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DATAMONGO-586 - Added chapter for Aggregation Framework support to the reference documentation. 

Added chapter to mongodb.xml.
Added myself to the authors list in index.xml
pull/58/merge
Thomas Darimont 13 years ago committed by Oliver Gierke
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  1. 4
      src/docbkx/index.xml
  2. 404
      src/docbkx/reference/mongodb.xml

4
src/docbkx/index.xml
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@ -30,6 +30,10 @@ @@ -30,6 +30,10 @@
<firstname>Jon</firstname>
<surname>Brisbin</surname>
</author>
<author>
<firstname>Thomas</firstname>
<surname>Darimont</surname>
</author>
</authorgroup>
<legalnotice>

404
src/docbkx/reference/mongodb.xml
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@ -2140,6 +2140,403 @@ GroupByResults&lt;XObject&gt; results = mongoTemplate.group(where("x").gt(0), @@ -2140,6 +2140,403 @@ GroupByResults&lt;XObject&gt; results = mongoTemplate.group(where("x").gt(0),
</section>
</section>
<section id="mongo.aggregation">
<title>Aggregation Framework Support</title>
<para>Spring Data MongoDB provides support for the Aggregation Framework
introduced to MongoDB in version 2.2.</para>
<para>The MongoDB Documentation describes the <ulink
url="http://docs.mongodb.org/manual/core/aggregation/">Aggregation
Framework</ulink> as follows:<quote>The MongoDB aggregation framework
provides a means to calculate aggregated values without having to use
map-reduce. While map-reduce is powerful, it is often more difficult than
necessary for many simple aggregation tasks, such as totaling or averaging
field values.</quote></para>
<para>For further information see the full <ulink
url="http://docs.mongodb.org/manual/aggregation/">reference
documentation</ulink> of the aggregation framework and other data
aggregation tools for MongoDB.</para>
<section id="mongo.aggregation.basic-concepts">
<title>Basic Concepts</title>
<para>The Aggregation Framework support in Spring Data MongoDB is based
on the following key abstractions <classname>Aggregation</classname>,
<classname>AggregationOperation</classname> and
<classname>AggregationResults</classname>.</para>
<itemizedlist>
<listitem>
<para><classname>Aggregation</classname></para>
<para>An Aggregation represents a MongoDB
<methodname>aggregate</methodname> operation and holds the
description of the aggregation pipline instructions. Aggregations
are created by inoking the appropriate
<code>newAggregation(…)</code> static factory Method of the
<classname>Aggregation</classname> class which takes the list of
<classname>AggregateOperation</classname> as a parameter next to the
optional input class.</para>
<para>The actual aggregate operation is executed by the
<methodname>aggregate</methodname> method of the
<classname>MongoTemplate</classname> which also takes the desired
output class as parameter. </para>
</listitem>
<listitem>
<para><classname>AggregationOperation</classname></para>
<para>An <classname>AggregationOperation</classname> represents a
MongoDB aggregation pipeline operation and describes the processing
that should be performed in this aggregation step. Although one
could manually create an <classname>AggregationOperation</classname>
the recommended way to construct an
<classname>AggregateOperation</classname> is to use the static
factory methods provided by the <classname>Aggregate</classname>
class.</para>
</listitem>
<listitem>
<para><classname>AggregationResults</classname></para>
<para><classname>AggregationResults</classname> is the container for
the result of an aggregate operation. It provides access to the raw
aggreation result in the form of an <classname>DBObject</classname>,
to the mapped objects and information which performed the
aggregation. </para>
</listitem>
</itemizedlist>
<para>The canonical example for using the Spring Data MongoDB support
for the MongoDB Aggregation Framework looks as follows:</para>
<programlisting language="java">import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;
…
Aggregation agg = newAggregation(
pipelineOP1(),
pipelineOP2(),
…
pipelineOPn()
);
AggregationResults&lt;OutputType&gt; results = mongoTemplate.aggregate(agg, "INPUT_COLLECTION_NAME", OutputType.class);
List&lt;OutputType&gt; mappedResult = results.getMappedResults();
…</programlisting>
<para>Note that if you provide an input class as the first parameter to
the <methodname>newAggregation</methodname> method the
<classname>MongoTemplate</classname> will derive the name of the input
collection from this class. Otherwise if you don't not specify an input
class you must provide the name of the input collection explicitly. If
an input-class and an explicity input-collection is provided the latter
takes precedence.</para>
</section>
<section id="mongo.aggregation.supported-aggregation-operations">
<title>Supported Aggregation Operations</title>
<para>The MongoDB Aggregation Framework provides the following types of
Aggregation Operations:</para>
<itemizedlist>
<listitem>
<para>Pipeline Aggregation Operators</para>
</listitem>
<listitem>
<para>Group Aggregation Operators</para>
</listitem>
<listitem>
<para>Boolean Aggregation Operators</para>
</listitem>
<listitem>
<para>Comparison Aggregation Operators</para>
</listitem>
<listitem>
<para>Arithmetic Aggregation Operators</para>
</listitem>
<listitem>
<para>String Aggregation Operators</para>
</listitem>
<listitem>
