Re: Spark Streaming ElasticSearch

[jainshasha]

Hi Siva

In that case u can use structured streaming foreach / foreachBatch function
which can help you process each record and write it into some sink 




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Re: Spark Streaming ElasticSearch

[Siva Samraj]

Hi Jainshasha,

I need to read each row from Dataframe and made some changes to it before
inserting it into ES.

Thanks
Siva

On Mon, Oct 5, 2020 at 8:06 PM jainshasha  wrote:

> Hi Siva
>
> To emit data into ES using spark structured streaming job you need to used
> ElasticSearch jar which has support for sink for spark structured streaming
> job. For this you can use this one my branch where we have integrated ES
> with spark 3.0 and scala 2.12 compatible
> https://github.com/ThalesGroup/spark/tree/guavus/v3.0.0
>
> Also in this you need to build three jars
> elasticsearch-hadoop-sql
> elasticsearch-hadoop-core
> elasticsearch-hadoop-mr
> which help in writing data into ES through spark structured streaming.
>
> And in your application job u can use this way to sink the data, remember
> with ES there is only support of append mode of structured streaming.
> val esDf = aggregatedDF
> .writeStream
> .outputMode("append")
> .format("org.elasticsearch.spark.sql")
> .option(CHECKPOINTLOCATION, kafkaCheckpointDirPath + "/es")
> .start("aggregation-job-index-latest-1")
>
>
> Let me know if you face any issues, will be happy to help you :)
>
>
>
>
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>

Re: Spark Streaming ElasticSearch

[jainshasha]

Hi Siva

To emit data into ES using spark structured streaming job you need to used
ElasticSearch jar which has support for sink for spark structured streaming
job. For this you can use this one my branch where we have integrated ES
with spark 3.0 and scala 2.12 compatible
https://github.com/ThalesGroup/spark/tree/guavus/v3.0.0

Also in this you need to build three jars 
elasticsearch-hadoop-sql
elasticsearch-hadoop-core
elasticsearch-hadoop-mr
which help in writing data into ES through spark structured streaming.

And in your application job u can use this way to sink the data, remember
with ES there is only support of append mode of structured streaming.
val esDf = aggregatedDF
.writeStream
.outputMode("append")
.format("org.elasticsearch.spark.sql")
.option(CHECKPOINTLOCATION, kafkaCheckpointDirPath + "/es")
.start("aggregation-job-index-latest-1")


Let me know if you face any issues, will be happy to help you :)




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Spark Streaming ElasticSearch

[Siva Samraj]

Hi Team,

I have a spark streaming job, which will read from kafka and write into
elastic via Http request.

I want to validate each request from Kafka and change the payload as per
business need and write into Elastic Search.

I have used ES Http Request to push the data into Elastic Search. Can some
guide me how to write the data into ES via a data frame?

*Code Snippet: *
 val dfInput = spark
  .readStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "localhost:9092")
  .option("subscribe", "test")
  .option("startingOffsets", "latest")
  .option("group.id", sourceTopicGroupId)
  .option("failOnDataLoss", "false")
  .option("maxOffsetsPerTrigger", maxOffsetsPerTrigger)
  .load()

import spark.implicits._

val resultDf = dfInput
  .withColumn("value", $"value".cast("string"))
  .select("value")

resultDf.writeStream.foreach(new ForeachWriter[Row] {
  override def open(partitionId: Long, version: Long): Boolean = true

  override def process(value: Row): Unit = {
processEventsData(value.get(0).asInstanceOf[String], deviceIndex,
msgIndex, retryOnConflict,auth,refreshInterval,deviceUrl,messageUrl,spark)
  }

  override def close(errorOrNull: Throwable): Unit = {
  }

}).trigger(Trigger.ProcessingTime(triggerPeriod)).start().awaitTermination()
//"1 second"
  }

Please suggest, is there any approach.

Thanks