diff --git a/docs/1.7/14.md b/docs/1.7/14.md index 86e3c7420bbdebc047ef5b6e8181870f0be3e9a1..3a5ff75704b6511d3afabe0b10c1a1ce0000093a 100644 --- a/docs/1.7/14.md +++ b/docs/1.7/14.md @@ -2,15 +2,15 @@ # Java Lambda Expressions -Java 8 introduced several new language features designed for faster and clearer coding. With the most important feature, the so-called “Lambda Expressions”, it opened the door to functional programming. Lambda expressions allow for implementing and passing functions in a straightforward way without having to declare additional (anonymous) classes. +Java 8引入了几个新的语言特性，旨在实现更快、更清晰的编码。最重要的特性，即所谓的“Lambda表达式”，为函数式编程打开了大门。Lambda表达式允许以简单的方式实现和传递函数，而不必声明其他(匿名)类。 -Attention Flink supports the usage of lambda expressions for all operators of the Java API, however, whenever a lambda expression uses Java generics you need to declare type information _explicitly_. +注意Flink支持JavaAPI的所有操作符使用lambda表达式，但是，每当lambda表达式使用Java泛型时，都需要声明信息类型 _explicitly_。 -This document shows how to use lambda expressions and describes current limitations. For a general introduction to the Flink API, please refer to the [Programming Guide](//ci.apache.org/projects/flink/flink-docs-release-1.7/dev/api_concepts.html) +本文档演示如何使用lambda表达式，并描述当前的限制。有关FLinkAPI的一般介绍，请参阅[编程Guide](//ci.apache.org/projects/flink/flink-docs-release-1.7/dev/api_concepts.html)] -### Examples and Limitations +### Examples and Limitations （实施例和限制） -The following example illustrates how to implement a simple, inline `map()` function that squares its input using a lambda expression. The types of input `i` and output parameters of the `map()` function need not to be declared as they are inferred by the Java compiler. +下面的示例说明了如何实现一个简单的内联`map()`函数，该函数使用lambda表达式对其输入进行平方。不需要声明`map()`函数的输入 `i` 和输出参数的类型，因为它们是由Java编译器推断的。 @@ -23,11 +23,11 @@ env.fromElements(1, 2, 3) -Flink can automatically extract the result type information from the implementation of the method signature `OUT map(IN value)` because `OUT` is not generic but `Integer`. +Flink可以从方法签名`OUT map(IN value)`的实现中自动提取结果类型信息，因为`OUT` 不是通用的，而是`Integer`。 -Unfortunately, functions such as `flatMap()` with a signature `void flatMap(IN value, Collector<OUT> out)` are compiled into `void flatMap(IN value, Collector out)` by the Java compiler. This makes it impossible for Flink to infer the type information for the output type automatically. +不幸的是，由Java编译器将诸如`flatMap()`和签名`void flatMap(IN value, Collector<OUT> out)` 之类的函数编译为`void flatMap(IN value, Collector out)`。这使得Flink无法自动推断输出类型的类型信息。 -Flink will most likely throw an exception similar to the following: +FLink最可能抛出类似以下内容的异常： @@ -40,7 +40,7 @@ org.apache.flink.api.common.functions.InvalidTypesException: The generic type pa -In this case, the type information needs to be _specified explicitly_, otherwise the output will be treated as type `Object` which leads to unefficient serialization. +在这种情况下，需要_显式地指定_类型信息，否则输出将被视为`Object`类型，这将导致无效的序列化。 @@ -67,7 +67,7 @@ input.flatMap((Integer number, Collector out) -> { -Similar problems occur when using a `map()` function with a generic return type. A method signature `Tuple2<Integer, Integer> map(Integer value)` is erasured to `Tuple2 map(Integer value)` in the example below. +在使用带有泛型返回类型的`map()`函数时，也会出现类似的问题。在下面的示例中，将一个方法签名`Tuple2<Integer, Integer> map(Integer value)` 删除为 `Tuple2 map(Integer value)` 。 @@ -82,7 +82,7 @@ env.fromElements(1, 2, 3) -In general, those problems can be solved in multiple ways: +一般来说，这些问题可以通过多种方式解决：