klion26 commented on a change in pull request #12798:
URL: https://github.com/apache/flink/pull/12798#discussion_r453438542
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -180,99 +158,68 @@ FROM Ticker
) MR;
{% endhighlight %}
-The query partitions the `Ticker` table by the `symbol` column and orders it
by the `rowtime`
-time attribute.
+此查询将 `Ticker` 表按照 `symbol` 列进行分区并按照 `rowtime` 属性进行排序。
-The `PATTERN` clause specifies that we are interested in a pattern with a
starting event `START_ROW`
-that is followed by one or more `PRICE_DOWN` events and concluded with a
`PRICE_UP` event. If such
-a pattern can be found, the next pattern match will be seeked at the last
`PRICE_UP` event as
-indicated by the `AFTER MATCH SKIP TO LAST` clause.
+`PATTERN` 子句指定我们对以下模式感兴趣：该模式具有开始事件 `START_ROW`，然后是一个或多个 `PRICE_DOWN` 事件，并以
`PRICE_UP` 事件结束。如果可以找到这样的模式，如 `AFTER MATCH SKIP TO LAST` 子句所示，则从最后一个 `PRICE_UP`
事件开始寻找下一个模式匹配。
-The `DEFINE` clause specifies the conditions that need to be met for a
`PRICE_DOWN` and `PRICE_UP`
-event. Although the `START_ROW` pattern variable is not present it has an
implicit condition that
-is evaluated always as `TRUE`.
+`DEFINE` 子句指定 `PRICE_DOWN` 和 `PRICE_UP` 事件需要满足的条件。尽管不存在 `START_ROW`
模式变量，但它具有一个始终被评估为 `TRUE` 隐式条件。
-A pattern variable `PRICE_DOWN` is defined as a row with a price that is
smaller than the price of
-the last row that met the `PRICE_DOWN` condition. For the initial case or when
there is no last row
-that met the `PRICE_DOWN` condition, the price of the row should be smaller
than the price of the
-preceding row in the pattern (referenced by `START_ROW`).
+模式变量 `PRICE_DOWN` 定义为价格小于满足 `PRICE_DOWN` 条件的最后一行。对于初始情况或没有满足 `PRICE_DOWN`
条件的最后一行时，该行的价格应小于该模式中前一行（由 `START_ROW` 引用）的价格。
-A pattern variable `PRICE_UP` is defined as a row with a price that is larger
than the price of the
-last row that met the `PRICE_DOWN` condition.
+模变变量 `PRICE_UP` 定义为价格大于满足 `PRICE_DOWN` 条件的最后一行。
Review comment:
`模变变量` -> `模式变量`？
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -998,29 +898,26 @@ The last result matched against the rows #5, #6.
XYZ 17 2018-09-17 10:00:05 2018-09-17 10:00:06
{% endhighlight %}
-Again, the first result matched against the rows #1, #2, #3, #4.
+同样，第一个结果与#1，#2，#3，#4行匹配。
Review comment:
```suggestion
同样，第一个结果与 #1，#2，#3，#4 行匹配。
```
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -976,16 +877,15 @@ The second result matched against the rows #5, #6.
XYZ 17 2018-09-17 10:00:05 2018-09-17 10:00:06
{% endhighlight %}
-Again, the first result matched against the rows #1, #2, #3, #4.
+同样，第一个结果与 #1，#2，#3，#4 行匹配。
-Compared to the previous strategy, the next match includes row #2 again for
the next matching.
-Therefore, the second result matched against the rows #2, #3, #4, #5.
+与上一个策略相比，下一个匹配再次包含 #2 行匹配。因此，第二个结果与 #2，#3，#4，#5 行匹配。
-The third result matched against the rows #3, #4, #5.
+第三个结果与#3、#4、#5行匹配。
-The forth result matched against the rows #4, #5, #6.
+第四个结果与#4，#5，#6行匹配。
Review comment:
```suggestion
第四个结果与 #4，#5，#6 行匹配。
```
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -976,16 +877,15 @@ The second result matched against the rows #5, #6.
XYZ 17 2018-09-17 10:00:05 2018-09-17 10:00:06
{% endhighlight %}
-Again, the first result matched against the rows #1, #2, #3, #4.
