the page number and the page metric that you need to sort on. Create this index as an array, so that the first entry (index 0) corresponds to the first page, the second entry (index 1) the second page, etc.
Then you sort the index using the metric specified.
When sorted, you end up with a new array which contains a new first, second etc. entries, and you read the input file writing to the output file in the order of the sorted index.
An apparent approach: For each metric, read all data for the metric (page by page), write data to new file. But this takes much time, especially when reading data from the file.
Is there any efficient ways?
Yes. After you get a working solution, measure it's efficiency, then decide which parts you wish to optimize. What and how you optimize will depend greatly on what results you get here (what are your bottlenecks).
A few generic things to consider:
if you have one set of steps that read data for a single metric and move it to the output, you should be able to parallelize that (have 20 sets of steps instead of one).
a 10Gb file will take a bit to process regardless of what hardware you run your code on (concievably, you could run it on a supercomputer but I am ignoring that case). You / your client may accept a slower solution if it displays it's progress / shows a progress bar.
do not use string comparisons for sorting;
Edit (addressing comment)
Consider performing the read as follows:
create a list of block offset for the blocks you want to read
create a list of worker threads, of fixed size (for example, 10 workers)
each idle worker will receive the file name and a block offset, then create a std::ifstream instance on the file, read the block, and return it to a receiving object (and then, request another block number, if any are left).
read pages should be passed to a central structure that manages/stores pages.
Also consider managing the memory for the blocks separately (for example, allocate chunks of multiple blocks preemptively, when you know the number of blocks to be read).
I first read header part, then sort metrics in alphabetic order. For each metric in the sorted list I read all data from the input file and write to the output file. To remove bottlenecks at reading data step, I used memory mapping. The results showed that when using memory mapping the execution time for an input file of 5 GB was reduced 5 ~ 6 times compared with when not using memory mapping. This way temporarily solve my problems. However, I will also consider suggestions of #utnapistim.
i've written a thrift-definition, and used this defintion to serialize multiple records in one file (i've added the size of the whole record at the beginning of each record). That is in short what I have done.
boost::shared_ptr<apache::thrift::transport::TMemoryBuffer> transport(new apache::thrift::transport::TMemoryBuffer);
boost::shared_ptr<apache::thrift::protocol::TBinaryProtocol> protocol(new apache::thrift::protocol::TBinaryProtocol(transport));
myClass->write(protocol.get());
const std::string & data(transport->getBufferAsString());
Afterwards i just print the string data in binary mode. Now I want to deserialize this file again. I wouldn't have any problem if there was only on record in the file, unfortunately I have to print multiple files, so I guess I have to work with offset based on the size i saved in the file along with the record itself. However, I can't seem to find any example I can use to achieve my goals, and the official documentation is quite lacking. Has anyone any tipps for me. If I'm missing some information, just ask.
Further Informations:
Of course I want to use use thrift to deserialize. However, one file can contain multiple records. For example: Imagine I have defined a struct in a thrift-definition file that contains car-Information. Now I serialize multiple car-structs in one output file. Serializing is no problem as i just append the data. If i want to deserialize however, I have to know where one record starts, and the next begins. That is my problem. I don't know how to tell thrift where one record begins and ends. I've searched the internet, but can't seem to find an example for c++ (i got one for python so far, but am not able to translate it to c++). The structure of one file can be described as followed: [lenghtofrecord1][record1][lengthofrecord2][record2][...]
Thanks in Advance
Michael
How about having a list<records> that you de/serialize as a whole? Or is it an absolute requirement to read them independently and randomly? If yes, I see 1,5 (one and a half) possible solutions:
Have a second file as an index. This holds a map< recordNumber, offset>, or simply a sorted list of integers-pairs, to quickly locate records. Since these data are much less than the records you probably can cache it in memory all the time.
The half solution: iff the record size is fixed, any records position could be calculated easily by multiplying recordSize * (recordNr-1). This way you don't even need the size prefix. If you have strings in the record or other variable-sized entities, this will not work, unless you force a fixed record size by reserving a buffer for each record with a predefined (maximum) size. It's a little ugly, thus the "half" solution, but you don't need the index file.
Although maybe not the perfect solution, this seems to work for me:
boost::shared_ptr<apache::thrift::transport::TMemoryBuffer> transport(new apache::thrift::transport::TMemoryBuffer);
boost::shared_ptr<apache::thrift::protocol::TBinaryProtocol> protocol(new apache::thrift::protocol::TBinaryProtocol(transport));
transport->resetBuffer((uint8_t*) buffer, sizeOfEntry);
Buffer is a char array containing the desired record (I used seekg for the offset) and sizeOfEntry is the records size. Afterwards I can go on with the automatically generated read-Method of my thrift-generated class. In Fact I had this solution earlier, I just messed up my offset, thus it didn't work.
I have a CSV file that has about 10 different columns. Im trying to figure out whats the best method to go about here.
Data looks like this:
"20070906 1 0 0 NO"
Theres about 40,000 records like this to be analyzed. Im not sure whats best here, split each column into its own vector, or put each whole row into a vector.
Thanks!
I think this is kind of subjective question but imho I think that having a single vector that contains the split up rows will likely be easier to manage than separate vectors for each column. You could even create a row object that the vector stores to make accessing and processing the data in the rows/columns more friendly.
Although if you are only doing processing on a column level and not on a row or entry level having individual column vectors would be easier.
Since the data set is fairly small (assuming you are using a PC and not some other device, like a smartphone), you can read the file line by line into a vector of strings and then parse the elements one by one and populate a vector of some structures holding the records data.