<para>Date Aggregation Operators</para>
</listitem>
<listitem>
<para>Conditional Aggregation Operators</para>
</listitem>
</itemizedlist>
<para>At the time of this writing we provide support for the following
Aggregation Operations in Spring Data MongoDB.</para>
<table>
<title>Aggregation Operations currently supported by Spring Data
MongoDB</title>
<tgroup cols="2">
<tbody>
<row>
<entry>Pipeline Aggregation Operators</entry>
<entry>project, skip, limit, unwind, group, sort,
geoNear</entry>
</row>
<row>
<entry>Group Aggregation Operators</entry>
<entry>add_to_set, first, last, max, min, avg, push, sum,
(*count)</entry>
</row>
<row>
<entry>Comparison Aggregation Operators</entry>
<entry>eq (*via: is), gt, gte, lt, lte, ne</entry>
</row>
</tbody>
</tgroup>
</table>
<para>Note that the aggregation operations not listed here are currently
not supported by Spring Data MongoDB. </para>
<para>*) The operation is mapped or added by Spring Data MongoDB.</para>
</section>
<section id="mongo.aggregation.introductory-example">
<title>Aggregation Framework Example 1</title>
<para>In this introductory example we want to aggregate a list of tags
to get the occurence count of a particular tag from a MongoDB collection
called <code>"tags"</code> sorted by the occurence count in descending
order. This example demonstrates the usage of grouping, sorting,
projections (selection) and unwinding (result splitting).</para>
<para>In order to do this we first create a new aggregation via the
<methodname>newAggregation</methodname> static factory method to which
we pass a list of aggregation operations. These aggregate operations
form the aggregation pipeline of our <classname>Aggregation</classname>.
</para>
<para>As a first step we select the <code>"tags"</code> field (which is
an array of strings) from the input collection with the
<methodname>project</methodname> operation. </para>
<para>In a second step we use the <methodname>unwind</methodname>
operation to generate a new document for each tag within the
<code>"tags"</code> array. </para>
<para>In the third step we use the <methodname>group</methodname>
operation to define a group for each <code>"tags"</code>-value for which
we aggregate the occurence count via the <methodname>count</methodname>
aggregation operator and collect the result in a new field called
<code>"n"</code>. </para>
<para>As a forth step we select the field <code>"n"</code> and create an
alias for the id-field generated from the previous group operation with
the name <code>"tag"</code>. </para>
<para>Finally as the fifth step we sort the resulting list of tags by
their occurence count in descending order via the
<methodname>sort</methodname> operation.</para>
<para>In order to let MongoDB perform the acutal aggregation operation
we call the <methodname>aggregate</methodname> Method on the
MongoTemplate with the created <classname>Aggregation</classname> as an
argument. </para>
<programlisting language="java">class TagCount {
private String tag;
private int n;
…
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;
…
Aggregation agg = newAggregation(
project("tags"),
unwind("tags"),
group("tags").and("n").count(),
project("n").and("tag").previousOperation(),
sort(DESC, "n")
);
AggregationResults&lt;TagCount&gt; results = mongoTemplate.aggregate(agg, "tags", TagCount.class);
List&lt;TagCount&gt; tagCount = results.getMappedResults();
…</programlisting>
<para>Note that the input collection is explicitly specified as the
<code>"tags"</code> parameter to the <methodname>aggregate</methodname>
Method. If the name of the input collection is not specified explicitly,
it is derived from the input-class passed as first parameter to the
<methodname>newAggreation</methodname> Method. </para>
</section>
<section id="mongo.aggregation.example-2">
<title>Aggregation Framework Example 2</title>
<para>This example is based on the <ulink
url="http://docs.mongodb.org/manual/tutorial/aggregation-examples/#largest-and-smallest-cities-by-state">Largest
and Smallest Cities by State</ulink> example from the MongoDB
Aggregation Framework documentation. We added additional sorting to
produce stable results with different MongoDB versions. Here we want to
return the smallest and largest cities by population for each state,
using the aggregation framework. This example demonstrates the usage of
grouping, sorting and projections (selection).</para>
<para>The class <classname>ZipInfo</classname> maps the structure of the
given input-collection. The class <classname>ZipInfoStats</classname>
defines the structure in the desired output format.</para>
<para>As a first step we use the <methodname>group</methodname>
operation to define a group from the input-collection. The grouping
criteria is the combination of the fields <code>"state"</code> and
<code>"city" </code>which forms the id structure of the group. We
aggregate the value of the <code>"population"</code> field from the
grouped elements with by using the <methodname>sum</methodname> operator
saving the result in the field <code>"pop"</code>.</para>
<para>In a second step we use the <methodname>sort</methodname>
operation to sort the intermediate-result by the fields
<code>"pop"</code>, <code>"state"</code> and <code>"city"</code> in
ascending order, such that the smallest city is at the top and the
biggest city is at the bottom of the result. Note that the sorting on