+同样，第一个结果与 #1，#2，#3，#4 行匹配。
-Compared to the previous strategy, the next match includes row #2 again for
the next matching.
-Therefore, the second result matched against the rows #2, #3, #4, #5.
+与上一个策略相比，下一个匹配再次包含 #2 行匹配。因此，第二个结果与 #2，#3，#4，#5 行匹配。
-The third result matched against the rows #3, #4, #5.
+第三个结果与#3、#4、#5行匹配。
-The forth result matched against the rows #4, #5, #6.
+第四个结果与#4，#5，#6行匹配。
-The last result matched against the rows #5, #6.
+最后一个结果与第5行、第6行匹配。
Review comment:
```suggestion
最后一个结果与第 5 行、第 6 行匹配。
```
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -180,99 +158,68 @@ FROM Ticker
) MR;
{% endhighlight %}
-The query partitions the `Ticker` table by the `symbol` column and orders it
by the `rowtime`
-time attribute.
+此查询将 `Ticker` 表按照 `symbol` 列进行分区并按照 `rowtime` 属性进行排序。
-The `PATTERN` clause specifies that we are interested in a pattern with a
starting event `START_ROW`
-that is followed by one or more `PRICE_DOWN` events and concluded with a
`PRICE_UP` event. If such
-a pattern can be found, the next pattern match will be seeked at the last
`PRICE_UP` event as
-indicated by the `AFTER MATCH SKIP TO LAST` clause.
+`PATTERN` 子句指定我们对以下模式感兴趣：该模式具有开始事件 `START_ROW`，然后是一个或多个 `PRICE_DOWN` 事件，并以
`PRICE_UP` 事件结束。如果可以找到这样的模式，如 `AFTER MATCH SKIP TO LAST` 子句所示，则从最后一个 `PRICE_UP`
事件开始寻找下一个模式匹配。
-The `DEFINE` clause specifies the conditions that need to be met for a
`PRICE_DOWN` and `PRICE_UP`
-event. Although the `START_ROW` pattern variable is not present it has an
implicit condition that
-is evaluated always as `TRUE`.
+`DEFINE` 子句指定 `PRICE_DOWN` 和 `PRICE_UP` 事件需要满足的条件。尽管不存在 `START_ROW`
模式变量，但它具有一个始终被评估为 `TRUE` 隐式条件。
-A pattern variable `PRICE_DOWN` is defined as a row with a price that is
smaller than the price of
-the last row that met the `PRICE_DOWN` condition. For the initial case or when
there is no last row
-that met the `PRICE_DOWN` condition, the price of the row should be smaller
than the price of the
-preceding row in the pattern (referenced by `START_ROW`).
+模式变量 `PRICE_DOWN` 定义为价格小于满足 `PRICE_DOWN` 条件的最后一行。对于初始情况或没有满足 `PRICE_DOWN`
条件的最后一行时，该行的价格应小于该模式中前一行（由 `START_ROW` 引用）的价格。
-A pattern variable `PRICE_UP` is defined as a row with a price that is larger
than the price of the
-last row that met the `PRICE_DOWN` condition.
+模变变量 `PRICE_UP` 定义为价格大于满足 `PRICE_DOWN` 条件的最后一行。
-This query produces a summary row for each period in which the price of a
stock was continuously
-decreasing.
+此查询为股票价格持续下跌的每个期间生成摘要行。
-The exact representation of the output rows is defined in the `MEASURES` part
of the query. The
-number of output rows is defined by the `ONE ROW PER MATCH` output mode.
+在查询的 `MEASURES` 子句部分定义确切的输出行信息。输出行数由 `ONE ROW PER MATCH` 输出方式定义。
{% highlight text %}
symbol start_tstamp bottom_tstamp end_tstamp
========= ================== ================== ==================
ACME 01-APR-11 10:00:04 01-APR-11 10:00:07 01-APR-11 10:00:08
{% endhighlight %}
-The resulting row describes a period of falling prices that started at
`01-APR-11 10:00:04` and
-achieved the lowest price at `01-APR-11 10:00:07` that increased again at
`01-APR-11 10:00:08`.
