Map/Reduce [map-reduce]

Mongoid provides a DSL around MongoDB's map/reduce framework, for performing custom map/reduce jobs or simple aggregations.

Execution

You can tell Mongoid off the class or a criteria to perform a map/reduce by calling map_reduce and providing map and reduce javascript functions.

map = %Q{
  function() {
    emit(this.name, { likes: this.likes });
  }
}

reduce = %Q{
  function(key, values) {
    var result = { likes: 0 };
    values.forEach(function(value) {
      result.likes += value.likes;
    });
    return result;
  }
}

Band.where(:likes.gt => 100).map_reduce(map, reduce).out(inline: 1)

Just like criteria, map/reduce calls are lazily evaluated. So nothing will hit the database until you iterate over the results, or make a call on the wrapper that would need to force a database hit.

Band.map_reduce(map, reduce).out(replace: "mr-results").each do |document|
  p document # { "_id" => "Tool", "value" => { "likes" => 200 }}
end

The only required thing you provide along with a map/reduce is where to output the results. If you do not provide this an error will be raised. Valid options to #out are:

• inline: 1: Don't store the output in a collection.
• replace: "name": Store in a collection with the provided name, and overwrite any documents that exist in it.
• merge: "name": Store in a collection with the provided name, and merge the results with the existing documents.
• reduce: "name": Store in a collection with the provided name, and reduce all existing results in that collection.

Raw Results

Results of Map/Reduce execution can be retrieved via the execute method or its aliases raw and results:

mr = Band.where(:likes.gt => 100).map_reduce(map, reduce).out(inline: 1)

mr.execute
# => {"results"=>[{"_id"=>"Tool", "value"=>{"likes"=>200.0}}],
      "timeMillis"=>14,
      "counts"=>{"input"=>4, "emit"=>4, "reduce"=>1, "output"=>1},
      "ok"=>1.0,
      "$clusterTime"=>{"clusterTime"=>#<BSON::Timestamp:0x00005633c2c2ad20 @seconds=1590105400, @increment=1>, "signature"=>{"hash"=><BSON::Binary:0x12240 type=generic data=0x0000000000000000...>, "keyId"=>0}},
      "operationTime"=>#<BSON::Timestamp:0x00005633c2c2aaf0 @seconds=1590105400, @increment=1>}

Statistics

MongoDB servers 4.2 and lower provide Map/Reduce execution statistics. As of MongoDB 4.4, Map/Reduce is implemented via the aggregation pipeline and statistics described in this section are not available.

The following methods are provided on the MapReduce object:

• counts: Number of documents read, emitted, reduced and output through the pipeline.
• input, emitted, reduced, output: individual count methods. Note that emitted and reduced methods are named differently from hash keys in counts.
• time: The time, in milliseconds, that Map/Reduce pipeline took to execute.

The following code illustrates retrieving the statistics:

mr = Band.where(:likes.gt => 100).map_reduce(map, reduce).out(inline: 1)

mr.counts
# => {"input"=>4, "emit"=>4, "reduce"=>1, "output"=>1}

mr.input
# => 4

mr.emitted
# => 4

mr.reduced
# => 1

mr.output
# => 1

mr.time
# => 14