This is my first real attempt at spark/scala so be gentle.
I have a file called test.json on HDFS that I'm trying to read and index
using Spark. I'm able to read the file via SQLContext.jsonFile() but when
I try to use SchemaRDD.saveToEs() I get an invalid JSON fragment received
error. I'm thinking that the saveToES() function isn't actually formatting
the output in json and instead is just sending the value field of the RDD.
What am I doing wrong?
Spark 1.2.0
Elasticsearch-hadoop 2.1.0.BUILD-20150217
test.json:
{"key":"value"}
spark-shell:
import org.apache.spark.SparkContext._
import org.elasticsearch.spark._
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._
val input =
sqlContext.jsonFile("hdfs://nameservice1/user/mshirley/test.json")
input.saveToEs("mshirley_spark_test/test")
error:
<snip>
org.elasticsearch.hadoop.rest.EsHadoopInvalidRequest: Found unrecoverable
error [Bad Request(400) - Invalid JSON fragment
received[["value"]][MapperParsingException[failed to parse]; n
ested: ElasticsearchParseException[Failed to derive xcontent from
(offset=13, length=9): [123, 34, 105, 110, 100, 101, 120, 34, 58, 123, 125,
125, 10, 91, 34, 118, 97, 108, 117, 101, 3
4, 93, 10]]; ]]; Bailing out..
<snip>
input:
res2: org.apache.spark.sql.SchemaRDD =
SchemaRDD[6] at RDD at SchemaRDD.scala:108
== Query Plan ==
== Physical Plan ==
PhysicalRDD [key#0], MappedRDD[5] at map at JsonRDD.scala:47
input.printSchema():
root
|-- key: string (nullable = true)
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