+该行结果描述了从 `01-APR-11 10:00:04` 开始的价格下跌期，在 `01-APR-11 10:00:07` 达到最低价格，到
`01-APR-11 10:00:08` 再次上涨。
-Partitioning
+<a name="partitioning"></a>
+
+分区
------------
-It is possible to look for patterns in partitioned data, e.g., trends for a
single ticker or a
-particular user. This can be expressed using the `PARTITION BY` clause. The
clause is similar to
-using `GROUP BY` for aggregations.
+可以在分区数据中寻找模式，例如单个股票行情或特定用户的趋势。这可以用 `PARTITION BY` 子句来表示。该子句类似于对聚合使用 `GROUP BY`。
+
+<span class="label label-danger">注意</span> 强烈建议对传入的数据进行分区，否则 `MATCH_RECOGNIZE`
子句将被转换为非并行算子，以确保全局排序。
-<span class="label label-danger">Attention</span> It is highly advised to
partition the incoming
-data because otherwise the `MATCH_RECOGNIZE` clause will be translated into a
non-parallel operator
-to ensure global ordering.
+<a name="order-of-events"></a>
-Order of Events
+事件顺序
---------------
-Apache Flink allows for searching for patterns based on time; either
-[processing time or event time](time_attributes.html).
+Apache Flink 可以根据时间（[处理时间或者事件时间]({% link
dev/table/streaming/time_attributes.zh.md %})）进行模式搜索。
-In case of event time, the events are sorted before they are passed to the
internal pattern state
-machine. As a consequence, the produced output will be correct regardless of
the order in which
-rows are appended to the table. Instead, the pattern is evaluated in the order
specified by the
-time contained in each row.
+如果是事件时间，则在将事件传递到内部模式状态机之前对其进行排序。所以，无论行添加到表的顺序如何，生成的输出都是正确的。相反，模式是按照每行中包含的时间指定的顺序计算的。
-The `MATCH_RECOGNIZE` clause assumes a [time attribute](time_attributes.html)
with ascending
-ordering as the first argument to `ORDER BY` clause.
+`MATCH_RECOGNIZE` 子句假定升序的 [时间属性]({% link
dev/table/streaming/time_attributes.zh.md %}) 是 `ORDER BY` 子句的第一个参数。
-For the example `Ticker` table, a definition like `ORDER BY rowtime ASC, price
DESC` is valid but
-`ORDER BY price, rowtime` or `ORDER BY rowtime DESC, price ASC` is not.
+对于示例 `Ticker` 表，诸如 `ORDER BY rowtime ASC, price DESC` 的定义是有效的，但 `ORDER BY
price, rowtime` 或者 `ORDER BY rowtime DESC, price ASC` 是无效的。
Define & Measures
-----------------
-The `DEFINE` and `MEASURES` keywords have similar meanings to the `WHERE` and
`SELECT` clauses in a
-simple SQL query.
+`DEFINE` 和 `MEASURES` 关键字与简单 SQL 查询中的 `WHERE` 和 `SELECT` 子句具有相近的含义。
-The `MEASURES` clause defines what will be included in the output of a
matching pattern. It can
-project columns and define expressions for evaluation. The number of produced
rows depends on the
-[output mode](#output-mode) setting.
+`MEASURES` 子句定义匹配模式的输出中要包含哪些内容。它可以投影列并定义表达式进行计算。产生的行数取决于[输出方式](#output-mode)设置。
-The `DEFINE` clause specifies conditions that rows have to fulfill in order to
be classified to a
-corresponding [pattern variable](#defining-a-pattern). If a condition is not
defined for a pattern
-variable, a default condition will be used which evaluates to `true` for every
row.
+`DEFINE` 子句指定行必须满足的条件才能被分类到相应的 [pattern
variable](#defining-a-pattern)。如果没有为模式变量定义条件，则将使用对每一行的计算结果为 `true` 的默认条件。
Review comment:
这句话中前面的 `pattern variable` 没有翻译，后面的翻译了，这里建议进行统一，可以统一进行翻译
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -180,99 +158,68 @@ FROM Ticker
) MR;
{% endhighlight %}
-The query partitions the `Ticker` table by the `symbol` column and orders it
by the `rowtime`
-time attribute.
