I'm not familiar with both Spark and Scala. I've read some articles on the Internet. I get documents from Elasticsearch using Spark successfully, but I'm stuck with how to pulling fields from documents.
I've got 33,617 documents:
import ...
val conf = new JobConf()
conf.set("es.resource", "index-name/type-name")
conf.set("es.nodes", "hostname1:9200,hostname2:9200")
conf.set("es.query", "{...}")
val esRDD = sc.newAPIHadoopRDD(conf, classOf[EsInputFormat[Text, MapWritable]], classOf[Text], classOf[MapWritable])
scala> esRDD.count() // That's GOOD!
res11: Long = 33617
scala> esRDD.take(5).foreach(row => println(row._2))
{@version=1, field1=a, ...}
{@version=1, field1=a, ...}
{@version=1, field1=b, ...}
{@version=1, field1=b, ...}
{@version=1, field1=b, ...}
I don't know how to use org.apache.hadoop.io.MapWritable
in Scala.
// Error!!
scala> esRDD.take(5).foreach(row => println(row._2("field1")))
error: org.apache.hadoop.io.MapWritable does not take parameters
esRDD.take(5).foreach(row => println(row._2("field1")))
// Oops. null is printed
scala> esRDD.take(5).foreach(row => println(row._2.get("field1")))
null
null
null
null
null
My final goal is to aggregate by field1
and print their count like this:
scala> esRDD.groupBy(???).mapValues(_.size)
Map(a => 2, b => 3) // How to get this output??
But, I couldn't figure it out.
$ bin/spark-shell --master local --jars jars/elasticsearch-spark_2.11-2.2.0.jar
scala> import org.elasticsearch.spark._
scala> val rdd: RDD[(String, Map[String, Any])] = sc.esRDD("index-name/type-name")
<console>:45: error: not found: type RDD
val rdd: RDD[(String, Map[String, Any])] = sc.esRDD("index-name/type-name")
^
scala> sc.esRDD("index-name/type-name")
java.lang.NoSuchMethodError: scala.Predef$.ArrowAssoc(Ljava/lang/Object;)Ljava/lang/Object;
at org.elasticsearch.spark.rdd.EsSpark$.esRDD(EsSpark.scala:26)
at org.elasticsearch.spark.package$SparkContextFunctions.esRDD(package.scala:20)
Elasticsearch-hadoop has native support for Spark, I would recommend using it - the API is much simpler:
import org.elasticsearch.spark._
val rdd: RDD[(String, Map[String, Any])] = sc.esRDD("index-name/type-name")
It's a simple rdd of tuples, where the key is the document ID and the Map represents your ES document.
You can map it into a different tuple like this:
val mapped = rdd.map{ case(id, doc) => (doc.get("field1").get, 1) }
I'm putting 1 since it seems you don't need the doc
anywhere else. And then perform a groupByKey
and a map:
mapped.groupByKey().map{ case(key,val) => (key, val.size) }
Also if you're using only the Spark connector you don't need the whole es-hadoop dependency, which is rather big, you can just use elasticsearch-spark
For more information you can check the documentation .
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