Merge pull request #44 from richardwei2008/p2_chapter13/10_Multi_word_queries

chapter13_part3: /100_Full_Text_Search/10_Multi_word_queries.asciidoc

Author: medcl

100_Full_Text_Search/10_Multi_word_queries.asciidoc

@@ -1,9 +1,7 @@
 [[match-multi-word]]
-=== Multiword Queries
+=== 多词查询
 
-If we could search for only one word at a time, full-text search would be
-pretty inflexible. Fortunately, the `match` query((("full text search", "multi-word queries")))((("match query", "multi-word query"))) makes multiword queries
-just as simple:
+如果我们一次只能搜索一个词，那么全文搜索就会不太灵活，幸运的是 `match` 查询让多词查询变得简单：((("full text search", "multi-word queries")))((("match query", "multi-word query")))
 
 [source,js]
 --------------------------------------------------
@@ -18,7 +16,7 @@ GET /my_index/my_type/_search
 --------------------------------------------------
 // SENSE: 100_Full_Text_Search/05_Match_query.json
 
-The preceding query returns all four documents in the results list:
+上面这个查询返回所有四个文档：
 
 [source,js]
 --------------------------------------------------
@@ -56,33 +54,22 @@ The preceding query returns all four documents in the results list:
 }
 --------------------------------------------------
 
-<1> Document 4 is the most relevant because it contains `"brown"` twice and `"dog"`
-    once.
+<1> 文档 4 最相关，因为它包含词 `"brown"` 两次以及 `"dog"` 一次。
 
-<2> Documents 2 and 3 both contain `brown` and `dog` once each, and the `title`
-    field is the same length in both docs, so they have the same score.
+<2> 文档 2、3 同时包含 `brown` 和 `dog` 各一次，而且它们 `title` 字段的长度相同，所以具有相同的评分。
 
-<3> Document 1 matches even though it contains only `brown`, not `dog`.
+<3> 文档 1 也能匹配，尽管它只有 `brown` 没有 `dog` 。
 
-Because the `match` query has to look for two terms&#x2014;`["brown","dog"]`&#x2014;internally it has to execute two `term` queries and combine their individual
-results into the overall result. To do this, it wraps the two `term` queries
-in a `bool` query, which we examine in detail in <<bool-query>>.
+因为 `match` 查询必须查找两个词（ `["brown","dog"]` ），它在内部实际上先执行两次 `term` 查询，然后将两次查询的结果合并作为最终结果输出。为了做到这点，它将两个 `term` 查询包入一个 `bool` 查询中，详细信息见 <<bool-query, 布尔查询>>。
 
-The important thing to take away from this is that any document whose
-`title` field contains _at least one of the specified terms_ will match the
-query.  The more terms that match, the more relevant the document.
+以上示例告诉我们一个重要信息：即任何文档只要 `title` 字段里包含 _指定词项中的至少一个词_ 就能匹配，被匹配的词项越多，文档就越相关。
 
 [[match-improving-precision]]
-==== Improving Precision
+==== 提高精度
 
-Matching any document that contains _any_ of the query terms may result in  a
-long tail of seemingly irrelevant results. ((("full text search", "multi-word queries", "improving precision")))((("precision", "improving for full text search multi-word queries"))) It's a shotgun approach to search.
-Perhaps we want to show only documents that contain _all_ of the query terms.
-In other words, instead of `brown OR dog`, we want to return only documents
-that match `brown AND dog`.
+用 _任意_ 查询词项匹配文档可能会导致结果中出现不相关的长尾。((("full text search", "multi-word queries", "improving precision")))((("precision", "improving for full text search multi-word queries")))这是种散弹式搜索。可能我们只想搜索包含 _所有_ 词项的文档，也就是说，不去匹配 `brown OR dog` ，而通过匹配 `brown AND dog` 找到所有文档。
 
-The `match` query accepts an `operator` parameter((("match query", "operator parameter")))((("or operator", "in match queries")))((("and operator", "in match queries"))) that defaults to `or`.
-You can change it to `and` to require that all specified terms must match:
+`match` 查询还可以接受 `operator` 操作符作为输入参数，默认情况下该操作符是 `or` 。我们可以将它修改成 `and` 让所有指定词项都必须匹配：
 
 [source,js]
 --------------------------------------------------
@@ -100,27 +87,18 @@ GET /my_index/my_type/_search
 --------------------------------------------------
 // SENSE: 100_Full_Text_Search/05_Match_query.json
 
-<1> The structure of the `match` query has to change slightly in order to
-    accommodate the `operator` parameter.
+<1>  `match` 查询的结构需要做稍许调整才能使用 `operator` 操作符参数。
 
-This query would exclude document 1, which contains only one of the two terms.
+这个查询可以把文档 1 排除在外，因为它只包含两个词项中的一个。
 
 [[match-precision]]
-==== Controlling Precision
+==== 控制精度
 
-The choice between _all_ and _any_ is a bit((("full text search", "multi-word queries", "controlling precision"))) too black-or-white. What if the
-user specified five query terms, and a document contains only four of them?
-Setting `operator` to `and` would exclude this document.
+在 _所有_ 与 _任意_ 间二选一有点过于非黑即白。((("full text search", "multi-word queries", "controlling precision")))如果用户给定 5 个查询词项，想查找只包含其中 4 个的文档，该如何处理？将 `operator` 操作符参数设置成 `and` 只会将此文档排除。
 
-Sometimes that is exactly what you want, but for most full-text search use
-cases, you want to include documents that may be relevant but exclude those
-that are unlikely to be relevant.  In other words, we need something
-in-between.
+有时候这正是我们期望的，但在全文搜索的大多数应用场景下，我们既想包含那些可能相关的文档，同时又排除那些不太相关的。换句话说，我们想要处于中间某种结果。
 
-The `match` query supports((("match query", "minimum_should_match parameter")))((("minimum_should_match parameter"))) the `minimum_should_match` parameter, which allows
-you to specify the number of terms that must match for a document to be considered
-relevant.  While you can specify an absolute number of terms, it usually makes
-sense to specify a percentage instead, as you have no control over the number of words the user may enter:
+`match` 查询支持 `minimum_should_match` 最小匹配参数，((("match query", "minimum_should_match parameter")))((("minimum_should_match parameter")))这让我们可以指定必须匹配的词项数用来表示一个文档是否相关。我们可以将其设置为某个具体数字，更常用的做法是将其设置为一个百分数，因为我们无法控制用户搜索时输入的单词数量：
 
 [source,js]
 --------------------------------------------------
@@ -138,18 +116,12 @@ GET /my_index/my_type/_search
 --------------------------------------------------
 // SENSE: 100_Full_Text_Search/05_Match_query.json
 
-When specified as a percentage, `minimum_should_match` does the right thing:
-in the preceding example with three terms, `75%` would be rounded down to `66.6%`,
-or two out of the three terms. No matter what you set it to, at least one term
-must match for a document to be considered a match.
+当给定百分比的时候， `minimum_should_match` 会做合适的事情：在之前三词项的示例中， `75%` 会自动被截断成 `66.6%` ，即三个里面两个词。无论这个值设置成什么，至少包含一个词项的文档才会被认为是匹配的。
 
 [NOTE]
 ====
-The `minimum_should_match` parameter is flexible, and different rules can
-be applied depending on the number of terms the user enters.  For the full
-documentation see the
+参数 `minimum_should_match` 的设置非常灵活，可以根据用户输入词项的数目应用不同的规则。完整的信息参考文档
 {ref}/query-dsl-minimum-should-match.html#query-dsl-minimum-should-match
 ====
 
-To fully understand how the `match` query handles multiword queries, we need
-to look at how to combine multiple queries with the `bool` query.
+为了完全理解 `match` 是如何处理多词查询的，我们就需要查看如何使用 `bool` 查询将多个查询条件组合在一起。