+此查询将 `Ticker` 表按照 `symbol` 列进行分区并按照 `rowtime` 属性进行排序。
-The `PATTERN` clause specifies that we are interested in a pattern with a
starting event `START_ROW`
-that is followed by one or more `PRICE_DOWN` events and concluded with a
`PRICE_UP` event. If such
-a pattern can be found, the next pattern match will be seeked at the last
`PRICE_UP` event as
-indicated by the `AFTER MATCH SKIP TO LAST` clause.
+`PATTERN` 子句指定我们对以下模式感兴趣：该模式具有开始事件 `START_ROW`，然后是一个或多个 `PRICE_DOWN` 事件，并以
`PRICE_UP` 事件结束。如果可以找到这样的模式，如 `AFTER MATCH SKIP TO LAST` 子句所示，则从最后一个 `PRICE_UP`
事件开始寻找下一个模式匹配。
-The `DEFINE` clause specifies the conditions that need to be met for a
`PRICE_DOWN` and `PRICE_UP`
-event. Although the `START_ROW` pattern variable is not present it has an
implicit condition that
-is evaluated always as `TRUE`.
+`DEFINE` 子句指定 `PRICE_DOWN` 和 `PRICE_UP` 事件需要满足的条件。尽管不存在 `START_ROW`
模式变量，但它具有一个始终被评估为 `TRUE` 隐式条件。
-A pattern variable `PRICE_DOWN` is defined as a row with a price that is
smaller than the price of
-the last row that met the `PRICE_DOWN` condition. For the initial case or when
there is no last row
-that met the `PRICE_DOWN` condition, the price of the row should be smaller
than the price of the
-preceding row in the pattern (referenced by `START_ROW`).
+模式变量 `PRICE_DOWN` 定义为价格小于满足 `PRICE_DOWN` 条件的最后一行。对于初始情况或没有满足 `PRICE_DOWN`
条件的最后一行时，该行的价格应小于该模式中前一行（由 `START_ROW` 引用）的价格。
-A pattern variable `PRICE_UP` is defined as a row with a price that is larger
than the price of the
-last row that met the `PRICE_DOWN` condition.
+模变变量 `PRICE_UP` 定义为价格大于满足 `PRICE_DOWN` 条件的最后一行。
-This query produces a summary row for each period in which the price of a
stock was continuously
-decreasing.
+此查询为股票价格持续下跌的每个期间生成摘要行。
-The exact representation of the output rows is defined in the `MEASURES` part
of the query. The
-number of output rows is defined by the `ONE ROW PER MATCH` output mode.
+在查询的 `MEASURES` 子句部分定义确切的输出行信息。输出行数由 `ONE ROW PER MATCH` 输出方式定义。
{% highlight text %}
symbol start_tstamp bottom_tstamp end_tstamp
========= ================== ================== ==================
ACME 01-APR-11 10:00:04 01-APR-11 10:00:07 01-APR-11 10:00:08
{% endhighlight %}
-The resulting row describes a period of falling prices that started at
`01-APR-11 10:00:04` and
-achieved the lowest price at `01-APR-11 10:00:07` that increased again at
`01-APR-11 10:00:08`.
+该行结果描述了从 `01-APR-11 10:00:04` 开始的价格下跌期，在 `01-APR-11 10:00:07` 达到最低价格，到
`01-APR-11 10:00:08` 再次上涨。
-Partitioning
+<a name="partitioning"></a>
+
+分区
------------
-It is possible to look for patterns in partitioned data, e.g., trends for a
single ticker or a
-particular user. This can be expressed using the `PARTITION BY` clause. The
clause is similar to
-using `GROUP BY` for aggregations.
+可以在分区数据中寻找模式，例如单个股票行情或特定用户的趋势。这可以用 `PARTITION BY` 子句来表示。该子句类似于对聚合使用 `GROUP BY`。
+
+<span class="label label-danger">注意</span> 强烈建议对传入的数据进行分区，否则 `MATCH_RECOGNIZE`
子句将被转换为非并行算子，以确保全局排序。
-<span class="label label-danger">Attention</span> It is highly advised to
partition the incoming
-data because otherwise the `MATCH_RECOGNIZE` clause will be translated into a
non-parallel operator
-to ensure global ordering.
