Re: Spark Streaming ElasticSearch

2020-10-06 Thread 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

2020-10-05 Thread 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

2020-10-05 Thread 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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