Does this help ?
final JavaHBaseContext hbaseContext = new JavaHBaseContext(javaSparkContext,
conf);
customerModels.foreachRDD(new Function<JavaRDD<Customer>, Void>() {
private static final long serialVersionUID = 1L;
@Override
public Void call(JavaRDD<Customer> currentRDD) throws Exception {
JavaRDD<Promotions> customerWithPromotion =
hbaseContext.mapPartition(currentRDD, new PromotionLookupFunction());
customerWithPromotion.persist(StorageLevel.MEMORY_AND_DISK_SER());
customerWithPromotion.foreachPartition(<promotions function>);
}
});
> On 21-Oct-2015, at 10:55 AM, Nipun Arora <nipunarora2...@gmail.com> wrote:
>
> Hi All,
>
> Can anyone provide a design pattern for the following code shown in the Spark
> User Manual, in JAVA ? I have the same exact use-case, and for some reason
> the design pattern for Java is missing.
>
> Scala version taken from :
> http://spark.apache.org/docs/latest/streaming-programming-guide.html#design-patterns-for-using-foreachrdd
>
> <http://spark.apache.org/docs/latest/streaming-programming-guide.html#design-patterns-for-using-foreachrdd>
>
> dstream.foreachRDD { rdd =>
> rdd.foreachPartition { partitionOfRecords =>
> val connection = createNewConnection()
> partitionOfRecords.foreach(record => connection.send(record))
> connection.close()
> }
> }
>
> I have googled for it and haven't really found a solution. This seems to be
> an important piece of information, especially for people who need to ship
> their code necessarily in Java because of constraints in the company (like
> me) :)
>
> I'd really appreciate any help
>
> Thanks
> Nipun
