SPARK STREAMING in Chinese translation

• spark streaming

Examples of using Spark streaming in English and their translations into Chinese

The system is backed by Apache HBase and Spark Streaming.
本系统由ApacheHBase和SparkStreaming支撑。

It can manipulate data in real time while using Spark Streaming.
它可在实时操作数据的同时，使用SparkStreaming。

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.
SparkStreaming使构建可扩展的容错流应用程序变得容易.

Spark Streaming can be used for processing the real-time streaming data.
SparkStreaming用来处理实时的数据流。

Spark Streaming can be used for processing the real-time streaming data.
使用SparkStreaming处理实时数据流。

We could easily use Spark Streaming for that purpose as follows.
我们可以使用SparkStreaming的方式很容易实现这一目标，如下所示：.

We could easily use Spark Streaming for that purpose as follows.
我们可以非常轻易地利用SparkStreaming来实现该目标：.

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.
SparkStreaming可以轻松构建可扩展的容错流应用程序。

This is often acceptable and many run Spark Streaming applications in this way.
这通常是可以接受的，许多运行的SparkStreaming应用程序都是这种方式。

With this basic knowledge, let us understand the fault-tolerance semantics of Spark Streaming.
与这个基础知识一起，让我们理解SparkStreaming的容错语义。

Adding structure to your streaming pipelines: moving from Spark streaming to structured streaming..
ApacheSpark系列技术直播-从SparkStreaming到StructuredStreaming.

This results in lag in the Spark streaming job since batches are processed sequentially.
这会导致Sparkstreaming作业滞后，因为这些作业是按顺序处理的。

The Cloudera blog has a post on using Spark Streaming for doing near-time session analysis.
Cloudera官方博客发布一篇用SparkStreaming进行近实时会话分析的文章。

Next, we move beyond the simple example and elaborate on the basics of Spark Streaming.
接下来，我们了解完了简单的例子，开始阐述SparkStreaming的基本知识。

This is the approach taken by Apache Spark Streaming, which runs on the Spark batch engine.
这就是在Spark批处理引擎上运行的ApacheSparkStreaming（以下简称SparkStreaming）所使用的方法。

This unification of disparate data processing capabilities is the key reason behind Spark Streaming's rapid adoption.
这种对不同数据的统一处理能力就是SparkStreaming会被大家迅速采用的关键原因之一。

This was a common problem for early Spark Streaming users before Structured Streaming was released.
这是早期SparkStreaming用户经常碰到的问题，直到StructuredStreaming出来才得到缓解。

Then there's a stream processing layer, which might include Storm, Spark Streaming, or Samza.
然后是流处理层，这可能包括Storm、SparkStreaming或者Samza。

Stream processing is also conducted by using Apache Kafka to stream data into Apache Flink or Spark Streaming.
与此同时，他们也使用ApacheKafka将数据导向Flink或SparkStreaming。

Spark Streaming provides a high-level abstraction called discretized stream or DStream, which represents a continuous stream of data.
SparkStreaming提供了一个高层次的抽象叫做离散流（discretizedstream）或者DStream，它代表一个连续的数据流。