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Difference between revisions of "MapReduce"

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(Created page with "<pre class=setup> #ENCODING import io import sys sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16') #MONGO from pymongo import MongoClient client = MongoClien...")
 
 
(76 intermediate revisions by 2 users not shown)
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<pre class=setup>
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{{TopTenTips}}
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#ENCODING
+
<div style="min-height:25em">
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import io
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==Introducing the MapReduce function==
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import sys
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The MapReduce function is an aggregate function that consists of two functions: Map and Reduce.
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16')
+
 
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#MONGO
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The map is always performed before the reduce.
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from pymongo import MongoClient
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client = MongoClient()
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The map function examines every document in the collection and emits '''(key,value)''' pairs.
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client.progzoo.authenticate('scott','tiger')
+
 
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db = client['progzoo']
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The map function takes no input however the current document can be accessed as '''this'''
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#PRETTY
+
 
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import pprint
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The reduce function has two inputs, for every distinct key emitted by map the reduce function is called with a list of the corresponding values.
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pp = pprint.PrettyPrinter(indent=4)
+
 
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</pre>
+
==Population of each continent==
 +
<div class=q data-lang="mongo">
 +
Here the map function emits the continent and the population for each country.
 +
 
 +
The reduce function uses the JavaScript function <code>Array.sum</code> to add the populations.
 +
<pre class="def"><nowiki>
 +
db.world.mapReduce(
 +
  function () {emit(this.continent, this.population);},
 +
  function (k, v) { return Array.sum(v); },
 +
  {out: {inline: 1}}
 +
);</nowiki></pre>
 +
</div>
 +
 
 +
==Number of countries in each continent==
 +
<div class=q data-lang="mongo">
 +
Instead of sending populations you can send a list one 1s to the reduce function.
 +
 
 +
The reduce function will now create a count of the number of countries in each continent.
 +
<pre class="def"><nowiki>
 +
db.world.mapReduce(
 +
  function () {emit(this.continent, 1);},
 +
  function (k, v) { return Array.sum(v); },
 +
  {out: {inline: 1}}
 +
);</nowiki></pre>
 +
</div>
 +
 
 +
==Count only some countries==
 +
<div class=q data-lang="mongo">
 +
The map function does not need to emit once for every entry.
 +
 
 +
In this example we are only counting the countries that have a large population.
 +
<pre class="def"><nowiki>
 +
db.world.mapReduce(
 +
  function () {
 +
    if (this.population > 100000000)
 +
    {
 +
      emit(this.continent, 1);
 +
    }
 +
  },
 +
  function (k, v) { return Array.sum(v); },
 +
  {out: {"inline": 1}}
 +
);</nowiki></pre>
 +
</div>
 +
 
 +
==Examine the reduce function==
 +
<div class=q data-lang="mongo">
 +
<p class="strong">Examine the reduce function.</p>
 +
 
 +
Here we emit the continent and the name, and in the reduce function we <code>return v.join(',')</code> to see a comma separated list of the values in the list.
 +
<pre class="def"><nowiki>
 +
db.world.mapReduce(
 +
  function () {
 +
    if (this.population > 100000000) {
 +
      emit(this.continent, this.name);
 +
    }
 +
  },
 +
  function (k, v) { return v.join(','); },
 +
  {out: {"inline": 1}}
 +
);</nowiki></pre>
 +
</div>
 +
 
 +
==Reduce to a single value==
 +
<div class=q data-lang="mongo">
 +
If you emit the same key every time you will get exactly one result from your query.
 +
 
 +
Here we emit the value 1 as the key and 1 as the value. The reduce function sums those 1s to get a count of the total number of countries.
 +
<pre class="def"><nowiki>
 +
db.world.mapReduce(
 +
  function () {
 +
    emit(1, 1);
 +
  },
 +
  function (k, v) { return Array.sum(v); },
 +
  {out: {"inline": 1}}
 +
);</nowiki></pre>
 +
</div>
  
