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How to implement sort in hadoop?


How to implement sort in hadoop?

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How to implement sort in hadoop?
Tag : sorting , By : Vlad Sirenko
Date : November 24 2020, 05:47 AM


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Hadoop configuration - are mapper/combiner affected by io.sort.factor and io.sort.mb?


Tag : development , By : eataix
Date : March 29 2020, 07:55 AM
This might help you Yes, they are used on the map side too (irrespective of whether you have a combiner or not):
MapTask.java io.sort.factor - line 1695 io.sort.mb - lines 932 - 944

how to sort numerically in hadoop's shuffle/sort phase?


Tag : sorting , By : 66.
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further Assuming you are using Hadoop Streaming, you need to use the KeyFieldBasedComparator class.
#!/usr/bin/env python
import sys
for line in sys.stdin:    
    print "%s" % (line.strip())
1
11
2
20
7
3
40
$HADOOP_HOME/bin/hadoop  jar $HADOOP_HOME/hadoop-streaming.jar 
-D mapred.output.key.comparator.class=org.apache.hadoop.mapred.lib.KeyFieldBasedComparator 
-D  mapred.text.key.comparator.options=-n 
-input /user/input.txt 
-output /user/output.txt 
-file ~/mapper.py 
-mapper ~/mapper.py 
-file ~/reducer.py 
-reducer ~/reducer.py
1   
2   
3   
7   
11  
20  
40

Golang Sort :does not implement sort.Interface (missing Len method)


Tag : sorting , By : Fenix Drakken
Date : March 29 2020, 07:55 AM
may help you . []*Team is not the same as Teams; you need to explicitly use or cast to the latter:
type Group struct {
   Teams Teams
}
sort.Sort(group.Teams)
type Group struct {
   Teams []*Team
}
sort.Sort(Teams(group.Teams))

How to implement sort on specific atribute of object in custom sort function?


Tag : python , By : Piotr Balas
Date : March 29 2020, 07:55 AM
seems to work fine If you want to use a key, you'll have to modify your functions accordingly, by adding a key argument, and using it every time you compare elements of the list (e.g., a[middle] < a[high] should be key(a[middle]) < key(a[high]), or key(a[i]) < key(pivot_val), etc.):
As an example:
def default_key(x): # default key: use the value as-is
    return x

def quick_sort(a, key=default_key):  # accept keyword argument `key`
    quick_sort2(a, 0, len(a)-1, key=key) # pass on the key

def quick_sort2(a, low, high, key=default_key):
    if low < high:
        split = partition(a, low, high, key=key)  # pass the key
        quick_sort2(a, low, split-1, key=key)
        quick_sort2(a, split + 1, high, key=key)


def partition(a, low, high, key):
    pivot_idx = get_pivot(a, low, high, key=key)
    ...
        if key(a[i]) < key(pivot_val):
            ...


def get_pivot(a, low, high, key=default_key):  # selecting best pivot
...
    if key(a[low]) < key(a[middle]):
        if key(a[middle]) < key(a[high]):
...

Difference between partial sort, total sort and secondary sort in hadoop


Tag : hadoop , By : woxorz
Date : March 29 2020, 07:55 AM
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