"state" and <code>"city"</code> is implicitly performed against the
group id fields which Spring Data MongoDB took care of. </para>
<para>In the third step we use a <methodname>group</methodname>
operation again to group the intermediate result by
<code>"state"</code>. Note that <code>"state"</code> again implicitly
references an group-id field. We select the name and the population
count of the biggest and smallest city with calls to the
<code>last(…)</code> and <code>first(...)</code> operator respectively
via the <methodname>project</methodname> operation.</para>
<para>As the forth step we select the <code>"state"</code> field from
the previous <methodname>group</methodname> operation. Note that
<code>"state"</code> again implicitly references an group-id field. As
we do not want an implict generated id to appear, we exclude the id from
the previous operation via
<code>and(previousOperation()).exclude()</code>. As we want to populate
the nested <classname>City</classname> structures in our output-class
accordingly we have to emit appropriate sub-documents with the nested
method. </para>
<para>Finally as the fifth step we sort the resulting list of
<classname>StateStats</classname> by their state name in ascending order
via the <methodname>sort</methodname> operation.</para>
<programlisting language="java">class ZipInfo {
String id;
String city;
String state;
@Field("pop") int population;
@Field("loc") double[] location;
…
}
class City {
String name;
int population;
…
}
class ZipInfoStats {
String id;
String state;
City biggestCity;
City smallestCity;
…
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;
…
TypedAggregation&lt;ZipInfo&gt; aggregation = newAggregation(ZipInfo.class,
group("state", "city").and("pop").sum("population"),
sort(ASC, "pop", "state", "city"),
group("state")
.and("biggestCity").last("city")
.and("biggestPop").last("pop")
.and("smallestCity").first("city")
.and("smallestPop").first("pop"),
project()
.and(previousOperation()).exclude()
.and("state").previousOperation()
.and("biggestCity").nested(bind("name", "biggestCity").and("population", "biggestPop"))
.and("smallestCity").nested(bind("name", "smallestCity").and("population", "smallestPop")),
sort(ASC, "state")
);
AggregationResults&lt;ZipInfoStats&gt; result = mongoTemplate.aggregate(aggregation, ZipInfoStats.class);
ZipInfoStats firstZipInfoStats = result.getMappedResults().get(0);
…
</programlisting>
<para>Note that we derive the name of the input-collection from the
<classname>ZipInfo</classname>-class passed as first parameter to the
<methodname>newAggregation</methodname>-Method.</para>
</section>
<section id="mongo.aggregation.example-3">
<title>Aggregation Framework Example 3</title>
<para>This example is based on the <ulink
url="http://docs.mongodb.org/manual/tutorial/aggregation-examples/#states-with-populations-over-10-million">States
with Populations Over 10 Million </ulink>example from the MongoDB
Aggregation Framework documentation. We added additional sorting to
produce stable results with different MongoDB versions. Here we want to
return all states with a population greater than 10 million, using the
aggregation framework. This example demonstrates the usage of grouping,
sorting and matching (filtering).</para>
<para>In the first step we group the input collection by the
<code>"state"</code> field and calculate the sum of the
<code>"population"</code> field and store the result in the new field
<code>"totalPop"</code>.</para>
<para>As a second step we sort the intermediate result by the
id-reference of the previous group operation in addition to the
<code>"totalPop"</code> field in ascending order.</para>
<para>Finally in the third step we filter the intermediate result by
using a <methodname>match</methodname> operation which accepts a
<classname>Criteria</classname> query as an argument.</para>
<programlisting language="java">class StateStats {
@Id String id;
String state;
@Field("totalPop") int totalPopulation;
…
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;
…
TypedAggregation&lt;ZipInfo&gt; agg = newAggregation(ZipInfo.class,
group("state").and("totalPop").sum("population"),
sort(ASC, previousOperation(), "totalPop"),
match(where("totalPop").gte(10 * 1000 * 1000))
);
AggregationResults&lt;StateStats&gt; result = mongoTemplate.aggregate(agg, StateStats.class);
List&lt;StateStats&gt; stateStatsList = result.getMappedResults();
…</programlisting>
<para>Note that we derive the name of the input-collection from the
<classname>ZipInfo</classname>-class passed as first parameter to the
<methodname>newAggregation</methodname>-Method.</para>
</section>
</section>
<section id="mongo.custom-converters">
<title>Overriding default mapping with custom converters</title>
@ -2574,9 +2971,10 @@ mongoTemplate.dropCollection("MyNewCollection"); </programlisting> @@ -2574,9 +2971,10 @@ mongoTemplate.dropCollection("MyNewCollection"); </programlisting>
<listitem>
<para><literal>&lt;T&gt; T</literal> <emphasis role="bold">execute
</emphasis> <literal>(DbCallback&lt;T&gt; action) </literal>
Executes a DbCallback translating any exceptions as
necessary.</para>
</emphasis> <literal>(DbCallback&lt;T&gt; action) Spring Data
MongoDB provides support for the Aggregation Framework introduced to
MongoDB in version 2.2.</literal> Executes a DbCallback translating
any exceptions as necessary.</para>
</listitem>
<listitem>

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