Question

我有一个用例，我需要在从Kafka读取消息后执行某些计算并将结果保存到HDFS和第三方应用程序中，从spark spark调用RESTAPI。

我对此几乎没有疑问：

我们如何直接从spark streaming中调用RESTAPI。
如何使用流批处理时间管理RESTAPI超时。

Answer 1

此代码不会按原样编译。但这是给定用例的方法。

val conf = new SparkConf().setAppName("App name").setMaster("yarn")
val ssc = new StreamingContext(conf, Seconds(1))

val dstream = KafkaUtils.createStream(ssc, zkQuorum, group, topicMap)

dstream.foreachRDD { rdd =>

  //Write the rdd to HDFS directly
  rdd.saveAsTextFile("hdfs/location/to/save")

  //loop through each parttion in rdd
  rdd.foreachPartition { partitionOfRecords =>

    //1. Create HttpClient object here
    //2.a POST data to API

    //Use it if you want record level control in rdd or partion
    partitionOfRecords.foreach { record =>
      //2.b Post the the date to API
      record.toString
    }
  }
  //Use 2.a or 2.b to POST data as per your req
}

ssc.start()
ssc.awaitTermination()

大多数HttpClients（用于REST调用）支持请求超时。

使用Apache HttpClient进行带有超时的Http POST调用

val CONNECTION_TIMEOUT_MS = 20000; // Timeout in millis (20 sec).

val requestConfig = RequestConfig.custom()
  .setConnectionRequestTimeout(CONNECTION_TIMEOUT_MS)
  .setConnectTimeout(CONNECTION_TIMEOUT_MS)
  .setSocketTimeout(CONNECTION_TIMEOUT_MS)
  .build();

HttpClientBuilder.create().build();

val client: CloseableHttpClient = HttpClientBuilder.create().build();

val url = "https://selfsolve.apple.com/wcResults.do"
val post = new HttpPost(url);

//Set config to post
post.setConfig(requestConfig)

post.setEntity(EntityBuilder.create.setText("some text to post to API").build())

val response: HttpResponse = client.execute(post)

来自Spark Streaming的RestAPI服务调用

1 个答案: