How does reducer in hadoop mapreduce handles keys with values more than what single container can handle?
I am hinting at a case, where input data is skewed heavily to that level where there are huge number records against a key emitted in mapper phase. After shuffle & sort phase, these records against that key cannot be passed to a single container (reducer JVM) owing to limited heap space. How does hadoop mapreduce handle such cases? I am assuming the iterator we get the in the reducer is some sort of a distributed iterator and not just in-memory.
I tried going through a lot of documentation but could not find a mention of it somewhere. But I could see that pig does that and would like to understand how plain mapreduce achieves this.
Any pointers would be much appreciated !!
hadoop mapreduce reducers
asked Nov 22 at 19:07
akshay
43
add a comment |
I am hinting at a case, where input data is skewed heavily to that level where there are huge number records against a key emitted in mapper phase. After shuffle & sort phase, these records against that key cannot be passed to a single container (reducer JVM) owing to limited heap space. How does hadoop mapreduce handle such cases? I am assuming the iterator we get the in the reducer is some sort of a distributed iterator and not just in-memory.
I tried going through a lot of documentation but could not find a mention of it somewhere. But I could see that pig does that and would like to understand how plain mapreduce achieves this.
Any pointers would be much appreciated !!
hadoop mapreduce reducers
asked Nov 22 at 19:07
akshay
43
MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31
add a comment |
I am hinting at a case, where input data is skewed heavily to that level where there are huge number records against a key emitted in mapper phase. After shuffle & sort phase, these records against that key cannot be passed to a single container (reducer JVM) owing to limited heap space. How does hadoop mapreduce handle such cases? I am assuming the iterator we get the in the reducer is some sort of a distributed iterator and not just in-memory.
I tried going through a lot of documentation but could not find a mention of it somewhere. But I could see that pig does that and would like to understand how plain mapreduce achieves this.
Any pointers would be much appreciated !!
hadoop mapreduce reducers
asked Nov 22 at 19:07
akshay
43
I am hinting at a case, where input data is skewed heavily to that level where there are huge number records against a key emitted in mapper phase. After shuffle & sort phase, these records against that key cannot be passed to a single container (reducer JVM) owing to limited heap space. How does hadoop mapreduce handle such cases? I am assuming the iterator we get the in the reducer is some sort of a distributed iterator and not just in-memory.
I tried going through a lot of documentation but could not find a mention of it somewhere. But I could see that pig does that and would like to understand how plain mapreduce achieves this.
Any pointers would be much appreciated !!
hadoop mapreduce reducers
hadoop mapreduce reducers
asked Nov 22 at 19:07
akshay
43
asked Nov 22 at 19:07
akshay
43
asked Nov 22 at 19:07
akshay
43
asked Nov 22 at 19:07
akshay
43
asked Nov 22 at 19:07
akshay
43
43
MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31
add a comment |
MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31
MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31
MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31
add a comment |
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MapReduce isn't immune to out of memory issues
– cricket_007
Nov 22 at 20:31