−
==Introducing the MapReduce function==
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==Emit a name==
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The MapReduce function is an aggregate function that consists of two functions: Map and Reduce. As the name would suggest, the map is always performed before the reduce.<br/><br/>
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<div class=q data-lang="mongo">
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The map function takes data and breaks it down into tuples (key/value pairs) for each element in the dataset<br/>
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You can use the list given in the reduce function.
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The reduce function then takes the result of the map function and simply reduces it in to a smaller set of tuples by merging all values with the same key.<br/><br/>
 
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Map is used to deal with [https://en.wikipedia.org/wiki/Embarrassingly_parallel "embarassingly parallel problems"] where a task can be broken down into subtasks that can then be ran simultaneously without affecting each other. Instead of just processing elements one by one, all elements can all be dealt with at the same time in parallel. This allows for massively reduced processing times as well as large scalability across multiple servers, making it an attractive solution to handling [https://en.wikipedia.org/wiki/Big_data Big Data].
 
  
−
<div class=q data-lang="py3">
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Here we emit the key '''this.continent''' and the value '''this.name'''.
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<p class=strong></p>
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The reduce function returns the first element of the collected list.
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<pre class=def></pre>
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<pre class="def"><nowiki>
−
<div class=ans></div>
+
db.world.mapReduce(
 +
  function () {
 +
    emit(this.continent, this.name);
 +
  },
 +
  function (k, v) { return v[0]; },
 +
  {out: {"inline": 1}}
 +
);</nowiki></pre>
 
</div>
 
</div>

Latest revision as of 09:47, 26 June 2018

Top Tips

Introducing the MapReduce function

The MapReduce function is an aggregate function that consists of two functions: Map and Reduce.

The map is always performed before the reduce.

The map function examines every document in the collection and emits (key,value) pairs.

The map function takes no input however the current document can be accessed as this

The reduce function has two inputs, for every distinct key emitted by map the reduce function is called with a list of the corresponding values.

Population of each continent

Here the map function emits the continent and the population for each country.

The reduce function uses the JavaScript function Array.sum to add the populations. 

db.world.mapReduce(
  function () {emit(this.continent, this.population);}, 
  function (k, v) { return Array.sum(v); },
  {out: {inline: 1}}
);

Number of countries in each continent

Instead of sending populations you can send a list one 1s to the reduce function.

The reduce function will now create a count of the number of countries in each continent. 

db.world.mapReduce(
  function () {emit(this.continent, 1);}, 
  function (k, v) { return Array.sum(v); },
  {out: {inline: 1}}
);

Count only some countries

The map function does not need to emit once for every entry.

In this example we are only counting the countries that have a large population. 

db.world.mapReduce(
  function () {
    if (this.population > 100000000)
    {
      emit(this.continent, 1);
    }
  },
  function (k, v) { return Array.sum(v); },
  {out: {"inline": 1}}
);

Examine the reduce function

Examine the reduce function.

Here we emit the continent and the name, and in the reduce function we return v.join(',') to see a comma separated list of the values in the list. 

db.world.mapReduce(
  function () {
    if (this.population > 100000000) {
      emit(this.continent, this.name);
    }
  },
  function (k, v) { return v.join(','); },
  {out: {"inline": 1}}
);

Reduce to a single value

If you emit the same key every time you will get exactly one result from your query.

Here we emit the value 1 as the key and 1 as the value. The reduce function sums those 1s to get a count of the total number of countries. 

db.world.mapReduce(
  function () {
    emit(1, 1);
  },
  function (k, v) { return Array.sum(v); },
  {out: {"inline": 1}}
);

Emit a name

You can use the list given in the reduce function.

Here we emit the key this.continent and the value this.name. The reduce function returns the first element of the collected list. 

db.world.mapReduce(
  function () {
    emit(this.continent, this.name);
  },
  function (k, v) { return v[0]; },
  {out: {"inline": 1}}
);
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