scala - Elasticsearch + Spark:使用自定义文档_id编写json

Question

我正在尝试从Spark在Elasticsearch中编写对象集合。我必须满足两个要求:

文档已在JSON中序列化，应按

的原样编写

应该提供Elasticsearch文档_id

到目前为止，这是我尝试过的。
saveJsonToEs()
我试图像这样使用 saveJsonToEs() (序列化文档包含具有所需Elasticsearch ID的 _id字段):

val rdd: RDD[String] = job.map{ r => r.toJson() }

val cfg = Map(
  ("es.resource", "myindex/mytype"),
  ("es.mapping.id", "_id"),
  ("es.mapping.exclude", "_id")
)

EsSpark.saveJsonToEs(rdd, cfg)

但是 elasticsearch-hadoop 库给出了以下异常:

Caused by: org.elasticsearch.hadoop.EsHadoopIllegalArgumentException: When writing data as JSON, the field exclusion feature is ignored. This is most likely not what the user intended. Bailing out...
    at org.elasticsearch.hadoop.util.Assert.isTrue(Assert.java:60)
    at org.elasticsearch.hadoop.rest.InitializationUtils.validateSettings(InitializationUtils.java:253)

如果我删除 es.mapping.exclude但保留 es.mapping.id并发送一个内部带有 _id的JSON(例如 {"_id":"blah",...})

val cfg = Map(
  ("es.resource", "myindex/mytype"),
  ("es.mapping.id", "_id")
)

EsSpark.saveJsonToEs(rdd, cfg)

我收到此错误:

Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 15 in stage 84.0 failed 4 times, most recent failure: Lost task 15.3 in stage 84.0 (TID 628, 172.31.35.69, executor 1): org.apache.spark.util.TaskCompletionListenerException: Found unrecoverable error [172.31.30.184:9200] returned Bad Request(400) - Field [_id] is a metadata field and cannot be added inside a document. Use the index API request parameters.; Bailing out..
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:105)
    at org.apache.spark.scheduler.Task.run(Task.scala:112)
...

当我尝试将此ID作为其他字段发送时(例如 {"superID":"blah",...":

 val cfg = Map(
  ("es.resource", "myindex/mytype"),
  ("es.mapping.id", "superID")
)

EsSpark.saveJsonToEs(rdd, cfg)

它无法提取字段:

17/12/20 15:15:38 WARN TaskSetManager: Lost task 8.0 in stage 84.0 (TID 586, 172.31.33.56, executor 0): org.elasticsearch.hadoop.EsHadoopIllegalArgumentException: [JsonExtractor for field [superId]] cannot extract value from entity [class java.lang.String] | instance [{...,"superID":"7f48c8ee6a8a"}]
    at org.elasticsearch.hadoop.serialization.bulk.AbstractBulkFactory$FieldWriter.write(AbstractBulkFactory.java:106)
    at org.elasticsearch.hadoop.serialization.bulk.TemplatedBulk.writeTemplate(TemplatedBulk.java:80)
    at org.elasticsearch.hadoop.serialization.bulk.TemplatedBulk.write(TemplatedBulk.java:56)
    at org.elasticsearch.hadoop.rest.RestRepository.writeToIndex(RestRepository.java:161)
    at org.elasticsearch.spark.rdd.EsRDDWriter.write(EsRDDWriter.scala:67)
    at org.elasticsearch.spark.rdd.EsSpark$$anonfun$doSaveToEs$1.apply(EsSpark.scala:107)
    at org.elasticsearch.spark.rdd.EsSpark$$anonfun$doSaveToEs$1.apply(EsSpark.scala:107)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)

当我从配置中删除 es.mapping.id和 es.mapping.exclude时，它可以工作，但是文档ID由Elasticsearch生成(违反了要求2):

val rdd: RDD[String] = job.map{ r => r.toJson() }

val cfg = Map(
  ("es.resource", "myindex/mytype"),
)

EsSpark.saveJsonToEs(rdd, cfg)

saveToEsWithMeta()
还有另一个函数提供 _id和其他 metadata进行插入: saveToEsWithMeta() 可以解决需求2，但无法满足需求1。

val rdd: RDD[(String, String)] = job.map{
  r => r._id -> r.toJson()
}

val cfg = Map(
  ("es.resource", "myindex/mytype"),
)

EsSpark.saveToEsWithMeta(rdd, cfg)

实际上，Elasticsearch甚至无法解析 elasticsearch-hadoop发送的内容:

Caused by: org.apache.spark.util.TaskCompletionListenerException: Found unrecoverable error [<es_host>:9200] returned Bad Request(400) - failed to parse; Bailing out..
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:105)
    at org.apache.spark.scheduler.Task.run(Task.scala:112)

问题

是否可以将Spark中的 (documentID, serializedDocument)集合写入Elasticsearch(使用 elasticsearch-hadoop)？

附言我正在使用Elasticsearch 5.6.3和Spark 2.1.1。

Answer 1

最终我发现了问题:这是配置中的错字。

[JsonExtractor for field [superId]] cannot extract value from entity [class java.lang.String] | instance [{...,"superID":"7f48c8ee6a8a"}]

它正在寻找字段 superID，但是只有 superID(请注意情况)。在这个问题上，它也有点误导，因为在代码中，它看起来像 "es.mapping.id", "superID"(这是不正确的)。

实际的解决方案就像 Levi Ramsey建议的那样:

val json = """{"foo":"bar","superID":"deadbeef"}"""

val rdd = spark.makeRDD(Seq(json))
val cfg = Map(
  ("es.mapping.id", "superID"),
  ("es.resource", "myindex/mytype")
)
EsSpark.saveJsonToEs(rdd, cfg = cfg)

区别在于 es.mapping.id不能是 _id(如原始帖子中所述， _id是元数据，而Elasticsearch不接受它)。

自然，这意味着应该将新字段 superID添加到映射中(除非映射是动态的)。如果在索引中存储其他字段是一种负担，则还应该:

exclude来自映射

并禁用其索引

非常感谢 Alex Savitsky指向正确的方向。