+<a name="order-of-events"></a>
-Order of Events
+事件顺序
---------------
-Apache Flink allows for searching for patterns based on time; either
-[processing time or event time](time_attributes.html).
+Apache Flink 可以根据时间（[处理时间或者事件时间]({% link
dev/table/streaming/time_attributes.zh.md %})）进行模式搜索。
-In case of event time, the events are sorted before they are passed to the
internal pattern state
-machine. As a consequence, the produced output will be correct regardless of
the order in which
-rows are appended to the table. Instead, the pattern is evaluated in the order
specified by the
-time contained in each row.
+如果是事件时间，则在将事件传递到内部模式状态机之前对其进行排序。所以，无论行添加到表的顺序如何，生成的输出都是正确的。相反，模式是按照每行中包含的时间指定的顺序计算的。
-The `MATCH_RECOGNIZE` clause assumes a [time attribute](time_attributes.html)
with ascending
-ordering as the first argument to `ORDER BY` clause.
+`MATCH_RECOGNIZE` 子句假定升序的 [时间属性]({% link
dev/table/streaming/time_attributes.zh.md %}) 是 `ORDER BY` 子句的第一个参数。
-For the example `Ticker` table, a definition like `ORDER BY rowtime ASC, price
DESC` is valid but
-`ORDER BY price, rowtime` or `ORDER BY rowtime DESC, price ASC` is not.
+对于示例 `Ticker` 表，诸如 `ORDER BY rowtime ASC, price DESC` 的定义是有效的，但 `ORDER BY
price, rowtime` 或者 `ORDER BY rowtime DESC, price ASC` 是无效的。
Define & Measures
-----------------
-The `DEFINE` and `MEASURES` keywords have similar meanings to the `WHERE` and
`SELECT` clauses in a
-simple SQL query.
+`DEFINE` 和 `MEASURES` 关键字与简单 SQL 查询中的 `WHERE` 和 `SELECT` 子句具有相近的含义。
-The `MEASURES` clause defines what will be included in the output of a
matching pattern. It can
-project columns and define expressions for evaluation. The number of produced
rows depends on the
-[output mode](#output-mode) setting.
+`MEASURES` 子句定义匹配模式的输出中要包含哪些内容。它可以投影列并定义表达式进行计算。产生的行数取决于[输出方式](#output-mode)设置。
-The `DEFINE` clause specifies conditions that rows have to fulfill in order to
be classified to a
-corresponding [pattern variable](#defining-a-pattern). If a condition is not
defined for a pattern
-variable, a default condition will be used which evaluates to `true` for every
row.
+`DEFINE` 子句指定行必须满足的条件才能被分类到相应的 [pattern
variable](#defining-a-pattern)。如果没有为模式变量定义条件，则将使用对每一行的计算结果为 `true` 的默认条件。
-For a more detailed explanation about expressions that can be used in those
clauses, please have a
-look at the [event stream navigation](#pattern-navigation) section.
+有关在这些子句中可使用的表达式的更详细的说明，请查看 [event stream navigation](#pattern-navigation) 部分。
Review comment:
这里的 `event stream navigation` 和上面也一样
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -180,99 +158,68 @@ FROM Ticker
) MR;
{% endhighlight %}
-The query partitions the `Ticker` table by the `symbol` column and orders it
by the `rowtime`
-time attribute.
+此查询将 `Ticker` 表按照 `symbol` 列进行分区并按照 `rowtime` 属性进行排序。
-The `PATTERN` clause specifies that we are interested in a pattern with a
starting event `START_ROW`
-that is followed by one or more `PRICE_DOWN` events and concluded with a
`PRICE_UP` event. If such
-a pattern can be found, the next pattern match will be seeked at the last
`PRICE_UP` event as
-indicated by the `AFTER MATCH SKIP TO LAST` clause.
+`PATTERN` 子句指定我们对以下模式感兴趣：该模式具有开始事件 `START_ROW`，然后是一个或多个 `PRICE_DOWN` 事件，并以
`PRICE_UP` 事件结束。如果可以找到这样的模式，如 `AFTER MATCH SKIP TO LAST` 子句所示，则从最后一个 `PRICE_UP`
事件开始寻找下一个模式匹配。
-The `DEFINE` clause specifies the conditions that need to be met for a
`PRICE_DOWN` and `PRICE_UP`
-event. Although the `START_ROW` pattern variable is not present it has an
implicit condition that
-is evaluated always as `TRUE`.
