I went through the cloudera blog and I got an article(Link below).Refer to the third point.
http://blog.cloudera.com/blog/2011/01/lessons-learned-from-clouderas-hadoop-developer-training-course/
As per my understanding, if there are 2 input splits, then the broken line will be read by the record reader of the first input split.
If I am getting it correct, can you tell me how it does that i.e how the record reader of the first split reads the broken line past the input split ?
As per my understanding, if there are 2 input splits, then the broken line will be read by the record reader of the first input split.
Yes, this is correct.
can you tell me how it does that i.e how the record reader of the first split reads the broken line past the input split
An InputSplit doesn't contain the raw data, but rather the information needed to extract the data. A FileInputSplit (which is what you're referring to) contains a path to the file as well as the byte offsets to read in the file. It is then up to the RecordReader to go out and read that data. This means that it can read past the end byte offset defined by the split.
Related
I have a project in spring batch where I must read from two .txt files, one has many lines and the other is a control file that has the number of lines that should be read from the first file. I know that I must use partition to process these files because the first one is very large and I need to divide it and be able to restart it in case it fails but I don't know how the reader should handle these files since both files do not have the same width in their lines.
None of the files have a header or separator in their lines, so i have to obtain the fields according to a range mainly in the first one.
One of my doubts is whether I should read both in the same reader? And how should I set the reader FixedLengthTokenizer and DefaultLineMapper to handle both files in the case of using the same reader??
These are examples of the input file and the control file
- input file
09459915032508501149343120020562580292792085100204001530012282921883101 the txt file can contain up to 50000 lines
- control file
00128*
It only has one line
Thanks!
I must read from two .txt files, one has many lines and the other is a control file that has the number of lines that should be read from the first file
Here is a possible way to tackle your use case:
Create a first step (tasklet) that reads the control file and put the number of lines to read in the job execution context (to share it with the next step)
Create a second step (chunk-oriented) with a step scoped reader that is configured to read only the number of lines calculated by the first step (get value from job execution context)
You can read more about sharing data between steps here: https://docs.spring.io/spring-batch/docs/4.2.x/reference/html/common-patterns.html#passingDataToFutureSteps
I would like to know how the files are split in Hadoop. I mean, i know they are split by some size (e.g. 64MB), but does the break occur, at the end of a line or at some character etc?
Also how does the name node keep track of the sequence in which the files are split, like how to assemble them in which order after they are collected from the data nodes.
LineRecordReader reads every line and sends key/value pairs to mapper instance.
If EOL appears before defined block size(in this case 64MB), reader continues to next line.
Now, If reader reaches block size and not EOL, then it continues to read until EOL and set as a block.
Now, next block starts from where reader stopped(i.e., after EOL).
Reference
I am a novice in Hadoop and here I have the following questions:
(1) As I can understand, the original input file is split into several blocks and distributed over the network. Does a map function always execute on a block in its entirety? Could there be more than one map functions executing on data in a single block?
(2) Is there any way that it can be learned, from within the map function, which section of the original input text the mapper is currently working on? I would like to get something like a serial number, for instance, for each block starting from the first block of the input text.
(3) Is it possible to make the splits of the input text in such a way that each block has a predefined word count? If possible then how?
Any help would be appreciated.
As I can understand, the original input file is split into several blocks and distributed over the network. Does a map function always execute on a block in its entirety? Could there be more than one map functions executing on data in a single block?
No. A block(split to be precise) gets processed by only one mapper.
Is there any way that it can be learned, from within the map function, which section of the original input text the mapper is currently working on? I would like to get something like a serial number, for instance, for each block starting from the first block of the input text.
You can get some valuable info, like the file containing split's data, the position of the first byte in the file to process. etc, with the help of FileSplit class. You might find it helpful.
Is it possible to make the splits of the input text in such a way that each block has a predefined word count? If possible then how?
You can do that by extending FileInputFormat class. To begin with you could do this :
In your getSplits() method maintain a counter. Now, as you read the file line by line keep on tokenizing them. Collect each token and increase the counter by 1. Once the counter reaches the desired value, emit the data read upto this point as one split. Reset the counter and start with the second split.
HTH
If you define a small max split size you can actually have multiple mappers processing a single HDFS block (say 32mb max split for a 128 MB block size - you'll get 4 mappers working on the same HDFS block). With the standard input formats, you'll typically never see two or more mappers processing the same part of the block (the same records).
MapContext.getInputSplit() can usually be cast to a FileSplit and then you have the Path, offset and length of the file being / block being processed).
If your input files are true text flies, then you can use the method suggested by Tariq, but note this is highly inefficient for larger data sources as the Job Client has to process each input file to discover the split locations (so you end up reading each file twice). If you really only want each mapper to process a set number of words, you could run a job to re-format the text files into sequence files (or another format), and write the records down to disk with a fixed number of words per file (using Multiple outputs to get a file per number of words, but this again is inefficient). Maybe if you shared the use case as for why you want a fixed number of words, we can better understand your needs and come up with alternatives
I have designed a system where each map function is suppose to load its input (file split containing multiple CSV records) into a data structure and process them rather than processing line by line. There will be multiple Mapppers since I will be processing millions of records hence one mapper is totally inefficient.
I see from the example in WordCount, that the map function is reading line by line. Almost as of the map function is invoked for each line from the split it receives. I believe the input to this map should be the complete lines itself instead of sending it one line at a time.
Reduce function has other tasks at hand. So I guess, the map function could be tweaked to do the task its assigned. Is there a workaround?
From what you explain I understand that your map input is not single line but some structure built from the several lines. In this case - you should create your own InputFormat which will convert the input stream (from the split) to the sequence of objects of YourDataStructure cluss. And Your mapper will accept these YourDataStructure objects.
If the whole script is actually structure you want to process - I would suggest to do all the logic in mapper in one trick - you should know when there is last line in split. It can be done by inheriting TextInputFormat and tweak it to indicate you that there is last line. Then you build your structure in mapper, line by line, and when last line is indicated - do the job.
gurus!
A long time i can't found answer on following question: how hadoop splitting big file during writing.
Example:
1) Block size 64 Mb
2) File size 128 Mb (flat file, containing text).
When i writing file it's will be split at 2 part (file size / block size).
But... Could occurrence following
Block1 will be ended at
...
word300 word301 wo
and Block 2 will be start
rd302 word303
...
Write case will be
Block1 will be ended at
...
word300 word301
and Block 2 will be start
word302** word303
...
or can you link at the place where write about hadoop splitting algoritms.
Thank you in advance!
looks this wiki page, hadoop InputFormat will read the last line of the FileSplit past the split boundary and, when reading other than the first FileSplit, it ignores the content up to the first newline.
The file will be split arbitrarily based on bytes. So it will likely split it into something like wo and rd302.
This is not a problem you have to typically worried about and is how the system is designed. The InputFormat and RecordReader part of a MapReduce job deal with records split between record boundaries.