From 5908daf8645ecee3c8157eae87616c08a2c3069f Mon Sep 17 00:00:00 2001
From: node <nodexy@gmail.com>
Date: Fri, 6 Jan 2017 12:18:43 +0800
Subject: [PATCH 1/2] 
 chapter1_part7:/010_Intro/35_Tutorial_Aggregations.asciidoc

---
 010_Intro/35_Tutorial_Aggregations.asciidoc | 29 ++++++++-------------
 1 file changed, 11 insertions(+), 18 deletions(-)

diff --git a/010_Intro/35_Tutorial_Aggregations.asciidoc b/010_Intro/35_Tutorial_Aggregations.asciidoc
index 47429874c..805830b9c 100644
--- a/010_Intro/35_Tutorial_Aggregations.asciidoc
+++ b/010_Intro/35_Tutorial_Aggregations.asciidoc
@@ -1,11 +1,9 @@
-=== Analytics
+[[_analytics]]
+=== 分析
 
-Finally, we come to our last business requirement: allow managers to run
-analytics over the employee directory.((("analytics")))  Elasticsearch has functionality called
-_aggregations_, which ((("aggregations")))allow you to generate sophisticated analytics over your
-data. It is similar to `GROUP BY` in SQL, but much more powerful.
+终于到了最后一个业务需求：支持管理者对雇员目录做分析。((("analytics"))) Elasticsearch 有一个功能叫聚合（aggregations），((("aggregations")))允许我们基于数据生成一些精细的分析结果。聚合与 SQL 中的 `GROUP BY` 类似但更强大。
 
-For example, let's find the most popular interests enjoyed by our employees:
+举个例子，挖掘出雇员中最受欢迎的兴趣爱好：
 
 [source,js]
 --------------------------------------------------
@@ -20,7 +18,7 @@ GET /megacorp/employee/_search
 --------------------------------------------------
 // SENSE: 010_Intro/35_Aggregations.json
 
-Ignore the syntax for now and just look at the results:
+暂时忽略掉语法，直接看看结果：
 
 [source,js]
 --------------------------------------------------
@@ -53,6 +51,7 @@ in sports.  These aggregations are not precalculated; they are generated on
 the fly from the documents that match the current query. If we want to know
 the popular interests of people called Smith, we can just add the
 appropriate query into the mix:
+可以看到，两位员工对音乐感兴趣，一位对林地感兴趣，一位对运动感兴趣。这些聚合并非预先统计，而是从匹配当前查询的文档中即时生成。如果想知道叫 Smith 的雇员中最受欢迎的兴趣爱好，可以直接添加适当的查询来组合查询：
 
 [source,js]
 --------------------------------------------------
@@ -74,7 +73,7 @@ GET /megacorp/employee/_search
 --------------------------------------------------
 // SENSE: 010_Intro/35_Aggregations.json
 
-The `all_interests` aggregation has changed to include only documents matching our query:
+`all_interests` 聚合已经变为只包含匹配查询的文档：
 
 [source,js]
 --------------------------------------------------
@@ -93,8 +92,7 @@ The `all_interests` aggregation has changed to include only documents matching o
   }
 --------------------------------------------------
 
-Aggregations allow hierarchical rollups too.((("aggregations", "hierarchical rollups in")))  For example, let's find the
-average age of employees who share a particular interest:
+聚合还支持分级汇总 ((("aggregations", "hierarchical rollups in"))) 。比如，查询特定兴趣爱好员工的平均年龄：
 
 [source,js]
 --------------------------------------------------
@@ -114,8 +112,7 @@ GET /megacorp/employee/_search
 --------------------------------------------------
 // SENSE: 010_Intro/35_Aggregations.json
 
-The aggregations that we get back are a bit more complicated, but still fairly
-easy to understand:
+得到的聚合结果有点儿复杂，但理解起来还是很简单的：
 
 [source,js]
 --------------------------------------------------
@@ -147,10 +144,6 @@ easy to understand:
   }
 --------------------------------------------------
 
-The output is basically an enriched version of the first aggregation we ran.
-We still have a list of interests and their counts, but now each interest has
-an additional `avg_age`, which shows the average age for all employees having
-that interest.
+输出基本是第一次聚合的加强版。依然有一个兴趣及数量的列表，只不过每个兴趣都有了一个附加的 `avg_age` 属性，代表有这个兴趣爱好的所有员工的平均年龄。
 
-Even if you don't understand the syntax yet, you can easily see how complex aggregations and groupings can be accomplished using this feature.
-The sky is the limit as to what kind of data you can extract!
+即使现在不太理解这些语法也没有关系，依然很容易了解到复杂聚合及分组通过 Elasticsearch 特性实现得很完美。可提取的数据类型毫无限制。

From 03473fca764c3940e50f3b626abfbe20d7aec98c Mon Sep 17 00:00:00 2001
From: node <nodexy@gmail.com>
Date: Fri, 6 Jan 2017 15:02:51 +0800
Subject: [PATCH 2/2] remove redundancy original text

---
 010_Intro/35_Tutorial_Aggregations.asciidoc | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/010_Intro/35_Tutorial_Aggregations.asciidoc b/010_Intro/35_Tutorial_Aggregations.asciidoc
index 805830b9c..63d8b29d1 100644
--- a/010_Intro/35_Tutorial_Aggregations.asciidoc
+++ b/010_Intro/35_Tutorial_Aggregations.asciidoc
@@ -46,11 +46,6 @@ GET /megacorp/employee/_search
 }
 --------------------------------------------------
 
-We can see that two employees are interested in music, one in forestry, and one
-in sports.  These aggregations are not precalculated; they are generated on
-the fly from the documents that match the current query. If we want to know
-the popular interests of people called Smith, we can just add the
-appropriate query into the mix:
 可以看到，两位员工对音乐感兴趣，一位对林地感兴趣，一位对运动感兴趣。这些聚合并非预先统计，而是从匹配当前查询的文档中即时生成。如果想知道叫 Smith 的雇员中最受欢迎的兴趣爱好，可以直接添加适当的查询来组合查询：
 
 [source,js]