+`DEFINE` 子句指定 `PRICE_DOWN` 和 `PRICE_UP` 事件需要满足的条件。尽管不存在 `START_ROW`
模式变量，但它具有一个始终被评估为 `TRUE` 隐式条件。
-A pattern variable `PRICE_DOWN` is defined as a row with a price that is
smaller than the price of
-the last row that met the `PRICE_DOWN` condition. For the initial case or when
there is no last row
-that met the `PRICE_DOWN` condition, the price of the row should be smaller
than the price of the
-preceding row in the pattern (referenced by `START_ROW`).
+模式变量 `PRICE_DOWN` 定义为价格小于满足 `PRICE_DOWN` 条件的最后一行。对于初始情况或没有满足 `PRICE_DOWN`
条件的最后一行时，该行的价格应小于该模式中前一行（由 `START_ROW` 引用）的价格。
-A pattern variable `PRICE_UP` is defined as a row with a price that is larger
than the price of the
-last row that met the `PRICE_DOWN` condition.
+模变变量 `PRICE_UP` 定义为价格大于满足 `PRICE_DOWN` 条件的最后一行。
-This query produces a summary row for each period in which the price of a
stock was continuously
-decreasing.
+此查询为股票价格持续下跌的每个期间生成摘要行。
-The exact representation of the output rows is defined in the `MEASURES` part
of the query. The
-number of output rows is defined by the `ONE ROW PER MATCH` output mode.
+在查询的 `MEASURES` 子句部分定义确切的输出行信息。输出行数由 `ONE ROW PER MATCH` 输出方式定义。
{% highlight text %}
symbol start_tstamp bottom_tstamp end_tstamp
========= ================== ================== ==================
ACME 01-APR-11 10:00:04 01-APR-11 10:00:07 01-APR-11 10:00:08
{% endhighlight %}
-The resulting row describes a period of falling prices that started at
`01-APR-11 10:00:04` and
-achieved the lowest price at `01-APR-11 10:00:07` that increased again at
`01-APR-11 10:00:08`.
+该行结果描述了从 `01-APR-11 10:00:04` 开始的价格下跌期，在 `01-APR-11 10:00:07` 达到最低价格，到
`01-APR-11 10:00:08` 再次上涨。
-Partitioning
+<a name="partitioning"></a>
+
+分区
------------
-It is possible to look for patterns in partitioned data, e.g., trends for a
single ticker or a
-particular user. This can be expressed using the `PARTITION BY` clause. The
clause is similar to
-using `GROUP BY` for aggregations.
+可以在分区数据中寻找模式，例如单个股票行情或特定用户的趋势。这可以用 `PARTITION BY` 子句来表示。该子句类似于对聚合使用 `GROUP BY`。
+
+<span class="label label-danger">注意</span> 强烈建议对传入的数据进行分区，否则 `MATCH_RECOGNIZE`
子句将被转换为非并行算子，以确保全局排序。
-<span class="label label-danger">Attention</span> It is highly advised to
partition the incoming
-data because otherwise the `MATCH_RECOGNIZE` clause will be translated into a
non-parallel operator
-to ensure global ordering.
+<a name="order-of-events"></a>
-Order of Events
+事件顺序
---------------
-Apache Flink allows for searching for patterns based on time; either
-[processing time or event time](time_attributes.html).
+Apache Flink 可以根据时间（[处理时间或者事件时间]({% link
dev/table/streaming/time_attributes.zh.md %})）进行模式搜索。
-In case of event time, the events are sorted before they are passed to the
internal pattern state
-machine. As a consequence, the produced output will be correct regardless of
the order in which
-rows are appended to the table. Instead, the pattern is evaluated in the order
specified by the
-time contained in each row.
+如果是事件时间，则在将事件传递到内部模式状态机之前对其进行排序。所以，无论行添加到表的顺序如何，生成的输出都是正确的。相反，模式是按照每行中包含的时间指定的顺序计算的。
-The `MATCH_RECOGNIZE` clause assumes a [time attribute](time_attributes.html)
with ascending
-ordering as the first argument to `ORDER BY` clause.
+`MATCH_RECOGNIZE` 子句假定升序的 [时间属性]({% link
dev/table/streaming/time_attributes.zh.md %}) 是 `ORDER BY` 子句的第一个参数。
-For the example `Ticker` table, a definition like `ORDER BY rowtime ASC, price
DESC` is valid but
-`ORDER BY price, rowtime` or `ORDER BY rowtime DESC, price ASC` is not.
+对于示例 `Ticker` 表，诸如 `ORDER BY rowtime ASC, price DESC` 的定义是有效的，但 `ORDER BY
price, rowtime` 或者 `ORDER BY rowtime DESC, price ASC` 是无效的。
Define & Measures
-----------------
-The `DEFINE` and `MEASURES` keywords have similar meanings to the `WHERE` and
`SELECT` clauses in a
-simple SQL query.
+`DEFINE` 和 `MEASURES` 关键字与简单 SQL 查询中的 `WHERE` 和 `SELECT` 子句具有相近的含义。
-The `MEASURES` clause defines what will be included in the output of a
matching pattern. It can
-project columns and define expressions for evaluation. The number of produced
rows depends on the
-[output mode](#output-mode) setting.
+`MEASURES` 子句定义匹配模式的输出中要包含哪些内容。它可以投影列并定义表达式进行计算。产生的行数取决于[输出方式](#output-mode)设置。
-The `DEFINE` clause specifies conditions that rows have to fulfill in order to
be classified to a
-corresponding [pattern variable](#defining-a-pattern). If a condition is not
defined for a pattern
-variable, a default condition will be used which evaluates to `true` for every
row.
+`DEFINE` 子句指定行必须满足的条件才能被分类到相应的 [pattern
variable](#defining-a-pattern)。如果没有为模式变量定义条件，则将使用对每一行的计算结果为 `true` 的默认条件。
-For a more detailed explanation about expressions that can be used in those
clauses, please have a
-look at the [event stream navigation](#pattern-navigation) section.
+有关在这些子句中可使用的表达式的更详细的说明，请查看 [event stream navigation](#pattern-navigation) 部分。
### Aggregations
-Aggregations can be used in `DEFINE` and `MEASURES` clauses. Both
-[built-in]({{ site.baseurl }}/dev/table/functions/systemFunctions.html) and
custom
-[user defined]({{ site.baseurl }}/dev/table/functions/udfs.html) functions are
supported.
+Aggregations 可以在 `DEFINE` 和 `MEASURES` 子句中使用。支持[内置函数]({% link
dev/table/functions/systemFunctions.zh.md %})和[用户自定义函数]({% link
dev/table/functions/udfs.zh.md %})。
-Aggregate functions are applied to each subset of rows mapped to a match. In
order to understand
-how those subsets are evaluated have a look at the [event stream
navigation](#pattern-navigation)
-section.
+对相应匹配项的行子集可以使用 Aggregate functions。请查看 [event stream
navigation](#pattern-navigation) 部分以了解如何计算这些子集。
Review comment:
这里的 `event stream navigation` 建议翻译，下面的标题已经翻译了
##########
File path: docs/dev/table/streaming/match_recognize.zh.md
##########
@@ -976,16 +877,15 @@ The second result matched against the rows #5, #6.
XYZ 17 2018-09-17 10:00:05 2018-09-17 10:00:06
{% endhighlight %}
-Again, the first result matched against the rows #1, #2, #3, #4.
+同样，第一个结果与 #1，#2，#3，#4 行匹配。
-Compared to the previous strategy, the next match includes row #2 again for
the next matching.
-Therefore, the second result matched against the rows #2, #3, #4, #5.
+与上一个策略相比，下一个匹配再次包含 #2 行匹配。因此，第二个结果与 #2，#3，#4，#5 行匹配。
-The third result matched against the rows #3, #4, #5.
+第三个结果与#3、#4、#5行匹配。
Review comment:
```suggestion
第三个结果与 #3、#4、#5 行匹配。
```
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